Patent Grant
10335036
The present invention relates to methods and systems for non-invasive measurements in the human body, and in particular, methods and systems related to detecting physiologically dependent optical parameters in the human body.
Measuring neural activity in the brain is useful for medical diagnostics, neuromodulation therapies, neuroengineering, or brain-computer interfacing. For example, it may be desirable to measure neural activity in the brain of a patient to determine if a particular region of the brain has been impacted by reduced blood irrigation, a hemorrhage, any other type of damage. For instance, in cases where the patient has suffered a traumatic brain injury, such as stroke, it may be desirable to determine whether the patient should undergo a therapeutic procedure. Measuring neural activity in the brain also may be used to determine the efficacy of such a therapeutic procedure.
Conventional methods for measuring neural activity in the brain include diffuse optical tomography (DOT), and functional near-infrared spectroscopy (fNIRS), as well as others. These applications only employ a moderate amount of near-infrared or visible light radiation, thus being comparatively safe and gentle for a biological subject in comparison to X-Ray Computed Tomography (CT) scans, positron emission tomography (PET), or other methods that use higher-energy and potentially harmful radiation. Moreover, in contrast to methods, such as functional magnetic resonance imaging (fMRI), these optically-based imaging methods do not require large magnets or magnetic shielding, and thus, can be scaled to wearable or portable form factors, which is especially important in applications such as brain-computer interfacing.
Because DOT and fNIRS rely on light, which scatters many times inside brain, skull, dura, pia, and skin tissues, the light paths occurring in these techniques comprise random or “diffusive” walks, and therefore, only limited spatial resolution can be obtained by a conventional optical detector, often on the order of centimeters. The reason for this limited spatial resolution is that the paths of photons striking the detector in such schemes are highly variable and difficult, and even impossible to predict without detailed microscopic knowledge of the scattering characteristics of the brain volume of interest, which is typically unavailable in practice (i.e., in the setting of non-invasive measurements through skull for brain imaging and brain interfacing). In summary, light scattering prevents optical imaging from achieving high resolution deep inside tissue.
There is an increasing interest in ultrasound modulated optical tomography (UOT) to detect more precisely localized changes in biological tissues, e.g., on a sub-millimeter length scale, inside thick biological tissue, such as the brain (see U.S. Pat. No. 8,423,116; Sakadzic S, Wang L V, “High-Resolution Ultrasound-Modulated Optical Tomography in Biological Tissues,” Optics Letters, Vol. 29, No. 23, pp. 2770-2772, Dec. 1, 2004). These localized changes may include changes in light absorption in the brain that reflect neural activity and neurovascular coupling, such as a blood-oxygen-level dependent signal, for application in diagnostics, therapeutics, or, notably, brain computer interfacing (see Steinbrink J, Villringer A, Kempf F, Haux D. Boden S, Obrig H., “Illuminating the BOLD Signal: Combined fMRI-fNIRS Studies,” Magnetic Resonance Imaging, Vol. 24, No. 4, pp. 495-505, May 31, 2006). Thus, there is an increasing interest in ultrasound modulated optical tomography (UOT) in biomedical applications due to its potential to simultaneously achieve good resolution and imaging depth.
In UOT, a highly localized ultrasound focus, e.g., millimeter or sub-millimeter in size, is used to selectively perturb (i.e., “tag”) light (e.g., light generated by a near-infrared coherent laser) passing through a voxel size of tissue defined by the size of the ultrasound focus. Due to the acousto-optic effect, light passing through the ultrasonic beam undergoes a frequency shift defined by multiples of the ultrasonic frequency. By detecting the frequency-shifted light, i.e., the tagged light, spatial information characterizing the biological tissue within the voxel can be acquired. As a result, spatial resolution is boosted from the centimeter-scale diffusive spread of light in the biological tissue to approximately a millimeter-scale voxel size. This ultrasound tagging of light relies on mechanisms known in the field (see Mahan G D, Engler W E, Tiemann J J, Uzgiris E, “Ultrasonic Tagging of Light: Theory,” Proceedings of the National Academy of Sciences, Vol. 95, No. 24, pp. 14015-14019, Nov. 24, 1998).
Typical UOT implementations generate weak signals that make it difficult to differentiate ultrasound-tagged light passing through the focal voxel from a much larger amount of unmodulated light which is measured as DC shot noise. Thus, conventional UOT has the challenge of obtaining optical information through several centimeters of biological tissue, for example, noninvasive measurements through the human skull used to measure functional changes in the brain.
Various methods have been developed to detect the very small fraction of tagged light out of a large background of untagged light by detecting the speckle pattern of light resulting from the interference of many multiply-scattered optical waves with different phases and amplitudes, which combine in a resultant wave whose amplitude, and therefore intensity, as well as phase, varies randomly. In the context of neuroengineering and brain computer interfacing, a key challenge is to render these methods to be sufficiently sensitive to be useful for through-human-skull functional neuroimaging.
One technique uses a narrow spectral filter to separate out the untagged light striking a single-pixel detector, and is immune to speckle decorrelation (greater than ˜0.1 ms-1 ms) due to the scatters' motion (for example, blood flow) inside living biological tissue, but requires bulky and expensive equipment.
Another technique uses crystal-based holography to combine a reference light beam and the sample light beam into a constructive interference pattern, but can be adversely affected by rapid speckle decorrelation, since the response time of the crystal is usually much longer than the speckle correlation time.
Still another technique, referred to as heterodyne parallel speckle detection (PSD), employs optical interference together with a spatially resolved detector array (e.g., a conventional charge-coupled device (CCD) camera) used as an array of independent detectors for collecting the signal over a large number of coherence areas (see Atlan M, Forget B C, Ramaz F, Boccara A C, Gross M, “Pulsed Acousto-Optic Imaging in Dynamic Scattering Media With Heterodyne Parallel Speckle Detection,” Optics Letter, Vol. 30, No. 11, pp. 1360-1362, Jun. 1, 2005). Such configuration improves the signal-to-noise ratio relative to a single-detector and relative to approaches based on other modes of separating tagged and untagged light, such as spectral filters. However, the conventional CCD cameras used for heterodyne PSD have low frame rates, and therefore suffer from a relatively low speed relative to the speckle decorrelation time, thereby making this set up insufficient for in vivo deep tissue applications. Furthermore, conventional CCD cameras record both the AC signal and the DC background for each pixel. Thus, only a few bits of a pixel value can be used to represent the useful AC signal, while most of the bits are wasted in representing the DC background, resulting in a low efficiency in the use of bits.
Lock-in cameras, as compared to conventional CCD cameras, have been used for comparatively bit-efficient and noise resistant heterodyne PSD (see Liu Y, Shen Y, Ma C, Shi J, Wang L V, “Lock-in Camera Based Heterodyne Holography for Ultrasound-Modulated Optical Tomography Inside Dynamic Scattering Media,” Applied Physics Letters, Vol. 108, No. 23, 231106, Jun. 6, 2016; see also Liu Y, Ma C, Shen Y, Wang L V, “Bit-Efficient, Sub-Millisecond Wavefront Measurement Using a Lock-In Camera for Time-Reversal Based Optical Focusing Inside Scattering Media,” Optics Letters, Vol. 41, No. 7, pp. 1321-1324, Apr. 1, 2016). For each pixel, a lock-in camera is capable of performing lock-in detection and outputting only information of the AC signal as a single AC amplitude map that is transferred to a computer, and thus, provides an efficient means of detecting and processing the speckle pattern.
Besides the challenges posed by the signal-to-noise ratio, speckle decorrelation time, and efficient pixel bit processing, another challenge involves obtaining sufficient axial resolution (i.e., the depth resolution or ultrasound propagation direction). To address this challenge, UOT has been applied in a pulsed wave (PW) mode for heterodyne PSD, rather than a continuous (CW) mode (see Li Y Zhang H, Kim C, Wagner K H, Hemmer P., Wang L V, “Pulsed Ultrasound-Modulated Optical Tomography Using Spectral-Hole Burning as a Narrowband Spectral Filter,” Applied Physics Letters, Vol. 93, No. 1, 011111, Jul. 7, 2008; Ruan H, Mather M L, Morgan S P, “Pulsed Ultrasound Modulated Optical Tomography with Harmonic Lock-In Holography Detection,” JOSA A, Vol. 30, No. 7, pp. 1409-1416, Jul. 1, 2013).
PW UOT has the benefit of enabling improved axial resolution compared to CW UOT. That is, with CW UOT, any light passing through the tissue, even though outside of the focal voxel, may be inadvertently tagged by the continuously propagating ultrasound energy along the ultrasound axis, thereby decreasing the signal-to-noise ratio. With PW UOT, the light passing through the tissue is pulsed only when the ultrasound pulses travels through the focal voxel, such that light outside of the focal voxel will not be tagged by the ultrasound energy. Although PW UOT improves axial resolution, the pulsed UOT signals are weak relative to continuous UOT signals.
Although the UOT schemes described above may be sufficient for certain applications, such UOT schemes are inappropriate for the application of 3D-resolved, highly sensitive detection of small signals (e.g., blood-oxygen-level dependent signals) non-invasively through thick scattering layers, such as the human skull.
In accordance with a first aspect of the present inventions, an ultrasound modulated optical tomography (UOT) system comprises an acoustic assembly configured for delivering ultrasound into a target voxel (e.g., one comprising brain matter) within an anatomical structure. The target voxel may be relatively small, e.g., less than one mm3.
The UOT system further comprises an interferometer configured for delivering sample light into the anatomical structure, whereby a portion of the sample light passing through the target voxel is scattered by the anatomical structure as signal light, and another portion of the sample light not passing through the target voxel is scattered by the anatomical structure as background light that combines with the signal light to create a sample light pattern. The interferometer is further configured for combining reference light with the sample light pattern to generate an interference light pattern. The reference light may be combined with the signal light in a homodyne manner. For example, the interferometer may be further configured for frequency shifting the sample light by the frequency of the ultrasound, such that the reference light is combined with the signal light in the homodyne manner. In one embodiment, the interferometer comprises a light source configured for generating source light, a beam splitter configured for splitting the source light into the sample light and the reference light, and a light combiner configured for combining the reference light with the signal light and the background light to generate the interference light pattern.
The UOT system further comprises a controller configured for operating the acoustic assembly and the interferometer to pulse the ultrasound and the sample light in synchrony, such that only the signal light is frequency shifted by the ultrasound. In one embodiment, the pulses of the sample light are identical. In this case, the interferometer may comprise at least one 1×N fiber splitter and at least one N×1 fiber coupler configured for generating the identical pulses of the sample light from a single optical pulse.
The controller is further configured for operating the interferometer to sequentially modulate the interference light pattern to generate a plurality of different interference light patterns. In one embodiment, the interferometer is configured for sequentially modulating the interference light pattern by phase modulating the interference light pattern, e.g., by setting different phase differences (e.g., 0, π/2, π, and 3π/2) between sequential pulses of the sample light and the reference light. In this case, the interferometer may comprise an optical phase shifter configured for setting a phase difference between the sample light and the reference light to phase modulate the interference light pattern.
In another embodiment, the controller is configured for operating the acoustic assembly and the interferometer to pulse the ultrasound and the sample light in synchrony, such that only a single pulse of the sample light is delivered into the anatomical structure for each pulse of the ultrasound delivered into the target voxel. In still another embodiment, the controller is configured for operating the acoustic assembly and the interferometer to pulse the ultrasound and the sample light in synchrony, such that multiple pulses of the sample light are delivered into the anatomical structure for each pulse of the ultrasound delivered into the target voxel.
The UOT system further comprises an array of detectors configured for simultaneously detecting spatial components of each different interference light pattern. Each detector respectively stores a plurality of values in a plurality of bins representative of the respective spatial components of the interference light patterns. Each of the interference light patterns may comprise a speckle light pattern, in which case, the spatial components may comprise speckle grains of the speckle light pattern. The array of detectors may be configured for simultaneously detecting spatial components of each different interference light pattern, and storing the plurality of values for all of the interference patterns in the plurality of bins within 10 milliseconds, and preferably within 1 microsecond to 1 millisecond. The UOT system may further comprise a lock-in camera that includes the array of detectors and corresponding bins.
The UOT system further comprises a processor configured for determining a physiologically-dependent optical parameter (e.g., the level of deoxygenated and/or oxygenated hemoglobin concentration or relative abundance or the level of water concentration or relative water concentration of brain matter) based on the plurality of values stored in the bins of each detector. In one embodiment, the processor is configured for determining neural activity within the target voxel based on the determined physiologically-dependent optical parameter. In another embodiment, the processor is configured for reconstructing the amplitude of the signal light using the plurality of values stored in each of the bins, and determining the physiologically-dependent optical parameter of the target voxel based on the reconstructed amplitude of the signal light. Each value may be respectively stored in each of the bins as an intensity of the spatial component of the respective interference light pattern, in which case, the processor may be configured for using the plurality of values stored in each of the bins to extract a product of the amplitude of the signal light and a known amplitude of the reference light, and determining the amplitude of the signal light from the extracted product.
In accordance with a second aspect of the present inventions, a method of performing pulsed UOT comprises delivering ultrasound into a target voxel (e.g., one comprising brain matter) within an anatomical structure. The target voxel may be relatively small, e.g., less than one mm3.
The method further comprises delivering sample light into the anatomical structure, whereby a portion of the sample light passing through the target voxel is scattered by the anatomical structure as signal light, and another portion of the sample light not passing through the target voxel is scattered by the anatomical structure as background light that combines with the signal light to create a sample light pattern.
The method further comprises pulsing the ultrasound and the sample light in synchrony, such that only the signal light is frequency shifted by the ultrasound. In one method, the pulses of the sample light are identical. For example, the identical pulses of the sample light may be generated from a single optical pulse.
The method further comprises combining reference light with the sample light pattern to generate an interference light pattern. The method may further comprise generating source light, and splitting the source light into the sample light and the reference light. The reference light may be combined with the signal light in a homodyne manner. For example, the method may further comprise frequency shifting the sample light by the frequency of the ultrasound, such that the reference light is combined with the signal light in the homodyne manner. In one method, the ultrasound and the sample light are pulsed in synchrony, such that only a single pulse of the sample light is delivered into the anatomical structure for each pulse of the ultrasound delivered into the anatomical structure. In another method, the ultrasound and the sample light are pulsed in synchrony, such that multiple pulses of the sample light are delivered into the anatomical structure for each pulse of the ultrasound delivered into the anatomical structure.
The method further comprises sequentially modulating the interference light pattern to generate a plurality of different interference light patterns. In one method, the interference light pattern may be sequentially modulated by phase modulating the interference light pattern. For example, the interference light pattern may be phase modulated by setting different phase differences (e.g., 0, π/2, π, and 3π/2) between sequential pulses of the sample light and the reference light.
The method further comprises simultaneously detecting spatial components of each different interference light pattern. The method further comprises storing a plurality of values for each detected spatial component in a plurality of bins. The plurality of values is representative of the spatial component for the respective interference light patterns. Each of the interference light patterns may comprise a speckle light pattern, in which case, the spatial components may comprise speckle grains of the speckle light pattern. The spatial components of each different interference light pattern may be simultaneously detected, and the plurality of values for all of the interference patterns may be stored in the plurality of bins within 10 milliseconds, and preferably within 1 microsecond to 1 millisecond.
The method further comprises determining a physiologically-dependent optical parameter (e.g., the level of deoxygenated and/or oxygenated hemoglobin concentration or relative abundance or the level of water concentration or relative water concentration of brain matter of brain matter) of the target voxel based on the plurality of values stored in the bins. One method further comprises determining neural activity within the target voxel based on the determined physiologically-dependent optical parameter. Another method further comprises reconstructing the amplitude of the signal light using the plurality of values stored in each of the bins, in which case, the physiologically-dependent optical parameter of the target voxel may be determined based on the reconstructed amplitude of the signal light. Each value respectively stored in each of the bins may be an intensity of the spatial component of the respective interference light pattern, in which case, the plurality of values stored in each of the bins may be used to extract a product of the amplitude of the signal light and a known amplitude of the reference light, and the amplitude of the signal light may be determined from the extracted product.
Other and further aspects and features of the invention will be evident from reading the following detailed description of the preferred embodiments, which are intended to illustrate, not limit, the invention.
The drawings illustrate the design and utility of preferred embodiments of the present invention, in which similar elements are referred to by common reference numerals. In order to better appreciate how the above-recited and other advantages and objects of the present inventions are obtained, a more particular description of the present inventions briefly described above will be rendered by reference to specific embodiments thereof, which are illustrated in the accompanying drawings. Understanding that these drawings depict only typical embodiments of the invention and are not therefore to be considered limiting of its scope, the invention will be described and explained with additional specificity and detail through the use of the accompanying drawings in which:
The ultrasound modulated optical tomography (UOT) systems described herein utilize the combination of a pulsed ultrasound sequence that tags light propagating through an anatomical structure, and a selective lock-in camera that detects the tagged light (e.g., via parallel speckle detection (PSD)), as opposed to a conventional camera, to provide a highly efficient and scalable scheme that enables detection of highly localized and high spatial resolution UOT signals (e.g., blood-oxygen level dependent signals) at great depth inside a biological specimen, e.g., noninvasively through the entire thickness of the human skull and into the underlying cerebral cortical brain matter. The UOT systems may utilize a specific homodyne interference scheme that enables shot noise limited detection of the signal light. Such UOT signals may be used for, e.g., brain-computer interfacing, medical diagnostics, or medical therapeutics. Although the UOT systems are described herein as being used to image brain tissue for exemplary purposes, such UOT system can be used to image other anatomical parts of the body.
Referring to
In the illustrated embodiment, the physiologically-dependent optical parameter may be, e.g., a level of deoxygenated and/or oxygenated hemoglobin concentration or relative abundance, although in other embodiments, the physiologically-dependent optical parameter can be any parameter that varies in accordance with a change in an optical property of the target voxel 14 (e.g., light absorption). The physiologically-dependent optical parameters may alternatively comprise an analyte concentration in the blood, analyte/metabolite in tissue, concentration of a substance (e.g., blood, hemoglobin) or a structure within tissue, the presence and concentration of lamellar bodies in amniotic fluid for determining the level of lung maturity of a fetus, the presence and/or concentration of meconium in the amniotic fluid, optical properties of other extravascular fluids, such as pleural, pericardial, peritoneal, and synovial fluids. The physiologically-dependent optical parameter may be used internally within the UOT system 10 or may be transmitted to external devices for use therein, e.g., medical devices, entertainment devices, neuromodulation stimulation devices, alarm systems, video games, etc.
The UOT system 10 generally includes an acoustic assembly 20, an interferometer 22, a controller 24, a lock-in camera 28, and a processor 30.
The acoustic assembly 20 is configured for delivering ultrasound 32 into the target voxel 14. Preferably, the acoustic assembly 20 focuses the ultrasound 32 on this target voxel 14 in order to maximize the imaging resolution of the UOT system 10; that is, the more focused the ultrasound 32 is, the smaller the target voxel 14 may be defined, thereby increasing the resolution of the UOT system 10.
Preferably, the frequency fus of the ultrasound 32 is selected (e.g., in the range of 100 KHz-10 MHz), such that the ultrasound 32 can pass efficiently through the skull and brain matter without significant attenuation that would otherwise cause insufficient ultrasound pressure at the target voxel 14, so that detectable UOT modulation of the light is created, as described in further detail below. It should be appreciated that the wavelength of such ultrasound in brain matter, given that the speed of sound in brain matter is similar to that of water (1500 meter/second), is on the order of fractions of a millimeter to a few millimeters. Thus, the acoustic assembly 20 may obtain ultrasound focal confinement at the target voxel 14 laterally on the order of the wavelength of the ultrasound 32 (e.g., less than 1 mm), and axially on the order of the wavelength of the ultrasound 32 when the acoustic assembly 20 is operated to pulse the ultrasound 32 at short durations (e.g., a single cycle), as will be described in further detail below.
Referring further to
The signal generator 36 is configured for generating alternating current (AC) signals for driving the ultrasound transducer arrangement 34 at a defined ultrasound frequency, duration, and intensity. The AC drive signal may be electrical or optical, depending on the nature of the ultrasound transducer arrangement. The signal generator 36 includes control inputs (not shown) for receiving control signals from the controller 24 that cause the ultrasound transducer arrangement 34 to emit the ultrasound 32 at a selected time, duration, and intensity. Thus, as will be described in further detail below, the controller 24 may selectively pulse the ultrasound 32.
In one particular embodiment, the transducer arrangement 34 is a head-mounted steerable ultrasonic array coupled to the skin of the patient via hydrogel or other means of mechanical coupling in order to effectively launch the ultrasound 32 towards the precisely defined target voxel 14 within the anatomical structure 16, and in this case, the three-dimensional volume of the brain, while compensating the ultrasound wavefront using well-known phased array techniques to achieve efficient and selective ultrasound delivery to the target voxel 14.
Referring to
The reference light 42 may be combined with the signal light 44 in the sample light pattern 47 in a homodyne manner, e.g., by initially frequency shifting the sample light 40 by the frequency fus of the ultrasound 32 delivered into the target voxel 14 by the acoustic assembly 20. That is, if unmodified, the sample light portion 40a passing through the target voxel 14 will be frequency shifted (i.e., tagged) by the ultrasound 32 that also passes through the target voxel 14, such that the signal light 44 will have frequencies f−fus. Presumably, the sample light portion 40b not passing through the target voxel 14 will not be frequency shifted (i.e., untagged) by the ultrasound 32, such that the background light 46 will have a frequency f, i.e., the frequency of the sample light 40. It is also that not all of the sample light portion 40a passing through the target voxel 14 will be tagged by the ultrasound 32 (i.e., there exists a tagging efficiency (i.e., the number of tagged photons relative to a number of untagged photons scattered by the target voxel 14)), and therefore, some of the sample light portion 40a passing through the target voxel 14 will be scattered by the anatomical structure 16 as background light 46.
However, assuming that the reference light 42 and the sample light 40 output by the interferometer 22 have the same frequency f, in order to combine the ultrasound tagged signal light 44 in the sample light pattern 47 and the reference light 42 in a homodyne manner, which requires the reference light 42 and signal light 44 to have the same frequency, the frequency f of the sample light 40 or the reference light 42 must initially be shifted relative to each other by the ultrasound frequency fus, such that, upon combining by the interferometer 22, the frequency of the ultrasound tagged signal light 44 will be shifted to the same frequency as the reference light 42, and the frequency of the untagged background light 46 will differ from the frequency of the reference light 42 by the ultrasound frequency fus. Thus, either the sample light 40 or the reference light 42 will be pre-conditioned, such that the ultrasound tagged signal light 44 will interfere with the reference light 42 in a homodyne manner, resulting in a DC interference component between the reference light 42 and signal light 44 that can be detected by the lock-in camera 28 as the signal component during each pulse, as will be described in further detail below. In contrast, the frequency shifting of the sample light 40 before it enters the anatomical structure 16, or the frequency shifting of the reference light 42, will prevent the untagged background light 46 from interfering with the reference light 42 in a homodyne manner.
In the embodiment illustrated in
The interferometer 22 is further configured for modulating (and in the illustrated embodiment, phase modulating) the interference light pattern to generate a plurality of different interference light patterns, which as will be described in further detail below, enables the amplitude of the signal light 44 to be distinguished from the background light 46.
Referring further to
The light source 50 is configured for generating coherent light as the source light 38, preferably at a single wavelength (e.g., in the range of 605 nm to 1300 nm), and may take the form of, e.g., a laser diode. In alternative embodiments, multiple light source(s) (not shown) may be used to generate the source light 38 at multiple distinct wavelengths, e.g., one generating source light 38 within the range of 605 nm to 800 nm, and another generating source light 38 within the range of 800 nm to 1300 nm. The coherence length of the source light 38 is preferably at least one meter in order to generate the best speckle contrast in the speckle light pattern 48. The light source 50 may receive power from a drive circuit (not shown), which may include control inputs for receiving control signals from the controller 24 that cause the light source 50 to emit the source light 38 at a selected time, duration, and intensity. Thus, as will be described in further detail below, the controller 24 may selectively pulse the source light 38, and thus the sample light 40 and reference light 42.
As specifically illustrated in
The optical phase shifter 54 is configured for setting the phase difference between the sample light 40 and reference light 42. The optical phase shifter 54 may include control inputs (not shown) for receiving control signals from the controller 24 that cause the optical phase shifter 54 to set the phase of the reference light 42 relative to the sample light 40. Thus, as will be described in further detail below, the controller 24 may selectively set the phase between the sample light 40 and the reference light 42.
The optical frequency shifter 56 is configured for down frequency shifting the sample light 40 by the ultrasound frequency fus to f−fus, such that the frequency of the ultrasound tagged signal light 44 will be f, while the frequency of the background light 46 will be f−fus, thereby enabling the homodyne combination of the reference light 42 at frequency f and the ultrasound tagged signal light 44 at frequency f, as described above with respect to
In any event, the frequency shifter 54 may include a local oscillator (not shown) that outputs a signal having a fixed or variable frequency. The local oscillator may be variable, in which case, it may have a control input for receiving control signals from the controller 24 that cause the local oscillator to output a signal at a defined frequency. Alternatively, the local oscillator may be fixed, in which case, it will output a signal having a fixed frequency. In either case, the frequency of the signal output by the local oscillator will be equal to the frequency fus of the ultrasound 32 emitted by the acoustic assembly 20.
The light combiner 58 is configured for combining the reference light 42 with the sample light pattern 47 via superposition to generate the interference light pattern 48. The light combiner 58 can take the form of, e.g., a combiner/splitter mirror.
The path length adjustment mechanism 60 is configured for adjusting the optical path length of the reference light 42 (i.e., the reference arm) to nominally match the expected optical path length of the combined sample light 40 and signal light 44 (i.e., the sample arm), such that the signal light 44 and the reference light 42 reach the light combiner 58 at the same time. The path length adjustment mechanism 60 may include a beam splitter/combiner 64 and an adjustable mirror 66 that can be displaced relative to the beam splitter/combiner 64. The beam/splitter combiner 64 is configured for redirecting the reference light 42 at a ninety-degree angle towards the mirror 66, and redirecting the reference light 42 reflected back from the mirror 66 at a ninety-degree angle towards the light combiner 58. Thus, adjusting the distance between the mirror 66 and the beam splitter/combiner 64 will adjust the optical path length of the reference arm to match the optical path length of the sample arm.
The mirror assembly 62 is configured for confining the optical light paths in the interferometer 22 into a small form factor, and in the illustrated embodiment, includes a first tilted, completely reflective, mirror 62a configured for redirecting the sample light 40 at a ninety-degree angle towards the biological specimen 16, and a second tilted, completely reflective, mirror 62b configured for redirecting the signal light 44 (and coincidentally a portion of the background light 46) towards the light combiner 58.
Referring back to
The controller 24 is further configured for operating the interferometer 22 to sequentially modulate the interference light pattern 48 (in the illustrated embodiment, by sending on/off control signals to the optical phase shifter 54) to generate a plurality of different interference light patterns. As will be described in further detail below, the interferometer 22 will set different phases (and in the illustrated embodiment, four different phases equal to 0, π/2, π, and 3π/2) between sequential pulses of the sample light 40 and the reference light 42 to facilitate quadrature detection of the signal light 44. As will be also described in further detail below, the controller 24 is further configured for synchronously operating the lock-in camera 28, such that the bin shifting of data detected by the lock-in camera 28 is performed in synchrony with the phase changes in the interferometer 22.
Referring further to
Thus, each detector 68 of the lock-in camera 28 respectively stores a plurality of values in a plurality of bins 70a-70d representative of the spatial component of the four interference light patterns 48, and in this case, four bins 70a-d (in general, 70) for storing four values from the respective four interference light patterns 48. The spatial component values stored in the bins 70 of a respective detector 68 may be, e.g., the intensity values of the respective spatial component of interference light patterns 48. For example, for any particular detector 68 (or pixel) corresponding to a particular spatial component (or speckle grain), four power values Pa-Pd for the four interference patterns 48 will be respectively stored in the four bins 70a-70d. As will be described in further detail below, the spatial component power values Pa-Pd detected by each detector 68 of the camera 28 for the four interference patterns 48 can be used to reconstruct the amplitude of the signal light 44, and thus, can be said to be representative of the physiologically-dependent optical parameters (e.g., optical absorption) of the target voxel 14. The lock-in camera 28 includes control inputs (not shown) for receiving control signals from the controller 24, such that the detection and binning of the data can be coordinated with the pulsing of the ultrasound 32 and sample light 40 described in further detail below.
Although only a single lock-in camera 28 is illustrated, it should be appreciated that multiple lock-in cameras 28 (e.g., in an array) or a lock-in camera in the form of multiple camera sensor chips on a common circuit board, can be used to increase the number of detectors 68 (i.e., pixels). Although not illustrated, the system 10 may include magnification optics and/or apertures to magnify the individual speckle grains, which may have a size on the order of the wavelength of the near-infrared or visible light used to acquire the data voxel, and hence on the order of hundreds of nanometers in size, to approximately the sizes of the detectors 68 of the lock-in camera 28. Thus, in the illustrated embodiment, the pixel sizes and pitches of the lock-in camera 28 are matched to the speckle grain sizes and pitches of the interference light pattern 48 via the appropriate magnification, although other embodiments are possible.
Referring to
During one acquisition of a single data voxel (i.e., acquisition of data characterizing the target voxel 14), an ultrasound pulse train consisting of four separate, but identical, ultrasound pulses Ua-Ud are delivered into the target voxel 14. In this embodiment, the duration τ of each ultrasound pulse U is equal to only one full cycle of the ultrasound 32 to maximize the data acquisition speed, and thus, is equal to 1/fus, although in alternative embodiments, the duration t may be several ultrasound cycles long (e.g., on the order of 1 microsecond or less than one microsecond). It should be noted that it is desirable to minimize the duration t of the ultrasound pulse U in order to minimize ultrasound focal confinement at the target voxel 14.
The duty cycle of the ultrasound pulses Ua-Ud (i.e., the time that elapses between the beginning of one pulse U to the beginning of the next pulse U) is τduty. The duty cycle τduty may be selected to allow each ultrasound pulse U to exit the anatomical structure 16 before the next measurement is taken, such that the ultrasound tagged signal light 44 is only present at high pressures at the three-dimensional location of the target voxel 14. The frame rate of the lock-in camera 28 should be selected to match the duty cycle τduty of the ultrasound pulse U, such that there exists one ultrasound pulse U per frame.
A light pulse train consisting of four sample light pulses La-Ld is also delivered into the anatomical structure 16 in synchrony with the delivery of the four ultrasound pulses Ua-Ud, such that, as each ultrasound pulse U passes through the target voxel 14, the sample light pulse L likewise passes through the target voxel 14.
In this manner, only the signal light 44 (and none of the background light 46) is tagged with the ultrasound, as discussed above. In this particular embodiment, only one sample light pulse L is delivered for each ultrasound pulse U. Thus, there is a one-to-one correspondence between the sample light pulses La-Ld and the ultrasound pulses Ua-Ud. Although each of the sample light pulses L is illustrated in
For each of the four separate ultrasound pulses Ua-Ud occurring during the acquisition of a single data voxel, the phase difference between the reference light 42 and the sample light 40 is set to a different setting, and in this case, to one of 0, π/2, π, and 3π/2. In the illustrated embodiment, the phase between the reference light 42 and the sample light 40 is sequentially set to 0, π/2, π, and 3π/2, although these phase settings can be performed in any order, as long as all four phase settings 0, π/2, π, and 3π/2 are used during the acquisition of a single data voxel.
The respective pulses of the sample light pattern 47 and reference light 42 are then combined into the interference light patterns 48, each having four corresponding interference pulses Ia-Id that can be detected by the lock-in camera 28. That is, for each interference pulse I, a detector 68 detects a spatial component of the respective interference pulse I (e.g., a speckle grain in the case where the interference light pattern 48 includes a speckle pattern) and stores the spatial component value (e.g., power) within a respective one of the bins 70.
That is, at phase φ=0, a given pixel n will detect and store the value of the respective spatial component of the interference pulse Ia into bin 1 of the pixel n; at phase φ=π/2, the pixel n will detect and store the value of the respective spatial component of the interference pulse Ib into bin 2 of the pixel n; at phase φ=π, the pixel n will detect and store the value of the respective spatial component of the interference pulse Ic into bin 3 of the pixel n; and at phase φ=3π/2, the pixel n will detect and store the value of the respective spatial component of the interference pulse Id into bin 4 of the pixel n.
Similarly, at phase φ=0, the next pixel n+1 will detect and store the value of the respective spatial component of the interference pulse Ia into bin 1 of the pixel n+1; at phase φ=π/2, the pixel n+1 will detect and store the value of the respective spatial component of the interference pulse Ib into bin 2 of the pixel n+1; at phase φ=π, the pixel n+1 will detect and store the value of the respective spatial component of the interference pulse Ic into bin 3 of the pixel n+1; and at phase φ=3π/2, the pixel n+1 will detect and store the value of the respective spatial component of the interference pulse Id into bin 4 of the pixel n+1.
Similarly, at phase φ=0, the next pixel n+2 will detect and store the value of the respective spatial component of the interference pulse Ia into bin 1 of the pixel n+2; at phase φ=π/2, the pixel n+2 will detect and store the value of the respective spatial component of the interference pulse Ib into bin 2 of the pixel n+2; at phase φ=π, the pixel n+2 will detect and store the value of the respective spatial component of the interference pulse Ic into bin 3 of the pixel n+2; and at phase φ=3π/2, the pixel n+2 will detect and store the value of the respective spatial component of the interference pulse Id into bin 4 of the pixel n+2.
Thus, for each of an n number of pixels, four values will be respectively stored in the four bins 1-4. Significantly, in the case where the interference light pattern 48 includes a speckle light pattern, it is important that all four sample light pulses P be delivered by the interferometer 22 to the target voxel 14 and that all four interference pulses I be detected and recorded by the camera 28 within the characteristic speckle decorrelation time of the target voxel 14, which scales super-linearly with the depth into the anatomical structure 16 at which the target voxel 14 is located. For imaging deep inside a living biological tissue, such as through the human skull and into the human cerebral cortex, the speckle decorrelation time is expected to be on the order of microseconds to tens of microseconds. For imaging directly into living brain matter in the absence of skull, speckle decorrelation times have been measured to be on the order of ten milliseconds for 1-millimeter penetration or 1-millisecond for 3-millimeter penetration. Notably, the speckle decorrelation time impacts the depth scaling of lock-in camera based UOT in dynamic scattering media, such as biological tissue, namely the constraint that multiple phase-shifted measurements must be made within the speckle decorrelation time (see, e.g., Qureshi M M, Brake J., Jeon H J, Ruan H, Liu Y, Safi A M, Eom T J, Yang C., Chung E, “In Vivo Study of Optical Speckle Decorrelation Time Across Depths in the Mouse Brain,” Biomedical Optics Express, Vol. 8, No. 11, pp. 4855-4864 (Nov. 1, 2017). Thus, it is important that the time window in which the set of quadrature measurements is short enough that the target voxel 14 does not have the time to de-correlate significantly. Otherwise, the signal-to-noise ratio is diminished.
Referring to
In particular, during the acquisition of four consecutive data voxels (as opposed to only one in the pulsing sequence of
A light pulse train consisting of four sets of sample light pulses, with each set comprising four sample light pulses La-Ld, are also delivered into the anatomical structure 16 in synchrony with the delivery of the four ultrasound pulses U, such that as each ultrasound pulse U passes through the target voxel 14, the corresponding set of four sample light pulses La-Ld, likewise pass through the target voxel 14. Thus, only the signal light 44 (and none of the background light 46) is tagged with the ultrasound, as discussed above. Thus, four sample light pulses La-Ld are delivered for each ultrasound pulse U. Thus, there is a four-to-one correspondence between the sample light pulses La-Ld and ultrasound pulses U.
Thus, in the same manner described above with respect to the pulsing sequence illustrated in
It can be appreciated that the use of the lock-in camera 28 provides for a high-speed and precisely timed detection method that can capture differences in a light field far faster than the frame rates of conventional cameras. In the illustrated embodiment, the lock-in camera 28 rapidly measures the four quadratures of the pulse sequences illustrated in
It should be appreciated that in addition to the ability of the combination of the pulsed UOT with a lock-in camera to provide high axial spatial resolution and high sensitivity from the high-speed lock-in detection, such combination also provides the additional advantage of efficiently detecting the signal light associated with a specific time point on the ultrasound phase cycle (e.g., at the peaks of the ultrasound phase cycle). As such, the pulsed UOT/lock-in camera combination can accurately image tissue with a relatively small number of data measurements, and thus, a relatively short period of time, preferably within the speckle decorrelation time of the target voxel. In comparison, a continuous wave approach results in averaging light signal detection over a range of arbitrarily placed points on the ultrasound phase cycle, leading to a diminished overall detection sensitivity, requiring that, for sufficient sensitivity, data measurements be taken over a period time longer than the speckle decorrelation time of the target voxel. Thus, the use of pulsed UOT in combination with the lock-in camera allows deeper imaging into tissue.
The detection processes illustrated in
In particular, this optical arrangement includes a first 1×2 fiber splitter 72a in which a single optical pulse P (generated by the light source 50) is input via an optical fiber 74 and split into two identical optical pulses P1, P2. Two optical fibers 74a, 74b of different optical lengths are connected to the respective outputs of the first 1×2 fiber splitter 72a, such that the two identical optical pulses P1, P2 respectively propagate within the two optical fibers 74a, 74b. The optical arrangement further includes a first 2×1 fiber coupler 76a into which the two identical optical pulses P1, P2 are input and combined, and output to a single optical fiber 74c. By making the lengths of the optical fibers 74a, 74b different from each other, the single optical pulse P input into the first 1×2 fiber splitter 72a is effectively split into two identical optical pulses that propagate through the single optical fiber 74c and are spaced out by a time difference determined by the optical path length difference between the two optical fibers 74a, 74b. This conveniently enables the creation of two optical pulses that track each other identically.
Another fiber coupler and pair of optical fibers can be added to create four identical optical pulses separated from each other in time. In particular, the optical arrangement further includes a second 1×2 fiber splitter 72b to which the single optical fiber 74c carrying the two identical and temporally spaced optical pulses P1, P2 is coupled. Thus, the two identical optical pulses P1, P2 are input into the second 1×2 fiber splitter 72b and split into four identical optical pulses P1a, P1b, P2a, P2b (i.e., the optical pulse P1 is split into optical pulses P1a, P1b, and the optical pulse P2 is split into optical pulses P2a, P2b). Two optical fibers 74d, 74e of different optical lengths are connected to the respective outputs of the second 1×2 fiber splitter 72b, such that the two sets of two identical optical pulses P1a, P1b and P2a, P2b respectively propagate within the two optical fibers 72d, 72e. The optical arrangement further includes a second 2×1 fiber coupler 76d into which the two sets of identical optical pulses P1a, P1b and P2a, P2b are input and combined, and output to a single optical fiber 74f. By making the lengths of the optical fibers 74d, 74e different from each other, the two optical pulses input into the second 1×2 fiber splitter 72b are effectively split into four identical optical pulses that propagate through the single optical fiber 74f and spaced out by a time difference determined by the optical path length difference between the two optical fibers 74d, 74e. This conveniently enables the creation of four optical pulses that track each other identically.
Referring back to
The spatial component power values Pa-Pd for all four interference light patterns Ia-Id can be used in accordance with known “quadrature detection” methods to reconstruct the amplitude of the signal light 44, which is proportional to the number of tagged photons emerging from the target voxel 14 (i.e., the number of photons in the signal light 44), and thus, can be used to measure optical absorption in the target voxel 14 (e.g., for the purpose of measuring spatially localized neural activity-correlated changes in the level of deoxygenated and/or oxygenated hemoglobin concentration or relative abundance in the brain, which appear as localized changes in the optical absorption of blood). In the illustrated embodiment, it should be understood that because of the diffusive scattering of light over large distances through the brain and skull, the interference light pattern 48 detected by the lock-in camera 28 takes the form of a random speckle pattern in which each localized speckle grain has a definite, but random phase offset in the interference light pattern 48 (i.e., a beat pattern) between the reference light 42 and the signal light 44. This results in the unknown random phases in the beat patterns measured by each detector 68 (or pixel) in the equations set forth below.
In particular, the power detected at a single detector 68 (or pixel) for each optical pulse at one of the four phases can be expressed as:
The terms Pbackground+Psignal+Preference are constant across all four optical pulses with different control phase values φcontrol. The terms 2(Psignal×Pbackground)1/2×cos (2π×fus−φunknown2)+2(Preference×Pbackground)1/2×cos(2π×fus−φunknown3) oscillate at the frequency fus, and are not detected by the lock-in camera 28, and thus, can be ignored. As such, equation [1] can be reduced to:
Thus, the term magnitude of Psignal×Preference can be extracted by shifting the control phase φcontrol successively on each of four successive pulses φcontrol=0, π/2, π, and 3π/2. Even though φunknown is an unknown and random phase, specific to each pixel, which results from the laser speckle pattern due to light scattering in the tissue, by measuring and storing each of these four measurements at different control phase values φcontrol, the value of the interference term 2(Psignal×Preference)1/2 may be extracted via the known principal of “quadrature detection.” Because the power of the reference light Preference is known or independently measurable, the interference term 2(Psignal×Preference)1/2 serves as a measurement of the power of the signal light Psignal. Thus, using a known scaling relationship, the power of the signal light Psignal can be determined (either in the absolute sense or relative sense) from the extracted term interference term 2(Psignal×Preference)1/2.
Because the speckle phases are random, according to the known principles of parallel speckle detection in UOT or in wavefront measurement from strongly scattering media, it is known that a single-pixel detector will not scale to high signal to noise ratios. In particular, the aggregate signal over a large single-pixel detector would scale as the square root of detector size, but so would shot noise in the background, and hence the signal to noise ratio performance of a large detector would not increase with detector size. In contrast, as described in the equations below, with lock-in detection at each detector (or pixel), the aggregate signal scales linearly with the number of pixels, while the aggregate background shot noise scales as the square root, and hence signal to noise performance increases as the square root of the number of pixels, giving a strong advantage for using large numbers of pixels.
It can be assumed that the amplitude of Preference is much greater than the amplitude of Pbackground, and the amplitude of Psignal is naturally much less than the amplitude of Preference, since the ultrasound tagged signal light 44 originates from a very small target voxel 14 within the tissue and the tagging efficiency (i.e., the number of tagged photons relative to a number of untagged photons scattered by the target voxel 14) within that target voxel 14 is a small fraction. Thus, only interference terms containing Preference are significant in the sum representing the intensity measured by each pixel (i.e., Pbackground+Psignal+Preference+2(Psignal×Preference)1/2×cos(φcontrol−φunknown1)).
Therefore, the dominant signal source contributing to detection has the following number of photons impinging on one pixel:
With a number of pixels N, the signal-to-noise ratio (SNR) scales with N1/2, since the total shot noise grows as N1/2, whereas the total signal grows as N, so that:
It should be appreciated that although the UOT system 10 has been described as using a 4-bin quadrature detection scheme to reconstruct the amplitude of the signal light 44 from the interference light patterns 48, and therefore, utilizes four bins 70 (and four optical pulses) for each detector 68 (or pixel) of the lock-in camera 28 to store the intensity values of the respective four interference patterns 48 over the four different phases, the UOT system 10 may utilize less than four phases (e.g., three phases equal to 0, 2π/3, and 4π/3), or may even utilize two phases (e.g., 0 and π) to reconstruct the amplitude of the signal light 44 from the interference light patterns 48, and therefore utilizes three bins 70 (and three optical pulses) or only two bins 70 (and only two optical pulses) for each detector 68 (or pixel) to store the intensity values of the respective interference patterns 48 over the phases. It should further be appreciated that although the phases of the 4-bin quadrature scheme, as well as the three-bin and two-bin detection schemes, have been described as being equally spaced, the phases used in any of these detection schemes can be unequally spaced. For example, for the three-bin detection scheme, the phases can be selected to be 0, π, and 4π/3, or for a two-bin detection scheme, the phases can be selected to be 0 and 4π/3.
In the case of a two-bin detection scheme, rather than obtaining a quadrature amplitude from each pixel 68, the power of the signal light 44 can be computed as the absolute difference between the two intensity values stored in the two bins 70 for each pixel 68 and then averaged in accordance with the following equation:
However, the two-bin detection scheme represents a simplification that leads to only a small constant decrease factor in the signal to noise ratio. The dominant signal source contributing to detection has the following number of photons impinging on one pixel:
With a number of pixels N, the signal-to-noise ratio (SNR) scales with N1/2, since the total shot noise grows as N1/2, whereas the total signal grows as N, so that:
Notably, the use of a two-bin detection scheme, rather than the four-bin quadrature scheme, provides the advantage that only two optical pulses, as opposed to four optical pulses, needs to be generated, thereby shortening the time period needed to take a measurement of the target voxel 14, and thus, alleviating the speckle decorrelation time limitation.
In an optional embodiment, a digital optical phase conjugation (DOPC) technique can be used to boost the sensitivity of the pulsed UOT detection. DOPC can be performed in the context of schemes that rely on time reversal based optical phase conjugation using “guidestars” localized in three dimensions, for instance, using schemes, such as Time Reversal of Ultrasound-Encoded Light (TRUE) (see, e.g., Xu X, Liu H., Wang L V, “Time-Reversed Ultrasonically Encoded Optical Focusing into Scattering Media,” Nature Photonics, Vol. 5, No. 3, pp. 154-157 (Mar. 1, 2011); Wang Y M, Judkewitz B, DiMarzio C A, Yang C., “Deep-Tissue Focal Fluorescence Imaging with Digitally Time-Reversed Ultrasound-Encoded Light,” Nature Communications, Vol. 3, Article 928 (Jun. 16, 2012); Horstmeyer R., Ruan H, Yang C, “Guidestar-Assisted Wavefront-Shaping Methods for Focusing Light into Biological Tissue,” Nature Photonics, Vol. 9, No. 9, pp. 563-571 (Sep. 1, 2015).
These methods are used to focus light to a guide-star-defined point deep inside a scattering medium, by measuring the wavefront emanating from the guidestar and digitally time-reversing (e.g., phase conjugating) light in order to cause the light to “play back” its path through the scattering medium and come to focus at the guidestar position. In the context of UOT, the guidestar is the focal point of an ultrasound beam. In these methods, the phase of a tagged light field originating from a given three-dimensional guidestar voxel in the brain is measured using demodulation and quadrature detection, and then an approximate phase-conjugate, i.e., approximate time-reverse light field, possibly amplified in intensity, is “played back” to focus light to the three-dimensional guidestar location despite the effects of strong or even diffusive scattering in the tissue.
In the context of the UOT system 10 described herein, the phase of the wavefront of the signal light 44 originating from the target voxel 14 (i.e., the guidestar) is measured using the pulsed UOT detection scheme described above, as illustrated in
Referring to
The SLM array 78 may include any of a number of different amplitude and/or phase modulator structures, such as liquid crystals, re-positionable microelectromechanical systems (MEMS) mirrors, ferroelectrics, digital micro-mirror device pixels, among others. In one embodiment, the SLM array 78 may be semi-transparent (e.g., a liquid crystal modulator backed by a partial reflector), and can be inserted into the light path between the entry of the reference light 42 and the lock-in camera 28. The SLM array 78 may be built directly on top of the lock-in camera 28 to create a phase conjugation array, with this arrangement being similar to the pulsed UOT detection scheme described above.
Referring to
The improvement in contrast of this return light 80 (i.e., the phase conjugate light field) to the target voxel 14 is given by: Contrast A=α*((N−1)/M+1), wherein N is the number of input optical modes (or the number of photons if less than the number of input optical modes), which is approximately equal to the number of pixels on the phase conjugation array); M is the number of target optical modes in the target voxel 14, and α equals 1 when a full phase and amplitude conjugation is performed, and is some value smaller than 1 when a phase only, amplitude only, and/or coarse grain phase conjugation is performed. The term “coarse grain,” in this context, means that the phase playback at each pixel can take only a finite number of possible values.
The phase conjugation process can be iterated many times, each time taking the light field, resulting from the last step, and phase conjugating that scattered light field. The contrast improvement can be expected to grow as (contrast A)K, where K is the number of iterations. Thus, the number of photons traveling through the target voxel 14 can be exponentially amplified, thereby improving the effective modulation depth of the UOT (i.e., the fraction of the ultrasound tagged photons reaching the detector). The addition of phase conjugation to the pulsed UOT system 10 could be used to increase the number of collected tagged photons, increase modulation depth, or decrease ultrasound intensity or duty cycle requirements.
Performance estimates for the UOT system 10 described herein in the detection of a blood-oxygen-level dependent signal in the brain through the skull as a function of the number of pixels in the lock-in camera 28 used (in this case, 10 million pixels or higher) indicate that neural activity dependent changes in the blood-oxygen-level dependent signal could be detected at hundreds to thousands of voxels per 100 millisecond temporal sample. In this calculation, the use of a 2 MHz ultrasound, and thus a spatial resolution on the order of ½ millimeter, is assumed, exceeding the spatial resolution of traditional blood-oxygen-level dependent signal measurements, like functional MRI (fMRI), and vastly exceeding the many millimeter to multiple centimeter-scale spatial resolution of diffuse optical tomography, including time-gated forms of diffuse optical tomography. In this calculation, it is further assumed that millions of tagged photons must be collected from the target voxel 14 per temporal sample in order to measure naturally occurring blood-oxygen-level dependent signals functional changes in the human brain, which are on the order of small fractions of a percent, while overcoming shot noise fluctuations in the number of detected tagged photons.
In one embodiment, the processor 30 utilizes blood-oxygen-level dependent signals detected by the lock-in camera 28 to determine the neural activity in the brain; that is, blood-oxygen-level dependent signals provide a sense of the level of deoxygenated and/or oxygenated hemoglobin concentration or relative abundance in the target voxel 14 in the brain, and given the known coupling between cerebral hemodynamics and neuronal activity, the processor 30 can thereby determine the extent of neuronal activity in that target voxel 14. In another embodiment, the UOT system 10 detects blood-oxygen-level dependent signals over multiple wavelengths of the sample light, in which case, the processor 30 may determine and compare the optical absorption characteristics of the target voxel 14 of blood-oxygen-level dependent signals over the different wavelengths of sample light in order to determine the level of deoxygenated and/or oxygenated hemoglobin concentration or relative abundance present in the target voxel 14 according to known principles of functional infrared spectroscopy, for instance by solving two equations in two unknowns relating the measured absorption at two wavelengths to the level of deoxygenated and/or oxygenated hemoglobin concentration or relative abundance in the blood, or alternatively several equations in several unknowns representing absorption at several wavelengths in order to determine the concentrations of several molecular species in the target voxel 14.
In one particularly advantageous embodiment, instead of detecting blood-oxygen-level dependent signals, the processor 30 may detect faster signals of neuronal activity, such as in the brain, to determine the extent of neuronal activity in the target voxel 14. Neuronal activity generates fast changes in optical properties, called “fast signals,” which have a latency of about 10-100 milliseconds and are much faster than the metabolic (approximately 100-1000 milliseconds) and hemodynamic (hundreds of milliseconds to seconds) evoked responses (see Franceschini, M A and Boas, D A, “Noninvasive Measurement of Neuronal Activity with Near-Infrared Optical Imaging,” Neuroimage, Vol. 21, No. 1, pp. 372-386 (January 2004)). Additionally, is believed that brain matter (e.g., neurons and the extracellular matrix around neurons) hydrates and dehydrates as neurons fire (due to ion transport in and out of the neurons), which could be measured via determining the absorption characteristics of water in the target voxel 14. In this case, it is preferred that the target voxel 14 be minimized as much as possible by selecting the appropriate ultrasound frequency (e.g., two to six times the size of a neuron, approximately 100 micrometers) in order to maximize sensitivity to highly localized changes in fast indicators of neural activity. As illustrated in
Regardless of the nature of the detected signal and physiologically-dependent optical parameter, the processor 30 may optionally use a computational model of light propagation in the tissue, and deconvolution or inverse problem optimization methods/algorithms, to improve the spatial resolution of the resulting measurement. Empirical measurements of a sample may be compared to those predicted by a model of the spatial layout of absorbers of the sample incorporating an effective point spread function of detection, such that the model may be improved to obtain an optimal match between the model predictions and the observed signals from the sample (see Powell S., Srridge S R, Leung T S, “Gradient-Based Quantitative Image Reconstruction in Ultrasound-Modulated Optical Tomography: First Harmonic Measurement Type in a Linearized Diffusion Formulation,” IEEE Transactions on Medical Imaging, Vol. 35, No. 2, pp. 456-467 (February 2016).
Although the UOT system 10 has been described herein as acquiring only one measurement of the target voxel 14, it should be appreciated that the UOT system 10 may acquire multiple measurements of the target voxel 14 over time that yields a time trace indicative of time varying physiologically depending optical properties in the target voxel 14, such as time-varying optical absorption in the target voxel 14 due to functional changes in the brain. Optionally, two time traces of the target voxel 14 can be acquired, one time trace being generated with the ultrasound 32 turned on at regular intervals in the same manner described above, and another time trace generated with the ultrasound 32 turned off at regular intervals. For example, a measurement of the target voxel 14 may be acquired when the ultrasound 32 turned on to create a first data point on the first time trace; a measurement of the target voxel 14 may be acquired when the ultrasound 32 turned off to create a first data point on the second time trace; a measurement of the target voxel 14 may be acquired when the ultrasound 32 turned on to create a second data point on the first time trace; a measurement of the target voxel 14 may be acquired when the ultrasound 32 turned off to create a second data point on the second time trace; and so forth. The second time trace may provide a baseline null signal measurement trace, which is useful for tracking secondary variations distinct from the first time trace's signal variations due to the ultrasound 32.
Referring now to
In the illustrated embodiment, the wearable unit 90 includes a support structure 94 that either contains or carries the transducer arrangement 34 of the acoustic assembly 20 (shown in
The auxiliary unit 92 includes a housing 96 that contains the controller 24 and the processor 30 (shown in
The interferometer 22 and lock-in camera 28 are preferably mechanically and electrically isolated from the acoustic assembly 20, such that the emission of the ultrasound 32 by the acoustic assembly 20, as well as the generation of RF and other electronic signals by the acoustic assembly 20 minimally affects the detection of the optical signals by the interferometer 22 and generation of data by the lock-in camera 28. The wearable unit 90 may include shielding (not shown) to prevent electrical interference and appropriate materials that attenuate the propagation of acoustic waves through the support structure 94.
Having described the arrangement of function of the UOT system 10, one method of operating the UOT system on a patient will now be described. In this method, ultrasound 32 is delivered into the target voxel 14 in the anatomical structure 16, and sample light 40 is delivered into the anatomical structure 16, wherein a portion 40a of the sample light 40 passing through the target voxel 14 is scattered by the anatomical structure 16 as the signal light 44, and another portion 40b of the sample light 40 not passing through the target voxel 14 is scattered by the anatomical structure 16 as background light 46 that combines with the signal light 44 to create the sample light pattern 47. As exemplified above, the anatomical structure 16 may be an intact head comprising the scalp, skull, and brain matter. Due to the high resolution of the UOT system 10, the target voxel 14 may be smaller than one mm3.
The reference light 42 is combined with the sample light pattern 47 to generate an interference light pattern 48 (e.g., in a homodyne manner), and in this method, a speckle light pattern. The ultrasound 32 and sample light 40 are pulsed in synchrony, such that only the signal light 44 is shifted (i.e., tagged) by the ultrasound 32. That is, as described above, each pulse of the sample light 40 will pass through the target voxel 14 only as the ultrasound 32 passes through the target voxel 14, such that no portion of the background light 46 will be tagged by the ultrasound 32. The interference light pattern 48 is sequentially modulated to generate a plurality of different interference light patterns 48. The spatial components of any particular interference light pattern 48 can then be simultaneously detected, and a plurality of values can be stored in the respective bins 70 (either in bins 70a, in bins 70b, in bins 70c, or bins 70d) of the detectors 68. The values are representative of the spatial component for the respective interference light pattern 48. The physiologically-dependent optical parameter of the target voxel 14 is then determined based on the spatial component values stored in the bins 70. Due to the high speed of the lock-in camera 28, the spatial components for any particular interference light pattern 48 may be simultaneously detected and stored in the respective bins 70 very quickly. For example, in one embodiment, the spatial components for any particular interference light pattern 48 may be simultaneously detected, and the resulting spatial component values for all the interference light patterns 48 are stored in the respective bins 70 within 1 millisecond. In another embodiment, the spatial components for any particular interference light pattern 48 may be simultaneously detected, and the resulting spatial component values for all the interference light patterns 48 are stored in the respective bins 70 within 1 microsecond to 1 millisecond.
Referring to
The controller 24 operates the acoustic assembly 20 to generate and deliver a pulse of ultrasound 32 having a frequency fus (initially, ultrasound pulse Ua illustrated in
The wavelength (and thus, the frequency f) of the source light 38 may be selected based on the physiologically-dependent optical parameter to be ultimately determined. For example, if the physiologically-dependent optical parameter is the level of deoxygenated and/or oxygenated hemoglobin concentration or relative abundance, the wavelength of the source light 38 may be in the range of 605 nanometers to 950 nanometers, whereas if the physiologically-dependent optical parameter to be determined is a water absorption level (level of water concentration or relative water concentration), the wavelength of the source light 38 may be in the range of 950-1080 nanometers.
Next, prior to the pulse of sample light 40 entering the anatomical structure 16, the controller 24 operates the interferometer 22 to frequency shift the pulse of sample light 40 by the ultrasound frequency fus, e.g., by sending a control signal to the frequency shifter 56, resulting in the pulse of sample light 40 having a frequency f−fus(step 110). The frequency-shifted pulse of sample light 40 is then delivered into and diffusively scattered within the anatomical structure 16 (step 112). As the pulse of frequency shifted sample light 40 scatters diffusively through the anatomical structure 16, a portion will pass through the target voxel 14 and be frequency shifted (i.e., tagged) back to its original frequency f by the pulse of ultrasound 32 passing through the target voxel 14, resulting in a pulse of scattered signal light 44 having the same frequency f (step 114); and remaining portion will not pass through the target voxel 14, and thus will not be frequency shifted by the pulse of ultrasound 32, resulting in a pulse of scattered background light 46 having a frequency f−fus (the same frequency as the frequency shifted sample light 40 prior to entering the anatomical structure 16) (step 116).
Next, the interferometer 22 then combines (e.g., via the light combiner 58) the pulse of reference light 42 with the pulses of sample light pattern 47 to generate a pulse of an interference light pattern 48 (initially, the interference light pattern pulse Ia illustrated in
At this point, only one quadrature measurement has been taken. If the interferometer 22 has not been set to all four of the phases (step 124), the controller 24 then repeats steps 102-122 to take the next quadrature measurement. That is, the next pulse of ultrasound 32 (e.g., ultrasound pulse Ub illustrated in
Thus, it can be appreciated that steps 102-122 will be repeated to take the remaining quadrature measurements to generate and detect the pulses of the remaining interference light patterns (e.g., the third and fourth interference light pattern pulses Ic, Id illustrated in
After all four quadrature measurements have been taken, the controller 24 recalls the spatial component values of the detected interference light pattern pulses 48 from the bins 70 of the lock-in camera 28 and transfers these values to the processor 30 (step 126). The processor 30 reconstructs the amplitude of the signal light 44 from the four interference light patterns 48 based on these spatial component values (e.g., by using the quadrature equation [2]) (step 128). Steps 102-128 can be iterated to repeatedly acquire data measurements of the target voxel 14, and if a sufficient number of data measurements have been acquired (step 130), the processor 30 may then determine the physiologically-dependent optical parameter (e.g., level of deoxygenated and/or oxygenated hemoglobin concentration or relative abundance or level of water concentration or relative water concentration) of the target voxel 14 based on the data measurements (step 132). In the case where the target voxel 14 is brain matter, the processor 30 may further determine the level of neural activity within the target voxel 14 based on the determined physiologically-dependent optical parameter (step 134).
For example, if the physiologically-dependent optical parameter is the level of deoxygenated and/or oxygenated hemoglobin concentration or relative abundance, and if the amplitude of the signal light 44 is relatively low (or high), indicating high absorption of light by blood in the target voxel 14, it can be assumed that there is a relatively high (or low) hemodynamic response (depending on the light wavelength used) through the target voxel 14, and thus, a substantial amount of neural activity in the target voxel 14. In contrast, if the amplitude of the signal light 44 is relatively high (or low), indicating low absorption of light by blood in the target voxel 14, it can be assumed that there is a relatively low hemodynamic response (depending on the wavelength) through the target voxel 14, and thus, comparatively little neural activity in the target voxel 14.
If the physiologically-dependent optical parameter is the level of water concentration or relative water concentration, and if the amplitude of the signal light 44 greatly varies over a short period of time, indicating a fast signal of neural activity in the brain tissue, it can be assumed that there is a substantial amount of neural activity in the target voxel 14. In contrast, if the amplitude of the signal light 44 varies very little over a short period of time, indicating that there is no fast signal of neural activity in the brain matter, it can be assumed that there is very little or no neural activity in the target voxel 14.
Referring to
The method 100′ is similar to the method 100 illustrated in
That is, during the delivery of current pulse of ultrasound 32 (e.g., ultrasound pulse U illustrated in
After all four quadrature measurements have been taken at steps 102-124, as in the manner described above with respect to the method 100 of
Although particular embodiments of the present inventions have been shown and described, it will be understood that it is not intended to limit the present inventions to the preferred embodiments, and it will be obvious to those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the present inventions. Thus, the present inventions are intended to cover alternatives, modifications, and equivalents, which may be included within the spirit and scope of the present inventions as defined by the claims.
Pursuant to 35 U.S.C. § 119(e), this application claims the benefit of U.S. Provisional Patent Application 62/590,150, filed Nov. 22, 2017, and U.S. Provisional Patent Application 62/596,446, filed Dec. 8, 2017, which are expressly incorporated herein by reference. This application is also related to U.S. patent application Ser. No. 15/844,398 and U.S. patent application Ser. No. 15/844,411, filed on the same date, which are expressly incorporated herein by reference.
| Number | Name | Date | Kind |
|---|---|---|---|
| 5213105 | Gratton et al. | May 1993 | A |
| 5856667 | Spirig et al. | Jan 1999 | A |
| 6041248 | Wang | Mar 2000 | A |
| 6205353 | Alfano et al. | Mar 2001 | B1 |
| 6334699 | Gladnick | Jan 2002 | B1 |
| 6738653 | Sfez et al. | May 2004 | B1 |
| 6777659 | Schwarte | Aug 2004 | B1 |
| 6825455 | Schwarte | Nov 2004 | B1 |
| 6957096 | Sfez et al. | Oct 2005 | B2 |
| 7053357 | Schwarte | May 2006 | B2 |
| 7060957 | Lange et al. | Jun 2006 | B2 |
| 7119906 | Pepper et al. | Oct 2006 | B2 |
| 7144370 | Fomitchov | Dec 2006 | B2 |
| 7498621 | Seitz | Mar 2009 | B2 |
| 7508505 | Lustenberger et al. | Mar 2009 | B2 |
| 7515948 | Balberg et al. | Apr 2009 | B1 |
| 7521663 | Wäny | Apr 2009 | B2 |
| 7541602 | Metzger et al. | Jun 2009 | B2 |
| 7560701 | Oggier et al. | Jul 2009 | B2 |
| 7586077 | Lehmann et al. | Sep 2009 | B2 |
| 7595476 | Beer et al. | Sep 2009 | B2 |
| 7620445 | Tsujita | Nov 2009 | B2 |
| 7622704 | Wäny | Nov 2009 | B2 |
| 7647830 | Sfez et al. | Jan 2010 | B2 |
| 7671671 | Buettgen et al. | Mar 2010 | B2 |
| 7701028 | Kaufmann et al. | Apr 2010 | B2 |
| 7733742 | Gross et al. | Jun 2010 | B2 |
| 7747301 | Cheng et al. | Jun 2010 | B2 |
| 7884310 | Buettgen | Feb 2011 | B2 |
| 7889257 | Oggier et al. | Feb 2011 | B2 |
| 7897928 | Kaufmann et al. | Mar 2011 | B2 |
| 7898649 | Masumura | Mar 2011 | B2 |
| 7917312 | Wang et al. | Mar 2011 | B2 |
| 7923673 | Büttgen et al. | Apr 2011 | B2 |
| 8017858 | Mann | Sep 2011 | B2 |
| 8044999 | Mullen et al. | Oct 2011 | B2 |
| 8103329 | Fomitchov et al. | Jan 2012 | B2 |
| 8106472 | Kaufmann et al. | Jan 2012 | B2 |
| 8108022 | Balberg et al. | Jan 2012 | B2 |
| 8115158 | Buettgen | Feb 2012 | B2 |
| 8126524 | Balberg et al. | Feb 2012 | B2 |
| 8143605 | Metzger et al. | Mar 2012 | B2 |
| 8223215 | Oggier et al. | Jul 2012 | B2 |
| 8280494 | Masumura | Oct 2012 | B2 |
| 8289502 | Yoshida | Oct 2012 | B2 |
| 8299504 | Seitz | Oct 2012 | B2 |
| 8315483 | Shuster | Nov 2012 | B2 |
| 8326567 | Masumura | Dec 2012 | B2 |
| 8336391 | Rokni et al. | Dec 2012 | B2 |
| 8385691 | Shuster | Feb 2013 | B2 |
| 8400149 | Stoughton et al. | Mar 2013 | B2 |
| 8405823 | Pfaff | Mar 2013 | B2 |
| 8423116 | Balberg et al. | Apr 2013 | B2 |
| 8450674 | Yang et al. | May 2013 | B2 |
| 8454512 | Wang et al. | Jun 2013 | B2 |
| 8525998 | Yaqoob et al. | Sep 2013 | B2 |
| 8562658 | Shoham et al. | Oct 2013 | B2 |
| 8644900 | Balberg et al. | Feb 2014 | B2 |
| 8717574 | Yang et al. | May 2014 | B2 |
| 8754939 | Oggier et al. | Jun 2014 | B2 |
| 8803967 | Oggier et al. | Aug 2014 | B2 |
| 8817255 | Masumura | Aug 2014 | B2 |
| 8830573 | Cui et al. | Sep 2014 | B2 |
| 8867798 | Shuster | Oct 2014 | B2 |
| 8917442 | Baym et al. | Dec 2014 | B2 |
| 8922759 | Gassert et al. | Dec 2014 | B2 |
| 8954130 | Masumura | Feb 2015 | B2 |
| 8964028 | Oggier | Feb 2015 | B2 |
| 8976433 | Masumura | Mar 2015 | B2 |
| 8997572 | Wang et al. | Apr 2015 | B2 |
| 9000349 | Lehmann et al. | Apr 2015 | B1 |
| 9027412 | Rokni et al. | May 2015 | B2 |
| 9046338 | Boccara et al. | Jun 2015 | B2 |
| 9057695 | Masumura | Jun 2015 | B2 |
| 9076709 | Felber et al. | Jul 2015 | B2 |
| 9086365 | Wang et al. | Jul 2015 | B2 |
| 9117712 | Oggier et al. | Aug 2015 | B1 |
| 9131170 | Mandelis et al. | Sep 2015 | B2 |
| 9131880 | Balberg et al. | Sep 2015 | B2 |
| 9140795 | Lehmann et al. | Sep 2015 | B2 |
| 9164033 | Edwards et al. | Oct 2015 | B2 |
| 9209327 | Neukom et al. | Dec 2015 | B2 |
| 9226666 | Wang et al. | Jan 2016 | B2 |
| 9232896 | Baym et al. | Jan 2016 | B2 |
| 9234841 | Wang et al. | Jan 2016 | B2 |
| 9237850 | Metzger et al. | Jan 2016 | B2 |
| 9282931 | Tearney et al. | Mar 2016 | B2 |
| 9304490 | Masumura | Apr 2016 | B2 |
| 9313423 | Wang et al. | Apr 2016 | B2 |
| 9329035 | Oggier | May 2016 | B2 |
| 9335154 | Wax et al. | May 2016 | B2 |
| 9335605 | Wang et al. | May 2016 | B2 |
| 9341715 | Buettgen et al. | May 2016 | B2 |
| 9351705 | Wang et al. | May 2016 | B2 |
| 9435891 | Oggier | Sep 2016 | B2 |
| 9442196 | Buettgen et al. | Sep 2016 | B2 |
| 9466938 | Dupret et al. | Oct 2016 | B2 |
| 9486128 | Hannaford et al. | Nov 2016 | B1 |
| 9488573 | Edwards et al. | Nov 2016 | B2 |
| 9528966 | Wang et al. | Dec 2016 | B2 |
| 9555444 | Goodman et al. | Jan 2017 | B2 |
| 9619486 | Shuster | Apr 2017 | B2 |
| 9655527 | Wang et al. | May 2017 | B2 |
| 9668672 | Zalevsky et al. | Jun 2017 | B2 |
| 9698196 | Buettgen et al. | Jul 2017 | B2 |
| 9713448 | Caplan et al. | Jul 2017 | B2 |
| 9720505 | Gribetz et al. | Aug 2017 | B2 |
| 9730649 | Jepsen | Aug 2017 | B1 |
| 9839365 | Homyk et al. | Dec 2017 | B1 |
| 20050085725 | Nagar et al. | Apr 2005 | A1 |
| 20050256403 | Fomitchov | Nov 2005 | A1 |
| 20060023621 | Hwang et al. | Feb 2006 | A1 |
| 20060122475 | Balberg et al. | Jun 2006 | A1 |
| 20060184042 | Wang et al. | Aug 2006 | A1 |
| 20060184049 | Tsujita | Aug 2006 | A1 |
| 20060224053 | Black et al. | Oct 2006 | A1 |
| 20060247506 | Balberg et al. | Nov 2006 | A1 |
| 20060253007 | Cheng et al. | Nov 2006 | A1 |
| 20060264717 | Pesach et al. | Nov 2006 | A1 |
| 20070093702 | Yu et al. | Apr 2007 | A1 |
| 20080219584 | Mullen et al. | Sep 2008 | A1 |
| 20080296514 | Metzger et al. | Dec 2008 | A1 |
| 20080312533 | Balberg et al. | Dec 2008 | A1 |
| 20090066949 | Masumura | Mar 2009 | A1 |
| 20090069674 | Masumura et al. | Mar 2009 | A1 |
| 20090069676 | Nishihara | Mar 2009 | A1 |
| 20090069685 | Nishihara et al. | Mar 2009 | A1 |
| 20090069687 | Igarashi | Mar 2009 | A1 |
| 20090124902 | Herrmann | May 2009 | A1 |
| 20090171210 | Wang | Jul 2009 | A1 |
| 20090253989 | Caplan et al. | Oct 2009 | A1 |
| 20090264722 | Metzger et al. | Oct 2009 | A1 |
| 20100000330 | Rokni et al. | Jan 2010 | A1 |
| 20100069750 | Masumura | Mar 2010 | A1 |
| 20100070233 | Masumura | Mar 2010 | A1 |
| 20100073674 | Yoshida | Mar 2010 | A1 |
| 20100152559 | Cheng et al. | Jun 2010 | A1 |
| 20100152591 | Yu et al. | Jun 2010 | A1 |
| 20100285518 | Viator et al. | Nov 2010 | A1 |
| 20110071402 | Masumura | Mar 2011 | A1 |
| 20110101241 | Cottier et al. | May 2011 | A1 |
| 20110172513 | Nakajima et al. | Jul 2011 | A1 |
| 20110228097 | Motta | Sep 2011 | A1 |
| 20110237956 | Edwards et al. | Sep 2011 | A1 |
| 20110249912 | Shuster | Oct 2011 | A1 |
| 20120022381 | Tearney et al. | Jan 2012 | A1 |
| 20120070817 | Wang et al. | Mar 2012 | A1 |
| 20120127557 | Masumura | May 2012 | A1 |
| 20120275262 | Song et al. | Nov 2012 | A1 |
| 20140204389 | Mukoh | Jul 2014 | A1 |
| 20140218748 | Wax et al. | Aug 2014 | A1 |
| 20150238092 | Masumura | Aug 2015 | A1 |
| 20150245771 | Wang et al. | Sep 2015 | A1 |
| 20160058395 | Muser | Mar 2016 | A1 |
| 20160187533 | Maucec et al. | Jun 2016 | A1 |
| 20160235305 | Wang et al. | Aug 2016 | A1 |
| 20160249812 | Wang et al. | Sep 2016 | A1 |
| 20160299218 | Lehmann | Oct 2016 | A1 |
| 20160305914 | Wang et al. | Oct 2016 | A1 |
| 20170038000 | Fuchsle et al. | Feb 2017 | A1 |
| 20170038300 | Dake et al. | Feb 2017 | A1 |
| 20170038459 | Kubacki et al. | Feb 2017 | A1 |
| 20170065182 | Wang et al. | Mar 2017 | A1 |
| 20170090018 | Buettgen et al. | Mar 2017 | A1 |
| 20170105636 | Wang et al. | Apr 2017 | A1 |
| 20170122915 | Vogt et al. | May 2017 | A1 |
| Number | Date | Country |
|---|---|---|
| 2009305257 | May 2014 | AU |
| 102176859 | Jan 2014 | CN |
| 104107051 | Oct 2014 | CN |
| 104382558 | Mar 2015 | CN |
| 1 458 087 | Oct 2005 | EP |
| 1 771 844 | Apr 2007 | EP |
| 2016891 | Jan 2009 | EP |
| 2036487 | Mar 2009 | EP |
| 2036488 | Mar 2009 | EP |
| 2036490 | Mar 2009 | EP |
| 2163189 | Mar 2010 | EP |
| 1675501 | Sep 2013 | EP |
| 1771882 | Sep 2013 | EP |
| 2240798 | Aug 2016 | EP |
| 2016891 | Oct 2016 | EP |
| 2594959 | Jan 2017 | EP |
| 2815251 | Mar 2017 | EP |
| 2009501581 | Jan 2009 | JP |
| WO2005025399 | Mar 2005 | WO |
| WO2005025399 | May 2005 | WO |
| 2006025649 | Mar 2006 | WO |
| 2006093666 | Sep 2006 | WO |
| WO2007035934 | Mar 2007 | WO |
| WO2008040771 | Apr 2008 | WO |
| WO2008040771 | Aug 2008 | WO |
| WO2010043851 | Apr 2010 | WO |
| WO2012080837 | Jun 2012 | WO |
| WO2012080838 | Jun 2012 | WO |
| WO2014106823 | Jul 2014 | WO |
| WO2016138637 | Sep 2016 | WO |
| WO2016193554 | Dec 2016 | WO |
| Entry |
|---|
| Broussard GJ, Liang R, Tian L., Monitoring activity in neural circuits with genetically encoded indicators, Frontiers in molecular neuroscience, 2014;7. |
| Franceschini MA, Fantini S, Toronov V, Filiaci ME, Gratton E., “Cerebral hemodynamics measured by near-infrared spectroscopy at rest and during motor activation”. In Proceedings of the Optical Society of America in Vivo Optical Imaging Workshop 2000 (pp. 73-80), Optical Society of America. |
| Franceschini, MA and Boas, DA, “Noninvasive Measurement of Neuronal Activity with Near-Infrared Optical Imaging,” Neuroimage, vol. 21, No. 1, pp. 372-386 (Jan. 2004)). |
| Goense J, Merkle H, Logothetis NK, “High-resolution of fMRI reveals laminar differences in neurovascular coupling between positive and negative BOLD responses”. Neuron, Nov. 8, 2012; 76(3):629-39. |
| Gratton G, Fabiani M., “Fast optical imaging of human brain function”, Frontiers in human neuroscience, 2010;4. |
| Horinaka H, Osawa M. Hashimoto K, Wada K, Cho Y., “Extraction of quasi-straightforward-propagating photons from diffused light transmitting through a scattering medium by polarization modulation”. Optics Letters, Jul. 1, 1995; 20(13):1501-3. |
| Horstmeyer R., Ruan H, Yang C, “Guidestar-Assisted Wavefront-Shaping Methods for Focusing Light into Biological Tissue,” Nature Photonics, vol. 9, No. 9, pp. 563-571 (Sep. 1, 2015). |
| Laforest T, Verdant A, Dupret A, Gigan S., Ramaz F, Tessier G, “Co-Integration of a Smart CMOS Image Sensor and a Spatial Light Modulator for Real-Time Optical Phase Modulation,” Proc. Of SPIE-IS&T, vol. 2014, 9022:90220N-1 (Mar. 2014). |
| Leveque S, Boccara AC, Lebec M, Saint-Jalmes H, “Ultrasonic tagging of photon paths in scattering media: parallel speckle modulation processing”. Optics Letters, Feb. 1, 1999; 24(3):181-3. |
| Liu Y, Ma C, Shen Y, Wang LV, “Bit-Efficient, Sub-Millisecond Wavefront Measurement Using a Lock-In Camera for Time-Reversal Based Optical Focusing Inside Scattering Media,” Optics Letters, vol. 41, No. 7, pp. 1321-1324, Apr. 1, 2016. |
| Liu Y, Shen Y, Ma C, Shi J, Wang LV, “Lock-in Camera Based Heterodyne Holography for Ultrasound-Modulated Optical Tomography Inside Dynamic Scattering Media,” Applied Physics Letters, vol. 108, No. 23, 231106, Jun. 6, 2016. |
| Mahan GD, Engler WE, Tiemann JJ, Uzgiris E, “Ultrasonic Tagging of Light: Theory,” Proceedings of the National Academy of Sciences, vol. 95, No. 24, pp. 14015-14019, Nov. 24, 1998. |
| Patwardhan SV, Culver JP. Quantitative diffuse optical tomography for small animals using an ultrafast gated image intensifier. Journal of biomedical optics. Jan 1, 2008; 13(1):011009. |
| Powell S., Srridge SR, Leung TS, “Gradient-Based Quantitative Image Reconstruction in Ultrasound-Modulated Optical Tomography: First Harmonic Measurement Type in a Linearized Diffusion Formulation,” IEEE Transactions on Medical Imaging, vol. 35, No. 2, pp. 456-467 (Feb. 2016). |
| Qureshi MM, Brake J., Jeon HJ, Ruan H, Liu Y, Safi AM, Eom TJ, Yang C., Chung E, “In Vivo Study of Optical Speckle Decorrelation Time Across Depths in the Mouse Brain,” Biomedical Optics Express, vol. 8, No. 11, pp. 4855-4864 (Nov. 1, 2017). |
| Sakadzic S, Wang LV, “High-Resolution Ultrasound-Modulated Optical Tomography in Biological Tissues,” Optics Letters, vol. 29, No. 23, pp. 2770-2772, Dec. 1, 2004). |
| Schmitt, JM, Gandjbackhche, AH, Bonner RF, “Use of polarized light to discriminate short-part photons in a multiply scattering medium”. Applied Optics, Oct. 20, 1992; 31(30):6535-46. |
| Steinbrink J, Villringer A, Kempf F, Haux D. Boden S, Obrig H., “Illuminating the BOLD Signal: Combined fMRI-fNIRS Studies,” Magnetic Resonance Imaging, vol. 24, No. 4, pp. 495-505, May 31, 2006). |
| Van der Laan JD, Wright JB, Scrymgeour DA, Kemme SA, Dereniak EL, “Evolution of circular and linear polarization in scattering environments”, Optics Express, Dec. 14, 2015; 23(25):31874-88. |
| Wang YM, Judkewitz B, DiMarzio CA, Yang C., “Deep-Tissue Focal Fluorescence Imaging with Digitally Time-Reversed Ultrasound-Encoded Light,” Nature Communications, vol. 3, Article 928 (Jun. 16 2012). |
| Wang, RK, Jacques SL, Ma Z, Hurst S, Hanson SR, Gruber A, Three dimensional optical angiography. Optics Express, Apr. 2, 2007; 15(7):4083-97. |
| Xu X, Liu H., Wang LV, “Time-Reversed Ultrasonically Encoded Optical Focusing into Scattering Media,” Nature Photonics, vol. 5, No. 3, pp. 154-157 (Mar. 1, 2011). |
| Atlan, M. et al., Pulsed acousto-optic imaging in dynamic scattering media with heterodyne parallel speckle detection, Optics Letters, vol. 30, No. 11, Jun. 1, 2005, 1360-1362. |
| Choma, Michael A. et al., Instantaneous quadrature low-coherence interferometry with 3×3 fiber-optic couplers, Optic Letters, vol. 28, No. 22, Nov. 15, 2003, 2162-2164. |
| Hale, Thomas C. et al., Photorefractive optical lock-in vibration spectral measurement, Applied Optics, vol. 36, No. 31, Nov. 1, 1997, 8248-8258. |
| Khoury, Jehad et al., Photorefractive optical lock-in detector, Optics Letters, vol. 16, No. 18, Sep. 15, 1991, 1442-1444. |
| Li, Youzhi et al., Pulsed ultrasound-modulated optical tomography using spectral-hole burning as a narrowband spectral filter, Applied Physics Letter, 93, 011111 (2008). |
| Liu, Yan et al., Bit-efficient, sub-millisecond wavefront measurement using a lock-in camera for time-reversal based optical focusing inside scattering media, Opt. Lett. Apr. 1, 2016; 41(7): 1321-1324. |
| Liu, Yan et al., Lock-in camera based heterodyne holography for ultrasound-modulated optical tomography inside dynamic scattering media, Appl. Phys. Lett. 108, 231106 (2016). |
| Mao, Shu et al., Optical Lock-In Detection of FRET Using Synthetic and Genetically Encoded Optical Switches, Biophysical Journal, vol. 94, Jun. 2008, 4515-4524. |
| Marriott, Gerard et al., Optical lock-in detection imaging microscopy for contrast-enhanced imaging in living cells, PNAS, Nov. 18, 2008, vol. 105, No. 46, 17789-17794. |
| Ruan, Haowen et al., Pulsed ultrasound modulated optical tomography with harmonic lock-in holography detection, J. Opt. Soc. Am. A, vol. 30, No. 7, Jul. 2013, 1409-1416. |
| Strauss, Charlie E.M. et al., Synthetic-array heterodyne detection: a single-element detector acts as an array, Oct. 15, 1994, vol. 19, No. 20, Optics Letters, 1609-1611. |
| Tucker-Schwartz, Jason M. et al., Photothermal optical lock-in optical coherence tomography for in vivo imaging, Jun. 1, 2015, vol. 6, No. 6, DOI:10.1364/BOE.6.002268, Biomedical Optics Express, 2268-2282. |
| Yaqoob, Zahid et al., Harmonically-related diffraction gratings-based interferometer for quadrature phase measurements, Sep. 4, 2006, vol. 14, No. 18, Optics Express, 8127-8137. |
| Gratton, Gabriele et al., Dynamic brain imaging: Event-related optical signal (EROS) measures of the time course and localization of cognitive-related activity, Psychonomic Bulletin & Review, 1998, 5 (4), 535-563. |
| Matthews, Thomas E. et al., Deep tissue imaging using spectroscopic analysis of multiply scattered light, Optica, vol. 1, No. 2, Aug. 2014, 105-111. |
| Giacomelli, Michael G. et al., Imaging beyond the ballistic limit in coherence imaging using multiply scattered light, Optics Express, Feb. 28, 2011, vol. 19, No. 5, 4268-4279. |
| Puszka, Agathe et al., Time-resolved diffuse optical tomography using fast-gated single-photon avalanche diodes, Aug. 1, 2013, vol. 4, No. 8, DOI:10.1364/BOE.4.001351, Biomedical Optics Express, 1351-1365. |
| Singh M. et al., Assessment of ultrasound modulation of near infrared light on the quantification of scattering coefficient, Medical Physics, vol. 37, No. 7, Jun. 28, 2010, 3744-3751. |
| D.S. Elson, . et al., Ultrasound-mediated optical tomography: a review of current methods, Interface Focus, vol. 1, No. 4, Jun. 2, 2011, 632-648. |
| Number | Date | Country | |
|---|---|---|---|
| 20190150743 A1 | May 2019 | US |
| Number | Date | Country | |
|---|---|---|---|
| 62590150 | Nov 2017 | US | |
| 62596446 | Dec 2017 | US |
