For many decades, the reference method for the diagnosis of cancer has been histopathological examination of tissues using conventional microscopy. This process is known as Surgical Pathology. In Surgical Pathology, samples can be produced from surgical procedures (tumor resection), diagnostic biopsies or autopsies. These samples go through a process that includes dissection, fixation, and cutting of tissue into precisely thin slices which are stained for contrast and mounted onto glass slides. The slides are examined by a pathologist under a microscope, and their interpretations of the tissue results in the pathology “read” of the sample.
Advanced optical and electromagnetic (“EM”) imaging approaches have been reported for the determination of tumor margin: These include the use of Fluorescence Imaging [1], Near Infrared spectroscopy [2,3], Raman Spectroscopy [4, 5], and Terahertz reflectivity [6].
Raman spectrum comprises three primary regions of interest: a) the fingerprint region (“FP”) region having wavenumbers typically in the range of about 400 cm−1 to about 1800 cm−1; b) the silent region having wavenumbers typically in the range of about 1800 cm−1 to about 2800 cm−1; and c) the high wavenumber region (“HWN”) region having wavenumbers typically in the range of about 2800 cm−1 to about 3800 cm−1. The FP region typically comprises a series of multiple peaks and is rich in Raman spectral information. In the case of biological samples, the fingerprint region contains information on the content of biomolecular components, such as DNA, proteins, phospholipids, lipids, and the like. Most of the research efforts have only used the FP region for detection of cancerous tissue [7] and the HWN region has largely been underexplored. The relatively underappreciated HWN region typically includes a composite broad spectral shape that includes several underlying peaks associated with the biomolecular content. Recent work in the HWN range has demonstrated successful classification of cancerous tissue versus normal tissue with high sensitivity and specificity [8-10]. The HWN Raman spectral range features reduced unwanted fluorescence and is unaffected by glass as well as tissue marking dye Raman spectra. In addition, it has been shown that combining information from the FP and HWN regions can lead to enhanced performance for some applications [11, 12].
To date, measurement of these specific wavenumber characteristics typically requires a “conventional spectrometer” based system. These systems are often complex and expensive. The present disclosure provides an improved alternative to prior art systems.
According to an aspect of the present disclosure, a system for analyzing a sample material using Raman spectral light is provided. The system includes at least one light source, at least one light detector, at least on narrow band pass filter, and an analyzer. The at least one light source is configured to produce excitation light at one or more wavelengths. The system is configured such that excitation light produced by the light source is directed to the sample material to interrogate the sample material, and the at least one narrow band pass filter is positioned to receive Raman scattered light produced as a result of the excitation light interrogation, and the at least one detector is positioned to receive the Raman scattered light that has passed through the at least one narrow band pass filter. The analyzer is in communication with the light source and the at least one light detector and a memory storing instructions. The instructions when executed cause the processor to a) control the light source to produce excitation light at the one or more wavelengths; and b) process signals produced by the light detector to analyze the sample material, the signals representative of the intensity of the Raman scattered light received by the at least one light detector corresponding to one or more wavenumbers in a high wavenumber region of a Raman spectrum.
In any of the aspects or embodiments described above and herein, the at least one light detector may include “N” number of the light detectors, where “N” is an integer equal to or greater than two, and the at least one narrow band pass filter may include “N” number of the narrow band pass filters, and the system may include an “N” way optical splitter device configured to split the received Raman scattered light into “N” paths. The system may be configured such that the optical splitter device is positioned to receive the Raman scattered light and is configured to split the received Raman scattered light into “N” paths, and a respective one of the “N” number of said light detectors and a respective one of the “N” number of said narrow band pass detectors is positioned in a respective one of the “N” paths. The system may be configured such that the split amount of Raman scattered light in each respective path passes through the respective said narrow band pass filter and is received by the respective said light detector.
In any of the aspects or embodiments described above and herein, “N” may equal four.
In any of the aspects or embodiments described above and herein, the system may further include a wavelength controller configured to tune an output of the light source relative to a single said excitation wavelength.
In any of the aspects or embodiments described above and herein, each of the “N” number of narrow band pass filters may be centered on a respective one of the wavenumbers, and the respective one of the wavenumbers of each narrow band pass filter is different than the respective one of wavenumbers of the other narrow band pass filters.
In any of the aspects or embodiments described above and herein, the instructions when executed may cause the processor to process the signals produced by each light detector to produce one or more ratios of the signals representative of the intensity of the Raman scattered light at different respective one of the wavenumbers.
In any of the aspects or embodiments described above and herein, the narrow band pass filters may be configured to have a band pass range of wavelengths that corresponds to a range of 100 cm−1 to 5 cm−1 of said wavenumbers.
In any of the aspects or embodiments described above and herein, the sample material may be a biological tissue sample.
In any of the aspects or embodiments described above and herein, the system may include a wavelength controller configured to selectively cause the light source to produce a plurality of said excitation wavelengths.
In any of the aspects or embodiments described above and herein, the wavelength controller may be in communication with the analyzer, and the instructions when executed may cause the processor to control the wavelength controller to sweep through the plurality of excitation wavelengths.
In any of the aspects or embodiments described above and herein, the at least one light source may include “N” number of light sources where “N” is an integer equal to or greater than two, each light source configured to produce excitation light at a single wavelength, and the single wavelength of excitation light for each light source is different than the single wavelength of excitation light produced by the others of the light sources, and the system may further include an optical switch configured to selectively cause the excitation light from one of the light sources to be passed to the sample material, and a demultiplexer disposed to receive and configured to demultiplex said signals produced by the light detector.
In any of the aspects or embodiments described above and herein, the at least one light source includes “N” number of light sources where “N” is an integer equal to or greater than two, each light source configured to produce excitation light at a single wavelength, and the single wavelength of excitation light for each light source is different than the single wavelength of excitation light produced by the others of the light sources, and the system further may further include an optical combiner configured to combine the excitation light from all of the light sources to form a combined beam of excitation light, and a demultiplexer disposed to receive and configured to demultiplex said signals produced by the light detector.
In any of the aspects or embodiments described above and herein, each light source may be driven by a discrete frequency, and the discrete frequency used to drive each respective light source is different than the discrete frequency used to drive the other respective light sources, and the demultiplexer may be configured to demultiplex the signals produced by the light detector using synchronous detection at each respective discrete frequency.
In any of the aspects or embodiments described above and herein, each light source may be driven by a digital code, and the digital code used to drive each respective light source is different than the digital code used to drive the other respective light sources, and the demultiplexer is configured to demultiplex said signals produced by the light detector using synchronous detection at each respective digital code.
In any of the aspects or embodiments described above and herein, the at least one narrow band pass filter may be tunable and in communication with the analyzer, and the instructions when executed cause the processor to control tunable narrow band pass filter.
In any of the aspects or embodiments described above and herein, the system may include a probe configured to include one or more light conduits for passage of excitation light to the sample material, and for passage of Raman scattered light collected at the sample material.
According to another aspect of the present disclosure, a method for analyzing a sample material using Raman spectral light is provided. The method includes a) interrogating a sample material with excitation light at one or more wavelengths, the excitation light produced by at least one light source; b) filtering Raman scattered light produced by the interrogation using at least one narrow band pass filter; c) detecting the Raman scattering light after said Raman scattering light has passed through the narrow band pass filter using at least one light detector, and producing signals representative of an intensity of the detected Raman scattering light using the at least one detector; and d) processing the signals to analyze the sample material, said processing using the detected intensity of the Raman scattering light at one or more wavenumbers in a high wavenumber region of a Raman spectrum.
In any of the aspects or embodiments described above and herein, the excitation light may be produced by one light source, and the at least one narrow band pass filter may include “N” number of narrow band pass filters, wherein “N” is an integer equal to or greater than two, and the at least one light detector may include “N” number of light detectors, and the method may further include the step of splitting the Raman scattered light produced by the interrogation into “N” paths, and the filtering step may include filtering the split Raman scattered light in each of the “N” paths using a respective one of the narrow band pass filters, and the detecting step may include detecting the split Raman scattered light in each of the “N” paths using a respective one of the light detectors.
In any of the aspects or embodiments described above and herein, the method may further include tuning an output of the light source relative to a single excitation wavelength using a wavelength controller.
In any of the aspects or embodiments described above and herein, each of the “N” number of narrow band pass filters may be centered on a respective one of the wavenumbers, and the respective one of the wavenumbers of each narrow band pass filter is different than the respective one of the wavenumbers of the other narrow band pass filters.
In any of the aspects or embodiments described above and herein, the processing step may include producing one or more ratios of the signals representative of the intensity of the Raman scattered light at different respective one of the wavenumbers.
In any of the aspects or embodiments described above and herein, the step of interrogating the sample material with excitation light may include interrogating the sample material at a plurality of wavelengths of excitation light produced by a single light source.
In any of the aspects or embodiments described above and herein, the step of interrogating the sample material may include sweeping through the plurality of excitation wavelengths.
In any of the aspects or embodiments described above and herein, the step of interrogating the sample material with excitation light at one or more wavelengths produced by at least one light source, may include interrogating the sample material with excitation light at “N” wavelengths, where “N” is an integer equal to or greater than two, using “N” number of light sources, wherein each of the “N” wavelengths is different than the other of the “N” wavelengths, and the method may further include switching the excitation light passed to the sample material between said “N” light sources, and demultiplexing the signals produced by the light detector.
In any of the aspects or embodiments described above and herein, the step of interrogating the sample material with excitation light at one or more wavelengths produced by at least one light source, may include interrogating the sample material with excitation light at “N” wavelengths, where “N” is an integer equal to or greater than two, using “N” number of light sources, wherein each of the “N” wavelengths is different than the other of the “N” wavelengths, and the method may further include combining the excitation light from all of the light sources to form a combined beam of excitation light, and demultiplexing the signals produced by the light detector.
In any of the aspects or embodiments described above and herein, each light source may be driven by a discrete frequency, and the discrete frequency used to drive each respective light source may be different than the discrete frequency used to drive the other respective light sources, and the step of demultiplexing may use synchronous detection at each respective discrete frequency.
In any of the aspects or embodiments described above and herein, each light source may be driven by a digital code, and the digital code used to drive each respective light source may be different than the digital code used to drive the other respective light sources, and the step of demultiplexing may use synchronous detection at each respective digital code.
In any of the aspects or embodiments described above and herein, the at least one light source may be a tunable narrow band pass filter in communication with the analyzer, and the method may further include tuning the tunable narrow band pass filter.
The foregoing features and elements may be combined in various combinations without exclusivity, unless expressly indicated otherwise. These features and elements as well as the operation thereof will become more apparent in light of the following description and the accompanying drawings. It should be understood, however, the following description and drawings are intended to be exemplary in nature and non-limiting.
Experimental data has indicated ratios of intensity measurements at predetermined wavenumber values can be used to form a “barcoding” approach for identifying the HWN profile shape of a material, which in turn can be used to classifying the material. For example, we have discovered that wavenumbers 2851 cm−1, 2892 cm−1, 2938 cm−1, and 3008 cm−1 can be used to produce six (6) different intensity measurement ratios (e.g., 2851/2892; 2851/2938; 2851/3008; 2892/2938; 2892/3008; and 2938/3008) [13]. An intensity measurement at a wavenumber value of about 2851 cm−1 is understood to reflect C—H vibrations of CH2 and is further understood to be primarily attributable to the tissue lipid content. An intensity measurement at a wavenumber value of about 2938 cm−1 is understood to reflect C—H vibrations of the CH3 group and are further understood to be primarily attributable to the tissue protein content. An intensity measurement at a wavenumber value of about 2892 cm−1 is understood to reflect a CH2 asymmetric stretch of both proteins and lipids within the tissue. An intensity measurement at a wavenumber value of about 3008 cm−1 is understood to reflect the ═C—H vibration associated with lipids and fatty acids that may be present within the tissue. Ratiometric values as described above can be used to create an identifier (i.e., a “barcode”) that can be used to identify an HWN profile shape and to classify a tissue type. This ratiometric aspect of the present disclosure also produces useful parameter values representative of relative tissue constituent contents (e.g., the tissue protein content relative to the tissue lipid content, etc.) and is useful to mitigate variances that may occur (e.g., variances in base line intensity, etc.). Hence, the ratiometric parameters utilized within the present disclosure facilitate tissue type classification. It should be noted that the aforesaid wavenumber values represent examples of wavenumber values that may have significance in certain tissue analysis applications. Other wavenumber values may have significance in alternative tissue analysis applications. Furthermore, the specific wavenumber values provided above represent a wavenumber associated with a HWN peak. These aforesaid wavenumber positions identified in
Aspects of the present disclosure include a system 20 and method for analyzing a biological sample and other materials. To facilitate the description herein, the present disclosure is described in the context of a biological sample. However, as stated above embodiments of the present disclosure system 20 and methods described herein may be used to non-invasively examine a variety of materials. The system 20 includes at least one light source, at least one light detector, at least one narrow passband filter, and an analyzer. Non-limiting exemplary embodiments of the present disclosure system 20 are described herein in greater detail. Unless otherwise indicated, the one or more light sources, the at least one light detector, and analyzer described below may be used in each of the example present disclosure system embodiments described herein.
The one or more light sources are configured to emit coherent light at wavelengths that are useful in Raman spectroscopy. An example of an acceptable coherent light source is a laser. The present disclosure is not limited to using any particular type of laser, or lasers at all. Examples of laser types that may be used include solid state, gas, diode laser or vertical-cavity surface-emitting lasers (VCSELs). The light source is not limited to coherent light at any particular wavelength or wavelength band, but as indicated above coherent light at wavelengths that are useful in Raman spectroscopy are preferred. The operation of the one or more light sources may be controlled by the analyzer.
The at least one light detector is configured to receive Raman scattered light from the interrogated tissue and produce signals representative thereof. The light detector is in signal communication with the analyzer to permit the transfer of signals produced by the light detector to the analyzer. The light detector may be configured to detect Raman scattered light within an acceptable range of wavelengths and intensities for the purposes described herein. The light detector may be chosen to provide optimal performance at one or more wavelengths of light, and at low light intensity levels. Non-limiting examples of light detectors include light detectors that convert light energy into an electrical signal such as a simple photodiode. A specific non-limiting example of a light detector that may be used is an avalanche photodiode. The present disclosure is not limited to any particular type of light detector. In some embodiments, the light intensity sensed by a light detector may be integrated for a time duration “T” to increase the effective signal to noise ratio (SNR).
As will be described herein, embodiments of the present disclosure may include optical elements such as lenses, filters, dichroic mirrors, and the like for processing the excitation light and Raman scattered light. Optical elements such as photonic filters may be used to permit passage of Raman light within one or more defined bandwidths, or to limit optical interference from non-Raman scattered light, or to block excitation light, or any combination thereof from the detection path. The present disclosure is not limited to any particular type of photonic filter and may use more than one type of photonic filter. Non-limiting examples of acceptable photonic tunable filters include colloidal crystal arrays, liquid crystals, acousto-optic tunable filters (AOTF), Fabry Perot, electro-optic, and the like. In some embodiments of the present disclosure, one or more narrow band pass filters may be included that are individually configured to attenuate the received Raman scattered light outside of a predetermined narrow range. In most present disclosure embodiments, the narrow band pass filters are configured to have a band pass range of wavelengths that correspond to a range of 100 cm−1 to 5 cm−1 wavenumbers. More typically, present disclosure narrow band pass filters are configured to have a band pass range of wavelengths that correspond to a range of 80 cm−1 to 20 cm−1 wavenumbers.
The analyzer is in communication with other components within the system 20, such as the one or more light sources, the at least one light detector, and the like to control and or receive signals therefrom to perform the functions described herein. The analyzer may include any type of computing device, computational circuit, processor(s), CPU, computer, or the like capable of executing a series of instructions that are stored in memory. The instructions may include an operating system, and/or executable software modules such as program files, system data, buffers, drivers, utilities, and the like. The executable instructions may apply to any functionality described herein to enable the system to accomplish the same algorithmically and/or coordination of system components. The analyzer may include one or more memory devices and is not limited to any particular type of memory device. The memory device may include read-only memory, random access memory, volatile memory, non-volatile memory, static memory, dynamic memory, flash memory, cache memory, and/or any device that stores digital information. The analyzer may include, or may be in communication with, an input device that enables a user to enter data and/or instructions, and may include, or be in communication with, an output device configured, for example to display information (e.g., a visual display or a printer), or to transfer data, etc. Communications between the analyzer and other system components may be via a hardwire connection or via a wireless connection.
An embodiment of a present disclosure system 20 that utilizes a form of hyperspectral detection is diagrammatically shown in
In the operation of a system embodiment as shown in
An embodiment of a present disclosure system 20 that utilizes a form of hyperspectral detection is diagrammatically shown in
In the operation of a system embodiment as shown in
Another embodiment of a present disclosure system 20 that utilizes a form of hyperspectral detection is diagrammatically shown in
In the operation of a system embodiment as shown in
Another embodiment of a present disclosure system 20 that utilizes a form of hyperspectral detection is diagrammatically shown in
In the operation of a system embodiment as shown in
Another embodiment of a present disclosure system 20 that utilizes a form of hyperspectral detection is diagrammatically shown in
In the operation of a system embodiment as shown in
As indicated above, the present disclosure is described above primarily in the context of a system 20 and method for examining a biological sample; e.g., a breast tissue sample. Embodiments of the present disclosure are not, however, limited to examining biological samples. The present disclosure system 20 and methods described above may be used to non-invasively examine a variety of materials (e.g., pharmaceutical products, chemical products, food products, etc.) Hence, in applications for analysis of materials (regardless of the material type), the HWN profiles may represent constituents normally present within the material under analysis.
As is clear from the description above, the present disclosure provides a system and methodology for analyzing materials (e.g., classification of tissue types) that obviates the need for a spectrometer. The present disclosure leverages the Raman HWN spectral range using one or more narrow band pass filters to “sample” the HWN profile of the material being analyzed at meaningful points on the HWN profile. As described above, the present disclosure permits sample analysis using determined Raman scattered light intensity values, or ratiometric values based on those intensity values, or some combination thereof. The analysis (e.g., classification) of the sample may utilize an empirical database within a comparative analysis, or an algorithmic/multiparametric approach into which identifying information (e.g., intensity values and/or ratiometric values) may be utilized, or a trained classifier that permits evaluation using a plurality of data sets, or the like. In addition, while spontaneous Raman spectra have been used in the present disclosure (e.g.,
Aspects of the present disclosure are described herein in terms of system embodiments. The system embodiments are described and shown diagrammatically. The present disclosure system embodiments may be configured to analyze ex-vivo samples, or in the case of biospecimen applications the system embodiments may be configured to permit in-vivo analyses. For example, the aforesaid systems may be configured as a probe (e.g., the entirety of the system is configured as a probe) or may be configured to include a probe that can be used for in-vivo sample interrogation. The probe may be configured to deliver the excitation light and to collect the Raman scattering light.
While the principles of the disclosure have been described above in connection with specific apparatuses and methods, it is to be clearly understood that this description is made only by way of example and not as limitation on the scope of the disclosure. Specific details are given in the above description to provide a thorough understanding of the embodiments. However, it is understood that the embodiments may be practiced without these specific details. For example, the system embodiment examples provided herein are non-limiting examples of the present disclosure system. Each of the exemplary systems are described as including certain optical elements (e.g., filters, etc.). The disclosure of these optical elements within the respective exemplary system embodiments should not be construed as these optical elements being required. In alternative embodiments, some described optical elements may be omitted or exchanged with different optical elements that provide the same similar functionality, and additional optical elements may be included.
The singular forms “a,” “an,” and “the” refer to one or more than one, unless the context clearly dictates otherwise. For example, the term “comprising a specimen” includes single or plural specimens and is considered equivalent to the phrase “comprising at least one specimen.” The term “or” refers to a single element of stated alternative elements or a combination of two or more elements unless the context clearly indicates otherwise. As used herein, “comprises” means “includes.” Thus, “comprising A or B,” means “including A or B, or A and B,” without excluding additional elements.
It is noted that various connections are set forth between elements in the present description and drawings (the contents of which are included in this disclosure by way of reference). It is noted that these connections are general and, unless specified otherwise, may be direct or indirect and that this specification is not intended to be limiting in this respect. Any reference to attached, fixed, connected or the like may include permanent, removable, temporary, partial, full and/or any other possible attachment option.
No element, component, or method step in the present disclosure is intended to be dedicated to the public regardless of whether the element, component, or method step is explicitly recited in the claims. No claim element herein is to be construed under the provisions of 35 U.S.C. 112(f) unless the element is expressly recited using the phrase “means for.” As used herein, the terms “comprises”, “comprising”, or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Additionally, even though some features, concepts, or aspects of the disclosures may be described herein as being a preferred arrangement or method, such description is not intended to suggest that such feature is required or necessary unless expressly so stated. Still further, exemplary, or representative values and ranges may be included to assist in understanding the present application, however, such values and ranges are not to be construed in a limiting sense and are intended to be critical values or ranges only if so expressly stated.
This application claims priority to U.S. Patent Appln. No. 63/055,987 filed Jul. 24, 2020, which is hereby incorporated by reference in its entirety.
Filing Document | Filing Date | Country | Kind |
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PCT/US2021/043196 | 7/26/2021 | WO |
Number | Date | Country | |
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63055987 | Jul 2020 | US |