Patent Application
20150141768
Generally, the present invention relates to fiber-optic sensors for quantitative optical spectroscopy. In particular, the present invention is directed to a smart fiber-optic sensor system for optical spectroscopy of biological tissue, for use in robot-assisted laparoscopic (RAL) procedures. Particularly, the present invention is directed to a smart fiber-optic sensor system for RAL procedures, which includes a temperature sensor to prevent charring and collateral damage to the biological tissue being treated by laparoscopic electrosurgical devices.
Robot-assisted laparoscopy (RAL) is an emerging, minimally-invasive surgical (MIS) technique that combines the advantages of both laparoscopy and robotic surgery. In addition, RAL systems, such as the da Vinci Surgical System®, represent the latest innovations in the field of MIS technology. Thus, because of the desirable benefits of MIS to the patient, such as reduced trauma to the surgical site and reduced post-operative recovery time, the number of laparoscopic and robot-assisted surgeries performed annually continues to increase, as highly invasive or “open” surgical procedures are converted to MIS procedures.
Robot-assisted laparoscopy (RAL) combines the benefits of minimal invasiveness provided by laparoscopic techniques with the features of robotic surgery, which includes providing multiple degrees of motion at the robotic end-effector that carries the surgical cutting instrument; providing 3-dimensional views, decreasing the fatigue and tension tremor of the surgeon when controlling the laparoscopic instrument; and providing improved dexterity and precision when executing the surgical procedure. Although RAL has only recently been adopted in the field of surgery, it has been increasingly adopted for use in the fields of gynecologic oncology, urology, cardiac surgery, liver resection, pancreatic surgery, prostatectomy, and general surgery.
Despite improvements over the years, clinically relevant problems still exist with laparoscopic electrosurgical tissue dissection or cutting devices, such as those used by RAL systems. For example, surgeons are often unable to prevent collateral damage to tissue at or near the surgical site due to heat that is generated by the uncontrolled spread of energy from the flow of electrical current that is delivered to the surgical site by the electrosurgical device used to perform robot-assisted laparoscopic (RAL) procedures. In particular, the heat energy that is generated from the electrosurgical cutting instrument generally results in the overheating, charring, and tearing of the tissue near or proximate to the surgical site, which can complicate the surgical procedure and lengthen patient recovery time. Furthermore, due to the nature of laparoscopic procedures, such as robot-assisted laparoscopic procedures, the field of view provided to a surgeon when completing the procedure is small, and as a result, tissue burns typically go unnoticed when they occur. The effects of these unnoticed burns may remain latent, such that the impact on the health of the patient is not realized until after the operation is complete, at which time diagnosis becomes more difficult. Moreover, it is estimated that patients have been burned over 230,000 times every year due to the use of electrosurgical equipment during laparoscopic procedures, while complications during electrosurgery on the small and large intestine, bile duct and during the performance of hysterectomies have been reported at clinically relevant rates. Injuries to ovaries have also been documented during electrosurgical treatment of polycystic ovary syndrome.
Furthermore, surgeons have requested that robot-assisted laparoscopic (RAL) systems provide additional information regarding real-time tissue diagnosis, which can assist the surgeon in deciding what and where to cut during surgery. In response, numerous imaging techniques, such as MRI, fluorescence, confocal microscopy and optical coherence tomography, have been applied to assist surgeons during a robot-assisted surgical procedure to visualize blood vessels, tumors and nerves. Among these imaging modalities, fluorescence imaging has been pursued for incorporation into various commercial systems, such as the da Vinci® surgical system. However, such imaging methods are generally limited to providing high-resolution structural information, but little diagnostic information regarding the physiology of the tissue being investigated or treated. Furthermore, few attempts have been made to obtain quantitative information about the characteristics and physiology of biological tissue, as well as biological tumor tissue that is manipulated or treated by a robot-assisted laparoscopy (RAL) surgical system.
Optical spectroscopy, such as fiber-optic-based diffuse reflectance spectroscopy (DRS), is a nondestructive and noninvasive technique that provides quantitative information of biological tissue in-vivo, using the optical properties of the tissue, such as wavelength-dependent light absorption and light-scattering properties of the tissue. That is, DRS provides various information regarding the biological tissue based on the light absorption and light scattering properties imparted by the tissue. For example, light scattering in biological tissue is affected by the local inhomogeneities in the refractive index of the tissue, whereby such inhomogeneities include cellular organelles of the tissue and the extracellular matrix of the tissue. Such inhomogeneities, which cause light scattering in biological tissue, have been found to change with carcinogenesis and tumor necrosis. The amount of light absorption of biological tissue is primarily the result of hemoglobin concentrations, which allows for quantitative characterization of tissue perfusion and oxygenation (SO2). As such, quantitative DRS has recently been used for pre-cancer detection and cancer diagnostics, intra-operative tumor margin assessment, monitoring of tumor response to therapy, and tissue oximetry, as well as surgical guidance. Thus, it would be desirable to have a robotic fiber-optic instrument (RFOI) device that utilizes DRS to provide real-time tissue diagnosis to facilitate surgeons in deciding what to cut (e.g. malignant vs. normal/benign tissue) and where to cut, so as to reduce undesired tissue damages during a robot-assisted laparoscopic (RAL) procedure.
Therefore, there is a need for a smart fiber-optic sensor system that provides quantitative optical spectroscopy for robot-assisted laparoscopic (RAL) surgical systems in accordance with the concepts of the present invention. In addition, there is a need for a smart fiber-optic sensor system for robot-assisted laparoscopic (RAL) surgical systems that includes an interferometric temperature carried by a robotic end-effector to identify the temperature of the tissue being treated during laparoscopic procedures to prevent tissue damage. There is also a need for a smart fiber-optic sensor system that integrates a diffuse reflectance spectroscopy (DRS) channel, a self-calibration channel, a fiber-optic pressure, and a temperature sensor into a single probe or instrument for use in a robot-assisted laparoscopic system to provide quantitative tissue characteristics, diagnosis and temperature of the tissue in real time during the laparoscopic procedure. In addition, there is a need for a smart fiber-optic sensor system that carries out robot-assisted laparoscopy (RAL) procedures with a reduced amount of tissue damage in the form of burning and charring, so as to reduce the overall cost of the surgical procedure and patient recovery time, while lessening the risk the surgeon assumes in performing such procedures.
In light of the foregoing, it is a first aspect of the present invention to provide a smart fiber optic sensor comprising a sensing channel for illuminating a specimen and for collecting spectral reflections from the specimen from which specimen spectral data can be determined; a pressure sensing channel for collecting pressure sensor spectral reflections from which a contact pressure can be determined; a temperature sensing channel for collecting temperature sensor spectral reflections from which a temperature of the specimen can be determined; and a calibration channel for obtaining calibration spectral reflections usable for correcting the specimen spectral data.
A further aspect of the present invention is to provide a method for utilizing a smart fiber optic sensor for measuring a specimen, the method comprising contacting the specimen with the smart fiber optic sensor; generating, using the smart fiber optic sensor, specimen spectral data, pressure sensor spectral data, temperature sensor spectral data and calibration spectral data; calculating a contact pressure at an interface of the smart fiber optic sensor and the specimen using the pressure sensor spectral data; calculating a temperature at the interface using the temperature sensor spectral data; and correcting specimen spectral data using the calibration spectral data.
The subject matter described herein comprises smart fiber-optic sensors, systems, and methods for quantitative tissue optical spectroscopy for robot-assisted surgical systems. In one embodiment, the system can include a smart fiber-optic sensor comprising a specimen sensing channel, a self-calibrating channel, a pressure-sensing channel, and a temperature-sensing channel, which operate concurrently and in real time to prevent heat-related damage to the target tissue during a robot-assisted laparoscopic (RAL) procedure.
These and other features and advantages of the present invention will become better understood with regard to the following description, appended claims, and accompanying drawings wherein:
A smart fiber-optic sensor system for use with robotic surgical systems, such as robot-assisted laparoscopy (RAL) systems is generally referred to by numeral 100, as shown in
As shown in
A first fiber-optic channel 110 comprises a diffuse reflectance spectroscopy (DRS) sensing channel 110 that includes a first light source 106 and a first spectrometer channel A, designated 104. A second fiber-optic channel 120 comprises a self-calibration channel 120, wherein the illumination source comprises the first light source 106 and a second spectrometer channel C, designated 108. Thus, both the DRS-sensing channel 110 and the self-calibration channel 120 are configured to share the first light source 106. Optionally, the self-calibration channel 120 may utilize the same spectrometer and/or spectrometer channel as either of the sensing channel 110 or a fiber-optic pressure sensor channel to be discussed.
A third fiber-optic channel 130 comprises a fiber-optic pressure sensor channel 130, which includes a second light source 115 and a third spectrometer channel B, designated 112.
A fourth fiber-optic channel 131 comprises a fiber-optic temperature sensor channel 131, which includes the second light source 115 and a fourth spectrometer channel D, designated 132. In one aspect, the temperature-sensing channel 131 may comprise an interferometric temperature sensor, which is able to provide real-time temperature data at the probe-specimen interface, in a manner to be discussed.
As such, the reflectance and/or fluorescence spectrum from the specimen of target biological tissue, designated as 146, can be detected by the first spectrometer channel A 104; the calibration spectrum can be detected by the second spectrometer channel C 108; the spectrum from a pressure sensor can be detected by the third spectrometer channel B 112; and the spectrum from the temperature sensor can be detected by the fourth spectrometer channel D 132.
In an alternative embodiment, three separate spectrometers may be used and shared among the fiber-optic channels rather than using a four-channel spectrometer. In another alternative embodiment, a dual-channel spectrometer may be used instead of a three-channel spectrometer, whereby each spectrometer comprises a dual-channel fiber-optic spectrometer, such as those manufactured by Avantes BV, wherein one channel could detect DRS from the sensing channel, and the second spectrometer channel is shared by each of the calibration channel 120, the pressure-sensing channel 130, and the temperature-sensing channel 131. That is, the second channel of a dual-channel spectrometer could detect the signals from the calibration channel, the pressure sensor, and the temperature sensor. In one embodiment the spectrometers may comprise a white light emitting diode (LED) based miniature spectrometer comprising a high-power, white LED and a USB 4000 spectrometer, such as those manufactured by Ocean Optics of Orlando, Fla., in one aspect, the spectrometers may comprise a 1-mm optical fiber for illumination and another 1-mm optical fiber for collection with a source-to-detector separation (SDS) of 2.3 mm.
The fiber-optic pressure sensor channel 130 may comprise an interferometric pressure sensor, which may provide real-time pressure data at the interface of the probe tip 144 and the specimen 148, such that an operator or technician can manually control the pressure applied by the tip 144 of the robotic surgical system at the interface within an optimal minimal range. It should be appreciated that the robotic surgical system may be configured to take corrective action automatically based on the pressure detected by the pressure sensor channel 130. This ensures optimal specimen coupling between the probe tip 144 and the specimen 146, so that the surgical robot does not apply unnecessary levels of pressure on the sensor tip 144 that could affect the physiology of the biological tissue specimen 146.
In another embodiment, the fiber-optic temperature sensor channel 131 may comprise an interferometric temperature sensor, which provides real-time temperature data at the interface of the probe tip 144 and the tissue specimen 146. As a result, the operator of the robot-assisted surgical system can identify the temperature of the tissue specimen 146, so that an operator of the robotic surgical system can control the electrosurgical device (or through automated corrective action at the robotic surgical system), such as an ultrasound device, used during the laparoscopic surgical procedure in a manner to prevent burning and charring of the tissue.
Thus, the smart fiber-optic sensor or probe 105 may be configured to integrate or combine the DRS-sensing channel 110, the calibration channel 120, the interferometric pressure-sensing channel 130, and/or the interferometric temperature-sensing channel 132 into a single optical probe. Furthermore, the smart fiber-optic sensor 105 may be configured for use in connection with any probe instrument, including but not limited to, side-firing and forward-firing probes.
It should also be appreciated that the smart fiber-optic sensor 105 is configured to be utilized with a robotic surgical system 147, shown in
With regard to the DRS-sensing channel 110, it may comprise a detection fiber portion, or collection leg 124, which is coupled to the first spectrometer 104 at coupler 114. The DRS-sensing channel 110 may also comprise an illumination fiber leg 126 that is coupled to the first light source 108 at coupler 116 for collecting DRS data from the biological tissue specimen 146, such as an in-vivo tissue specimen, for example.
In one embodiment, the first light source 106 may comprise a white light source, which uses white light emitting diodes (LEDs), such as white LEDs, LE-1x-c manufactured by WT&T Inc., for example. The light source 106 may also generate light having a wavelength, which is in the range of about 400 to 700 nm, which serves as the light source for the DRS-sensing channel 110. In one embodiment, the DRS-sensing channel 110 may comprise a high-power white LED as the light source for DRS and/or one or multiple UV (ultraviolet)/visible LEDs (with or without a bandpass filter) as the excitation source for fluorescence spectroscopy. The white LED and color LED(s) may share the same light source fibers (152,
The DRS-sensing channel 110 may comprise a channel, wherein light from the first light source 106 illuminates the biological tissue sample, or specimen 146, whereupon at least one detection fiber 150 is able to capture the reflected light (i.e., spectral data), which is ultimately provided to the spectrometer 104 via the fiber array shown in cross-sectional views of
The calibration channel 120 includes an illumination fiber leg 126 and a calibration return leg 128, as shown in
In addition, the fiber-optic pressure sensor channel 130 may comprise the second illumination fiber leg 135 and a pressure return leg 133. The second illumination fiber leg 135 is coupled to the second light source 115 at a second light source coupler 125, while the pressure return leg 133 is coupled to the spectrometer B 112 at a spectrometer coupler 122. The second illumination fiber leg 135 and the pressure return leg 133 may comprise a single lead in/out fiber (single-mode or multi-mode) forming a low-coherence DFPI at the end face of the lead in/out fiber proximate to the probe tip 144. The second light source 115 may comprise an 850 nm light emitting diode (LED) with a spectral width of about 30 or 60 nm, such as that provided by LEDs manufactured by Appointech Inc.
In order to monitor the physical changes of the specimen tissue 146 that occur due to the application of heat from the electrosurgical device used during robot-assisted laparoscopic procedures, the temperature sensor channel 131, as shown in
Thus, as previously discussed, the smart fiber-optic sensor 105 includes a collection fiber leg 124, a first illumination fiber leg 126, a second illumination fiber leg 135, a calibration return leg 128, a pressure return leg 133, and a temperature return leg 136. The smart fiber-optic sensor 105 also includes a probe tip portion 140, which is coupled to a breakout tube 136 by a probe leg 138. In particular, the probe portion includes the probe tip 144. In one aspect, the probe tip portion 140 may include a calibration housing portion 142 and the rigid probe tip 144. The probe tip 144 is configured to contact the surface of the biological tissue specimen 148, such that the optical fibers of the DRS channel 110, the pressure channel 130, and the temperature channel 131 are brought into proximity or contact with the tissue specimen 146 as necessary to carry out the functions discussed herein. In a further aspect, the tissue specimen 146 may comprise a tissue sample or any turbid medium. Thus, the contact pressure at the probe tip/specimen interface may be calculated and controlled by the robotic surgical system 147 using the fiber-optic pressure-sensing channel 130. Additionally, the contact temperature at the probe tip/specimen interface may also be calculated and manually controlled by the user, or automatically controlled by the robotic surgical system using the fiber-optic temperature-sensing channel 131.
In one embodiment, the calibration source fiber 154 and the calibration return fiber 156 may comprise the same fiber (i.e., a source/return calibration fiber). For example, a single source-return calibration fiber may originate from the light source 106, enter the housing section 142, and then bend or loop back in such a manner that the calibration source/return fiber exits the housing section 142. That is, the calibration source-return fiber can be bent within the housing section 142 in the smart fiber-optic sensor, such that the calibration source fiber 154 functions as the calibration return fiber (since a mirror or other reflective element is not used). The calibration fiber would then be configured to interface with spectrometer channel 108 via the calibration return leg 128. In particular, the reflective material 160 would not be utilized in this particular embodiment. Furthermore, although the cross-sectional view of
In another embodiment, the smart fiber-optic sensor 105 may comprise a calibration channel that can be used to record the lamp spectrum and instrument/fiber responses concurrently with tissue measurements. For example, at least one calibration source fiber 154 can transmit, or communicate calibration light and calibration return fiber 156 can collect, or communicate the calibration light reflected by the reflective material 160 within calibration housing 142 and transmit it to the spectrometer 108. The calibration spectra from the calibration channel can be detected by the spectrometer 108 and can be used for the calibration of the specimen spectrum that is obtained concurrently.
In a further embodiment, the calibration source fiber 154 of the calibration channel 120 may have the same diameter as, and run along the illumination fiber 152 of the sensing channel 110. The calibration return fiber 156 may be the same diameter as the collection fiber 150 in the tissue channel to achieve an identical bending response. To account for wavelength dependence, a correlation factor may be applied before being processed with the spectral data collected from the tissue specimen 146. For example, because the calibration channel 120 may have wavelength responses that differ from the wavelength responses exhibited in the sensing channel 110, the wavelength response in the calibration channel 120 may require correction and/or compensation. To correct the wavelength dependence of the calibration channel 120, a spectral measurement may be taken from a reflectance standard (e.g., a Spectralon puck), which is characterized by a flat wavelength response. A correction factor may then be generated for each sensor or probe by dividing the spectral data of the reflectance standard by the self-calibration spectrum concurrently obtained with spectral data of the reflectance standard. For example, the correlation factor may be characterized by the following equation:
F
corr(λ)=Puck(λ)/SCpuck(λ),
where Puck (A) is measured from a Spectralon puck by the sensing channel 110, and SCpuck (A) is the concurrent spectrum measured by the calibration channel 120. The calibrated reference phantom and tissue spectra can be input into the fast-scalable Monte Carlo inverse model, which extracts the tissue μs′ and μs values from which tissue absorber concentrations can be derived. With the smart fiber-optic sensor system 100, no separate calibration measurements are needed. Exemplary Monte Carlo algorithms suitable for use with the subject matter described herein can be found, for example, in international patent application number PCT/US2007/006624 to Palmer et al.; international patent application number PCT/US2008/0270091 to Ramanujam et al.; and U.S. Pat. No. 7,835,786 to Palmer et al., the entireties of which are incorporated herein by reference, in an alternative embodiment, a diffusion algorithm or inverse diffusion algorithm may be used instead of a Monte Carlo algorithm. Notably, tissue measurements can be started right after the instrument is turned on and fiber bending loss can be accounted for in real time. As a result, such features may provide substantial time savings.
Still referring to
δ=y0(P)/P=1.74×10−5a4/h3(nm/psi)
where y0 (nm) is the deflection of the diaphragm at the center, a=D/2 (μm) is the effective radius of diaphragm 172 (
A non-transitory computer readable medium comprising computer executable instructions, that when executed by a processor of a computer 318, can perform steps comprising collecting spectra from the specimen, calculating and displaying probe pressure for the operator to manually adjust it, adjusting integration time, as necessary, calibrating the sample spectrum, perform spectral analysis, and display the extracted specimen optical properties and physiological parameters, in one aspect, data can be automatically stored if and only if pressure is within an optimal range and upon successful calibration. An optimal range can comprise a minimal optimal range wherein spectral data will be minimally affected by the contact pressure, it is anticipated that an optimal range will comprise 0 to 20 or 0 to 30 psi. The optimal range can comprise a preset value for a processing unit to base decisions off of. For example, a processing unit can automatically analyze and save specimen spectral data if contact pressure is within the minimal optimal range. The minimal optimal range may be dependent on the type of tissue analyzed (e.g., cervical, oral) and the underlying tissue composition. Computer executable instructions can control the smart fiber-optic system, load reference phantom and default parameters (such as integration time and desired pressure range), collect spectra from specimen and pressure sensor, calculate and display the probe pressure for the operator to manually adjust it, adjust integration time, calibrate the sample spectrum, perform spectral analysis, and display the extracted tissue optical properties and physiological parameters. It is expected that the time required to measure and analyze the spectra from a specimen be less than two seconds.
in one aspect,
In particular, the measurement of temperature T of the tissue specimen 146 using the sensor 400 is based on the following equation: La′=La+[(ab−af)·Lb]·(T−T0), where La′ is the initial cavity length, Lb is the gauge length of the tube 410 at room temperature T0, αb is the coefficient of thermal expansion (CTE) of the borosilicate tube 410, and αf is the coefficient of thermal expansion (CTW) of the fused silica fiber of fiber-optic legs 159A and 159B. Furthermore, it is assumed that Lb>>La.
During testing of the temperature sensor 400 inside a temperature chamber, the results shown in
During operation of the temperature sensor 400, the exposed end 440 of the temperature sensor 400 is brought into contact with the tissue specimen 146. Next, light from the second light source 115 is launched into the temperature sensor 400 via leg 159A using the lead in/out fiber 159 to which the second light source 115 is coupled. The low-coherence light propagates into the air cavity 430, where the light beam is partially reflected by the end 420B of the leg 159B, as shown by R1, and at least partially reflected by the surface of the end 420A of the fiber leg 159A, as shown by R2. The reflected light beams R1 and R2 then propagate back through the in/out fiber 159 to the spectrometer D 132, where the reflected light beams interfere with each other. Thus, by analyzing the interferogram that is generated, the length La of the cavity 430 can be calculated in real-time with nanometer to sub-nanometer accuracy. Thus, the temperature applied at the exposed end 440 of the sensor 400 from the tissue specimen 146 changes the cavity length La due to the thermal expansion or contraction of the tube 410. The reflected light beams R1 and R2 may comprise reflectance data and/or temperature sensor spectral data. The temperature sensor 400 may be operated within a linear region (i.e. a small region on one side of an interference fringe near its quadrature point) for optimal sensitivity and the largest signal bandwidth. It should be appreciated that the temperature sensor 400 may have an operating range from about room temperature to about 200° C.
Generating specimen spectral data may comprise transmitting a illumination light via at least one illumination fiber within the sensing channel from a first light source to the specimen 146 and collecting the specimen spectral data using at least one detection fiber in the sensing channel, wherein the specimen spectral data can comprises the illumination light from the first light source diffusely reflected from the specimen at one or more wavelengths.
Step 506 includes calculating contact pressure at the probe tip 144 using the spectral data from the pressure sensor. The pressure sensor spectral data may comprise reflectance data reflected along a cavity length of the DFPI, as discussed above. The pressure sensor may be disposed at the probe tip 144 of the smart fiber-optic sensor 100. The pressure is calculated by transmitting a low-coherence illumination light using a fiber-optic fiber to a DFPI pressure sensor and collecting spectral data reflected by the pressure sensor via the same fiber-optic fiber. As illustrated in
Step 507 includes measuring the temperature T of the specimen tissue 146 as detected by the temperature sensor 400, as previously discussed. That is, the change in cavity length La due to the change in temperature of the capillary tube 410 is detected using the interferogram that is generated by the reflected light beams R1 and R2 and using the algorithm discussed above. Once the temperature T is identified, a user of the robot-assisted surgical system 147 may reduce the intensity of the electrical current applied by the electrosurgical cutting device at the specimen tissue 146 in order to reduce the temperature of the tissue 146, and prevent damage thereto. In addition, the robotic surgical system 147 may be configured to automatically take corrective action to control the electrosurgical device to prevent overheating and damage to the tissue 146. It should be appreciated that this step can be performed at any desired step in process 500.
Next, step 508 includes correcting the specimen spectral data by using the calibration data. Correcting specimen spectral data may comprise transmitting calibration light via at least one calibration source fiber disposed in calibration channel, wherein the calibration light and the illumination light of the sensing channel can be generated simultaneously from the shared, first light source. Correcting specimen spectral data may further comprise collecting correcting spectral data associated with the calibration light via at least one calibration return fiber of the calibration channel contemporaneously with the collection of the spectral data of the specimen. The specimen spectral data received from the sensing channel may be corrected using the calibration spectral data received from the calibration channel.
Optional steps that may be incorporated in the process 500 include analyzing and storing the specimen spectral data. Analyzing and storing the collected spectral data may comprise analyzing the calibrated spectral data to extract the specimen optical and physiological properties of the tissue specimen 146 using, for example, an inverse MC model for reflectance. In one aspect, the data can be automatically analyzed and stored using a determination based upon the pressure data. If the pressure data is within a specified, preset range, then the specimen spectral data and calibration data can be automatically analyzed and/or stored.
Thus, it is desirable to utilize a powered smart sensor system for performing in vivo quantitative DRS of soft tissues at a wavelength range from about 420-720 nm. The applications related to cancer screening in a global population can be greatly improved by the methods and systems disclosed herein. The smart sensor technology disclosed herein can incorporate innovations to several component areas. For example, white LEDs, miniature spectrometers, and a smart fiber-optic sensor can reduce the complexity, size, and cost of conventional optical spectroscopy systems. The systems and methods disclosed herein also minimize the amount of technical skill required to perform optical spectroscopy for early cancer detection applications. The compact integration of a tissue sensing portion, a pressure sensor, and a calibration portion into a single fiber-optic probe enables significant improvement in accuracy and robustness for extraction of tissue optical properties. By limiting or controlling the probe pressure and performing real-time calibration both systematic and random errors in reflectance measurements can be reduced. In addition, by providing temperature sensing of the tissue prevents tissue damage in the form of charring and burning. Further, the sensitivity and specificity for early cancer diagnosis can be improved.
Although the smart sensor discussed herein can be useful for screening and diagnostics for cancers such as oral and cervical cancers, it is not limited thereto. The systems and methods disclosed can be translated to any organ or tissue site, such as the skin, bladder, etc. and can also be used for non-cancer applications such as monitoring vital signs during major surgeries in an intra-operative setting. The systems and methods disclosed herein can be used for any optical spectroscopy application.
Therefore, one advantage of the present invention is that a smart fiber-optic sensor for optical spectroscopy includes a temperature sensor that allows surgeons to identify when the temperature of a tissue specimen being treated by an electrosurgical cutting device exceeds a desired level to prevent unwanted charring and damage to the tissue at the surgical site. Another advantage of the present invention is that a smart fiber-optic sensor for optical spectroscopy includes a temperature sensor that allows surgeons to identify when the spread of heat from an electrosurgical device, such as a laparoscopic surgical device, exceeds a desired area. Still another advantage of the present invention is that a smart fiber-optic sensor for optical spectroscopy is configured for attachment or made integral with an articulating end-effector of a robotic surgical system, such as a robot-assisted laparoscopic (RAL) surgical system.
Thus, it can be seen that the objects of the invention have been satisfied by the structure and its method for use presented above. While in accordance with the Patent Statutes, only the best mode and preferred embodiment has been presented and described in detail, it is to be understood that the invention is not limited thereto or thereby. Accordingly, for an appreciation of the true scope and breadth of the invention, reference should be made to the following claims.
The disclosure of each of the following references is hereby incorporated herein by reference in its entirety.
[1] Schwarz, R. A., W. Gao, D. Daye, M. D. Williams, R. Richards-Kortum, and A. M. Gillenwater, Autofluorescence and diffuse reflectance spectroscopy of oral epithelial tissue using a depth-sensitive fiber-optic probe. Appl Opt, 2008. 47(6): p. 825-34.
[2] Wang, A., V. Nammalavar, and R. Drezek, Targeting spectral signatures of progressively dysplastic stratified epithelia using angularly variable fiber geometry in reflectance Monte Carlo simulations. J Biomed Opt, 2007. 12(4): p. 044012.
[3] Liu, Q. and N. Ramanujam, Sequential estimation of optical properties of a two-layered epithelial tissue model from depth-resolved ultraviolet-visible diffuse reflectance spectra. Appl Opt, 2006. 45(19): p. 4776-90.
[4] Utzinger, U. and R. R. Richards-Kortum, Fiber optic probes for biomedical optical spectroscopy. J Biomed Opt, 2003. 8(1): p. 121-47.
[5] Reif, R., M. S. Amorosino, K. W. Calabro, O. A'Amar, S. K. Singh, and I. J. Bigio, Analysis of changes in reflectance measurements on biological tissues subjected to different probe pressures. J Biomed Opt, 2008. 13(1): p. 010502.
[6] Ti, Y. and W. C. Lin, Effects of probe contact pressure on in vivo optical spectroscopy. Opt Express, 2008. 16(6): p. 4250-62.
[7] Nichols, M. G., E. L. Hull, and T. H. Foster, Design and testing of a white-light, steady-state diffuse reflectance spectrometer for determination of optical properties of highly scattering systems. Appl Opt, 1997. 36(1): p. 93-104.
[8] Marin, N. M., N. MacKinnon, C. MacAulay, S. K. Chang, E. N. Atkinson, D. Cox, D. Serachitopol, B. Pikkula, M. Follen, and R. Richards-Kortum, Calibration standards for multicenter clinical trials of fluorescence spectroscopy for in vivo diagnosis. J Biomed Opt, 2006. 11(1): p. 014010.
[9] Palmer, G. M. and N. Ramanujam, Monte Carlo-based inverse model for calculating tissue optical properties. Part I: Theory and validation on synthetic phantoms. Appl Opt, 2006. 45(5): p. 1062-71.
[10] Yu, B., D. W. Kim, J. Deng, H. Xiao, and A. Wang, Fiber Fabry-Perot sensors for detection of partial discharges in power transformers. Appl Opt, 2003. 42(16): p. 3241-50.
[11] Yu, B., A. Wang, G. Pickrell, and J. Xu, Tunable-optical-filter-based white-light interferometry for sensing. Opt Lett, 2005. 30(12): p. 1452-4.
[12] Xu, J., G. R. Pickrell, B. Yu, M. Han, Y. Zhu, X. Wang, K. L. Cooper, and A. Wang. Epoxy-free high temperature fiber optic pressure sensors for gas turbine engine applications in Sensors for Harsh Environments. 2004: Proc. of SPIE. Vol. 5590.
[13] Prahl, S., Mie scattering program. 2005, Oregon Medical Laser Center, available at http://omlc.ogi.edu/software/mie/index/html.
Thus, it can be seen that the objects of the invention have been satisfied by the structure and its method for use presented above. While in accordance with the Patent Statutes, only the best mode and preferred embodiment has been presented and described in detail, it is to be understood that the invention is not limited thereto or thereby. Accordingly, for an appreciation of the true scope and breadth of the invention, reference should be made to the following claims.
This application claims the benefit of U.S. Provisional Application No. 61/895,148 filed on Oct. 24, 2013, the content of which is incorporated herein by reference.
| Number | Date | Country | |
|---|---|---|---|
| 61895148 | Oct 2013 | US |
