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Purpose. Cherenkov imaging during radiotherapy provides a real time visualization of beam delivery on patient tissue, which can be used dynamically for incident detection or to review a summary of the delivered surface signal for treatment verification. Very few photons form the images, and one limitation is that the noise level per frame can be quite high, and mottle in the cumulative processed images can cause mild overall noise. This work focused on removing or suppressing noise via image postprocessing. Approach. Images were analyzed for peak-signal-to-noise and spatial frequencies present, and several established noise/mottle reduction algorithms were chosen based upon these observations. These included total variation minimization (TV-L1), non-local means filter (NLM), block-matching 3D (BM3D), alpha (adaptive) trimmed mean (ATM), and bilateral filtering. Each were applied to images acquired using a BeamSite camera (DoseOptics) imaged signal from 6x photons from a TrueBeam linac delivering dose at 600 MU min -1 incident on an anthropomorphic phantom and tissue slab phantom in various configurations and beam angles. The standard denoised images were tested for PSNR, noise power spectrum (NPS) and image sharpness. Results. The average peak-signal-to-noise ratio (PSNR) increase was 17.4% for TV-L1. NLM denoising increased the average PSNR by 19.1%, BM3D processing increased it by12.1% and the bilateral filter increased the average PSNR by 19.0%. Lastly, the ATM filter resulted in the lowest average PSNR increase of 10.9%. Of all of these, the NLM and bilateral filters produced improved edge sharpness with, generally, the lowest NPS curve. Conclusion. For cumulative image Cherenkov data, NLM and the bilateral filter yielded optimal denoising with the TV-L1 algorithm giving comparable results. Single video frame Cherenkov images exhibit much higher noise levels compared to cumulative images. Noise suppression algorithms for these frame rates will likely be a different processing pipeline involving these filters incorporated with machine learning., (Creative Commons Attribution license.)

Background and Purpose: Cardiac implanted electronic devices (CIED) require dose monitoring during each fraction of radiotherapy, which can be time consuming and may have delayed read-out times. This study explores the potential of Cherenkov imaging combined with scintillation dosimetry as an alternative verification system., Methods and Materials: Time-gated, complementary metal-oxide-semiconductor (iCMOS) cameras were used to collect video images of anthropomorphic phantoms and patients undergoing radiation treatment near chest wall cardiac devices. Scintillator discs and optically stimulated luminescence dosimeters (OSLDs) were used for dose measurement. Accuracy of spatial delivery was assessed by overlaying predicted surface dose outlines derived from the treatment planning system (TPS) with the Cherenkov images. Dose measurements from OSLDs and scintillators were compared., Results: In phantom studies, Cherenkov images visibly indicated when dose was delivered to the CIED as compared to non-overlapping dose deliveries. Comparison with dose overlays revealed congruence at the planned position and non-congruence when the phantom was shifted from the initial position. Absolute doses derived from scintillator discs aligned well with the OSLD measurements and TPS predictions for three different positions, measuring within 10 % for in-field positions and within 5 % for out-of-field positions. For two patients with CIEDs imaged over 18 fractions, Cherenkov imaging confirmed positional accuracy for all fractions, and dose measured by scintillator discs deviated by <0.015 Gy from the OSLD measurements., Conclusions: Cherenkov imaging combined with scintillation dosimetry presents an alternative methodology for CIED monitoring with the added benefit of instantly detecting deviations, enabling timely corrective actions or proper patient triage., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: L.A.J. has a financial interest in DoseOptics, the manufacturer of cameras used in this study. She has a conflict of interest management plan at Dartmouth College and Dartmouth-Health, which includes an independent review of the research integrity before publication. The following authors have patents related to Cherenkov imaging: US10940332 (L.A.J., R.Z. and D.J.G.) and US10201718B2 (R.Z. and D.J.G). Patents are assigned to The Trustees of Dartmouth College. M.J. is employed by DoseOptics and S.M.D is a consultant for DoseOptics., (© 2024 The Author(s).)

Objective . With the introduction of Cherenkov imaging technology on the Halcyon O-ring linear accelerator platform, we seek to demonstrate the imaging feasibility and optimize camera placement. Approach . Imaging parameters were probed by acquiring triggering data Cherenkov image frames for simplistic beams on the Halcyon and comparing the analyzed metrics with those from the TrueBeam platform. Camera position was analyzed by performing 3D rendering of patient treatment plans for various sites and iterating over camera positions to assess treatment area visibility. Main results . Commercial Cherenkov imaging systems are compatible with the pulse timing of the Halcyon, and this platform design favorably impacts signal to noise in Cherenkov image frames. Additionally, ideal camera placement is treatment site dependent and is always within a biconical zone of visibility centered on the isocenter. Visibility data is provided for four treatment sites, with suggestions for camera placement based on room dimensions. Median visibility values were highest for right breast plans, with values of 80.33% and 68.49% for the front and rear views respectively. Head and neck plans presented with the lowest values at 26.44% and 38.18% respectively. Significance . This work presents the first formal camera positional analysis for Cherenkov imaging on any platform and serves as a template for performing similar work for other irradiation platforms. Additionally, this study confirms the Cherenkov imaging parameters do not need to be changed for optimal imaging on the Halcyon. Lastly, the presented methodology provides a framework which could be further expanded to other optical imaging systems which rely on line of sight visibility to the patient., (© 2023 Institute of Physics and Engineering in Medicine.)

Purpose: Cherenkov imaging is clinically available as a radiation therapy treatment verification tool. The aim of this work was to discover the benefits of always-on Cherenkov imaging as a novel incident detection and quality improvement system through review of all imaging at our center., Methods and Materials: Multicamera Cherenkov imaging systems were permanently installed in 3 treatment bunkers, imaging continuously over a year. Images were acquired as part of normal treatment procedures and reviewed for potential treatment delivery anomalies., Results: In total, 622 unique patients were evaluated for this study. We identified 9 patients with treatment anomalies occurring over their course of treatment, which were only detected with Cherenkov imaging. Categorizing each event indicated issues arising in simulation, planning, pretreatment review, and treatment delivery, and none of the incidents were detected before this review by conventional measures. The incidents identified in this study included dose to unintended areas in planning, dose to unintended areas due to positioning at treatment, and nonideal bolus placement during setup., Conclusions: Cherenkov imaging was shown to provide a unique method of detecting radiation therapy incidents that would have otherwise gone undetected. Although none of the events detected in this study reached the threshold of reporting, they identified opportunities for practice improvement and demonstrated added value of Cherenkov imaging in quality assurance programs., (Copyright © 2022 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.)

Introduction/background: The goal of Total Skin Electron Therapy (TSET) is to achieve a uniform surface dose, although assessment of this is never really done and typically limited points are sampled. A computational treatment simulation approach was developed to estimate dose distributions over the body surface, to compare uniformity of (i) the 6 pose Stanford technique and (ii) the rotational technique., Methods: The relative angular dose distributions from electron beam irradiation was calculated by Monte Carlo simulation for cylinders with a range of diameters, approximating body part curvatures. These were used to project dose onto a 3D body model of the TSET patient's skin surfaces. Computer animation methods were used to accumulate the dose values, for display and analysis of the homogeneity of coverage., Results: The rotational technique provided more uniform coverage than the Stanford technique. Anomalies of under dose were observed in lateral abdominal regions, above the shoulders and in the perineum. The Stanford technique had larger areas of low dose laterally. In the rotational technique, 90% of the patient's skin was within ±10% of the prescribed dose, while this percentage decreased to 60% or 85% for the Stanford technique, varying with patient body mass. Interestingly, the highest discrepancy was most apparent in high body mass patients, which can be attributed to the loss of tangent dose at low angles of curvature., Discussion/conclusion: This simulation and visualization approach is a practical means to analyze TSET dose, requiring only optical surface body topography scans. Under- and over-exposed body regions can be found, and irradiation could be customized to each patient. Dose Area Histogram (DAH) distribution analysis showed the rotational technique to have better uniformity, with most areas within 10% of the umbilicus value. Future use of this approach to analyze dose coverage is possible as a routine planning tool., (Copyright © 2022. Published by Elsevier Inc.)

Purpose: In mono-isocentric radiation therapy treatment plans designed to treat the whole breast and supraclavicular lymph nodes, the fields meet at isocenter, forming the match line. Insufficient coverage at the match line can lead to recurrence, and overlap over weeks of treatment can lead to increased risk of healthy tissue toxicity. Cherenkov imaging was used to assess the accuracy of delivery at the match line and identify potential incidents during patient treatments., Methods and Materials: A controlled calibration was constructed from the deconvolved Cherenkov images from the delivery of a modified patient treatment plan to an anthropomorphic phantom with introduced separation and overlap. The trend from this calibration was then used to evaluate the field match line for accuracy and inter-fraction consistency for two patients., Results: The intersection point between matching field profiles was directly correlated to the distance (gap/overlap) between the fields (anthropomorphic phantom R 2 = 0.994 "breath hold" and R 2 = 0.990 "free breathing"). The profile intersection points from two patients' imaging sessions yielded an average of +1.40 mm offset (overlap) and -1.32 mm offset (gap), thereby introducing roughly a 25.0% over-dose and a -23.6% under-dose (R 2 = 0.994)., Conclusions: This study shows that field match regions can be detected and quantified by taking deconvolved Cherenkov images and using their product image to create steep intensity gradients, causing match lines to stand out. These regions can then be quantitatively translated into a dose consequence. This approach offers a high sensitivity detection method which can quantify match line variability and errors in vivo., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Purpose: The value of Cherenkov imaging as an on-patient, real-time, treatment delivery verification system was examined in a 64-patient cohort during routine radiation treatments in a single-center study., Methods and Materials: Cherenkov cameras were mounted in treatment rooms and used to image patients during their standard radiation therapy regimen for various sites, predominantly for whole breast and total skin electron therapy. For most patients, multiple fractions were imaged, with some involving bolus or scintillators on the skin. Measures of repeatability were calculated with a mean distance to conformity (MDC) for breast irradiation images., Results: In breast treatments, Cherenkov images identified fractions when treatment delivery resulted in dose on the contralateral breast, the arm, or the chin and found nonideal bolus positioning. In sarcoma treatments, safe positioning of the contralateral leg was monitored. For all 199 imaged breast treatment fields, the interfraction MDC was within 7 mm compared with the first day of treatment (with only 7.5% of treatments exceeding 3 mm), and all but 1 fell within 7 mm relative to the treatment plan. The value of imaging dose through clear bolus or quantifying surface dose with scintillator dots was examined. Cherenkov imaging also was able to assess field match lines in cerebral-spinal and breast irradiation with nodes. Treatment imaging of other anatomic sites confirmed the value of surface dose imaging more broadly., Conclusions: Daily radiation therapy can be imaged routinely via Cherenkov emissions. Both the real-time images and the posttreatment, cumulative images provide surrogate maps of surface dose delivery that can be used for incident discovery and/or continuous improvement in many delivery techniques. In this initial 64-patient cohort, we discovered 6 minor incidents using Cherenkov imaging; these otherwise would have gone undetected. In addition, imaging provides automated, quantitative metrics useful for determining the quality of radiation therapy delivery., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Purpose: The novel scintillator-based system described in this study is capable of accurately and remotely measuring surface dose during Total Skin Electron Therapy (TSET); this dosimeter does not require post-exposure processing or annealing and has been shown to be re-usable, resistant to radiation damage, have minimal impact on surface dose, and reduce chances of operator error compared to existing technologies e.g. optically stimulated luminescence detector (OSLD). The purpose of this study was to quantitatively analyze the workflow required to measure surface dose using this new scintillator dosimeter and compare it to that of standard OSLDs., Methods: Disc-shaped scintillators were attached to a flat-faced phantom and a patient undergoing TSET. Light emission from these plastic discs was captured using a time-gated, intensified, camera during irradiation and converted to dose using an external calibration factor. Time required to complete each step (daily QA, dosimeter preparation, attachment, removal, registration, and readout) of the scintillator and OSLD surface dosimetry workflows was tracked., Results: In phantoms, scintillators and OSLDs surface doses agreed within 3% for all data points. During patient imaging it was found that surface dose measured by OSLD and scintillator agreed within 5% and 3% for 35/35 and 32/35 dosimetry sites, respectively. The end-to-end time required to measure surface dose during phantom experiments for a single dosimeter was 78 and 202 sec for scintillator and OSL dosimeters, respectively. During patient treatment, surface dose was assessed at 7 different body locations by scintillator and OSL dosimeters in 386 and 754 sec, respectively., Conclusion: Scintillators have been shown to report dose nearly twice as fast as OSLDs with substantially less manual work and reduced chances of human error. Scintillator dose measurements are automatically saved to an electronic patient file and images contain a permanent record of the dose delivered during treatment., (© 2020 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.)

Purpose: Quality assurance (QA) of dose homogeneity in total skin electron therapy (TSET) is challenging since each patient is positioned in six standing poses with two beam angles. Our study tested the feasibility of a unique approach for TSET QA through computational display of the cumulative dose, constructed and synthesized by computer animation methods. Approach: Dose distributions from Cherenkov emission images were projected onto a scanned 3D body model. Topographically mapped surfaces of the patient were recorded in each of six different delivery positions, while a Cherenkov camera acquired images. Computer animation methods allowed a fitted 3D human body model of the patient to be created with deformation of the limbs and torso to each position. A two-dimensional skin map was extracted from the 3D model of the full surface of the patient. This allowed the dose mapping to be additively accumulated independent of body position, with the total dose summed in a 2D map and reinterpreted on the 3D body display. Results: For the body model, the mean Hausdorff error distance was below 2 cm, setting the spatial accuracy limit. The dose distribution over the patient's 3D model generally matched the Cherenkov/dose images. The dose distribution mapping was estimated to be near 1.5 cm accuracy based upon a phantom study. The body model must most closely match at the edges of the mesh to ensure that high dose gradients are not projected onto the wrong location. Otherwise 2 to 3 cm level errors in positioning in the mesh do not appear to cause larger than 5% dose errors. The cumulative dose images showed regions of overlap laterally and regions of low intensity in the posterior arms. Conclusions: The proposed modeling and animation can be used to visualize and analyze the accumulated dose in TSET via display of the summed dose/Cherenkov images on a single body surface., (© 2020 Society of Photo-Optical Instrumentation Engineers (SPIE).)

Purpose: Patients have reported sensations of seeing light flashes during radiation therapy, even with their eyes closed. These observations have been attributed to either direct excitation of retinal pigments or generation of Cherenkov light inside the eye. Both in vivo human and ex vivo animal eye imaging was used to confirm light intensity and spectra to determine its origin and overall observability., Methods and Materials: A time-gated and intensified camera was used to capture light exiting the eye of a patient undergoing stereotactic radiosurgery in real time, thereby verifying the detectability of light through the pupil. These data were compared with follow-up mechanistic imaging of ex vivo animal eyes with thin radiation beams to evaluate emission spectra and signal intensity variation with anatomic depth. Angular dependency of light emission from the eye was also measured., Results: Patient imaging showed that light generation in the eye during radiation therapy can be captured with a signal-to-noise ratio of 68. Irradiation of ex vivo eye samples confirmed that the spectrum matched that of Cherenkov emission and that signal intensity was largely homogeneous throughout the entire eye, from the cornea to the retina, with a slight maximum near 10 mm depth. Observation of the signal external to the eye was possible through the pupil from 0° to 90°, with a detected emission near 2500 photons per millisecond (during peak emission of the ON cycle of the pulsed delivery), which is over 2 orders of magnitude higher than the visible detection threshold., Conclusions: By quantifying the spectra and magnitude of the signal, we now have direct experimental observations that Cherenkov light is generated in the eye during radiation therapy and can contribute to perceived light flashes. Furthermore, this technique can be used to further study and measure phosphenes in the radiation therapy clinic., (Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved.)

Subdiffuse spatial frequency domain imaging (sd-SFDI) data of 42 freshly excised, bread-loafed tumor resections from breast-conserving surgery (BCS) were evaluated using texture analysis and a machine learning framework for tissue classification. Resections contained 56 regions of interest (RoIs) determined by expert histopathological analysis. RoIs were coregistered with sd-SFDI data and sampled into ∼4  ×  4  mm2 subimage samples of confirmed and homogeneous histological categories. Sd-SFDI reflectance textures were analyzed using gray-level co-occurrence matrix pixel statistics, image primitives, and power spectral density curve parameters. Texture metrics exhibited statistical significance (p-value  <  0.05) between three benign and three malignant tissue subtypes. Pairs of benign and malignant subtypes underwent texture-based, binary classification with correlation-based feature selection. Classification performance was evaluated using fivefold cross-validation and feature grid searching. Classification using subdiffuse, monochromatic reflectance (illumination spatial frequency of fx  =  1.37  mm  −  1, optical wavelength of λ  =  490  nm) achieved accuracies ranging from 0.55 (95% CI: 0.41 to 0.69) to 0.95 (95% CI: 0.90 to 1.00) depending on the benign–malignant diagnosis pair. Texture analysis of sd-SFDI data maintains the spatial context within images, is free of light transport model assumptions, and may provide an alternative, computationally efficient approach for wide field-of-view (cm2) BCS tumor margin assessment relative to pixel-based optical scatter or color properties alone.

Purpose: The aim of this study was to create an optical imaging-based system for quality assurance (QA) testing of a dedicated Co-60 total body irradiation (TBI) machine. Our goal is to streamline the QA process by minimizing the amount time necessary for tests such as verification of dose rate and field homogeneity., Methods: Plastic scintillating rods were placed directly on the patient treatment couch of a dedicated TBI 60 Co irradiator. A tripod-mounted intensified camera was placed directly adjacent to the couch. Images were acquired over a 30-s period once the cobalt source was fully exposed. Real-time image filtering was used; cumulative images were flatfield corrected as well as background and darkfield subtracted. Scintillators were used to measure light-radiation field correspondence, dose rate, field homogeneity, and symmetry. Dose rate effects were measured by modifying the height of the treatment couch and scintillator response was compared to ionization chamber (IC) measurements. Optically stimulated luminesce detector (OSLD) used as reference dosimeters during field symmetry and homogeneity testing., Results: The scintillator-based system accurately reported changes in dose rate. When comparing normalized output values for IC vs scintillators over a range of source-to-surface distances, a linear relationship (R 2  = 0.99) was observed. Normalized scintillator signal matched OSLD measurements with <1.5% difference during field homogeneity and symmetry testing. Beam symmetry across both axes of the field was within 2%. The light field was found to correspond to 90 ± 3% of the isodose maximum along the longitudinal and latitudinal axis, respectively. Scintillator imaging output results using a single image stack requiring no postexposure processing (needed for OSLD) or repeat manual measurements (needed for IC)., Conclusion: Imaging of scintillation light emission from plastic rods is a viable and efficient method for carrying out TBI 60 Co irradiator QA. We have shown that this technique can accurately measure field homogeneity, symmetry, light-radiation field correspondence, and dose rate effects., (© 2019 American Association of Physicists in Medicine.)

Previous work has shown that capturing optical emission from plastic discs attached directly to the skin can be a viable means to accurately measure surface dose during total skin electron therapy. This method can provide accurate dosimetric information rapidly and remotely without the need for postprocessing. The objective of this study was to: (1) improve the robustness and usability of the scintillators and (2) enhance sensitivity of the optical imaging system to improve scintillator emission detection as related to tissue surface dose. Baseline measurements of scintillator optical output were obtained by attaching the plastic discs to a flat tissue phantom and simultaneously irradiating and imaging them. Impact on underlying surface dose was evaluated by placing the discs on-top of the active element of an ionization chamber. A protective coating and adhesive backing were added to allow easier logistical use, and they were also subjected to disinfection procedures, while verifying that these changes did not affect the linearity of response with dose. The camera was modified such that the peak of detector quantum efficiency better overlapped with the emission spectra of the scintillating discs. Patient imaging was carried out and surface dose measurements were captured by the updated camera and compared to those produced by optically stimulated luminescence detectors (OSLD). The updated camera was able to measure surface dose with < 3 %   difference compared to OSLD–Cherenkov emission from the patient was suppressed and scintillation detection was enhanced by 25 × and 7 ×  , respectively. Improved scintillators increase underlying surface dose on average by 5.2  ±  0.1 %   and light output decreased by 2.6  ±  0.3 %  . Disinfection had < 0.02 %   change on scintillator light output. The enhanced sensitivity of the imaging system to scintillator optical emission spectrum can now enable a reduction in physical dimensions of the dosimeters without loss in ability to detect light output.

Purpose: The goal of this work is to produce a surface-dosimetry method capable of accurately and remotely measuring skin dose for patients undergoing total skin electron therapy (TSET) without the need for postexposure dosimeter processing. A rapid and wireless surface-dosimetry system was developed to improve clinical workflow. Scintillator-surface dosimetry was conducted on patients undergoing TSET by imaging scintillator targets with an intensified camera during TSET delivery., Methods and Materials: Disc-shaped scintillator targets were attached to the skin surface of patients undergoing TSET and imaged with an intensified, time-gated, and linear accelerator-synchronized camera. Optically stimulated luminescence dosimeters (OSLDs) were placed directly adjacent to scintillators at several dosimetry sites to serve as an absolute dose reference. Real-time image-processing methods were used to produce background-subtracted intensity maps of Cherenkov and scintillation emission. Rapid conversion of scintillator-light output to dose was achieved by using a custom fitting algorithm and calibration factor. Surface doses measured by scintillators were compared with those from OSLDs., Results: Absolute surface-dose measurements for 99 dosimetry sites were evaluated. According to paired OSLD estimates, scintillator dosimeters were able to report dose with <3% difference in 88 of 99 observed dosimetry sites and <5% difference in 98 of 99 observed dosimetry sites. Fitting a linear regression to dose data reported by scintillator versus OSLD, per dosimetry site, yielded an R 2  = 0.94., Conclusions: Scintillators were able to report dose within <3% accuracy of OSLDs. Imaging of calibrated scintillator targets via an intensified, linear accelerator-synchronized camera provides rapid absolute surface-dosimetry measurements for patients treated with TSET. This technique has the potential to reduce the amount of time and effort necessary to conduct full-body dosimetry and can be adopted for use in any surface-dosimetry setting where the region of interest is observable throughout treatment., (Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.)

Purpose: A remote imaging system tracking Cherenkov emission was analyzed to verify that the linear accelerator (linac) beam shape could be quantitatively measured at the irradiation surface for Quality Audit (QA)., Methods: The Cherenkov camera recorded 2D dose images delivered on a solid acrylonitrile butadiene styrene (ABS) plastic phantom surface for a range of square beam sizes, and 6 MV photons. Imaging was done at source to surface distance (SSD) of 100 cm and compared to GaF film images and linac light fields of the same beam sizes, ranging over 5 × 5 cm 2 up to 20 × 20 cm 2 . Line profiles of each field were compared in both X and Y jaw directions. Each measurement was repeated on two different Clinac2100 machines. An interreader comparison of the beam width interpretation was completed using procedures commonly employed for beam to light field coincidence verification. Cherenkov measurements are also done for beams of complex treatment plan and isocenter QA., Results: The Cherenkov image widths matched with the measured GaF images and light field images, with accuracy in the range of ±1 mm standard deviation. The differences between the measurements were minor and within tolerance of geometrical requirement of standard linac QA procedures conducted by human setup verification, which had a similar error range. The measurement made by the remote imaging system allowed for beam shape extraction of radiation fields at the SSD location of the beam., Conclusions: The proposed Cherenkov image acquisition system provides a valid way to remotely confirm radiation field sizes and provides similar information to that obtained from the linac light field or GaF film estimates of the beam size. The major benefit of this approach is that with a fixed installation of the camera, testing could be done completely under software control with automated image analysis, potentially simplifying conventional QA procedures with appropriate calibration of boundary definitions, and the natural extension to capturing dynamic treatment beamlets at SSD could have future value, such as verification of beam plans with complex beam shapes, like IMRT or "star-shot" QA for the isocenter., (© 2018 American Association of Physicists in Medicine.)

Imaging Cherenkov emission during radiotherapy permits real-time visualization of external beam delivery on superficial tissue. This signal is linear with absorbed dose in homogeneous media, indicating potential for quantitative dosimetry. In humans, the inherent heterogeneity of tissue optical properties (primarily from blood and skin pigment) distorts the linearity between detected Cherenkov signal and absorbed dose. We examine the potential to correct for superficial vasculature using spatial frequency domain imaging (SFDI) to map tissue optical properties for large fields of view. In phantoms, applying intensity corrections to simulate blood vessels improves Cherenkov image (CI) negative contrast by 24% for a vessel 1.9-mm-in diameter. In human trials, SFDI and CI are acquired for women undergoing whole breast radiotherapy. Applied corrections reduce heterogeneity due to vasculature within the sampling limits of the SFDI from a 22% difference as compared to the treatment plan, down to 6% in one region and from 14% down to 4% in another region. The optimal use for this combined imaging system approach is to correct for small heterogeneities such as superficial blood vessels or for interpatient variations in blood/melanin content such that the corrected CI more closely represents the surface dose delivered., ((2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).)

For prostate cancer (PCa) patients, radical prostatectomy (complete removal of the prostate) is the only curative surgical option. To date, there is no clinical technique allowing for real-time assessment of surgical margins to minimize the extent of residual cancer. Here, we present a tissue interrogation technique using a dual excitation wavelength Raman spectroscopy system capable of sequentially acquiring fingerprint (FP) and high wavenumber (HWN) Raman spectra. Results demonstrate the ability of the system to detect PCa in post-prostatectomy specimens. In total, 477 Raman spectra were collected from 18 human prostate slices. Each area measured with Raman spectroscopy was characterized as either normal or cancer based on histopathological analyses, and each spectrum was classified based on supervised learning using support vector machines (SVMs). Based on receiver operating characteristic (ROC) analysis, FP (area under the curve [AUC] = 0.89) had slightly superior cancer detection capabilities compared with HWN (AUC = 0.86). Optimal performance resulted from combining the spectral information from FP and HWN (AUC = 0.91), suggesting that the use of these two spectral regions may provide complementary molecular information for PCa detection. The use of leave-one-(spectrum)-out (LOO) or leave-one-patient-out (LOPO) cross-validation produced similar classification results when combining FP with HWN. Our findings suggest that the application of machine learning using multiple data points from the same patient does not result in biases necessarily impacting the reliability of the classification models., Competing Interests: F.L. is co-founder of ODS Medical Inc., a medical device company that seeks to commercialize the Raman spectroscopy system for real-time detection of tissue abnormalities.

Objective: To test if Raman spectroscopy (RS) is an appropriate tool for the diagnosis and possibly grading of prostate cancer (PCa)., Patients and Methods: Between 20 and 50 Raman spectra were acquired from 32 fresh and non-processed post-prostatectomy specimens using a macroscopic handheld RS probe. Each measured area was characterized and categorized according to histopathological criteria: tissue type (extraprostatic or prostatic); tissue malignancy (benign or malignant); cancer grade (Grade Groups [GGs] 1-5); and tissue glandular level. The data were analysed using machine-learning classification with neural network., Results: The RS technique was able to distinguish prostate from extraprostatic tissue with a sensitivity of 82% and a specificity of 83% and benign from malignant tissue with a sensitivity of 87% and a specificity of 86%. In an exploratory fashion, RS differentiated benign from GG1 in 726/801 spectra (91%; sensitivity 80%, specificity 91%), from GG2 in 588/805 spectra (73%; sensitivity 76%, specificity 73%), from GG3 in 670/797 spectra (84%; sensitivity 86%, specificity 84%), from GG4 in 711/802 spectra (88%; sensitivity 77%, specificity 89%) and from GG5 in 729/818 spectra (89%; sensitivity 90%, specificity 89%)., Conclusion: Current diagnostic approaches of PCa using needle biopsies have suboptimal cancer detection rates and a significant risk of infection. Standard non-targeted random sampling results in false-negative biopsies in 15-30% of patients, which affects clinical management. RS, a non-destructive tissue interrogation technique providing vibrational molecular information, resolved the highly complex architecture of the prostate and detect cancer with high accuracy using a fibre optic probe to interrogate radical prostatectomy (RP) specimens from 32 patients (947 spectra). This proof-of-principle paves the way for the development of in vivo tumour targeting spectroscopy tools for informed biopsy collection to address the clinical need for accurate PCa diagnosis and possibly to improve surgical resection during RP as a complement to histopathological analysis., (© 2018 The Authors BJU International © 2018 BJU International Published by John Wiley & Sons Ltd.)

Medical devices face many hurdles before they enter routine clinical practice to address unmet clinical needs. This is also the case for biomedical optical spectroscopy and imaging systems that are used here to illustrate the opportunities and challenges involved. Following initial concept, stages in clinical translation include instrument development, preclinical testing, clinical prototyping, clinical trials, prototype-to-product conversion, regulatory approval, commercialization, and finally clinical adoption and dissemination, all in the face of potentially competing technologies. Optical technologies face additional challenges from their being extremely diverse, often targeting entirely different diseases and having orders-of-magnitude differences in resolution and tissue penetration. However, these technologies can potentially address a wide variety of unmet clinical needs since they provide rich intrinsic biochemical and structural information, have high sensitivity and specificity for disease detection and localization, and are practical, safe (minimally invasive, nonionizing), and relatively affordable., ((2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).)

Modern cancer diagnosis requires histological, molecular, and genomic tumor analyses. Tumor sampling is often achieved using a targeted needle biopsy approach. Targeting errors and cancer heterogeneity causing inaccurate sampling are important limitations of this blind technique leading to non-diagnostic or poor quality samples, and the need for repeated biopsies pose elevated patient risk. An optical technology that can analyze the molecular nature of the tissue prior to harvesting could improve cancer targeting and mitigate patient risk. Here we report on the design, development, and validation of an in situ intraoperative, label-free, cancer detection system based on high wavenumber Raman spectroscopy. This optical detection device was engineered into a commercially available biopsy system allowing tumor analysis prior to tissue harvesting without disrupting workflow. Using a dual validation approach we show that high wavenumber Raman spectroscopy can detect human dense cancer with >60% cancer cells in situ during surgery with a sensitivity and specificity of 80% and 90%, respectively. We also demonstrate for the first time the use of this system in a swine brain biopsy model. These studies set the stage for the clinical translation of this optical molecular imaging method for high yield and safe targeted biopsy.

Imaging of Cherenkov light emission from patient tissue during fractionated radiotherapy has been shown to be a possible way to visualize beam delivery in real time. If this tool is advanced as a delivery verification methodology, then a sequence of image processing steps must be established to maximize accurate recovery of beam edges. This was analyzed and developed here, focusing on the noise characteristics and representative images from both phantoms and patients undergoing whole breast radiotherapy. The processing included temporally integrating video data into a single, composite summary image at each control point. Each image stack was also median filtered for denoising and ultimately thresholded into a binary image, and morphologic small hole removal was used. These processed images were used for day-to-day comparison computation, and either the Dice coefficient or the mean distance to conformity values can be used to analyze them. Systematic position shifts of the phantom up to 5 mm approached the observed variation values of the patient data. This processing algorithm can be used to analyze the variations seen in patients being treated concurrently with daily Cherenkov imaging to quantify the day-to-day disparities in delivery as a quality audit system for position/beam verification.

Effectiveness of surgery as a cancer treatment is reduced when all cancer cells are not detected during surgery, leading to recurrences that negatively impact survival. To maximize cancer cell detection during cancer surgery, we designed an in situ intraoperative, label-free, optical cancer detection system that combines intrinsic fluorescence spectroscopy, diffuse reflectance spectroscopy, and Raman spectroscopy. Using this multimodal optical cancer detection system, we found that brain, lung, colon, and skin cancers could be detected in situ during surgery with an accuracy, sensitivity, and specificity of 97%, 100%, and 93%, respectively. This highly sensitive optical molecular imaging approach can profoundly impact a wide range of surgical and noninvasive interventional oncology procedures by improving cancer detection capabilities, thereby reducing cancer burden and improving survival and quality of life. Cancer Res; 77(14); 3942-50. ©2017 AACR ., (©2017 American Association for Cancer Research.)

Ambient light artifacts can confound Raman spectroscopy measurements performed in a clinical setting such as during open surgery. However, requiring light sources to be turned off during intraoperative spectral acquisition can be impractical because it can slow down the procedure by requiring surgeons to acquire data under light conditions different from the routine clinical practice. Here a filter system is introduced allowing in vivo Raman spectroscopy measurements to be performed with the light source of a neurosurgical microscope turned on, without interfering with the standard procedure. Ex vivo and in vivo results on calf and human brain, respectively, show that when the new filter system is used there is no significant difference between Raman spectra acquired under pitch dark conditions or with the microscope light source turned on. This is important for the clinical translation of Raman spectroscopy because of the resulting decrease in total imaging time for each measurement and because the surgeon can now acquire spectroscopic data with no disruption of the surgical workflow.

There is an urgent need for improved techniques for disease detection. Optical spectroscopy and imaging technologies have potential for non- or minimally-invasive use in a wide range of clinical applications. The focus here, in vivo Raman spectroscopy (RS), measures inelastic light scattering based on interaction with the vibrational and rotational modes of common molecular bonds in cells and tissue. The Raman 'signature' can be used to assess physiological status and can also be altered by disease. This information can supplement existing diagnostic (e.g. radiological imaging) techniques for disease screening and diagnosis, in interventional guidance for identifying disease margins, and in monitoring treatment responses. Using fiberoptic-based light delivery and collection, RS is most easily performed on accessible tissue surfaces, either on the skin, in hollow organs or intra-operatively. The strength of RS lies in the high biochemical information content of the spectra, that characteristically show an array of very narrow peaks associated with specific chemical bonds. This results in high sensitivity and specificity, for example to distinguish malignant or premalignant from normal tissues. A critical issue is that the Raman signal is often very weak, limiting clinical use to point-by-point measurements. However, non-linear techniques using pulsed-laser sources have been developed to enable in vivo Raman imaging. Changes in Raman spectra with disease are often subtle and spectrally distributed, requiring full spectral scanning, together with the use of tissue classification algorithms that must be trained on large numbers of independent measurements. Recent advances in instrumentation and spectral analysis have substantially improved the clinical feasibility of RS, so that it is now being investigated with increased success in a wide range of cancer types and locations, as well as for non-oncological conditions. This review covers recent advances and continuing challenges, with emphasis on clinical translation.

Surgical treatment of brain cancer is limited by the inability of current imaging capabilities such as magnetic resonance imaging (MRI) to detect the entirety of this locally invasive cancer. This results in residual cancer cells remaining following surgery, leading to recurrence and death. We demonstrate that intraoperative Raman spectroscopy can detect invasive cancer cells centimeters beyond pathological T1-contrast-enhanced and T2-weighted MRI signals. This intraoperative optical guide can be used to detect invasive cancer cells and minimize post-surgical cancer burden. The detection of distant invasive cancer cells beyond MRI signal has the potential to increase the effectiveness of surgery and directly lengthen patient survival.

Invasive brain cancer cells cannot be visualized during surgery and so they are often not removed. These residual cancer cells give rise to recurrences.

In glioma surgery, Protoporphyrin IX (PpIX) fluorescence may identify residual tumor that could be resected while minimizing damage to normal brain. We demonstrate that improved sensitivity for wide-field spectroscopic fluorescence imaging is achieved with minimal disruption to the neurosurgical workflow using an electron-multiplying charge-coupled device (EMCCD) relative to a state-of-the-art CMOS system. In phantom experiments the EMCCD system can detect at least two orders-of-magnitude lower PpIX. Ex vivo tissue imaging on a rat glioma model demonstrates improved fluorescence contrast compared with neurosurgical fluorescence microscope technology, and the fluorescence detection is confirmed with measurements from a clinically-validated spectroscopic probe. Greater PpIX sensitivity in wide-field fluorescence imaging may improve the residual tumor detection during surgery with consequent impact on survival.

A detailed characterization study is presented of a Raman spectroscopy system designed to maximize the volume of resected cancer tissue in glioma surgery based on in vivo molecular tissue characterization. It consists of a hand-held probe system measuring spectrally resolved inelastically scattered light interacting with tissue, designed and optimized for in vivo measurements. Factors such as linearity of the signal with integration time and laser power, and their impact on signal to noise ratio, are studied leading to optimal data acquisition parameters. The impact of ambient light sources in the operating room is assessed and recommendations made for optimal operating conditions. In vivo Raman spectra of normal brain, cancer and necrotic tissue were measured in 10 patients, demonstrating that real-time inelastic scattering measurements can distinguish necrosis from vital tissue (including tumor and normal brain tissue) with an accuracy of 87%, a sensitivity of 84% and a specificity of 89%.

Obtaining accurate quantitative information on the concentration and distribution of fluorescent markers lying at a depth below the surface of optically turbid media, such as tissue, is a significant challenge. Here, we introduce a fluorescence reconstruction technique based on a diffusion light transport model that can be used during surgery, including guiding resection of brain tumors, for depth-resolved quantitative imaging of near-infrared fluorescent markers. Hyperspectral fluorescence images are used to compute a topographic map of the fluorophore distribution, which yields structural and optical constraints for a three-dimensional subsequent hyperspectral diffuse fluorescence reconstruction algorithm. Using the model fluorophore Alexa Fluor 647 and brain-like tissue phantoms, the technique yielded estimates of fluorophore concentration within ±25% of the true value to depths of 5 to 9 mm, depending on the concentration. The approach is practical for integration into a neurosurgical fluorescence microscope and has potential to further extend fluorescence-guided resection using objective and quantified metrics of the presence of residual tumor tissue.

Cancers are often impossible to visually distinguish from normal tissue. This is critical for brain cancer where residual invasive cancer cells frequently remain after surgery, leading to disease recurrence and a negative impact on overall survival. No preoperative or intraoperative technology exists to identify all cancer cells that have invaded normal brain. To address this problem, we developed a handheld contact Raman spectroscopy probe technique for live, local detection of cancer cells in the human brain. Using this probe intraoperatively, we were able to accurately differentiate normal brain from dense cancer and normal brain invaded by cancer cells, with a sensitivity of 93% and a specificity of 91%. This Raman-based probe enabled detection of the previously undetectable diffusely invasive brain cancer cells at cellular resolution in patients with grade 2 to 4 gliomas. This intraoperative technology may therefore be able to classify cell populations in real time, making it an ideal guide for surgical resection and decision-making., (Copyright © 2015, American Association for the Advancement of Science.)

A diffuse imaging method is presented that enables wide-field estimation of the depth of fluorescent molecular markers in turbid media by quantifying the deformation of the detected fluorescence spectra due to the wavelength-dependent light attenuation by overlying tissue. This is achieved by measuring the ratio of the fluorescence at two wavelengths in combination with normalization techniques based on diffuse reflectance measurements to evaluate tissue attenuation variations for different depths. It is demonstrated that fluorescence topography can be achieved up to a 5 mm depth using a near-infrared dye with millimeter depth accuracy in turbid media having optical properties representative of normal brain tissue. Wide-field depth estimates are made using optical technology integrated onto a commercial surgical microscope, making this approach feasible for real-world applications., (© 2015 Society of Photo-Optical Instrumentation Engineers (SPIE))

The extraction of tissue samples during brain needle biopsy can cause life-threatening hemorrhage because of significant blood vessel injury during the procedure. Vessel rupture can have significant consequences for patient health, ranging from transient neurological deficits to death. Here, we present a sub-diffuse optical tomography technique that can be integrated into neurosurgical workflow to detect the presence of blood vessels. A proof-of-concept study performed on a realistic brain tissue phantom is presented and demonstrates that interstitial optical tomography (iOT) can detect several 1 mm diameter high-contrast absorbing objects located <2  mm from the needle.

Purpose: To determine whether pretreatment biomarkers obtained from diffuse optical spectroscopic tomographic (DOST) imaging predicts breast tumor response to neoadjuvant chemotherapy (NAC), which would have value to potentially eliminate delays in prescribing definitive local regional therapy that may occur from a standard complete 6- to 8-month course of NAC., Experimental Design: Nineteen patients undergoing NAC were imaged with DOST before, during, and after treatment. The DOST images of total hemoglobin concentration (HbT), tissue oxygen saturation (StO2), and water (H2O) fraction at different time points have been used for testing the abilities of differentiating patients having pathologic complete response (pCR) versus pathologic incomplete response (pIR)., Results: Significant differences (P < 0.001, AUC = 1.0) were found between pCR patients versus pIR in outcome, based on the percentage change in tumor HbT within the first cycle of treatment. In addition, pretreatment tumor HbT (pretreatment HbT) relative to the contralateral breast was statistically significant (P = 0.01, AUC = 0.92) in differentiating pCR from pIR., Conclusions: This is the first clinical evidence that DOST HbT may differentiate the two groups with predictive significance based on data acquired before NAC even begins. The study also demonstrates the potential of accelerating the validation of optimal NAC regimens through future randomized clinical trials by reducing the number of patients required and the length of time they need to be followed by using a validated imaging surrogate as an outcome measure., (©2014 American Association for Cancer Research.)

Purpose: To determine whether Cherenkov light imaging can visualize radiation therapy in real time during breast radiation therapy., Methods and Materials: An intensified charge-coupled device (CCD) camera was synchronized to the 3.25-μs radiation pulses of the clinical linear accelerator with the intensifier set × 100. Cherenkov images were acquired continuously (2.8 frames/s) during fractionated whole breast irradiation with each frame an accumulation of 100 radiation pulses (approximately 5 monitor units)., Results: The first patient images ever created are used to illustrate that Cherenkov emission can be visualized as a video during conditions typical for breast radiation therapy, even with complex treatment plans, mixed energies, and modulated treatment fields. Images were generated correlating to the superficial dose received by the patient and potentially the location of the resulting skin reactions. Major blood vessels are visible in the image, providing the potential to use these as biological landmarks for improved geometric accuracy. The potential for this system to detect radiation therapy misadministrations, which can result from hardware malfunction or patient positioning setup errors during individual fractions, is shown., Conclusions: Cherenkoscopy is a unique method for visualizing surface dose resulting in real-time quality control. We propose that this system could detect radiation therapy errors in everyday clinical practice at a time when these errors can be corrected to result in improved safety and quality of radiation therapy., (Copyright © 2014 Elsevier Inc. All rights reserved.)

The goal of this study was to determine dominant factors affecting treatment response in pancreatic cancer photodynamic therapy (PDT), based on clinically available information in the VERTPAC-01 trial. This trial investigated the safety and efficacy of verteporfin PDT in 15 patients with locally advanced pancreatic adenocarcinoma. CT scans before and after contrast enhancement from the 15 patients in the VERTPAC-01 trial were used to determine venous-phase blood contrast enhancement and this was correlated with necrotic volume determined from post-treatment CT scans, along with estimation of optical absorption in the pancreas for use in light modeling of the PDT treatment. Energy threshold contours yielded estimates for necrotic volume based on this light modeling. Both contrast-derived venous blood content and necrotic volume from light modeling yielded strong correlations with observed necrotic volume (R² = 0.85 and 0.91, respectively). These correlations were much stronger than those obtained by correlating energy delivered versus necrotic volume in the VERTPAC-01 study and in retrospective analysis from a prior clinical study. This demonstrates that contrast CT can provide key surrogate dosimetry information to assess treatment response. It also implies that light attenuation is likely the dominant factor in the VERTPAC treatment response, as opposed to other factors such as drug distribution. This study is the first to show that contrast CT provides needed surrogate dosimetry information to predict treatment response in a manner which uses standard-of-care clinical images, rather than invasive dosimetry methods.

Multimodal approaches that combine near-infrared (NIR) and conventional imaging modalities have been shown to improve optical parameter estimation dramatically and thus represent a prevailing trend in NIR imaging. These approaches typically involve applying anatomical templates from magnetic resonance imaging/computed tomography/ultrasound images to guide the recovery of optical parameters. However, merging these data sets using current technology requires multiple software packages, substantial expertise, significant time-commitment, and often results in unacceptably poor mesh quality for optical image reconstruction, a reality that represents a significant roadblock for translational research of multimodal NIR imaging. This work addresses these challenges directly by introducing automated digital imaging and communications in medicine image stack segmentation and a new one-click three-dimensional mesh generator optimized for multimodal NIR imaging, and combining these capabilities into a single software package (available for free download) with a streamlined workflow. Image processing time and mesh quality benchmarks were examined for four common multimodal NIR use-cases (breast, brain, pancreas, and small animal) and were compared to a commercial image processing package. Applying these tools resulted in a fivefold decrease in image processing time and 62% improvement in minimum mesh quality, in the absence of extra mesh postprocessing. These capabilities represent a significant step toward enabling translational multimodal NIR research for both expert and nonexpert users in an open-source platform.

The dynamic vascular changes in the breast resulting from manipulation of both inspired end-tidal partial pressure of oxygen and carbon dioxide were imaged using a 30 s per frame frequency-domain near-infrared spectral (NIRS) tomography system. By analyzing the images from five subjects with asymptomatic mammography under different inspired gas stimulation sequences, the mixture that maximized tissue vascular and oxygenation changes was established. These results indicate maximum changes in deoxy-hemoglobin, oxygen saturation, and total hemoglobin of 21, 9, and 3%, respectively. Using this inspired gas manipulation sequence, an individual case study of a subject with locally advanced breast cancer undergoing neoadjuvant chemotherapy (NAC) was analyzed. Dynamic NIRS imaging was performed at different time points during treatment. The maximum tumor dynamic changes in deoxy-hemoglobin increased from less than 7% at cycle 1, day 5 (C1, D5) to 17% at (C1, D28), which indicated a complete response to NAC early during treatment and was subsequently confirmed pathologically at the time of surgery.

Small animal fluorescence molecular imaging (FMI) can be a powerful tool for preclinical drug discovery and development studies. However, light absorption by tissue chromophores (e.g., hemoglobin, water, lipids, melanin) typically limits optical signal propagation through thicknesses larger than a few millimeters. Compared to other visible wavelengths, tissue absorption for red and near-infrared (near-IR) light absorption dramatically decreases and non-elastic scattering becomes the dominant light-tissue interaction mechanism. The relatively recent development of fluorescent agents that absorb and emit light in the near-IR range (600-1000 nm), has driven the development of imaging systems and light propagation models that can achieve whole body three-dimensional imaging in small animals. Despite great strides in this area, the ill-posed nature of diffuse fluorescence tomography remains a significant problem for the stability, contrast recovery and spatial resolution of image reconstruction techniques and the optimal approach to FMI in small animals has yet to be agreed on. The majority of research groups have invested in charge-coupled device (CCD)-based systems that provide abundant tissue-sampling but suboptimal sensitivity, while our group and a few others have pursued systems based on very high sensitivity detectors, that at this time allow dense tissue sampling to be achieved only at the cost of low imaging throughput. Here we demonstrate the methodology for applying single-photon detection technology in a fluorescence tomography system to localize a cancerous brain lesion in a mouse model. The fluorescence tomography (FT) system employed single photon counting using photomultiplier tubes (PMT) and information-rich time-domain light detection in a non-contact conformation. This provides a simultaneous collection of transmitted excitation and emission light, and includes automatic fluorescence excitation exposure control, laser referencing, and co-registration with a small animal computed tomography (microCT) system. A nude mouse model was used for imaging. The animal was inoculated orthotopically with a human glioma cell line (U251) in the left cerebral hemisphere and imaged 2 weeks later. The tumor was made to fluoresce by injecting a fluorescent tracer, IRDye 800CW-EGF (LI-COR Biosciences, Lincoln, NE) targeted to epidermal growth factor receptor, a cell membrane protein known to be overexpressed in the U251 tumor line and many other cancers. A second, untargeted fluorescent tracer, Alexa Fluor 647 (Life Technologies, Grand Island, NY) was also injected to account for non-receptor mediated effects on the uptake of the targeted tracers to provide a means of quantifying tracer binding and receptor availability/density. A CT-guided, time-domain algorithm was used to reconstruct the location of both fluorescent tracers (i.e., the location of the tumor) in the mouse brain and their ability to localize the tumor was verified by contrast-enhanced magnetic resonance imaging. Though demonstrated for fluorescence imaging in a glioma mouse model, the methodology presented in this video can be extended to different tumor models in various small animal models potentially up to the size of a rat.

A high frequency ultrasound-coupled fluorescence tomography system, primarily designed for imaging of protoporphyrin IX production in skin tumors in vivo, is demonstrated for the first time. The design couples fiber-based spectral sampling of the protoporphyrin IX fluorescence emission with high frequency ultrasound imaging, allowing thin-layer fluorescence intensities to be quantified. The system measurements are obtained by serial illumination of four linear source locations, with parallel detection at each of five interspersed detection locations, providing 20 overlapping measures of subsurface fluorescence from both superficial and deep locations in the ultrasound field. Tissue layers are defined from the segmented ultrasound images and diffusion theory used to estimate the fluorescence in these layers. The system calibration is presented with simulation and phantom validation of the system in multilayer regions. Pilot in-vivo data are also presented, showing recovery of subcutaneous tumor tissue values of protoporphyrin IX in a subcutaneous U251 tumor, which has less fluorescence than the skin.