Michael Jermyn

Intraoperative brain cancer detection with Raman spectroscopy in humans

A handheld Raman spectroscopy probe enabled detection of invasive brain cancer intraoperatively in patients with grade 2 to 4 gliomas. Probing for brain tumors Gliomas are invasive cancers, spreading quietly throughout the brain. They pose a formidable challenge to surgeons who try to remove all cancer cells during resection; leaving any cancer behind can lower the patient’s prospects for survival. Jermyn et al. adapted Raman spectroscopy for the operating room by developing an imaging technique that uses a commercially available, handheld contact fiber optic probe. The probe’s optic cables were connected to a near-infrared laser, for stimulating tissue molecules; in turn, these components were linked to a computer to visualize resulting spectra in real time. When held against human brain tissue, the probe measured the Raman scattering signal, which was separated from background signals and differentiated from “normal” tissues using certain algorithms. The authors tested the probe in 17 patients with grade 2 to 4 gliomas who were undergoing surgery and compared imaging results with 161 biopsy samples. Intraoperative Raman imaging allowed the authors to detect both invasive and dense cancer cells with an accuracy of 92%. By comparison, the surgeon, using standard surgical tools like the bright-field microscope and magnetic resonance imaging, identified cancer with 73% accuracy. Such label-free, portable, intraoperative imaging technologies will be important in improving the efficiency of tumor resections and, in turn, for extending survival times of glioma patients. 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.

Phase I/II study of verteporfin photodynamic therapy in locally advanced pancreatic cancer.

Background:Patients with pancreatic cancer have a poor prognosis apart from the few suitable for surgery. Photodynamic therapy (PDT) produces localised tissue necrosis but previous studies using the photosensitiser meso-tetrahydroxyphenylchlorin (mTHPC) caused prolonged skin photosensitivity. This study assessed a shorter acting photosensitiser, verteporfin.Methods:Fifteen inoperable patients with locally advanced cancers were sensitised with 0.4 mg kg−1 verteporfin. After 60–90 min, laser light (690 nm) was delivered via single (13 patients) or multiple (2 patients) fibres positioned percutaneously under computed tomography (CT) guidance, the light dose escalating (initially 5 J, doubling after each three patients) until 12 mm of necrosis was achieved consistently.Results:In all, 12 mm lesions were seen consistently at 40 J, but with considerable variation in necrosis volume (mean volume 3.5 cm3 at 40 J). Minor, self-limiting extrapancreatic effects were seen in multifibre patients. No adverse interactions were seen in patients given chemotherapy or radiotherapy before or after PDT. After PDT, one patient underwent an R0 Whipple’s pancreaticoduodenectomy.Conclusions:Verteporfin PDT-induced tumour necrosis in locally advanced pancreatic cancer is feasible and safe. It can be delivered with a much shorter drug light interval and with less photosensitivity than with older compounds.

Fast segmentation and high-quality three-dimensional volume mesh creation from medical images for diffuse optical tomography

Abstract. 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.

Cherenkov Video Imaging Allows for the First Visualization of Radiation Therapy in Real Time

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.

Predicting Breast Tumor Response to Neoadjuvant Chemotherapy with Diffuse Optical Spectroscopic Tomography prior to Treatment

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. Clin Cancer Res; 20(23); 6006–15. ©2014 AACR.

Characterization of a Raman spectroscopy probe system for intraoperative brain tissue classification

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%.

Imaging targeted-agent binding in vivo with two probes

An approach to quantitatively image targeted-agent binding rate in vivo is demonstrated with dual-probe injection of both targeted and nontargeted fluorescent dyes. Images of a binding rate constant are created that reveal lower than expected uptake of epidermal growth factor in an orthotopic xenograft pancreas tumor (2.3 x 10(-5) s(-1)), as compared to the normal pancreas (3.4 x 10(-5) s(-1)). This approach allows noninvasive assessment of tumor receptor targeting in vivo to determine the expected contrast, spatial localization, and efficacy in therapeutic agent delivery.

System development for high frequency ultrasound-guided fluorescence quantification of skin layers

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.

Neural networks improve brain cancer detection with Raman spectroscopy in the presence of operating room light artifacts

Abstract. 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 vivo Raman spectroscopy can detect these invasive cancer cells in patients with grade 2 to 4 gliomas. The robustness of this Raman signal can be dampened by spectral artifacts generated by lights in the operating room. We found that artificial neural networks (ANNs) can overcome these spectral artifacts using nonparametric and adaptive models to detect complex nonlinear spectral characteristics. Coupling ANN with Raman spectroscopy simplifies the intraoperative use of Raman spectroscopy by limiting changes required to the standard neurosurgical workflow. The ability to detect invasive brain cancer under these conditions may reduce residual cancer remaining after surgery and improve patient survival.

Computed Tomography-guided Time-domain Diffuse Fluorescence Tomography in Small Animals for Localization of Cancer Biomarkers

Small animal fluorescence molecular imaging (FMI) can be a powerful tool for preclinical drug discovery and development studies1. However, light absorption by tissue chromophores (e.g., hemoglobin, water, lipids, melanin) typically limits optical signal propagation through thicknesses larger than a few millimeters2. 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 animals3. 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 sensitivity4-9, while our group and a few others10-13 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 conformation11. This provides a simultaneous collection of transmitted excitation and emission light, and includes automatic fluorescence excitation exposure control14, laser referencing, and co-registration with a small animal computed tomography (microCT) system15. 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 cancers18. 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/density27. 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 rat17.