Julien Pichette

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.

Intraoperative video-rate hemodynamic response assessment in human cortex using snapshot hyperspectral optical imaging

Abstract. Using light, we are able to visualize the hemodynamic behavior of the brain to better understand neurovascular coupling and cerebral metabolism. In vivo optical imaging of tissue using endogenous chromophores necessitates spectroscopic detection to ensure molecular specificity as well as sufficiently high imaging speed and signal-to-noise ratio, to allow dynamic physiological changes to be captured, isolated, and used as surrogate of pathophysiological processes. An optical imaging system is introduced using a 16-bands on-chip hyperspectral camera. Using this system, we show that up to three dyes can be imaged and quantified in a tissue phantom at video-rate through the optics of a surgical microscope. In vivo human patient data are presented demonstrating brain hemodynamic response can be measured intraoperatively with molecular specificity at high speed.

Macroscopic-imaging technique for subsurface quantification of near-infrared markers during surgery

Abstract. 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.

Sensitivity analysis aimed at blood vessels detection using interstitial optical tomography during brain needle biopsy procedures.

A brain needle biopsy procedure is performed for suspected brain lesions in order to sample tissue that is subsequently analysed using standard histopathology techniques. A common complication resulting from this procedure is brain hemorrhaging from blood vessels clipped off during tissue extraction. Interstitial optical tomography (iOT) has recently been introduced by our group as a mean to assess the presence of blood vessels in the vicinity of the needle. The clinical need to improve safety requires the detection of blood vessels within 2 mm from the outer surface of the needle, since this distance is representative of the volume of tissue that is aspirated durirng tissue extraction. Here, a sensitivity analysis is presented to establish the intrinsic detection limits of iOT based on simulations and experiments using brain tissue phantoms. It is demonstrated that absorbers can be detected with diameters >300 μm located up to >2 mm from the biopsy needle core for bulk optical properties consistent with brain tissue.

Imaging system based on diffusive reflectance spectroscopy for blood vessels detection during brain biopsy procedure

During the diagnosis and treatment process for brain cancer, clinicians often need to achieve a brain biopsy to get histological data. However there are risks associated with this procedure: 1) collected samples are not always representative of the tumor and 2) there is a risk of blood vessel rupture when the sample is taken. This type of bleeding occurs between 0.3 and 59.8% of the cases and the mortality rate can be as high as 3.9% (Dammers et al, Woodworth et al). Here we present a diffuse reflectance spectroscopy imaging system directly integrated on a brain biopsy needle to guide surgeon during needle biopsy procedures. To mitigate the risks associated with the procedure, our imaging system combines 18 optical fibers (9 used as white-light sources and 9 used as detectors) to acquire a total of 81 reflectance spectra per acquisition. A tomographic algorithm (Goyette et al) is used to reconstruct an image in the vicinity of the needle based on the optical contrast due to the optical absorption of hemoglobin (Hb) which is the main absorber in brain. The evaluation and characterization tests were first carried out in vitro using tissue-simulating phantoms reproducing human brain optical properties (absorption and scattering).

Intraoperative brain hemodynamic response assessment with real-time hyperspectral optical imaging(Conference Presentation)

Following normal neuronal activity, there is an increase in cerebral blood flow and cerebral blood volume to provide oxygenated hemoglobin to active neurons. For abnormal activity such as epileptiform discharges, this hemodynamic response may be inadequate to meet the high metabolic demands. To verify this hypothesis, we developed a novel hyperspectral imaging system able to monitor real-time cortical hemodynamic changes during brain surgery. The imaging system is directly integrated into a surgical microscope, using the white-light source for illumination. A snapshot hyperspectral camera is used for detection (4x4 mosaic filter array detecting 16 wavelengths simultaneously). We present calibration experiments where phantoms made of intralipid and food dyes were imaged. Relative concentrations of three dyes were recovered at a video rate of 30 frames per second. We also present hyperspectral recordings during brain surgery of epileptic patients with concurrent electrocorticography recordings. Relative concentration maps of oxygenated and deoxygenated hemoglobin were extracted from the data, allowing real-time studies of hemodynamic changes with a good spatial resolution. Finally, we present preliminary results on phantoms obtained with an integrated spatial frequency domain imaging system to recover tissue optical properties. This additional module, used together with the hyperspectral imaging system, will allow quantification of hemoglobin concentrations maps. Our hyperspectral imaging system offers a new tool to analyze hemodynamic changes, especially in the case of epileptiform discharges. It also offers an opportunity to study brain connectivity by analyzing correlations between hemodynamic responses of different tissue regions.

Multimodal optical biopsy probe to improve the safety and diagnostic yield of brain needle biopsies (Conference Presentation)

Brain needle biopsy (BNB) is performed to collect tissue when precise neuropathological diagnosis is required to provide information about tumor type, grade, and growth patterns. The principal risks associated with this procedure are intracranial hemorrhage (due to clipping blood vessels during tissue extraction), incorrect tumor typing/grading due to non-representative or non-diagnostic samples (e.g. necrotic tissue), and missing the lesion. We present an innovative device using sub-diffuse optical tomography to detect blood vessels and Raman spectroscopy to detect molecular differences between tissue types, in order to reduce the risks of misdiagnosis, incorrect tumour grading, and non-diagnostic samples. The needle probe integrates optical fibers directly onto the external cannula of a commercial BNB needle, and can perform measurements for both optical techniques through the same fibers. This integrated optical spectroscopy system uses diffuse reflectance signals to perform a 360-degree reconstruction of the tissue adjacent to the biopsy needle, based on the optical contrast associated with hemoglobin light absorption, thereby localizing blood vessels. Raman spectra measurements are also performed interstitially for tissue characterization. A detailed sensitivity of the system is presented to demonstrate that it can detect absorbers with diameters <300 µm located up to ∼2 mm from the biopsy needle core, for bulk optical properties consistent with brain tissue. Results from animal experiments are presented to validate blood vessel detection and Raman spectrum measurement without disruption of the surgical workflow. We also present phantom measurements of Raman spectra with the needle probe and a comparison with a clinically validated Raman spectroscopy probe.

Intraoperative detection of glioma invasion beyond MRI enhancement with Raman spectroscopy in humans

Cancer tissue is frequently impossible to distinguish from normal brain during surgery. Gliomas are a class of brain cancer which invade into the normal brain. If left unresected, these invasive cancer cells are the source of glioma recurrence. Moreover, these invasion areas do not show up on standard-of-care pre-operative Magnetic Resonance Imaging (MRI). This inability to fully visualize invasive brain cancers results in subtotal surgical resections, negatively impacting patient survival. To address this issue, we have demonstrated the efficacy of single-point in vivo Raman spectroscopy using a contact hand-held fiber optic probe for rapid detection of cancer invasion in 8 patients with low and high grade gliomas. Using a supervised machine learning algorithm to analyze the Raman spectra obtained in vivo, we were able to distinguish normal brain from the presence of cancer cells with sensitivity and specificity greater than 90%. Moreover, by correlating these results with pre-operative MRI we demonstrate the ability to detect low density cancer invasion up to 1.5cm beyond the cancer extent visible using MRI. This represents the potential for significant improvements in progression-free and overall patient survival, by identifying previously undetectable residual cancer cell populations and preventing the resection of normal brain tissue. While the importance of maximizing the volume of tumor resection is important for all grades of gliomas, the impact for low grade gliomas can be dramatic because surgery can even be curative. This convenient technology can rapidly classify cancer invasion in real-time, making it ideal for intraoperative use in brain tumor resection.