Hyperspectral Imaging of the Hemodynamic and Metabolic States of the Exposed Cortex: Investigating a Commercial Snapshot Solution

Lightfield hyperspectral imaging in neuro-oncology surgery: an IDEAL 0 and 1 study

Introduction

Hyperspectral imaging (HSI) has shown promise in the field of intra-operative imaging and tissue differentiation as it carries the capability to provide real-time information invisible to the naked eye whilst remaining label free. Previous iterations of intra-operative HSI systems have shown limitations, either due to carrying a large footprint limiting ease of use within the confines of a neurosurgical theater environment, having a slow image acquisition time, or by compromising spatial/spectral resolution in favor of improvements to the surgical workflow. Lightfield hyperspectral imaging is a novel technique that has the potential to facilitate video rate image acquisition whilst maintaining a high spectral resolution. Our pre-clinical and first-in-human studies (IDEAL 0 and 1, respectively) demonstrate the necessary steps leading to the first in-vivo use of a real-time lightfield hyperspectral system in neuro-oncology surgery.

Methods

A lightfield hyperspectral camera (Cubert Ultris ×50) was integrated in a bespoke imaging system setup so that it could be safely adopted into the open neurosurgical workflow whilst maintaining sterility. Our system allowed the surgeon to capture in-vivo hyperspectral data (155 bands, 350-1,000 nm) at 1.5 Hz. Following successful implementation in a pre-clinical setup (IDEAL 0), our system was evaluated during brain tumor surgery in a single patient to remove a posterior fossa meningioma (IDEAL 1). Feedback from the theater team was analyzed and incorporated in a follow-up design aimed at implementing an IDEAL 2a study.

Results

Focusing on our IDEAL 1 study results, hyperspectral information was acquired from the cerebellum and associated meningioma with minimal disruption to the neurosurgical workflow. To the best of our knowledge, this is the first demonstration of HSI acquisition with 100+ spectral bands at a frame rate over 1Hz in surgery.

Discussion

This work demonstrated that a lightfield hyperspectral imaging system not only meets the design criteria and specifications outlined in an IDEAL-0 (pre-clinical) study, but also that it can translate into clinical practice as illustrated by a successful first in human study (IDEAL 1). This opens doors for further development and optimisation, given the increasing evidence that hyperspectral imaging can provide live, wide-field, and label-free intra-operative imaging and tissue differentiation.

Review on the Application of Hyperspectral Imaging Technology of the Exposed Cortex in Cerebral Surgery

The study of brain science is vital to human health. The application of hyperspectral imaging in biomedical fields has grown dramatically in recent years due to their unique optical imaging method and multidimensional information acquisition. Hyperspectral imaging technology can acquire two-dimensional spatial information and one-dimensional spectral information of biological samples simultaneously, covering the ultraviolet, visible and infrared spectral ranges with high spectral resolution, which can provide diagnostic information about the physiological, morphological and biochemical components of tissues and organs. This technology also presents finer spectral features for brain imaging studies, and further provides more auxiliary information for cerebral disease research. This paper reviews the recent advance of hyperspectral imaging in cerebral diagnosis. Firstly, the experimental setup, image acquisition and pre-processing, and analysis methods of hyperspectral technology were introduced. Secondly, the latest research progress and applications of hyperspectral imaging in brain tissue metabolism, hemodynamics, and brain cancer diagnosis in recent years were summarized briefly. Finally, the limitations of the application of hyperspectral imaging in cerebral disease diagnosis field were analyzed, and the future development direction was proposed.

Detection of cutaneous oxygen saturation using a novel snapshot hyperspectral camera: a feasibility study

Background

Tissue necrosis, a consequence of inadequate tissue oxygenation, is a common post-operative complication. As current surgical assessments are often limited to visual and tactile feedback, additional techniques that can aid in the interrogation of tissue viability are needed to improve patient outcomes. In this bi-institutional pilot study, the performance of a novel snapshot hyperspectral imaging camera to detect superficial cutaneous oxygen saturation (StO₂) was evaluated.

Methods

Healthy human volunteers were recruited at two participating centers. Cutaneous StO₂ of the forearm was determined by a snapshot hyperspectral camera on two separate study days during occlusion-reperfusion of the brachial artery and after induction of local vasodilation. To calculate the blood StO₂ at each pixel in the multispectral image, spectra were selected, and fitting was performed over wavelengths ranging from 470 to 950 nm.

Results

Quantitative detection of physiological changes in cutaneous StO₂ levels was feasible in all sixteen volunteers. A significant (P<0.001) decrease in cutaneous StO₂ levels from 78.3% (SD: 15.3) at baseline to 60.6% (SD: 19.8) at the end of occlusion phase was observed, although StO₂ levels returned to baseline after five minutes. Mean cutaneous StO₂ values were similar in the same subjects on separate study days (Pearson R2: 0.92 and 0.77, respectively) at both centers. Local vasodilation did not yield significant changes in cutaneous StO₂ values.

Conclusions

This pilot study demonstrated the feasibility of a snapshot hyperspectral camera for detecting quantitative physiological changes in cutaneous StO₂ in normal human volunteers, and serves as a precursor for further validation in perioperative studies.

Optimal Spectral Combination of a Hyperspectral Camera for Intraoperative Hemodynamic and Metabolic Brain Mapping

Intraoperative optical imaging is a localization technique for the functional areas of the human brain cortex during neurosurgical procedures. These areas are assessed by monitoring the oxygenated (HbO2) and deoxygenated hemoglobin (Hb) concentration changes occurring in the brain. Sometimes, the functional status of the brain is assessed using metabolic biomarkers: the oxidative state of cytochrome-c-oxidase (oxCCO). A setup composed of a white light source and a hyperspectral or a standard RGB camera could be used to identify the functional areas. The choice of the best spectral configuration is still based on an empirical approach. We propose in this study a method to define the optimal spectral combinations of a commercial hyperspectral camera for the computation of hemodynamic and metabolic brain maps. The method is based on a Monte Carlo framework that simulates the acquisition of the intrinsic optical signal following a neuronal activation. The results indicate that the optimal spectral combination of a hyperspectral camera aims to accurately quantify the HbO2 (0.5% error), Hb (4.4% error), and oxCCO (15% error) responses in the brain following neuronal activation. We also show that RGB imaging is a low cost and accurate solution to compute Hb maps (4% error), but not accurate to compute HbO2 (48% error) or oxCCO (1036% error) maps.