XRelevanceCAM: towards explainable tissue characterization with improved localisation of pathological structures in probe-based confocal laser endomicroscopy.

PURPOSE: Probe-based confocal laser endomicroscopy (pCLE) enables intraoperative tissue characterization with improved resection rates of brain tumours. Although a plethora of deep learning models have been developed for automating tissue characterization, their lack of transparency is a concern. To tackle this issue, techniques like Class Activation Map (CAM) and its variations highlight image regions related to model decisions. However, they often fall short of providing human-interpretable visual explanations for surgical decision support, primarily due to the shattered gradient problem or insufficient theoretical underpinning. METHODS: In this paper, we introduce XRelevanceCAM, an explanation method rooted in a better backpropagation approach, incorporating sensitivity and conservation axioms. This enhanced method offers greater theoretical foundation and effectively mitigates the shattered gradient issue when compared to other CAM variants. RESULTS: Qualitative and quantitative evaluations are based on ex vivo pCLE data of brain tumours. XRelevanceCAM effectively highlights clinically relevant areas that characterize the tissue type. Specifically, it yields a remarkable 56% improvement over our closest baseline, RelevanceCAM, in the network's shallowest layer as measured by the mean Intersection over Union (mIoU) metric based on ground-truth annotations (from 18 to 28.07%). Furthermore, a 6% improvement in mIoU is observed when generating the final saliency map from all network layers. CONCLUSION: We introduce a new CAM variation, XRelevanceCAM, for precise identification of clinically important structures in pCLE data. This can aid introperative decision support in brain tumour resection surgery, as validated in our performance study.

Development, Implementation and Application of Confocal Laser Endomicroscopy in Brain, Head and Neck Surgery-A Review.

When we talk about visualization methods in surgery, it is important to mention that the diagnosis of tumors and how we define tumor borders intraoperatively in a correct way are two main things that would not be possible to achieve without this grand variety of visualization methods we have at our disposal nowadays. In addition, histopathology also plays a very important role, and its importance cannot be neglected either. Some biopsy specimens, e.g., frozen sections, are examined by a histopathologist and lead to tumor diagnosis and the definition of its borders. Furthermore, surgical resection is a very important point when it comes to prognosis and life survival. Confocal laser endomicroscopy (CLE) is an imaging technique that provides microscopic information on the tissue in real time. CLE of disorders, such as head, neck and brain tumors, has only recently been suggested to contribute to both immediate tumor characterization and detection. It can be used as an additional tool for surgical biopsies during biopsy or surgical procedures and for inspection of resection margins during surgery. In this review, we analyze the development, implementation, advantages and disadvantages as well as the future directions of this technique in neurosurgical and otorhinolaryngological disciplines.

Confocal Laser Endomicroscopy in Oncological Surgery.

The therapy of choice in the treatment of abnormalities in the human body, is to attempt a personalized diagnosis and with minimal invasiveness, ideally resulting in total resection (surgery) or turning off (intervention) of the pathology with preservation of normal functional tissue, followed by additional treatments, e [...].

Real-Time Overlapping of Indocyanine Green-Video Angiography With White Light Imaging for Vascular Neurosurgery: Technique, Implementation, and Clinical Experience.

BACKGROUND: Fluorescent-guided techniques in vascular neurosurgery can be demonstrated via black and white indocyanine green videoangiography (ICG-VA). Multispectral imaging (MFL) is a new method, which overlaps fluorescence with the white light and provides a fluorescent white light augmented reality image to the surgeon. OBJECTIVE: To investigate (a) whether MFL can enhance the visualization of the blood-flow with simultaneous visualization of the anatomic structures and (b) if MFL can ergonomically improve the microvascular surgical treatment compared to ICG-VA. METHODS: A digital imaging of the blood flow after intravenous injection of ICG on 7 pigs was performed in real time under white light, standard fluorescence, and MFL. The blood flow was interrupted with a surgical clip, demonstrating the blockage of the blood flow. We prospectively included 30 patients with vascular deformities. The vasculature was visualized on the microscope's monitor and through the microscope's eyepiece. RESULTS: In the animal experiment, the visualization of the anatomy and the blood flow under MFL produced high resolution images. The occlusion of blood vessels demonstrated sufficiently the blockage of tissue perfusion and its reperfusion after clip removal. During all 30 surgical cases, the MFL technique and the direct delivery of the pseudo-colored image through the eyepiece allowed for enhanced anatomic and dynamic data. CONCLUSION: MFL was shown to be superior to the classic ICG-VA, delivering enhanced data and notably improving the workflow due to the simultaneous and precise white light visualization of the blood flow and the surrounding anatomic structures.