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Integration of indocyanine green videoangiography with operative microscope: augmented reality for interactive assessment of vascular structures and blood flow.

ABSTRACT: Preservation of adequate blood flow and exclusion of flow from lesions are key concepts of vascular neurosurgery. Indocyanine green (ICG) fluorescence videoangiography is now widely used for the intraoperative assessment of vessel patency.Here, we present a proof-of-concept investigation of fluorescence angiography with augmented microscopy enhancement: real-time overlay of fluorescence videoangiography within the white light field of view of conventional operative microscopy.The femoral artery was exposed in 7 anesthetized rats. The dissection microscope was augmented to integrate real-time electronically processed near-infrared filtered images with conventional white light images seen through the standard oculars. This was accomplished by using an integrated organic light-emitting diode display to yield superimposition of white light and processed near-infrared images. ICG solution was injected into the jugular vein, and fluorescent femoral artery flow was observed.Fluorescence angiography with augmented microscopy enhancement was able to detect ICG fluorescence in a small artery of interest. Fluorescence appeared as a bright-green signal in the ocular overlaid with the anatomic image and limited to the anatomic borders of the femoral artery and its branches. Surrounding anatomic structures were clearly visualized. Observation of ICG within the vessel lumens permitted visualization of the blood flow. Recorded video loops could be reviewed in an offline mode for more detailed assessment of the vasculature.The overlay of fluorescence videoangiography within the field of view of the white light operative microscope allows real-time assessment of the blood flow within vessels during simultaneous surgical manipulation. This technique could improve intraoperative decision making during complex neurovascular procedures.

SUBMITTER: Martirosyan NL

PROVIDER: S-EPMC5399681 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

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Integration of indocyanine green videoangiography with operative microscope: augmented reality for interactive assessment of vascular structures and blood flow.

Martirosyan Nikolay L NL Skoch Jesse J Watson Jeffrey R JR Lemole G Michael GM Romanowski Marek M Anton Rein R

Neurosurgery 20150601

<h4>Background</h4>Preservation of adequate blood flow and exclusion of flow from lesions are key concepts of vascular neurosurgery. Indocyanine green (ICG) fluorescence videoangiography is now widely used for the intraoperative assessment of vessel patency.<h4>Objective</h4>Here, we present a proof-of-concept investigation of fluorescence angiography with augmented microscopy enhancement: real-time overlay of fluorescence videoangiography within the white light field of view of conventional ope ...[more]

PMID: 25710107

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Project description:There have been few anatomical structure segmentation studies using deep learning. Numbers of training and ground truth images applied were small and the accuracies of which were low or inconsistent. For a surgical video anatomy analysis, various obstacles, including a variable fast-changing view, large deformations, occlusions, low illumination, and inadequate focus occur. In addition, it is difficult and costly to obtain a large and accurate dataset on operational video anatomical structures, including arteries. In this study, we investigated cerebral artery segmentation using an automatic ground-truth generation method. Indocyanine green (ICG) fluorescence intraoperative cerebral videoangiography was used to create a ground-truth dataset mainly for cerebral arteries and partly for cerebral blood vessels, including veins. Four different neural network models were trained using the dataset and compared. Before augmentation, 35,975 training images and 11,266 validation images were used. After augmentation, 260,499 training and 90,129 validation images were used. A Dice score of 79% for cerebral artery segmentation was achieved using the DeepLabv3+ model trained using an automatically generated dataset. Strict validation in different patient groups was conducted. Arteries were also discerned from the veins using the ICG videoangiography phase. We achieved fair accuracy, which demonstrated the appropriateness of the methodology. This study proved the feasibility of operating field view of the cerebral artery segmentation using deep learning, and the effectiveness of the automatic blood vessel ground truth generation method using ICG fluorescence videoangiography. Using this method, computer vision can discern blood vessels and arteries from veins in a neurosurgical microscope field of view. Thus, this technique is essential for neurosurgical field vessel anatomy-based navigation. In addition, surgical assistance, safety, and autonomous surgery neurorobotics that can detect or manipulate cerebral vessels would require computer vision to identify blood vessels and arteries.

Project description:Objective:Hyperperfusion syndrome (HPS) after bypass surgery for moyamoya disease (MMD) mainly results from redistribution of blood flow, which leads to poor outcomes, while effective methods to predict HPS are still lacking. Indocyanine green (ICG) videoangiography can assess regional cerebral blood flow changes semiquantitatively with the application of FLOW 800 software. The purpose of this study was to investigate whether the intraoperative evaluation of local hemodynamic changes around anastomotic sites using FLOW 800 videoangiography mapping can predict the incidence of HPS and clinical outcomes. Methods:Of the patients who were diagnosed with MMD in our hospital between August 2018 and December 2019, who underwent superficial temporal artery-middle cerebral artery bypass surgeries, we investigated 65 hemispheres (in 62 patients) in which intraoperative ICG analysis was performed using FLOW 800 (Zeiss Meditec, Oberkochen, Germany) to evaluate the local cerebral hemodynamics before and after anastomosis. Regions of interest were set at more than 2 points on the brain surface according to the location and situation of recipient arteries in the surgical area. Peak cerebral blood volume (CBV), regional cerebral blood flow (CBF), and time to peak (TTP) were calculated from the selected points. As the data were available intraoperatively, anastomoses were performed in a suitable area. According to the occurrence of HPS, patients were divided into the asymptomatic and symptomatic groups, from which hemodynamic parameters were compared. Furthermore, ROC analysis was performed to determine the diagnostic accuracy of change rates in CBV, CBF, and TTP (i.e., ?CBV, ?CBF, and ?TTP) for predicting HPS. Results:Data from the 62 patients were analyzed, and all patients were closely assessed during hospitalization after the procedures. The values of ?CBV and ?CBF were significantly higher in the symptomatic group (p < 0.01), while ?TTP is slightly lower in the symptomatic group with no statistical differences (p = 0.72). Hemodynamic parameters including ?CBV and ?CBF, calculated by FLOW 800, had high sensitivity and specificity according to the ROC curve (?CBV: AUC = 0.743, 95% CI, 0.605-0.881, p = 0.002; ?CBF: AUC = 0.852, 95% CI, 0.750-0.954, p < 0.01), which could be used as predictors for HPS. Conclusions:Intraoperative ICG-FLOW 800 videoangiography mapping is a safe method which can reflect hemodynamic characteristics in the surgical area for MMD, the findings of which correlate with the occurrence of HPS. Parameters including ?CBV and ?CBF are proven to be efficient in the prediction of HPS.

Dataset Information

Integration of indocyanine green videoangiography with operative microscope: augmented reality for interactive assessment of vascular structures and blood flow.

Publications

Integration of indocyanine green videoangiography with operative microscope: augmented reality for interactive assessment of vascular structures and blood flow.

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