HEPATIC VCAR

Hepatic VCAR is a CT image analysis software package intended to aid clinicians in assessing liver morphology and lesions from DICOM 3.0 CT scans through automated segmentation and quantitative analysis. It utilizes advanced algorithms for 3D visualization, liver and lesion segmentation, vessel analysis, and features like a virtual scalpel, with user oversight for final contour adjustments.

Hepatic VCAR is a CT image analysis software package designed for the analysis and visualization of liver CT data obtained from DICOM 3.0 compliant CT scans. Its primary purpose is to assist clinicians in assessing liver morphology, including the identification and measurement of liver lesions, provided these lesions exhibit a different CT appearance from the surrounding liver tissue. The software facilitates tracking changes in liver morphology and lesions over time through automated tools for segmenting and measuring the liver, liver lobes, liver segments, and lesions. Key functionalities of Hepatic VCAR include lesion segmentation, liver segmentation, portal vein segmentation, separation of liver segments based on portal vein branches, and a 'Virtual Scalpel' feature. The software provides initial 3D segmentation, vessel analysis, visualization, and quantitative analysis of liver anatomy. Users retain the ability to manually adjust the automatically generated contours and confirm the final segmentation. Hepatic VCAR can be deployed as a standalone post-processing application on GE Healthcare's AW VolumeShare 5 workstation and AW Server image processing platforms.

AI Regulatory Concerns

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• Q1. What is the quantitative accuracy and reproducibility of the automated liver and lesion segmentation algorithms compared to manual segmentation by expert radiologists across diverse patient populations and lesion types?; How does the 'Virtual Scalpel' feature account for anatomical variability and potential intraoperative changes when used for pre-surgical planning?; Are there specific CT acquisition parameters or contrast enhancement protocols recommended to optimize the performance of Hepatic VCAR's segmentation and analysis tools?; What is the minimum detectable change in lesion size or morphology over time that Hepatic VCAR can reliably quantify?; How does the software handle challenging cases, such as livers with diffuse disease, multiple closely spaced lesions, or images with significant artifacts?