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A Safe Framework for Quantitative In Vivo Human Evaluation of Image Guidance

Piper C. Cannon, James M. Ferguson, E. Pitt, Jason Shrand, Shaan Setia, Naren Nimmagadda, Eric J. Barth, Nicholas Kavoussi, Robert L. Galloway, S. Duke Herrell, Robert J. Webster

发表年份
2023
引用次数
2
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摘要

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Goal:</i> We present a new framework for in vivo image guidance evaluation and provide a case study on robotic partial nephrectomy. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Methods:</i> This framework (called the “bystander protocol”) involves two surgeons, one who solely performs the therapeutic process without image guidance, and another who solely periodically collects data to evaluate image guidance. This isolates the evaluation from the therapy, so that in-development image guidance systems can be tested without risk of negatively impacting the standard of care. We provide a case study applying this protocol in clinical cases during robotic partial nephrectomy surgery. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Results:</i> The bystander protocol was performed successfully in 6 patient cases. We find average lesion centroid localization error with our IGS system to be 6.5 mm in vivo compared to our prior result of 3.0 mm in phantoms. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Conclusions</i> : The bystander protocol is a safe, effective method for testing in-development image guidance systems in human subjects.

关键词

Protocol (science)Bystander effectComputer scienceImage (mathematics)MedicineComputer visionCentroidIn vivoMedical physicsArtificial intelligence

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