Artificial intelligence and hyperspectral imaging for image-guided assistance in minimally invasive surgery

BACKGROUNDIntraoperative imaging assists surgeons during minimally invasive procedures. Hyperspectral imaging (HSI) is a noninvasive and noncontact optical technique with great diagnostic potential in medicine. The combination with artificial intelligence (AI) approaches to analyze HSI data is calle...

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Veröffentlicht in:Chirurgie (Heidelberg, Germany) Germany), 2022-10, Vol.93 (10), p.940-947
Hauptverfasser: Chalopin, Claire, Nickel, Felix, Pfahl, Annekatrin, Köhler, Hannes, Maktabi, Marianne, Thieme, René, Sucher, Robert, Jansen-Winkeln, Boris, Studier-Fischer, Alexander, Seidlitz, Silvia, Maier-Hein, Lena, Neumuth, Thomas, Melzer, Andreas, Müller-Stich, Beat Peter, Gockel, Ines
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Zusammenfassung:BACKGROUNDIntraoperative imaging assists surgeons during minimally invasive procedures. Hyperspectral imaging (HSI) is a noninvasive and noncontact optical technique with great diagnostic potential in medicine. The combination with artificial intelligence (AI) approaches to analyze HSI data is called intelligent HSI in this article. OBJECTIVEWhat are the medical applications and advantages of intelligent HSI for minimally invasive visceral surgery? MATERIAL AND METHODSWithin various clinical studies HSI data from multiple in vivo tissue types and oncological resections were acquired using an HSI camera system. Different AI algorithms were evaluated for detection and discrimination of organs, risk structures and tumors. RESULTSIn an experimental animal study 20 different organs could be differentiated with high precision (> 95%) using AI. In vivo, the parathyroid glands could be discriminated from surrounding tissue with an F1 score of 47% and sensitivity of 75%, and the bile duct with an F1 score of 79% and sensitivity of 90%. Furthermore, ex vivo tumor tissue could be successfully detected with an area under the receiver operating characteristic (ROC) curve (AUC) larger than 0.91. DISCUSSIONThis study demonstrates that intelligent HSI can automatically and accurately detect different tissue types. Despite great progress in the last decade intelligent HSI still has limitations. Thus, accurate AI algorithms that are easier to understand for the user and an extensive standardized and continuously growing database are needed. Further clinical studies should support the various medical applications and lead to the adoption of intelligent HSI in the clinical routine practice.
ISSN:2731-698X
DOI:10.1007/s00104-022-01677-w