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Session: Onco
Session starts: Friday 27 January, 11:30
Presentation starts: 12:00
Room: Room 558

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Diederik Rasenberg ()
Mark Ramaekers ()
Misha Luyer ()

Abstract:
Background. Pancreatoduodenectomy is the cornerstone of surgical treatment for patients diagnosed with pancreatic head cancer. Preoperative planning is essential to assess vascular involvement of the tumor or aberrant arterial anatomy, however this requires specific expertise and can be challenging. Computer-aided detection (CAD) algorithms based on artificial intelligence techniques can provide pixel-level segmentations of the pancreatic tumor and may provide information on the resectability. This study assess the added value of three-dimensional (3D) patient models and computer-aided detection algorithms in determining resectability of pancreatic head tumors. Methods. This study included 14 hepatopancreatobiliary experts (13 surgeons and 1 radiologist) from 8 different hospitals. Participants assessed pancreatic tumors in a simulated setting via a crossover design. Three radiologically resectable and three radiologically borderline resectable cases were included. Groups were divided in controls (using CT-scan), a 3D-group (using CT-scan and 3D models) and a CAD-group (using CT-scan, 3D and CAD). Perceived fulfilment of preoperative evaluation needs, the quality and confidence of clinical decision-making were evaluated between groups. Results. A higher perceived ability to determine degrees and length of tumor-vessel contact was reported in the CAD-group compared to controls (P = 0.022 and P = 0.003, respectively). Lower degrees of tumor-vessel contact were predicted for radiologically borderline resectable tumors in the CAD-group compared to controls (P = 0.037). Higher confidence levels were observed in predicting the need for vascular resection in the 3D-group compared to the control group (P = 0.033) for all cases combined. Conclusion. CAD (including 3D) improved the perceived ability for experts to accurately assess vessel involvement compared to conventional CT evaluation. CAD and 3D are evolving techniques that may result in better diagnosis and treatment of pancreatic cancer.