R Sguinzi, J Vidal, F Poroes, DA Bartolucci, A Litchinko, E Gossin, A Fingerhut, C Toso, L Buhler, B Egger
Department of General Surgery, Fribourg Cantonal Hospital, 1700, Fribourg, Switzerland.
Department of Radiology, Fribourg Cantonal Hospital, 1700, Fribourg, Switzerland.
Heliyon. 2024 Dec 27;11(1):e41473. doi: 10.1016/j.heliyon.2024.e41473. eCollection 2025 Jan 15.
Current management of patients with borderline resectable pancreatic adenocarcinoma (BR-PDAC) depends on the degree of involvement of the major arterial and venous structures. The aim of this study was to evaluate 3D segmentation and printing to predict tumor size and vascular involvement of BR-PDAC to improve pre-operative planning of vascular resection and better select patients for neoadjuvant therapy.
We retrospectively evaluated 16 patients with BR-PDAC near vascular structures who underwent pancreatoduodenectomy (PD) with or without vascular resection between 2015 and 2021. The pre-operative computed tomography (CT) images were processed by segmentation with 3D reconstruction and printed as 3D models. Two radiologists specialized in pancreatic imaging and two pancreatic surgeons blindly and independently analyzed the pre-operative CT scans and 3D models using a defined checklist. Their evaluations were compared to the pre-operative 2D-CT reports utilized for patient management. A positive delta was defined by the 3D analysis resulting in greater accuracy in predicting vascular involvement as proven intraoperatively or histopathologically.
Fourteen PD, one total pancreatectomy, and one exploratory laparotomy were performed. Ten patients had a positive delta concerning vascular involvement of the superior mesenteric or portal vein. Tumor extension was also more accurately evaluated by 3D modeling than by 2D-CT (p < 0.05).
Our pilot study demonstrates that 3D segmentation can provide additional information for choosing the best treatment strategy and surgical plain in patients with BR-PDAC. Especially for upcoming mini-invasive techniques like laparoscopic and robotic resections, better pre-operative planning is essential to allow safety and prevent vascular injury.
目前，临界可切除胰腺腺癌（BR-PDAC）患者的治疗方案取决于主要动静脉结构的受累程度。本研究旨在评估三维分割和打印技术，以预测BR-PDAC的肿瘤大小和血管受累情况，从而改善血管切除术前规划，并更好地为新辅助治疗选择合适的患者。
我们回顾性评估了2015年至2021年间16例靠近血管结构的BR-PDAC患者，这些患者接受了有或无血管切除的胰十二指肠切除术（PD）。术前计算机断层扫描（CT）图像通过三维重建分割处理，并打印为三维模型。两名专门从事胰腺影像诊断的放射科医生和两名胰腺外科医生使用既定清单对术前CT扫描和三维模型进行了盲法独立分析。他们的评估结果与用于患者管理的术前二维CT报告进行了比较。三维分析在预测血管受累方面具有更高的准确性（术中或组织病理学证实），则定义为阳性差异。
共进行了1例全胰切除术、1例剖腹探查术和14例胰十二指肠切除术。10例患者在肠系膜上静脉或门静脉血管受累方面存在阳性差异。与二维CT相比，三维建模对肿瘤范围的评估也更准确（p < 0.05）。
我们的初步研究表明，三维分割可为BR-PDAC患者选择最佳治疗策略和手术方案提供额外信息。特别是对于即将开展的腹腔镜和机器人切除等微创技术，更好的术前规划对于确保手术安全和预防血管损伤至关重要。
