3D modeling to predict vascular involvement in resectable pancreatic adenocarcinoma
Background: 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 involvemen...
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Elsevier
2025-01-01
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024175044 |
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| author | Sguinzi R Vidal J Poroes F Bartolucci DA Litchinko A Gossin E Fingerhut A Toso C Buhler L Egger B |
| author_facet | Sguinzi R Vidal J Poroes F Bartolucci DA Litchinko A Gossin E Fingerhut A Toso C Buhler L Egger B |
| author_sort | Sguinzi R |
| collection | DOAJ |
| description | Background: 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. Methods: 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. Results: 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). Conclusions: 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. |
| format | Article |
| id | doaj-art-a0326335041c4b57b069cb0cdfa22d1e |
| institution | Kabale University |
| issn | 2405-8440 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj-art-a0326335041c4b57b069cb0cdfa22d1e2025-01-17T04:51:23ZengElsevierHeliyon2405-84402025-01-01111e414733D modeling to predict vascular involvement in resectable pancreatic adenocarcinomaSguinzi R0Vidal J1Poroes F2Bartolucci DA3Litchinko A4Gossin E5Fingerhut A6Toso C7Buhler L8Egger B9Department of General Surgery, Fribourg Cantonal Hospital, 1700, Fribourg, SwitzerlandDepartment of Radiology, Fribourg Cantonal Hospital, 1700, Fribourg, SwitzerlandDepartment of Radiology, Fribourg Cantonal Hospital, 1700, Fribourg, SwitzerlandDepartment of Radiology, Fribourg Cantonal Hospital, 1700, Fribourg, SwitzerlandDepartment of General Surgery, University Hospital of Geneva, 1205, SwitzerlandUniversity of Fribourg, Faculty of Science and Medicine - Section of Medicine, 1700, Fribourg, SwitzerlandDepartment of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, PR ChinaDepartment of General Surgery, University Hospital of Geneva, 1205, SwitzerlandDepartment of General Surgery, Fribourg Cantonal Hospital, 1700, Fribourg, SwitzerlandDepartment of General Surgery, Fribourg Cantonal Hospital, 1700, Fribourg, Switzerland; University of Fribourg, Faculty of Science and Medicine - Section of Medicine, 1700, Fribourg, Switzerland; Corresponding author. Surgery at the University of Fribourg, Surgery at the University of Bern FMH for Surgery and Visceral Surgery Department of Surgery HFR Fribourg - Cantonal Hospital HFR Fribourg – Cantonal Hospital Chemin des Pensionnats 2-6, Case postale, 1708, Fribourg, Switzerland.Background: 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. Methods: 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. Results: 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). Conclusions: 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.http://www.sciencedirect.com/science/article/pii/S2405844024175044Borderline resectable pancreatic cancer3D rendering3D printingVascular involvement of pancreatic cancerR1 resection |
| spellingShingle | Sguinzi R Vidal J Poroes F Bartolucci DA Litchinko A Gossin E Fingerhut A Toso C Buhler L Egger B 3D modeling to predict vascular involvement in resectable pancreatic adenocarcinoma Heliyon Borderline resectable pancreatic cancer 3D rendering 3D printing Vascular involvement of pancreatic cancer R1 resection |
| title | 3D modeling to predict vascular involvement in resectable pancreatic adenocarcinoma |
| title_full | 3D modeling to predict vascular involvement in resectable pancreatic adenocarcinoma |
| title_fullStr | 3D modeling to predict vascular involvement in resectable pancreatic adenocarcinoma |
| title_full_unstemmed | 3D modeling to predict vascular involvement in resectable pancreatic adenocarcinoma |
| title_short | 3D modeling to predict vascular involvement in resectable pancreatic adenocarcinoma |
| title_sort | 3d modeling to predict vascular involvement in resectable pancreatic adenocarcinoma |
| topic | Borderline resectable pancreatic cancer 3D rendering 3D printing Vascular involvement of pancreatic cancer R1 resection |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024175044 |
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