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CT Rendering and Radiomics Analysis in Post-Chemotherapy Retroperitoneal Lymph Node Dissection for Testicular Cancer To Anticipate Difficulties for Young Surgeons
Scavuzzo, A.; Figueroa-Rodriguez, P.; Stefano, A.; Jimenez Guedulain, N.; Muruato Araiza, S.; Cendejas Gomez, J.J.; Quiroz Compeaán, A.; Victorio Vargas, D.O.; Jiménez-Ríos, M.A. CT Rendering and Radiomic Analysis in Post-Chemotherapy Retroperitoneal Lymph Node Dissection for Testicular Cancer to Anticipate Difficulties for Young Surgeons. J. Imaging2023, 9, 71.
Scavuzzo, A.; Figueroa-Rodriguez, P.; Stefano, A.; Jimenez Guedulain, N.; Muruato Araiza, S.; Cendejas Gomez, J.J.; Quiroz Compeaán, A.; Victorio Vargas, D.O.; Jiménez-Ríos, M.A. CT Rendering and Radiomic Analysis in Post-Chemotherapy Retroperitoneal Lymph Node Dissection for Testicular Cancer to Anticipate Difficulties for Young Surgeons. J. Imaging 2023, 9, 71.
Scavuzzo, A.; Figueroa-Rodriguez, P.; Stefano, A.; Jimenez Guedulain, N.; Muruato Araiza, S.; Cendejas Gomez, J.J.; Quiroz Compeaán, A.; Victorio Vargas, D.O.; Jiménez-Ríos, M.A. CT Rendering and Radiomic Analysis in Post-Chemotherapy Retroperitoneal Lymph Node Dissection for Testicular Cancer to Anticipate Difficulties for Young Surgeons. J. Imaging2023, 9, 71.
Scavuzzo, A.; Figueroa-Rodriguez, P.; Stefano, A.; Jimenez Guedulain, N.; Muruato Araiza, S.; Cendejas Gomez, J.J.; Quiroz Compeaán, A.; Victorio Vargas, D.O.; Jiménez-Ríos, M.A. CT Rendering and Radiomic Analysis in Post-Chemotherapy Retroperitoneal Lymph Node Dissection for Testicular Cancer to Anticipate Difficulties for Young Surgeons. J. Imaging 2023, 9, 71.
Abstract
Post chemotherapy retroperitoneal lymph node dissection (PC-RPLND) in non-seminomatous germ-cell tumours (NSTGCTs) is a complex procedure. We evaluated whether 3D computed tomography (CT) rendering and their radiomics analysis help predict resectability by junior surgeons. The ambispective analysis was performed between 2016-2021. Prospective group (A) of 30 patients undergoing CT were segmented using 3D slicer software while retrospective group (B) of 30 patients were evaluated with conventional CT (without 3D reconstruction). CatFisher’s exact test showed a p-value of 0.13 for group A and 1.0 for Group B. Difference between proportion test showed a p-value of 0.009149 (IC 0.1-0.63). Proportion of correct classification showed a p-value of 0.645 (IC 0.55-0.87) for A, and 0.275 (IC 0.11-0.43) for Group B. Furthermore, 13 shape features were extracted: elongation, flatness, volume, sphericity, surface area, among others. Performing logistic regression with the entire dataset, n=60, the results were: Accuracy: 0.7, Precision: 0.65. Using n=30 randomly chosen, the best result obtained was Accuracy: 0.73, Precision: 0.83, with a p-value: 0.025 for Fisher's exact test. In conclusion, the results showed a significant difference in the prediction of resectability with conventional CT versus 3D reconstruction by junior surgeon versus experienced surgeon. Radiomics features used to elaborate an artificial intelligence model improve the prediction of resectability. The proposed model could be of great support in a university hospital, allowing to plan the surgery and to anticipate complications.
Keywords
testicular cancer; radiomics; retroperitoneal surgery
Subject
Medicine and Pharmacology, Urology and Nephrology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.