Giuseppe Vizzielli1, Francesco Cosentino2, Diego Raimondo3, Luigi C Turco2, Virginia Vargiu4, Raffaella Iodice3, Manuela Mastronardi3, Mohamed Mabrouk5, Giovanni Scambia1,4, Renato Seracchioli3. 1. Department of Women's and Children's Health and Public Health, Fondazione Policlinico Universitario "Agostino Gemelli" IRCCS, Rome, Italy. 2. Division of Gynecologic Oncology, Gemelli Molise, Campobasso, Italy. 3. Department of Gynecology and Human Reproduction Physiopathology, Department of Medical and Surgical Sciences, S. Orsola Hospital, University of Bologna, Bologna, Italy. 4. Università Cattolica del Sacro Cuore, Rome, Italy. 5. Department of Obstetrics and Gynecology, Faculty of Medicine, University of Cambridge, Cambridge, UK.
Abstract
INTRODUCTION: The complete surgical removal of endometriosis lesions is not always feasible because some implants may be very small or hidden. The use of intraoperative near-infrared radiation (NIR) imaging after intravenous injection of indocyanine green (ICG) coupled with robotic technical advances, including 3-dimensional (3D) and high-resolution vision, might improve detection rates. MATERIAL AND METHODS: This is a retrospective, multicenter case-control study (Canadian Task Force classification II-2) on medical records of women with endometriosis who underwent surgery at the Catholic University of Rome (Controls) and the University of Bologna (Cases) between January 2016 and March 2018. Surgical and post-surgical data from the procedures were collected. We compared the visual detection rate of endometriotic lesions using near-infrared radiation imaging after intravenous injection of indocyanine green (NIR-ICG) in Real 3D (Cases) with the 2D Camera approach (Controls) in symptomatic women with pelvic endometriosis. RESULTS: Twenty cases were matched as closely as possible with 27 controls. The numbers of suspected lesions identified both with the white light and the NIR-ICG approach were 116 and 70 in the Controls (2D) and Cases (3D), respectively. Among them, 16 of 116 controls (13.8%) and 12 of 70 cases (17.1%) were identified using only NIR-ICG imaging and collected as occult lesions (P = .536). The overall NIR-ICG lesion identification showed a positive predictive value of 97.8%, negative predictive value of 82.3%, sensitivity of 82.0%, and specificity of 97.9% for the Control group, and a positive predictive value of 100%, negative predictive value of 97.1%, sensitivity of 97.1%, and specificity of 100% for the Case group, confirming that NIR-ICG imaging is a good diagnostic and screening test (P = .643 and P = .791, according to the Cohen κ tests, respectively for the laparoscopic and robotic groups). CONCLUSIONS: The few differences observed did not seem to be clinically relevant, making the 2 procedures comparable in terms of the ability to visually detect endometriotic lesions. Further prospective trials are needed to confirm our results.
INTRODUCTION: The complete surgical removal of endometriosis lesions is not always feasible because some implants may be very small or hidden. The use of intraoperative near-infrared radiation (NIR) imaging after intravenous injection of indocyanine green (ICG) coupled with robotic technical advances, including 3-dimensional (3D) and high-resolution vision, might improve detection rates. MATERIAL AND METHODS: This is a retrospective, multicenter case-control study (Canadian Task Force classification II-2) on medical records of women with endometriosis who underwent surgery at the Catholic University of Rome (Controls) and the University of Bologna (Cases) between January 2016 and March 2018. Surgical and post-surgical data from the procedures were collected. We compared the visual detection rate of endometriotic lesions using near-infrared radiation imaging after intravenous injection of indocyanine green (NIR-ICG) in Real 3D (Cases) with the 2D Camera approach (Controls) in symptomatic women with pelvic endometriosis. RESULTS: Twenty cases were matched as closely as possible with 27 controls. The numbers of suspected lesions identified both with the white light and the NIR-ICG approach were 116 and 70 in the Controls (2D) and Cases (3D), respectively. Among them, 16 of 116 controls (13.8%) and 12 of 70 cases (17.1%) were identified using only NIR-ICG imaging and collected as occult lesions (P = .536). The overall NIR-ICG lesion identification showed a positive predictive value of 97.8%, negative predictive value of 82.3%, sensitivity of 82.0%, and specificity of 97.9% for the Control group, and a positive predictive value of 100%, negative predictive value of 97.1%, sensitivity of 97.1%, and specificity of 100% for the Case group, confirming that NIR-ICG imaging is a good diagnostic and screening test (P = .643 and P = .791, according to the Cohen κ tests, respectively for the laparoscopic and robotic groups). CONCLUSIONS: The few differences observed did not seem to be clinically relevant, making the 2 procedures comparable in terms of the ability to visually detect endometriotic lesions. Further prospective trials are needed to confirm our results.
Authors: Luigi Carlo Turco; Giuseppe Vizzielli; Virginia Vargiu; Salvatore Gueli Alletti; Maria De Ninno; Gabriella Ferrandina; Luigi Pedone Anchora; Giovanni Scambia; Francesco Cosentino Journal: Front Oncol Date: 2021-11-15 Impact factor: 6.244
Authors: Antonio Raffone; Diego Raimondo; Alessia Oliviero; Arianna Raspollini; Antonio Travaglino; Marco Torella; Gaetano Riemma; Marco La Verde; Pasquale De Franciscis; Paolo Casadio; Renato Seracchioli; Antonio Mollo Journal: Medicina (Kaunas) Date: 2022-06-13 Impact factor: 2.948
Authors: Emanuela Spagnolo; Ignacio Cristóbal Quevedo; Sara Gortázar de Las Casas; Ana López Carrasco; Maria Carbonell López; Isabel Pascual Migueláñez; Alicia Hernández Gutiérrez Journal: Front Surg Date: 2022-09-05