Open AccessReal three‐dimensional approach vs two‐dimensional camera with and without real‐time near‐infrared imaging with indocyanine green for detection of endometriosis: A case‐control study
Author(s) -
Vizzielli Giuseppe,
Cosentino Francesco,
Raimondo Diego,
Turco Luigi C.,
Vargiu Virginia,
Iodice Raffaella,
Mastronardi Manuela,
Mabrouk Mohamed,
Scambia Giovanni,
Seracchioli Renato
Publication year - 2020
Publication title -
acta obstetricia et gynecologica scandinavica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.401
H-Index - 102
eISSN - 1600-0412
pISSN - 0001-6349
DOI - 10.1111/aogs.13866
Subject(s) - indocyanine green , medicine , endometriosis , nuclear medicine , predictive value , radiology , surgery
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 three‐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.