OBJECTIVE: To assess the clinical usefulness of a structured reporting system based on ultrasound findings for management of adnexal masses. METHODS: This was a prospective multicenter study comprising 432 adnexal masses in 372 women (mean age, 44.0 (range, 13-78) years) over a 36-month period. Ninety-three (25%) women were postmenopausal and 279 (75%) women were premenopausal. Patients were evaluated with transvaginal ultrasound by one of three examiners expert in gynecological ultrasound. Reporting was provided to referring clinicians according to the Gynecologic Imaging Report and Data System (GI-RADS) classification. A predetermined management protocol was offered to referral clinicians. It was suggested that patients classified as GI-RADS 2 be managed with follow-up scan, patients classified as GI-RADS 3 undergo laparoscopic surgery and patients classified as GI-RADS 4 or 5 be referred to a gynecologic oncologist. Definitive histologic diagnosis was available in 370 cases and 62 additional cases were considered as benign because of spontaneous resolution during follow-up. These outcomes were used as the gold standard for calculating the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+) and negative likelihood ratio (LR-) of GI-RADS classification for identifying adnexal masses at high risk of malignancy, considering GI-RADS 4 and 5 as being malignant. RESULTS: Of the 432 tumors, 112 were malignant and 320 benign. The GI-RADS classification rate was as follows: GI-RADS 2, 92 (21%) cases; GI-RADS 3, 184 (43%) cases; GI-RADS 4, 40 (9%) cases; GI-RADS 5, (27%) 116 cases. Sensitivity for this system was 99.1% (95% CI, 95.1-99.8%), specificity was 85.9% (95% CI, 81.7-89.3%), LR+ was 7.05 (95% CI, 5.37-9.45) and LR- was 0.01 (95% CI, 0.001-0.07). PPV and NPV were 71.1% and 99.6%, respectively. CONCLUSIONS: The GI-RADS reporting system performed well in identifying adnexal masses at high risk of malignancy and seems to be useful for clinical decision-making.
OBJECTIVE: To assess the clinical usefulness of a structured reporting system based on ultrasound findings for management of adnexal masses. METHODS: This was a prospective multicenter study comprising 432 adnexal masses in 372 women (mean age, 44.0 (range, 13-78) years) over a 36-month period. Ninety-three (25%) women were postmenopausal and 279 (75%) women were premenopausal. Patients were evaluated with transvaginal ultrasound by one of three examiners expert in gynecological ultrasound. Reporting was provided to referring clinicians according to the Gynecologic Imaging Report and Data System (GI-RADS) classification. A predetermined management protocol was offered to referral clinicians. It was suggested that patients classified as GI-RADS 2 be managed with follow-up scan, patients classified as GI-RADS 3 undergo laparoscopic surgery and patients classified as GI-RADS 4 or 5 be referred to a gynecologic oncologist. Definitive histologic diagnosis was available in 370 cases and 62 additional cases were considered as benign because of spontaneous resolution during follow-up. These outcomes were used as the gold standard for calculating the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+) and negative likelihood ratio (LR-) of GI-RADS classification for identifying adnexal masses at high risk of malignancy, considering GI-RADS 4 and 5 as being malignant. RESULTS: Of the 432 tumors, 112 were malignant and 320 benign. The GI-RADS classification rate was as follows: GI-RADS 2, 92 (21%) cases; GI-RADS 3, 184 (43%) cases; GI-RADS 4, 40 (9%) cases; GI-RADS 5, (27%) 116 cases. Sensitivity for this system was 99.1% (95% CI, 95.1-99.8%), specificity was 85.9% (95% CI, 81.7-89.3%), LR+ was 7.05 (95% CI, 5.37-9.45) and LR- was 0.01 (95% CI, 0.001-0.07). PPV and NPV were 71.1% and 99.6%, respectively. CONCLUSIONS: The GI-RADS reporting system performed well in identifying adnexal masses at high risk of malignancy and seems to be useful for clinical decision-making.
Authors: Michal Migda; Migda Bartosz; Marian S Migda; Marcin Kierszk; Gieryn Katarzyna; Marek Maleńczyk Journal: J Ovarian Res Date: 2018-11-03 Impact factor: 4.234
Authors: Dirk Timmerman; François Planchamp; Tom Bourne; Chiara Landolfo; Andreas du Bois; Luis Chiva; David Cibula; Nicole Concin; Daniela Fischerova; Wouter Froyman; Guillermo Gallardo Madueño; Birthe Lemley; Annika Loft; Liliana Mereu; Philippe Morice; Denis Querleu; Antonia Carla Testa; Ignace Vergote; Vincent Vandecaveye; Giovanni Scambia; Christina Fotopoulou Journal: Int J Gynecol Cancer Date: 2021-06-10 Impact factor: 3.437