scholarly journals EP34.03: A retrospective external validation of the ADNEX model to differentiate between benign and malignant adnexal masses

2019 ◽  
Vol 54 (S1) ◽  
pp. 441-441
Author(s):  
A. Esquivel Villabona ◽  
N. Rodriguez ◽  
C. Buritica ◽  
N. Rodríguez ◽  
A. Velandia ◽  
...  
Keyword(s):  
External Validation ◽  
Adnexal Masses

scholarly journals External validation of the adapted Risk of Malignancy Index incorporating tumor size in the preoperative evaluation of adnexal masses

2011 ◽  
Vol 159 (2) ◽  
pp. 422-425 ◽  
Author(s):  
Petronella A.J. van den Akker ◽  
Petra L.M. Zusterzeel ◽  
Anette L. Aalders ◽  
Marc P.L.M. Snijders ◽  
Rahul A.K. Samlal ◽  
...  
Keyword(s):  
Tumor Size ◽  
Preoperative Evaluation ◽  
External Validation ◽  
Adnexal Masses ◽  
Risk Of Malignancy ◽  
Risk Of Malignancy Index

scholarly journals OC05.05: External validation of “old” and new mathematical models to distinguish between benign and malignant adnexal masses

2009 ◽  
Vol 34 (S1) ◽  
pp. 8-8
Author(s):  
C. Van Holsbeke ◽  
B. Van Calster ◽  
G. B. Melis ◽  
A. Testa ◽  
S. Guerriero ◽  
...  
Keyword(s):  
Mathematical Models ◽  
External Validation ◽  
Adnexal Masses

scholarly journals EP34.09: A retrospective external validation of the GI‐RADS classification to differentiate between benign and malignant adnexal masses

2019 ◽  
Vol 54 (S1) ◽  
pp. 442-443
Author(s):  
A. Esquivel Villabona ◽  
N. Rodriguez ◽  
C. Buritica ◽  
N. Rodríguez ◽  
A. Gomez ◽  
...  
Keyword(s):  
External Validation ◽  
Adnexal Masses

scholarly journals Logistic models and artificial intelligence in the sonographic assessment of adnexal masses – a systematic review of the literature

2020 ◽  
Vol 22 (4) ◽  
pp. 469
Author(s):  
Mihaela Grigore ◽  
Razvan Mihai Popovici ◽  
Dumitru Gafitanu ◽  
Loredana Himiniuc ◽  
Mara Murarasu ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Systematic Review ◽  
High Performance ◽  
Ultrasound Examination ◽  
External Validation ◽  
Logistic Models ◽  
Medical Practitioners ◽  
Adnexal Masses ◽  
Surgical Evaluation ◽  
Malignant Condition

Adnexal masses are common, yet challenging, in gynecological practice. Making the differential diagnosis between their benign and malignant condition is essential for optimal surgical management, but reliable pre-surgical differentiation is sometimes difficult using clinical features, ultrasound examination, or tumor markers alone. A possible way to improve the diagnosis is using artificial intelligence (AI) or logistic models developed based on compiling and processing clinical, ultrasound, and tumor marker data together. Ample research has already been conducted in this regard that medical practitioners could benefit from. In this systematic review, we present logistic models and methods using AI, chosen based on their demonstrated high performance in clinical practice. Although some external validation of these models has been performed, further prospective studies are needed in order to select the best model or to create a new, more efficient, one for the pre-surgical evaluation of ovarian masses. 

External validation of the MR imaging scoring system for the management of adnexal masses

2016 ◽  
Vol 205 ◽  
pp. 115-119 ◽  
Author(s):  
Mireille Ruiz ◽  
Pénélope Labauge ◽  
Anne Louboutin ◽  
Olivier Limot ◽  
Arnaud Fauconnier ◽  
...  
Keyword(s):  
Mr Imaging ◽  
Scoring System ◽  
External Validation ◽  
Adnexal Masses

scholarly journals External Validation of Diagnostic Models to Estimate the Risk of Malignancy in Adnexal Masses

2011 ◽  
Vol 18 (3) ◽  
pp. 815-825 ◽  
Author(s):  
Caroline Van Holsbeke ◽  
Ben Van Calster ◽  
Tom Bourne ◽  
Silvia Ajossa ◽  
Antonia C. Testa ◽  
...  
Keyword(s):  
External Validation ◽  
Adnexal Masses ◽  
Diagnostic Models ◽  
Risk Of Malignancy

scholarly journals External Validation of the IOTA Classification in Women with Ovarian Masses Suspected to Be Endometrioma

2021 ◽  
Vol 10 (13) ◽  
pp. 2971
Author(s):  
Lee Cohen Ben-Meir ◽  
Roy Mashiach ◽  
Vered H. Eisenberg
Keyword(s):  
Expert Opinion ◽  
Transvaginal Ultrasound ◽  
External Validation ◽  
Likelihood Ratios ◽  
Predictive Values ◽  
Adnexal Masses ◽  
Tertiary Referral Center ◽  
Surgery Group ◽  
Simple Rules ◽  
Potentially Malignant

The study aimed to perform external validation of the International Ovarian Tumor Analysis (IOTA) classification of adnexal masses as benign or malignant in women with suspected endometrioma. A retrospective study including women referred to an endometriosis tertiary referral center for dedicated transvaginal ultrasound (TVUS). Adnexal masses were evaluated using the IOTA classification simple descriptors, simple rules and expert opinion. The reference standard was definitive histology after mass removal at laparoscopy. In total, 621 women were evaluated and divided into four groups: endometrioma on TVUS and confirmed on surgery (Group 1 = 181), endometrioma on TVUS but other benign cysts on surgery (Group 2 = 9), other cysts on TVUS but endometrioma on surgery (Group 3 = 2), masses classified as other findings or suspicious for malignancy on TVUS and confirmed on surgery (Group 4 = 5 potentially malignant, 11 benign). This gave a sensitivity 98.9%, specificity 64%, positive 95.3% and negative 88.9% predictive values, positive 2.74 and negative 0.02 likelihood ratios and 94.7% overall accuracy. The surgical diagnosis for the five masses suspected to be malignant was: borderline serous tumor (2), borderline mucinous tumor (2), and endometrioid lesion with complex hyperplasia without atypia (1). The conclusions were that the IOTA classification simple descriptors, simple rules and expert opinion performs well for classifying adnexal masses suspected to be endometrioma. The most common potentially malignant masses in these women were borderline ovarian tumors.

scholarly journals OC04.01: External validation of IOTA three-step strategy for assessment of adnexal masses

2018 ◽  
Vol 52 ◽  
pp. 7-7
Author(s):  
J. Hidalgo ◽  
M. Aubá ◽  
B. Olartecoechea ◽  
T. Errasti ◽  
A. Ruiz-Zambrana ◽  
...  
Keyword(s):  
External Validation ◽  
Adnexal Masses
Sign in / Sign up

Export Citation Format

Share Document