Cargando…
Differentiation of Endometriomas from Ovarian Hemorrhagic Cysts at Magnetic Resonance: The Role of Texture Analysis
Background and Objectives: To assess ovarian cysts with texture analysis (TA) in magnetic resonance (MRI) images for establishing a differentiation criterion for endometriomas and functional hemorrhagic cysts (HCs) that could potentially outperform their classic MRI diagnostic features. Materials an...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7598287/ https://www.ncbi.nlm.nih.gov/pubmed/32977428 http://dx.doi.org/10.3390/medicina56100487 |
_version_ | 1783602562735276032 |
---|---|
author | Lupean, Roxana-Adelina Ștefan, Paul-Andrei Csutak, Csaba Lebovici, Andrei Măluțan, Andrei Mihai Buiga, Rareş Melincovici, Carmen Stanca Mihu, Carmen Mihaela |
author_facet | Lupean, Roxana-Adelina Ștefan, Paul-Andrei Csutak, Csaba Lebovici, Andrei Măluțan, Andrei Mihai Buiga, Rareş Melincovici, Carmen Stanca Mihu, Carmen Mihaela |
author_sort | Lupean, Roxana-Adelina |
collection | PubMed |
description | Background and Objectives: To assess ovarian cysts with texture analysis (TA) in magnetic resonance (MRI) images for establishing a differentiation criterion for endometriomas and functional hemorrhagic cysts (HCs) that could potentially outperform their classic MRI diagnostic features. Materials and Methods: Forty-three patients with known ovarian cysts who underwent MRI were retrospectively included (endometriomas, n = 29; HCs, n = 14). TA was performed using dedicated software based on T2-weighted images, by incorporating the whole lesions in a three-dimensional region of interest. The most discriminative texture features were highlighted by three selection methods (Fisher, probability of classification error and average correlation coefficients, and mutual information). The absolute values of these parameters were compared through univariate, multivariate, and receiver operating characteristic analyses. The ability of the two classic diagnostic signs (“T2 shading” and “T2 dark spots”) to diagnose endometriomas was assessed by quantifying their sensitivity (Se) and specificity (Sp), following their conventional assessment on T1-and T2-weighted images by two radiologists. Results: The diagnostic power of the one texture parameter that was an independent predictor of endometriomas (entropy, 75% Se and 100% Sp) and of the predictive model composed of all parameters that showed statistically significant results at the univariate analysis (100% Se, 100% Sp) outperformed the ones shown by the classic MRI endometrioma features (“T2 shading”, 75.86% Se and 35.71% Sp; “T2 dark spots”, 55.17% Se and 64.29% Sp). Conclusion: Whole-lesion MRI TA has the potential to offer a superior discrimination criterion between endometriomas and HCs compared to the classic evaluation of the two lesions’ MRI signal behaviors. |
format | Online Article Text |
id | pubmed-7598287 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75982872020-10-31 Differentiation of Endometriomas from Ovarian Hemorrhagic Cysts at Magnetic Resonance: The Role of Texture Analysis Lupean, Roxana-Adelina Ștefan, Paul-Andrei Csutak, Csaba Lebovici, Andrei Măluțan, Andrei Mihai Buiga, Rareş Melincovici, Carmen Stanca Mihu, Carmen Mihaela Medicina (Kaunas) Article Background and Objectives: To assess ovarian cysts with texture analysis (TA) in magnetic resonance (MRI) images for establishing a differentiation criterion for endometriomas and functional hemorrhagic cysts (HCs) that could potentially outperform their classic MRI diagnostic features. Materials and Methods: Forty-three patients with known ovarian cysts who underwent MRI were retrospectively included (endometriomas, n = 29; HCs, n = 14). TA was performed using dedicated software based on T2-weighted images, by incorporating the whole lesions in a three-dimensional region of interest. The most discriminative texture features were highlighted by three selection methods (Fisher, probability of classification error and average correlation coefficients, and mutual information). The absolute values of these parameters were compared through univariate, multivariate, and receiver operating characteristic analyses. The ability of the two classic diagnostic signs (“T2 shading” and “T2 dark spots”) to diagnose endometriomas was assessed by quantifying their sensitivity (Se) and specificity (Sp), following their conventional assessment on T1-and T2-weighted images by two radiologists. Results: The diagnostic power of the one texture parameter that was an independent predictor of endometriomas (entropy, 75% Se and 100% Sp) and of the predictive model composed of all parameters that showed statistically significant results at the univariate analysis (100% Se, 100% Sp) outperformed the ones shown by the classic MRI endometrioma features (“T2 shading”, 75.86% Se and 35.71% Sp; “T2 dark spots”, 55.17% Se and 64.29% Sp). Conclusion: Whole-lesion MRI TA has the potential to offer a superior discrimination criterion between endometriomas and HCs compared to the classic evaluation of the two lesions’ MRI signal behaviors. MDPI 2020-09-23 /pmc/articles/PMC7598287/ /pubmed/32977428 http://dx.doi.org/10.3390/medicina56100487 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Lupean, Roxana-Adelina Ștefan, Paul-Andrei Csutak, Csaba Lebovici, Andrei Măluțan, Andrei Mihai Buiga, Rareş Melincovici, Carmen Stanca Mihu, Carmen Mihaela Differentiation of Endometriomas from Ovarian Hemorrhagic Cysts at Magnetic Resonance: The Role of Texture Analysis |
title | Differentiation of Endometriomas from Ovarian Hemorrhagic Cysts at Magnetic Resonance: The Role of Texture Analysis |
title_full | Differentiation of Endometriomas from Ovarian Hemorrhagic Cysts at Magnetic Resonance: The Role of Texture Analysis |
title_fullStr | Differentiation of Endometriomas from Ovarian Hemorrhagic Cysts at Magnetic Resonance: The Role of Texture Analysis |
title_full_unstemmed | Differentiation of Endometriomas from Ovarian Hemorrhagic Cysts at Magnetic Resonance: The Role of Texture Analysis |
title_short | Differentiation of Endometriomas from Ovarian Hemorrhagic Cysts at Magnetic Resonance: The Role of Texture Analysis |
title_sort | differentiation of endometriomas from ovarian hemorrhagic cysts at magnetic resonance: the role of texture analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7598287/ https://www.ncbi.nlm.nih.gov/pubmed/32977428 http://dx.doi.org/10.3390/medicina56100487 |
work_keys_str_mv | AT lupeanroxanaadelina differentiationofendometriomasfromovarianhemorrhagiccystsatmagneticresonancetheroleoftextureanalysis AT stefanpaulandrei differentiationofendometriomasfromovarianhemorrhagiccystsatmagneticresonancetheroleoftextureanalysis AT csutakcsaba differentiationofendometriomasfromovarianhemorrhagiccystsatmagneticresonancetheroleoftextureanalysis AT leboviciandrei differentiationofendometriomasfromovarianhemorrhagiccystsatmagneticresonancetheroleoftextureanalysis AT malutanandreimihai differentiationofendometriomasfromovarianhemorrhagiccystsatmagneticresonancetheroleoftextureanalysis AT buigarares differentiationofendometriomasfromovarianhemorrhagiccystsatmagneticresonancetheroleoftextureanalysis AT melincovicicarmenstanca differentiationofendometriomasfromovarianhemorrhagiccystsatmagneticresonancetheroleoftextureanalysis AT mihucarmenmihaela differentiationofendometriomasfromovarianhemorrhagiccystsatmagneticresonancetheroleoftextureanalysis |