Differentiation of affected and nonaffected ovaries in ovarian torsion with magnetic resonance imaging texture analysis
Rev. Assoc. Med. Bras. (1992)
;
68(5): 641-646, May 2022. graf
Article
in English
|
LILACS-Express
| LILACS
| ID: biblio-1376173
ABSTRACT
SUMMARY OBJECTIVE:
This study aimed to evaluate the feasibility of texture analysis on T2-weighted axial images in differentiating affected and nonaffected ovaries in ovarian torsion.METHODS:
We included 22 torsioned ovaries and 19 healthy ovaries. All patients were surgically proven ovarian torsion cases. On T2-weighted axial images, ovarian borders were delineated by the consensus of two radiologists for magnetic resonance imaging-based texture analysis. Statistical differences between texture features of affected and nonaffected ovaries were assessed.RESULTS:
A total of 44 texture features were extracted from each ovary using LIFEx software. Of these, 17 features were significantly different between affected and nonaffected ovaries in ovarian torsion. NGLDM_Coarseness and NGLDM_Contrast, which are the neighborhood gray-level difference matrix parameters, had the largest area under the curve 0.923. The best cutoff values for the NGLDM_Contrast and NGLDM_Coarseness were 0.45 and 0.01, respectively. With these cutoff levels, NGLDM_Contrast had the best accuracy (85.37%).CONCLUSION:
Magnetic resonance imaging-based texture analysis on axial T2-weighted images may help differentiate affected and nonaffected ovaries in ovarian torsion.
Full text:
Available
Index:
LILACS (Americas)
Type of study:
Prognostic study
Language:
English
Journal:
Rev. Assoc. Med. Bras. (1992)
Year:
2022
Type:
Article
Affiliation country:
Turkey
Institution/Affiliation country:
Giresun University Faculty of Medicine/TR
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