DTI histogram parameters correlate with the extent of myoinvasion and tumor type in endometrial carcinoma: a preliminary analysis. (May 2020)

• Record Type: Journal Article
• Authors: Ghosh, Adarsh; Singh, Tulika; Singla, Veenu; Bagga, Rashmi; Srinivasan, Radhika; Khandelwal, Niranjan
• Is Part Of: Acta radiologica. Volume 61:Number 5(2020)
• Page Start: 675
• Page End: 684
• Publication Date: 2020-05
• Subjects: Diffusion tensor imaging -- endometrial carcinoma -- staging -- histogram analysis -- texture analysis; Radiology, Medical -- Periodicals; Radiography, Medical -- Periodicals; Radiotherapy -- Periodicals; 616.0757
• DOI: 10.1177/0284185119875019
• Languages: English
• ISSNs: 0284-1851

Abstract

Background: Myoinvasion and tumor-type determines surgical planning in endometrial carcinoma. Purpose: To evaluate whole tumor diffusion tensor imaging histogram texture parameters in evaluating myoinvasion and tumor type in endometrial carcinoma. Material and Methods: Twenty-seven patients with endometrial carcinoma underwent diffusion tensor imaging on a 1.5-T MRI system using echo-planar imaging sequence with 0 and 700 s/mm 2 b values. Whole tumor histogram parameters were obtained from fractional anisotropy, mean diffusivity maps. Mann–Whitney U test and receiver operating characteristic curve analyses were used Results: The mean fractional anisotropy of tumors with no myoinvasion was significantly higher than tumors which underwent myoinvasion, suggesting higher anisotropy in tumors which did not invade the myometrium. Voxel-wise heterogeneity in distribution of fractional anisotropy and mean diffusivity was seen in the form of higher uniformity and lower entropy of tumors with superficial <50% myoinvasion versus >50% myoinvasion. Uniformity, entropy, and energy of voxel-wise fractional anisotropy distribution gave an area under the curve of 0.827, 0.821, and 0.796, respectively, in predicting the presence of deep myometrial invasion while energy, entropy, and uniformity of mean diffusivity distribution in tumor gave an area under the curve of 0.84, 0.815, and 0.809 respectively. Tumor type was predicted with an area under the curve of 0.747, 0.759, and 0.765 for the uniformity, energy, and entropy of voxel-wise fractional anisotropy distribution. A logistic regression combining all the important histogram parameters obtained 94% and 88% sensitivity and 88% and 80% specificity in predicting deep myoinvasion and tumor type, respectively. Conclusion: Diffusion tensor histogram analysis can better characterize endometrial carcinomas and can be used as a quantitative marker of tumor behavior.