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Abstract #0592

MRI Texture Analysis in the Characterization of Cervical Carcinoma

Mandi Wang1, Jose Angelo Perucho1, Queenie Chan2, and Elaine Lee1
1Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, Hong Kong, 2Philips Healthcare, Hong Kong, China

MRI texture analysis was performed in 100 patients with cervical carcinoma. TexRAD software was used for texture extraction and analysis on ADC maps and T1c images. Texture features were compared between histological subtypes, tumour grades, FIGO stages and nodal status. Feature selection was achieved with AUC ≥ 0.70. ADC-derived MPP5 was significantly lower in SCC than ACA, Entropy6 derived from both ADC and T1c increased from FIGO I~II to FIGO III~IV, and ADC-derived Entropy3 was higher in positive nodal status than negative. No texture features could differentiate tumour grades with acceptable diagnostic efficiency.

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