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Multi-institutional validation of a novel textural analysis tool for preoperative stratification of suspected thyroid tumors on diffusion-weighted MRI.


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Authors

Brown, Anna M 
Nagala, Sidhartha 
McLean, Mary A 
Lu, Yonggang 
Scoffings, Daniel 

Abstract

PURPOSE: Ultrasound-guided fine needle aspirate cytology fails to diagnose many malignant thyroid nodules; consequently, patients may undergo diagnostic lobectomy. This study assessed whether textural analysis (TA) could noninvasively stratify thyroid nodules accurately using diffusion-weighted MRI (DW-MRI). METHODS: This multi-institutional study examined 3T DW-MRI images obtained with spin echo echo planar imaging sequences. The training data set included 26 patients from Cambridge, United Kingdom, and the test data set included 18 thyroid cancer patients from Memorial Sloan Kettering Cancer Center (New York, New York, USA). Apparent diffusion coefficients (ADCs) were compared over regions of interest (ROIs) defined on thyroid nodules. TA, linear discriminant analysis (LDA), and feature reduction were performed using the 21 MaZda-generated texture parameters that best distinguished benign and malignant ROIs. RESULTS: Training data set mean ADC values were significantly different for benign and malignant nodules (P = 0.02) with a sensitivity and specificity of 70% and 63%, respectively, and a receiver operator characteristic (ROC) area under the curve (AUC) of 0.73. The LDA model of the top 21 textural features correctly classified 89/94 DW-MRI ROIs with 92% sensitivity, 96% specificity, and an AUC of 0.97. This algorithm correctly classified 16/18 (89%) patients in the independently obtained test set of thyroid DW-MRI scans. CONCLUSION: TA classifies thyroid nodules with high sensitivity and specificity on multi-institutional DW-MRI data sets. This method requires further validation in a larger prospective study. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance.

Description

Keywords

diffusion-weighted MRI, textural analysis, thyroid tumors, Adult, Aged, Area Under Curve, Cohort Studies, Diffusion Magnetic Resonance Imaging, Female, Humans, Image Interpretation, Computer-Assisted, Male, Middle Aged, Reproducibility of Results, Thyroid Gland, Thyroid Neoplasms

Journal Title

Magn Reson Med

Conference Name

Journal ISSN

0740-3194
1522-2594

Volume Title

Publisher

Wiley
Sponsorship
Cancer Research UK (C14303/A17197)
Cancer Research UK (11562)
Grant sponsor: Cancer Research UK Cambridge Institute; Grant number: C14303/A17197; Grant sponsor: Addenbrooke’s Charitable Trust; Grant sponsor: University of Cambridge; Grant sponsor: Cambridge Experimental Cancer Medicine Centre; Grant sponsor: National Institute for Health Research Cambridge Biomedical Research Centre; Grant sponsor: National Cancer Institute/National Institutes of Health; Grant numbers: 1R21CA176660-01A1 and P50 CA172012-01A1.