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


Authors: Brown, A. M.; Nagala, S.; McLean, M. A.; Lu, Y. G.; Scoffings, D.; Apte, A.; Gonen, M.; Stambuk, H. E.; Shaha, A. R.; Tuttle, R. M.; Deasy, J. O.; Priest, A. N.; Jani, P.; Shukla-Dave, A.; Griffiths, J.
Article Title: Multi-institutional validation of a novel textural analysis tool for preoperative stratification of suspected thyroid tumors on diffusion-weighted MRI
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. (C) 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance.
Keywords: classification; diagnosis; diffusion-weighted mri; lesions; nodules; images; needle-aspiration-cytology; coefficient values; differentiate benign; textural analysis; thyroid tumors
Journal Title: Magnetic Resonance in Medicine
Volume: 75
Issue: 4
ISSN: 0740-3194
Publisher: John Wiley & Sons  
Date Published: 2016-04-01
Start Page: 1708
End Page: 1716
Language: English
ACCESSION: WOS:000372910900032
DOI: 10.1002/mrm.25743
PROVIDER: wos
PMCID: PMC4654719
PUBMED: 25995019
Notes: Article -- Source: Wos
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MSK Authors
  1. Ashok R Shaha
    697 Shaha
  2. Mithat Gonen
    1028 Gonen
  3. Robert M Tuttle
    481 Tuttle
  4. Hilda Stambuk
    48 Stambuk
  5. Yonggang Lu
    11 Lu
  6. Amita Dave
    137 Dave
  7. Joseph Owen Deasy
    524 Deasy
  8. Aditya Apte
    203 Apte