Yonghong Hao1, Chu Pan1, WeiWei Chen1, Tao Li2, WenZhen Zhu1, JianPin Qi1. 1. Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. 2. Department of Radiology, Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Abstract
PURPOSE: To explore the usefulness of whole-lesion histogram analysis of apparent diffusion coefficient (ADC) derived from reduced field-of-view (r-FOV) diffusion-weighted imaging (DWI) in differentiating malignant and benign thyroid nodules and stratifying papillary thyroid cancer (PTC) with aggressive histological features. MATERIALS AND METHODS: This Institutional Review Board-approved, retrospective study included 93 patients with 101 pathologically proven thyroid nodules. All patients underwent preoperative r-FOV DWI at 3T. The whole-lesion ADC assessments were performed for each patient. Histogram-derived ADC parameters between different subgroups (pathologic type, extrathyroidal extension, lymph node metastasis) were compared. Receiver operating characteristic curve analysis was used to determine optimal histogram parameters in differentiating benign and malignant nodules and predicting aggressiveness of PTC. RESULTS: Mean ADC, median ADC, 5th percentile ADC, 25th percentile ADC, 75th percentile ADC, 95th percentile ADC (all P < 0.001), and kurtosis (P = 0.001) were significantly lower in malignant thyroid nodules, and mean ADC achieved the highest AUC (0.919) with a cutoff value of 1842.78 × 10-6 mm2 /s in differentiating malignant and benign nodules. Compared to the PTCs without extrathyroidal extension, PTCs with extrathyroidal extension showed significantly lower median ADC, 5th percentile ADC, and 25th percentile ADC. The 5th percentile ADC achieved the highest AUC (0.757) with cutoff value of 911.5 × 10-6 mm2 /s for differentiating between PTCs with and without extrathyroidal extension. CONCLUSION: Whole-lesion ADC histogram analysis might help to differentiate malignant nodules from benign ones and show the PTCs with extrathyroidal extension. J. Magn. Reson. Imaging 2016;44:1546-1555.
PURPOSE: To explore the usefulness of whole-lesion histogram analysis of apparent diffusion coefficient (ADC) derived from reduced field-of-view (r-FOV) diffusion-weighted imaging (DWI) in differentiating malignant and benign thyroid nodules and stratifying papillary thyroid cancer (PTC) with aggressive histological features. MATERIALS AND METHODS: This Institutional Review Board-approved, retrospective study included 93 patients with 101 pathologically proven thyroid nodules. All patients underwent preoperative r-FOV DWI at 3T. The whole-lesion ADC assessments were performed for each patient. Histogram-derived ADC parameters between different subgroups (pathologic type, extrathyroidal extension, lymph node metastasis) were compared. Receiver operating characteristic curve analysis was used to determine optimal histogram parameters in differentiating benign and malignant nodules and predicting aggressiveness of PTC. RESULTS: Mean ADC, median ADC, 5th percentile ADC, 25th percentile ADC, 75th percentile ADC, 95th percentile ADC (all P < 0.001), and kurtosis (P = 0.001) were significantly lower in malignant thyroid nodules, and mean ADC achieved the highest AUC (0.919) with a cutoff value of 1842.78 × 10-6 mm2 /s in differentiating malignant and benign nodules. Compared to the PTCs without extrathyroidal extension, PTCs with extrathyroidal extension showed significantly lower median ADC, 5th percentile ADC, and 25th percentile ADC. The 5th percentile ADC achieved the highest AUC (0.757) with cutoff value of 911.5 × 10-6 mm2 /s for differentiating between PTCs with and without extrathyroidal extension. CONCLUSION: Whole-lesion ADC histogram analysis might help to differentiate malignant nodules from benign ones and show the PTCs with extrathyroidal extension. J. Magn. Reson. Imaging 2016;44:1546-1555.
Authors: David Aramburu Núñez; Yonggang Lu; Ramesh Paudyal; Vaios Hatzoglou; Andre L Moreira; Jung Hun Oh; Hilda E Stambuk; Yousef Mazaheri; Mithat Gonen; Ronald A Ghossein; Ashok R Shaha; R Michael Tuttle; Amita Shukla-Dave Journal: Tomography Date: 2019-03