Differentiation between malignant and benign thyroid nodules and stratification of papillary thyroid cancer with aggressive histological features: Whole-lesion diffusion-weighted imaging histogram analysis.
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.



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.



Mean ADC, median ADC, 5thpercentile ADC, 25thpercentile ADC, 75thpercentile ADC, 95thpercentile 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 × 10-6mm2/s in differentiating malignant and benign nodules. Compared to the PTCs without extrathyroidal extension, PTCs with extrathyroidal extension showed significantly lower median ADC, 5thpercentile ADC, and 25thpercentile ADC. The 5thpercentile ADC achieved the highest AUC (0.757) with cutoff value of 911.5 × 10-6mm2/s for differentiating between PTCs with and without extrathyroidal extension.



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.
Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yonghong
Y
Hao
Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Chu
C
Pan
Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
WeiWei
W
Chen
Department of Radiology, Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Tao
T
Li
Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
WenZhen
W
Zhu
Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
JianPin
J
Qi
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002291:Carcinoma, Papillary / Q000000981:diagnostic imaging* / Q000473:pathology*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D003937:Diagnosis, Differential; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009361:Neoplasm Invasiveness; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D000077273:Thyroid Cancer, Papillary; D013964:Thyroid Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology*; D016606:Thyroid Nodule / Q000000981:diagnostic imaging* / Q000473:pathology*
aggression; diffusion magnetic resonance imaging; histogram; thyroid cancer; thyroid nodules