Related Experiment Video For Thyroid neoplasms
Updated: Aug 2, 2025

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Unenhanced magnetic resonance imaging of papillary thyroid carcinoma with emphasis on diffusion kurtosis imaging
Qiying Tang1, Xinyou Liu2, Qiuli Jiang3
1Department of Radiology, Xiamen Branch, Zhongshan Hospital, Fudan University, Xiamen, China.
Background:
The aim of this study was to investigate the value of unenhanced magnetic resonance imaging (MRI) with diffusion kurtosis imaging (DKI) in diagnosing papillary thyroid carcinoma (PTC).
Methods:
In all, 77 consecutive patients comprising a total of 77 thyroid nodules were enrolled in this study. Of these nodules, 41 were histopathologically confirmed PTCs and 36 were benign nodules. All patients underwent thyroid MRI including T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and DKI. All the images were assessed by 2 radiologists. The signal intensity ratio (SIR) of these nodules on T1WI and T2WI, the apparent diffusion coefficient (ADC) from DWI, and mean diffusivity (MD) and mean kurtosis (MK) from DKI were measured. Morphological features on these images were also evaluated. Univariate and multivariate logistic regression analyses were used to evaluate the value of these parameters as potential predictors of PTC.
Results:
In the univariate analyses, the features that significantly indicated PTC were decreased ADC value (P<0.001), decreased MD value (P<0.001), increased MK value (P<0.001), younger age (P=0.001), female tendency (P=0.049), smaller tumor diameter (P<0.001), solid component (P<0.001), and irregular margin (P<0.001). In the multivariate analysis, decreased MD value (odds ratio =25.321; P=0.001), smaller diameter (odds ratio =13.751; P=0.006), and irregular margin (odds ratio =16.003; P=0.003) were independent risk factors for PTC. The combined predictor of MD, diameter, and margin showed an area under the receiver operating characteristic (ROC) curve of 0.996 in diagnosing PTC, with an optimal cutoff value of 0.69 (95.1% sensitivity, 100.0% specificity).
Conclusions:
Lower MD value from DKI, smaller diameter, and irregular margin are useful predictive biomarkers for PTC.
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