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  • × Yaqiong Ge
  • × BMC Medical Imaging
  • × 2022
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BMC Medical Imaging,2022年

Wei Wei, Junjun Li, Jinjing Yang, Xiaowen Hu, Guofeng Zhang, Yaqiong Ge

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BMC Medical Imaging,2022年

Zedong Dai, Hong Li, Jie Zhu, Xilin Sun, Bin Song, Ran Wei, Hao Wang, Wenjuan Hu, Yaqiong Ge

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BMC Medical Imaging,2022年

Junjun Li, Wei Wei, Jinjing Yang, Guofeng Zhang, Xiaowen Hu, Yaqiong Ge

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BMC Medical Imaging,,222022年

Bin Song, Xilin Sun, Yuzhong Zhuang, Ran Wei, Lanyun Wang, Hao Wang, Zedong Dai, Yaqiong Ge

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BackgroundTo assess the potential of apparent diffusion coefficient (ADC) map in predicting aggressiveness of papillary thyroid carcinoma (PTC) based on whole-tumor histogram-based analysis.MethodsA total of 88 patients with PTC confirmed by pathology, who underwent neck magnetic resonance imaging, were enrolled in this retrospective study. Whole-lesion histogram features were extracted from ADC maps and compared between the aggressive and non-aggressive groups. Multivariable logistic regression analysis was performed for identifying independent predictive factors. Receiver operating characteristic curve analysis was used to evaluate the performances of significant factors, and an optimal predictive model for aggressiveness of PTC was developed.ResultsThe aggressive and non-aggressive groups comprised 67 (mean age, 44.03 ± 13.99 years) and 21 (mean age, 43.86 ± 12.16 years) patients, respectively. Five histogram features were included into the final predictive model. ADC_firstorder_TotalEnergy had the best performance (area under the curve [AUC] = 0.77). The final combined model showed an optimal performance, with AUC and accuracy of 0.88 and 0.75, respectively.ConclusionsWhole-lesion histogram analysis based on ADC maps could be utilized for evaluating aggressiveness in PTC.