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基于CT影像组学列线图鉴别甲状腺良性与恶性滤泡性肿瘤的价值
引用本文:唐鹏洲,任采月,王月明,周正荣.基于CT影像组学列线图鉴别甲状腺良性与恶性滤泡性肿瘤的价值[J].中华放射学杂志,2022(2):136-141.
作者姓名:唐鹏洲  任采月  王月明  周正荣
作者单位:复旦大学附属肿瘤医院放射科;上海市质子重离子医院核医学科
基金项目:上海市科技创新行动计划(18140901200)。
摘    要:目的:探讨基于CT影像组学列线图鉴别甲状腺滤泡性肿瘤良生与恶性的价值。方法:回顾性收集2016年1月至2018年12月复旦大学附属肿瘤医院经手术病理证实的200例甲状腺滤泡性肿瘤患者的临床资料及CT图像,其中甲状腺滤泡癌(FTC)46例、甲状腺滤泡腺瘤(FTA)154例。采用随机数表法随机分为训练集( n=...

关 键 词:甲状腺肿瘤  腺癌,滤泡性  体层摄影术,X线计算机  影像组学  列线图

The value of diagnostic nomogram based on CT radiomics for the preoperative differentiation between benign and malignant thyroid follicular neoplasms
Tang Pengzhou,Ren Caiyue,Wang Yueming,Zhou Zhengrong.The value of diagnostic nomogram based on CT radiomics for the preoperative differentiation between benign and malignant thyroid follicular neoplasms[J].Chinese Journal of Radiology,2022(2):136-141.
Authors:Tang Pengzhou  Ren Caiyue  Wang Yueming  Zhou Zhengrong
Institution:(Department of Radiology,Fudan University Shanghai Cancer Center,Shanghai 200032,China;Department of Nuclear Medicine,Shanghai Proton and Heavy Ion Center,Shanghai 201315,China)
Abstract:Objective To investigate the value of nomogram constructed by CT-based radiomics for differentiating benign and malignant thyroid follicular neoplasms.Methods Totally 200 post-surgery patients with pathologically confirmed thyroid follicular neoplasms in Fudan University Shanghai Cancer Center from January 2016 to December 2018 were retrospectively analyzed.Among the patients,46 were follicular thyroid carcinoma(FTC)and 154 patients were follicular thyroid adenoma(FTA).The patients were randomly divided into a training set(n=140)and validation set(n=60)using a random number table.CT signs and radiomics features of each patient were analyzed within the LIFEx package.A predictive model was developed by the least absolute shrinkage and selection operator regression to build a nomogram based on selected parameters.The predictive effectiveness of differentiating benign and malignant thyroid follicular neoplasms was evaluated by the area under receiver operating characteristic curve(AUC).Calibration plots were formulated to evaluate the reliability and accuracy of the nomogram based on internal(training set)and external(validation set)validity.The clinical value of the nomogram was estimated through the decision curve analysis.Results The prediction nomogram was built with 4 selected parameters,including grey level zone length matrix(GLZLM)-gray-level zone length matrix_zone length non-uniformity,GLZLM-gray-level zone length matrix_low gray-level zone emphasis,CONVENTIONAL_HUQ3,CONVENTIONAL_HUmean.In training and validation sets,the AUCs for differentiating FTC and FTA were 0.863(95%CI 0.746-0.932),0.792(95%CI 0.658-0.917),accuracy were 87.9%and 75.0%,sensitivity were 67.9%and 66.7%,specificity were 91.1%and 90.5%,respectively.The calibration curves indicated good consistency between actual observation and prediction for differentiating the malignancy.Decision curve analysis demonstrated the nomogram was clinically useful.Conclusions The CT radiomics mode shows the certain value and great potential to identify benign or malignant thyroid follicular neoplasms and the nomogram can accurately and intuitively predict the malignancy potential in patients with thyroid follicular neoplasms.
Keywords:Thyroid neoplasms  Adenocarcinoma  follicular  Tomography  X-ray computed  Radiomics  Nomogram
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