Jie Liu, Jingchao Yu, Yanan Wei, Wei Li, Jinle Lu, Yating Chen, Meng Wang
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引用次数: 0
Abstract
Background: Whether prophylactic central lymph node dissection is necessary for patients with clinically node-negative (cN0) papillary thyroid microcarcinoma (PTMC) remains controversial. Herein, we aimed to establish an ultrasound (US) radiomics (Rad) score for assessing the probability of central lymph node metastasis (CLNM) in such patients.
Methods: 480 patients (327 in the training cohort, 153 in the validation cohort) who underwent thyroid surgery for cN0 PTMC at two institutions between January 2018 and December 2020 were included. Radiomics features were extracted from the US images. Least absolute shrinkage and selection operator logistic regression were utilized to generate a Rad score. A nomogram consisting of the Rad score and clinical factors was then constructed for the training cohort. Both cohorts assessed model performance using discrimination, calibration, and clinical usefulness.
Results: Based on the six most valuable radiomics features, the Rad score was calculated for each patient. A multivariate analysis revealed that a higher Rad score (P < 0.001), younger age (P = 0.006), and presence of capsule invasion (P = 0.030) were independently associated with CLNM. A nomogram integrating these three factors demonstrated good calibration and promising clinical utility in the training and validation cohorts. The nomogram yielded areas under the curve of 0.795 (95% confidence interval [CI], 0.745-0.846) and 0.774 (95% CI, 0.696-0.852) in the training and validation cohorts, respectively.
Conclusions: The radiomics nomogram may be a clinically useful tool for the individual prediction of CLNM in patients with cN0 PTMC.
背景:临床结节阴性(cN0)甲状腺乳头状微小癌(PTMC)患者是否有必要进行预防性中央淋巴结清扫仍存在争议。在此,我们旨在建立一个超声(US)放射组学(Rad)评分,用于评估此类患者发生中央淋巴结转移(CLNM)的概率。方法:纳入2018年1月至2020年12月期间在两家机构接受甲状腺手术治疗cN0 PTMC的480例患者(训练队列327例,验证队列153例)。从 US 图像中提取放射组学特征。利用最小绝对收缩和选择算子逻辑回归生成Rad评分。然后为训练队列构建了一个由 Rad 评分和临床因素组成的提名图。两个队列都通过辨别、校准和临床实用性评估了模型的性能:根据六个最有价值的放射组学特征,计算出了每位患者的 Rad 评分。多变量分析表明,Rad 评分越高(P 结论:放射组学提名图可能是一种有效的诊断方法:放射组学提名图可能是预测 cN0 PTMC 患者 CLNM 的临床有用工具。