开发基于多模态超声放射组学的甲状腺微小结节准确分类的诊断。该研究是一项回顾性研究，包括179名患者中的181个甲状腺微小结节。应用纵向应变弹性成像(SE)、剪切波弹性成像(SWE)和B模式超声(BMUS)图像来提取放射组学特征。使用最小冗余最大相关和最小绝对收缩选择运算符算法选择恶性相关的特征。然后建立BMUS、SE和SWE放射组学分数(Rad-scores)。采用放射组学组合临床数据进行多元逻辑回归分析，并最终建立了诊断准确性的标准图谱。评估其表现时考虑校准、识别和临床实用性。还建立了一个独立的临床风险因素的临床预测模型进行比较。通过多元逻辑回归分析，确定了纵横比≥1、平均弹性指数、BMUS Rad-score、SE Rad-score和SWE Rad-score作为甲状腺微小结节恶性预测的独立因子。基于这些特征的放射组学标志物呈现出良好的校准和识别能力(AUC分别为0.903和0.881)，均优于临床预测模型(AUC分别为0.791和0.626)。决策曲线分析也确认了标准图谱的临床实用性。净分类指数和综合区别提高的显著改善表明，多模态超声放射组学特征可能作为分类甲状腺微小结节的新的成像标志物。结合多模态超声放射组学特征和临床因素的标准图谱有潜力在临床上用于甲状腺微小结节的准确诊断。版权所有 © 2023 Elsevier Inc.

To develop a multimodal ultrasound radiomics nomogram for accurate classification of thyroid micronodules.A retrospective study including 181 thyroid micronodules within 179 patients was conducted. Radiomics features were extracted from strain elastography (SE), shear wave elastography (SWE) and B-mode ultrasound (BMUS) images. Minimum redundancy maximum relevance and least absolute shrinkage and selection operator algorithms were used to select malignancy-related features. BMUS, SE, and SWE radiomics scores (Rad-scores) were then constructed. Multivariable logistic regression was conducted using radiomics signatures along with clinical data, and a nomogram was ultimately established. The calibration, discriminative, and clinical usefulness were considered to evaluate its performance. A clinical prediction model was also built using independent clinical risk factors for comparison.An aspect ratio ≥ 1, mean elasticity index, BMUS Rad-score, SE Rad-score, and SWE Rad-score were identified as the independent predictors for predicting malignancy of thyroid micronodules by multivariable logistic regression. The radiomics nomogram based on these characteristics showed favorable calibration and discriminative capabilities (AUCs: 0.903 and 0.881 for training and validation cohorts, respectively), all outperforming clinical prediction model (AUCs: 0.791 and 0.626, respectively). The decision curve analysis also confirmed clinical usefulness of the nomogram. The significant improvement of net reclassification index and integrated discriminatory improvement indicated that multimodal ultrasound radiomics signatures might work as new imaging markers for classifying thyroid micronodules.The nomogram combining multimodal ultrasound radiomics features and clinical factors has the potential to be used for accurate diagnosis of thyroid micronodules in the clinic.Copyright © 2023. Published by Elsevier Inc.