本研究旨在构建和验证术前乳腺恶性肿瘤Ki-67表达的预测模型，以协助制定个体化治疗策略。本回顾性研究已获得机构审查委员会的批准，并包括197例入院的乳腺恶性肿瘤患者。基于14%阈值，将Ki-67表达分为低表达和高表达两组。利用1702个放射组学特征构建了放射组学标志，基于肿瘤周围（10毫米）和肿瘤内部感兴趣区域。通过多变量 logistic 回归，结合放射组学标志和超声（US）特征，建立了预测模型。为了评估模型的校准性、临床应用性和预测能力，采用决策曲线分析（DCA）、校准曲线和受试者工作特征曲线进行评估，分别得到了较满意的结果。最终的预测模型包括三个独立预测因子：肿瘤大小（P = .037）、放射组学标志（P < .001）和US报告的淋巴结状态（P = .018）。该预测模型在训练队列表现良好，特异度为0.944，灵敏度为0.745，曲线下面积（AUC）为0.905。验证队列的特异度为0.909，灵敏度为0.727，AUC为0.882。DCA显示了该预测模型的临床实用性，校准曲线显示了预测值和观察值之间的高一致性。本研究所采用的预测模型可以准确预测患有恶性乳腺肿瘤的人群中的Ki-67表达，有助于制定个体化治疗方法。版权所有 © 2023 大学放射学协会。由 Elsevier Inc. 发表并保留所有权利。

This study aimed to create and verify a nomogram for preoperative prediction of Ki-67 expression in breast malignancy to assist in the development of personalized treatment strategies.This retrospective study received approval from the institutional review board and included a cohort of 197 patients with breast malignancy who were admitted to our hospital. Ki-67 expression was divided into two groups based on a 14% threshold: low and high. A radiomics signature was built utilizing 1702 radiomics features based on an intra- and peritumoral (10 mm) regions of interest. Using multivariate logistic regression, radiomics signature, and ultrasound (US) characteristics, the nomogram was developed. To evaluate the model's calibration, clinical application, and predictive ability, decision curve analysis (DCA), the calibration curve, and the receiver operating characteristic curve were used, respectively.The final nomogram included three independent predictors: tumor size (P = .037), radiomics signature (P < .001), and US-reported lymph node status (P = .018). The nomogram exhibited satisfactory performance in the training cohort, demonstrating a specificity of 0.944, a sensitivity of 0.745, and an area under the curve (AUC) of 0.905. The validation cohort recorded a specificity of 0.909, a sensitivity of 0.727, and an AUC of 0.882. The DCA showed the nomogram's clinical utility, and the calibration curve revealed a high consistency among the expected and detected values.The nomogram used in this investigation can accurately predict Ki-67 expression in people with malignant breast tumors, helping to develop personalized treatment approaches.Copyright © 2023 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.