基于多模态超声特征的乳腺非肿块病变评估提名图:一项单中心研究。

IF 2.9 3区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING BMC Medical Imaging Pub Date : 2024-10-21 DOI:10.1186/s12880-024-01462-7
Li-Fang Yu, Luo-Xi Zhu, Chao-Chao Dai, Xiao-Jing Xu, Yan-Juan Tan, Hong-Ju Yan, Ling-Yun Bao
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引用次数: 0

摘要

背景:正确识别和诊断乳腺非肿块病变具有挑战性。本研究旨在探索与恶性乳腺非肿块病变(NMLs)相关的多模态超声特征,并评估其综合诊断性能:这项回顾性分析针对573例乳腺非肿块病变进行,其中309例为良性,264例为恶性,由两名经验丰富的放射科医生对其多模态超声特征(B型、彩色多普勒和应变弹性成像)进行评估。采用单变量和多变量逻辑回归分析探讨与恶性肿瘤相关的多模态超声特征,并绘制了提名图。在训练组和验证组中,通过接收器操作特征曲线(ROC)、校准曲线和决策曲线对诊断性能和临床实用性进行了评估和验证:结果:多模态超声特征包括线性(几率比 [OR] = 4.69)或节段性分布(OR = 7.67)、后部阴影(OR = 3.14)、钙化(OR = 7.40)、血管过少(OR = 0.38)、弹性评分 4(OR = 7.00)和 5(OR = 15.77),这些都是与恶性乳腺 NML 相关的独立因素。基于这些特征的提名图在训练组和验证组中的诊断性能与经验丰富的放射科医生相当,特异性(89.4%、89.5% vs. 81.2%)和阳性预测值(PPV)(89.2%、90.4% vs. 82.4%)均优于放射科医生。提名图在训练组和验证组中也显示出良好的校准性(所有 P > 0.05)。决策曲线分析表明,在广泛的阈值概率范围内(训练队列为 0.05-1,验证队列为 0.05-0.93),以提名图为指导的干预措施都是有益的:综合利用线性或节段性分布、后方阴影、钙化、高血管性和高弹性评分,以提名图的形式显示,对恶性乳腺 NML 的诊断效果令人满意,这可能有助于肿瘤的成像解释和临床管理。
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Nomogram based on multimodal ultrasound features for evaluating breast nonmass lesions: a single center study.

Background: It is challenging to correctly identify and diagnose breast nonmass lesions. This study aimed to explore the multimodal ultrasound features associated with malignant breast nonmass lesions (NMLs), and evaluate their combined diagnostic performance.

Methods: This retrospective analysis was conducted on 573 breast NMLs, including 309 were benign and 264 were malignant, their multimodal ultrasound features (B-mode, color Doppler and strain elastography) were assessed by two experienced radiologists. Univariate and multivariate logistic regression analysises were used to explore multimodal ultrasound features associated with malignancy, and a nomogram was developed. Diagnostic performance and clinical utility were evaluated and validated by the receiver operating characteristic (ROC) curve, calibration curve and decision curve in the training and validation cohorts.

Results: Multimodal ultrasound features including linear (odds ratio [OR] = 4.69) or segmental distribution (OR = 7.67), posterior shadowing (OR = 3.14), calcification (OR = 7.40), hypovascularity (OR = 0.38), elasticity scored 4 (OR = 7.00) and 5 (OR = 15.77) were independent factors associated with malignant breast NMLs. The nomogram based on these features exhibited diagnostic performance in the training and validation cohorts were comparable to that of experienced radiologists, with superior specificity (89.4%, 89.5% vs. 81.2%) and positive predictive value (PPV) (89.2%, 90.4% vs. 82.4%). The nomogram also demonstrated good calibration in both training and validation cohorts (all P > 0.05). Decision curve analysis indicated that interventions guided by the nomogram would be beneficial across a wide range of threshold probabilities (0.05-1 in the training cohort and 0.05-0.93 in the validation cohort).

Conclusions: The combined use of linear or segmental distribution, posterior shadowing, calcification, hypervascularity and high elasticity score, displayed as a nomogram, demonstrated satisfied diagnostic performance for malignant breast NMLs, which may contribute to the imaging interpretation and clinical management of tumors.

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来源期刊
BMC Medical Imaging
BMC Medical Imaging RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
4.60
自引率
3.70%
发文量
198
审稿时长
27 weeks
期刊介绍: BMC Medical Imaging is an open access journal publishing original peer-reviewed research articles in the development, evaluation, and use of imaging techniques and image processing tools to diagnose and manage disease.
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