Role of Multidetector Computed Tomography in Evaluating Incidentally Detected Breast Lesions

Author:

Moschetta Marco1,Scardapane Arnaldo1,Lorusso Valentina1,Rella Leonarda1,Telegrafo Michele1,Serio Gabriella2,Angelelli Giuseppe1,Ianora Amato Antonio Stabile1

Affiliation:

1. Section of Diagnostic Imaging, Interdisciplinary Department of Medicine, Aldo Moro University of Bari Medical School, Bari - Italy

2. Section of Pathological Anatomy, Department of Emergency and Organ Transplantation, Aldo Moro University of Bari Medical School, Bari - Italy

Abstract

Aims and Background Computed tomography (CT) does not represent the primary method for the evaluation of breast lesions; however, it can detect breast abnormalities, even when performed for other reasons related to thoracic structures. The aim of this study is to evaluate the potential benefits of 320-row multidetector CT (MDCT) in evaluating and differentiating incidentally detected breast lesions by using vessel probe and 3D analysis software with net enhancement value. Methods and Study design Sixty-two breast lesions in 46 patients who underwent 320-row chest CT examination were retrospectively evaluated. CT scans were assessed searching for the presence, location, number, morphological features, and density of breast nodules. Net enhancement was calculated by subtracting precontrast density from the density obtained by postcontrast values. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy of CT were calculated for morphological features and net enhancement. Results Thirty of 62 lesions were found to be malignant at histological examination and 32 were found to be benign. When morphological features were considered, the sensitivity, specificity, accuracy, PPV, and NPV of CT were 87%, 100%, 88%, 100%, and 50%, respectively. Based on net enhancement, CT reached a sensitivity, specificity, accuracy, PPV, and NPV of 100%, 94%, 97%, 94%, and 100%, respectively. Conclusions MDCT allows to recognize and characterize breast lesions based on morphological features. Net enhancement can be proposed as an additional accurate feature of CT.

Publisher

SAGE Publications

Subject

Cancer Research,Oncology,General Medicine

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3