Evaluation of High-risk (B3) Breast Lesions on MRI: The Role of Diffusion-weighted Imaging and Texture Analysis Features in Predicting Upgrade to Malignancy.

IF 1 4区 医学 Q4 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Tahsin Aybal, Onur Buğdayci, Erkin Aribal, Handan Kaya, Mustafa Ümit Uğurlu, Can Ilgin
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引用次数: 0

Abstract

Objective: This study aimed to investigate the potential malignancy associated with high-risk breast lesions using breast magnetic resonance imaging (MRI) characteristics, apparent diffusion coefficient (ADC) measurements, and texture analysis parameters.

Methods: This retrospective study included 40 patients with 41 lesions diagnosed as high-risk lesions after needle biopsy. All the patients underwent surgery. Based on the histopathologic results of the surgical excision, the patients were divided into 2 groups: those diagnosed with malignancy and those who were not. The MRI characteristics of the lesions were recorded. The ADC values of the lesions were measured. Textural analysis of the lesions was also performed.

Results: Fourteen lesions (34.1%) were upgraded to malignancy. The median ADCmean values ​​in the malignant group were 1.114 × 10-3 versus 1.383×10-3 mm2/s in the nonmalignant group, which was statistically significant (P < 0.001). The cutoff value for the mean ADC was 1.163 ×10-3 mm2/s. The sensitivity and specificity were 71.4% and 85.2%, respectively. Among the texture analysis parameters, kurtosis values obtained from images on the ADC map and the first subtracted dynamic contrast-enhanced (DCE) series and contrast values obtained from images on the second subtracted DCE series were found to be statistically significant (P = 0.016, P = 0.019, and P = 0.045, respectively) between the malignant and nonmalignant groups.

Conclusions: ADC measurements and texture analysis parameters provide useful diagnostic information for determining which high-risk breast lesions will progress to malignancy.

高危(B3)乳腺病变的MRI评估:弥散加权成像和质地分析特征在预测恶性肿瘤升级中的作用
目的:本研究旨在通过乳腺磁共振成像(MRI)特征、表观扩散系数(ADC)测量和织构分析参数,探讨乳腺高危病变的潜在恶性肿瘤。方法:本回顾性研究纳入40例经针活检诊断为高危病变的41个病变。所有的病人都接受了手术。根据手术切除后的组织病理学结果,将患者分为两组:确诊为恶性肿瘤的患者和确诊为非恶性肿瘤的患者。记录病变的MRI特征。测量病变的ADC值。还对病变进行了结构分析。结果:14个病变(34.1%)转为恶性。恶性组ADCmean中位数为1.114 ×10-3,非恶性组为1.383×10-3 mm2/s,差异有统计学意义(P < 0.001)。平均ADC的截止值为1.163 ×10-3 mm2/s。敏感性和特异性分别为71.4%和85.2%。在纹理分析参数中,恶性组与非恶性组在ADC图和第一个减去动态对比增强(DCE)序列的图像上获得的峰度值和第二个减去动态对比增强(DCE)序列的图像上获得的对比度值具有统计学意义(P = 0.016, P = 0.019, P = 0.045)。结论:ADC测量和质地分析参数为确定哪些高危乳腺病变会发展为恶性肿瘤提供了有用的诊断信息。
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来源期刊
CiteScore
2.50
自引率
0.00%
发文量
230
审稿时长
4-8 weeks
期刊介绍: The mission of Journal of Computer Assisted Tomography is to showcase the latest clinical and research developments in CT, MR, and closely related diagnostic techniques. We encourage submission of both original research and review articles that have immediate or promissory clinical applications. Topics of special interest include: 1) functional MR and CT of the brain and body; 2) advanced/innovative MRI techniques (diffusion, perfusion, rapid scanning); and 3) advanced/innovative CT techniques (perfusion, multi-energy, dose-reduction, and processing).
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