Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria.
Department of Biomedical Sciences, Humanitas University, Milan, Italy.
Eur J Radiol. 2024 Jan;170:111271. doi: 10.1016/j.ejrad.2023.111271. Epub 2023 Dec 19.
We aimed to investigate the effect of using visual or automatic enhancement curve type assessment on the diagnostic performance of the Kaiser Score (KS), a clinical decision rule for breast MRI.
This IRB-approved retrospective study analyzed consecutive conventional BI-RADS 0, 4 or 5 patients who underwent biopsy after 1.5T breast MRI according to EUSOBI recommendations between 2013 and 2015. The KS includes five criteria (spiculations; signal intensity (SI)-time curve type; margins of the lesion; internal enhancement; and presence of edema) resulting in scores from 1 (=lowest) to 11 (=highest risk of breast cancer). Enhancement curve types (Persistent, Plateau or Wash-out) were assessed by two radiologists independently visually and using a pixel-wise color-coded computed parametric map of curve types. KS diagnostic performance differences between readings were compared by ROC analysis.
In total 220 lesions (147 benign, 73 malignant) including mass (n = 148) and non-mass lesions (n = 72) were analyzed. KS reading performance in distinguishing benign from malignant lesions did not differ between visual analysis and parametric map (P = 0.119; visual: AUC 0.875, sensitivity 95 %, specificity 63 %; and map: AUC 0.901, sensitivity 97 %, specificity 65 %). Additionally, analyzing mass and non-mass lesions separately, showed no difference between parametric map based and visual curve type-based KS analysis as well (P = 0.130 and P = 0.787).
The performance of the Kaiser Score is largely independent of the curve type assessment methodology, confirming its robustness as a clinical decision rule for breast MRI in any type of breast lesion in clinical routine.
本研究旨在探讨在使用视觉或自动增强曲线类型评估对 Kaiser 评分（KS）的诊断性能的影响，KS 是一种用于乳腺 MRI 的临床决策规则。
这项经机构审查委员会批准的回顾性研究分析了 2013 年至 2015 年间，根据 EUSOBI 建议，在 1.5T 乳腺 MRI 后进行活检的连续常规 BI-RADS 0、4 或 5 患者。KS 包括五个标准（分叶状；信号强度（SI）-时间曲线类型；病变边缘；内部增强；和水肿的存在），评分范围为 1（最低）至 11（乳腺癌风险最高）。增强曲线类型（持续型、平台型或洗脱型）由两位放射科医生独立通过视觉和使用像素级彩色编码的曲线类型计算参数图进行评估。通过 ROC 分析比较两种阅读方式下 KS 诊断性能的差异。
共分析了 220 个病灶（147 个良性，73 个恶性），包括肿块（n=148）和非肿块病变（n=72）。视觉分析和参数图之间 KS 对良恶性病变的鉴别性能没有差异（P=0.119；视觉：AUC 0.875，敏感度 95%，特异性 63%；图：AUC 0.901，敏感度 97%，特异性 65%）。此外，分别分析肿块和非肿块病变，基于参数图和基于视觉曲线类型的 KS 分析之间也没有差异（P=0.130 和 P=0.787）。
KS 的性能在很大程度上独立于曲线类型评估方法，证实了其作为临床决策规则在临床常规中用于任何类型乳腺病变的乳腺 MRI 的稳健性。
