Zhang Bing, Feng Linlin, Wang Lin, Chen Xin, Li Xiaohui, Yang Quanxin
Department of Radiology, Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, China.
Nan Fang Yi Ke Da Xue Xue Bao. 2020 Apr 30;40(4):562-566. doi: 10.12122/j.issn.1673-4254.2020.04.18.
To evaluate the diagnostic efficacy of Kaiser score for breast lesions presenting as non-mass enhancement.
We collected data from patients with breast lesions presenting as non-mass enhancement on preoperative DCE-MRI between January, 2014 and June, 2019. All the cases were confirmed by surgical pathology or puncture biopsy. With pathology results as the gold standard, we evaluated the diagnostic efficacy of Kaiser score and MRI BI-RADS classification and the consistency between the diagnostic results by the two methods and the pathological results.
A total of 90 lesions were detected in 88 patients, including 28 benign lesions (31.1%) and 62 malignant lesions (68.9%). For diagnosis of the lesions, the sensitivity, specificity, positive predictive value, negative predictive value and accuracy of Kaiser Score were 100%, 75%, 89.9%, 100% and 92%, as compared with 93.5%, 46.4%, 79.5%, 76.5% and 78.9% of MRI BI-RADS, respectively. The diagnostic specificity of Kaiser score was significantly higher than that of BI-RADS classification (=0.021).
The Kaiser score system provides a diagnostic strategy for BI-RADS classification of breast lesions with non-mass enhancement and has a better diagnostic efficacy than BI-RADS classification alone. The use of Kaiser score can significantly improve the diagnostic specificity of such breast lesions for inexperienced radiologists.
评估凯泽评分对表现为非肿块强化的乳腺病变的诊断效能。
收集2014年1月至2019年6月期间术前DCE-MRI表现为非肿块强化的乳腺病变患者的数据。所有病例均经手术病理或穿刺活检确诊。以病理结果为金标准,评估凯泽评分和MRI BI-RADS分类的诊断效能以及两种方法诊断结果与病理结果之间的一致性。
88例患者共检测到90个病变,其中良性病变28个(31.1%),恶性病变62个(68.9%)。对于病变的诊断,凯泽评分的敏感性、特异性、阳性预测值、阴性预测值和准确性分别为100%、75%、89.9%、100%和92%,而MRI BI-RADS的相应值分别为93.5%、46.4%、79.5%、76.5%和78.9%。凯泽评分的诊断特异性显著高于BI-RADS分类(=0.021)。
凯泽评分系统为表现为非肿块强化的乳腺病变的BI-RADS分类提供了一种诊断策略,且诊断效能优于单独的BI-RADS分类。对于经验不足的放射科医生,使用凯泽评分可显著提高此类乳腺病变的诊断特异性。