External validation of multiparametric magnetic resonance imaging-based decision rules for characterizing breast lesions and comparison to Kaiser score and breast imaging reporting and data system (BI-RADS) category.

IF 2.9 2区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Quantitative Imaging in Medicine and Surgery Pub Date : 2025-01-02 Epub Date: 2024-12-30 DOI:10.21037/qims-23-1783
Yongyu An, Guoqun Mao, Sisi Zheng, Yangyang Bu, Zhen Fang, Jiangnan Lin, Changyu Zhou
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Abstract

Background: Breast imaging reporting and data system (BI-RADS) provides standard descriptors but not detailed decision rules for characterizing breast lesions. Diffusion-weighted imaging (DWI) and T2-weighted imaging (T2WI) are also not incorporated in the BI-RADS. Several multiparametric magnetic resonance imaging (mpMRI)-based decision rules have been developed to differentiate breast lesions, but lack external validation. This study aims to externally validate several mpMRI-based decision rules for characterizing breast lesions and compare them with Kaiser score and BI-RADS category.

Methods: There were 206 patients with 218 pathology-proven breast lesions (99 malignancies) included in this retrospective study from January 2018 to May 2018. Two radiologists blinded to pathology evaluated breast lesions according to the three mpMRI-based decision rules (Kim, Istomin, Zhong) and Kaiser score. BI-RADS category was extracted from radiology reports and also analysed. The diagnostic performances of the four decision rules and BI-RADS category were calculated and compared for different lesion types [mass and non-mass enhancement (NME)] and size (≤10 and >10 mm). The unnecessary biopsy rates for BI-RADS 4 lesions were calculated by the four decision rules.

Results: The three mpMRI-based decision rules showed area under the curve (AUC) of 0.81-0.87 for all lesions, 0.86-0.92 for mass lesions, 0.68-0.82 for NME, and 0.68-0.87 for lesion size ≤10 mm, 0.82-0.87 for lesion size >10 mm. Kaiser score showed the highest diagnostic performance for all subgroups except for lesion size ≤10 mm. No significant differences were found in AUC between Kaiser score and BI-RADS category. The mpMRI-based decision rules showed high sensitivity of 100% in all subgroups at the expense of low specificity (range, 2.9-41.2%). In contrast, Kaiser score demonstrated a significantly higher specificity of 73.5-92.9% than the three mpMRI-based decision rules at the cost of a decreased sensitivity (range, 60.0-93.6%) in different subgroups. The unnecessary biopsy rates for BI-RADS 4 lesions were 9.8% (Istomin), 12.2% (Zhong), 14.6% (Kim) and 70.7% (Kaiser score), respectively.

Conclusions: The mpMRI-based decision rules showed high sensitivity but low specificity for characterizing breast lesions, and their diagnostic efficiencies were inferior to Kaiser score and BI-RADS category.

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基于多参数磁共振成像的乳腺病变特征判定规则的外部验证,并与Kaiser评分和乳腺成像报告和数据系统(BI-RADS)类别进行比较。
背景:乳腺成像报告和数据系统(BI-RADS)提供了标准的描述符,但不是乳腺病变特征的详细决策规则。弥散加权成像(DWI)和t2加权成像(T2WI)也未纳入BI-RADS。一些基于多参数磁共振成像(mpMRI)的决策规则已被开发用于区分乳腺病变,但缺乏外部验证。本研究旨在从外部验证几种基于mpmri的乳腺病变特征判定规则,并将其与Kaiser评分和BI-RADS分类进行比较。方法:回顾性研究2018年1月至2018年5月206例经病理证实的218例乳腺病变(99例恶性肿瘤)。两名不了解病理学的放射科医生根据三种基于mpmri的决策规则(Kim, Istomin, Zhong)和Kaiser评分来评估乳腺病变。从放射学报告中提取BI-RADS分类并进行分析。计算四种决策规则和BI-RADS分类对不同病灶类型[肿块和非肿块增强(NME)]和大小(≤10和>10 mm)的诊断性能并进行比较。根据四个决策规则计算BI-RADS 4病变的不必要活检率。结果:三种基于mpmri的决策规则显示,所有病变的曲线下面积(AUC)为0.81 ~ 0.87,肿块为0.86 ~ 0.92,NME为0.68 ~ 0.82,病变大小≤10 mm为0.68 ~ 0.87,病变大小为> ~ 10 mm为0.82 ~ 0.87。除病变大小≤10 mm外,Kaiser评分对所有亚组的诊断效能最高。Kaiser评分与BI-RADS评分的AUC无显著差异。基于mpmri的决策规则在所有亚组中显示出100%的高灵敏度,但特异性较低(范围为2.9-41.2%)。相比之下,Kaiser评分在不同亚组中的特异性为73.5-92.9%,明显高于三种基于mpmri的决策规则,但代价是灵敏度降低(范围为60.6 -93.6%)。BI-RADS 4病变的不必要活检率分别为9.8% (Istomin)、12.2% (Zhong)、14.6% (Kim)和70.7% (Kaiser评分)。结论:基于mpmri的决策规则对乳腺病变的诊断敏感性高,特异性低,诊断效率低于Kaiser评分和BI-RADS分类。
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来源期刊
Quantitative Imaging in Medicine and Surgery
Quantitative Imaging in Medicine and Surgery Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
4.20
自引率
17.90%
发文量
252
期刊介绍: Information not localized
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