Department of Radiology, Hôpital Tenon, Assistance Publique-Hôpitaux de Paris, 75020, Paris, France.
Department of Radiology, Hôpital Tenon, Assistance Publique-Hôpitaux de Paris, 75020, Paris, France.
Diagn Interv Imaging. 2023 Jun;104(6):284-291. doi: 10.1016/j.diii.2023.01.010. Epub 2023 Feb 15.
The purpose of this retrospective study was to demonstrate the validity of early enhancement criteria on ultrafast magnetic resonance imaging (MRI) sequence to predict malignancy in a large population, and the benefit of diffusion-weighted imaging (DWI) to improve the performance of breast MRI.
Women who underwent breast MRI examination between April 2018 and September 2020 and further breast biopsy were retrospectively included. Two readers quoted the different conventional features and classified the lesion according to the BI-RADS classification based on the conventional protocol. Then, the readers checked for the presence of early enhancement (≤ 30 s) on ultrafast sequence and the presence of an apparent diffusion coefficient (ADC) ≥ 1.5 × 10 mm/s to classify the lesions based on morphology and these two functional criteria only.
Two hundred fifty-seven women (median age: 51 years; range: 16-92 years) with 436 lesions (157 benign, 11 borderline and 268 malignant) were included. A MRI protocol plus two simple functional features, early enhancement (≤ 30 s) and an ADC value ≥ 1.5 × 10 mm/s, had a greater accuracy than the conventional protocol to distinguish benign from malignant breast lesions with or without ADC value (P = 0.01 and P = 0.001, respectively) on MRI, mainly due to better classification of benign lesions (increased specificity) with increasing diagnostic confidence of 3.7% and 7.8% respectively.
BI-RADS analysis based on a simple short MRI protocol plus early enhancement on ultrafast sequence and ADC value has a greaterr diagnostic accuracy than a conventional protocol and may avoid unnecessary biopsy.
本回顾性研究旨在证明在大样本人群中，超快磁共振成像（MRI）序列上早期强化标准预测恶性肿瘤的有效性，以及扩散加权成像（DWI）改善乳腺 MRI 性能的作用。
回顾性纳入 2018 年 4 月至 2020 年 9 月间行乳腺 MRI 检查并进一步行乳腺活检的女性。两名读者引用了不同的常规特征，并根据常规方案基于 BI-RADS 分类对病变进行分类。然后，读者检查了超快序列上是否存在早期强化（≤30s）以及表观扩散系数（ADC）是否≥1.5×10mm/s，仅基于形态学和这两个功能标准对病变进行分类。
共纳入 257 名女性（中位年龄：51 岁；范围：16-92 岁）和 436 个病灶（157 个良性、11 个交界性和 268 个恶性）。与不包括 ADC 值时相比，MRI 加两个简单的功能特征（早期强化（≤30s）和 ADC 值≥1.5×10mm/s）的 MRI 协议具有更高的准确性，可区分良性和恶性乳腺病变（分别为 P=0.01 和 P=0.001），主要是由于良性病变的分类更好（特异性增加），诊断置信度分别增加了 3.7%和 7.8%。
基于简单的短 MRI 方案的 BI-RADS 分析加上超快序列上的早期强化和 ADC 值，比常规方案具有更高的诊断准确性，可能避免不必要的活检。
