Al-Khawari Hanaa, Athyal Reji, Kovacs Agnes, Al-Saleh Mervat, Madda John Patrick
Department of Radiology, Faculty of Medicine, Kuwait University, Safat, Kuwait.
Hematol Oncol Stem Cell Ther. 2009;2(3):403-10. doi: 10.1016/s1658-3876(09)50009-x.
Fischer developed a scoring system in 1999 that made identifying malignant lesions much easier for inexperienced radiologists. Our study was performed to assess whether this scoring system would help beginners to accurately diagnose breast lesions on magnetic resonance (MR) imaging and to assess the correlation between the magnetic resonance mammography Breast Imaging Reporting and Data System (MRM BI-RADS) grade and the final diagnosis.
The lesion morphology and contrast kinetics of 63 masses in 41 patients were evaluated on MRI and accorded a MRM BI-RADS final assessment category using the Fischer scoring system. The accuracy was evaluated after the final diagnosis was obtained by tissue sampling and follow-up imaging.
There were 25 malignant and 30 benign lesions. Eight lesions were seen by MRI only and we could not verify their pathology since we did not have MR-guided biopsy facilities at the time of the study. On MR mammography, the proven carcinomatous lesions were characterized as BI-RADS category V in 16 (64%), category IV in 7 (28%), and category III in 2 (8%) lesions. Benign lesions were graded as category V in 3 (10%), category IV in 6 (20%), and category III in 3 (10%), category II in 10 (33%) and category I in 8 (27%) lesions. The MRM BI-RADS category accurately predicted malignancy in 92% and a benign pathology in 70% of the lesions. The overlap between the MRM features of chronic inflammatory lesions and carcinomas resulted in a lower accuracy in diagnosing benign as compared to malignant lesions.
The MRM BI-RADS lexicon using the Fischer scoring system is useful and has a high predictive value, especially for malignant breast lesions, and is easy to apply. Overlapping features between benign inflammatory and malignant lesions might yield a reduced accuracy in inflammatory pathologies.
1999年菲舍尔开发了一种评分系统，使经验不足的放射科医生更容易识别恶性病变。我们进行这项研究是为了评估该评分系统是否有助于初学者在磁共振（MR）成像上准确诊断乳腺病变，并评估磁共振乳腺造影乳腺影像报告和数据系统（MRM BI-RADS）分级与最终诊断之间的相关性。
对41例患者的63个肿块的病变形态和对比剂动力学进行了MRI评估，并使用菲舍尔评分系统给予MRM BI-RADS最终评估类别。在通过组织取样和随访成像获得最终诊断后评估准确性。
有25个恶性病变和30个良性病变。仅通过MRI发现8个病变，由于研究时我们没有MR引导活检设备，因此无法核实其病理情况。在MR乳腺造影上，经证实的癌性病变在16个（64%）病变中被归类为BI-RADS V类，在7个（28%）病变中为IV类，在2个（8%）病变中为III类。良性病变在3个（10%）病变中被分级为V类，在6个（20%）病变中为IV类，在3个（10%）病变中为III类，在10个（33%）病变中为II类，在8个（27%）病变中为I类。MRM BI-RADS类别在92%的病变中准确预测了恶性，在70%的病变中准确预测了良性病理。慢性炎症病变和癌的MRM特征之间的重叠导致诊断良性病变的准确性低于恶性病变。
使用菲舍尔评分系统的MRM BI-RADS词典是有用的，具有较高的预测价值，尤其是对于乳腺恶性病变，且易于应用。良性炎症和恶性病变之间的重叠特征可能会降低炎症性病变的诊断准确性。
