医学
新辅助治疗
放射科
乳腺癌
阶段(地层学)
淋巴结
磁共振成像
放射治疗
腋窝淋巴结清扫术
解剖(医学)
肿瘤科
前哨淋巴结
癌症
内科学
古生物学
生物
作者
Beatriu Reig,Alana A. Lewin,Linda Du,Laura Heacock,Hildegard K. Toth,Samantha L. Heller,Yiming Gao,Linda Moy
出处
期刊:Radiographics
[Radiological Society of North America]
日期:2021-05-01
卷期号:41 (3): 665-679
被引量:57
标识
DOI:10.1148/rg.2021200134
摘要
Neoadjuvant therapy is increasingly being used to treat early-stage triple-negative and human epidermal growth factor 2–overexpressing breast cancers, as well as locally advanced and inflammatory breast cancers. The rationales for neoadjuvant therapy are to shrink tumor size and potentially decrease the extent of surgery, to serve as an in vivo test of response to therapy, and to reveal prognostic information for the patient. MRI is the most accurate modality to demonstrate response to therapy and to help ensure accurate presurgical planning. Changes in lesion diameter, volume, and enhancement are used to predict complete response, partial response, or nonresponse to therapy. However, residual disease may be overestimated or underestimated at MRI. Fibrosis, necrotic tumors, and residual benign masses may be causes of overestimation of residual disease. Nonmass lesions, invasive lobular carcinoma, hormone receptor–positive tumors, nonconcentric shrinkage patterns, the use of antiangiogenic therapy, and late-enhancing foci may be causes of underestimation of residual disease. In patients with known axillary lymph node metastasis, neoadjuvant therapy may be followed by targeted axillary dissection to avoid the potential morbidity associated with an axillary lymph node dissection. Diffusion-weighted imaging, radiomics, machine learning, and deep learning methods are under investigation to improve MRI accuracy in predicting treatment response. ©RSNA, 2021
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