乳腺MRI影像组学联合21基因检测预测乳腺癌复发风险的研究进展

Advances in Breast MRI Radiomics Combined with 21-gene Detection to Predict BreastCancerRecurrenceRisk

乳腺癌具有高度异质性,且生物学行为差异大,不同患者的治疗方法与疗效不尽相同.在发展迅速的现代医疗水平之下,术后复发转移仍是其死亡的重要原因之一.因此如何更精准地预测乳腺癌患者术后复发风险成为当前临床工作中亟待解决的问题.21基因检测是近年来快速发展的乳腺癌复发风险预测的可靠方法,但是由于恶性肿瘤普遍存在的异质性,乳腺癌患者的基因检测不可避免会存在取样的局限性.乳腺MRI影像组学无创且高通量地提取MRI图像中的影像学特征,并结合临床特征获取更多肿瘤内在信息进而指导临床实现精准治疗,具有显著的临床应用价值.近年来已有国内外学者利用影像组学技术预测乳腺肿瘤复发风险,然而目前影像学标志物缺乏足够的生物学验证使其临床应用受限.因此联合乳腺MRI影像组学与21基因检测,寻找影像学特征与检测结果的相关性,或能通过无创的MRI影像学检查代替相应临床指标以预测乳腺癌复发风险具有重要意义.本文就以上两者的关联以及其研究进展进行综述,以期为临床诊疗提供借鉴.

Breast cancer is highly heterogeneous,and has large differences in biological behavior.Different patients have different treatment methods and curative effects.Under the rapidly developing modern medical level,postoperative recurrence and metastasis are still one of the important causes of death.Therefore,how to more accurately predict the postoperative recurrence risk of breast cancer patients has become an urgent problem to be solved in current clinical work.21-gene detection is a reliable method for predicting the recurrence risk of breast cancer that has developed rapidly in recent years.However,due to the ubiquitous heterogeneity of malignant tumors,genetic testing of breast cancer patients inevitably has sampling limitations.Breast MRI radiomics can be used to non-invasively and high-throughput extract imaging features from MR images,and combine with clinical features to obtain more intrinsic tumor information to guide the clinical realization of precise treatment,which has significant clinical application value.In recent years,domestic and foreign researchers have used radiomics technology to predict the risk of breast tumor recurrence.However,the current lack of sufficient biological validation of imaging markers limits their clinical application.Therefore,combining breast MRI radiomics and 21-gene detection to find the correlation between imaging features and detection results,non-invasive MRI examinations can replace the corresponding clinical indicators to predict the risk of breast cancer recurrence. This article reviews the relationshipbetween the above two and their research progress, in order to provide reference for clinical diagnosis and treatment.