Utility of apparent diffusion coefficient as an imaging biomarker for assessing the proliferative potential of invasive ductal breast cancer

作者：Zhuang, Z.; Zhang, Q.; Zhang, D.; Cheng, F.; Suo, S.; Geng, X.; Hua, J.^*; Xu, J.^*

来源：Clinical Radiology, 2018, 73(5): 473-478.

DOI：10.1016/j.crad.2017.11.019

• INTERNATIONAL EXPERT CONSENSUS
• KI-67 LABELING INDEX
• CARCINOMA IN-SITU
• PROGNOSTIC-FACTORS
• PRIMARY THERAPY
• PARAMETERS
• LESIONS
• MRI
• DIFFERENTIATION
• HIGHLIGHTS

AIM: To determine the clinical utility of apparent diffusion coefficient (ADC) metrics for the non-invasive assessment of tumour proliferation indicated by Ki-67 labelling index (LI) in invasive ductal breast cancer. @@@ MATERIALS AND METHODS: Eighty patients with 80 histopathologically proven invasive ductal breast cancers underwent diffusion-weighted imaging with b-values of 0 and 800 s/mm(2) at a 3-T system. ADC metrics including ADC, ADC(median), ADC(min), ADC(max), and Delta ADC (ADC(max)-ADC(min)) were recorded from the entire tumour volume on ADC maps, and correlated with the Ki-67 LI. Ki-67 staining of >= 14% was considered to indicate high proliferation and <14% was considered to indicate low proliferation. @@@ RESULTS: ADC(min), ADC(max), and Delta ADC showed significant correlations with the Ki-67 LI (for all tumours, r = -.311, 0.436, and 0.551, respectively; for luminal/human epidermal growth factor receptor 2 (HER2)-negative group, r = -0.437, 0.512, and 0.639, respectively; all p<0.01), whereas ADC(mean) and ADC(median) showed no significant correlation (both p>0.05). Receiver operating characteristic (ROC) curve analysis for the differentiation of high-from low-proliferation groups showed that Delta ADC yielded the highest area under the ROC curve for the whole tumour population (0.825; 95% confidence interval [CI]: 0.724, 0.901), as well as for the luminal/HER2-negative group (0.844; 95% CI: 0.692, 0.940). @@@ CONCLUSION: Delta ADC may serve as a promising imaging biomarker for the prediction of Ki-67 proliferation status in invasive ductal breast cancer.

• 出版日期2018-5
• 单位上海交通大学