Pre-treatment CT-based radiomics nomogram for predicting microsatellite instability status in colorectal cancer

医学 列线图 无线电技术 结直肠癌 逻辑回归 放射科 回顾性队列研究 多元分析 肿瘤科 内科学 微卫星不稳定性 队列 癌症 基因 等位基因 化学 微卫星 生物化学
作者
Qian Pei,Xiaoping Yi,Chen Chen,Peipei Pang,Yan Fu,Guangwu Lei,Changyong Chen,Fengbo Tan,Guanghui Gong,Qingling Li,Hongyan Zai,Bihong T. Chen
出处
期刊:European Radiology [Springer Science+Business Media]
卷期号:32 (1): 714-724 被引量:50
标识
DOI:10.1007/s00330-021-08167-3
摘要

Stratification of microsatellite instability (MSI) status in patients with colorectal cancer (CRC) improves clinical decision-making for cancer treatment. The present study aimed to develop a radiomics nomogram to predict the pre-treatment MSI status in patients with CRC. A total of 762 patients with CRC confirmed by surgical pathology and MSI status determined with polymerase chain reaction (PCR) method were retrospectively recruited between January 2013 and May 2019. Radiomics features were extracted from routine pre-treatment abdominal pelvic computed tomography (CT) scans acquired as part of the patients’ clinical care. A radiomics nomogram was constructed using multivariate logistic regression. The performance of the nomogram was evaluated using discrimination, calibration, and decision curves. The radiomics nomogram incorporating radiomics signatures, tumor location, patient age, high-density lipoprotein expression, and platelet counts showed good discrimination between patients with non-MSI-H and MSI-H, with an area under the curve (AUC) of 0.74 [95% CI, 0.68–0.80] in the training cohort and 0.77 [95% CI, 0.68–0.85] in the validation cohort. Favorable clinical application was observed using decision curve analysis. The addition of pathological characteristics to the nomogram failed to show incremental prognostic value. We developed a radiomics nomogram incorporating radiomics signatures and clinical indicators, which could potentially be used to facilitate the individualized prediction of MSI status in patients with CRC. • There is an unmet need to non-invasively determine MSI status prior to treatment. However, the traditional radiological evaluation of CT is limited for evaluating MSI status. • Our non-invasive CT imaging-based radiomics method could efficiently distinguish patients with high MSI disease from those with low MSI disease. • Our radiomics approach demonstrated promising diagnostic efficiency for MSI status, similar to the commonly used IHC method.
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