Role of tumor-specific and whole-body imaging biomarkers for prediction of recurrence in patients with stage III colorectal cancer.

IF 2.3 3区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Amir A Borhani, Peng Zhang, Brenda Diergaarde, Sophie Darwiche, Kalina Chuperlovska, Stewart C Wang, Robert E Schoen, Grace L Su
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引用次数: 0

Abstract

Background: Imaging biomarkers are emerging as non-invasive predictors of cancer prognosis and clinical outcome. We assessed tumor-specific ("radiomics") and body composition imaging features ("morphomics") extracted from baseline pre-treatment CT for prediction of recurrence in patients with stage III colorectal cancer (CRC).

Methods: Patients with newly diagnosed stage III CRC were enrolled in this prospective observational study. Patients with available preoperative scans were included (N = 101). The tumor, if visible, was manually segmented and first-order radiomics features were extracted with a commercially available software. The morphomics features (reflecting muscle, fat, and bone characteristics) were extracted in a standardized fashion using a proprietary software and the values were adjusted and normalized based on a reference standard. Time to recurrence was the final outcome. Correlation between demographics, clinical features, radiomics, and morphomics features and outcome were assessed using univariate and multivariate tests as well as Kaplan-Meier and log-rank tests.

Results: Morphomic analysis was performed in all 101 patients. 60 patients had discrete tumors suitable for radiomics analysis. These patients had lower ECOG score (p < 0.05), more muscle mass (p > 0.05), and lower fat density (p > 0.05) compared to the patients in whom radiomics analysis could not be performed. Pathological stage (HR: 2.69; p = 0.03), CEA level after surgery (HR: 1.11 for 1 ng/mL; p < 0.005), bone mineral density (HR: 1.01 for 1 Hounsfield Unit; p < 0.01), and tumor skewness (HR: 0.33 for 1 unit; p < 0.05) had association with recurrence based on both univariate and multivariate analyses. A model using Cox's regression analyses was able to divide the patients into low-, medium-, and high-risk for recurrence.

Conclusions: Both radiomics and morphomics features were independently associated with the risk of CRC recurrence and, when combined, each contributed valuable information to explain risk of recurrence.

Trial registration: Clinical trial.gov NCT02842203. Patient recruitment occurred between 22/07/2016 and 18/03/2020.

肿瘤特异性和全身成像生物标志物在预测 III 期结直肠癌患者复发中的作用。
背景:影像生物标志物正在成为癌症预后和临床结果的非侵入性预测指标。我们评估了从治疗前基线 CT 中提取的肿瘤特异性("放射组学")和身体成分成像特征("形态组学"),用于预测 III 期结直肠癌(CRC)患者的复发:这项前瞻性观察研究招募了新确诊的 III 期 CRC 患者。有术前扫描结果的患者被纳入研究(N = 101)。如果肿瘤可见,则进行人工分割,并使用市售软件提取一阶放射组学特征。形态组学特征(反映肌肉、脂肪和骨骼特征)使用专有软件以标准化方式提取,并根据参考标准对数值进行调整和归一化。复发时间是最终结果。使用单变量和多变量检验以及 Kaplan-Meier 检验和对数秩检验评估人口统计学、临床特征、放射组学和形态组学特征与结果之间的相关性:对所有 101 例患者进行了形态组学分析。60名患者的肿瘤离散,适合进行放射组学分析。与无法进行放射组学分析的患者相比,这些患者的 ECOG 评分较低(P 0.05),脂肪密度较低(P > 0.05)。病理分期(HR:2.69;P = 0.03)、术后 CEA 水平(HR:1 毫微克/毫升为 1.11;P放射组学和形态组学特征均与 CRC 复发风险独立相关,当两者结合时,每个特征都为解释复发风险提供了有价值的信息:临床试验.gov NCT02842203。患者招募时间为2016年7月22日至2020年3月18日。
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来源期刊
Abdominal Radiology
Abdominal Radiology Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
5.20
自引率
8.30%
发文量
334
期刊介绍: Abdominal Radiology seeks to meet the professional needs of the abdominal radiologist by publishing clinically pertinent original, review and practice related articles on the gastrointestinal and genitourinary tracts and abdominal interventional and radiologic procedures. Case reports are generally not accepted unless they are the first report of a new disease or condition, or part of a special solicited section. Reasons to Publish Your Article in Abdominal Radiology: · Official journal of the Society of Abdominal Radiology (SAR) · Published in Cooperation with: European Society of Gastrointestinal and Abdominal Radiology (ESGAR) European Society of Urogenital Radiology (ESUR) Asian Society of Abdominal Radiology (ASAR) · Efficient handling and Expeditious review · Author feedback is provided in a mentoring style · Global readership · Readers can earn CME credits
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