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磁共振成像-放射组学评估结直肠癌同步肝转移化疗反应。

Magnetic resonance imaging-radiomics evaluation of response to chemotherapy for synchronous liver metastasis of colorectal cancer.

机构信息

Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital of Hangzhou Medical College, Hangzhou 310000, Zhejiang Province, China.

Department of Radiology, Hangzhou Medical College, Hangzhou 310000, Zhejiang Province, China.

出版信息

World J Gastroenterol. 2021 Oct 14;27(38):6465-6475. doi: 10.3748/wjg.v27.i38.6465.

Abstract

BACKGROUND

Synchronous liver metastasis (SLM) is an indicator of poor prognosis for colorectal cancer (CRC). Nearly 50% of CRC patients develop hepatic metastasis, with 15%-25% of them presenting with SLM. The evaluation of SLM in CRC is crucial for precise and personalized treatment. It is beneficial to detect its response to chemotherapy and choose an optimal treatment method.

AIM

To construct prediction models based on magnetic resonance imaging (MRI)-radiomics and clinical parameters to evaluate the chemotherapy response in SLM of CRC.

METHODS

A total of 102 CRC patients with 223 SLM lesions were identified and divided into disease response (DR) and disease non-response (non-DR) to chemotherapy. After standardizing the MRI images, the volume of interest was delineated and radiomics features were calculated. The MRI-radiomics logistic model was constructed after methods of variance/Mann-Whitney test, correlation analysis, and least absolute shrinkage and selection operator in feature selecting. The radiomics score was calculated. The receiver operating characteristics curves by the DeLong test were analyzed with MedCalc software to compare the validity of all models. Additionally, the area under curves (AUCs) of DWI, T2WI, and portal phase of contrast-enhanced sequences radiomics model (Ra-DWI, Ra-T2WI, and Ra-portal phase of contrast-enhanced sequences) were calculated. The radiomics-clinical nomogram was generated by combining radiomics features and clinical characteristics of CA19-9 and clinical N staging.

RESULTS

The AUCs of the MRI-radiomics model were 0.733 and 0.753 for the training (156 lesions with 68 non-DR and 88 DR) and the validation (67 lesions with 29 non-DR and 38 DR) set, respectively. Additionally, the AUCs of the training and the validation set of Ra-DWI were higher than those of Ra-T2WI and Ra-portal phase of contrast-enhanced sequences (training set: 0.652 0.628 and 0.633, validation set: 0.661 0.575 and 0.543). After chemotherapy, the top four of twelve delta-radiomics features of Ra-DWI in the DR group belonged to gray-level run-length matrices radiomics parameters. The radiomics-clinical nomogram containing radiomics score, CA19-9, and clinical N staging was built. This radiomics-clinical nomogram can effectively discriminate the patients with DR from non-DR with a higher AUC of 0.809 (95% confidence interval: 0.751-0.858).

CONCLUSION

MRI-radiomics is conducive to predict chemotherapeutic response in SLM patients of CRC. The radiomics-clinical nomogram, involving radiomics score, CA19-9, and clinical N staging is more effective in predicting chemotherapeutic response.

摘要

背景

同步肝转移(SLM)是结直肠癌(CRC)预后不良的指标。近 50%的 CRC 患者发生肝转移,其中 15%-25%的患者存在 SLM。评估 CRC 中的 SLM 对于精确和个性化治疗至关重要。它有助于检测其对化疗的反应并选择最佳治疗方法。

目的

构建基于磁共振成像(MRI)-放射组学和临床参数的预测模型,以评估 CRC 中 SLM 的化疗反应。

方法

共纳入 102 例 CRC 患者的 223 个 SLM 病变,根据化疗后疾病反应(DR)和非反应(non-DR)分为两组。对 MRI 图像进行标准化后,划定感兴趣区域并计算放射组学特征。采用方差/Mann-Whitney 检验、相关性分析和最小绝对收缩和选择算子(LASSO)进行特征选择后,构建 MRI-放射组学逻辑模型。计算放射组学评分。使用 MedCalc 软件分析 DeLong 检验的受试者工作特征曲线,比较所有模型的有效性。此外,计算 DWI、T2WI 和对比增强序列门静脉期的放射组学模型(Ra-DWI、Ra-T2WI 和 Ra-portal phase of contrast-enhanced sequences)的曲线下面积(AUCs)。通过结合 CA19-9 和临床 N 分期的放射组学特征和临床特征,生成放射组学-临床列线图。

结果

MRI-放射组学模型在训练集(156 个病变,68 个非 DR 和 88 个 DR)和验证集(67 个病变,29 个非 DR 和 38 个 DR)中的 AUC 分别为 0.733 和 0.753。此外,Ra-DWI 在训练集和验证集的 AUC 均高于 Ra-T2WI 和 Ra-portal phase of contrast-enhanced sequences(训练集:0.652、0.628 和 0.633,验证集:0.661、0.575 和 0.543)。化疗后,DR 组 Ra-DWI 的 12 个 delta-放射组学特征中排名前四的属于灰度游程矩阵放射组学参数。构建包含放射组学评分、CA19-9 和临床 N 分期的放射组学-临床列线图。该放射组学-临床列线图可以有效地将 DR 患者与非 DR 患者区分开来,AUC 为 0.809(95%置信区间:0.751-0.858)。

结论

MRI-放射组学有助于预测 CRC 患者的化疗反应。包含放射组学评分、CA19-9 和临床 N 分期的放射组学-临床列线图在预测化疗反应方面更为有效。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/109f/8517787/ff5b692d491a/WJG-27-6465-g001.jpg

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