Corti Anna, De Cecco Loris, Cavalieri Stefano, Lenoci Deborah, Pistore Federico, Calareso Giuseppina, Mattavelli Davide, de Graaf Pim, Leemans C René, Brakenhoff Ruud H, Ravanelli Marco, Poli Tito, Licitra Lisa, Corino Valentina, Mainardi Luca
Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy.
Integrated Biology of Rare Tumors, Department of Research, Fondazione IRCCS, Istituto Nazionale dei Tumori, Milan, Italy.
Biomark Res. 2023 Jul 16;11(1):69. doi: 10.1186/s40364-023-00494-5.
. At present, the prognostic prediction in advanced oral cavity squamous cell carcinoma (OCSCC) is based on the tumor-node-metastasis (TNM) staging system, and the most used imaging modality in these patients is magnetic resonance image (MRI). With the aim to improve the prediction, we developed an MRI-based radiomic signature as a prognostic marker for overall survival (OS) in OCSCC patients and compared it with published gene expression signatures for prognosis of OS in head and neck cancer patients, replicated herein on our OCSCC dataset.
For each patient, 1072 radiomic features were extracted from T1 and T2-weighted MRI (T1w and T2w). Features selection was performed, and an optimal set of five of them was used to fit a Cox proportional hazard regression model for OS. The radiomic signature was developed on a multi-centric locally advanced OCSCC retrospective dataset (n = 123) and validated on a prospective cohort (n = 108).
The performance of the signature was evaluated in terms of C-index (0.68 (IQR 0.66-0.70)), hazard ratio (HR 2.64 (95% CI 1.62-4.31)), and high/low risk group stratification (log-rank p < 0.001, Kaplan-Meier curves). When tested on a multi-centric prospective cohort (n = 108), the signature had a C-index of 0.62 (IQR 0.58-0.64) and outperformed the clinical and pathologic TNM stage and six out of seven gene expression prognostic signatures. In addition, the significant difference of the radiomic signature between stages III and IVa/b in patients receiving surgery suggests a potential association of MRI features with the pathologic stage.
Overall, the present study suggests that MRI signatures, containing non-invasive and cost-effective remarkable information, could be exploited as prognostic tools.
目前,晚期口腔鳞状细胞癌(OCSCC)的预后预测基于肿瘤-淋巴结-转移(TNM)分期系统,这些患者最常用的成像方式是磁共振成像(MRI)。为了改善预测,我们开发了一种基于MRI的放射组学特征作为OCSCC患者总生存期(OS)的预后标志物,并将其与已发表的用于头颈癌患者OS预后的基因表达特征进行比较,本文在我们的OCSCC数据集上进行了重复验证。
对于每位患者,从T1加权和T2加权MRI(T1w和T2w)中提取1072个放射组学特征。进行特征选择,并使用其中五个最佳特征集来拟合OS的Cox比例风险回归模型。放射组学特征是在一个多中心局部晚期OCSCC回顾性数据集(n = 123)上开发的,并在前瞻性队列(n = 108)中进行验证。
根据C指数(0.68(IQR 0.66 - 0.70))、风险比(HR 2.64(95% CI 1.62 - 4.31))和高/低风险组分层(对数秩p < 0.001,Kaplan-Meier曲线)对该特征的性能进行了评估。当在多中心前瞻性队列(n = 108)上进行测试时,该特征的C指数为0.62(IQR 0.58 - 0.64),优于临床和病理TNM分期以及七个基因表达预后特征中的六个。此外,接受手术的患者在III期和IVa/b期之间放射组学特征的显著差异表明MRI特征与病理分期之间可能存在关联。
总体而言,本研究表明,包含非侵入性且具有成本效益的显著信息的MRI特征可作为预后工具加以利用。