基于核磁共振成像的放射组学在舌癌中的预后作用:一项多中心验证研究

Marta Tagliabue, Francesca Ruju, Chiara Mossinelli, Aurora Gaeta, Sara Raimondi, Stefania Volpe, Mattia Zaffaroni, Lars Johannes Isaksson, Cristina Garibaldi, Marta Cremonesi, Anna Rapino, Susanna Chiocca, Giacomo Pietrobon, Daniela Alterio, Giuseppe Trisolini, Patrizia Morbini, Vittorio Rampinelli, Alberto Grammatica, Giuseppe Petralia, Barbara Alicja Jereczek-Fossa, Lorenzo Preda, Marco Ravanelli, Roberto Maroldi, Cesare Piazza, Marco Benazzo, Mohssen Ansarin
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引用次数: 0

摘要

目的 放射组学是一个新兴领域,它利用从医学影像中提取的定量特征来预测具有临床意义的结果。验证研究结果对于评估放射组学的适用性至关重要。我们旨在验证之前发表的磁共振成像(MRI)放射组学模型,以预测口腔舌鳞状细胞癌(OTSCC)的肿瘤预后。所有患者均进行了术前 MRI 检查,包括对比增强 T1 加权(CE-T1)、弥散加权序列和表观弥散系数图。我们评估了总生存率(OS)、无局部复发生存率(LRRFS)和特异性死亡率(CSM)。我们根据临床和放射学数据建立了不同的模型。结果我们从意大利三家机构收集了112名连续的独立患者,对之前发表的基于79名不同患者的磁共振成像放射学模型进行了验证。验证队列中临床-放射学混合模型的 C 指数低于训练队列中的 C 指数,但在大多数情况下仍为 > 0.5。CE-T1序列为模型提供了最佳拟合度:对于OS、LRRFS和CSM,获得的C指数分别为0.61、0.59、0.64(治疗前模型)和0.65、0.69、0.70(治疗后模型)。这些发现鼓励了进一步的研究,旨在克服目前由于成像采集、处理和肿瘤体积划分的可变性而造成的局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The prognostic role of MRI-based radiomics in tongue carcinoma: a multicentric validation study

The prognostic role of MRI-based radiomics in tongue carcinoma: a multicentric validation study

Purpose

Radiomics is an emerging field that utilizes quantitative features extracted from medical images to predict clinically meaningful outcomes. Validating findings is crucial to assess radiomics applicability. We aimed to validate previously published magnetic resonance imaging (MRI) radiomics models to predict oncological outcomes in oral tongue squamous cell carcinoma (OTSCC).

Materials and methods

Retrospective multicentric study on OTSCC surgically treated from 2010 to 2019. All patients performed preoperative MRI, including contrast-enhanced T1-weighted (CE-T1), diffusion-weighted sequences and apparent diffusion coefficient map. We evaluated overall survival (OS), locoregional recurrence-free survival (LRRFS), cause-specific mortality (CSM). We elaborated different models based on clinical and radiomic data. C-indexes assessed the prediction accuracy of the models.

Results

We collected 112 consecutive independent patients from three Italian Institutions to validate the previously published MRI radiomic models based on 79 different patients. The C-indexes for the hybrid clinical-radiomic models in the validation cohort were lower than those in the training cohort but remained > 0.5 in most cases. CE-T1 sequence provided the best fit to the models: the C-indexes obtained were 0.61, 0.59, 0.64 (pretreatment model) and 0.65, 0.69, 0.70 (posttreatment model) for OS, LRRFS and CSM, respectively.

Conclusion

Our clinical-radiomic models retain a potential to predict OS, LRRFS and CSM in heterogeneous cohorts across different centers. These findings encourage further research, aimed at overcoming current limitations, due to the variability of imaging acquisition, processing and tumor volume delineation.

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