Mohammadpour Saman, Emami Hassan, Rabiei Reza, Hosseini Azamossadat, Moghaddasi Hamid, Faeghi Fariborz, Bagherzadeh Rafat
Shahid Beheshti University Faculty of Medicine, Department of Health Information Technology and Management, Tehran, Iran.
Shahid Beheshti University Faculty of Medicine, Department of Radiology Technology, Tehran, Iran.
Mol Imaging Radionucl Ther. 2025 Feb 7;34(1):10-25. doi: 10.4274/mirt.galenos.2024.86402.
Among the most important diagnostic indicators of colorectal cancer; however, measuring molecular alterations are invasive and expensive. This study aimed to investigate the application of image processing to predict molecular alterations in colorectal cancer.
In this scoping review, we searched for relevant literature by searching the Web of Science, Scopus, and PubMed databases. The method of selecting the articles and reporting the findings was according to the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses; moreover, the Strengthening the Reporting of Observational Studies in Epidemiology checklist was used to assess the quality of the studies.
Sixty seven out of 2,223 articles, 67 were relevant to the aim of the study, and finally 41 studies with sufficient quality were reviewed. The prediction of Kirsten Rat Sarcoma Viral Oncogene Homolog (KRAS), Neuroblastoma RAS Viral (NRAS), B-Raf proto-oncogene, serine/threonine kinase (BRAF), Tumor Protein 53 (TP53), Adenomatous Polyposis Coli, and microsatellite instability (MSI) with the help of image analysis has received more attention than other molecular characteristics. The studies used computed tomography (CT), magnetic resonance imaging (MRI), and F-FDG positron emission tomography (PET)/CT with radionics and quantitative analysis to predict molecular alterations in colorectal cancer, analyzing features like texture, maximum standard uptake value, and MTV using various statistical methods. In 39 studies, there was a significant relationship between the features extracted from these images and molecular alterations. Different modalities were used to measure the area under the receiver operating characteristic curve for predicting the alterations in KRAS, MSI, BRAF, and TP53, with an average of 78, 81, 80 and 71%, respectively.
This scoping review underscores the potential of radiogenomics in predicting molecular alterations in colorectal cancer through non-invasive imaging modalities, like CT, MRI, and F-FDG PET/CT. The analysis of 41 studies showed the appropriate prediction of key alterations, such as KRAS, NRAS, BRAF, TP53, and MSI, highlighting the promise of radionics and texture features in enhancing predictive accuracy.
虽然分子改变的检测是结直肠癌最重要的诊断指标之一，但检测方法具有侵入性且成本高昂。本研究旨在探讨图像处理技术在预测结直肠癌分子改变方面的应用。
在本范围综述中，我们通过检索科学网、Scopus和PubMed数据库来查找相关文献。文章的选取方法和研究结果的报告遵循系统评价与Meta分析的首选报告项目指南；此外，还使用了加强流行病学观察性研究报告清单来评估研究质量。
在2223篇文章中，有67篇与研究目的相关，最终对41项质量足够的研究进行了综述。借助图像分析对 Kirsten 大鼠肉瘤病毒癌基因同源物（KRAS）、神经母细胞瘤RAS病毒（NRAS）、B-Raf原癌基因、丝氨酸/苏氨酸激酶（BRAF）、肿瘤蛋白53（TP53）、腺瘤性息肉病基因和微卫星不稳定性（MSI）的预测比其他分子特征受到了更多关注。这些研究使用计算机断层扫描（CT）、磁共振成像（MRI）以及F-FDG正电子发射断层扫描（PET）/CT结合放射组学和定量分析来预测结直肠癌的分子改变，使用各种统计方法分析纹理、最大标准摄取值和代谢体积等特征。在39项研究中，从这些图像中提取的特征与分子改变之间存在显著关系。使用不同的模态来测量预测KRAS、MSI、BRAF和TP53改变的受试者操作特征曲线下面积，平均分别为78%、81%、80%和71%。
本范围综述强调了放射组学通过CT、MRI和F-FDG PET/CT等非侵入性成像方式预测结直肠癌分子改变的潜力。对41项研究的分析表明，对KRAS、NRAS、BRAF、TP53和MSI等关键改变有适当的预测，突出了放射组学和纹理特征在提高预测准确性方面的前景。
