基于影像组学鉴别肺腺癌与肺鳞癌：一项系统评价与Meta分析
Radiomics in distinguishing between lung adenocarcinoma and lung squamous cell carcinoma: a systematic review and meta-analysis.
作者信息
Shi Lili, Zhao Jinli, Wei Zhichao, Wu Huiqun, Sheng Meihong
机构信息
Medical School, Nantong University, Nantong, China.
Department of Radiology, Affiliated Hospital of Nantong University, Nantong, China.
出版信息
Front Oncol. 2024 Sep 24;14:1381217. doi: 10.3389/fonc.2024.1381217. eCollection 2024.
OBJECTIVES
The aim of this study was to systematically review the studies on radiomics models in distinguishing between lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) and evaluate the classification performance of radiomics models using images from various imaging techniques.
MATERIALS AND METHODS
PubMed, Embase and Web of Science Core Collection were utilized to search for radiomics studies that differentiate between LUAD and LUSC. The assessment of the quality of studies included utilized the improved Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) and Radiomics Quality Score (RQS). Meta-analysis was conducted to assess the classification performance of radiomics models using various imaging techniques.
RESULTS
The qualitative analysis included 40 studies, while the quantitative synthesis included 21 studies. Median RQS for 40 studies was 12 (range -519). Sixteen studies were deemed to have a low risk of bias and low concerns regarding applicability. The radiomics model based on CT images had a pooled sensitivity of 0.78 (95%CI: 0.710.83), specificity of 0.85 (95%CI:0.730.92), and the area under summary receiver operating characteristic curve (SROC-AUC) of 0.86 (95%CI:0.820.89). As for PET images, the pooled sensitivity was 0.80 (95%CI: 0.610.91), specificity was 0.77 (95%CI: 0.600.88), and the SROC-AUC was 0.85 (95%CI: 0.820.88). PET/CT images had a pooled sensitivity of 0.87 (95%CI: 0.720.94), specificity of 0.88 (95%CI: 0.800.93), and an SROC-AUC of 0.93 (95%CI: 0.910.95). MRI images had a pooled sensitivity of 0.73 (95%CI: 0.610.82), specificity of 0.80 (95%CI: 0.650.90), and an SROC-AUC of 0.79 (95%CI: 0.75~0.82).
CONCLUSION
Radiomics models demonstrate potential in distinguishing between LUAD and LUSC. Nevertheless, it is crucial to conduct a well-designed and powered prospective radiomics studies to establish their credibility in clinical application.
SYSTEMATIC REVIEW REGISTRATION
https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=412851, identifier CRD42023412851.
目的
本研究旨在系统回顾关于影像组学模型鉴别肺腺癌（LUAD）和肺鳞癌（LUSC）的研究，并使用来自各种成像技术的图像评估影像组学模型的分类性能。
材料与方法
利用PubMed、Embase和Web of Science核心合集检索鉴别LUAD和LUSC的影像组学研究。研究质量评估采用改进的诊断准确性研究质量评估（QUADAS-2）和影像组学质量评分（RQS）。进行荟萃分析以评估使用各种成像技术的影像组学模型的分类性能。
结果
定性分析纳入40项研究，定量综合纳入21项研究。40项研究的RQS中位数为12（范围-5至19）。16项研究被认为偏倚风险低且适用性方面顾虑少。基于CT图像的影像组学模型合并敏感度为0.78（95%CI：0.710.83），特异度为0.85（95%CI：0.730.92），汇总受试者工作特征曲线下面积（SROC-AUC）为0.86（95%CI：0.820.89）。对于PET图像，合并敏感度为0.80（95%CI：0.610.91），特异度为0.77（95%CI：0.600.88），SROC-AUC为0.85（95%CI：0.820.88）。PET/CT图像合并敏感度为0.87（95%CI：0.720.94），特异度为0.88（95%CI：0.800.93），SROC-AUC为0.93（95%CI：0.910.95）。MRI图像合并敏感度为0.73（95%CI：0.610.82），特异度为0.80（95%CI：0.65~0.90），SROC-AUC为
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