Faiella Eliodoro, Santucci Domiziana, Calabrese Alessandro, Russo Fabrizio, Vadalà Gianluca, Zobel Bruno Beomonte, Soda Paolo, Iannello Giulio, de Felice Carlo, Denaro Vincenzo
Department of Radiology, University of Rome "Campus Bio-Medico", Via Alvaro del Portillo, 00128 Roma, Italy.
Department of Radiology, University of Rome "Sapienza", Viale del Policlinico, 00161 Roma, Italy.
Int J Environ Res Public Health. 2022 Feb 8;19(3):1880. doi: 10.3390/ijerph19031880.
(1) Background: The purpose of this review is to study the role of radiomics as a supporting tool in predicting bone disease status, differentiating benign from malignant bone lesions, and characterizing malignant bone lesions. (2) Methods: Two reviewers conducted the literature search independently. Thirteen articles on radiomics as a decision support tool for bone lesions were selected. The quality of the methodology was evaluated according to the radiomics quality score (RQS). (3) Results: All studies were published between 2018 and 2021 and were retrospective in design. Eleven (85%) studies were MRI-based, and two (15%) were CT-based. The sample size was <200 patients for all studies. There is significant heterogeneity in the literature, as evidenced by the relatively low RQS value (average score = 22.6%). There is not a homogeneous protocol used for MRI sequences among the different studies, although the highest predictive ability was always obtained in T2W-FS. Six articles (46%) reported on the potential application of the model in a clinical setting with a decision curve analysis (DCA). (4) Conclusions: Despite the variability in the radiomics method application, the similarity of results and conclusions observed is encouraging. Substantial limits were found; prospective and multicentric studies are needed to affirm the role of radiomics as a supporting tool.
(1) 背景：本综述的目的是研究放射组学作为一种辅助工具在预测骨疾病状态、鉴别骨良性与恶性病变以及对恶性骨病变进行特征描述方面的作用。(2) 方法：两名研究者独立进行文献检索。选取了13篇关于放射组学作为骨病变决策支持工具的文章。根据放射组学质量评分（RQS）对方法学质量进行评估。(3) 结果：所有研究均发表于2018年至2021年之间，且均为回顾性研究设计。11项（85%）研究基于MRI，2项（15%）基于CT。所有研究的样本量均小于200例患者。文献中存在显著异质性，RQS值相对较低（平均得分 = 22.6%）即证明了这一点。不同研究之间用于MRI序列的方案并不统一，尽管在T2W-FS序列中总是能获得最高的预测能力。6篇文章（46%）报道了模型在临床环境中通过决策曲线分析（DCA）的潜在应用。(4) 结论：尽管放射组学方法的应用存在差异，但观察到的结果和结论的相似性令人鼓舞。发现了实质性的局限性；需要开展前瞻性和多中心研究来确定放射组学作为一种辅助工具的作用。
