Department of Precision Medicine, University of Campania "L. Vanvitelli", 80138, Naples, Italy.
Dipartimento Di Diagnostica Per Immagini, Radioterapia Oncologica Ed Ematologia - Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy.
Radiol Med. 2021 Dec;126(12):1571-1583. doi: 10.1007/s11547-021-01436-7. Epub 2021 Dec 4.
Radiomics can provide quantitative features from medical imaging that can be correlated with various biological features and clinical endpoints. Delta radiomics, on the other hand, consists in the analysis of feature variation at different acquisition time points, usually before and after therapy. The aim of this study was to provide a systematic review of the different delta radiomics approaches.
Eligible articles were searched in Embase, PubMed, and ScienceDirect using a search string that included free text and/or Medical Subject Headings (MeSH) with three key search terms: "radiomics", "texture", and "delta". Studies were analysed using QUADAS-2 and the RQS tool.
Forty-eight studies were finally included. The studies were divided into preclinical/methodological (five studies, 10.4%); rectal cancer (six studies, 12.5%); lung cancer (twelve studies, 25%); sarcoma (five studies, 10.4%); prostate cancer (three studies, 6.3%), head and neck cancer (six studies, 12.5%); gastrointestinal malignancies excluding rectum (seven studies, 14.6%), and other disease sites (four studies, 8.3%). The median RQS of all studies was 25% (mean 21% ± 12%), with 13 studies (30.2%) achieving a quality score < 10% and 22 studies (51.2%) < 25%.
Delta radiomics shows potential benefit for several clinical endpoints in oncology (differential diagnosis, prognosis and prediction of treatment response, and evaluation of side effects). Nevertheless, the studies included in this systematic review suffer from the bias of overall low quality, so that the conclusions are currently heterogeneous, not robust, and not replicable. Further research with prospective and multicentre studies is needed for the clinical validation of delta radiomics approaches.
放射组学可以从医学影像中提供定量特征,这些特征可以与各种生物学特征和临床终点相关联。另一方面,Delta 放射组学由在不同采集时间点(通常在治疗前后)分析特征变化组成。本研究的目的是对不同的 Delta 放射组学方法进行系统评价。
使用包括自由文本和/或医学主题词(MeSH)的搜索字符串,在 Embase、PubMed 和 ScienceDirect 中搜索合格的文章,使用三个关键搜索词:“放射组学”、“纹理”和“Delta”。使用 QUADAS-2 和 RQS 工具对研究进行分析。
最终纳入 48 项研究。这些研究分为临床前/方法学(5 项研究,占 10.4%);直肠癌(6 项研究,占 12.5%);肺癌(12 项研究,占 25%);肉瘤(5 项研究,占 10.4%);前列腺癌(3 项研究,占 6.3%);头颈部癌症(6 项研究,占 12.5%);胃肠道恶性肿瘤(不包括直肠)(7 项研究,占 14.6%)和其他疾病部位(4 项研究,占 8.3%)。所有研究的 RQS 中位数为 25%(平均 21%±12%),13 项研究(30.2%)质量评分<10%,22 项研究(51.2%)<25%。
Delta 放射组学在肿瘤学的几个临床终点(鉴别诊断、预后和预测治疗反应以及评估副作用)方面显示出潜在的益处。然而,本系统评价纳入的研究存在整体质量较低的偏倚,因此目前的结论是不一致的、不稳健的、不可复制的。需要进一步开展前瞻性和多中心研究,以验证 Delta 放射组学方法的临床有效性。