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基于MRI的膀胱癌影像组学:系统评价与影像组学质量评分评估

MRI-Based Radiomics in Bladder Cancer: A Systematic Review and Radiomics Quality Score Assessment.

作者信息

Boca Bianca, Caraiani Cosmin, Telecan Teodora, Pintican Roxana, Lebovici Andrei, Andras Iulia, Crisan Nicolae, Pavel Alexandru, Diosan Laura, Balint Zoltan, Lupsor-Platon Monica, Buruian Mircea Marian

机构信息

Department of Radiology, "George Emil Palade", University of Medicine, Pharmacy, Science and Technology of Targu Mures, 540139 Targu Mures, Romania.

Department of Medical Imaging and Nuclear Medicine, "Iuliu Hațieganu" University of Medicine and Pharmacy Cluj-Napoca, 400012 Cluj-Napoca, Romania.

出版信息

Diagnostics (Basel). 2023 Jul 6;13(13):2300. doi: 10.3390/diagnostics13132300.

Abstract

(1): Background: With the recent introduction of vesical imaging reporting and data system (VI-RADS), magnetic resonance imaging (MRI) has become the main imaging method used for the preoperative local staging of bladder cancer (BCa). However, the VI-RADS score is subject to interobserver variability and cannot provide information about tumor cellularity. These limitations may be overcome by using a quantitative approach, such as the new emerging domain of radiomics. (2) Aim: To systematically review published studies on the use of MRI-based radiomics in bladder cancer. (3) Materials and Methods: We performed literature research using the PubMed MEDLINE, Scopus, and Web of Science databases using PRISMA principles. A total of 1092 papers that addressed the use of radiomics for BC staging, grading, and treatment response were retrieved using the keywords "bladder cancer", "magnetic resonance imaging", "radiomics", and "textural analysis". (4) Results: 26 papers met the eligibility criteria and were included in the final review. The principal applications of radiomics were preoperative tumor staging ( = 13), preoperative prediction of tumor grade or molecular correlates ( = 9), and prediction of prognosis/response to neoadjuvant therapy ( = 4). Most of the developed radiomics models included second-order features mainly derived from filtered images. These models were validated in 16 studies. The average radiomics quality score was 11.7, ranging between 8.33% and 52.77%. (5) Conclusions: MRI-based radiomics holds promise as a quantitative imaging biomarker of BCa characterization and prognosis. However, there is still need for improving the standardization of image preprocessing, feature extraction, and external validation before applying radiomics models in the clinical setting.

摘要

(1) 背景:随着膀胱影像报告和数据系统(VI-RADS)的近期引入,磁共振成像(MRI)已成为用于膀胱癌(BCa)术前局部分期的主要成像方法。然而,VI-RADS评分存在观察者间差异,且无法提供肿瘤细胞密度信息。这些局限性可通过使用定量方法来克服,比如新兴的放射组学领域。(2) 目的:系统回顾已发表的关于基于MRI的放射组学在膀胱癌中应用的研究。(3) 材料与方法:我们按照PRISMA原则,使用PubMed MEDLINE、Scopus和Web of Science数据库进行文献研究。通过关键词“膀胱癌”“磁共振成像”“放射组学”和“纹理分析”,共检索到1092篇涉及放射组学用于BC分期、分级和治疗反应的论文。(4) 结果:26篇论文符合纳入标准并被纳入最终综述。放射组学的主要应用为术前肿瘤分期(n = 13)、术前肿瘤分级或分子相关性预测(n = 9)以及预后/新辅助治疗反应预测(n = 4)。大多数已开发的放射组学模型包括主要从滤波图像中导出的二阶特征。这些模型在16项研究中得到验证。放射组学质量评分平均为11.7,范围在8.33%至52.77%之间。(5) 结论:基于MRI的放射组学有望成为BCa特征化和预后的定量成像生物标志物。然而,在将放射组学模型应用于临床之前,仍需要提高图像预处理、特征提取和外部验证的标准化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94b1/10341244/350866e91ca9/diagnostics-13-02300-g001.jpg

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