Please use this identifier to cite or link to this item:
https://doi.org/10.5173/ceju.2023.252
Title: | Radiomics vs radiologist in bladder and renal cancer. Results from a systematic review | Authors: | Tramanzoli, Pietro Castellani, Daniele De Stefano, Virgilio Brocca, Carlo Nedbal, Carlotta Chiacchio, Giuseppe Galosi, Andrea Benedetto Da Silva, Rodrigo Donalisio Teoh, Jeremy Yuen-Chun Tiong, Ho Yee Naik, Nithesh Somani, Bhaskar K Gauhar, Vineet |
Keywords: | Science & Technology Life Sciences & Biomedicine Urology & Nephrology diagnosis computer-assisted neoplasm staging urinary bladder neoplasms renal neoplasms radiomics CT METASTASIS PREDICTION |
Issue Date: | 1-Jan-2023 | Publisher: | POLISH UROLOGICAL ASSOC | Citation: | Tramanzoli, Pietro, Castellani, Daniele, De Stefano, Virgilio, Brocca, Carlo, Nedbal, Carlotta, Chiacchio, Giuseppe, Galosi, Andrea Benedetto, Da Silva, Rodrigo Donalisio, Teoh, Jeremy Yuen-Chun, Tiong, Ho Yee, Naik, Nithesh, Somani, Bhaskar K, Gauhar, Vineet (2023-01-01). Radiomics vs radiologist in bladder and renal cancer. Results from a systematic review. CENTRAL EUROPEAN JOURNAL OF UROLOGY 76 (1). ScholarBank@NUS Repository. https://doi.org/10.5173/ceju.2023.252 | Abstract: | Introduction Radiomics in uro-oncology is a rapidly evolving science proving to be a novel approach for optimizing the analysis of massive data from medical images to provide auxiliary guidance in clinicaissues. This scoping review aimed to identify key aspects wherein radiomics can potentially improve the accuracy of diagnosis, staging, and grading of renal and bladder cancer. Material and methods A literature search was performed in June 2022 using PubMed, Embase, and Cochrane Central Controlled Register of Trials. Studies were included if radiomics were compared with radiological reports only. Results Twenty-two papers were included, 4 were pertinent to bladder cancer, and 18 to renal cancer. Radiomics outperforms the visual assessment by radiologists in contrast-enhanced computed tomog-raphy (CECT) to predict muscle invasion but are equivalent to CT reporting by radiologists in predicting lymph node metastasis. Magnetic resonance imaging (MRI) radiomics outperforms radiological reporting for lymph node metastasis. Radiomics perform better than radiologists reporting the probability of renal cell carcinoma, improving interreader concordance and performance. Radiomics also helps to determine differences in types of renal pathology and between malignant lesions from their benign counterparts. Radiomics can be helpful to establish a model for differentiating low-grade from high-grade clear cell renal cancer with high accuracy just from contrast-enhanced CT scans. Conclusions Our review shows that radiomic models outperform individual reports by radiologists by their ability to incorporate many more complex radiological features. | Source Title: | CENTRAL EUROPEAN JOURNAL OF UROLOGY | URI: | https://scholarbank.nus.edu.sg/handle/10635/242060 | ISSN: | 2080-4806 2080-4873 |
DOI: | 10.5173/ceju.2023.252 |
Appears in Collections: | Elements Staff Publications |
Show full item record
Files in This Item:
File | Description | Size | Format | Access Settings | Version | |
---|---|---|---|---|---|---|
Radiomics vs radiologist in bladder and renal cancer. Results from a systematic review.pdf | 1.56 MB | Adobe PDF | OPEN | None | View/Download |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.