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Lim EJ, Yen J, Fong KY, Tiong HY, Aslim EJ, Ng LG, Castellani D, Borgheresi A, Agostini A, Somani BK, Gauhar V, Gan VHL. Radiomics in Kidney Transplantation: A Scoping Review of Current Applications, Limitations, and Future Directions. Transplantation 2024; 108:643-653. [PMID: 37389652 DOI: 10.1097/tp.0000000000004711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/01/2023]
Abstract
Radiomics is increasingly applied to the diagnosis, management, and outcome prediction of various urological conditions. The purpose of this scoping review is to evaluate the current evidence of the application of radiomics in kidney transplantation, especially its utility in diagnostics and therapeutics. An electronic literature search on radiomics in the setting of transplantation was conducted on PubMed, EMBASE, and Scopus from inception to September 23, 2022. A total of 16 studies were included. The most widely studied clinical utility of radiomics in kidney transplantation is its use as an adjunct to diagnose rejection, potentially reducing the need for unnecessary biopsies or guiding decisions for earlier biopsies to optimize graft survival. Technology such as optical coherence tomography is a noninvasive procedure to build high-resolution optical cross-section images of the kidney cortex in situ and in real time, which can provide histopathological information of donor kidney candidates for transplantation, and to predict posttransplant function. This review shows that, although radiomics in kidney transplants is still in its infancy, it has the potential for large-scale implementation. Its greatest potential lies in the correlation with conventional established diagnostic evaluation for living donors and potential in predicting and detecting rejection postoperatively.
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Affiliation(s)
- Ee Jean Lim
- Department of Urology, Singapore General Hospital, Singapore
| | - Jie Yen
- Department of Urology, Singapore General Hospital, Singapore
| | - Khi Yung Fong
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Ho Yee Tiong
- Department of Urology, National University Hospital, Singapore
| | | | - Lay Guat Ng
- Department of Urology, Singapore General Hospital, Singapore
| | - Daniele Castellani
- Urology Unit, Azienda Ospedaliero Universitaria delle Marche, Università Politecnica delle Marche, Ancona, Italy
| | - Alessandra Borgheresi
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Ancona, Italy
- Department of Radiology, University Hospital "Azienda Ospedaliera Universitaria delle Marche," Ancona, Italy
| | - Andrea Agostini
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Ancona, Italy
- Department of Radiology, University Hospital "Azienda Ospedaliera Universitaria delle Marche," Ancona, Italy
| | - Bhaskar Kumar Somani
- Department of Urology, University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom
| | - Vineet Gauhar
- Department of Urology, Ng Teng Fong Hospital, Singapore
| | - Valerie Huei Li Gan
- Department of Urology, Singapore General Hospital, Singapore
- SingHealth Duke-NUS Transplant Centre, Singapore
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Martin-Noguerol T, Luna A. External validation of AI algorithms in breast radiology: the last healthcare security checkpoint? Quant Imaging Med Surg 2021; 11:2888-2892. [PMID: 34079749 DOI: 10.21037/qims-20-1409] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Affiliation(s)
| | - Antonio Luna
- Radiology Department, HTmédica, Clinica Las Nieves, Jaén, Spain
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