Literature DB >> 33994170

Radiomics for Renal Cell Carcinoma: Predicting Outcomes from Immunotherapy and Targeted Therapies-A Narrative Review.

Kathrine S Rallis1, Sam O Kleeman2, Michael Grant3, Katherine L Ordidge4, Anju Sahdev4, Thomas Powles3.   

Abstract

T-cell immunotherapy and molecular targeted therapies have become standard-of-care treatments for renal cell carcinoma (RCC). There is a need to develop robust biomarkers that predict patient outcomes to targeted therapies to personalise treatment. In recent years, quantitative analysis of imaging features, termed radiomics, has been used to extract tumour features. This narrative mini review summarises the evidence for radiomics prediction of immunotherapy and molecular targeted therapy outcomes in RCC. Radiomics may predict survival, treatment response, and disease progression in RCC treated with tyrosine kinase inhibitors (eg, sunitinib) and immune checkpoint inhibitors (eg, nivolumab). Further validation is necessary in large-scale studies. PATIENT
SUMMARY: We summarise evidence on the ability of features extracted from CT (computed tomography) scans to predict patient outcomes from new treatments for kidney cancer. Although these features can predict treatment outcomes for patients, including survival, treatment response, and cancer progression, further research is necessary before this technology can be applied clinically.
Copyright © 2021 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Artificial intelligence; Immunotherapy; Kidney cancer; Machine learning; Molecular targeted therapy; Precision medicine; Radiomics; Renal cell carcinoma; Review

Mesh:

Substances:

Year:  2021        PMID: 33994170     DOI: 10.1016/j.euf.2021.04.024

Source DB:  PubMed          Journal:  Eur Urol Focus        ISSN: 2405-4569


  3 in total

1.  MRI-Based Radiomics and Urine Creatinine for the Differentiation of Renal Angiomyolipoma With Minimal Fat From Renal Cell Carcinoma: A Preliminary Study.

Authors:  Lian Jian; Yan Liu; Yu Xie; Shusuan Jiang; Mingji Ye; Huashan Lin
Journal:  Front Oncol       Date:  2022-05-26       Impact factor: 5.738

2.  Radiomics of Contrast-Enhanced Computed Tomography: A Potential Biomarker for Pretreatment Prediction of the Response to Bacillus Calmette-Guerin Immunotherapy in Non-Muscle-Invasive Bladder Cancer.

Authors:  Lei Ye; Yuntian Chen; Hui Xu; Zhaoxiang Wang; Haixia Li; Jin Qi; Jing Wang; Jin Yao; Jiaming Liu; Bin Song
Journal:  Front Cell Dev Biol       Date:  2022-02-25

3.  A radiogenomics biomarker based on immunological heterogeneity for non-invasive prognosis of renal clear cell carcinoma.

Authors:  Jiahao Gao; Fangdie Ye; Fang Han; Haowen Jiang; Jiawen Zhang
Journal:  Front Immunol       Date:  2022-09-13       Impact factor: 8.786

  3 in total

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