Literature DB >> 33495866

Radiomics to better characterize small renal masses.

Teele Kuusk1,2, Joana B Neves2, Maxine Tran2,3, Axel Bex4,5,6.   

Abstract

PURPOSE: Radiomics is a specific field of medical research that uses programmable recognition tools to extract objective information from standard images to combine with clinical data, with the aim of improving diagnostic, prognostic, and predictive accuracy beyond standard visual interpretation. We performed a narrative review of radiomic applications that may support improved characterization of small renal masses (SRM). The main focus of the review was to identify and discuss methods which may accurately differentiate benign from malignant renal masses, specifically between renal cell carcinoma (RCC) subtypes and from angiomyolipoma without visible fat (fat-poor AML) and oncocytoma. Furthermore, prediction of grade, sarcomatoid features, and gene mutations would be of importance in terms of potential clinical utility in prognostic stratification and selecting personalised patient management strategies.
METHODS: A detailed search of original articles was performed using the PubMed-MEDLINE database until 20 September 2020 to identify the English literature relevant to radiomics applications in renal tumour assessment. In total, 42 articles were included in the analysis in 3 main categories related to SRM: prediction of benign versus malignant SRM, subtypes, and nuclear grade, and other features of aggressiveness.
CONCLUSION: Overall, studies reported the superiority of radiomics over expert radiological assessment, but were mainly of retrospective design and therefore of low-quality evidence. However, it is clear that radiomics is an attractive modality that has the potential to improve the non-invasive diagnostic accuracy of SRM imaging and prediction of its natural behaviour. Further prospective validation studies of radiomics are needed to augment management algorithms of SRM.
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.

Entities:  

Keywords:  Artificial intelligence; Imaging; Radiomics; Renal cell carcinoma; Small renal mass

Mesh:

Year:  2021        PMID: 33495866     DOI: 10.1007/s00345-021-03602-y

Source DB:  PubMed          Journal:  World J Urol        ISSN: 0724-4983            Impact factor:   4.226


  49 in total

1.  Association of Prevalence of Benign Pathologic Findings After Partial Nephrectomy With Preoperative Imaging Patterns in the United States From 2007 to 2014.

Authors:  Jae Heon Kim; Shufeng Li; Yash Khandwala; Kyung Jin Chung; Hyung Keun Park; Benjamin I Chung
Journal:  JAMA Surg       Date:  2019-03-01       Impact factor: 14.766

2.  Renal Mass Biopsy is Associated with Reduction in Surgery for Early-Stage Kidney Cancer.

Authors:  Hiten D Patel; Paige E Nichols; Zhuo Tony Su; Mohit Gupta; Joseph G Cheaib; Mohamad E Allaf; Phillip M Pierorazio
Journal:  Urology       Date:  2019-09-16       Impact factor: 2.649

Review 3.  Renal tumor biopsy: indicators, technique, safety, accuracy results, and impact on treatment decision management.

Authors:  Jaime O Herrera-Caceres; Antonio Finelli; Michael A S Jewett
Journal:  World J Urol       Date:  2018-07-18       Impact factor: 4.226

4.  Shared decision-making for the management of small renal masses - development and acceptability testing of a novel patient decision aid.

Authors:  Kristen McAlpine; Rodney H Breau; Dawn Stacey; Christopher Knee; Michael A S Jewett; Philippe D Violette; Patrick O Richard; Ilias Cagiannos; Christopher Morash; Luke T Lavallée
Journal:  Can Urol Assoc J       Date:  2020-06-16       Impact factor: 1.862

5.  Contemporary surgical management of renal oncocytoma: a nation's outcome.

Authors:  Joana B Neves; John Withington; Sarah Fowler; Prasad Patki; Ravi Barod; Faiz Mumtaz; Tim O'Brien; Michael Aitchison; Axel Bex; Maxine G B Tran
Journal:  BJU Int       Date:  2018-03-02       Impact factor: 5.588

Review 6.  Systematic Review and Meta-analysis of Diagnostic Accuracy of Percutaneous Renal Tumour Biopsy.

Authors:  Lorenzo Marconi; Saeed Dabestani; Thomas B Lam; Fabian Hofmann; Fiona Stewart; John Norrie; Axel Bex; Karim Bensalah; Steven E Canfield; Milan Hora; Markus A Kuczyk; Axel S Merseburger; Peter F A Mulders; Thomas Powles; Michael Staehler; Borje Ljungberg; Alessandro Volpe
Journal:  Eur Urol       Date:  2015-08-29       Impact factor: 20.096

7.  Does renal tumor biopsies for small renal carcinoma increase the risk of upstaging on final surgery pathology report and the risk of recurrence?

Authors:  Charles Asselin; Antonio Finelli; Rodney H Breau; Ranjeeta Mallick; Anil Kapoor; Ricardo A Rendon; Simon Tanguay; Frédéric Pouliot; Adrian Fairey; Luke T Lavallée; Franck Bladou; Jun Kawakami; Alan I So; Patrick O Richard
Journal:  Urol Oncol       Date:  2020-07-18       Impact factor: 3.498

Review 8.  Characterization of small (<4cm) solid renal masses by computed tomography and magnetic resonance imaging: Current evidence and further development.

Authors:  N Schieda; R S Lim; M D F McInnes; I Thomassin; R Renard-Penna; S Tavolaro; F H Cornelis
Journal:  Diagn Interv Imaging       Date:  2018-03-30       Impact factor: 4.026

9.  Radiomics of computed tomography and magnetic resonance imaging in renal cell carcinoma-a systematic review and meta-analysis.

Authors:  Stephan Ursprung; Lucian Beer; Annemarie Bruining; Ramona Woitek; Grant D Stewart; Ferdia A Gallagher; Evis Sala
Journal:  Eur Radiol       Date:  2020-02-14       Impact factor: 5.315

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  1 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

  1 in total

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