Evidence map›Paper›PMID 40109982›Full record

ReviewBJUI compass2025

Renal parenchymal volume analysis: Clinical and research applications.

Carlos Munoz-Lopez, Kieran Lewis, Nityam Rathi, Eran Maina, Akira Kazama, Anne Wong, Angelica Bartholomew, Worapat Attawettayanon, Yunlin Ye, Zhiling Zhang and 6 more

Abstract readReview
In one paragraph

Review in BJUI compass, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Carlos Munoz-LopezGlickman Urological and Kidney Institute, Cleveland Clinic Cleveland OH USA.
Kieran LewisGlickman Urological and Kidney Institute, Cleveland Clinic Cleveland OH USA.
Nityam RathiGlickman Urological and Kidney Institute, Cleveland Clinic Cleveland OH USA.ORCID https://orcid.org/0000-0002-6718-8170
Eran MainaGlickman Urological and Kidney Institute, Cleveland Clinic Cleveland OH USA.
Akira KazamaGlickman Urological and Kidney Institute, Cleveland Clinic Cleveland OH USA.ORCID https://orcid.org/0000-0002-8354-6388
Anne WongGlickman Urological and Kidney Institute, Cleveland Clinic Cleveland OH USA.
Angelica BartholomewGlickman Urological and Kidney Institute, Cleveland Clinic Cleveland OH USA.
Worapat AttawettayanonDivision of Urology, Department of Surgery, Faculty of Medicine, Songklanagarind Hospital Prince of Songkla University Songkhla Thailand.
Yunlin YeDepartment of Urology, Sun Yat-sen University Cancer Center Guangzhou P. R. China.ORCID https://orcid.org/0000-0001-5424-7066
Zhiling ZhangDepartment of Urology, Sun Yat-sen University Cancer Center Guangzhou P. R. China.ORCID https://orcid.org/0000-0003-1821-4587
Wen DongDepartment of Urology, Sun Yat-sen University Cancer Center Guangzhou P. R. China.
Rebecca A CampbellGlickman Urological and Kidney Institute, Cleveland Clinic Cleveland OH USA.
Nicholas HellerGlickman Urological and Kidney Institute, Cleveland Clinic Cleveland OH USA.ORCID https://orcid.org/0000-0001-8516-8707
Erick RemerGlickman Urological and Kidney Institute, Cleveland Clinic Cleveland OH USA.
Christopher WeightGlickman Urological and Kidney Institute, Cleveland Clinic Cleveland OH USA.
Steven C CampbellGlickman Urological and Kidney Institute, Cleveland Clinic Cleveland OH USA.ORCID https://orcid.org/0000-0002-9110-0343

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objectives: In most patients, the renal parenchymal volumes in each kidney directly correlate with function and can be used as a proxy to determine split renal function (SRF). This simple principle forms the basis for parenchymal volume analysis (PVA) with semiautomated software, which can be leveraged to predict SRF and new-baseline glomerular filtration rate (NBGFR) following nephrectomy. PVA was originally used to evaluate renal transplantation donors and has replaced nuclear renal scans (NRS) in this domain. PVA has subsequently been explored for the management of patients with kidney cancer for whom difficult decisions about radical versus partial nephrectomy can be influenced by accurate prediction of NBGFR. Our objective is to present a comprehensive review of the applications of PVA in urology including their clinical and research implications. Methods: Key articles utilizing renal PVA to improve clinical care and facilitate urologic research were reviewed with special emphasis on take-home points of clinical relevance and their contributions to progress in the field. Results: There have been considerable advances in renal PVA over the past 15 years, which is now established as a reference standard for the prediction of functional outcomes after renal surgery. PVA provides improved accuracy when compared to NRS-based estimates or non-SRF-based algorithms. PVA can be performed in minutes using routine preoperative cross-sectional imaging and can be readily applied at the point of care. Additionally, PVA has important research applications, enabling the precise study of the determinants of functional recovery after partial nephrectomy, which can affect surgical approaches to this procedure. Conclusions: Despite the wide availability of PVA, primarily for use in renal transplantation, it has not been widely implemented for other urologic purposes at most centres. Our hope is that this narrative review will increase PVA utilization in urology and facilitate further progress in the field.

Indexed as

functional recoverykidney cancernew baseline glomerular filtration rateparenchymal volume analysispartial nephrectomyradical nephrectomysplit renal function

Identifiers

PMID40109982
PMCPMC11922601

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.