Evidence map›Paper›PMID 35216855›Full record

ReviewEuropean urology2022

Novel Imaging Methods for Renal Mass Characterization: A Collaborative Review.

Eduard Roussel, Umberto Capitanio, Alexander Kutikov, Egbert Oosterwijk, Ivan Pedrosa, Steven P Rowe, Michael A Gorin

Open access · greenAbstract readReview
In one paragraph

Review in European urology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
76citing papers in PubMed, 4 pooled it
18.2field-weighted citation impact, top 1% of its field
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

76 citing papers in PubMed, 4 syntheses or guidelines pooled it, 127 citations in OpenAlex.

  1. Pooled it
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  13. Pharmaceutics · 2026
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  20. Evaluation of [EJNMMI research · 2025
    Article

16 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 2 countries.

Eduard RousselDepartment of Urology, University Hospitals Leuven, Leuven, Belgium.
Umberto CapitanioDepartment of Urology, University Vita-Salute, San Raffaele Scientific Institute, Milan, Italy; Division of Experimental Oncology, URI, Urological Research Institute, IRCCS San Raffaele Scientific Institute, Milan, Italy.
Alexander KutikovDivision of Urology, Department of Surgery, Fox Chase Cancer Center, Temple University Health System, Philadelphia, PA, USA.
Egbert OosterwijkDepartment of Urology, Radboud University Medical Center, Radboud Institute for Molecular Life Sciences (RIMLS), Nijmegen, The Netherlands.
Ivan PedrosaDepartment of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA; Advanced Imaging Research Center. University of Texas Southwestern Medical Center, Dallas, TX, USA; Department of Urology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Steven P RoweThe Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; The James Buchanan Brady Urological Institute and Department of Urology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Michael A GorinUrology Associates and UPMC Western Maryland, Cumberland, MD, USA; Department of Urology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA. Electronic address: mgorin@urologyassociatesmd.org.
Fox Chase Cancer Center · USKU Leuven · BE

Funding

Translational Research Central ServicesP30CA006973 · NCI · JOHNS HOPKINS UNIVERSITY · PI ALAN KEITH MEEKER · 1985 to 2026
$208.6M
NON-INVASIVE PHYSIOLOGIC PREDICTORS OF AGGRESSIVENESS IN RENAL CELL CARCINOMAR01CA154475 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI PEDROSA, IVAN · 2011 to 2024
$4.3M
NCI NIH HHS P30 CA006973NCI NIH HHS R01 CA154475
6 · The paper itself

Abstract

contextThe incidental detection of localized renal masses has been rising steadily, but a significant proportion of these tumors are benign or indolent and, in most cases, do not require treatment. At the present time, a majority of patients with an incidentally detected renal tumor undergo treatment for the presumption of cancer, leading to a significant number of unnecessary surgical interventions that can result in complications including loss of renal function. Thus, there exists a clinical need for improved tools to aid in the pretreatment characterization of renal tumors to inform patient management.

objectiveTo systematically review the evidence on noninvasive, imaging-based tools for solid renal mass characterization. EVIDENCE ACQUISITION: The MEDLINE database was systematically searched for relevant studies on novel imaging techniques and interpretative tools for the characterization of solid renal masses, published in the past 10 yr. EVIDENCE SYNTHESIS: Over the past decade, several novel imaging tools have offered promise for the improved characterization of indeterminate renal masses. Technologies of particular note include multiparametric magnetic resonance imaging of the kidney, molecular imaging with targeted radiopharmaceutical agents, and use of radiomics as well as artificial intelligence to enhance the interpretation of imaging studies. Among these,

conclusionsA number of novel imaging tools stand poised to aid in the noninvasive characterization of indeterminate renal masses. In the future, these tools may aid in patient management by providing a comprehensive virtual biopsy, complete with information on tumor histology, underlying molecular abnormalities, and ultimately disease prognosis. PATIENT SUMMARY: Not all renal tumors require treatment, as a significant proportion are either benign or have limited metastatic potential. Several innovative imaging tools have shown promise for their ability to improve the characterization of renal tumors and provide guidance in terms of patient management.

Indexed as

Carcinoma, Renal CellKidney NeoplasmsArtificial IntelligenceFemaleHumansMagnetic Resonance ImagingMaleRadiopharmaceuticalsTechnetium Tc 99m SestamibiRadiopharmaceuticalsTechnetium Tc 99m Sestamibi(99m)Tc-sestamibiArtificial intelligenceGirentuximabKidney cancerMachine learningMultiparametric magnetic resonance imagingPETRadiomicsRenal cell carcinomaSPECTVirtual biopsy

Identifiers

PMID35216855
PMCPMC9844544
OpenAlexW4213322284

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.