Evidence map›Paper›PMID 38345143›Full record

ArticleJournal of magnetic resonance imaging : JMRI2024

Understanding Spatial Correlation Between Multiparametric MRI Performance and Prostate Cancer.

Fatemeh Zabihollahy, Sohaib Naim, Pornphan Wibulpolprasert, Robert E Reiter, Steven S Raman, Kyunghyun Sung

Open access · greenAbstract read
In one paragraph

Article in Journal of magnetic resonance imaging : JMRI, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.7field-weighted citation impact, top 17% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
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

6 authors at 2 institutions in 2 countries.

Fatemeh ZabihollahyDepartment of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA.ORCID 0000-0003-3362-1009
Sohaib NaimDepartment of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA.
Pornphan WibulpolprasertDepartment of Diagnostic and Therapeutic Radiology, Faculty of Medicine, Ramathibodi Hospital, Bangkok, Thailand.
Robert E ReiterDepartment of Urology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA.
Steven S RamanDepartment of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA.
Kyunghyun SungDepartment of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA.ORCID 0000-0003-4175-5322
University of California, Los Angeles · USRamathibodi Hospital · TH

Funding

Integrating Quantitative MRI and Artificial Intelligence to Improve Prostate Cancer ClassificationR01CA248506 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SUNG, KYUNG HYUN, WU, HOLDEN H · 2020 to 2024
$3.0M
Racially-associated MRI analysis and modeling for predicting aggressive prostate cancerR01CA272702 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Harrison Kim, Kyung Hyun Sung · 2023 to 2026
$2.4M
Division of Cancer Prevention, National Cancer Institute R01-CA248506Division of Cancer Prevention, National Cancer Institute R01-CA272702Integrated Diagnostics Program of the Departments of Radiological Sciences and Pathology in the UCLA David Geffen School of MedicineNCI NIH HHS R01 CA248506NCI NIH HHS R01 CA272702
6 · The paper itself

Abstract

backgroundMultiparametric MRI (mpMRI) has shown a substantial impact on prostate cancer (PCa) diagnosis. However, the understanding of the spatial correlation between mpMRI performance and PCa location is still limited. PURPOSE: To investigate the association between mpMRI performance and tumor spatial location within the prostate using a prostate sector map, described by Prostate Imaging Reporting and Data System (PI-RADS) v2.1. STUDY TYPE: Retrospective. SUBJECTS: One thousand one hundred forty-three men who underwent mpMRI before radical prostatectomy between 2010 and 2022. FIELD STRENGTH/SEQUENCE: 3.0 T. T2-weighted turbo spin-echo, a single-shot spin-echo EPI sequence for diffusion-weighted imaging, and a gradient echo sequence for dynamic contrast-enhanced MRI sequences. ASSESSMENT: Integrated relative cancer prevalence (rCP), detection rate (DR), and positive predictive value (PPV) maps corresponding to the prostate sector map for PCa lesions were created. The relationship between tumor location and its detection/missing by radiologists on mpMRI compared to WMHP as a reference standard was investigated. STATISTICAL TESTS: A weighted chi-square test was performed to examine the statistical differences for rCP, DR, and PPV of the aggregated sectors within the zone, anterior/posterior, left/right prostate, and different levels of the prostate with a statistically significant level of 0.05.

resultsA total of 1665 PCa lesions were identified in 1143 patients, and from those 1060 lesions were clinically significant (cs)PCa tumors (any Gleason score [GS] ≥7). Our sector-based analysis utilizing weighted chi-square tests suggested that the left posterior part of PZ had a high likelihood of missing csPCa lesions at a DR of 67.0%. Aggregated sector analysis indicated that the anterior or apex locations in PZ had the significantly lowest csPCa detection at 67.3% and 71.5%, respectively. DATA

conclusionSpatial characteristics of the per-lesion-based mpMRI performance for diagnosis of PCa were studied. Our results demonstrated that there is a spatial correlation between mpMRI performance and locations of PCa on the prostate. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Indexed as

Multiparametric Magnetic Resonance ImagingProstateProstatic NeoplasmsAgedContrast MediaDiffusion Magnetic Resonance ImagingHumansMagnetic Resonance ImagingMaleMiddle AgedProstatectomyReproducibility of ResultsRetrospective StudiesContrast Mediamultiparametric MRIPI‐RADSprostate cancerprostate sector mapwhole‐mount histopathology

Identifiers

PMID38345143
PMCPMC11317542
OpenAlexW4391746979

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.