Evidence map›Paper›PMID 34666162›Full record

ArticleMagnetic resonance imaging2022

Identification of prostate cancer using multiparametric MR imaging characteristics of prostate tissues referenced to whole mount histopathology.

Matthew Gibbons, Olga Starobinets, Jeffry P Simko, John Kurhanewicz, Peter R Carroll, Susan M Noworolski

Open access · greenAbstract read

In one paragraph

Article in Magnetic resonance imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it

0cells of the map it votes in

5citing papers in PubMed

1.6field-weighted citation impact, top 15% 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

5 citing papers in PubMed, 12 citations in OpenAlex.

Three-dimensional reconstruction of gigapixel whole-mount histopathology specimens with RAPID.Scientific reports · 2026
Article
The impact of benign tissue within cancerous regions in the prostate: Characterizing sparse and dense prostate cancers on whole-mount histopathology and on multiparametric MRI.Magnetic resonance imaging · 2024
Article
Full resolution reconstruction of whole-mount sections from digitized individual tissue fragments.Scientific reports · 2024
Article
Prostate cancer lesion detection, volume quantification and high-grade cancer differentiation using cancer risk maps derived from multiparametric MRI with histopathology as the reference standard.Magnetic resonance imaging · 2023
Article
Dictionary learning compressed sensing reconstruction: pilot validation of accelerated echo planar J-resolved spectroscopic imaging in prostate cancer.Magma (New York, N.Y.) · 2022
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 3 institutions in 1 country.

Matthew GibbonsDeparment of Radiology and Biomedical Imaging, University of California, 185 Berry Street, San Francisco, CA, USA. Electronic address: matthew.gibbons@ucsf.edu.

Olga StarobinetsDeparment of Radiology and Biomedical Imaging, University of California, 185 Berry Street, San Francisco, CA, USA.

Jeffry P SimkoDepartment of Urology, University of California, 550 16th Street, San Francisco, CA, USA; Department of Pathology, University of California, 1825 4th Street, San Francisco, CA, USA. Electronic address: jeff.simko@ucsf.edu.

John KurhanewiczDeparment of Radiology and Biomedical Imaging, University of California, 185 Berry Street, San Francisco, CA, USA; Department of Urology, University of California, 550 16th Street, San Francisco, CA, USA. Electronic address: john.kurnanewicz@ucsf.edu.

Peter R CarrollDepartment of Urology, University of California, 550 16th Street, San Francisco, CA, USA. Electronic address: peter.carroll@ucsf.edu.

Susan M NoworolskiDeparment of Radiology and Biomedical Imaging, University of California, 185 Berry Street, San Francisco, CA, USA. Electronic address: susan.noworolski@ucsf.edu.

Berry (United States) · USUniversity of California, San Francisco · USUniversity of California System · US

Funding

DCE MRI to Improve Prostate Cancer Identification and CharacterizationR01CA148708 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI NOWOROLSKI, SUSAN M · 2010 to 2014

$1.3M

NCI NIH HHS R01 CA148708

6 · The paper itself

Abstract

In this study, the objective was to characterize the MR signatures of the various benign prostate tissues and to differentiate them from cancer. Data was from seventy prostate cancer patients who underwent multiparametric MRI (mpMRI) and subsequent prostatectomy. The scans included T2-weighted imaging (T2W), diffusion weighted imaging, dynamic contrast-enhanced MRI (DCE MRI), and MR spectroscopic imaging. Histopathology tissue information was translated to MRI images. The mpMRI parameters were characterized separately per zone and by tissue type. The tissues were ordered according to trends in tissue parameter means. The peripheral zone tissue order was cystic atrophy, high grade prostatic intraepithelial neoplasia (HGPIN), normal, atrophy, inflammation, and cancer. Decreasing values for tissue order were exhibited by ADC (1.8 10

Indexed as

ProstateProstatic NeoplasmsContrast MediaHumansMagnetic Resonance ImagingMaleProstatectomyRetrospective StudiesContrast MediaDiffusion-weighted imagingDynamic contrast-enhanced imagingHistopathologyMagnetic resonance spectroscopy imagingMultiparametric MRIProstate cancer

Identifiers

PMID34666162

DOI10.1016/j.mri.2021.10.008

PMCPMC9931199

OpenAlexW3205171814

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.