Evidence map›Paper›PMID 22901591›Full record

ArticleThe Journal of urology2012

Correlation of magnetic resonance imaging tumor volume with histopathology.

Baris Turkbey, Haresh Mani, Omer Aras, Ardeshir R Rastinehad, Vijay Shah, Marcelino Bernardo, Thomas Pohida, Dagane Daar, Compton Benjamin, Yolanda L McKinney and 5 more

Abstract readComparative Study
In one paragraph

Article in The Journal of urology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 84 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
84citing papers in PubMed, 1 pooled it
–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

84 citing papers in PubMed, 1 synthesis or guideline pooled it.

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

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Baris TurkbeyMolecular Imaging Program, National Cancer Institute, Bethesda, Maryland.
Haresh ManiLaboratory of Pathology, National Cancer Institute, Bethesda, Maryland.
Omer ArasMolecular Imaging Program, National Cancer Institute, Bethesda, Maryland.
Ardeshir R RastinehadUrologic Oncology Branch, National Cancer Institute, Bethesda, Maryland.
Vijay ShahVirtualScopics, Rochester, New York.
Marcelino BernardoMolecular Imaging Program, National Cancer Institute, Bethesda, Maryland; Imaging Physics, SAIC Frederick, Inc., NCI-Frederick, Frederick, Maryland.
Thomas PohidaDivision of Computational Bioscience, Center for Information Technology and Center for Interventional Oncology, NCI and Radiology, Bethesda, Maryland.
Dagane DaarMolecular Imaging Program, National Cancer Institute, Bethesda, Maryland.
Compton BenjaminUrologic Oncology Branch, National Cancer Institute, Bethesda, Maryland.
Yolanda L McKinneyMolecular Imaging Program, National Cancer Institute, Bethesda, Maryland.
W Marston LinehanUrologic Oncology Branch, National Cancer Institute, Bethesda, Maryland.
Bradford J WoodImaging Sciences, Clinical Center, National Institutes of Health, Bethesda, Maryland.
Maria J MerinoLaboratory of Pathology, National Cancer Institute, Bethesda, Maryland.
Peter L ChoykeMolecular Imaging Program, National Cancer Institute, Bethesda, Maryland.
Peter A PintoUrologic Oncology Branch, National Cancer Institute, Bethesda, Maryland; Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, Maryland. Electronic address: pintop@mail.nih.gov.

Funding

Prostate Cancer ImagingZIABC010655 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI CHOYKE, PETER L · 2009 to 2025
$49.2M
Center for Interventional OncologyZIDBC011242 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI WOOD, BRADFORD J · 2009 to 2025
$18.7M
Clinical Nursing and Data Management CoreZIDBC011089 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI LINEHAN, WILLIAM MARSTON · 2009 to 2025
$17.4M
Signal Processing And Instrumentation SectionZIACT000261 · CIT · CENTER FOR INFORMATION TECHNOLOGY · PI POHIDA, THOMAS J · 2009 to 2021
$16.7M
Prostate SectionZIABC011081 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI PINTO, PETER · 2009 to 2025
$15.2M
Clinical Fellowship Training ProgramZIEBC011023 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI PINTO, PETER · 2009 to 2025
$10.3M
Translational Surgical PathologyZIESC000853 · NCI · DIVISION OF CLINICAL SCIENCES - NCI · PI MERINO, MARIA · 2009 to 2025
$4.3M
miRNA profiling of prostate cancer in young and older male patientsZIABC011406 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI MERINO, MARIA · 2011 to 2023
$1.8M
Interventional OncologyZIACL040015 · CLC · CLINICAL CENTER · PI WOOD, BRADFORD · 2009 to 2025
$0k
Navigation Tools for Image Guided Minimally invasive TherapiesZIACL040011 · CLC · CLINICAL CENTER · PI WOOD, BRADFORD · 2009 to 2025
$0k
Intramural NIH HHS Z99 CA999999
6 · The paper itself

Abstract

purposeThe biology of prostate cancer may be influenced by the index lesion. The definition of index lesion volume is important for appropriate decision making, especially for image guided focal treatment. We determined the accuracy of magnetic resonance imaging for determining index tumor volume compared with volumes derived from histopathology. MATERIALS AND

methodsWe evaluated 135 patients (mean age 59.3 years) with a mean prostate specific antigen of 6.74 ng/dl who underwent multiparametric 3T endorectal coil magnetic resonance imaging of the prostate and subsequent radical prostatectomy. Index tumor volume was determined prospectively and independently by magnetic resonance imaging and histopathology. The ellipsoid formula was applied to determine histopathology tumor volume, whereas manual tumor segmentation was used to determine magnetic resonance tumor volume. Histopathology tumor volume was correlated with age and prostate specific antigen whereas magnetic resonance tumor volume involved Pearson correlation and linear regression methods. In addition, the predictive power of magnetic resonance tumor volume, prostate specific antigen and age for estimating histopathology tumor volume (greater than 0.5 cm(3)) was assessed by ROC analysis. The same analysis was also conducted for the 1.15 shrinkage factor corrected histopathology data set.

resultsThere was a positive correlation between histopathology tumor volume and magnetic resonance tumor volume (Pearson coefficient 0.633, p <0.0001), but a weak correlation between prostate specific antigen and histopathology tumor volume (Pearson coefficient 0.237, p = 0.003). On linear regression analysis histopathology tumor volume and magnetic resonance tumor volume were correlated (r(2) = 0.401, p <0.00001). On ROC analysis AUC values for magnetic resonance tumor volume, prostate specific antigen and age in estimating tumors larger than 0.5 cm(3) at histopathology were 0.949 (p <0.0000001), 0.685 (p = 0.001) and 0.627 (p = 0.02), respectively. Similar results were found in the analysis with shrinkage factor corrected tumor volumes at histopathology.

conclusionsMagnetic resonance imaging can accurately estimate index tumor volume as determined by histology. Magnetic resonance imaging has better accuracy in predicting histopathology tumor volume in tumors larger than 0.5 cm(3) than prostate specific antigen and age. Index tumor volume as determined by magnetic resonance imaging may be helpful in planning treatment, specifically in identifying tumor margins for image guided focal therapy and possibly selecting better active surveillance candidates.

Indexed as

Magnetic Resonance ImagingTumor BurdenHumansMaleMiddle AgedProstatic NeoplasmsReproducibility of ResultsRetrospective Studies

Identifiers

PMID22901591
PMCPMC5462598

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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.