Evidence map›Paper›PMID 29733695›Full record

ArticleAJR. American journal of roentgenology2018

Can Apparent Diffusion Coefficient Values Assist PI-RADS Version 2 DWI Scoring? A Correlation Study Using the PI-RADSv2 and International Society of Urological Pathology Systems.

Sonia Gaur, Stephanie Harmon, Lauren Rosenblum, Matthew D Greer, Sherif Mehralivand, Mehmet Coskun, Maria J Merino, Bradford J Wood, Joanna H Shih, Peter A Pinto and 2 more

Open access · greenAbstract read
In one paragraph

Article in AJR. American journal of roentgenology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.9field-weighted citation impact, top 11% 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

18 citing papers in PubMed, 38 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. PI-RADS: Where Next?Radiology · 2023
    Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. PI-RADSv2.1: Current status.Turkish journal of urology · 2021
    Review
  15. Article
  16. Article
  17. Article
  18. 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

12 authors at 2 institutions in 1 country.

Sonia Gaur1 Molecular Imaging Program, National Cancer Institute, National Institutes of Health, 10 Center Dr, Rm B3B85, Bethesda, MD 20814.
Stephanie Harmon2 Clinical Research Directorate, Clinical Monitoring Research Program, Leidos Biomedical Research, National Cancer Institute, Frederick, MD.
Lauren Rosenblum1 Molecular Imaging Program, National Cancer Institute, National Institutes of Health, 10 Center Dr, Rm B3B85, Bethesda, MD 20814.
Matthew D Greer1 Molecular Imaging Program, National Cancer Institute, National Institutes of Health, 10 Center Dr, Rm B3B85, Bethesda, MD 20814.
Sherif Mehralivand3 Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD.
Mehmet Coskun4 İzmir Katip Çelebi University, Atatürk Training and Research Hospital, Izmir, Turkey.
Maria J Merino1 Molecular Imaging Program, National Cancer Institute, National Institutes of Health, 10 Center Dr, Rm B3B85, Bethesda, MD 20814.
Bradford J Wood5 Center for Interventional Oncology, Clinical Center, National Institutes of Health, Bethesda, MD.
Joanna H Shih6 Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Rockville, MD.
Peter A Pinto3 Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD.
Peter L Choyke1 Molecular Imaging Program, National Cancer Institute, National Institutes of Health, 10 Center Dr, Rm B3B85, Bethesda, MD 20814.
Baris Turkbey1 Molecular Imaging Program, National Cancer Institute, National Institutes of Health, 10 Center Dr, Rm B3B85, Bethesda, MD 20814.
National Cancer Institute · USNational Institutes of Health Clinical Center · US

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
Prostate Cancer ImagingZ01BC010655 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI CHOYKE, PETER L · 2005 to 2008
$2.1M
Interventional OncologyZIACL040015 · CLC · CLINICAL CENTER · PI WOOD, BRADFORD · 2009 to 2025
$0k
CCR NIH HHS HHSN261200800001CIntramural NIH HHS Z01 BC010655NCI NIH HHS HHSN261200800001E
6 · The paper itself

Abstract

objectiveThe purposes of this study were to assess correlation of apparent diffusion coefficient (ADC) and normalized ADC (ratio of tumor to nontumor tissue) with the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) and updated International Society of Urological Pathology (ISUP) categories and to determine how to optimally use ADC metrics for objective assistance in categorizing lesions within PI-RADSv2 guidelines. MATERIALS AND

methodsIn this retrospective study, 100 patients (median age, 62 years; range, 44-75 years; prostate-specific antigen level, 7.18 ng/mL; range, 1.70-84.56 ng/mL) underwent 3-T multiparametric MRI of the prostate with an endorectal coil. Mean ADC was extracted from ROIs based on subsequent prostatectomy specimens. Histopathologic analysis revealed 172 lesions (113 peripheral, 59 transition zone). Two radiologists blinded to histopathologic outcome assigned PI-RADSv2 categories. Kendall tau was used to correlate ADC metrics with PI-RADSv2 and ISUP categories. ROC curves were used to assess the utility of ADC metrics in differentiating each reader's PI-RADSv2 DWI category 4 or 5 assessment in the whole prostate and by zone.

resultsADC metrics negatively correlated with ISUP category in the whole prostate (ADC, τ = -0.21, p = 0.0002; normalized ADC, τ = -0.21, p = 0.0001). Moderate negative correlation was found in expert PI-RADSv2 DWI categories (ADC, τ = -0.34; normalized ADC, τ = -0.31; each p < 0.0001) maintained across zones. In the whole prostate, AUCs of ADC and normalized ADC were 87% and 82% for predicting expert PI-RADSv2 DWI category 4 or 5. A derived optimal cutoff ADC less than 1061 and normalized ADC less than 0.65 achieved positive predictive values of 83% and 84% for correct classification of PI-RADSv2 DWI category 4 or 5 by an expert reader. Consistent relations and predictive values were found by an independent novice reader.

conclusionADC and normalized ADC inversely correlate with PI-RADSv2 and ISUP categories and can serve as quantitative metrics to assist with assigning PI-RADSv2 DWI category 4 or 5.

Indexed as

AdultAgedCorrelation of DataDiffusion Magnetic Resonance ImagingHumansMaleMiddle AgedNeoplasm GradingProstatectomyProstate-Specific AntigenProstatic NeoplasmsRetrospective StudiesProstate-Specific Antigenapparent diffusion coefficientInternational Society of Urological Pathologymultiparametric MRIPI-RADSprostate

Identifiers

PMID29733695
PMCPMC7984719
OpenAlexW2799394481

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.