Evidence map›Paper›PMID 29167070›Full record

ArticleAcademic radiology2018

Performance of Ultrafast DCE-MRI for Diagnosis of Prostate Cancer.

Aritrick Chatterjee, Dianning He, Xiaobing Fan, Shiyang Wang, Teodora Szasz, Ambereen Yousuf, Federico Pineda, Tatjana Antic, Melvy Mathew, Gregory S Karczmar and 1 more

Abstract read
In one paragraph

Article in Academic radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
2.8field-weighted citation impact, top 10% 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

21 citing papers in PubMed, 36 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Vaccines in Breast Cancer: Challenges and Breakthroughs.Diagnostics (Basel, Switzerland) · 2023
    Review
  7. Value for combination of TZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2023
    Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. New prostate MRI techniques and sequences.Abdominal radiology (New York) · 2020
    Review
  16. Review
  17. Article
  18. Article
  19. Article
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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

11 authors at 1 institution in 2 countries.

Aritrick ChatterjeeDepartment of Radiology, The University of Chicago, 5841 S Maryland Ave, MC 2026, Chicago, IL 60637.
Dianning HeDepartment of Radiology, The University of Chicago, 5841 S Maryland Ave, MC 2026, Chicago, IL 60637; Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, China.
Xiaobing FanDepartment of Radiology, The University of Chicago, 5841 S Maryland Ave, MC 2026, Chicago, IL 60637.
Shiyang WangDepartment of Radiology, The University of Chicago, 5841 S Maryland Ave, MC 2026, Chicago, IL 60637.
Teodora SzaszResearch Computing Center, The University of Chicago, Chicago, Illinois.
Ambereen YousufDepartment of Radiology, The University of Chicago, 5841 S Maryland Ave, MC 2026, Chicago, IL 60637.
Federico PinedaDepartment of Radiology, The University of Chicago, 5841 S Maryland Ave, MC 2026, Chicago, IL 60637.
Tatjana AnticDepartment of Pathology, The University of Chicago, Chicago, Illinois.
Melvy MathewDepartment of Radiology, The University of Chicago, 5841 S Maryland Ave, MC 2026, Chicago, IL 60637.
Gregory S KarczmarDepartment of Radiology, The University of Chicago, 5841 S Maryland Ave, MC 2026, Chicago, IL 60637.
Aytekin OtoDepartment of Radiology, The University of Chicago, 5841 S Maryland Ave, MC 2026, Chicago, IL 60637. Electronic address: aoto@radiology.bsd.uchicago.edu.
University of Chicago · US

Funding

VIRAL ONCOLOGY CORE FACILITYP30CA014599 · NCI · UNIVERSITY OF CHICAGO · PI MARK W. LINGEN · 1985 to 2026
$122.1M
Quantitative MRI for Predicting Response of Breast Cancer to Neoadjuvant TherapyU01CA142565 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI KARCZMAR, GREGORY S., NANDA, RITA · 2010 to 2019
$4.5M
Breast Cancer Screening with Quantitative Ultra-Fast DCEMRI and Clinical Risk AssessmentR01CA218700 · NCI · UNIVERSITY OF CHICAGO · PI KARCZMAR, GREGORY S. · 2017 to 2021
$3.0M
Quantitative DCEMRI of Prostate Cancer Correlation with Gold StandardsR01CA172801 · NCI · UNIVERSITY OF CHICAGO · PI KARCZMAR, GREGORY S., OTO, AYTEKIN · 2013 to 2017
$2.3M
3T MRI Scanner for multidisciplinary imaging and image-guided therapyS10OD018448 · OD · UNIVERSITY OF CHICAGO · PI KARCZMAR, GREGORY S. · 2014 to 2014
$2.0M
NCI NIH HHS P30 CA014599NCI NIH HHS R01 CA172801NCI NIH HHS R01 CA218700NCI NIH HHS U01 CA142565NIH HHS S10 OD018448
6 · The paper itself

Abstract

RATIONALE AND

objectivesThis study aimed to test high temporal resolution dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for different zones of the prostate and evaluate its performance in the diagnosis of prostate cancer (PCa). Determine whether the addition of ultrafast DCE-MRI improves the performance of multiparametric MRI. MATERIALS AND

methodsPatients (n = 20) with pathologically confirmed PCa underwent preoperative 3T MRI with T2-weighted, diffusion-weighted, and high temporal resolution (~2.2 seconds) DCE-MRI using gadoterate meglumine (Guerbet, Bloomington, IN) without an endorectal coil. DCE-MRI data were analyzed by fitting signal intensity with an empirical mathematical model to obtain parameters: percent signal enhancement, enhancement rate (α), washout rate (β), initial enhancement slope, and enhancement start time along with apparent diffusion coefficient (ADC) and T2 values. Regions of interests were placed on sites of prostatectomy verified malignancy (n = 46) and normal tissue (n = 71) from different zones.

resultsCancer (α = 6.45 ± 4.71 s

conclusionQuantitative parameters from empirical mathematical model fits to ultrafast DCE-MRI improve diagnosis of PCa. DCE-MRI with higher temporal resolution may capture clinically useful information for PCa diagnosis that would be missed by low temporal resolution DCE-MRI. This new information could improve the performance of multiparametric MRI in PCa detection.

Indexed as

Diffusion Magnetic Resonance ImagingAdultAgedContrast MediaHumansMaleMeglumineMiddle AgedOrganometallic CompoundsProstatectomyProstatic NeoplasmsROC CurveContrast Mediagadoterate meglumineMeglumineOrganometallic Compoundsempirical mathematical modelmpMRIProstate cancerultrafast DCE-MRI

Identifiers

PMID29167070
PMCPMC6535050
OpenAlexW2768532922

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.