Evidence map›Paper›PMID 32153416›Full record

ArticleFrontiers in physiology2020

Multiparametric Mapping Magnetic Resonance Imaging of Pancreatic Disease.

Lixia Wang, Srinivas Gaddam, Nan Wang, Yibin Xie, Zixin Deng, Zhengwei Zhou, Zhaoyang Fan, Tao Jiang, Anthony G Christodoulou, Fei Han and 5 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in physiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 14% 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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 40 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Review
  6. Article
  7. Whole pancreas water TMagma (New York, N.Y.) · 2025
    Article
  8. FastMagnetic resonance letters · 2024
    Article
  9. Article
  10. TBiophysical reports · 2024
    Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Review
  18. Review
  19. Article
  20. 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

15 authors at 4 institutions in 2 countries.

Lixia WangDepartment of Radiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Srinivas GaddamDivision of Digestive and Liver Diseases, Cedars-Sinai Medical Center, Los Angeles, CA, United States.
Nan WangDepartment of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States.
Yibin XieCedars-Sinai Biomedical Imaging Research Institute, Los Angeles, CA, United States.
Zixin DengCedars-Sinai Biomedical Imaging Research Institute, Los Angeles, CA, United States.
Zhengwei ZhouCedars-Sinai Biomedical Imaging Research Institute, Los Angeles, CA, United States.
Zhaoyang FanCedars-Sinai Biomedical Imaging Research Institute, Los Angeles, CA, United States.
Tao JiangDepartment of Radiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Anthony G ChristodoulouCedars-Sinai Biomedical Imaging Research Institute, Los Angeles, CA, United States.
Fei HanDepartment of Nuclear Science and Engineering, Siemens Healthineers, Princeton, NJ, United States.
Simon K LoDivision of Digestive and Liver Diseases, Cedars-Sinai Medical Center, Los Angeles, CA, United States.
Ashley M WachsmanCedars-Sinai Biomedical Imaging Research Institute, Los Angeles, CA, United States.
Andrew Eugene HendifarDepartment of Gastrointestinal Malignancies, Cedars-Sinai Medical Center, Los Angeles, CA, United States.
Stephen J PandolDivision of Digestive and Liver Diseases, Cedars-Sinai Medical Center, Los Angeles, CA, United States.
Debiao LiCedars-Sinai Biomedical Imaging Research Institute, Los Angeles, CA, United States.
Cedars-Sinai Medical Center · USCapital Medical University · CNSiemens (United States) · USUniversity of California, Los Angeles · US

Funding

Pathophysiology, Epidemiology, and Prevention of Pancreatogenic Diabetes - Administrative SupplementU01DK108314 · NIDDK · CEDARS-SINAI MEDICAL CENTER · PI Mark Goodarzi, Stephen J. Pandol · 2015 to 2026
$6.1M
NIDDK NIH HHS U01 DK108314
6 · The paper itself

Abstract

backgroundCurrent magnetic resonance imaging (MRI) of pancreatic disease is qualitative in nature. Quantitative imaging offers several advantages, including increased reproducibility and sensitivity to detect mild or diffuse disease. The role of multiparametric mapping MRI in characterizing various tissue types in pancreatic disease such as chronic pancreatitis (CP) and pancreatic ductal adenocarcinoma (PDAC) has rarely been evaluated. PURPOSE: To evaluate the feasibility of multiparametric mapping [T1, T2, and apparent diffusion coefficient (ADC)] in defining tissue characteristics that occur in CP and PDAC to improve disease diagnosis. MATERIALS AND

methodsPancreatic MRI was performed in 17 patients with PDAC undergoing therapy, 7 patients with CP, and 29 healthy volunteers with no pancreatic disease. T1 modified Look-Locker Inversion Recovery (T1 MOLLI), T2-prepared gradient-echo, and multi-slice single-shot echo-planar diffusion weighted imaging (SS-EPI DWI) sequences were used for data acquisition. Regions of interest (ROIs) of pancreas in PDAC, CP, and control subjects were outlined by an experienced radiologist. One-way analysis of variance (ANOVA) was used to compare the difference between groups and regions of the pancreas, and Tukey tests were used for multiple comparison testing within groups. Receiver operator characteristic (ROC) curves were analyzed, and the areas under the curves (AUCs) were calculated using single parameter and combined parameters, respectively.

resultsT1, T2, and ADC values of the entire pancreas among PDAC, CP, and control subjects; and between upstream and downstream portions of the pancreas in PDAC patients were all significantly different (

conclusionMultiparametric mapping MRI is feasible for the evaluation of the differences between PDAC, CP, and normal pancreas tissues. The combination of multiple parameters of T1, T2, and ADC provides a higher accuracy than any single parameter alone in tissue characterization of the pancreas.

Indexed as

ADCchronic pancreatitismagnetic resonance imagingpancreatic ductal adenocarcinomaparametric mappingT1T2

Identifiers

PMID32153416
PMCPMC7047169
OpenAlexW3006879470

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.