Evidence map›Paper›PMID 38445104›Full record

ArticleFrontiers in radiology2024

Practical guidance to identify and troubleshoot suboptimal DSC-MRI results.

Melissa A Prah, Kathleen M Schmainda

Abstract read
In one paragraph

Article in Frontiers in radiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
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

2 authors.

Melissa A PrahDepartment of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States.
Kathleen M SchmaindaDepartment of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States.

Funding

Quantitative (Perfusion and Diffusion) MRI Biomarkers to Measure Glioma ResponseU01CA176110 · NCI · MEDICAL COLLEGE OF WISCONSIN · PI SCHMAINDA, KATHLEEN MARIE · 2014 to 2023
$4.9M
New treatment monitoring biomarkers for brain tumors using multiparametric MRI with machine learningR01CA255123 · NCI · MEDICAL COLLEGE OF WISCONSIN · PI SCHMAINDA, KATHLEEN MARIE · 2021 to 2025
$2.6M
Establishing the clinical utility of a consensus DSC-MRI ProtocolR01CA264992 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Jerrold L Boxerman, Leland Hu · 2022 to 2026
$2.4M
NCI NIH HHS R01 CA255123NCI NIH HHS R01 CA264992NCI NIH HHS U01 CA176110
6 · The paper itself

Abstract

Relative cerebral blood volume (rCBV) derived from dynamic susceptibility contrast (DSC) perfusion MR imaging (pMRI) has been shown to be a robust marker of neuroradiological tumor burden. Recent consensus recommendations in pMRI acquisition strategies have provided a pathway for pMRI inclusion in diverse patient care centers, regardless of size or experience. However, even with proper implementation and execution of the DSC-MRI protocol, issues will arise that many centers may not easily recognize or be aware of. Furthermore, missed pMRI issues are not always apparent in the resulting rCBV images, potentiating inaccurate or missed radiological diagnoses. Therefore, we gathered from our database of DSC-MRI datasets, true-to-life examples showcasing the breakdowns in acquisition, postprocessing, and interpretation, along with appropriate mitigation strategies when possible. The pMRI issues addressed include those related to image acquisition and postprocessing with a focus on contrast agent administration, timing, and rate, signal-to-noise quality, and susceptibility artifact. The goal of this work is to provide guidance to minimize and recognize pMRI issues to ensure that only quality data is interpreted.

Indexed as

brain tumorCNR/contrast-to-noise ratioDSC-MRI/Dynamic susceptibility contrastguideissues/troubleshootingperfusionpostprocessingrCBV/rCBF

Identifiers

PMID38445104
PMCPMC10913595

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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.