Evidence map›Paper›PMID 41002286›Full record

ArticleRadiology. Imaging cancer2025

Multiparametric Dynamic Contrast Imaging for Voxelwise Quantitative Assessment of Brain Tumors.

Yang Chen, Jiayu Xiao, Steven Cen, Zhehao Hu, Junzhou Chen, Mark S Shiroishi, Frances E Chow, Jason C Ye, David D Tran, Kyle Hurth and 6 more

Abstract read
In one paragraph

Article in Radiology. Imaging cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors.

Yang ChenDepartment of Radiology, Keck School of Medicine, University of Southern California, 2250 Alcazar St, CSC Rm 104, Los Angeles, CA 90033.ORCID 0009-0001-7995-4119
Jiayu XiaoDepartment of Radiology, Keck School of Medicine, University of Southern California, 2250 Alcazar St, CSC Rm 104, Los Angeles, CA 90033.ORCID 0000-0001-7478-6534
Steven CenDepartment of Radiology, Keck School of Medicine, University of Southern California, 2250 Alcazar St, CSC Rm 104, Los Angeles, CA 90033.
Zhehao HuDepartment of Radiology, Keck School of Medicine, University of Southern California, 2250 Alcazar St, CSC Rm 104, Los Angeles, CA 90033.
Junzhou ChenDepartment of Radiology, Keck School of Medicine, University of Southern California, 2250 Alcazar St, CSC Rm 104, Los Angeles, CA 90033.
Mark S ShiroishiDepartment of Radiology, Los Angeles General Medical Center, Los Angeles, Calif.
Frances E ChowDepartment of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, Calif.
Jason C YeDepartment of Radiation Oncology, Keck School of Medicine, University of Southern California, Los Angeles, Calif.
David D TranDepartment of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, Calif.ORCID 0000-0002-2380-8921
Kyle HurthDepartment of Clinical Pathology, Keck School of Medicine, University of Southern California, Los Angeles, Calif.
Gabriel ZadaDepartment of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, Calif.ORCID 0000-0001-5821-902X
Hsu-Lei LeeBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, Calif.ORCID 0000-0001-5509-5199
Anthony G ChristodoulouDepartment of Radiological Sciences, University of California, Los Angeles, Los Angeles, Calif.ORCID 0000-0002-9334-8684
Debiao LiBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, Calif.ORCID 0000-0001-8560-8231
Eric ChangDepartment of Radiation Oncology, Keck School of Medicine, University of Southern California, Los Angeles, Calif.
Zhaoyang FanDepartment of Radiology, Keck School of Medicine, University of Southern California, 2250 Alcazar St, CSC Rm 104, Los Angeles, CA 90033.ORCID 0000-0002-2693-0260

Funding

Expanding on a new paradigm for MRI in pediatric congenital heart diseaseR01HL127153 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI CHRISTODOULOU, ANTHONY G, FINN, JOHN PAUL · 2015 to 2024
$6.1M
Motion-Resolved, Comprehensive Quantitative Tissue Characterization Using MR MultitaskingR01EB028146 · NIBIB · CEDARS-SINAI MEDICAL CENTER · PI CHRISTODOULOU, ANTHONY G, LI, DEBIAO · 2019 to 2022
$2.5M
SSFP Cardiovascular MR Imaging on 3.0T Using Unified-Coil Local ShimmingR01HL156818 · NHLBI · WEILL MEDICAL COLL OF CORNELL UNIV · PI SPINCEMAILLE, PASCAL, YANG, HSIN-JUNG · 2021 to 2024
$2.5M
Fully Quantitative Low-Dose, Motion-Resolved Dynamic Contrast-Enhanced MRI in Pancreatic AdenocarcinomaR01EB032801 · NIBIB · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Anthony G Christodoulou, Debiao Li · 2022 to 2026
$2.1M
NHLBI NIH HHS R01 HL127153NHLBI NIH HHS R01 HL156818NIBIB NIH HHS R01 EB028146NIBIB NIH HHS R01 EB032801
6 · The paper itself

Abstract

Purpose To develop a multiparametric dynamic contrast imaging (mpDYCI) technique that enables simultaneous quantification of brain tissue perfusion, microvasculature permeability, transmembrane water efflux, and susceptibility and can be integrated into the routine brain tumor imaging protocol for voxelwise multifaceted quantitative brain tumor assessment. Materials and Methods In this prospective study conducted from March 2023 to April 2024, the mpDYCI technique was evaluated. The mpDYCI technique builds on an MR Multitasking-based dynamic T1 and T2* mapping method and incorporates several technical optimizations in pulse sequence, image reconstruction, T1/T2* quantification, and quantitative metric estimation to achieve robust whole-brain multiparametric quantification. The intersession repeatability and accuracy of mpDYCI metrics were assessed, using intraclass correlation coefficient (ICC), through digital phantom and in vivo experiments involving healthy individuals and individuals with brain tumors. The feasibility of integrating mpDYCI into the routine brain imaging protocol and its clinical utilities based on complementary information from intrinsically coregistered multiple quantitative metrics were also explored. Results In vivo experiments were performed in six healthy participants (mean age, 33 years; range, 27-48 years; three female) and 55 participants with brain tumors (mean age, 56 years; range, 24-81 years; 36 female). Quantitative metrics derived from mpDYCI demonstrated good to excellent repeatability (ICC ≥ 0.80) and excellent agreement with reference standards (range, 6.86%-15.21% percentage error or ICC ≥ 0.93). Histogram analysis, voxel clustering, and histologic validation confirmed the capability of mpDYCI to capture the intratumoral heterogeneity. Low voxelwise correlations between each pair of mpDYCI metrics (correlation coefficient ≤ 0.33 except for one pair) suggested that each metric provides complementary information. Furthermore, mpDYCI exhibited the potential to help differentiate treatment-related effects from true tumor progression in brain metastases. Conclusion With a single 7.5-minute scan and single-dose contrast media injection, mpDYCI can simultaneously quantify perfusion, permeability, water efflux, and susceptibility, thereby enabling comprehensive voxelwise characterization of brain tumors.

Indexed as

Brain NeoplasmsContrast MediaMagnetic Resonance ImagingMultiparametric Magnetic Resonance ImagingAdultBrainFemaleHumansMaleMiddle AgedPhantoms, ImagingProspective StudiesContrast MediaBrain/Brain StemBrain Tumor HeterogeneityCNSDynamic Contrast-enhanced MRIDynamic Susceptibility Contrast MRIMR–Dynamic Contrast EnhancedMR ImagingMR PerfusionMultiparametric MR ImagingQuantitative Susceptibility MappingReconstruction AlgorithmsTumor Immune Microenvironment

Identifiers

PMID41002286
PMCPMC12492422

What OpenQuestion holds

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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.