Evidence map›Paper›PMID 39389776›Full record

ArticleAJNR. American journal of neuroradiology2025

Multisite Benchmark Study for Standardized Relative CBV in Untreated Brain Metastases Using the DSC-MRI Consensus Acquisition Protocol.

Sarah Kohn Loizzo, Melissa A Prah, Min J Kong, Daniel Phung, Javier C Urcuyo, Jason Ye, Frank J Attenello, Jesse Mendoza, Yuxiang Zhou, Mark S Shiroishi and 2 more

Abstract readMulticenter Study
In one paragraph

Article in AJNR. American journal of neuroradiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Sarah Kohn LoizzoFrom the Department of Radiation Oncology (S.K.L.), Medical College of Wisconsin, Milwaukee, Wisconsin.
Melissa A PrahDepartment of Biophysics (M.A.P., K.M.S.), Medical College of Wisconsin, Milwaukee, Wisconsin.ORCID 0000-0001-9775-9926
Min J KongDepartment of Radiology (M.J.K., Y.Z., L.S.H.), Mayo Clinic Arizona, Phoenix, Arizona.ORCID 0000-0003-0563-5681
Daniel PhungDepartment of Radiology (D.P., J.M., M.S.S.), Keck School of Medicine of the University of Southern California, Los Angeles, California.ORCID 0000-0001-6597-2431
Javier C UrcuyoMathematical Neuro-Oncology Lab (J.C.U.), Mayo Clinic Arizona, Scottsdale, Arizona.
Jason YeDepartment of Radiation Oncology (J.Y.), Keck School of Medicine of USC, Los Angeles, California.
Frank J AttenelloDepartment of Neurological Surgery (F.J.A.), Keck School of Medicine of USC, Los Angeles, California.
Jesse MendozaDepartment of Radiology (D.P., J.M., M.S.S.), Keck School of Medicine of the University of Southern California, Los Angeles, California.
Yuxiang ZhouDepartment of Radiology (M.J.K., Y.Z., L.S.H.), Mayo Clinic Arizona, Phoenix, Arizona.ORCID 0000-0002-3462-2305
Mark S ShiroishiDepartment of Radiology (D.P., J.M., M.S.S.), Keck School of Medicine of the University of Southern California, Los Angeles, California.ORCID 0000-0002-1422-0288
Leland S HuDepartment of Radiology (M.J.K., Y.Z., L.S.H.), Mayo Clinic Arizona, Phoenix, Arizona.ORCID 0000-0001-9282-7619
Kathleen M SchmaindaDepartment of Biophysics (M.A.P., K.M.S.), Medical College of Wisconsin, Milwaukee, Wisconsin kathleen@mcw.edu.ORCID 0000-0001-6402-2602

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
Langworthy Diversity Supplement: Image-based models of tumor-immune dynamics in glioblastomaU01CA250481 · NCI · MAYO CLINIC ARIZONA · PI CANOLL, PETER, HU, LELAND · 2021 to 2025
$3.8M
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 CA264992NCI NIH HHS U01 CA176110NCI NIH HHS U01 CA250481
6 · The paper itself

Abstract

background and purposeA national consensus recommendation for the collection of DSC-MRI perfusion data, used to create maps of relative CBV (rCBV), has been recently established for primary and metastatic brain tumors. The goal was to reduce intersite variability and improve ease of comparison across time and sites, fostering widespread use of this informative measure. To translate this goal into practice, the prospective collection of consensus DSC-MRI data and characterization of derived rCBV maps in brain metastases is needed. The purpose of this multisite study was to determine rCBV in untreated brain metastases in comparison to glioblastoma (GBM) and normal-appearing brain by using the national consensus protocol. MATERIALS AND

methodsSubjects from 3 sites with untreated enhancing brain metastases underwent DSC-MRI according to a recommended option that uses a midrange flip angle, GRE-EPI acquisition, and the administration of both a preload and second DSC-MRI dose of 0.1 mmol/kg gadolinium-based contrast agent. Quantitative maps of standardized relative CBV (srCBV) were generated and enhancing lesion ROIs determined from postcontrast T1-weighted images alone or calibrated difference maps, termed Δ T1 (dT1) maps. Mean srCBV for metastases were compared with normal-appearing white matter (NAWM) and GBM from a previous study. Comparisons were performed by using either the Wilcoxon signed-rank test for paired comparisons or the Mann-Whitney

resultsForty-nine patients with a primary histology of lung (

conclusionsUsing the consensus DSC-MRI protocol, mean srCBV values were determined for treatment-naïve brain metastases in comparison to normal-appearing white matter and GBM thus setting the benchmark for all subsequent studies adherent to the national consensus recommendation.

Indexed as

Brain NeoplasmsCerebrovascular CirculationMagnetic Resonance AngiographyMagnetic Resonance ImagingAdultAgedBenchmarkingFemaleHumansMaleMiddle AgedReproducibility of ResultsSensitivity and Specificity

Identifiers

PMID39389776
PMCPMC11979803

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