Evidence map›Paper›PMID 41368710›Full record

ArticleJournal of magnetic resonance imaging : JMRI2026

Mapping Intracellular Volume Fraction With Susceptibility Source Decomposition as a Marker for Tissue Cellularity.

Giulia Debiasi, Oliver C Kiersnowski, Giovanni Librizzi, Luca Roccatagliata, Renzo Manara, Mauro Costagli, Alessandra Bertoldo, Chunlei Liu

Abstract read
In one paragraph

Article in Journal of magnetic resonance imaging : JMRI, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Giulia DebiasiDepartment of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA.ORCID https://orcid.org/0000-0001-8550-9356
Oliver C KiersnowskiIRCCS Ospedale Policlinico San Martino, Genova, Italy.
Giovanni LibrizziPadova Neuroscience Center, University of Padova, Padova, Italy.
Luca RoccatagliataIRCCS Ospedale Policlinico San Martino, Genova, Italy.
Renzo ManaraPadova Neuroscience Center, University of Padova, Padova, Italy.
Mauro CostagliIRCCS Ospedale Policlinico San Martino, Genova, Italy.
Alessandra BertoldoPadova Neuroscience Center, University of Padova, Padova, Italy.
Chunlei LiuDepartment of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA.

Funding

Robotically-actuated, low-noise, concurrent TMS-EEG-fMRI systemR01MH127104 · NIMH · UNIVERSITY OF CALIFORNIA BERKELEY · PI LIU, CHUNLEI, LUSTIG, MICHAEL · 2021 to 2024
$6.5M
Imaging brain iron and protein aggregation with MRI for assessing Alzheimer's disease pathology and progressionR01AG070826 · NIA · UNIVERSITY OF CALIFORNIA BERKELEY · PI GRINBERG, LEA TENENHOLZ, LIU, CHUNLEI · 2021 to 2025
$3.3M
NIH HHS R01AG070826NIH HHS R01MH127104Weill Neurohub
6 · The paper itself

Abstract

backgroundPathophysiological changes affect tissue cell composition and density. For example, neurodegenerative disorders and brain tumors are associated with cell loss and abnormal accumulation, respectively. In these scenarios, if monitored and tracked, tissue cellularity might be used to inform clinical diagnosis and management. PURPOSE: To propose and evaluate a new marker of tissue cellularity, called susceptibility-Derived Cellularity Index (χDCI), that would be readily available for clinical applications with fast acquisition and at high resolution. STUDY TYPE: Retrospective study. POPULATION/SUBJECTS: 24 healthy subjects (7/17 M/F, 70 ± 11 years) and 21 patients with IDH-wild type glioblastoma (16/5 M/F, 65 ± 8 years). FIELD STRENGTH/SEQUENCE: 3 T MRI sequences including 3D T1w pre- and post-contrast agent injection, 3D T2w, 3D FLAIR, 3D multi-echo gradient recalled echo, 2D diffusion weighted imaging. ASSESSMENT: χDCI was computed based on parameters estimated with DECOMPOSE-QSM. The Neurite Density Index (NDI) was estimated with the NODDI model. T1w images were used for region of interest (ROIs) segmentations with FreeSurfer (i.e., cortical gray matter, white matter, thalamus, caudate, putamen, pallidum, hippocampus and amygdala). For the patients with glioblastoma, regions of contrast enhancement, necrosis, and edema were also included in the analysis. STATISTICAL TESTS: Pearson's correlation analysis between mean χDCI and NDI values in the ROIs was carried out separately for the two cohorts of participants (significance level = 0.05, after correction for multiple comparisons).

resultsSignificant correlations were observed between χDCI and NDI in white matter (r = 0.56) and putamen (r = 0.69) for the healthy participants. Significant positive correlations were also found in white matter (r = 0.6), pallidum (r = 0.48), putamen (r = 0.79), thalamus (r = 0.64) and edema (r = 0.69) for the patient cohort. DATA

conclusionχDCI is proposed as a marker of tissue cellularity. The significant associations between χDCI and NDI in several regions investigated in the present study support the potential of χDCI as a proxy of intracellular volume fraction. LEVEL OF EVIDENCE: 3: TECHNICAL EFFICACY: Stage 1.

Indexed as

BrainBrain NeoplasmsGlioblastomaMagnetic Resonance ImagingAgedAged, 80 and overContrast MediaFemaleHumansImage Processing, Computer-AssistedImaging, Three-DimensionalMaleMiddle AgedRetrospective StudiesContrast Mediacellularitydiffusionglioblastomamagnetic susceptibility

Identifiers

PMID41368710
PMCPMC12963808

What OpenQuestion holds

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LicenceCC BY
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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.