Evidence map›Paper›PMID 41831008›Full record

ArticleNeuroradiology2026

Segmentation and morphometry of intracranial internal carotid artery calcification in relation to brain atrophy.

Xiao Xu, Nikhil N Chaudhari, Phoebe Imms, Nahian F Chowdhury, Fangyun C Liu, Jorge A Solis Galvan, Bavrina Bigjahan, Grant Schleifer, Maria Ashna, Blake Hannagan and 17 more

Abstract read
In one paragraph

Article in Neuroradiology, 2026. 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

27 authors.

Xiao XuAlfred E. Mann Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, United States.
Nikhil N ChaudhariAlfred E. Mann Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, United States.
Phoebe ImmsEthel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, United States.
Nahian F ChowdhuryEthel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, United States.
Fangyun C LiuEthel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, United States.
Jorge A Solis GalvanAlfred E. Mann Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, United States.
Bavrina BigjahanDepartment of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, United States.
Grant SchleiferDepartment of Physical Medicine and Rehabilitation, Harvard Medical School, Cambridge, United States.
Maria AshnaBrain and Creativity Institute, University of Southern California, Los Angeles, United States.
Blake HannaganEconomic Science Institute, Argyros School of Business and Economics, Chapman University, Orange, United States.
Giuseppe BarisanoDepartment of Neurosurgery, Stanford University, Stanford, United States.
Daniel K CummingsEconomic Science Institute, Argyros School of Business and Economics, Chapman University, Orange, United States.
Daniel Eid RodriguezInstitute of Biomedical Research, Universidad Mayor de San Simon, Cochabamba, Bolivia.
Paul L HooperEconomic Science Institute, Argyros School of Business and Economics, Chapman University, Orange, United States.
Edmond SeabrightSchool of Collective Intelligence, Université Mohammed VI Polytechnique, Marrakesh, Morocco.
Randall C ThompsonSaint Luke's Mid America Heart Institute, University of Missouri-Kansas City, Kansas City, United States.
Benjamin C TrumbleCenter for Evolution and Medicine, School of Human Evolution and Social Change, Arizona State University, Tempe, United States.
Michael D GurvenDepartment of Anthropology, University of California, Santa Barbara, Santa Barbara, United States.
Jonathan StieglitzDepartment of Social and Behavioral Sciences, Toulouse School of Economics, Toulouse, France.
Caleb E FinchEthel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, United States.
M Linda SutherlandMemorialCare Health Systems, Fountain Valley, United States.
James D SutherlandMemorialCare Health Systems, Fountain Valley, United States.
Helena C ChuiDepartment of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, United States.
Margaret GatzCenter for Economic and Social Research, Dana and David Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, United States.
Wendy J MackDepartment of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, United States.
Hillard S KaplanEconomic Science Institute, Argyros School of Business and Economics, Chapman University, Orange, United States.
Andrei IrimiaAlfred E. Mann Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, United States. irimia@usc.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIntracranial internal carotid artery calcification (iICAC) is a form of intracranial arteriosclerosis and is associated with an elevated risk of stroke and dementia. However, iICAC’s relationship with brain atrophy remains poorly understood. We aimed to automatically quantify iICAC morphometric characteristics and evaluate their associations with regional brain volumes (BVs).

methodsWe developed an automated approach to compute iICAC surface area and thickness from CT brain scans in a sample of physically active South American subsistence farmers (n = 1,232, age range: 40 years to 92 years, 48.1% female, 794 Tsimane and 438 Moseten). Linear regression models were used to assess associations between two iICAC features and regional BVs, adjusted for age, sex, population, and total intracranial volume.

resultsSignificant negative relationships were found between regional BVs and iICAC surface area, but not iICAC thickness. Frontal, parietal, temporal, and subcortical BVs exhibited significant negative associations with iICAC surface area (standardized β range: -0.146 to -0.066, p ≤ 0.013), while the occipital BV did not (standardized [Formula: see text] = -0.035, p = 0.249; [Formula: see text] = 0.007, p = 0.810). Subcortical BVs demonstrated the strongest negative associations with iICAC surface area (standardized [Formula: see text] = -0.146, p < 0.001; [Formula: see text] = -0.139, p < 0.001).

conclusioniICAC surface area—assumed to reflect arterial stiffness—shows a stronger relationship with regional BV loss than iICAC thickness—assumed to indicate arterial stenosis. The findings suggest that brain regions primarily supplied by the anterior circulation are more vulnerable to iICAC-related atrophy. Subcortical BVs showed the strongest negative associations with iICAC surface area, with region-specific analyses identifying significant effects in the putamen, thalamus, hippocampus, amygdala, pallidum, and ventral diencephalon, suggesting heightened vulnerability of deep gray-matter structures to iICAC-related atrophy.

Indexed as

BrainCarotid Artery DiseasesCarotid Artery, InternalTomography, X-Ray ComputedVascular CalcificationAdultAgedAged, 80 and overAtrophyFemaleHumansMaleMiddle AgedBrain volumeComputed tomographyIntracranial artery calcificationMorphometry

Identifiers

PMID41831008
PMCPMC13139289

What OpenQuestion holds

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LicenceCC BY
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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.