Evidence map›Paper›PMID 41325793›Full record

ArticleJournal of stroke and cerebrovascular diseases : the official journal of National Stroke Association2026

Worse visibility of deep medullary veins is associated with larger lateral ventricles but not with cortical thickness.

Sushruth Manchineella, Henry Rusinek, Yuan Ma, Xiuyuan Hugh Wang, Surendra Maharjan, Liangdong Zhou, Tracy Butler, Yi Li, Alexus Jones, Emily Tanzi and 7 more

Abstract read
In one paragraph

Article in Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association, 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

17 authors.

Sushruth ManchineellaBrain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, USA. Electronic address: sushruth.manchi@gmail.com.
Henry RusinekDepartment of Radiology, NYU School of Medicine, New York, USA. Electronic address: hr18@nyu.edu.
Yuan MaDepartment of Epidemiology, Harvard TH Chen School of Public Health, Boston, Massachusetts, USA. Electronic address: yuanma@hsph.harvard.edu.
Xiuyuan Hugh WangBrain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, USA. Electronic address: xiw4004@med.cornell.edu.
Surendra MaharjanBrain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, USA. Electronic address: sum4018@med.cornel.edu.
Liangdong ZhouBrain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, USA. Electronic address: liz2018@med.cornel.edu.
Tracy ButlerBrain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, USA. Electronic address: tab2006@med.cornel.edu.
Yi LiBrain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, USA. Electronic address: yil4008@med.cornel.edu.
Alexus JonesBrain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, USA. Electronic address: alj4006@med.cornel.edu.
Emily TanziBrain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, USA. Electronic address: ebt4001@med.cornel.edu.
Gloria C ChiangBrain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, USA. Electronic address: gcc9004@med.cornel.edu.
Silky PahlajaniBrain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, USA. Electronic address: sip9018@med.cornel.edu.
Katarzyna Olejniczak-GniadekNeurorehabilitation Clinic, Military Institute of Medicine, Warsaw, Poland. Electronic address: kgniadek-olejniczak@wim.mil.pl.
Seyed Hani HojjatiBrain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, USA. Electronic address: sh4006@med.cornel.edu.
Thomas MaloneyBrain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, USA. Electronic address: trm4001@med.cornel.edu.
Mony J de LeonBrain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, USA. Electronic address: mony.deleon@gmail.com.
Lidia GlodzikBrain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, USA. Electronic address: lig4005@med.cornel.edu.

Funding

PREDICTORS OF COGNITIVE DECLINE IN NORMAL AGINGR01AG012101 · NIA · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI DE LEON, MONY J., RUSINEK, HENRY · 1993 to 2015
$6.7M
Blood Pressure, Cerebral Perfusion & Cognitive Outcome In Hypertension.R01HL111724 · NHLBI · WEILL MEDICAL COLL OF CORNELL UNIV · PI GLODZIK, LIDIA · 2012 to 2025
$6.6M
Biomarkers in Early Alzheimer's Disease (AD).R01AG022374 · NIA · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI DE LEON, MONY J., RUSINEK, HENRY · 2004 to 2015
$5.2M
PET Measures of CSF Clearance in Preclinical Alzheimer's DiseaseRF1AG057570 · NIA · WEILL MEDICAL COLL OF CORNELL UNIV · PI DE LEON, MONY J. · 2017 to 2017
$4.1M
CSF Clearance in Sporadic Alzheimer's DiseaseR01AG057848 · NIA · WEILL MEDICAL COLL OF CORNELL UNIV · PI LI, YI · 2018 to 2023
$4.0M
Hypertension, brain clearance and markers of neurodegenerationR01NS104364 · NINDS · WEILL MEDICAL COLL OF CORNELL UNIV · PI GLODZIK, LIDIA · 2018 to 2022
$3.7M
CSF Clearance with 11C-Butanol PET Predicts Amyloid DepositionR56AG058913 · NIA · WEILL MEDICAL COLL OF CORNELL UNIV · PI DE LEON, MONY J., RUSINEK, HENRY · 2018 to 2018
$861k
NHLBI NIH HHS R01 HL111724NIA NIH HHS R01 AG012101NIA NIH HHS R01 AG022374NIA NIH HHS R01 AG057848NIA NIH HHS R56 AG058913NIA NIH HHS RF1 AG057570NINDS NIH HHS R01 NS104364
6 · The paper itself

Abstract

backgroundDeep medullary veins (DMVs) play important roles within the cerebrovascular network related to brain drainage and clearance. Although they have been previously correlated with brain volume, it is unknown whether their count is specifically correlated with subcortical or cortical volume changes. PURPOSE: This study aims to better understand the relationship between DMVs, subcortical (lateral ventricle to intracranial volume ratio (ICV)) and cortical atrophy (cortical thickness) to identify whether DMVs can be a predictor of volume changes in these regions.

methodsWe performed a retrospective analysis of 332 cognitively healthy subjects previously followed between 2010 and 2019. Imaging and patient charts were analyzed for baseline demographic and clinical characteristics. Patients underwent a standardized cognitive interview and received a magnetic resonance imaging scan to assess DMVs, cortical thickness, lateral ventricle and global gray matter (GM) volumes, white matter lesions (WMLs) and microbleeds.

resultsAmong 332 patients (62% female, median age 70), lateral ventricle/ICV was significantly related to DMV count (p<0.001). Similarly, sex stratified analyses confirmed that a larger lateral ventricle/ICV ratio, but not cortical thickness or global GM volumes, was associated with fewer DMVs. In the entire group, subcortical atrophy remained a significant predictor of DMVs even after accounting for baseline characteristics, WMLs, microbleeds and total gray matter volume.

conclusionsIn a large cohort of cognitively unaffected people, subcortical, but not cortical, atrophy was significantly correlated with venous health as measured by DMVs. Reduced DMVs are a strong predictor of ventricular enlargement.

Indexed as

Brain Cortical ThicknessCerebral CortexCerebral VeinsLateral VentriclesMagnetic Resonance ImagingMedulla OblongataAdultAgedAged, 80 and overAtrophyCognitionFemaleHumansMaleMiddle AgedOrgan Sizecortical atrophydeep medullary veinsSWIventricular enlargement

Identifiers

PMID41325793
PMCPMC13012701

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

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.