Evidence map›Paper›PMID 40208877›Full record

ArticlePloS one2025

Assessing the cardioprotective effects of exercise in APOE mouse models using deep learning and photon-counting micro-CT.

Alex J Allphin, Rohan Nadkarni, Zay Y Han, Darin P Clark, Ketan B Ghaghada, Alexandra Badea, Cristian T Badea

Abstract read
In one paragraph

Article in PloS one, 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
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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

7 authors.

Alex J AllphinQuantitative Imaging and Analysis Lab, Department of Radiology, Duke University Medical Center, Durham, North Carolina, United States of America.ORCID 0000-0003-2789-705X
Rohan NadkarniQuantitative Imaging and Analysis Lab, Department of Radiology, Duke University Medical Center, Durham, North Carolina, United States of America.
Zay Y HanQuantitative Imaging and Analysis Lab, Department of Radiology, Duke University Medical Center, Durham, North Carolina, United States of America.
Darin P ClarkQuantitative Imaging and Analysis Lab, Department of Radiology, Duke University Medical Center, Durham, North Carolina, United States of America.
Ketan B GhaghadaDepartment of Radiology, Baylor College of Medicine, Houston, Texas, United States of America.
Alexandra BadeaQuantitative Imaging and Analysis Lab, Department of Radiology, Duke University Medical Center, Durham, North Carolina, United States of America.
Cristian T BadeaQuantitative Imaging and Analysis Lab, Department of Radiology, Duke University Medical Center, Durham, North Carolina, United States of America.

Funding

Sex and APOE genotype interact to alter immune regulated metabolism in ADRF1AG057895 · NIA · DUKE UNIVERSITY · PI BADEA, ALEXANDRA, COLTON, CAROL ANNE · 2019 to 2019
$5.8M
Brain networks in mouse models of agingR01AG066184 · NIA · DUKE UNIVERSITY · PI BADEA, ALEXANDRA · 2019 to 2023
$3.8M
Multiorgan Photon Counting CT and Machine Learning to Elucidate Aging Mechanisms and InterventionsR01AG070149 · NIA · DUKE UNIVERSITY · PI CRISTIAN T BADEA, Alexandra Badea · 2024 to 2026
$2.1M
Sex and APOE genotype interact to alter immune regulated metabolism in ADR56AG057895 · NIA · DUKE UNIVERSITY · PI BADEA, ALEXANDRA, COLTON, CAROL ANNE · 2017 to 2017
$1.1M
NIA NIH HHS R01 AG066184NIA NIH HHS R01 AG070149NIA NIH HHS R56 AG057895NIA NIH HHS RF1 AG057895
6 · The paper itself

Abstract

backgroundThe allelic variations of the apolipoprotein E (APOE) gene play a critical role in regulating lipid metabolism and significantly impact cardiovascular disease risk (CVD). This study aimed to evaluate the impact of exercise on cardiac structure and function in mouse models expressing different APOE genotypes using photon-counting computed tomography (PCCT) and deep learning-based segmentation.

methodsA total of 140 mice were grouped based on APOE genotype (APOE2, APOE3, APOE4), sex, and exercise regimen. All mice were maintained on a controlled diet to isolate the effects of exercise. Low dose cardiac photon counting micro-CT imaging with intrinsic gating was performed using a custom-built micro-PCCT system and data was reconstructed with an iterative algorithm incorporating both temporal and spectral dimensions. A liposomal-iodine nanoparticle contrast agent was intravenously administered to uniformly opacify cardiovascular structures. Cardiac structures were segmented using a 3D U-Net deep learning model that was trained and validated on manually labeled data. Statistical analyses, including ANOVA, post-hoc analysis, and stratified group comparisons, were used to assess the effects of genotype, sex, and exercise on key cardiac metrics, including ejection fraction and cardiac index.

resultsThe PCCT imaging pipeline provided high-resolution images with enhanced contrast between blood compartment and myocardium allowing for precise segmentation of cardiac features. Deep learning-based segmentation achieved high accuracy with an average Dice coefficient of 0.85. Exercise significantly improved cardiac performance, with ejection fraction increasing by up to 18% and cardiac index by 46% in exercised males, who generally benefited more from exercise. Females, particularly those with the APOE4 genotype, also showed improvements, with a 31% higher ejection fraction in exercised versus non-exercised mice. Stratified analyses confirmed that both sexes benefited from exercise, with males showing larger effect sizes. APOE3 and APOE4 genotypes derived the greatest benefit, while APOE2 mice showed no significant improvement.

conclusionsThis study demonstrates the utility of PCCT combined with deep learning segmentation in assessing the cardioprotective effects of exercise in APOE mouse models. These findings highlight the importance of genotype-specific approaches in understanding and potentially mitigating the impact of CVD through lifestyle interventions such as exercise.

Indexed as

Apolipoproteins ECardiovascular DiseasesDeep LearningPhysical Conditioning, AnimalX-Ray MicrotomographyAnimalsDisease Models, AnimalFemaleGenotypeHeartMaleMiceApolipoproteins E

Identifiers

PMID40208877
PMCPMC11984728

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.