Evidence map›Paper›PMID 42051549›Full record

ArticleFrontiers in neuroscience2026

A multimodal imaging-based integrative framework for HIV-associated cognitive impairment and treatment response.

Xing Qiu, Md Nasir Uddin, Lu Wang, Alicia Tyrell, Abrar Faiyaz, Nhat Hoang, Yuchuan Zhuang, Madalina E Tivarus, Jianhui Zhong, Miriam T Weber and 1 more

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 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
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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

11 authors.

Xing QiuDepartment of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, United States.
Md Nasir UddinDepartment of Neurology, University of Rochester, Rochester, NY, United States.
Lu WangDepartment of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, United States.
Alicia TyrellDepartment of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, United States.
Abrar FaiyazDepartment of Neurology, University of Rochester, Rochester, NY, United States.
Nhat HoangDepartment of Physics and Astronomy, University of Rochester, Rochester, NY, United States.
Yuchuan ZhuangDepartment of Electrical and Computer Engineering, University of Rochester, Rochester, NY, United States.
Madalina E TivarusDepartment of Imaging Sciences, University of Rochester, Rochester, NY, United States.
Jianhui ZhongDepartment of Biomedical Engineering, University of Rochester, Rochester, NY, United States.
Miriam T WeberDepartment of Neurology, University of Rochester, Rochester, NY, United States.
Giovanni SchifittoDepartment of Neurology, University of Rochester, Rochester, NY, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Combination antiretroviral therapy (cART) has been shown to reduce inflammation in persons with HIV (PWH), leading to overall improvements in cognition. However, these improvements are patient-dependent and not always observable over short treatment periods. Methods: We applied a multimodal integrative model to associate various baseline MR neuroimaging metrics with baseline neurocognitive performance and their longitudinal changes over 12 weeks of cART treatment. Features in our model included volumetric data, cerebral blood flow metrics, cerebrovascular reactivity, and diffusion MRI data from cortical, subcortical, and white matter regions of the brain. Our integrative model, which includes multilayered principal component analysis, penalized regression, and feature weight back-propagation, is designed for "large p, small n" data and offers better interpretability than deep-learning methods. Results: There is a modest association between imaging metrics and baseline neurocognitive scores for both PWH and age-matched healthy controls, driven primarily by subcortical regions. In contrast, baseline imaging features exhibited stronger associations with longitudinal changes in cognitive performance over 12 weeks of cART in PWH than with baseline cognitive scores. The multimodal integrative model outperformed all comparable unimodal models in explaining longitudinal cognitive change. Among unimodal analyses, models based on cerebral blood flow and free-water-corrected fractional anisotropy demonstrated the strongest associations. Frequently selected predictors included the frontal pole (cortical gray matter); the amygdala, putamen, and hippocampus (subcortical gray matter); and the posterior limb of the internal capsule (white matter). Discussion: Our approach provides an interpretable statistical framework that integrates complementary information across various imaging modalities into a robust and interpretable model for short-term cognitive trajectories in PWH undergoing cART.

Indexed as

braincognitive impairmentHIVinterpretable machine learningMRImultimodal integrationneuroimaging

Identifiers

PMID42051549
PMCPMC13111216

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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.