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Record W4409620049 · doi:10.21037/qims-24-1830

A preliminary study of synthetic magnetic resonance imaging on the changes of subcortical gray matter nuclei in obstructive sleep apnea patients

2025· article· en· W4409620049 on OpenAlexaboutno aff
Kun Peng, Ning Zhang, Qing Liu, Ailian Xiao, Kaiyu Wang, Hui Zhang

Bibliographic record

VenueQuantitative Imaging in Medicine and Surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsnot available
Fundersnot available
KeywordsGray (unit)Magnetic resonance imagingObstructive sleep apneaMedicineRadiologyNuclear magnetic resonanceInternal medicinePhysics

Abstract

fetched live from OpenAlex

Background: Obstructive sleep apnea (OSA) is a relatively common sleep disorder, which can damage the brain structure and thus trigger cognitive impairment. We aimed to assess changes in volume and relaxation values of subcortical gray matter nuclei in patients with moderate to severe OSA using synthetic magnetic resonance imaging (SyMRI). Methods: A total of 30 patients with moderate to severe OSA, newly diagnosed by polysomnography (PSG), and 30 age-, sex-, education-, and handedness-matched healthy controls (HC) were recruited. All participants underwent the Montreal Cognitive Assessment (MoCA) Scale. Conventional MRI, three-dimensional T1-weighted brain volume (3D T1-BRAVO), and SyMRI were performed on both groups using a 3.0TMR scanner. After scanning, original SyMRI data were post-processed using SyMRI8.0 software to automatically generate T1, T2, and proton density (PD) quantitative maps, and subcortical gray matter nuclei were obtained using SPM12 software (Matlab R2015b). Cognitive scale scores, subcortical gray matter nuclei volume, and relaxation quantitative values were compared between groups. Volume and relaxation quantitative values were corrected for multiple comparisons using a false discovery rate (FDR). SyMRI quantitative parameters with statistically significant differences underwent receiver operating characteristic (ROC) analysis to calculate the area under the curve (AUC). Correlations between changes in abnormal brain volume and relaxation values and MoCA scores were analyzed in the OSA group, using FDR for multiple comparisons and corrections. Results: Compared to controls, the OSA group exhibited a significant decrease in bilateral thalamic volume (P=0.002, 0.003, uncorrected). T1 values increased significantly in the left hippocampus, amygdala, caudate nucleus, right pallidum, thalamus, and bilateral putamen (P=0.02, 0.040, 0.01, <0.001, 0.03, 0.04, 0.004, uncorrected). The left hippocampus showed significantly increased T2 values (P=0.03, uncorrected). In contrast, the PD values increased significantly in the left amygdala, nucleus accumbens, right pallidum, putamen, bilateral caudate nucleus, and thalamus (P=0.02, 0.041, 0.01, 0.006, 0.007, 0.03, 0.047, 0.009, uncorrected). After FDR correction, significant differences persisted in the bilateral thalamic volume, T1 values of left caudate, right putamen and pallidum, PD values of left amygdala, right pallidum, putamen, bilateral caudate nucleus, and thalamus. ROC curve analysis revealed significant differences in bilateral thalamic volume, T1 values of left caudate nucleus, right putamen and pallidum, PD values of left amygdala, caudate nucleus, right putamen, pallidum, and thalamus between OSA patients and controls (P=0.002, 0.001, 0.01, 0.007, <0.001, 0.02, 0.007, 0.01, 0.01, 0.03; AUC 0.668-0.770). After controlling for age, body mass index (BMI), and years of education, OSA patients showed negative correlations between visual space and executive function and the right putamen T1 and PD values (r=-0.390, -0.449; P=0.045, 0.02) and positive correlations with the left amygdala PD value (r=0.397; P=0.04). No significant differences were found in partial correlation analysis after FDR correction. Conclusions: SyMRI offers sensitive detection of abnormal volume and relaxation value changes in subcortical gray matter nuclei among patients with moderate to severe OSA. These findings provide valuable imaging information for quantifying subcortical gray matter nuclei damage in OSA and advancing our understanding of the neuropathological mechanisms underlying cognitive impairment.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.318
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2025
Admission routes1
Has abstractyes

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