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Published on: September 25, 2019
Acute-Phase T2-FLAIR Radiomics in Acute Carbon Monoxide Poisoning: Deep White Matter Vulnerability and Lucid-Interval
Jiaxun Guo1, Guyue Lei1, Ruichi Zhang1
1From the West China School of Public Health (J.G., R.Z., Y.W., Z.L.), Toxicology (Z.L.), West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China and West China School of Medicine (G.L.), Sichuan University, Chengdu, Sichuan, China.
Background And Purpose:
Delayed encephalopathy after acute carbon monoxide poisoning (DEACMP) remains difficult to predict during the lucid interval. We tested whether routine acute-phase T2-FLAIR radiomics could detect subvisual deep-white-matter vulnerability and improve lucid-interval DEACMP risk stratification.
Materials And Methods:
We retrospectively analyzed 786 adults with acute carbon monoxide poisoning, including 201 acute-phase T2-FLAIR MRI scans split chronologically into imaging-training and held-out imaging-test sets. Six-compartment radiomics and clinical-radiomic stacking used training-restricted preprocessing and model development. Repeated MRI assessed temporal behavior; blinded visual MRI benchmarking and MRI-training downsampling were used as support analyses.
Results:
Deep white matter showed the dominant DEACMP radiomic signal: 8/9 atlas-guided candidate bundles were cross-sectionally significant after false-discovery-rate correction, and 7/9 showed repeated-MRI group-level elevation without DEACMP-by-time divergence. Pallidal texture supported a secondary DEACMP-dependent urinary-incontinence phenotype. In the held-out imaging-test set, stacking achieved AUC 0.876, Brier score 0.170, sensitivity 0.800, and specificity 0.839.
Conclusions:
Acute-phase T2-FLAIR radiomics delineated a deep-white-matter-dominant imaging phenotype associated with DEACMP risk and a separable DEACMP-dependent pallidal texture phenotype linked to urinary incontinence. Clinical-radiomic stacking improved lucid-interval DEACMP risk stratification, supporting T2-FLAIR radiomics as a research-stage subvisual risk-stratification approach.
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