Background: Prior studies on the clinical impact of intracerebral hemorrhage (ICH) location have used visual localization of hematomas to neuroanatomical structures. However, hematomas often cross neuroanatomical structure boundaries with inter-reviewer variability in visual localization. To address these limitations, we applied voxel-wise analysis to identify brain regions where ICH presence is independently predictive of worse outcomes.
Methods: We included consecutive patients with acute spontaneous ICH from a comprehensive stroke center in a derivation cohort and validated the results in patients from the control arm of a multicenter clinical trial. Using general linear models, we created and publicly shared a voxel-wise map of brain regions where ICH presence was associated with higher 3-month modified Rankin Scale scores, independent of hematoma volume and clinical risk factors. We also determined the optimal overlap threshold between baseline hematoma and voxel-wise map to categorize ICH location into high versus low risk.
Results: Excluding those with missing variables, head computed tomography processing pipeline failure and poor scan quality, 559 of 780 patients were included in derivation (mean age, 69.3±14.5 years; 311 [55.6%] males) and 345 of 500 (mean age, 62.5±12.9 years; 206 [59.7%] males) in validation cohorts. In a voxel-wise analysis, ICH presence in deep white matter, thalami, caudate, midbrain, and pons was associated with worse outcomes. At the patient level, >22% overlap of baseline hematoma with voxel-wise map optimally binarized ICH location to high- versus low-risk categories. In both the derivation and validation cohorts, a high-risk ICH location was independently associated with worse outcomes (higher 3-month modified Rankin Scale score), after adjusting for patients' age, symptom severity at admission, baseline hematoma volume, and the presence of intraventricular hemorrhage, with adjusted odds ratios of 2 ([95% CI, 1.3-3.0] =0.001) and 1.7 ([95% CI, 1.1-2.9] =0.027), respectively.
Conclusions: We created and publicly shared a voxel-wise map of brain regions where hematoma presence predicts worse outcomes, independent of volume and clinical risk factors.
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http://dx.doi.org/10.1161/STROKEAHA.124.048453 | DOI Listing |
Stroke
March 2025
Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT. (G.A.K., M.-C.C., D.Z., B.C.H., E.B., A.M., S.P.).
Background: Prior studies on the clinical impact of intracerebral hemorrhage (ICH) location have used visual localization of hematomas to neuroanatomical structures. However, hematomas often cross neuroanatomical structure boundaries with inter-reviewer variability in visual localization. To address these limitations, we applied voxel-wise analysis to identify brain regions where ICH presence is independently predictive of worse outcomes.
View Article and Find Full Text PDFNeurology
April 2025
Laboratory on Quantitative Medical Imaging, National Institute of Biomedical Imaging and Bioengineering, Bethesda, MD.
Background And Objectives: Diffusion tensor-based morphometry (DTBM) provides a more accurate assessment of volumetric changes in white matter structures than conventional T1-based TBM techniques. We sought to determine whether DTBM could detect volume loss in the corticospinal tract (CST) and whether this marker was associated with impaired stroke recovery.
Methods: Retrospective clinical MRI scans were obtained from a cohort of participants enrolled in a natural history study with acute anterior circulation ischemic stroke and unilateral arm impairment (NIH Stroke Scale [NIHSS] arm motor item score ≥2).
Med Phys
February 2025
Medical Physics Department, Memorial Sloan Kettering Cancer Center, New York, USA.
Background: The synthesis of CT from CBCT images using AI methods has been explored in radiotherapy to improve adaptive workflows. However, the model training process can be particularly challenging for the abdominal region due to dataset disparities between CT and CBCT images caused by organ motion, low soft tissue contrast, and inconsistencies in air volumes. These factors might impact the implicit prediction uncertainties, which are not actively considered on the synthetized images, overlooking poorly predicted image regions that might lead to inaccuracies in the dose calculation.
View Article and Find Full Text PDFPhys Imaging Radiat Oncol
January 2025
Univ. Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, F-35000 Rennes, France.
Background And Purpose: Cone-beam computed tomography (CBCT) is essential in image-guided radiotherapy (RT) for patient positioning and daily dose calculation. However, CT numbers in CBCT fluctuate and differ from those in computed tomography (CT), requiring synthetic CT (sCT) generation to improve dose calculation accuracy. CBCT-to-sCT synthesis remains a challenging and uncertain task in clinical practice.
View Article and Find Full Text PDFFront Neurol
January 2025
Department of Kinesiology, Penn State University, 19 Recreation Building, University Park, PA, United States.
Introduction: Resting state-fMRI, provides a sensitive method for detecting changes in brain functional integrity, both with respect to regional oxygenated blood flow and whole network connectivity. The primary goal of this report was to examine alterations in functional connectivity in collegiate American football players after a season of repetitive head impact exposure.
Methods: Collegiate football players completed a rs-fMRI at pre-season and 1 week into post-season.
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