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Karki, Pragalv

https://orcid.org/0000-0002-4234-6945

Mayo Clinic

Mayo Clinic

Citations 1

Real‐Time 2D Phase‐Contrast MRI to Assess Cardiac‐ and Respiratory‐Driven CSF Movement in Normal Pressure Hydrocephalus
Karki, Pragalv , Murphy, Matthew C. , Ganji, Sandeep , Gunter, Jeffrey L. , Graff‐Radford, Jonathan, Cutsforth‐Gregory, Jeremy K. , Elder, Benjamin D. , Jack, Clifford R. , Jack, Clifford R , Ganji, Sandeep K , Graff‐Radford, Jonathan , Jones, David T. , Botha, Hugo , Huston, John , Cogswell, Petrice M.

Journal of Neuroimaging | December 31, 2024 | Volume: 35 | Issue: 1 | Pages: No page available

10.1111/jon.70000 Get It

ABSTRACT Background and Purpose In idiopathic normal pressure hydrocephalus (iNPH) patients, cerebrospinal fluid (CSF) flow is typically evaluated with a cardiac‐gated two‐dimensional (2D) phase‐contrast (PC) MRI through the cerebral aqueduct. This approach is limited by the evaluation of a single location and does not account for respiration effects on flow. In this study, we quantified the cardiac and respiratory contributions to CSF movement at multiple intracranial locations using a real‐time 2D PC‐MRI and evaluated the diagnostic value of CSF dynamics biomarkers in classifying iNPH patients. Methods This study included 37 participants: 16 iNPH, 10 Alzheimer's disease (AD), and 11 cognitively unimpaired (CU) controls. Anatomical and real‐time (non‐gated) PC images were acquired in a 3T Philips scanner. CSF flow was assessed at the foramen magnum, fourth ventricle, Sylvian fissure, lateral ventricle, and cerebral aqueduct. We calculated three CSF dynamics biomarkers: mean velocity amplitude, cardiac signal power, and respiratory signal power. Biomarkers from each location were evaluated for classifying iNPH versus AD and CU using support vector machine (SVM). A p ‐value of 0.05 or less was considered statistically significant. Results The velocity amplitude and cardiac signal power were significantly reduced in iNPH compared to CU ( p < 0.005) and AD ( p < 0.05) at the lateral ventricle. The SVM model using biomarkers from the lateral ventricle performed significantly better at classifying iNPH than the other locations in terms of accuracy ( p < 0.005) and diagnostic odds ratio ( p < 0.05). Conclusion Evaluation of CSF movement beyond the cerebral aqueduct may aid in identifying patients with and understanding the pathophysiology of iNPH.