Academic Appointments

  • Clinical Scholar, Radiology

Professional Education

  • Doctor of Philosophy, Georgia Institute of Technology (2018)
  • Doctor of Medicine, Medical College Of Georgia (2020)
  • Diagnostic Radiology Residency, Mallinckrodt Institute of Radiology at Washington University in Saint Louis and Barnes Jewish Hospital, Diagnostic Radiology (2025)
  • General Surgery Internship, Saint Joseph Hospital, Denver, General Surgery (2021)
  • MD, Medical College of Georgia, Medicine (2020)
  • PhD, Georgia Tech & Emory University, Biomedical Engineering (2018)

Stanford Advisors

Contact

  • Academic
    lindskev@stanford.edu
    University - Scholar Department: Radiology Position: Postdoctoral Scholar

Additional Info

Lab Affiliations

All Publications

  • Characterizing the spatial patterns and determinants of cerebrospinal fluid pseudorandom flow in the human brain with low b-value diffusion MRI IMAGING NEUROSCIENCE Nazeri, A., Hosseini, H., Dehkharghanian, T., Lindsay, K. E., LaMontagne, P., Shimony, J. S., Benzinger, T. L. S., Sotiras, A. 2025; 3

    Abstract

    The circulation of cerebrospinal fluid (CSF) is essential for maintaining brain homeostasis and clearance, and impairments in its flow can lead to various brain disorders. Recent studies have shown that CSF effective motility can be interrogated using low b-value diffusion magnetic resonance imaging (low-b dMRI). Nevertheless, the spatial organization of intracranial CSF flow dynamics remains largely elusive. Here, we developed a whole-brain voxel-based analysis framework, termed CSF pseudo-diffusion spatial statistics ( C Ψ SS ), to examine CSF mean pseudo-diffusivity ( M Ψ ) , a measure of CSF flow magnitude derived from low-b dMRI. We showed that intracranial CSF M Ψ demonstrates characteristic covariance patterns by employing seed-based correlation analysis. Next, we applied non-negative matrix factorization analysis to further elucidate the covariance patterns of CSF M Ψ in a hypothesis-free, data-driven way. We identified 10 distinct CSF compartments with high reproducibility and reliability, reflected by a high mean adjusted Rand index with a low standard deviation (0.82 [SD: 0.018]) in split-half analyses of the discovery multimodal aging dataset (n = 187). The identified patterns displayed similar M Ψ across three replication datasets. In discovery and replication multimodal aging cohorts (unique n = 264), our study revealed that age, sex, brain atrophy, ventricular anatomy, and cerebral perfusion differentially influence M Ψ across these CSF spaces. Notably, of the 35 individuals exhibiting anomalous CSF flow patterns, five displayed clinically consequential incidental findings on multimodal neuroradiological examinations, which were not observed in other participants ( p = 3 . 04 × 10 - 5 ) . Our work sets forth a new paradigm to study CSF flow, with potential applications in clinical settings.

    View details for DOI 10.1162/imag_a_00473

    View details for Web of Science ID 001521319600001

    View details for PubMedID 40322527

    View details for PubMedCentralID PMC12048033

https://orcid.org/0000-0001-5115-8308