Biology subjects

Nazeri, A.

Publications and source records attributed to Nazeri, A..

5 recordsLinked to original sources

bioRxiv2026

Automated Ventricle Assessment via Three-dimensional Anatomical Reconstruction (AVA-TAR): a computational toolkit for autonomous lateral ventricle assessment in preclinical hydrocephalus models

IntroductionCurrent workflows for studying hydrocephalus in rodent models rely on manual segmentation or qualitative assessment of ventricular size on small animal magnetic resonance imaging, which are both inefficient and prone to variability. Atlas-based methods enable more streamlined segmentation, but their analysis is limited to morphologically normal samples. ObjectiveThis study aimed to develop and internally validate a deep learning model that performs automated segmentation of lateral ventricles in rodent brain MRIs, allowing for 3D ventricle reconstruction, morphological analysis, and ventriculomegaly detection. MethodsFour U-Net++ neural networks, each with different encoder backbones, were trained using 307 rodent brain MRIs (262 rats, 45 mice), each with manually segmented lateral ventricles serving as the ground truth. Model performance was evaluated using the Dice coefficient, intersection over union (IoU), and Hausdorff index. The most optimal model was evaluated further for its ability to quantify ventricle volume, convexity, surface area, and symmetry. ResultsThe U-Net++ model with an EfficientNet-B1 encoder achieved high accuracy (Dice: 0.823 {+/-} 0.136; IoU: 0.721 {+/-} 0.85). Further assessment of its morphological predictions found strong correlations with manual measurements of ventricular morphology, with Pearson and interclass correlation coefficients exceeding 0.96 across all metrics. The full validated pipeline was packaged into a publicly available application, hosted at https://ava-tar.org. ConclusionThis study introduces a deep learning tool for automated segmentation and morphological analysis of lateral ventricles in rodent MRIs. The tools efficiency and accuracy in quantifying ventricle morphology offers significant utility in preclinical hydrocephalus research with potential future application in the clinical setting.

neuroscience↗

bioRxiv2026

Simultaneous Real-time Imaging of Neurofluid and Neurovascular Dynamics Using Ultrafast Flow-weighted Echo-Planar Imaging

Cerebrospinal fluid (CSF) circulation is tightly coupled to cerebral blood flow under the fixed-volume constraint of the cranial vault, with cardiac pulsations and respiration acting as dominant physiological drivers. Disruption of these flow dynamics has been implicated in various neurological disorders, motivating the need for imaging methods that capture CSF and vascular flow simultaneously and in real time. Conventional phase contrast MRI (PC-MRI) provides quantitative CSF velocity measurements but relies on cardiac gating and velocity encoding, which limit temporal resolution, dynamic range, and sensitivity to non-cardiac fluctuations. Here, we introduce self-gated ultrafast real-time flow-weighted echo-planar imaging (SURF-EPI), an inflow-weighted approach in which signal intensity reflects the replacement of saturated spins by freshly inflowing, unsaturated water molecules, yielding higher signal with higher flow. This allows simultaneous assessment of arterial inflow, venous outflow, and CSF motion at high temporal resolution. SURF-EPI was acquired at the C2-C3 spinal level, enabling real-time imaging of CSF flow dynamics in the cervical spinal canal alongside arterial and venous blood flow in major cervical vessels (frame-rate: 21.7 Hz). In addition to frequency-domain analyses, we leveraged intrinsic arterial signal fluctuations as a timing reference to reconstruct cardiac-resolved CSF dynamics for individual cardiac cycles without external physiological recordings. Frequency-domain analysis revealed distinct spectral signatures in CSF flow compared with neurovascular flow, including broadened cardiac peaks and enhanced respiratory modulation, particularly within the ventral spinal canal. In contrast, dorsal CSF showed increased power within the cardiac frequency band, higher coherence with cervical vasculature at the cardiac frequency, and reduced non-cardiac contributions. Time-domain analysis showed strong correlation between CSF flow waveforms derived from SURF-EPI and PC-MRI. Beyond ensemble-averaged waveforms, SURF-EPI enabled beat-to-beat analysis, revealing substantial cycle-to-cycle variability in CSF flow that is not captured by time-averaged gated approaches. Together, these findings establish SURF-EPI as a rapid, complementary framework to PC-MRI, enabling real-time neurofluid imaging with integrated time- and frequency-domain characterization of CSF and neurovascular flow dynamics.

neuroscience↗

bioRxiv2025

Indirect Deuterium Displacement Exchange Imaging for Non-invasive High-Resolution CSF Production Mapping

Cerebrospinal fluid (CSF) production is central to brain homeostasis, yet existing measurement techniques are invasive, technically demanding, and confounded by intracranial perturbations. Here, we introduce indirect deuterium displacement exchange imaging (CSF-iDDxI), a noninvasive MRI approach for mapping CSF production in vivo. The method leverages intravenously infused deuterium oxide (D2O), which crosses the blood-CSF barrier, replaces existing H2O in CSF, producing concentration-dependent attenuation of proton (1H) signal within CSF spaces. Using high-resolution 3D balanced steady-state free precession MRI in rats, we demonstrate robust and spatially widespread D2O-induced CSF signal loss that is selectively suppressed by acetazolamide, a carbonic anhydrase inhibitor known to suppress CSF production by the choroid plexus. Dynamic imaging during intravenous D2O infusion further revealed that cortical parenchymal signal changes were unaffected by acetazolamide, confirming specificity to CSF production. Exploratory kinetic modeling estimated rapid CSF water turnover (k {approx} 0.09 min-1) under physiological conditions, reduced to k {approx} 0.031 min-1 with acetazolamide suppression, consistent with prior isotope tracer studies. Together, these findings establish CSF-iDDxI as a sensitive, pharmacologically validated tool for quantifying CSF production and turnover.

neuroscience↗

bioRxiv2023

The Spatial Patterns and Determinants of Cerebrospinal Fluid Circulation in the Human Brain

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 circulation 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{Psi}SS), to examine CSF mean pseudo-diffusivity (M{Psi}), a measure of CSF flow magnitude derived from low-b dMRI. We showed that intracranial CSF M{Psi} demonstrates characteristic covariance patterns by employing seed-based correlation analysis. Importantly, we applied non-negative matrix factorization analysis to further elucidate the covariance patterns of CSF M{Psi} in a hypothesis-free, data-driven way. We identified distinct CSF spaces that consistently displayed unique pseudo-diffusion characteristics across multiple imaging datasets. Our study revealed that age, sex, brain atrophy, ventricular anatomy, and cerebral perfusion differentially influence M{Psi} across these CSF spaces. Notably, individuals with anomalous CSF flow patterns displayed incidental findings on multimodal neuroradiological examinations. Our work sets forth a new paradigm to study CSF flow, with potential applications in clinical settings.

neuroscience↗

bioRxiv2022

Neurodevelopmental Patterns of Early Postnatal White Matter Maturation Represent Distinct Underlying Microstructure and Histology

During the early postnatal period, cerebral white matter undergoes rapid maturation through a complex series of interrelated cellular and histogenetic processes. Accurately quantifying these processes is important for improving understanding of early brain development, developmental abnormalities related to prematurity, and neurodevelopmental diseases. Past efforts have used magnetic resonance imaging (MRI) to track these developmental processes in vivo. However, most previous studies have relied on single imaging modality data and have often been limited by small samples and analytics that do not evaluate complex multivariate imaging patterns. Here, we applied an advanced unsupervised multivariate pattern analysis technique, non-negative matrix factorization (NMF), to T2w/T1w signal ratio maps from a large cohort of newborns (Developing Human Connectome Project [dHCP], n=342), revealing patterns of synchronous white matter maturation. These patterns showed divergent age-related maturational trajectories and differential susceptibility to premature birth, which were replicated in an independent large sample of newborns (Early Life Adversity, Biological Embedding, and Risk for Developmental Precursors of Mental Disorders [eLABE], n=239). Furthermore, we showed that T2w/T1w signal variations in white matter maturational patterns are explained by differential contributions of white matter microstructure indices (i.e., free water content and neurite density index) derived from neurite orientation dispersion and density imaging (NODDI) modeling of diffusion-weighted MRI. Finally, we demonstrated how white matter maturation patterns relate to distinct histological features by comparing our findings with postmortem late fetal/early postnatal brain tissue staining. Together, these results delineate a novel MRI representation of white matter microstructural and histological reorganization during the early postnatal development.

neuroscience↗