Suheyla Cetin Karayumak

• Doctor of Philosophy
• Instructor at Harvard Medical School

Tractography parcellation classifies streamlines reconstructed from diffusion MRI into anatomically defined fiber tracts for clinical and research applications. However, clinical scans often have incomplete fields of view (FOV) where brain regions are partially imaged, leading to partial, or truncated fiber tracts. To address this challenge, we int...

Tractography parcellation classifies streamlines reconstructed from diffusion MRI into anatomically defined fiber tracts for clinical and research applications. However, clinical scans often have incomplete fields of view (FOV) where brain regions are partially imaged, leading to partial or truncated fiber tracts. To address this challenge, we intr...

The cerebellum, long implicated in movement, is now recognized as a contributor to higher-order cognition. The cerebellar pathways provide key structural links between the cerebellum and cerebral regions integral to language, memory, and executive function. Here, we present a large-scale, cross-sectional diffusion MRI (dMRI) analysis investigating...

Parcellation of white matter tractography provides anatomical features for disease prediction, anatomical tract segmentation, surgical brain mapping, and non-imaging phenotype classifications. However, parcellation does not always reach 100% accuracy due to various factors, including inter-individual anatomical variability and the quality of neuroi...

Background The time following a recent onset of psychosis is a critical period during which intervention may be maximally effective. Studying individuals in this period also offers an opportunity to investigate putative brain biomarkers of illness prior to the long-term effects of chronicity and medication. The Human Connectome Project for Early Ps...

The study of brain differences across Eastern and Western populations provides vital insights for understanding potential cultural and genetic influences on cognition and mental health. Diffusion MRI (dMRI) tractography is an important tool in assessing white matter (WM) connectivity and brain tissue microstructure across different populations. How...

Neuroimaging-based prediction of neurocognitive measures is valuable for studying how the brain's structure relates to cognitive function. However, the accuracy of prediction using popular linear regression models is relatively low. We propose a novel deep regression method, namely TractoSCR, that allows full supervision for contrastive learning in...

Purpose Diffusion MRI (dMRI) data typically suffer of marked cross-site variability, which prevents naively performing pooled analyses. To attenuate cross-site variability, harmonization methods such as the rotational invariant spherical harmonics (RISH) have been introduced to harmonize the dMRI data at the signal level. A common requirement of th...

Background Mild traumatic brain injury (mTBI) is common in children. Long-term cognitive and behavioral outcomes as well as underlying structural brain alterations following pediatric mTBI have yet to be determined. In addition, the effect of age-at-injury on long-term outcomes is largely unknown. Methods Children with a history of mTBI ( n = 406;...

This article describes the rationale, aims, and methodology of the Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ). This is the largest international collaboration to date that will develop algorithms to predict trajectories and outcomes of individuals at clinical high risk (CHR) for psychosis and to advance the development and use of...

The Adolescent Brain Cognitive Development (ABCD) Study® has collected data from over 10,000 children across 21 sites, providing insights into adolescent brain development. However, site-specific scanner variability has made it challenging to use diffusion MRI (dMRI) data from this study. To address this, a dataset of harmonized and processed ABCD...

Motivation: Existing white matter atlases are usually created based on a certain population, which may omit subtle differences across populations from different cultures. Goal(s): This study presents a fine-scale white matter atlas that is created concurrently using high-quality diffusion MRI data from both Eastern and Western populations. Approa...

Background Alterations in brain connectivity may underlie neuropsychiatric conditions such as schizophrenia. We here assessed the degree of convergence of frontostriatal fiber projections in 56 young adult healthy controls (HCs) and 108 matched Early Psychosis-Non-Affective patients (EP-NAs) using our novel fiber cluster analysis of whole brain dif...

Studies applying Free Water Imaging have consistently reported significant global increases in extracellular free water (FW) in populations of individuals with early psychosis. However, these published studies focused on homogenous clinical participant groups (e.g., only first episode or chronic), thereby limiting our understanding of the time cour...

The Adolescent Brain Cognitive Development (ABCD) study is a groundbreaking effort aimed at providing a comprehensive understanding of adolescent brain development. With data collected from over 10,000 children across 21 sites, this study promises to unlock key insights into the cognitive, behavioral, and neuroimaging data that underpins this criti...

Neuroimaging-based prediction of neurocognitive measures is valuable for studying how the brain's structure relates to cognitive function. However, the accuracy of prediction using popular linear regression models is relatively low. We propose Supervised Contrastive Regression (SCR), a simple yet effective method that allows full supervision for co...

Background Alterations in brain connectivity may underlie neuropsychiatric conditions such as schizophrenia. We here assessed the degree of convergence of frontostriatal fiber projections in 56 young adult healthy controls (HCs) and 108 matched Early Psychosis-Non-Affective patients (EP-NAs) using our novel fiber cluster analysis of whole brain dif...

Objectives: Disrupted auditory networks play an important role in the pathophysiology of psychosis, with abnormalities already observed in individuals at clinical high-risk for psychosis (CHR). Here, we examine structural and functional connectivity of an auditory network in CHR utilising state-of-the-art electroencephalography and diffusion imagin...

Postmortem studies are currently considered a gold standard for investigating brain structure at the cellular level. To investigate cellular changes in the context of human development, aging, or disease treatment, non-invasive in-vivo imaging methods such as diffusion MRI (dMRI) are needed. However, dMRI measures are only indirect measures and req...

Cognitive deficits are among the best predictors of real-world functioning in schizophrenia. However, our understanding of how cognitive deficits relate to neuropathology and clinical presentation over the disease lifespan is limited. Here, we combine multi-site, harmonized cognitive, imaging, demographic, and clinical data from over 900 individual...

Quantification methods based on the acquisition of diffusion magnetic resonance imaging (dMRI) with multiple diffusion weightings (e.g., multi-shell) are becoming increasingly applied to study the in-vivo brain. Compared to single-shell data for diffusion tensor imaging (DTI), multi-shell data allows to apply more complex models such as diffusion k...

Background: Alterations in the peripheral inflammatory profile and white matter (WM) deterioration are frequent in Major Depressive Disorder (MDD). The present study applies free-water imaging to investigate the relationship between altered peripheral inflammation and WM microstructure and their predictive value in determining response to ketamine...

Studies applying Free Water Imaging have consistently reported significant global increases in extracellular FW in populations of individuals with early psychosis. However, these published studies focused on homogenous clinical participant groups (e.g., only first episode or chronic), thereby limiting our understanding of the time course of free wa...

Research suggests electroconvulsive therapy (ECT) induces an acute neuroinflammatory response and changes in white matter (WM) structural connectivity. However, whether these processes are related, either to each other or to eventual treatment outcomes, has yet to be determined. We examined the relationship between levels of peripheral pro-inflamma...

We present a large-scale harmonized dMRI study where we have performed successful white matter (WM) tractography parcellation across ~10k subjects from the ABCD study. We first assess the effects of data harmonization on WM parcellation, followed by an evaluation of WM parcellation using the entire harmonized dataset. We show that after harmonizati...

This report presents an overview of how machine learning is rapidly advancing clinical translational imaging in ways that will aid in the early detection, prediction, and treatment of diseases that threaten brain health. Towards this goal, we aresharing the information presented at a symposium, “Neuroimaging Indicators of Brain Structure and Functi...

Subtle alterations in white matter microstructure are observed in youth at clinical high risk (CHR) for psychosis. However, the timing of these changes and their relationships to the emergence of psychosis remain unclear. Here, we track the evolution of white matter abnormalities in a large, longitudinal cohort of CHR individuals comprising the Nor...

White matter (WM) abnormalities are repeatedly demonstrated across the schizophrenia time-course. However, our understanding of how demographic and clinical variables interact, influence, or are dependent on WM pathologies is limited. The most well-known barriers to progress are heterogeneous findings due to small sample sizes and the confounding i...

Diffusion MRI studies consistently report group differences in white matter between individuals diagnosed with schizophrenia and healthy controls. Nevertheless, the abnormalities found at the group-level are often not observed at the individual level. Among the different approaches aiming to study white matter abnormalities at the subject level, no...

The heterogeneity of schizophrenia has defied efforts to derive reproducible and definitive anatomical maps of structural brain changes associated with the disorder. We aimed to map deviations from normative ranges of brain structure for individual patients and evaluate whether the loci of individual deviations recapitulated group-average brain map...

Objective: Sexual dimorphism has been investigated in schizophrenia, although sex-specific differences among individuals who are at clinical high-risk (CHR) for developing psychosis have been inconclusive. This study aims to characterize sexual dimorphism of language areas in the brain by investigating the asymmetry of four white matter tracts rele...

Tractography from high-dimensional diffusion magnetic resonance imaging (dMRI) data allows brain’s structural connectivity analysis. Recent dMRI studies aim to compare connectivity patterns across subject groups and disease populations to understand subtle abnormalities in the brain’s white matter connectivity and distributions of biologically sens...

Introduction Recent network-based analyses suggest that schizophrenia symptoms are intricately connected and interdependent, such that central symptoms can activate adjacent symptoms and increase global symptom burden. Here, we sought to identify key clinical and neurobiological factors that relate to symptom organization in established schizophren...

Ketamine is increasingly being used as a therapeutic for treatment-resistant depression (TRD), yet the effects of ketamine on the human brain remain largely unknown. This pilot study employed diffusion magnetic resonance imaging (dMRI) to examine relationships between ketamine treatment and white matter (WM) microstructure, with the aim of increasi...

Several prominent theories of schizophrenia suggest that structural white matter pathologies may follow a developmental, maturational, and/or degenerative process. However, a lack of lifespan studies has precluded verification of these theories. Here, we analyze the largest sample of carefully harmonized diffusion MRI data to comprehensively charac...

The B-SNIP consortium identified three brain-based Biotypes across the psychosis spectrum, independent of clinical phenomenology. To externally validate the Biotype model, we used free-water fractional volume (FW) and free-water corrected fractional anisotropy (FAT) to compare white matter differences across Biotypes and clinical diagnoses. Diffusi...

The findings from diffusion-weighted magnetic resonance imaging (dMRI) studies often show inconsistent and sometimes contradictory results due to small sample sizes as well as differences in acquisition parameters and pre-/post-processing methods. To address these challenges, collaborative multi-site initiatives have provided an opportunity to coll...

Introduction: Clarifying the role of neuroinflammation in schizophrenia is subject to its detection in the living brain. Free-water (FW) imaging is an in vivo diffusion-weighted magnetic resonance imaging (dMRI) technique that measures water molecules freely diffusing in the brain and is hypothesized to detect inflammatory processes. Here, we aime...

Fiber tracking produces large tractography datasets that are tens of gigabytes in size consisting of millions of streamlines. Such vast amounts of data require formats that allow for efficient storage, transfer, and visualization. We present TRAKO, a new data format based on the Graphics Layer Transmission Format (glTF) that enables immediate graph...

Axonal myelination and repair, critical processes for brain development, maturation, and aging, remain controlled by sexual hormones. Whether this influence is reflected in structural brain differences between sexes, and whether it can be quantified by neuroimaging, remains controversial. Diffusion-weighted magnetic resonance imaging (dMRI) is an i...

Synopsis We propose to study whole-brain white matter connectivity differences between females and males using diffusion MRI (dMRI) tractography. We leverage a well-established data-driven fiber clustering pipeline and a novel suprathreshold fiber cluster statistical method. We study a large cohort of 707 healthy adult subjects from the Human Conne...

Schizophrenia (SZ) is proposed as a disorder of dysconnectivity underlying cognitive impairments and clinical manifestations. Although previous studies have shown extracellular changes in white matter of first-episode SZ, little is known about the transition period towards chronicity and its association with cognition. Free-water (FW) imaging was a...

Early neuroimaging work in twin studies focused on studying genetic and environmental influence on gray matter macrostructure. However, it is also important to understand how gray matter microstructure is influenced by genes and environment to facilitate future investigations of their influence in mental disorders. Advanced diffusion MRI (dMRI) mea...

Cross-scanner and cross-protocol variability of diffusion magnetic resonance imaging (dMRI) data are known to be major obstacles in multi-site clinical studies since they limit the ability to aggregate dMRI data and derived measures. Computational algorithms that harmonize the data and minimize such variability are critical to reliably combine data...

White matter tract segmentation, i.e. identifying tractography fibers (streamline trajectories) belonging to anatomically meaningful fiber tracts, is an essential step to enable tract quantification and visualization. In this study, we present a deep learning tractography segmentation method (DeepWMA) that allows fast and consistent identification...

Background Studies in individuals at clinical high risk (CHR) for psychosis provide a powerful means to predict outcomes and inform putative mechanisms underlying conversion to psychosis. In previous work, we applied advanced diffusion imaging methods to reveal that white matter pathology in a CHR population is characterized by cellular-specific ch...

Background The association of white matter (WM) abnormalities with clinical variables in schizophrenia (SCZ) is poorly understood. We investigated the clinical correlates of WM impairments using imaging data of 597 patients with SCZ and 490 healthy controls (HC). We focused on lifelong changes of WM (measured by Fractional Anisotropy [FA]) in SCZ a...

Tractography from high-dimensional diffusion magnetic resonance imaging (dMRI) data allows brain's structural connectivity analysis. Recent dMRI studies aim to compare connectivity patterns across thousands of subjects to understand subtle abnormalities in brain's white matter connectivity across disease populations. Besides connectivity difference...

Introduction Disruptions in homeostatic and hedonic food motivation are proposed to underlie anorexia nervosa (AN) and atypical AN, restrictive eating disorders which commonly onset in puberty. Ghrelin, a neuroprotective hormone that drives hedonic eating is increased in AN and is expressed in the hippocampus. White matter (WM) undergoes significan...

Fiber tracking produces large tractography datasets that are tens of gigabytes in size consisting of millions of streamlines. Such vast amounts of data require formats that allow for efficient storage, transfer, and visualization. We present TRAKO, a new data format based on the Graphics Layer Transmission Format (glTF) that enables immediate graph...

Background The heterogeneity of schizophrenia has defied efforts to derive reproducible and definitive anatomical maps of structural brain changes associated with the disorder. We aimed to map deviations from normative ranges of brain structure for individual patients and evaluate whether the loci of individual deviations recapitulated group-averag...

We present a deep learning tractography segmentation method that allows fast and consistent white matter fiber tract identification across healthy and disease populations and across multiple diffusion MRI (dMRI) acquisitions. We create a large-scale training tractography dataset of 1 million labeled fiber samples (54 anatomical tracts are included)...

Background: In previous work, we applied novel in vivo imaging methods to reveal that white matter pathology in patients with first-episode psychosis (FEP) is mainly characterized by excessive extracellular free-water, and to a lesser extent by cellular processes, such as demyelination. Here, we apply a back-translational approach to evaluate whet...

We present a summary of competition results in the multi-shell diffusion MRI harmonisation and enhancement challenge (MUSHAC). MUSHAC is an open competition intended to stimulate the development of computational methods that reduce scanner- and protocol-related variabilities in multi-shell diffusion MRI data across multi-site studies. Twelve differ...

Background Diffusion MRI abnormalities are frequently reported in psychosis studies, leading to hypotheses regarding the involvement of white matter disruptions, as well as their lifespan trajectories. Nevertheless, little consensus exists regarding the location and extent of such disruptions. Poor reproducibility could result from lack of standard...

Background Altered gamma-band connectivity has been shown across all stages of schizophrenia (SZ) and for persons at High Risk for Psychosis (HRP). Oscillations in the gamma-band frequency range are suggested to play a crucial role for both local and long-range synchronization within the brain during perceptual and cognitive processes. Structural c...

Background Evidence for age related brain white matter (WM) abnormalities in schizophrenia (SZ) has been observed using MRI, and interpreted by various studies as reflecting either developmental, maturational and/or degenerative pathology. Such conflicting findings, mostly due to lack of longitudinal data and statistical power, have hindered consen...

Background Auditory verbal hallucinations (AVH) are one of the hallmarks of psychosis, but they also appear in 5–10 % of healthy individuals. Structural and functional imaging studies implicate the superior temporal gyrus and inferior frontal language areas in generation of AVH. Here, we examined white matter in tracts interconnecting these regions...

Diffusion MRI (dMRI) data is increasingly being acquired on multiple scanners as part of large multi-center neuroimaging studies. However, diffusion imaging is particularly sensitive to scanner-specific differences in coil sensitivity, reconstruction algorithms, acquisition parameters as well as the scanner magnetic field strength, which precludes...

A joint and integrated analysis of multi-site diffusion MRI (dMRI) datasets can dramatically increase the statistical power of neuroimaging studies and enable comparative studies pertaining to several brain disorders. However, dMRI data sets acquired on multiple scanners cannot be naively pooled for joint analysis due to scanner specific nonlinear...

A joint and integrated analysis of multi-site diffusion MRI (dMRI) datasets can dramatically increase the statistical power of neuroimaging studies and enable comparative studies pertaining to several brain disorders. However, dMRI data sets acquired on multiple scanners cannot be naively pooled for joint analysis due to scanner specific nonlinear...

Characterization of anisotropy via diffusion MRI reveals fiber crossings in a substantial portion of voxels within the white-matter (WM) regions of the human brain. A considerable number of such voxels could exhibit asymmetric features such as bends and junctions. However, widely employed reconstruction methods yield symmetric Orientation Distribut...

QSM is used to estimate the underlying tissue magnetic susceptibility and oxygen saturation in veins. This paper presents vessel orientation as a new regularization term to improve the accuracy of \(l_1\) regularized QSM reconstruction in cerebral veins. For that purpose, the vessel tree is first extracted from an initial QSM reconstruction. In a s...

Image quality in non-contrast-enhanced (NCE) angiograms is often limited by scan time constraints. An effective solution is to undersample angiographic acquisitions and to recover vessel images with penalized reconstructions. However, conventional methods leverage penalty terms with uniform spatial weighting, which typically yield insufficient supp...

A diffusion-MRI processing method is presented for representing the inherent asymmetry of the underlying intravoxel geometry, which emerges in regions with bending, crossing, or sprouting fibers. The orientation distribution functions (ODFs) obtained through conventional approaches such as q-ball imaging and spherical deconvolution result in symmet...

A new vascular structure segmentation method, which is based on a cylindrical flux-based higher order tensor (HOT), is presented. On a vessel structure, the HOT naturally models branching points, which create challenges for vessel segmentation algorithms. In a general linear HOT model embedded in 3D, one has to work with an even order tensor due to...

Extraction of vascular structures, such as cerebral arteries from angiography data, is an important step in the detection and analysis of vessel anomalies and pathologies such as aneurysms. It is also important to create accurate and smooth surface models for the hemodynamic or flow dynamic analysis, functional assessment, interventional and surgic...

In this paper, we view the segmentation of cerebral blood vessels from Digital Subtraction Angiography (DSA) and Rotational Angiography (RA) problem from a tensor estimation and tractography perspective as in diffusion tensor imaging (DTI). We have developed a flux based multi-directional cylinder model that fits to a second-order tensor whose prin...

Though conventional coronary angiography (CCA) has been the standard of reference for diagnosing coronary artery disease in the past decades, computed tomography angiography (CTA) has rapidly emerged, and is nowadays widely used in clinical practice. Here, we introduce a standardized evaluation framework to reliably evaluate and compare the perform...

In this paper, we present a tubular structure segmentation method that utilizes a second order tensor constructed from directional intensity measurements, which is inspired from diffusion tensor image (DTI) modeling. The constructed anisotropic tensor which is fit inside a vessel drives the segmentation analogously to a tractography approach in DTI...

In this work, we present an automatic branch and stenoses detection method that is capable of detecting all types of plaques in Computed Tomography Angiography (CTA) modality. Our method is based on the vessel extraction algorithm we proposed in [1], and detects branches and stenoses in a very fast way. We demonstrate the performance of our branch...

In this paper, we propose a novel tubular structure segmen-tation method, which is based on an intensity-based tensor that fits to a vessel. Our model is initialized with a single seed point and it is ca-pable of capturing whole vessel tree by an automatic branch detection algorithm. The centerline of the vessel as well as its thickness is extracte...