Publications by authors named "Andrew Nencka"

In functional magnetic resonance imaging (fMRI) of the blood oxygen level-dependent (BOLD) contrast, gradient-recalled echo (GRE) acquisitions offer high sensitivity but suffer from susceptibility-induced signal loss and lack specificity to microvasculature. In contrast, spin echo (SE) acquisitions provide improved specificity at the cost of reduced sensitivity. This study introduces Asymmetric Spin Echo Multi-Echo Echo Planar Imaging (ASEME-EPI), a technique designed to combine the benefits of both GRE and SE for high-field preclinical fMRI.

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Introduction: Emerging evidence illustrates that temporal lobe epilepsy (TLE) involves network disruptions represented by hyperexcitability and other seizure-related neural plasticity. However, these associations are not well-characterized. Our study characterizes the whole brain white matter connectome abnormalities in TLE patients compared to healthy controls (HCs) from the prospective Epilepsy Connectome Project study.

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Objective: To develop MRI-derived carpal kinematic metrics and investigating their stability.

Methods: The study used a 4D MRI method to track scaphoid, lunate, and capitate movements in the wrist. A panel of 120 metrics for radial-ulnar deviation and flexion-extension was created using polynomial models of scaphoid and lunate movements relative to the capitate.

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Background: Chronic low back pain (cLBP) has been associated with alterations in brain functional connectivity (FC) but based upon heterogeneous populations and single network analyses. Our goal is to study a more homogeneous cLBP population and focus on multiple cross-network (CN) connectivity analysis. We hypothesize that within this population: 1) altered CN FC, involving emotion and reward/aversion functions are related to their pain levels and 2) altered relationships are dependent upon pain phenotype (constant neuropathic vs intermittent pain).

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Diffusion-weighted magnetic resonance imaging (DW-MRI) is a promising technique for assessing spinal cord injury (SCI) that has historically been challenged by the presence of metallic stabilization hardware. This study leverages recent advances in metal-artifact resistant multi-spectral DW-MRI to enable diffusion quantification throughout the spinal cord even after fusion stabilization. Twelve participants with cervical spinal cord injuries treated with fusion stabilization and 49 asymptomatic able-bodied control participants underwent multi-spectral DW-MRI evaluation.

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Short-range functional connectivity in the limbic network is increased in patients with temporal lobe epilepsy (TLE), and recent studies have shown that cortical myelin content correlates with fMRI connectivity. We thus hypothesized that myelin may increase progressively in the epileptic network. We compared T1w/T2w gray matter myelin maps between TLE patients and age-matched controls and assessed relationships between myelin and aging.

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Dramatic advances in the management of congenital heart disease (CHD) have improved survival to adulthood from less than 10% in the 1960s to over 90% in the current era, such that adult CHD (ACHD) patients now outnumber their pediatric counterparts. ACHD patients demonstrate domain-specific neurocognitive deficits associated with reduced quality of life that include deficits in educational attainment and social interaction. Our hypothesis is that ACHD patients exhibit vascular brain injury and structural/physiological brain alterations that are predictive of specific neurocognitive deficits modified by behavioral and environmental enrichment proxies of cognitive reserve (e.

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Objective: Social determinants of health, including the effects of neighborhood disadvantage, impact epilepsy prevalence, treatment, and outcomes. This study characterized the association between aberrant white matter connectivity in temporal lobe epilepsy (TLE) and disadvantage using a US census-based neighborhood disadvantage metric, the Area Deprivation Index (ADI), derived from measures of income, education, employment, and housing quality.

Methods: Participants including 74 TLE patients (47 male, mean age = 39.

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Introduction: Wrist instability remains a common health concern. The potential of dynamic Magnetic Resonance Imaging (MRI) in assessing carpal dynamics associated with this condition is a field of ongoing research. This study contributes to this line of inquiry by developing MRI-derived carpal kinematic metrics and investigating their stability.

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Introduction: This study investigated tissue diffusion properties within the spinal cord of individuals treated for cervical spondylotic myelopathy (CSM) using post-decompression stabilization hardware. While previous research has indicated the potential of diffusion-weighted MRI (DW-MRI) markers of CSM, the metallic implants often used to stabilize the decompressed spine hamper conventional DW-MRI.

Methods: Utilizing recent developments in DW-MRI metal-artifact suppression technologies, imaging data was acquired from 38 CSM study participants who had undergone instrumented fusion, as well as asymptomatic (non-instrumented) control participants.

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Background: Chronic pain has been associated with alterations in brain connectivity, both within networks (regional) and between networks (cross-network connectivity). Functional connectivity (FC) data on chronic back pain are limited and based on heterogeneous pain populations. Patients with postsurgical persistent spinal pain syndrome (PSPS) type 2 are good candidates for spinal cord stimulation (SCS) therapy.

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Temporal lobe epilepsy (TLE) is the most common epilepsy syndrome that empirically represents a network disorder, which makes graph theory (GT) a practical approach to understand it. Multi-shell diffusion-weighted imaging (DWI) was obtained from 89 TLE and 50 controls. GT measures extracted from harmonized DWI matrices were used as factors in a support vector machine (SVM) analysis to discriminate between groups, and in a k-means algorithm to find intrinsic structural phenotypes within TLE.

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One in eight men will be affected by prostate cancer (PCa) in their lives. While the current clinical standard prognostic marker for PCa is the Gleason score, it is subject to inter-reviewer variability. This study compares two machine learning methods for discriminating between cancerous regions on digitized histology from 47 PCa patients.

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Background: Radiomics is an approach to medical imaging that quantifies the features normally translated into visual display. While both radiomic and clinical markers have shown promise in predicting response to neoadjuvant chemoradiation therapy (nCRT) for rectal cancer, the interrelationship is not yet clear.

Methods: A retrospective, single-institution study of patients treated with nCRT for locally advanced rectal cancer was performed.

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Background: There are now clinically available automated MRI analysis software programs that compare brain volumes of patients to a normative sample and provide -score data for various brain regions. These programs have yet to be validated in primary progressive aphasia (PPA).

Objective: To address this gap in the literature, we examined Neuroreader -scores in PPA, relative to visual MRI assessment.

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A preliminary exploration of technical methodology for dynamic analysis of scaphoid, capitate, and lunate during unconstrained movements is performed in this study. A heavily accelerated and fat-saturated 3D Cartesian MRI acquisition was used to capture temporal frames of the unconstrained moving wrist of 5 healthy subjects. A slab-to-volume point-cloud based registration was then utilized to register the moving volumes to a high-resolution image volume collected at a neutral resting position.

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Repetitive head impact (RHI) exposure has been associated with differences in brain structure among younger active athletes, most often within the hippocampus. Studies of former athletes at early-midlife are limited. We investigated the association between RHI exposure and gray matter (GM) structure, as well as moderating factors, among former athletes in early-midlife.

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Article Synopsis
  • The study aimed to compare deep learning (DL) image reconstruction with conventional MRI methods, focusing on noise reduction settings of 50% and 75% among orthopedic MRI datasets.
  • It involved 54 patients and utilized quantitative metrics like edge sharpness and signal-to-noise ratio, alongside expert radiologist rankings to assess image quality and diagnostic confidence.
  • Results revealed that both DL settings yielded better image quality than conventional methods, but there was less consensus among radiologists on which DL setting was superior.
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Advanced diffusion MRI models are being explored to study the complex microstructure of the brain with higher accuracy. However, these techniques require long acquisition times. Simultaneous Multi-Slice (SMS) accelerates data acquisition by exciting multiple image slices simultaneously and separating the overlapping slices using a mathematical model, which makes use of the distinct information coming from an array of receive coils.

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Cardiac magnetic resonance imaging (CMR) is considered the gold standard for measuring cardiac function. Further, in a single CMR exam, information about cardiac structure, tissue composition, and blood flow could be obtained. Nevertheless, CMR is underutilized due to long scanning times, the need for multiple breath-holds, use of a contrast agent, and relatively high cost.

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Temporal lobe epilepsy (TLE) has been conceptualized as focal disease with a discrete neurobiological focus and can respond well to targeted resection or ablation. In contrast, the neuro-cognitive deficits resulting from TLE can be widespread involving regions beyond the primary epileptic network. We hypothesize that this seemingly paradoxical findings can be explained by differences in connectivity between the primary epileptic region which is hyper-connected and its secondary influence on global connectome organization.

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Purpose: Simultaneous multi-slice acquisitions are essential for modern neuroimaging research, enabling high temporal resolution functional and high-resolution q-space sampling diffusion acquisitions. Recently, deep learning reconstruction techniques have been introduced for unaliasing these accelerated acquisitions, and robust artificial-neural-networks for k-space interpolation (RAKI) have shown promising capabilities. This study systematically examines the impacts of hyperparameter selections for RAKI networks, and introduces a novel technique for training data generation which is analogous to the split-slice formalism used in slice-GRAPPA.

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Background: 7T cardiac magnetic resonance imaging (MRI) introduces several advantages, as well as some limitations, compared to lower-field imaging. The capabilities of ultra-high field (UHF) MRI have not been fully exploited in cardiac functional imaging.

Aim: To optimize 7T cardiac MRI functional imaging without the need for conducting B1 shimming or subject-specific tuning, which improves scan efficiency.

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Recent studies have demonstrated the promising capabilities of magnetic resonance imaging (MRI)-based quantitative susceptibility maps (QSM) in producing biomarkers of brain injury. The present study aims to further explore acute QSM changes in athletes after sports concussion and investigate prognostication capabilities of QSM-derived imaging metrics. The QSM were derived from neurological MRI data acquired on a cohort ( = 78) of concussed male American football athletes within 48 h of injury.

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Prostate cancer primarily arises from the glandular epithelium. Histomophometric techniques have been used to assess the glandular epithelium in automated detection and classification pipelines; however, they are often rigid in their implementation, and their performance suffers on large datasets where variation in staining, imaging, and preparation is difficult to control. The purpose of this study is to quantify performance of a pixelwise segmentation algorithm that was trained using different combinations of weak and strong stroma, epithelium, and lumen labels in a prostate histology dataset.

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