About

The Laboratory of Mathematics in Imaging (LMI) is focused on the application of mathematical theory, analysis, modeling, and signal processing to medical imaging. Research projects within the group cover both novel theoretical contributions and translational clinical efforts. The research team combine strengths in computer science and mathematics with radiology, neuroscience, and novel MRI sequence developmentLearn more

Recent Publications

Amyloid-PET of the White Matter: Relationship to Free Water, Fiber Integrity, and Cognition in Patients With Dementia and Small Vessel Disease

Ottoy J, Ozzoude M, Zukotynski K, Kang MS, Adamo S, Scott C, Ramirez J, Swardfager W, Lam B, Bhan A, et al. Amyloid-PET of the White Matter: Relationship to Free Water, Fiber Integrity, and Cognition in Patients With Dementia and Small Vessel Disease. J Cereb Blood Flow Metab. 2023 :271678X231152001.Abstract
White matter (WM) injury is frequently observed along with dementia. Positron emission tomography with amyloid-ligands (Aβ-PET) recently gained interest for detecting WM injury. Yet, little is understood about the origin of the altered Aβ-PET signal in WM regions. Here, we investigated the relative contributions of diffusion MRI-based microstructural alterations, including free water and tissue-specific properties, to Aβ-PET in WM and to cognition. We included a unique cohort of 115 participants covering the spectrum of low-to-severe white matter hyperintensity (WMH) burden and cognitively normal to dementia. We applied a bi-tensor diffusion-MRI model that differentiates between (i) the extracellular WM compartment (represented via free water), and (ii) the fiber-specific compartment (via free water-adjusted fractional anisotropy [FA]). We observed that, in regions of WMH, a decrease in Aβ-PET related most closely to higher free water and higher WMH volume. In contrast, in normal-appearing WM, an increase in Aβ-PET related more closely to higher cortical Aβ (together with lower free water-adjusted FA). In relation to cognitive impairment, we observed a closer relationship with higher free water than with either free water-adjusted FA or WM PET. Our findings support free water and Aβ-PET as markers of WM abnormalities in patients with mixed dementia, and contribute to a better understanding of processes giving rise to the WM PET signal.
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Superficial White Matter Analysis: An Efficient Point-Cloud-Based Deep Learning Framework With Supervised Contrastive Learning for Consistent Tractography Parcellation Across Populations and dMRI Acquisitions

Xue T, Zhang F, Zhang C, Chen Y, Song Y, Golby AJ, Makris N, Rathi Y, Cai W, O'Donnell LJ. Superficial White Matter Analysis: An Efficient Point-Cloud-Based Deep Learning Framework With Supervised Contrastive Learning for Consistent Tractography Parcellation Across Populations and dMRI Acquisitions. Med Image Anal. 2023;85 :102759.Abstract
Diffusion MRI tractography is an advanced imaging technique that enables in vivo mapping of the brain's white matter connections. White matter parcellation classifies tractography streamlines into clusters or anatomically meaningful tracts. It enables quantification and visualization of whole-brain tractography. Currently, most parcellation methods focus on the deep white matter (DWM), whereas fewer methods address the superficial white matter (SWM) due to its complexity. We propose a novel two-stage deep-learning-based framework, Superficial White Matter Analysis (SupWMA), that performs an efficient and consistent parcellation of 198 SWM clusters from whole-brain tractography. A point-cloud-based network is adapted to our SWM parcellation task, and supervised contrastive learning enables more discriminative representations between plausible streamlines and outliers for SWM. We train our model on a large-scale tractography dataset including streamline samples from labeled long- and medium-range (over 40 mm) SWM clusters and anatomically implausible streamline samples, and we perform testing on six independently acquired datasets of different ages and health conditions (including neonates and patients with space-occupying brain tumors). Compared to several state-of-the-art methods, SupWMA obtains highly consistent and accurate SWM parcellation results on all datasets, showing good generalization across the lifespan in health and disease. In addition, the computational speed of SupWMA is much faster than other methods.
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A Comparison of Manual and Automated Neural Architecture Search for White Matter Tract Segmentation

Tchetchenian A, Zhu Y, Zhang F, O'Donnell LJ, Song Y, Meijering E. A Comparison of Manual and Automated Neural Architecture Search for White Matter Tract Segmentation. Sci Rep. 2023;13 (1) :1617.Abstract
Segmentation of white matter tracts in diffusion magnetic resonance images is an important first step in many imaging studies of the brain in health and disease. Similar to medical image segmentation in general, a popular approach to white matter tract segmentation is to use U-Net based artificial neural network architectures. Despite many suggested improvements to the U-Net architecture in recent years, there is a lack of systematic comparison of architectural variants for white matter tract segmentation. In this paper, we evaluate multiple U-Net based architectures specifically for this purpose. We compare the results of these networks to those achieved by our own various architecture changes, as well as to new U-Net architectures designed automatically via neural architecture search (NAS). To the best of our knowledge, this is the first study to systematically compare multiple U-Net based architectures for white matter tract segmentation, and the first to use NAS. We find that the recently proposed medical imaging segmentation network UNet3+ slightly outperforms the current state of the art for white matter tract segmentation, and achieves a notably better mean Dice score for segmentation of the fornix (+ 0.01 and + 0.006 mean Dice increase for left and right fornix respectively), a tract that the current state of the art model struggles to segment. UNet3+ also outperforms the current state of the art when little training data is available. Additionally, manual architecture search found that a minor segmentation improvement is observed when an additional, deeper layer is added to the U-shape of UNet3+. However, all networks, including those designed via NAS, achieve similar results, suggesting that there may be benefit in exploring networks that deviate from the general U-Net paradigm.
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Coaching to Bedside Shift Report and Its Correlation to Hospital Consumer Assessment of Healthcare Providers and Systems and Value-Based Purchasing Dimension Scores: A Multihospital Implementation Study

O'Donnell L, George E, Donnelly J, Bilderback A, Buchanan D. Coaching to Bedside Shift Report and Its Correlation to Hospital Consumer Assessment of Healthcare Providers and Systems and Value-Based Purchasing Dimension Scores: A Multihospital Implementation Study. J Nurs Adm. 2023;53 (1) :12-18.Abstract
OBJECTIVE: The objective of this multihospital study was to investigate how the intervention of coaching to bedside shift report (BSR) correlates with Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) outcomes and relates to Centers for Medicare and Medicaid Services (CMS) Hospital Value-Based Purchasing (VBP) Program points over a 4-year period (2017-2020) for an acute care hospital health system. BACKGROUND: Hospital leaders' responsibilities include intertwined areas of patient experience and fiscal accountability. Coaching to BSR is reported to have numerous benefits to the patient's experience. Published studies completed with hospital systems evaluating the intervention of coaching to BSR and how it correlated to patient experience and VBP are limited. METHODS: Coaching to BSR was implemented at 16 adult acute care hospitals. Patient-reported BSR rates were collected in tandem with HCAHPS for 4 years. Statistical correlations were assessed between patient-reported BSR and HCAHPS and consequential effect on VBP dimension scores. RESULTS: Coaching to BSR had a significant impact on top- and bottom-box "rate the hospital" HCAHPS scores at a system and hospital level. Value-based purchasing points and percentages increased over 2017-2020, potentially leading to lower CMS penalty claims over the period the BSR was implemented. CONCLUSIONS: Coaching is a key factor when creating a favorable patient experience. The implementation and sustainability of coaching to BSR may result in improved patient experience ratings and increase VBP point accumulation to hospital systems.
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White Matter Microstructure Is Associated with Serum Neuroactive Steroids and Psychological Functioning

Umminger LF, Rojczyk P, Seitz-Holland J, Sollmann N, Kaufmann E, Kinzel P, Zhang F, Kochsiek J, Langhein M, Kim CL, et al. White Matter Microstructure Is Associated with Serum Neuroactive Steroids and Psychological Functioning. J Neurotrauma. 2023.Abstract
Military service members are at increased risk for mental health issues, and comorbidity with mild traumatic brain injury (mTBI) is common. Largely overlapping symptoms between conditions suggest a shared pathophysiology. The present work investigates the associations among white matter microstructure, psychological functioning, and serum neuroactive steroids that are part of the stress-response system. Diffusion-weighted brain imaging was acquired from 163 participants (with and without military affiliation) and free-water-corrected fractional anisotropy (FAT) was extracted. Associations between serum neurosteroid levels of allopregnanolone (ALLO) and pregnenolone (PREGNE), psychological functioning, and whole-brain white matter microstructure were assessed using regression models. Moderation models tested the effect of mTBI and comorbid post-traumatic stress disorder (PTSD) and mTBI on these associations. ALLO is associated with whole-brain white matter FAT (β = 0.24, t = 3.05, p = 0.006). This association is significantly modulated by PTSD+mTBI comorbidity (β = 0.00, t = 2.50, p = 0.027), although an mTBI diagnosis alone did not significantly impact this association (p = 0.088). There was no significant association between PREGNE and FAT (p = 0.380). Importantly, lower FAT is associated with poor psychological functioning (β = -0.19, t = -2.35, p = 0.020). This study provides novel insight into a potential common pathophysiological mechanism of neurosteroid dysregulation underlying the high risk for mental health issues in military service members. Further, comorbidity of PTSD and mTBI may bring the compensatory effects of the brain's stress response to their limit. Future research is needed to investigate whether neurosteroid regulation may be a promising tool for restoring brain health and improving psychological functioning.
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