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Quantitative Magnetic Resonance Imag...

Bae, Jonghyun.

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Quantitative Magnetic Resonance Imaging of Blood-Brain Barrier Permeability.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Quantitative Magnetic Resonance Imaging of Blood-Brain Barrier Permeability./
Author:	Bae, Jonghyun.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2023,
Description:	211 p.
Notes:	Source: Dissertations Abstracts International, Volume: 85-04, Section: B.
Contained By:	Dissertations Abstracts International85-04B.
Subject:	Medical imaging. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30312280
ISBN:	9798380618816

Quantitative Magnetic Resonance Imaging of Blood-Brain Barrier Permeability.
Bae, Jonghyun.

Quantitative Magnetic Resonance Imaging of Blood-Brain Barrier Permeability. - Ann Arbor : ProQuest Dissertations & Theses, 2023 - 211 p.

Source: Dissertations Abstracts International, Volume: 85-04, Section: B.

Thesis (Ph.D.)--New York University, 2023.

The Blood-Brain Barrier (BBB) is a cellular barrier lining the brain capillaries, which protects the brain parenchyma by halting the entry of neurotoxins. Recent studies have shown that increased BBB permeability is associated with aging and the progression of Alzheimer's disease (AD). Among non-invasive methodologies, Dynamic Contrast-Enhanced MRI (DCE-MRI) is a non-invasive imaging approach recognized for its capacity of quantitatively assessing BBB disruption. Through acquiring T1-weighted images during and after injecting a contrast agent intravenously, DCE-MRI enables the measurement of BBB permeability to Gadolinium-based contrast agent. However, previous DCE-MRI studies of BBB permeability faced several challenges, such as long scan times and inconsistent intra- and inter-study permeability measures, thereby limiting its potential as a biomarker for AD.In this dissertation, we address these challenges to improve the measurement of subtle BBB permeability changes. First, we propose a novel pharmacokinetic model that accurately measures BBB permeability while reducing scan time. Our results demonstrate that the conventional Patlak model tends to overestimate permeability measures when the scan time is reduced from 30 min to 10 min. In contrast, our proposed model with vascular transport design yields accurate measurements with a reduced scan time.To reduce the variability in permeability measures arising from the selection of the input function, we develop a deep learning approach to automatically predict a local capillary-level input function (CIF). The feasibility of CIF is demonstrated using our breast cancer dataset,{A0}where kinetic parameters estimated with network-predicted CIF show similar diagnostic performance to that obtained from the conventional approach.In our animal experiments, we first examine the sensitivity of our measurements by systematically inducing different levels of subtle BBB disruption using focused ultrasound with varying acoustic power. The results suggest that our imaging method is capable of detecting subtle differences in BBB disruption. Subsequently, we investigate BBB permeability changes in AD pathology using a transgenic mouse model of AD. The results indicate that BBB disruption occurs in AD transgenic mice at an early age and worsens with aging.Finally, recognizing the importance of image reconstruction, we develop a digital reference object (DRO) that provides a wide variety of ground-truth data to assess image reconstruction techniques. The proposed developments in this dissertation contribute to more accurate measurements of subtle BBB permeability changes in aging and AD. Moreover, these advancements serve as a guide for developing future study designs for BBB permeability measurements.

ISBN: 9798380618816Subjects--Topical Terms:

3172799
Medical imaging.
Subjects--Index Terms:

Alzheimer's disease

Quantitative Magnetic Resonance Imaging of Blood-Brain Barrier Permeability.
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520 $a The Blood-Brain Barrier (BBB) is a cellular barrier lining the brain capillaries, which protects the brain parenchyma by halting the entry of neurotoxins. Recent studies have shown that increased BBB permeability is associated with aging and the progression of Alzheimer's disease (AD). Among non-invasive methodologies, Dynamic Contrast-Enhanced MRI (DCE-MRI) is a non-invasive imaging approach recognized for its capacity of quantitatively assessing BBB disruption. Through acquiring T1-weighted images during and after injecting a contrast agent intravenously, DCE-MRI enables the measurement of BBB permeability to Gadolinium-based contrast agent. However, previous DCE-MRI studies of BBB permeability faced several challenges, such as long scan times and inconsistent intra- and inter-study permeability measures, thereby limiting its potential as a biomarker for AD.In this dissertation, we address these challenges to improve the measurement of subtle BBB permeability changes. First, we propose a novel pharmacokinetic model that accurately measures BBB permeability while reducing scan time. Our results demonstrate that the conventional Patlak model tends to overestimate permeability measures when the scan time is reduced from 30 min to 10 min. In contrast, our proposed model with vascular transport design yields accurate measurements with a reduced scan time.To reduce the variability in permeability measures arising from the selection of the input function, we develop a deep learning approach to automatically predict a local capillary-level input function (CIF). The feasibility of CIF is demonstrated using our breast cancer dataset,{A0}where kinetic parameters estimated with network-predicted CIF show similar diagnostic performance to that obtained from the conventional approach.In our animal experiments, we first examine the sensitivity of our measurements by systematically inducing different levels of subtle BBB disruption using focused ultrasound with varying acoustic power. The results suggest that our imaging method is capable of detecting subtle differences in BBB disruption. Subsequently, we investigate BBB permeability changes in AD pathology using a transgenic mouse model of AD. The results indicate that BBB disruption occurs in AD transgenic mice at an early age and worsens with aging.Finally, recognizing the importance of image reconstruction, we develop a digital reference object (DRO) that provides a wide variety of ground-truth data to assess image reconstruction techniques. The proposed developments in this dissertation contribute to more accurate measurements of subtle BBB permeability changes in aging and AD. Moreover, these advancements serve as a guide for developing future study designs for BBB permeability measurements.
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