Reducing CSF partial volume effects to enhance diffusion tensor imaging metrics of brain microstructure

Technological advances over recent decades now allow for in vivo observation of human brain tissue through the use of neuroimaging methods. While this field originated with techniques capable of capturing macrostructural details of brain anatomy, modern methods such as diffusion tensor imaging (DTI) that are now regularly implemented in research protocols have the ability to characterize brain microstructure. DTI has been used to reveal subtle micro-anatomical abnormalities in the prodromal phase ofº various diseases and also to delineate “normal” age-related changes in brain tissue across the lifespan. Nevertheless, imaging artifact in DTI remains a significant limitation for identifying true neural signatures of disease and brain-behavior relationships. Cerebrospinal fluid (CSF) contamination of brain voxels is a main source of error on DTI scans that causes partial volume effects and reduces the accuracy of tissue characterization. Several methods have been proposed to correct for CSF artifact though many of these methods introduce new limitations that may preclude certain applications. The purpose of this review is to discuss the complexity of signal acquisition as it relates to CSF artifact on DTI scans and review methods of CSF suppression in DTI. We will then discuss a technique that has been recently shown to effectively suppress the CSF signal in DTI data, resulting in fewer errors and improved measurement of brain tissue. This approach and related techniques have the potential to significantly improve our understanding of “normal” brain aging and neuropsychiatric and neurodegenerative diseases. Considerations for next-level applications are discussed

Consensus-based technical recommendations for clinical translation of renal ASL MRI

OBJECTIVES: This study aimed at developing technical recommendations for the acquisition, processing and analysis of renal ASL data in the human kidney at 1.5 T and 3 T field strengths that can promote standardization of renal perfusion measurements and facilitate the comparability of results across scanners and in multi-centre clinical studies. METHODS: An international panel of 23 renal ASL experts followed a modified Delphi process, including on-line surveys and two in-person meetings, to formulate a series of consensus statements regarding patient preparation, hardware, acquisition protocol, analysis steps and data reporting. RESULTS: Fifty-nine statements achieved consensus, while agreement could not be reached on two statements related to patient preparation. As a default protocol, the panel recommends pseudo-continuous (PCASL) or flow-sensitive alternating inversion recovery (FAIR) labelling with a single-slice spin-echo EPI readout with background suppression and a simple but robust quantification model. DISCUSSION: This approach is considered robust and reproducible and can provide renal perfusion images of adequate quality and SNR for most applications. If extended kidney coverage is desirable, a 2D multislice readout is recommended. These recommendations are based on current available evidence and expert opinion. Nonetheless they are expected to be updated as more data become available, since the renal ASL literature is rapidly expanding

Consensus-based technical recommendations for clinical translation of renal ASL MRI

Objectives: To develop technical recommendations for the acquisition, processing and analysis of renal ASL data in the human kidney at 1.5T and 3T field strengths that can promote standardization of renal perfusion measurements and facilitate the comparability of results across scanners and in multi-center clinical studies.Methods: An international panel of 23 renal ASL experts followed a modified Delphi process, including on-line surveys and two in-person meetings, to formulate a series of consensus statements regarding patient preparation, hardware, acquisition protocol, analysis steps and data reporting.Results: Fifty-nine statements achieved consensus, while agreement could not be reached on two statements related to patient preparation. As a default protocol, the panel recommends pseudo-continuous (PCASL) or flow-sensitive alternating inversion recovery (FAIR) labeling with a single-slice spin-echo EPI readout with background suppression, and a simple but robust quantification model.Discussion: This approach is considered robust and reproducible and can provide renal perfusion images of adequate quality and SNR for most applications. If extended kidney coverage is desirable, a 2D multislice readout is recommended. These recommendations are based on current available evidence and expert opinion. Nonetheless they are expected to be updated as more data becomes available, since the renal ASL literature is rapidly expanding

Techniques for Analysis and Motion Correction of Arterial Spin Labelling (ASL) Data from Dementia Group Studies

This investigation examines how Arterial Spin Labelling (ASL) Magnetic Resonance Imaging can be optimised to assist in the early diagnosis of diseases which cause dementia, by considering group study analysis and control of motion artefacts. ASL can produce quantitative cerebral blood flow maps noninvasively - without a radioactive or paramagnetic contrast agent being injected. ASL studies have already shown perfusion changes which correlate with the metabolic changes measured by Positron Emission Tomography in the early stages of dementia, before structural changes are evident. But the clinical use of ASL for dementia diagnosis is not yet widespread, due to a combination of a lack of protocol consistency, lack of accepted biomarkers, and sensitivity to motion artefacts. Applying ASL to improve early diagnosis of dementia may allow emerging treatments to be administered earlier, thus with greater effect. In this project, ASL data acquired from two separate patient cohorts ( (i) Young Onset Alzheimer’s Disease (YOAD) study, acquired at Queen Square; and (ii) Incidence and RISk of dementia (IRIS) study, acquired in Rotterdam) were analysed using a pipeline optimised for each acquisition protocol, with several statistical approaches considered including support-vector machine learning. Machine learning was also applied to improve the compatibility of the two studies, and to demonstrate a novel method to disentangle perfusion changes measured by ASL from grey matter atrophy. Also in this project, retrospective motion correction techniques for specific ASL sequences were developed, based on autofocusing and exploiting parallel imaging algorithms. These were tested using a specially developed simulation of the 3D GRASE ASL protocol, which is capable of modelling motion. The parallel imaging based approach was verified by performing a specifically designed MRI experiment involving deliberate motion, then applying the algorithm to demonstrably reduce motion artefacts retrospectively

Reducing CSF Partial Volume Effects to Enhance Diffusion Tensor Imaging Metrics of Brain Microstructure

Technological advances over recent decades now allow for in vivo observation of human brain tissue through the use of neuroimaging methods. While this field originated with techniques capable of capturing macrostructural details of brain anatomy, modern methods such as diffusion tensor imaging (DTI) that are now regularly implemented in research protocols have the ability to characterize brain microstructure. DTI has been used to reveal subtle micro-anatomical abnormalities in the prodromal phase ofº various diseases and also to delineate “normal” age-related changes in brain tissue across the lifespan. Nevertheless, imaging artifact in DTI remains a significant limitation for identifying true neural signatures of disease and brain-behavior relationships. Cerebrospinal fluid (CSF) contamination of brain voxels is a main source of error on DTI scans that causes partial volume effects and reduces the accuracy of tissue characterization. Several methods have been proposed to correct for CSF artifact though many of these methods introduce new limitations that may preclude certain applications. The purpose of this review is to discuss the complexity of signal acquisition as it relates to CSF artifact on DTI scans and review methods of CSF suppression in DTI. We will then discuss a technique that has been recently shown to effectively suppress the CSF signal in DTI data, resulting in fewer errors and improved measurement of brain tissue. This approach and related techniques have the potential to significantly improve our understanding of “normal” brain aging and neuropsychiatric and neurodegenerative diseases. Considerations for next-level applications are discussed

Acquisition and Reconstruction Techniques for Fat Quantification Using Magnetic Resonance Imaging

Quantifying the tissue fat concentration is important for several diseases in various organs including liver, heart, skeletal muscle and kidney. Uniquely, MRI can separate the signal from water and fat in-vivo, rendering it the most suitable imaging modality for non-invasive fat quantification. Chemical-shift-encoded MRI is commonly used for quantitative fat measurement due to its unique ability to generate a separate image for water and fat. The tissue fat concentration can be consequently estimated from the two images. However, several confounding factors can hinder the water/fat separation process, leading to incorrect estimation of fat concentration. The inhomogeneities of the main magnetic field represent the main obstacle to water/fat separation. Most existing techniques rely mainly on imposing spatial smoothness constraints to address this problem; however, these often fail to resolve large and abrupt variations in the magnetic field. A novel convex relaxation approach to water/fat separation is proposed. The technique is compared to existing methods, demonstrating its robustness to resolve abrupt magnetic field inhomogeneities. Water/fat separation requires the acquisition of multiple images with different echo-times, which prolongs the acquisition time. Bipolar acquisitions can efficiently acquire the required data in shorter time. However, they induce phase errors that significantly distort the fat measurements. A new bipolar acquisition strategy that overcomes the phase errors and provides accurate fat measurements is proposed. The technique is compared to the current clinical sequence, demonstrating its efficiency in phantoms and in-vivo experiments. The proposed acquisition technique is also applied on animal models to achieve higher spatial resolution than the current sequence. In conclusion, this dissertation describes a complete framework for accurate and precise MRI fat quantification. Novel acquisitions and reconstruction techniques that address the current challenges for fat quantification are proposed

Childhood Trauma And Emotion Processing Neurocircuitry

Childhood trauma is one of the strongest risk factors for a range of common and debilitating neuropsychiatric disorders, including anxiety, depression, and posttraumatic stress disorder (PTSD). These emotion-related disorders have their roots in childhood and adolescence, underscoring a critical need to understand their biological bases in early life. In this dissertation, we evaluate how childhood trauma impacts emotion processing neurocircuitry in a sample of high-risk urban youth, ages 7-15. In four inter-related studies, we test neural function and functional connectivity of core emotion processing regions, including the amygdala, insula, and pregenual/subgenual anterior cingulate cortex (pgACC/sgACC). To examine the relevance of observed neurological changes, we evaluate behavioral performance on emotion processing neuropsychological tasks, as well as specific dimensions of subjective affective experience. Results indicate that, relative to matched comparison youth, trauma-exposed youth have (1) increased neural response to salient emotional cues in amygdala and insula, (2) reduced functional connectivity between amygdala and pgACC/sgACC, a pathway critical for emotion regulation, and (3) altered within- and between-network connectivity of the salience network, involved in detecting and orienting attention to salient emotional stimuli. These neurological changes are accompanied by behavioral alterations: trauma-exposed youth have a lower ability to ignore distracting emotional information, and to automatically regulate emotion. Additionally, observed neurobehavioral changes relate to a specific dimension of affective experience – reward sensitivity (RS), rather than negative affect. Moreover, trauma-exposed youth with the greatest neurobehavioral impairment report lower RS, suggesting reduced positive environmental engagement. These results suggest that RS may be a marker of stress susceptibility, a notion supported by emerging basic and clinical research. Based on our neurobehavioral findings, we discuss potential implications for intervention, and relay an emerging framework that dissociates neurological effects of different trauma types (i.e., threat/victimization vs. deprivation/neglect). In closing, we discuss future directions, including longitudinal research and evaluating the modulation of learned fear – a neurobehavioral mechanism that depends on emotion processing neurocircuitry, but has yet to be tested in trauma-exposed youth