high-resolution-vivo-manual-segmentation-protocol-for-human

High-resolution <em>In Vivo</em> Manual Segmentation Protocol for Human Hippocampal Subfields Using 3T Magnetic Resonance Imaging

The human hippocampus has been broadly studied in the context of memory and normal brain function and its role in different neuropsychiatric disorders has ...

Centre For Addiction And Mental Health

University of Toronto

This paper describes phase maps. A review of the phase unwrapping problem is given. Different structures, in particular fringelines, cutlines, and poles, contained within a phase map are described and their origin and behavior investigated. The problem of phase unwrapping can then be addressed with a better understanding of the source of poles or inconsistencies. This understanding, along with some assumptions about what is being encoded in the phase of a magnetic resonance image, are used to derive a new method for phase unwrapping which relies only on the phase map. The method detects cutlines and distinguishes between noise-induced poles and signal undersampling poles based on the length of the fringelines. The method was shown to be robust to noise and successful in unwrapping challenging clinical cases.

Understanding phase maps in MRI: a new cutline phase unwrapping method.

Mammographic density is a heritable quantitative trait and is a strong risk factor for breast cancer in middle-aged and older women. However, little is known about the development of mammographic density in early life. We used MRI to measure the water content of the breast, which provides a measurement of the fibro-glandular content of breast tissue with similar accuracy to mammography, but without the attendant exposure to radiation.

Breast-tissue composition and other risk factors for breast cancer in young women: a cross-sectional study.

A novel three-dimensional simultaneous B(1) and T(1) mapping method is introduced: the method of slopes (MoS). The linearity of the spoiled gradient recalled echo (SPGR) signal vs flip angle relation is exploited: B(1) mapping is achieved by a two-point extrapolation to signal null with a correction scheme while T(1) mapping uses the slopes of the SPGR signal vs flip angle curves near the origin and near the signal null. This new method improves upon the existing variable flip angle (VFA) T(1)-mapping method in that (i) consistency between B(1) and T(1) maps is ensured (ii) the sampling scheme is T(1)-independent (iii) the noise bias and singularity, associated with using a linear form for the SPGR signal equation, is eliminated by using the full equation. The method is shown to yield accurate and robust results via simulations. Initial estimates of B(1) and T(1) values are obtained from three data points via simple computations and straight line approximations. Initial estimates of B(1) values, for a range of values, are shown to be accurate due to the proposed B(1) correction scheme. The accuracy and robustness of T(1) values is achieved via a non-linear fitting algorithm which includes a fourth data point sampled at high SNR. The MoS was validated by comparing resulting B(1) and T(1) maps with those obtained using other standard methods. Finally, the ability to obtain brain B(1) and T(1) maps using the MoS was demonstrated by in vivo experiments. The MoS is expected to perform well on other motion-free anatomical regions as well.

A novel method for simultaneous 3D B(1) and T(1) mapping: the method of slopes (MoS).

Endocannabinoid tone has recently been implicated in a number of prevalent neuropsychiatric conditions. [(11)C]CURB is the first available positron emission tomography (PET) radiotracer for imaging fatty acid amide hydrolase (FAAH), the enzyme which metabolizes the prominent endocannabinoid anandamide. Here, we sought to determine the most suitable kinetic modeling approach for quantifying [(11)C]CURB that binds selectively to FAAH. Six healthy volunteers were scanned with arterial blood sampling for 90 minutes. Kinetic parameters were estimated regionally using a one-tissue compartment model (TCM), a 2-TCM with and without irreversible trapping, and an irreversible 3-TCM. The 2-TCM with irreversible trapping provided the best identifiability of PET outcome measures among the approaches studied (coefficient of variation (COV) of the net influx constant K(i) and the composite parameter λk(3) (λ=K(1)/k(2)) <5%, and COV(k(3))<10%). Reducing scan time to 60 minutes did not compromise the identifiability of rate constants. Arterial spin labeling measures of regional cerebral blood flow were only slightly correlated with K(i), but not with k(3) or λk(3). Our data suggest that λk(3) is sensitive to changes in FAAH activity, therefore, optimal for PET quantification of FAAH activities with [(11)C]CURB. Simulations showed that [(11)C]CURB binding in healthy subjects is far from a flow-limited uptake.

Mapping human brain fatty acid amide hydrolase activity with PET.

The hippocampus is a neuroanatomical structure that has been widely studied in the context of learning, memory, stress, and neurodegeneration. Neuroanatomically, the hippocampus is subdivided into several subfields with intricate morphologies and complex three-dimensional relationships. Recent studies have demonstrated that the identification of different subfields is possible with high-resolution and -contrast image volumes acquired using ex vivo specimens in a small bore 9.4 T scanner and, more recently, in vivo, at 7 T. In these studies, the neuroanatomical definitions of boundaries between subfields are based upon salient differences in image contrast. Typically, the definition of subfields has not been possible using commonly available magnetic resonance (MR) scanners (i.e.: 1.5 or 3T) due to resolution and contrast limitations. To overcome the limited availability of post-mortem specimens and expertise in state-of-the-art high-field imaging, we propose a coupling of MR acquisition and detailed segmentation techniques that allow for the reliable identification of hippocampal anatomy (including subfields). High-resolution and -contrast T1- and T2-weighted image volumes were acquired from 5 volunteers (2 male; 3 female; age range: 29-57, avg. 37) using a clinical research-grade 3T scanner and have final super-sampled isotropic voxel dimensions of 0.3mm. We demonstrate that by using these acquisition techniques, our data results in contrast-to-noise ratios that compare well with high-resolution images acquired with long scan times using post-mortem data at higher field strengths. For the subfields, the cornus ammonis (CA) 1, CA2/CA3, CA4/dentate gyrus, stratum radiatum/stratum lacunosum/stratum moleculare, and subiculum were all labeled as separate structures. Hippocampal volumes are reported for each of the substructures and the hippocampus as a whole (range for hippocampus: 2456.72-3325.02 mm(3)). Intra-rater reliability of our manual segmentation protocol demonstrates high reliability for the whole hippocampus (mean Dice Kappa of 0.91; range 0.90-0.92) and for each of the subfields (range of Dice Kappas: 0.64-0.83). We demonstrate that our reliability is better than the Dice Kappas produced by simulating the following errors: a translation by a single voxel in all cardinal directions and 1% volumetric shrinkage and expansion. The completed hippocampal atlases are available freely online (info2.camh.net/kf-tigr/index.php/Hippocampus) and can be coupled with novel computational neuroanatomy techniques that will allow for them to be customized to the unique neuroanatomy of different subjects, and ultimately be utilized in different analysis pipelines.

A novel in vivo atlas of human hippocampal subfields using high-resolution 3 T magnetic resonance imaging.

The cerebellum has classically been linked to motor learning and coordination. However, there is renewed interest in the role of the cerebellum in non-motor functions such as cognition and in the context of different neuropsychiatric disorders. The contribution of neuroimaging studies to advancing understanding of cerebellar structure and function has been limited, partly due to the cerebellum being understudied as a result of contrast and resolution limitations of standard structural magnetic resonance images (MRI). These limitations inhibit proper visualization of the highly compact and detailed cerebellar foliations. In addition, there is a lack of robust algorithms that automatically and reliably identify the cerebellum and its subregions, further complicating the design of large-scale studies of the cerebellum. As such, automated segmentation of the cerebellar lobules would allow detailed population studies of the cerebellum and its subregions. In this manuscript, we describe a novel set of high-resolution in vivo atlases of the cerebellum developed by pairing MR imaging with a carefully validated manual segmentation protocol. Using these cerebellar atlases as inputs, we validate a novel automated segmentation algorithm that takes advantage of the neuroanatomical variability that exists in a given population under study in order to automatically identify the cerebellum, and its lobules. Our automatic segmentation results demonstrate good accuracy in the identification of all lobules (mean Kappa [κ]=0.731; range 0.40-0.89), and the entire cerebellum (mean κ=0.925; range 0.90-0.94) when compared to "gold-standard" manual segmentations. These results compare favorably in comparison to other publically available methods for automatic segmentation of the cerebellum. The completed cerebellar atlases are available freely online (http://imaging-genetics.camh.ca/cerebellum) and can be customized to the unique neuroanatomy of different subjects using the proposed segmentation pipeline (https://github.com/pipitone/MAGeTbrain).

Derivation of high-resolution MRI atlases of the human cerebellum at 3T and segmentation using multiple automatically generated templates.

To compare the total breast fat content computed from two separate studies, performed on different scanners and with different protocols, with the goal of defining a relationship to allow pooling the data.

Comparing average breast fat content results from two different protocols at 1.5T and 3T: can the data be pooled?

Glial disturbances are highly implicated in the pathophysiology of schizophrenia and may be linked with glutamatergic dysregulation. Myo-inositol (mI), a putative marker of glial cells, and choline (Cho), representative of membrane turnover, are both present in larger concentrations within glial cells than in neurons, and their elevation is often interpreted to reflect glial activation. Proton magnetic resonance spectroscopy ((1)H-MRS) allows for the evaluation of mI, Cho, glutamate, glutamate + glutamine (Glx), and N-acetylaspartate (NAA). A collective investigation of these measures in antipsychotic-naive patients experiencing their first nonaffective episode of psychosis (FEP) can improve the understanding of glial dysfunction and its implications in the early stages of schizophrenia. 3-Tesla (1)H-MRS (echo time = 35ms) was performed in 60 antipsychotic-naive patients with FEP and 60 age- and sex-matched healthy controls. mI, Cho, glutamate, Glx, and NAA were estimated using LCModel and corrected for cerebrospinal fluid composition within the voxel. mI, Cho, and glutamate were elevated in the FEP group. After correction for multiple comparisons, mI positively correlated with grandiosity. The relationships between mI and glutamate, and Cho and glutamate, were more positive in the FEP group. These findings are suggestive of glial activation in the absence of neuronal loss and may thereby provide support for the presence of a neuroinflammatory process within the early stages of schizophrenia. Dysregulation of glial function might result in the disruption of glutamatergic neurotransmission, which may influence positive symptomatology in patients with FEP.

Elevated Myo-Inositol, Choline, and Glutamate Levels in the Associative Striatum of Antipsychotic-Naive Patients With First-Episode Psychosis: A Proton Magnetic Resonance Spectroscopy Study With Implications for Glial Dysfunction.

Chavez Sofia

MRI Unit,
Research Imaging Centre,
Campbell Family Mental Health Research Institute,
MRI Unit, Research Imaging Centre, Campbell Family Mental Health Research Institute

Centre For Addiction And Mental Health

High-resolution In Vivo Manual Segmentation Protocol for Human Hippocampal Subfields Using 3T Magnetic Resonance Imaging

Chavez Sofia

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}MRI Unit,Research Imaging Centre,Campbell Family Mental Health Research Institute,MRI Unit, Research Imaging Centre, Campbell Family Mental Health Research Institute

Centre For Addiction And Mental Health

High-resolution In Vivo Manual Segmentation Protocol for Human Hippocampal Subfields Using 3T Magnetic Resonance Imaging

MRI Unit,
Research Imaging Centre,
Campbell Family Mental Health Research Institute,
MRI Unit, Research Imaging Centre, Campbell Family Mental Health Research Institute