Histological-MRI correlation in the primary motor cortex of patients with amyotrophic lateral sclerosis.

PURPOSE: To establish the relationship between ALS histopathology and quantitative MRI metrics. MATERIALS AND METHODS: ALS patients (N = 8) in advanced stages of the disease were enrolled and, immediately after death, the brain of each patient was removed. Freshly excised ALS tissue was imaged at 3.0 Tesla with T1 and T2 mapping protocols and subsequently stained with astrocyte, myelin, and neuronal markers. Measures of ALS histological stains were compared with the internal control (primary visual cortex) and longitudinal parametric maps. RESULTS: Post-mortem T1 -weighted images demonstrate diminished contrast between gray and white matter and alterations in T1 relaxation within the primary motor cortex. An increase in astrocyte number and reactivity as well as evident neuronal loss, a decrease in axonal density, and unraveling of the myelin sheaths in subcortical white matter were found in the ALS primary motor cortex exhibiting significant T1 relaxation and contrast changes. CONCLUSION: This study provides a histopathological basis for differences in MR T1 contrast and relaxation seen in the ALS brain.

Biochemical correlates of neuropsychiatric illness in maple syrup urine disease.

Maple syrup urine disease (MSUD) is an inherited disorder of branched chain amino acid metabolism presenting with neonatal encephalopathy, episodic metabolic decompensation, and chronic amino acid imbalances. Dietary management enables survival and reduces risk of acute crises. Liver transplantation has emerged as an effective way to eliminate acute decompensation risk. Psychiatric illness is a reported MSUD complication, but has not been well characterized and remains poorly understood. We report the prevalence and characteristics of neuropsychiatric problems among 37 classical MSUD patients (ages 5-35 years, 26 on dietary therapy, 11 after liver transplantation) and explore their underlying mechanisms. Compared with 26 age-matched controls, MSUD patients were at higher risk for disorders of cognition, attention, and mood. Using quantitative proton magnetic resonance spectroscopy, we found lower brain glutamate, N-acetylaspartate (NAA), and creatine concentrations in MSUD patients, which correlated with specific neuropsychiatric outcomes. Asymptomatic neonatal course and stringent longitudinal biochemical control proved fundamental to optimizing long-term mental health. Neuropsychiatric morbidity and neurochemistry were similar among transplanted and nontransplanted MSUD patients. In conclusion, amino acid dysregulation results in aberrant neural networks with neurochemical deficiencies that persist after transplant and correlate with neuropsychiatric morbidities. These findings may provide insight into general mechanisms of psychiatric illness.

An MRI-derived definition of MCI-to-AD conversion for long-term, automatic prognosis of MCI patients.

Alzheimer's disease (AD) and mild cognitive impairment (MCI) are of great current research interest. While there is no consensus on whether MCIs actually "convert" to AD, this concept is widely applied. Thus, the more important question is not whether MCIs convert, but what is the best such definition. We focus on automatic prognostication, nominally using only a baseline brain image, of whether an MCI will convert within a multi-year period following the initial clinical visit. This is not a traditional supervised learning problem since, in ADNI, there are no definitive labeled conversion examples. It is not unsupervised, either, since there are (labeled) ADs and Controls, as well as cognitive scores for MCIs. Prior works have defined MCI subclasses based on whether or not clinical scores significantly change from baseline. There are concerns with these definitions, however, since, e.g., most MCIs (and ADs) do not change from a baseline CDR = 0.5 at any subsequent visit in ADNI, even while physiological changes may be occurring. These works ignore rich phenotypical information in an MCI patient's brain scan and labeled AD and Control examples, in defining conversion. We propose an innovative definition, wherein an MCI is a converter if any of the patient's brain scans are classified "AD" by a Control-AD classifier. This definition bootstraps design of a second classifier, specifically trained to predict whether or not MCIs will convert. We thus predict whether an AD-Control classifier will predict that a patient has AD. Our results demonstrate that this definition leads not only to much higher prognostic accuracy than by-CDR conversion, but also to subpopulations more consistent with known AD biomarkers (including CSF markers). We also identify key prognostic brain region biomarkers.

Faraday shields within a solenoidal coil to reduce sample heating: numerical comparison of designs and experimental verification.

A comparison of methods to decrease RF power dissipation and related heating in conductive samples using passive conductors surrounding a sample in a solenoid coil is presented. Full-Maxwell finite difference time domain numerical calculations were performed to evaluate the effect of the passive conductors by calculating conservative and magnetically-induced electric field and magnetic field distributions. To validate the simulation method, experimental measurements of temperature increase were conducted using a solenoidal coil (diameter 3 mm), a saline sample (10 mM NaCl) and passive copper shielding wires (50 microm diameter). The temperature increase was 58% lower with the copper wires present for several different input powers to the coil. This was in good agreement with simulation for the same geometry, which indicated 57% lower power dissipated in the sample with conductors present. Simulations indicate that some designs should be capable of reducing temperature increase by more than 85%.

STAMPS: Software Tool for Automated MRI Post-processing on a supercomputer.

This paper describes a Software Tool for Automated MRI Post-processing (STAMP) of multiple types of brain MRIs on a workstation and for parallel processing on a supercomputer (STAMPS). This software tool enables the automation of nonlinear registration for a large image set and for multiple MR image types. The tool uses standard brain MRI post-processing tools (such as SPM, FSL, and HAMMER) for multiple MR image types in a pipeline fashion. It also contains novel MRI post-processing features. The STAMP image outputs can be used to perform brain analysis using Statistical Parametric Mapping (SPM) or single-/multi-image modality brain analysis using Support Vector Machines (SVMs). Since STAMPS is PBS-based, the supercomputer may be a multi-node computer cluster or one of the latest multi-core computers.