Simulation of MRI cluster plots and application to neurological segmentation

A data-oriented self-calibration and robust chemical-shift encoding by using clusterization (OSCAR): Theory, optimization and clinical validation in neuromuscular disorders

Multi-echo Chemical Shift-Encoded (CSE) methods for Fat-Water quantification are growing in clinical use due to their ability to estimate and correct some confounding effects. State of the art CSE water/fat separation approaches rely on a multi-peak fat spectrum with peak frequencies and relative amplitudes kept constant over the entire MRI dataset. However, the latter approximation introduces a systematic error in fat percentage quantification in patients where the differences in lipid chemical composition are significant (such as for neuromuscular disorders) because of the spatial dependence of the peak amplitudes. The present work aims to overcome this limitation by taking advantage of an unsupervised clusterization-based approach offering a reliable criterion to carry out a data-driven segmentation of the input MRI dataset into multiple regions. Results established that the presented algorithm is able to identify at least 4 different partitions from MRI dataset under which to perform independent self-calibration routines and was found robust in NMD imaging studies (as evaluated on a cohort of 24 subjects) against latest CSE techniques with either calibrated or non-calibrated approaches. Particularly, the PDFF of the thigh was more reproducible for the quantitative estimation of pathological muscular fat infiltrations, which may be promising to evaluate disease progression in clinical practice.

Clinical utility of magnetic resonance imaging in first-episode psychosis

BackgroundThere is no consensus as to whether magnetic resonance imaging (MRI) should be used as part of the initial clinical evaluation of patients with first-episode psychosis (FEP).Aims(a) To assess the logistical feasibility of routine MRI; (b) to define the clinical significance of radiological abnormalities in patients with FEP.MethodRadiological reports from MRI scans of two FEP samples were reviewed; one comprised 108 patients and 98 healthy controls recruited to a research study and the other comprised 241 patients scanned at initial clinical presentation plus 66 healthy controls.ResultsIn the great majority of patients, MRI was logistically feasible. Radiological abnormalities were reported in 6% of the research sample and in 15% of the clinical sample (odds ratio (OR)=3.1, 95% CI 1.26-7.57, χ²(1) = 6.63, P = 0.01). None of the findings necessitated a change in clinical management.ConclusionsRates of neuroradiological abnormalities in FEP are likely to be underestimated in research samples that often exclude patients with organic abnormalities. However, the majority of findings do not require intervention.

Voxel-based magnetic resonance imaging investigation of poor and preserved clinical insight in people with schizophrenia

AIM

To define regional grey-matter abnormalities in schizophrenia patients with poor insight (Insight^-), relative to patients with preserved clinical insight (Insight⁺), and healthy controls.

METHODS

Forty stable schizophrenia outpatients (20 Insight^- and 20 Insight⁺) and 20 healthy controls underwent whole brain magnetic resonance imaging (MRI). Insight in all patients was assessed using the Birchwood Insight Scale (BIS; a self-report measure). The two patient groups were pre-selected to match on most clinical and demographic parameters but, by design, they had markedly distinct BIS scores. Voxel-based morphometry employed in SPM8 was used to examine group differences in grey matter volumes across the whole brain.

RESULTS

The three participant groups were comparable in age [F(2,57) = 0.34, P = 0.71] and the patient groups did not differ in age at illness onset [t(38) = 0.87, P = 0.39]. Insight^- and Insight⁺ patient groups also did not differ in symptoms on the Positive and Negative Syndromes scale (PANSS): Positive symptoms [t(38) = 0.58, P = 0.57], negative symptoms [t(38) = 0.61, P = 0.55], general psychopathology [t(38) = 1.30, P = 0.20] and total PANSS scores [t(38) = 0.21, P = 0.84]. The two patient groups, as expected, varied significantly in the level of BIS-assessed insight [t(38) = 12.11, P < 0.001]. MRI results revealed lower fronto-temporal, parahippocampal, occipital and cerebellar grey matter volumes in Insight^- patients, relative to Insight⁺ patients and healthy controls (for all clusters, family-wise error corrected P < 0.05). Insight⁺ patient and healthy controls did not differ significantly (P > 0.20) from each other.

CONCLUSION

Our findings demonstrate a clear association between poor clinical insight and smaller fronto-temporal, occipital and cerebellar grey matter volumes in stable long-term schizophrenia patients.

A voxel-based morphometry comparison of the 3.0T ADNI-1 and ADNI-2 volumetric MRI protocols

OBJECTIVES

The Alzheimer's Disease Neuroimaging Initiative 3.0 T MRI image acquisition scheme changed between the original ADNI-1 grant and the two subsequent grants (ADNI-GO and ADNI-2). The aim of the current study was to investigate the compatibility of the 3.0 T ADNI-1 and ADNI-2 T1-weighted volumes using voxel-based morphometry (VBM).

METHODS

T1-weighted images of 30 subjects were acquired using a 3T GE Signa HDx using the ADNI-1 and ADNI-2 T1-weighted volume sequences. Images were pre-processed and analysed using SPM8. Global grey matter (GM), white matter (WM) and cerebrospinal fluid (CSF) volumes were compared, as well as voxel-by-voxel differences in GM and WM.

RESULTS

Correlation coefficients and percentage differences for each tissue type between ADNI-1 and ADNI-2 were as follows: ((GM: intraclass correlation coefficient (ICC) = 0.86, ADNI-1 3.09% < ADNI-2) (WM: ICC = 0.91, ADNI-1 2.92% > ADNI-2) (CSF: ICC = 0.90, ADNI-1 1.94% > ADNI-2)). For ADNI-2, widespread increases in GM were found relative to ADNI-1 (cerebellum and pre-central gyrus), with localised decreases along the midline and temporal lobes. For ADNI-1, widespread increases in WM were found relative to ADNI-2 (cerebellum and pre-central gyrus), together with localised decreases in the temporal gyrus.

CONCLUSIONS

The widespread increase in GM and localised decrease in WM in ADNI-2 compared to ADNI-1 images suggests that the image acquisition protocols are not directly comparable using SPM-8. Total volumes of GM, WM and CSF also differed between the protocols in the following order of magnitude: GM > WM > CSF. This has implications for studies aiming to analyse images acquired using the ADNI-1 and ADNI-2 protocols under VBM.

Eating disorder psychopathology, brain structure, neuropsychological correlates and risk mechanisms in very preterm young adults

This study investigates the prevalence of eating disorder (ED) psychopathology, neuropsychological function, structural brain correlates and risk mechanisms in a prospective cohort of very preterm (VPT) young adults. We assessed ED psychopathology and neuropsychological correlates in 143 cohort individuals born at <33 weeks of gestation. Structural brain correlates and risk factors at birth, in childhood and adolescence, were investigated using prospectively collected data throughout childhood/adolescence. VPT-born individuals had high levels of ED psychopathology at age 21 years. Executive function did not correlate with ED symptomatology. VPT adults presenting with ED psychopathology had smaller grey matter volume at age 14/15 years in the left posterior cerebellum and smaller white matter volume in the fusiform gyrus bilaterally, compared with VPT adults with no ED psychopathology. Caesarean delivery predicted engaging in compensatory behaviours, and severe eating difficulty at age 14 years predicted ED symptomatology in young adulthood. VPT individuals are at risk for ED symptomatology, with evidence of associated structural alterations in posterior brain regions. Further prospective studies are needed to clarify the pathways that lead from perinatal/obstetric complications to ED and relevant neurobiological mechanisms. © 2015 The Authors. European Eating Disorders Review published by John Wiley &Sons, Ltd.

Hippocampal glutamate-glutamine (Glx) in adults with Down syndrome: a preliminary study using in vivo proton magnetic resonance spectroscopy ((1)H MRS)

BACKGROUND

Down syndrome (DS), or trisomy 21, is one of the most common autosomal mutations. People with DS have intellectual disability (ID) and are at significantly increased risk of developing Alzheimer's disease (AD). The biological associates of both ID and AD in DS are poorly understood, but glutamate has been proposed to play a key role. In non-DS populations, glutamate is essential to learning and memory and glutamate-mediated excitotoxicity has been implicated in AD. However, the concentration of hippocampal glutamate in DS individuals with and without dementia has not previously been directly investigated. Proton magnetic resonance spectroscopy ((1)H MRS) can be used to measure in vivo the concentrations of glutamate-glutamine (Glx). The objective of the current study was to examine the hippocampal Glx concentration in non-demented DS (DS-) and demented DS (DS+) individuals.

METHODS

We examined 46 adults with DS (35 without dementia and 11 with dementia) and 39 healthy controls (HC) using (1)H MRS and measured their hippocampal Glx concentrations.

RESULTS

There was no significant difference in the hippocampal Glx concentration between DS+ and DS-, or between either of the DS groups and the healthy controls. Also, within DS, there was no significant correlation between hippocampal Glx concentration and measures of overall cognitive ability. Last, a sample size calculation based on the effect sizes from this study showed that it would have required 6,257 participants to provide 80% power to detect a significant difference between the groups which would indicate that there is a very low likelihood of a type 2 error accounting for the findings in this study.

CONCLUSIONS

Individuals with DS do not have clinically detectable differences in hippocampal Glx concentration. Other pathophysiological processes likely account for ID and AD in people with DS.

Computer simulation of magnetic resonance angiography imaging: model description and validation

With the development of medical imaging modalities and image processing algorithms, there arises a need for methods of their comprehensive quantitative evaluation. In particular, this concerns the algorithms for vessel tracking and segmentation in magnetic resonance angiography images. The problem can be approached by using synthetic images, where true geometry of vessels is known. This paper presents a framework for computer modeling of MRA imaging and the results of its validation. A new model incorporates blood flow simulation within MR signal computation kernel. The proposed solution is unique, especially with respect to the interface between flow and image formation processes. Furthermore it utilizes the concept of particle tracing. The particles reflect the flow of fluid they are immersed in and they are assigned magnetization vectors with temporal evolution controlled by MR physics. Such an approach ensures flexibility as the designed simulator is able to reconstruct flow profiles of any type. The proposed model is validated in a series of experiments with physical and digital flow phantoms. The synthesized 3D images contain various features (including artifacts) characteristic for the time-of-flight protocol and exhibit remarkable correlation with the data acquired in a real MR scanner. The obtained results support the primary goal of the conducted research, i.e. establishing a reference technique for a quantified validation of MR angiography image processing algorithms.

Examination of the predictive value of structural magnetic resonance scans in bipolar disorder: a pattern classification approach

BACKGROUND

Bipolar disorder (BD) is one of the leading causes of disability worldwide. Patients are further disadvantaged by delays in accurate diagnosis ranging between 5 and 10 years. We applied Gaussian process classifiers (GPCs) to structural magnetic resonance imaging (sMRI) data to evaluate the feasibility of using pattern recognition techniques for the diagnostic classification of patients with BD.

METHOD

GPCs were applied to gray (GM) and white matter (WM) sMRI data derived from two independent samples of patients with BD (cohort 1: n = 26; cohort 2: n = 14). Within each cohort patients were matched on age, sex and IQ to an equal number of healthy controls.

RESULTS

The diagnostic accuracy of the GPC for GM was 73% in cohort 1 and 72% in cohort 2; the sensitivity and specificity of the GM classification were respectively 69% and 77% in cohort 1 and 64% and 99% in cohort 2. The diagnostic accuracy of the GPC for WM was 69% in cohort 1 and 78% in cohort 2; the sensitivity and specificity of the WM classification were both 69% in cohort 1 and 71% and 86% respectively in cohort 2. In both samples, GM and WM clusters discriminating between patients and controls were localized within cortical and subcortical structures implicated in BD.

CONCLUSIONS

Our results demonstrate the predictive value of neuroanatomical data in discriminating patients with BD from healthy individuals. The overlap between discriminative networks and regions implicated in the pathophysiology of BD supports the biological plausibility of the classifiers.

Dementia in Down's syndrome: an MRI comparison with Alzheimer's disease in the general population

BACKGROUND

Down's syndrome (DS) is the most common genetic cause of intellectual disability. People with DS are at an increased risk of Alzheimer's disease (AD) compared to the general population. Neuroimaging studies of AD have focused on medial temporal structures; however, to our knowledge, no in vivo case-control study exists comparing the anatomy of dementia in DS to people with AD in the general population. We therefore compared the in vivo brain anatomy of people with DS and dementia (DS+) to those with AD in the general population.

METHOD

Using MRI in 192 adults, we compared the volume of whole brain matter, lateral ventricles, temporal lobes and hippocampus in DS subjects with and without dementia (DS+, DS-), to each other and to three non-DS groups. These included one group of individuals with AD and two groups of controls (each age-matched for their respective DS and general population AD cohorts).

RESULTS

AD and DS+ subjects showed significant reductions in the volume of the whole brain, hippocampus and temporal lobes and a significant elevation in the volume of the lateral ventricle, compared to their non-demented counterparts. People with DS+ had a smaller reduction in temporal lobe volume compared to individuals with AD.

CONCLUSIONS

DS+ and AD subjects have a significant reduction in volume of the same brain regions. We found preliminary evidence that DS individuals may be more sensitive to tissue loss than others and have less 'cognitive reserve'.

Fragile X syndrome: a pilot proton magnetic resonance spectroscopy study in premutation carriers

Purpose

There is increasing evidence that neurodevelopmental differences in people with Fragile X syndrome (FraX) may be explained by differences in glutamatergic metabolism. Premutation carriers of FraX were originally considered to be unaffected although several recent reports demonstrate neuroanatomical, cognitive, and emotional differences from controls. However there are few studies on brain metabolism in premutation carriers of FraX.

Methods

We used proton magnetic resonance spectroscopy to compare neuronal integrity of a number of brain metabolites including N-Acetyl Aspartate, Creatine + Phosphocreatinine, Choline, myoInositol, and Glutamate containing substances (Glx) in 17 male premutation carriers of FraX and 16 male healthy control individuals.

Results

There was no significant between-group difference in the concentration of any measured brain metabolites. However there was a differential increase in N-acetyl aspartate with aging in premutation FraX individuals compared to controls.

Conclusions

This is the first ¹ H-MRS study to examine premutation FraX individuals. Although we demonstrated no difference in the concentration of any of the metabolites examined between the groups, this may be due to the large age ranges included in the two samples. The differential increase in NAA levels with aging may reflect an abnormal synaptic pruning process.

A comprehensive testing protocol for MRI neuroanatomical segmentation techniques: Evaluation of a novel lateral ventricle segmentation method

Although a wide range of approaches have been developed to automatically assess the volume of brain regions from MRI, the reproducibility of these algorithms across different scanners and pulse sequences, their accuracy in different clinical populations and sensitivity to real changes in brain volume have not always been comprehensively examined. Firstly we present a comprehensive testing protocol which comprises 312 freely available MR images to assess the accuracy, reproducibility and sensitivity of automated brain segmentation techniques. Accuracy is assessed in infants, young adults and patients with Alzheimer's disease in comparison to gold standard measures by expert observers using a manual technique based on Cavalieri's principle. The protocol determines the reliability of segmentation between scanning sessions, different MRI pulse sequences and 1.5T and 3T field strengths and examines their sensitivity to small changes in volume using a large longitudinal dataset. Secondly we apply this testing protocol to a novel algorithm for segmenting the lateral ventricles and compare its performance to the widely used FSL FIRST and FreeSurfer methods. The testing protocol produced quantitative measures of accuracy, reliability and sensitivity of lateral ventricle volume estimates for each segmentation method. The novel algorithm showed high accuracy in all populations (intraclass correlation coefficient, ICC>0.95), good reproducibility between MRI pulse sequences (ICC>0.99) and was sensitive to age related changes in longitudinal data. FreeSurfer demonstrated high accuracy (ICC>0.95), good reproducibility (ICC>0.99) and sensitivity whilst FSL FIRST showed good accuracy in young adults and infants (ICC>0.90) and good reproducibility (ICC=0.98), but was unable to segment ventricular volume in patients with Alzheimer's disease or healthy subjects with large ventricles. Using the same computer system, the novel algorithm and FSL FIRST processed a single MRI image in less than 10min while FreeSurfer took approximately 7h. The testing protocol presented enables the accuracy, reproducibility and sensitivity of different algorithms to be compared. We also demonstrate that the novel segmentation algorithm and FreeSurfer are both effective in determining lateral ventricular volume and are well suited for multicentre and longitudinal MRI studies.

Simulation of High-Resolution Magnetic Resonance Images on the IBM Blue Gene/L Supercomputer Using SIMRI

Medical imaging system simulators are tools that provide a means to evaluate system architecture and create artificial image sets that are appropriate for specific applications. We have modified SIMRI, a Bloch equation-based magnetic resonance image simulator, in order to successfully generate high-resolution 3D MR images of the Montreal brain phantom using Blue Gene/L systems. Results show that redistribution of the workload allows an anatomically accurate 256³ voxel spin-echo simulation in less than 5 hours when executed on an 8192-node partition of a Blue Gene/L system.

Hippocampal proton MR spectroscopy in early Alzheimer's disease and mild cognitive impairment

Proton magnetic resonance spectroscopy ((1)H-MRS) studies have previously reported reduced brain N-acetyl aspartate (NAA) and increased myo-inositol (mI) in people with established Alzheimer's disease (AD). The earliest structure affected by AD is the hippocampus but relatively few studies have examined its neuronal integrity by MRS in AD and fewer still in people with amnestic mild cognitive impairment (MCI). We measured the hippocampal concentration of NAA, mI, choline (Cho) and creatine + phosphocreatine (Cr + PCr) in 39 patients with AD, 21 subjects with MCI and 38 age matched healthy elderly controls. Patients with AD had a significantly lower hippocampal [NAA] than controls, with subjects with MCI intermediate between the other two groups. [NAA] was positively correlated with memory in the impaired groups. Using mean hippocampal [NAA] and [Cr + PCr] we correctly classified 72% of people with AD, and 75% of controls. Reductions in [NAA] can be detected in the hippocampi of subjects with MCI and hippocampal [NAA] and [Cr + PCr] can distinguish between mild AD and normal elderly controls.

Subregional hippocampal deformations in major depressive disorder

BACKGROUND

Hippocampal atrophy is a well reported feature of major depressive disorder, although the evidence has been mixed. The present study sought to examine hippocampal volume and subregional morphology in patients with major depressive disorder, who were all medication-free and in an acute depressive episode of moderate severity.

METHODS

Structural magnetic resonance imaging scans were acquired in 37 patients (mean age 42 years) and 37 age, gender and IQ-matched healthy individuals. Hippocampal volume and subregional structural differences were measured by manual tracings and identification of homologous surface points to the central core of each hippocampus.

RESULTS

Both right (P=0.001) and left (P=0.005) hippocampal volumes were reduced in patients relative to healthy controls (n=37 patients and n=37 controls), while only the right hippocampus (P=0.016) showed a reduced volume in a subgroup of first-episode depression patients (n=13) relative to healthy controls. Shape analysis localised the subregional deformations to the subiculum and CA1 subfield extending into the CA2-3 subfields predominantly in the tail regions in the right (P=0.017) and left (P=0.011) hippocampi.

LIMITATIONS

As all patients were in an acute depressive episode, effects associated with depressive state cannot be distinguished from trait effects.

CONCLUSIONS

Subregional hippocampal deficits are present early in the course of major depression. The deformations may reflect structural correlates underlying functional memory impairments and distinguish depression from other psychiatric disorders.

Structural magnetic resonance imaging predictors of responsiveness to cognitive behaviour therapy in psychosis

BACKGROUND

Responsiveness to cognitive behaviour therapy (CBT) in psychosis may have a neurological basis. This study aimed to determine whether improvement in symptoms following CBT for psychosis (CBTp) in people with schizophrenia is positively associated with pre-therapy grey matter volume in brain regions involved in cognitive processing.

METHODS

Sixty outpatients stable on medication with at least one distressing symptom of schizophrenia and willing to receive CBTp in addition to their standard care (SC), and 25 healthy participants underwent magnetic resonance imaging. Subsequently, 30 patients received CBTp (CBTp+SC; 25 completers) for 6-8 months and 30 continued with their standard care (SC; 19 completers). Symptoms in all patients were assessed (blindly) at entry and follow-up.

RESULTS

The CBTp+SC and SC groups did not differ clinically at baseline, and only the CBTp+SC group showed improved symptoms at follow-up. Severity of baseline symptoms was not associated with CBTp responsiveness. Reduction with CBTp in positive symptoms was associated with greater right cerebellum (lobule VII) grey matter volume, in negative symptoms with left precentral gyrus and right inferior parietal lobule grey matter volumes, and in general psychopathology with greater right superior temporal gyrus, cuneus and cerebellum (Crus I) grey matter volumes. Grey matter volume in these brain areas did not correlate with the severity of baseline symptoms.

CONCLUSION

Grey matter volume of the frontal, temporal, parietal and cerebellar areas that are known to be involved in the co-ordination of mental activity, cognitive flexibility, and verbal learning and memory predict responsiveness to CBTp in patients with psychosis.

Alzheimer's disease and Down's syndrome: an in vivo MRI study

BACKGROUND

Individuals with Down's syndrome (DS) are at high risk of developing Alzheimer's disease (AD). However, few studies have investigated brain anatomy in DS individuals with AD.

METHOD

We compared whole brain anatomy, as measured by volumetric magnetic resonance imaging (MRI), in DS individuals with and without AD. We also investigated whether volumetric differences could reliably classify DS individuals according to AD status. We used volumetric MRI and manual tracing to examine regional brain anatomy in 19 DS adults with AD and 39 DS adults without AD.

RESULTS

DS individuals with AD had significantly smaller corrected volumes bilaterally of the hippocampus and caudate, and right amygdala and putamen, and a significantly larger corrected volume of left peripheral cerebrospinal fluid (CSF), compared to DS individuals without AD. The volume of the hippocampus and caudate nucleus correctly categorized 92% and 92% respectively of DS individuals without AD, and 75% and 80% respectively of DS individuals with AD.

CONCLUSIONS

DS individuals with AD have significant medial temporal and striatal volume reductions, and these may provide markers of clinical AD.

Proteome-based identification of plasma proteins associated with hippocampal metabolism in early Alzheimer's disease

BACKGROUND AND METHODS

There is an urgent need for peripheral surrogates of Alzheimer's disease (AD) that accurately reflect disease state and severity as well as correlate with key features of its neuropathology. The aim of this study was to identify plasma proteins associated with known in vivo markers of disease activity. In an earlier proteomic study of plasma, we discovered a panel of 15 proteins that were differentially expressed in AD and further validated complement factor-H (CFH) and alpha-2-macroglobulin (A2M) as AD-specific plasma biomarkers. In the present study, we extended these findings by testing the associations of these plasma proteins with neuro-imaging measures of disease progression in AD. We combined (1)H-magnetic resonance spectroscopy of the hippocampus and MRI-based hippocampal volumetry with proteomic analysis of plasma in early AD and mild cognitive impairment (MCI) to achieve this goal. Using (1)H-magnetic resonance spectroscopy, we derived estimates of the hippocampal metabolite ratio N-acetylaspartate/myo-inositol (NAA/mI), a biochemical measure that is associated with cognitive decline in early AD. We also undertook a proteomic analysis of plasma in these individuals using two-dimensional gel electrophoresis (2DGE).

RESULTS

We observed that two plasma proteins previously shown to be differentially expressed in AD, complement factor-H (CFH) and alpha-2-macroglobulin (A2M) showed significant positive correlations with hippocampal NAA/mI ratio in AD.

CONCLUSIONS

The association of plasma CFH and A2M with hippocampal NAA/mI in this cohort of AD subjects suggests that these proteins may reflect disease progression in early AD. These findings warrant validation in large population-based datasets.

Neurological basis of poor insight in psychosis: a voxel-based MRI study

BACKGROUND

As a reflection of poor insight, people with schizophrenia often disagree with carers and clinicians about whether (a) their experiences are abnormal, (b) they are mentally ill, and (c) they need treatment.

METHODS

This study used voxel-based morphometry to identify the associations between total and regional grey matter volumes and self-reported and observer-rated insight in 52 patients with schizophrenia or schizoaffective disorder. Thirty healthy participants were also studied.

RESULTS

There were positive associations in patients between (i) the ability to recognise experiences as abnormal and the total and right superior temporal gyrus grey matter volumes, (ii), awareness of problems ('something wrong') and the left precuneus grey matter volume and (iii) awareness of symptoms and attributing them to illness and grey matter volumes in the left superior-middle temporal gyrus and the right inferior temporal and lateral parietal gyri. The 'recognition of the need for medication' dimension did not correlate with total or any regional grey matter volumes. Relative to controls, patients had less total and regional grey matter volumes in the thalamus and middle occipital and superior temporal gyri.

CONCLUSIONS

Lower grey matter volumes in the temporal and parietal regions that have been implicated in self-monitoring, working memory and access to internal mental states are associated with poor insight on certain dimensions in psychosis.

Fast and reliable estimation of multiple parametric images using an integrated method for dynamic SPECT

Dynamic single photon emission computed tomography (SPECT) has demonstrated the potential to quantitatively estimate physiological parameters in the brain and the heart. The generalized linear least square (GLLS) method is a well-established method for solving linear compartment models with fast computational speed. However, the high level of noise intrinsic in the SPECT data leads to reliability and instability problems of GLLS for generating parametric images. An integrated method is proposed to restrict the noise in both the temporal and spatial domains to estimate multiple parametric images for dynamic SPECT. This method comprises three steps which are optimum image sampling schedule in the projection space, cluster analysis applied postreconstruction and parametric image generation with GLLS. The simulation and experimental studies for the neuronal nicotine acetylcholine receptor tracer of 5-[123I]-iodo-A-85380 were employed to evaluate the performance of the proposed method. The results of influx rate of K1 and volume of distribution of Vd demonstrated that the integrated method was successful in generating low noise parametric images for high noise SPECT data without enhancing the partial volume effect. Furthermore, the integrated method is computationally efficient for potential clinical applications.

Prefrontal cortex and insight in schizophrenia: a volumetric MRI study

Previous studies have suggested a relationship between frontal lobe-based neuropsychological functions and insight in schizophrenia. There is some evidence linking both smaller whole brain volume and frontal cortical atrophy to poor insight in this population. We investigated the relationship between total as well as specific prefrontal regional volumes and insight in schizophrenia. Twenty-eight stable outpatients with schizophrenia underwent magnetic resonance imaging scanning and assessment for insight. Insight was measured using the Birchwood self-report Insight Scale and the Expanded Schedule of Assessment of Insight. The whole brain and prefrontal regional (superior frontal, middle frontal, inferior frontal and orbitofrontal) volumes were then manually measured using the Cavalieri method and established criteria. Twenty healthy subjects were also scanned to provide control data for volumetric assessments. Smaller total prefrontal grey matter volume was moderately associated with a lower level of insight into the presence of illness. At the prefrontal sub-regional level, volumes of the superior, inferior and orbitofrontal regions contributed to this relationship, especially in males. It is concluded that smaller prefrontal grey matter volume is associated with poor insight into the presence of illness in stable schizophrenia patients. Future research should examine the association of specific dimensions of insight with frontal as well as non-frontal regional brain volumes.

Frontotemporal white matter changes in amyotrophic lateral sclerosis

Cognitive dysfunction can occur in some patients with amyotrophic lateral sclerosis (ALS) who are not suffering from dementia. The most striking and consistent cognitive deficit has been found using tests of verbal fluency. ALS patients with verbal fluency deficits have shown functional imaging abnormalities predominantly in frontotemporal regions using positron emission tomography (PET). This study used automated volumetric voxel-based analysis of grey and white matter densities of structural magnetic resonance imaging (MRI) scans to explore the underlying pattern of structural cerebral change in nondemented ALS patients with verbal fluency deficits. Two groups of ALS patients, defined by the presence or absence of cognitive impairment on the basis of the Written Verbal Fluency Test (ALSi, cognitively impaired, n=11; ALSu, cognitively unimpaired n=12) were compared with healthy age matched controls (n=12). A comparison of the ALSi group with controls revealed significantly (p<0.002) reduced white matter volume in extensive motor and non-motor regions, including regions corresponding to frontotemporal association fibres. These patients demonstrated a corresponding cognitive profile of executive and memory dysfunction. Less extensive white matter reductions were revealed in the comparison of the ALSu and control groups in regions corresponding to frontal association fibres. White matter volumes were also found to correlate with performance on memory tests. There were no significant reductions in grey matter volume in the comparison of either patient group with controls. The structural white matter abnormalities in frontal and temporal regions revealed here may underlie the cognitive and functional imaging abnormalities previously reported in non-demented ALS patients. The results also suggest that extra-motor structural abnormalities may be present in ALS patients with no evidence of cognitive change. The findings support the hypothesis of a continuum of extra-motor cerebral and cognitive change in this disorder.

The SIMRI project: a versatile and interactive MRI simulator

This paper gives an overview of SIMRI, a new 3D MRI simulator based on the Bloch equation. This simulator proposes an efficient management of the T2* effect, and in a unique simulator integrates most of the simulation features that are offered in different simulators. It takes into account the main static field value and enables realistic simulations of the chemical shift artifact, including off-resonance phenomena. It also simulates the artifacts linked to the static field inhomogeneity like those induced by susceptibility variation within an object. It is implemented in the C language and the MRI sequence programming is done using high level C functions with a simple programming interface. To manage large simulations, the magnetization kernel is implemented in a parallelized way that enables simulation on PC grid architecture. Furthermore, this simulator includes a 1D interactive interface for pedagogic purpose illustrating the magnetization vector motion as well as the MRI contrasts.

Selective deficit of hippocampal N-acetylaspartate in antipsychotic-naive patients with schizophrenia

BACKGROUND

Studies using proton magnetic resonance spectroscopy in schizophrenia have demonstrated abnormality of N-acetylaspartate but are confounded by the effects of phase of illness and medication. There is mounting evidence that antipsychotic medication influences N-acetylaspartate.

METHODS

A group of first-episode patients who had received no, or minimal, antipsychotic medication was examined at baseline and after 3 months treatment. Normal comparison subjects were examined at the same interval. Ratios of N-acetylaspartate, creatine plus phosphocreatine, and choline-containing compounds in the left prefrontal cortex, hippocampus, and basal ganglia were measured.

RESULTS

The mean duration of symptoms for all patients was 31.6 (SD 26.1) weeks. A significant reduction of hippocampal N-acetylaspartate/creatine plus phosphocreatine was found in the antipsychotic-naive group relative to those previously treated and to controls at baseline (F = 7.3, p <.002). No group differences were found at follow-up.

CONCLUSIONS

Hippocampal N-acetylaspartate/creatine plus phosphocreatine appears to be selectively affected early in the course of illness. The finding of neurochemical differences between treatment naive and previously treated patients confirms the relevance of medication status in proton magnetic resonance spectroscopy studies. Further investigation of the influence of medication at this stage of illness is warranted.

Feature-based, automated segmentation of cerebral infarct patterns using T2- and diffusion-weighted imaging

Diffusion-weighted imaging enables the diagnosis of cerebral ischemias very early, thus supporting therapies such as thrombolysis. However, morphology and tissue-characterizing parameters (e.g. relaxation times or water diffusion) may vary strongly in ischemic regions, indicating different underlying pathologic processes. As the determination of the parameters by a supervised segmentation is very time consuming, we evaluated whether different infarct patterns may be segmented by an automated, multidimensional feature-based method using a unified segmentation procedure. Ischemias were classified into 5 characteristic patterns. For each class, a 3D histogram based on T(2)- and diffusion-weighted images as well as calculated apparent diffusion coefficients (ADC) was generated from a representative data set. Healthy and pathologic tissue classes were segmented in the histogram as separate, local density maxima with freely shaped borders. Segmentation control parameters were optimized in a 3-step procedure. The method was evaluated using synthetic images as well as results of a supervised segmentation. For the analysis of cerebral ischemias, the optimal control parameter set led to sensitivities and specificities between 1.0 and 0.9.

Improved contrast in multispectral phase images derived from magnetic resonance exams of multiple sclerosis patients

We describe a method to extract data from multispectral MR exams of patients with Multiple Sclerosis (MS). The technique produces images of "spectral phase" (SP) relative to a reference tissue. SP images allow retrospective suppression of signal in the reference tissue, while maintaining high spatial resolution. Image quality in SP images was determined from MR exams of 5 MS patients selected at random from a clinical trial underway at our institute. Exams consisting of proton density weighted (PDw), T2 weighted (T2w), T1 weighted (T1w), and gadolinium-DTPA enhanced T1w (GAD) images were acquired from each patient. The MR exams were corrected for intensity nonuniformity, then filtered with an algorithm based upon anisotropic diffusion, to reduce noise. Principal component (PC) images and SP images relative to cerebrospinal fluid (SP(CSF)), normal appearing white matter (SP(NAWM)), gray matter (SP(GM)), and temporalis muscle (SP(MUS)) were then calculated. Contrast between tissues and MS lesions in the MR and derived images was then determined by measuring the signal-difference-to-noise ratio (dSNR) between tissues. Our new SP images provided better tissue contrast than the original MR, filtered MR, and PC images. Contrast improved between CSF and NAWM (from 19.5 to 56), CSF and GM (from 15 to 36), GM and NAWM (from 8 to 14), MS lesions and CSF (from 16 to 35), and between MS lesions and NAWM (from 24 to 47). (Maximum contrast in the original MR images compared to maximum contrast in the SP images.) The additional contrast in SP images may aid the quantification and analysis of lesion activity in MR exams of MS patients.

Pitfalls in the clustering of neuroimage data and improvements by global optimization strategies

In this paper, we examined three vector quantization (VQ) methods used for the unsupervised classification (clustering) of functional magnetic resonance imaging (fMRI) data. Classification means that each brain volume element (voxel), according to a given scanning raster, was assigned to one group of voxels based on similarity of the fMRI signal patterns. It was investigated how the VQ methods can isolate a cluster that describes the region involved in a particular brain function. As an example, word processing was stimulated by a word comparison task. VQ analysis methodology was verified using simulated fMRI response patterns. It was demonstrated in detail that VQ based on global rather than local optimization of the objective function yielded a higher performance. Performance was measured in statistically relevant series of VQ attempts using several indices for goodness, reliability and efficiency of VQ solutions. Furthermore, it was shown that a poor local optimization caused either an underestimation or an overestimation of the stimulus-induced brain activation. However, this was not observed if the cluster analysis was based upon a global optimization strategy.

Corpus callosum area and functioning in schizophrenic patients with auditory--verbal hallucinations

Auditory--verbal hallucinations (AVH) are a characteristic feature of schizophrenia. Patients with AVHs have been found to differ from non-hallucinating patients in volumes of certain asymmetrical brain structures on MRI, and on certain neuropsychological measures. There is also evidence of corpus callosum (CC) abnormalities in schizophrenia, and it has been proposed that abnormalities of inter-hemispheric transmission may underlie hallucinations and other symptoms. The aim of this study was to examine whether patients with AVHs have smaller corpora callosa than those without AVH, and whether CC size is related to performance on neuropsychological tests of functional cerebral asymmetry. Seventy-one DSM-IV male schizophrenics were recruited on the basis of their hallucination history plus 33 matched normal controls. Twenty-nine patients had no history of AVH, and 42 had a strong history of AVH. The mid-sagittal surface area and longitudinal length of the CC were measured from T(1)-weighted spin echo images. Callosal area was divided into four sections. There were no significant differences in any of the measurements between the two patient groups, or between patients with schizophrenia and controls. There was no association between CC measures and handedness, or performance on dichotic listening or finger tapping tasks. The results of this study do not lend support for there being a major morphological abnormality of the corpus callosum in schizophrenic patients, or for a specific relationship to AVH. However, a significant association between CC area and overall grey and white matter volumes was noted in the hallucinating patients and, to a lesser extent, in the non-hallucinators, which may point to differing influences on brain development or degeneration in such patients compared with normal controls.

Structural magnetic imaging of the hippocampus in early onset schizophrenia

BACKGROUND

Previous literature suggests that hippocampal volume reductions in schizophrenia may occur either during adolescence or at the point of transition to overt psychosis. The authors tested these hypotheses by examining the hippocampal formation in adolescents with recent onset schizophrenia.

METHODS

We compared the volumes of the left and right hippocampus, obtained using stereologic methods from magnetic resonance brain images, from 40 adolescents with recent onset schizophrenia to those of an equal number of matched healthy control subjects. Symptoms were rated using the Positive and Negative Syndrome Scale.

RESULTS

Compared with control subjects, adolescents with schizophrenia had reduced whole brain volume. After adjusting for brain volume, no group differences were observed in hippocampal volume. Duration of illness was negatively correlated with the volume of the left hippocampus. We found no effect of pregnancy and birth complications or family history of psychosis on hippocampal volumes. There was a negative correlation between severity of psychopathology and hippocampal volumes, which was significant for negative symptoms.

CONCLUSIONS

Specific hippocampal volume reductions in early onset schizophrenia do not seem to predate the onset of or to occur at the point of transition to psychosis but may develop in adolescence during the early stages of the illness.

Are auditory hallucinations the consequence of abnormal cerebral lateralization? A morphometric MRI study of the sylvian fissure and planum temporale

BACKGROUND

Auditory verbal hallucinations (AVHs) are a characteristic feature of schizophrenia. Patients with schizophrenia have been found to have reduced volumes of a variety of brain structures as well as a reduction in right-left asymmetries, using postmortem and magnetic resonance imaging (MRI) measures. There is also evidence that patients with AVHs differ in these structural asymmetries, relative to those patients who do not hallucinate. The aim of this study was to examine whether patients with and without a prominent history of AVHs differ, both from each other and in comparison with normal subjects, in the asymmetry of the sylvian fissure (SF) and planum temporale (PT).

METHODS

We recruited 74 DSM-IV male patients with schizophrenia (on the basis of their AVH history) and 32 matched normal control subjects. Thirty patients had no history of AVHs and 44 had a strong definitive history of AVHs. The SF length and PT area and volume were measured on a three-dimensional MRI spoiled GRASS volume sequence. Absolute measures and laterality coefficients were calculated.

RESULTS

: All groups had the normal leftward asymmetry in both the SF and PT. Planum temporale volume and surface area and SF length were all larger in the left hemisphere. There were no significant differences in any measures between the two patient groups or between schizophrenic patients and control subjects. Greater leftward asymmetry of the SF correlated with hallucinations and thought disorder within the prominent hallucinator group. An association was found between handedness and brain size, but this did not interact with diagnosis.

CONCLUSIONS

The results of this study do not confirm reports, based on smaller samples, of reduced structural asymmetries of either the SF or PT in schizophrenia, nor do they indicate a specific relationship to a propensity to experience AVHs. A modest correlation between leftward asymmetry of the SF and some positive symptomatology was found.

Mathematical segmentation of grey matter, white matter and cerebral spinal fluid from MR image pairs

The aims of this study were (1) to design a mathematical segmentation technique to allow extraction of grey matter, white matter and cerebral spinal fluid volumes from paired high resolution MR images and (2) to document the statistical accuracy of the method with different image combinations. A series of linear equations were derived that describe proportional tissue volumes in individual image voxels. The equations use estimates of pure tissue values to derive the proportion of each tissue within a single voxel. Repeatability of manual estimations of pure tissue values was assessed both using regions of interest and thresholding techniques. Statistical accuracy of tissue estimations for a variety of image pairs was assessed from measurements of root-mean-square noise and mean grey level intensity. The technique was used to produce parametric images of grey and white matter distribution. The segmentation technique showed greatest statistical accuracy when the first image has high grey/white matter contrast and the second image has little contrast or the rank order of the signal intensities from pure tissue is reversed. A combination of inversion recovery fast spin echo and fast FLAIR images produced a statistical error of 11% for grey matter and 10% for white matter for any given voxel. The effect of increasing sample size improves both of these figures to give a 1% statistical error on a 100 pixel sample.

Rapid relaxation times measurements by MRI: an in vivo application to contrast agent modeling for muscle fiber types characterization

This paper is a description of a simulation method to evaluate the contrast in NMR imaging and its aim is to help to optimize the use of contrast media in clinical imaging. Indeed, there is a need to define objective criteria in order to choose among several contrast media the ones that are the most effective and to define their optimal conditions of use, such as: the dose to be injected, the required time after injection to obtain the best enhancement and the optimal imaging sequence parameter values. The method is based on NMR signal simulation in the presence of contrast media and requires the fast measurement of the T1 and T2 relaxation times to obtain the dynamic relaxometry variation of tissues after contrast injection. In this work the fast imaging techniques that are to be described enable the measurement of T1 and T2 with a 30sec temporal resolution on 128*256 matrix images. The accuracy of the method was assessed in rabbit muscles after the injection of two gadolinium chelates (Gd-DTPA and Gd-DOTA) with the aim of improving the in vivo characterization of fast-twitch and slow-twitch muscle fiber types. The simulation results were in close agreement with contrast image analysis and showed, for relevant clinical doses, a small efficacy for both chelates. The interest of the proposed simulation method lies in the fact that it enables to objectively compare the efficacy of different contrast agents, to forecast the efficacy of a given contrast reagent and to define the optimal dose and the optimal imaging sequence parameters that give the best contrast. This simulation method obviates numerous prior experiments to evaluate the benefit expected from different contrast media. The method, which has been evaluated here for muscle investigations is applicable to any tissue analysis and can help to guide the best condition of use of contrast agents in MR imaging.

Parametric estimate of intensity inhomogeneities applied to MRI

This paper presents a new approach to the correction of intensity inhomogeneities in magnetic resonance imaging (MRI) that significantly improves intensity-based tissue segmentation. The distortion of the image brightness values by a low-frequency bias field impedes visual inspection and segmentation. The new correction method called parametric bias field correction (PABIC) is based on a simplified model of the imaging process, a parametric model of tissue class statistics, and a polynomial model of the inhomogeneity field. We assume that the image is composed of pixels assigned to a small number of categories with a priori known statistics. Further we assume that the image is corrupted by noise and a low-frequency inhomogeneity field. The estimation of the parametric bias field is formulated as a nonlinear energy minimization problem using an evolution strategy (ES). The resulting bias field is independent of the image region configurations and thus overcomes limitations of methods based on homomorphic filtering. Furthermore, PABIC can correct bias distortions much larger than the image contrast. Input parameters are the intensity statistics of the classes and the degree of the polynomial function. The polynomial approach combines bias correction with histogram adjustment, making it well suited for normalizing the intensity histogram of datasets from serial studies. We present simulations and a quantitative validation with phantom and test images. A large number of MR image data acquired with breast, surface, and head coils, both in two dimensions and three dimensions, have been processed and demonstrate the versatility and robustness of this new bias correction scheme.

A modified fuzzy clustering algorithm for operator independent brain tissue classification of dual echo MR images

Methods for brain tissue classification or segmentation of structural magnetic resonance imaging (MRI) data should ideally be independent of human operators for reasons of reliability and tractability. An algorithm is described for fully automated segmentation of dual echo, fast spin-echo MRI data. The method is used to assign fuzzy-membership values for each of four tissue classes (gray matter, white matter, cerebrospinal fluid and dura) to each voxel based on partition of a two dimensional feature space. Fuzzy clustering is modified for this application in two ways. First, a two component normal mixture model is initially fitted to the thresholded feature space to identify exemplary gray and white matter voxels. These exemplary data protect subsequently estimated cluster means against the tendency of unmodified fuzzy clustering to equalize the number of voxels in each class. Second, fuzzy clustering is implemented in a moving window scheme that accommodates reduced image contrast at the axial extremes of the transmitting/receiving coil. MRI data acquired from 5 normal volunteers were used to identify stable values for three arbitrary parameters of the algorithm: feature space threshold, relative weight of exemplary gray and white matter voxels, and moving window size. The modified algorithm incorporating these parameter values was then used to classify data from simulated images of the brain, validating the use of fuzzy-membership values as estimates of partial volume. Gray:white matter ratios were estimated from 20 twenty normal volunteers (mean age 32.8 years). Processing time for each three-dimensional image was approximately 30 min on a 170 MHz workstation. Mean cerebral gray and white matter volumes estimated from these automatically segmented images were very similar to comparable results previously obtained by operator dependent methods, but without their inherent unreliability.

Removal of extracerebral tissues in dual-echo magnetic resonance images via linear scale-space features

The location and masking of the brain and surrounding cerebrospinal fluid (CSF) in two-dimensional (2D) dual-echo fast spin-echo (FSE) magnetic resonance (MR) images of the head is achieved by an automated procedure with a voxel-based computational algorithm. Linear scale-space features are derived from the short-echo, proton-density (PD)-weighted images. The second-order Gaussian derivative (the Laplacian) operator is applied at three different spatial scales as a measure of image convexity/concavity with a first-order Gaussian derivative measure (the squared gradient) at a single scale used to circumscribe cortical regions. A mask obtained from the long-echo, T2-weighted image is used to remove extracerebral components of the visual system. A three-dimensional (3D) connectivity analysis then identifies the largest connected volume as the brain. Five dual-echo fast spin-echo images acquired by repeated scanning of the same normal volunteer were used to verify reproducibility; and coronal and axial acquisitions from another normal volunteer to demonstrate the method's robustness to data collected with non-cubic voxels. Images acquired from five individuals with Alzheimer's disease are also presented to show that the algorithm can be used in cases of non-normative anatomy. Validity is affirmed by demonstrating that cerebral volumes estimated by this method for all 12 images are highly correlated (R = 0.98) with estimates obtained by an expert human operator.

Reduced levels of GABA-benzodiazepine receptor in alcohol dependency in the absence of grey matter atrophy

BACKGROUND

We tested the hypothesis that reduced levels of the GABA-benzodiazepine receptor occur in alcohol dependency using single photon emission tomography (SPET) and the specific GABA-benzodiazepine ligand, 123I-iomazenil.

METHOD

Neurologically and cognitively unimpaired abstinent alcohol-dependent (n = 12) and non-alcohol-dependent male subject (n = 14) underwent a 123I-iomazenil SPET scan. SPET and magnetic resonance images were co-registered and voxel-based statistical tests performed. Subjects' clinical and alcohol history were obtained with standard questionnaires. The relationships between clinical and alcohol variables and the regional level of GABA-benzodiazepine receptors were investigated using multiple regression analysis.

RESULTS

Abstinent alcohol-dependent subjects had decreased levels of GABA-benzodiazepine receptor compared with non-alcohol-dependent subjects within the frontal, parietal and temporal cortices, including regions in which grey matter atrophy was absent.

CONCLUSIONS

Alcohol dependency is associated with reduced GABA-benzodiazepine receptor levels in the absence of grey matter atrophy in some cortical regions, such as within the parietal lobe. Regional variability of reduction in GABA-benzodiazepine receptors demonstrates that alcohol does not have a global, toxic effect on the brain.

Edge complexity and partial volume effects

PURPOSE

The accuracy of MR brain image segmentation is limited by so-called partial volume effects. We hypothesized that "edge complexity" (i.e., tissue class interface border complexity) significantly influences the magnitude of such effects.

METHOD

To investigate partial volume effects and provide a vehicle for validation of segmentation algorithm accuracy in brain MRI. We developed a computer simulation, the "gigabrain." The simulation is based on interpolated (supersampled) data from actual MR studies. The voxels are assigned to one of five compartments (gray matter, white matter, CSF, fat, or "background"), the compartment interfaces are "jittered" to add high frequency "signal" or "edge complexity," and the voxels are populated with appropriate values determined from human data, low pass filtered (based on the MR scanner's point spread function), and subsampled back to the sampling and voxel size of the original MR data set.

RESULTS

In comparison studies with actual phantoms and human MR data, our simulation approach was able to produce images whose appearance and quantitative values were comparable with the actual data, but only when edge complexity was added to the original MR data.

CONCLUSION

Edge complexity is a significant source of partial volume effects. MR simulations must include edge complexity to adequately test segmentation algorithms.

Reliability and validity of an algorithm for fuzzy tissue segmentation of MRI

PURPOSE

A new multistep, volumetric-based tissue segmentation algorithm that results in fuzzy (or probabilistic) voxel description is described. This algorithm is designed to accurately segment gray matter, white matter, and CSF and can be applied to both single channel high resolution and multispectral (multiecho) MR images.

METHOD

The reliability and validity of this method are evaluated by assessing (a) the stability of the algorithm across time, rater, and pulse sequence; (b) the accuracy of the method when applied to both real and synthetic image datasets; and (c) differences in specific tissue volumes between individuals with a specific genetic condition (fragile X syndrome) and normal control subjects.

RESULTS

The algorithm was found to have high reliability, accuracy, and validity. The finding of increased caudate gray matter volume associated with the fragile X syndrome is replicated in this sample.

CONCLUSION

Since this segmentation approach incorporates "fuzzy" or probabilistic methods, it has the potential to more accurately address partial volume effects, anatomical variation within "pure" tissue compartments, and more subtle changes in tissue volumes as a result of disease and treatment. The method is a component of software that is available in the public domain and has been implemented on an inexpensive personal computer thus offering an attractive and promising method for determining the status and progression of both normal development and pathology of the CNS.

Serial precision of metabolite peak area ratios and water referenced metabolite peak areas in proton MR spectroscopy of the human brain

The precision of cerebral proton magnetic resonance spectroscopy (MRS) measurements is critical both in the clinical setting and for research purposes. Marshall et al. have recently concluded that "disappointing in vivo repeatability...is likely to limit" the ability of MRS to detect modest changes. We present here a comprehensive study of the precision of short- and long-term metabolite peak area ratios and water referenced metabolite peak areas for long echo time point resolved spectroscopy (PRESS) spectra (repetition time (TR) = 2000 ms, echo time (TE) = 136 ms) acquired from the occipital lobes of normal volunteers and a phantom using a conventional whole body 1.5 T MR system and conventional acquisition and analysis protocols. Short-term in vitro precision determined by five repeat scans on five occasions was excellent as measured by a mean coefficient of variation (NAA/Cho = 1.3%, NAA/Cr + PCr = 1.0%, Cho/Cr + PCr = 1.6%, NAA/H2O = 0.5%, Cho/H2O = 1.2%, Cr + PCr/H2O = 0.8%). Long term in vitro precision using 100 spectra acquired over 2 years was also very good (NAA/Cho = 2.7%, NAA/Cr + PCr = 1.4%, Cho/Cr + PCr = 2.2%, NAA/H2O = 1.5%, Cho/H2O = 2.4%, Cr + PCr/H2O = 1.5%). Short-term in vivo precision determined by five repeat scans in a single scanning session on eight subjects was also excellent (NAA/Cho = 5.2%, NAA/Cr + PCr = 3.0%, Cho/Cr + PCr = 6.6%, NAA/H2O = 1.4%, Cho/H2O = 4.9%, Cr + PCr/H2O = 2.7%) and only worsened slightly for long-term in vivo precision determined by five repeat scans on eight subjects over 3 months (NAA/Cho = 5.2%, NAA/Cr + PCr = 4.8%, Cho/Cr + PCr = 7.7%, NAA/H2O = 2.5%, Cho/H2O = 6.4%, Cr + PCr/H2O = 3.8%). We attribute the excellent precision reported here to the use of highly automated techniques for voxel shimming, water suppression and peak area measurements. These results allow us to repudiate Marshall's assertion regarding disappointing repeatability of in vivo MRS.

A reproducible method for automated extraction of brain volumes from 3D human head MR images

An automated method for extracting brain volumes from three commonly acquired three-dimensional (3D) MR images (proton density, T1 weighted, and T2-weighted) of the human head is described. The procedure is divided into four levels: preprocessing, segmentation, scalp removal, and postprocessing. A user-provided reference point is the sole operator-dependent input required. The method's parameters were first optimized and then fixed and applied to 30 repeat data sets from 15 normal older adult subjects to investigate its reproducibility. Percent differences between total brain volumes (TBVs) for the subjects' repeated data sets ranged from .5% to 2.2%. We conclude that the method is both robust and reproducible and has the potential for wide application.