Investigation of the Inter- and Intrascanner Reproducibility and Repeatability of Radiomics Features in T1-Weighted Brain MRI.

BACKGROUND: Radiomics is the high throughput analysis of medical images using computer algorithms, which specifically assess textural features. It has increasingly been proposed as a tool for the development of imaging biomarkers. However, an important acknowledged limitation of radiomics is the lack of reproducibility of features produced. PURPOSE: To assess reproducibility and repeatability of radiomics variables in brain MRI through a multivisit, multicenter study. STUDY TYPE: Retrospective. POPULATION: Fourteen individuals visiting three institutions twice, 10 males with the mean age of 36.3 years and age range 25-51. FIELD STRENGTH: 3D T1W inversion recovery on three 1.5-T General Electric scanners. ASSESSMENT: Radiomics analysis by a consultant radiologist performed on the T1W images of the whole brain on all visits. All possible radiomics features were generated. STATISTICAL TEST: Concordance correlation coefficient (CCC) and dynamic range (DR) for all variables were calculated to assess the test-retest repeatability. Intraclass correlation coefficients (ICCs) were calculated to investigate the reproducibility of features across centers. RESULTS: Of 1596 features generated, 57 from center 1, 15 from center 2, and 22 from center 3 had a CCC > 0.9 and DR > 0.9. Eight variables had CCC > 0.9 and DR > 0.9 in all centers. Forty-one variables had an ICC of >0.9. No variables had CCC > 0.9, DR > 0.9, and ICC > 0.9. DATA CONCLUSION: Repeatability and reproducibility of variables is a significant limitation of radiomics analysis in 3DT1W brain MRI. Careful selection of radiomic features is required. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY STAGE: 2.

Sex differences in the association of photoperiod with hippocampal subfield volumes in older adults: A cross-sectional study in the UK Biobank cohort.

INTRODUCTION: Even though seasonal and sex-dependent changes in hippocampal and subfield volumes are well known in animals, little is known about changes in humans. We hypothesized that changes in photoperiod would predict changes in hippocampal subfield volumes and that this association would be different between females and males. METHODS: A total of 10,033 participants ranging in age from 45 to 79 years were scanned by MRI in a single location as part of the UK Biobank project. Hippocampal subfield volumes were obtained using automated processing and segmentation algorithms using the developmental version of the FreeSurfer v 6.0. Photoperiod was defined as the number of hours between sunrise and sunset on the day of scan. RESULTS: Photoperiod correlated positively with total hippocampal volume and all subfield volumes across participants as well as in each sex individually, with females showing greater seasonal variation in a majority of left subfield volumes compared with males. ANCOVAs revealed significant differences in rate of change in only left subiculum, CA-4, and GC-ML-DG between females and males. PLS showed highest loadings of hippocampal subfields in both females and males in GC-ML-DG, CA1, CA4, subiculum, and CA3 for left hemisphere and CA1, GC-ML-DG, CA4; subiculum and CA3 for right hemisphere in females; GC-ML-DG, CA1, subiculum, CA4 and CA3 for left hemisphere; CA1, GC-ML-DG, subiculum, CA4 and CA3 for right hemisphere in males. CONCLUSION: The influence of day length on hippocampal volume has implications for modeling age-related decline in memory in older adults, and sex differences suggest an important role for hormones in these effects.

Brainstem volume mediates seasonal variation in depressive symptoms: A cross sectional study in the UK Biobank cohort.

Seasonal differences in mood and depressive symptoms affect a large percentage of the general population, with seasonal affective disorder (SAD) representing the most common presentation. SAD affects up to 3% of the world's population, and it tends to be more predominant in females than males. The brainstem has been shown to be affected by photoperiodic changes, and that longer photoperiods are associated with higher neuronal density and decreased depressive-like behaviours. We predict that longer photoperiod days are associated with larger brainstem volumes and lower depressive scores, and that brainstem volume mediates the seasonality of depressive symptoms. Participants (N = 9289, 51.8% females and 48.1% males) ranging in age from 44 to 79 years were scanned by MRI at a single location. Photoperiod was found to be negatively correlated with low mood and anhedonia in females while photoperiod was found to be positively correlated with brainstem volumes. In females, whole brainstem, pons and medulla volumes individually mediated the relationship between photoperiod and both anhedonia and low mood, while midbrain volume mediated the relationship between photoperiod and anhedonia. No mediation effects were seen in males. Our study extends the understanding of the neurobiological factors that contribute to the pathophysiology of seasonal mood variations.

MRI and the distribution of bone marrow fat in hip osteoarthritis.

PURPOSE: To characterize the distribution of bone marrow fat in hip osteoarthritis (OA) using magnetic resonance imaging (MRI) and to assess its use as a potential biomarker. MATERIALS AND METHODS: In all, 67 subjects (39 female, 28 male) with either total hip replacement (THA) or different severities of radiographic OA, assessed by Kellgren-Lawrence grading (KLG), underwent 3T MRI of the pelvis using the IDEAL sequence to separate fat and water signals. Six regions of interest (ROIs) were identified within the proximal femur. Within each ROI the fractional-fat distribution, represented by pixel intensities, was described by its mean, standard deviation, skewness, kurtosis, and entropy. RESULTS: Hips were graded: 12 as severe symptomatic (THA), 33 had KLG0 or 1, 9 were KLG2, 11 with KLG3, and 2 with KLG4 were analyzed together. The fractional-fat content in the whole proximal femur did not vary with severity in males (mean (SD) 91.2 (6.0)%) but reduced with severity in females from 89.1 (6.7)% (KLG0,1), 91.5 (2.9)% (KLG2), 85.8 (16.7)% (KLG3,4) to 77.5 (11.9)% (THA) (analysis of variance [ANOVA] P = 0.029). These differences were most pronounced in the femoral head, where mean values fell with OA severity in both sexes from 97.9% (2.5%) (KLG0,1) to 73.0% (25.9%) (THA, P < 0.001) with the largest difference at the final stage. The standard deviation and the entropy of the distribution both increased (P < 0.001). CONCLUSION: Descriptors of the fractional fat distribution varied little with the severity of OA until the most severe stage, when changes appeared mainly in the femoral head, and have, therefore, limited value as biomarkers. LEVEL OF EVIDENCE: 2 J. Magn. Reson. Imaging 2017;45:42-50.

Fuzzy approximate entropy analysis of resting state fMRI signal complexity across the adult life span.

In this study, we present a method for measuring functional magnetic resonance imaging (fMRI) signal complexity using fuzzy approximate entropy (fApEn) and compare it with the established sample entropy (SampEn). Here we use resting state fMRI dataset of 86 healthy adults (41 males) with age ranging from 19 to 85 years. We expect the complexity of the resting state fMRI signals measured to be consistent with the Goldberger/Lipsitz model for robustness where healthier (younger) and more robust systems exhibit more complexity in their physiological output and system complexity decrease with age. The mean whole brain fApEn demonstrated significant negative correlation (r = -0.472, p<0.001) with age. In comparison, SampEn produced a non-significant negative correlation (r = -0.099, p = 0.367). fApEn also demonstrated a significant (p < 0.05) negative correlation with age regionally (frontal, parietal, limbic, temporal and cerebellum parietal lobes). There was no significant correlation regionally between the SampEn maps and age. These results support the Goldberger/Lipsitz model for robustness and have shown that fApEn is potentially a sensitive new method for the complexity analysis of fMRI data.

Nonlinear complexity analysis of brain FMRI signals in schizophrenia.

We investigated the differences in brain fMRI signal complexity in patients with schizophrenia while performing the Cyberball social exclusion task, using measures of Sample entropy and Hurst exponent (H). 13 patients meeting diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM IV) criteria for schizophrenia and 16 healthy controls underwent fMRI scanning at 1.5 T. The fMRI data of both groups of participants were pre-processed, the entropy characterized and the Hurst exponent extracted. Whole brain entropy and H maps of the groups were generated and analysed. The results after adjusting for age and sex differences together show that patients with schizophrenia exhibited higher complexity than healthy controls, at mean whole brain and regional levels. Also, both Sample entropy and Hurst exponent agree that patients with schizophrenia have more complex fMRI signals than healthy controls. These results suggest that schizophrenia is associated with more complex signal patterns when compared to healthy controls, supporting the increase in complexity hypothesis, where system complexity increases with age or disease, and also consistent with the notion that schizophrenia is characterised by a dysregulation of the nonlinear dynamics of underlying neuronal systems.

Variance in brain volume with advancing age: implications for defining the limits of normality.

BACKGROUND: Statistical models of normal ageing brain tissue volumes may support earlier diagnosis of increasingly common, yet still fatal, neurodegenerative diseases. For example, the statistically defined distribution of normal ageing brain tissue volumes may be used as a reference to assess patient volumes. To date, such models were often derived from mean values which were assumed to represent the distributions and boundaries, i.e. percentile ranks, of brain tissue volume. Since it was previously unknown, the objective of the present study was to determine if this assumption was robust, i.e. whether regression models derived from mean values accurately represented the distributions and boundaries of brain tissue volume at older ages. MATERIALS AND METHODS: We acquired T1-w magnetic resonance (MR) brain images of 227 normal and 219 Alzheimer's disease (AD) subjects (aged 55-89 years) from publicly available databanks. Using nonlinear regression within both samples, we compared mean and percentile rank estimates of whole brain tissue volume by age. RESULTS: In both the normal and AD sample, mean regression estimates of brain tissue volume often did not accurately represent percentile rank estimates (errors=-74% to 75%). In the normal sample, mean estimates generally underestimated differences in brain volume at percentile ranks below the mean. Conversely, in the AD sample, mean estimates generally underestimated differences in brain volume at percentile ranks above the mean. Differences between ages at the 5(th) percentile rank of normal subjects were ~39% greater than mean differences in the AD subjects. CONCLUSIONS: While more data are required to make true population inferences, our results indicate that mean regression estimates may not accurately represent the distributions of ageing brain tissue volumes. This suggests that percentile rank estimates will be required to robustly define the limits of brain tissue volume in normal ageing and neurodegenerative disease.

Childhood socioeconomic status and adult brain size: childhood socioeconomic status influences adult hippocampal size.

OBJECTIVE: To investigate in older adults without dementia the relationships between socioeconomic status (SES) in childhood and magnetic resonance imaging (MRI)-derived brain volume measures typical of brain aging and Alzheimer's disease (AD). METHODS: Using a cross-sectional and longitudinal observation approach, we invited volunteers without dementia, all born in 1936, and who were participants in the 1947 Scottish Mental Survey, for MR brain imaging; 249 of 320 (77%) agreed. We measured whole brain and hippocampal volumes and recorded childhood SES history, the number of years of education undertaken, and adult SES history. Mental ability at age 11 years was recorded in 1947 and was also available. RESULTS: Analysis shows a significant association between childhood SES and hippocampal volume after adjusting for mental ability at age 11 years, adult SES, gender, and education. INTERPRETATION: A significant association between childhood SES and hippocampal volumes in late life is consistent with the established neurodevelopmental findings that early life conditions have an effect on structural brain development. This remains detectable more than 50 years later.

Brain structural complexity and life course cognitive change.

Fractal measures such as fractal dimension (FD) can quantify the structural complexity of the brain. These have been used in clinical neuroscience to investigate brain development, ageing and in studies of psychiatric and neurological disorders. Here, we examined associations between the FD of white matter and cognitive changes across the life course in the absence of detectable brain disease. The FD was calculated from segmented cerebral white matter MR images in 217 subjects aged about 68years, in whom archived intelligence scores from age 11years were available. Cognitive test scores of fluid and crystallised intelligence were obtained at the time of MR imaging. Significant differences were found (intracranial volume, brain volume, white matter volume and Raven's Progressive Matrices score) between men and women at age 68years and novel associations were found between FD and measures of cognitive change over the life course from age 11 to 68years. Those with greater FD were found to have greater than expected fluid abilities at age 68years than predicted by their childhood intelligence and less cognitive decline from age 11 to 68years. These results are consistent with other reports that FD measures of cortical structural complexity increase across the early life course during maturation of the cerebral cortex and add new data to support an association between FD and cognitive ageing.

Do brain image databanks support understanding of normal ageing brain structure? A systematic review.

OBJECTIVE: To document accessible magnetic resonance (MR) brain images, metadata and statistical results from normal older subjects that may be used to improve diagnoses of dementia. METHODS: We systematically reviewed published brain image databanks (print literature and Internet) concerned with normal ageing brain structure. RESULTS: From nine eligible databanks, there appeared to be 944 normal subjects aged ≥60 years. However, many subjects were in more than one databank and not all were fully representative of normal ageing clinical characteristics. Therefore, there were approximately 343 subjects aged ≥60 years with metadata representative of normal ageing, but only 98 subjects were openly accessible. No databank had the range of MR image sequences, e.g. T2*, fluid-attenuated inversion recovery (FLAIR), required to effectively characterise the features of brain ageing. No databank supported random subject retrieval; therefore, manual selection bias and errors may occur in studies that use these subjects as controls. Finally, no databank stored results from statistical analyses of its brain image and metadata that may be validated with analyses of further data. CONCLUSION: Brain image databanks require open access, more subjects, metadata, MR image sequences, searchability and statistical results to improve understanding of normal ageing brain structure and diagnoses of dementia. KEY POINTS: • We reviewed databanks with structural MR brain images of normal older people. • Among these nine databanks, 98 normal subjects ≥60 years were openly accessible. • None had all the required sequences, random subject retrieval or statistical results. • More access, subjects, sequences, metadata, searchability and results are needed. • These may improve understanding of normal brain ageing and diagnoses of dementia.

Quantification techniques to minimize the effects of native T1 variation and B1 inhomogeneity in dynamic contrast-enhanced MRI of the breast at 3 T.

The variation of the native T(1) (T(10)) of different tissues and B(1) transmission-field inhomogeneity at 3 T are major contributors of errors in the quantification of breast dynamic contrast-enhanced MRI. To address these issues, we have introduced new enhancement indices derived from saturation-recovery snapshot-FLASH (SRSF) images. The stability of the new indices, i.e., the SRSF enhancement factor (EF(SRSF)) and its simplified version (EF'(SRSF)) with respect to differences in T(10) and B(1) inhomogeneity was compared against a typical index used in breast dynamic contrast-enhanced MRI, i.e., the enhancement ratio (ER), by using computer simulations. Imaging experiments with Gd-DTPA-doped gel phantoms and a female volunteer were also performed. A lower error was observed in the new indices compared to enhancement ratio in the presence of typical T(10) variation and B(1) inhomogeneity. At changes of relaxation rate (ΔR(1)) of 8 s(-1), the differences between a T(10) of 1266 and 566 ms are <1, 12, and 58%, respectively, for EF(SRSF), EF'(SRSF), and ER, whereas differences of 20, 8, and 51%, respectively, result from a 50% B(1) field reduction at the same ΔR(1). These quantification techniques may be a solution to minimize the effect of T(10) variation and B(1) inhomogeneity on dynamic contrast-enhanced MRI of the breast at 3 T.

The balance between cognitive reserve and brain imaging biomarkers of cerebrovascular and Alzheimer's diseases.

The cognitive reserve hypothesis explains the disparity between clinical and pathological phenotypes and why, in two individuals with the same extent of neuropathology, one may be demented while the other remains cognitively intact. We examined the balance between brain magnetic resonance imaging measures of the two most common pathologies associated with brain ageing, cerebrovascular disease and Alzheimer's disease, and parameters of cerebral reserve in well-characterized participants born in 1936, for whom childhood intelligence is known. Brain magnetic resonance imaging was carried out at 1.5T using fluid attenuation inversion recovery and T(1)-weighted volumetric sequences in 249 participants. Cerebrovascular disease was quantified by measuring brain white matter hyperintensities on fluid attenuation inversion recovery images using Scheltens' scale and Alzheimer's disease was measured from volumetric data using FreeSurfer to extract whole brain volume and hippocampal volumes in turn. The effect of these measures of brain burden on life-long cognitive ageing from the age of 11 to 68 years was compared with the effect of educational attainment and occupational grade using structural equation modelling. Complete brain burden and reserve data were available in 224 participants. We found that educational attainment, but not occupation, has a measurable and positive effect, with a standardized regression weight of +0.23, on late life cognitive ability in people without cognitive impairment aged 68 years, allowing for the influence of childhood intelligence and the two most common subclinical brain pathological burdens in the ageing brain. In addition, we demonstrate that the magnitude of the contribution of education is greater than the negative impact of either neuropathological burden alone, with standardized regression weights of -0.14 for white matter hyperintensities and -0.20 for hippocampal atrophy. This study illustrates how education counteracts the deleterious effects of cerebrovascular disease and Alzheimer's disease and highlights the importance of quantifying cognitive reserve in dementia research.

Inter-individual differences in fMRI entropy measurements in old age.

We investigated the association between individual differences in cognitive performance in old age and the approximate entropy (ApEn) measured from functional magnetic resonance imaging (fMRI) data acquired from 40 participants of the Aberdeen Birth Cohort 1936 (ABC1936), while undergoing a visual information processing task: inspection time (IT). Participants took a version of the Moray House Test (MHT) No. 12 at age 11, a valid measure of childhood intelligence. The same individuals completed a test of non-verbal reasoning (Raven's Standard Progressive Matrices [RPM]) aged about 68 years. The IT, MHT and RPM scores were used as indicators of cognitive performance. Our results show that higher regional signal entropy is associated with better cognitive performance. This finding was independent of ability in childhood but not independent of current cognitive ability. ApEn is used for the first time to identify a potential source of individual differences in cognitive ability using fMRI data.

Regional cerebral blood flow and aberrant motor behaviour in Alzheimer's disease.

Aberrant motor behaviour (AMB) in Alzheimer's disease shares behavioural correlates with obsessive compulsive disorder (OCD). We investigated whether AMB was also comparable in terms of metabolic activity in the orbitofrontal cortex (OFC), an area shown to be hyperactive in OCD. In this study 135 patients meeting research criteria for Alzheimer's disease were identified from a database of patients recruited as part of a phase II drug trial. These patients were assessed using the Neuropsychiatric Inventory, the Alzheimer's disease assessment scale, cognitive subscale and perfusion SPECT performed with 99Tc(m) hexamethylpropyleneamine oxime. Regions of interest were created for orbitofrontal cortices and basal ganglia. In 35 patients with AMB, adjusted tracer uptake was greater in the OFC. This reached statistical significance in right superior, left superior, right medial and left medial orbital gyri (p < 0.05). The association between AMB and hyperactivity in the OFC remained significant after adjusting for the presence of anxiety. These results parallel the OFC hypermetabolism consistently seen in OCD. One model of OCD, proposes that dysfunctional interactions between frontal regions, including the OFC, produce the characteristic symptoms of OCD. The behaviour is though to be brought about by a perceived incompleteness of performing a task and is caused by an error in normal reward signals initiated upon task completion. These finding indicate that AMB in Alzheimer's disease are brought about by the same mechanistic failure.

Cerebellar brain volume accounts for variance in cognitive performance in older adults.

INTRODUCTION: Frontal lobe atrophy is implicated in patterns of age-related cognitive decline. However, other brain areas, including the cerebellum, support the work of the frontal lobes and are also sensitive to the effects of ageing. A relationship between cerebellar brain volume and cognitive function in older adults is reported, but no study has separated variance associated with cerebellar gray matter volume and cerebellar white matter volume; and no study has examined whether or not brain volume in the cerebellum is related to cognitive function in older adults after statistical control for frontal lobe volume of gray and white matter. METHOD: We used voxel based morphometry (VBM) and structural equation modelling (SEM) to analyse relations between general cognitive ability (G) and volume of GM and WM in frontal areas and cerebellum in a sample of 228 older adults (121 males and 107 females). RESULTS: Results indicate that GM volume in the cerebellum predicts G, even when total intracranial volume (TICV) and GM gray and WM volumes in frontal lobes are statistically controlled. However, results differ for males and females, with males showing a stronger relationship between brain volume in the cerebellum and G. CONCLUSIONS: Results are discussed in light of neurological models of cognitive ageing and the significance of the cerebellum in models of cognitive functioning.

Between- and within-scanner variability in the CaliBrain study n-back cognitive task.

Psychiatric neuroimaging techniques are likely to improve understanding of the brain in health and disease, but studies tend to be small, based in one imaging centre and of unclear generalisability. Multicentre studies have great appeal but face problems if functional magnetic resonance imaging (fMRI) data from different centres are to be combined. Fourteen healthy volunteers had two brain scans on different days at three scanners. Considerable effort was first made to use similar scanning sequences and standardise task implementation across centres. The n-back cognitive task was used to investigate between- and within-scanner reproducibility and reliability. Both the functional imaging and behavioural results were in good accord with the existing literature. We found no significant differences in the activation/deactivation maps between scanners, or between repeat visits to the same scanners. Between- and within-scanner reproducibility and reliability was very similar. However, the smoothness of images from the scanners differed, suggesting that smoothness equalization might further reduce inter-scanner variability. Our results for the n-back task suggest it is possible to acquire fMRI data from different scanners which allows pooling across centres, when the same field strength scanners are used and scanning sequences and paradigm implementations are standardised.

Functional Magnetic Resonance Imaging (fMRI) reproducibility and variance components across visits and scanning sites with a finger tapping task.

Multicentre MRI studies offer great potential to increase study power and flexibility, but it is not yet clear how reproducible the results from multiple centres may be. Here we present results from the multicentre study 'CaliBrain', examining the reproducibility of fMRI data within and between three sites. Fourteen subjects were scanned twice on three 1.5 T GE scanners using an identical scanning protocol. We present data from a motor task with three conditions, sequential and random finger tapping and rest. Similar activation maps were obtained for each site and visit; brain areas consistently activated during the task included the premotor, primary motor and supplementary motor areas, the striatum and cerebellum. Reproducibility was evaluated within and between sites by comparing the extent and spatial agreement of activation maps at both the subject and group levels. The results were within the range previously reported for similar tasks on single scanners and both measures were found to be comparable within and between sites, with between site reproducibility similar to the within site measures. A variance components analysis was used to examine the effects of site, subject and visit. The contributions of site and visit were small and reproducibility was similar between and within sites, whereas the variance between subjects, and unexplained variance was large. These findings suggest that we can have confidence in combined results from multicentre fMRI studies, at least when a consistent protocol is followed on similar machines in all participating scanning sites and care is taken to select homogeneous subject groups.

B1 transmission-field inhomogeneity and enhancement ratio errors in dynamic contrast-enhanced MRI (DCE-MRI) of the breast at 3T.

PURPOSE: To quantify B(1) transmission-field inhomogeneity in breast imaging of normal volunteers at 3T using 3D T(1)-weighted spoiled gradient echo and to assess the resulting errors in enhancement ratio (ER) measured in dynamic contrast-enhanced MRI (DCE-MRI) studies of the breast. MATERIALS AND METHODS: A total of 25 volunteers underwent breast imaging at 3T and the B(1) transmission-fields were mapped. Gel phantoms that simulate pre- and postcontrast breast tissue T(1) were developed. The effects of B(1)-field inhomogeneity on ER, as measured using a 3D spoiled gradient echo sequence, were investigated by computer simulation and experiments on gel phantoms. RESULTS: It was observed that by using the patient orientation and MR scanner employed in this study, the B(1) transmission-field field is always reduced toward the volunteer's right side. The median B(1)-field in the right breast is reduced around 40% of the expected B(1)-field. For some volunteers the amplitude was reduced by more than 50%. Computer simulation and experiment showed that a reduction in B(1)-field decreases ER. This reduction increases with both B(1)-field error and contrast agent uptake. CONCLUSION: B(1) transmission-field inhomogeneity is a critical issue in breast imaging at 3T and causes errors in quantifying ER. These errors would be sufficient to reduce the conspicuity of a malignant lesion and could result in reduced sensitivity for cancer detection.

Prospective multi-centre Voxel Based Morphometry study employing scanner specific segmentations: procedure development using CaliBrain structural MRI data.

BACKGROUND: Structural Magnetic Resonance Imaging (sMRI) of the brain is employed in the assessment of a wide range of neuropsychiatric disorders. In order to improve statistical power in such studies it is desirable to pool scanning resources from multiple centres. The CaliBrain project was designed to provide for an assessment of scanner differences at three centres in Scotland, and to assess the practicality of pooling scans from multiple-centres. METHODS: We scanned healthy subjects twice on each of the 3 scanners in the CaliBrain project with T1-weighted sequences. The tissue classifier supplied within the Statistical Parametric Mapping (SPM5) application was used to map the grey and white tissue for each scan. We were thus able to assess within scanner variability and between scanner differences. We have sought to correct for between scanner differences by adjusting the probability mappings of tissue occupancy (tissue priors) used in SPM5 for tissue classification. The adjustment procedure resulted in separate sets of tissue priors being developed for each scanner and we refer to these as scanner specific priors. RESULTS: Voxel Based Morphometry (VBM) analyses and metric tests indicated that the use of scanner specific priors reduced tissue classification differences between scanners. However, the metric results also demonstrated that the between scanner differences were not reduced to the level of within scanner variability, the ideal for scanner harmonisation. CONCLUSION: Our results indicate the development of scanner specific priors for SPM can assist in pooling of scan resources from different research centres. This can facilitate improvements in the statistical power of quantitative brain imaging studies.

Shape analysis of 123I-N-omega-fluoropropyl-2-beta-carbomethoxy-3beta-(4-iodophenyl) nortropane single-photon emission computed tomography images in the assessment of patients with parkinsonian syndromes.

PURPOSE: The purpose of this study was to show the viability and performance of a shape-based pattern recognition technique applied to I-N-omega-fluoropropyl-2-beta-carbomethoxy-3beta-(4-iodophenyl) nortropane single-photon emission computed tomography (FP-CIT SPECT) in patients with parkinsonism. METHODS: A fully automated pattern recognition tool, based on the shape of FP-CIT SPECT images, was written using Java. Its performance was evaluated and compared with QuantiSPECT, a region-of-interest-based quantitation tool, and observer performance using receiver operating characteristic analysis and kappa statistics. The techniques were compared using a sample of patients and controls recruited from a prospective community-based study of first presentation of parkinsonian symptoms with longitudinal follow up (median 3 years). RESULTS: The shape-based technique as well as the conventional semiquantitative approach was performed by experienced observers. The technique had a high level of automation, thereby avoiding observer/operator variability. CONCLUSION: A pattern recognition approach is a viable alternative to traditional methods of analysis in FP-CIT SPECT and has additional advantages.