Plasma Glial Fibrillary Acidic Protein Is Associated with 18F-SMBT-1 PET: Two Putative Astrocyte Reactivity Biomarkers for Alzheimer's Disease

BACKGROUND

Astrocyte reactivity is an early event along the Alzheimer's disease (AD) continuum. Plasma glial fibrillary acidic protein (GFAP), posited to reflect astrocyte reactivity, is elevated across the AD continuum from preclinical to dementia stages. Monoamine oxidase-B (MAO-B) is also elevated in reactive astrocytes observed using 18F-SMBT-1 PET in AD.

OBJECTIVE

The objective of this study was to evaluate the association between the abovementioned astrocyte reactivity biomarkers.

METHODS

Plasma GFAP and Aβ were measured using the Simoa ® platform in participants who underwent brain 18F-SMBT-1 and Aβ-PET imaging, comprising 54 healthy control (13 Aβ-PET+ and 41 Aβ-PET-), 11 mild cognitively impaired (3 Aβ-PET+ and 8 Aβ-PET-) and 6 probable AD (5 Aβ-PET+ and 1 Aβ-PET-) individuals. Linear regressions were used to assess associations of interest.

RESULTS

Plasma GFAP was associated with 18F-SMBT-1 signal in brain regions prone to early Aβ deposition in AD, such as the supramarginal gyrus (SG), posterior cingulate (PC), lateral temporal (LT) and lateral occipital cortex (LO). After adjusting for age, sex, APOE ɛ4 genotype, and soluble Aβ (plasma Aβ 42/40 ratio), plasma GFAP was associated with 18F-SMBT-1 signal in the SG, PC, LT, LO, and superior parietal cortex (SP). On adjusting for age, sex, APOE ɛ4 genotype and insoluble Aβ (Aβ-PET), plasma GFAP was associated with 18F-SMBT-1 signal in the SG.

CONCLUSION

There is an association between plasma GFAP and regional 18F-SMBT-1 PET, and this association appears to be dependent on brain Aβ load.

Cross-Sectional and Longitudinal Comparison of Tau Imaging with 18F-MK6240 and 18F-Flortaucipir in Populations Matched for Age, MMSE and Brain Beta-Amyloid Burden

OBJECTIVES

Longitudinal tau quantification may provide a useful marker of drug efficacy in clinical trials. Different tau PET tracers may have different sensitivity to longitudinal changes, but without a head-to-head dataset or a carefully designed case-matching procedure, comparing results in different cohorts can be biased. In this study, we compared the tau PET tracers, 18F-MK6240 and 18F-flortaucipir (FTP), both cross-sectionally and longitudinally by case-matching subjects in the AIBL and ADNI longitudinal cohort studies.

METHODS

A subset of 113 participants from AIBL and 113 from ADNI imaged using 18F-MK6240 and 18F-FTP respectively, with baseline and follow-up, were matched based on baseline clinical diagnosis, MMSE, age and amyloid (Aβ) PET centiloid value. Subjects were grouped as 64 Aβ- cognitively unimpaired (CU), 22 Aβ+ CU, 14 Aβ+ mild cognitive impairment (MCI) and 13 Aβ+ Alzheimer's disease (AD). Tracer retention was measured in the mesial, temporoparietal, rest of the cortex, and a meta-temporal region composed of entorhinal, inferior/middle temporal, fusiform, parahippocampus and amygdala. T-tests were employed to assess group separation at baseline using SUVR Z-scores and longitudinally using SUVR%/Yr.

RESULTS

Both tracers detected statistically significant differences at baseline in most regions between all clinical groups. Only 18F-MK6240 showed statistically significant higher rate of SUVR increase in Aβ+ CU compared to Aβ- CU in the mesial, meta-temporal and temporoparietal regions.

CONCLUSION

18F-MK6240 appears to be a more sensitive tracer for change in tau level at the preclinical stage of AD.

Two-Year Prognostic Utility of Plasma p217+tau across the Alzheimer's Continuum

BACKGROUND

Plasma p217+tau has shown high concordance with cerebrospinal fluid (CSF) and positron emission tomography (PET) measures of amyloid-β (Aβ) and tau in Alzheimer's Disease (AD). However, its association with longitudinal cognition and comparative performance to PET Aβ and tau in predicting cognitive decline are unknown.

OBJECTIVES

To evaluate whether p217+tau can predict the rate of cognitive decline observed over two-year average follow-up and compare this to prediction based on Aβ (18F-NAV4694) and tau (18F-MK6240) PET. We also explored the sample size required to detect a 30% slowing in cognitive decline in a 2-year trial and selection test cost using p217+tau (pT+) as compared to PET Aβ (A+) and tau (T+) with and without p217+tau pre-screening.

DESIGN

A prospective observational cohort study.

SETTING

Participants of the Australian Imaging, Biomarker and Lifestyle Flagship Study of Ageing (AIBL) and Australian Dementia Network (ADNeT).

PARTICIPANTS

153 cognitively unimpaired (CU) and 50 cognitively impaired (CI) individuals.

MEASUREMENTS

Baseline p217+tau Simoa® assay, 18F-MK6240 tau-PET and 18F-NAV4694 Aβ-PET with neuropsychological follow-up (MMSE, CDR-SB, AIBL-PACC) over 2.4 ± 0.8 years.

RESULTS

In CI, p217+tau was a significant predictor of change in MMSE (β = -0.55, p < 0.001) and CDR-SB (β =0.61, p < 0.001) with an effect size similar to Aβ Centiloid (MMSE β = -0.48, p = 0.002; CDR-SB β = 0.43, p = 0.004) and meta-temporal (MetaT) tau SUVR (MMSE: β = -0.62, p < 0.001; CDR-SB: β = 0.65, p < 0.001). In CU, only MetaT tau SUVR was significantly associated with change in AIBL-PACC (β = -0.22, p = 0.008). Screening pT+ CI participants into a trial could lead to 24% reduction in sample size compared to screening with PET for A+ and 6-13% compared to screening with PET for T+ (different regions). This would translate to an 81-83% biomarker test cost-saving assuming the p217+tau test cost one-fifth of a PET scan. In a trial requiring PET A+ or T+, p217+tau pre-screening followed by PET in those who were pT+ would cost more in the CI group, compared to 26-38% biomarker test cost-saving in the CU.

CONCLUSIONS

Substantial cost reduction can be achieved using p217+tau alone to select participants with MCI or mild dementia for a clinical trial designed to slow cognitive decline over two years, compared to participant selection by PET. In pre-clinical AD trials, p217+tau provides significant cost-saving if used as a pre-screening measure for PET A+ or T+ but in MCI/mild dementia trials this may add to cost both in testing and in the increased number of participants needed for testing.

APOE ε2 resilience for Alzheimer's disease is mediated by plasma lipid species: Analysis of three independent cohort studies

INTRODUCTION

The apolipoprotein E (APOE) genotype is the strongest genetic risk factor for late-onset Alzheimer's disease. However, its effect on lipid metabolic pathways, and their mediating effect on disease risk, is poorly understood.

METHODS

We performed lipidomic analysis on three independent cohorts (the Australian Imaging, Biomarkers and Lifestyle [AIBL] flagship study, n = 1087; the Alzheimer's Disease Neuroimaging Initiative [ADNI] 1 study, n = 819; and the Busselton Health Study [BHS], n = 4384), and we defined associations between APOE ε2 and ε4 and 569 plasma/serum lipid species. Mediation analysis defined the proportion of the treatment effect of the APOE genotype mediated by plasma/serum lipid species.

RESULTS

A total of 237 and 104 lipid species were associated with APOE ε2 and ε4, respectively. Of these 68 (ε2) and 24 (ε4) were associated with prevalent Alzheimer's disease. Individual lipid species or lipidomic models of APOE genotypes mediated up to 30% and 10% of APOE ε2 and ε4 treatment effect, respectively.

DISCUSSION

Plasma lipid species mediate the treatment effect of APOE genotypes on Alzheimer's disease and as such represent a potential therapeutic target.

A Conformational Variant of p53 (U-p53AZ) as Blood-Based Biomarker for the Prediction of the Onset of Symptomatic Alzheimer's Disease

BACKGROUND

Ongoing research seeks to identify blood-based biomarkers able to predict onset and progression of Alzheimer's disease (AD).

OBJECTIVE

The unfolded conformational variant of p53 (U-p53AZ), previously observed in AD individuals, was evaluated in plasma samples from individuals participating in the Australian Imaging, Biomarkers and Lifestyle (AIBL) cohort for diagnostic and prognostic assessment, validated on a neuropsychological-based diagnosis, over the course of six years.

DESIGN

Retrospective Longitudinal Prognostic biomarker study.

SETTING

Single-center study based on the AIBL cohort.

PARTICIPANTS

482 participants of the AIBL cohort, aged 60-85 years, without uncontrolled diabetes, vascular disease, severe depression or psychiatric illnesses.

MEASUREMENTS

The AlzoSure® Predict test, consisting of immunoprecipitation (IP) followed by liquid chromatography (LC) tandem mass spectrometry (MS/MS), was performed to quantify the AZ 284® peptide as readout of U-p53AZ and compared with an independent neuropsychological diagnosis. The amyloid load via amyloid β-positron emission tomography (Aβ-PET) and supporting clinical information were included where possible.

RESULTS

U-p53AZ diagnostic and prognostic performance was assessed in both time-independent and time-dependent (36, 72 and 90 months following initial sampling) analyses. Prognostic performance of Aβ-PET and survival analyses with different risk factors (gender, Aβ-PET and APOE ε4 allele status) were also performed. U-p53AZ differentiated neuropsychologically graded AD from non-AD samples, and its detection at intermediate/high levels precisely identified present and future symptomatic AD. In both time-independent and time-dependent prognostic analyses U-p53AZ achieved area under the curve (AUC) >98%, significantly higher than Aβ-PET AUCs (between 84% and 93%, P respectively <0.0001 and <0.001). As single factor, U-p53AZ could clearly determine the risk of AD neuropsychological diagnosis over time (low versus intermediate/high U-p53AZ hazard ratio=2.99). Proportional hazards regression analysis identified U-p53AZ levels as a major independent predictor of AD onset.

CONCLUSIONS

These findings support use of U-p53AZ as blood-based biomarker predicting whether individuals would reach neuropsychologically-defined AD within six years prior to AD diagnosis. Integration of U-p53AZ in screening processes could support refined participant stratification for interventional studies.

Automating Quantitative Measures of an Established Conventional MRI Scoring System for Preterm-Born Infants Scanned between 29 and 47 Weeks' Postmenstrual Age

BACKGROUND AND PURPOSE

Conventional MR imaging scoring is a valuable tool for risk stratification and prognostication of outcomes, but manual scoring is time-consuming, operator-dependent, and requires high-level expertise. This study aimed to automate the regional measurements of an established brain MR imaging scoring system for preterm neonates scanned between 29 and 47 weeks' postmenstrual age.

MATERIALS AND METHODS

This study used T2WI from the longitudinal Prediction of PREterm Motor Outcomes cohort study and the developing Human Connectome Project. Measures of biparietal width, interhemispheric distance, callosal thickness, transcerebellar diameter, lateral ventricular diameter, and deep gray matter area were extracted manually (Prediction of PREterm Motor Outcomes study only) and automatically. Scans with poor quality, failure of automated analysis, or severe pathology were excluded. Agreement, reliability, and associations between manual and automated measures were assessed and compared against statistics for manual measures. Associations between measures with postmenstrual age, gestational age at birth, and birth weight were examined (Pearson correlation) in both cohorts.

RESULTS

A total of 652 MRIs (86%) were suitable for analysis. Automated measures showed good-to-excellent agreement and good reliability with manual measures, except for interhemispheric distance at early MR imaging (scanned between 29 and 35 weeks, postmenstrual age; in line with poor manual reliability) and callosal thickness measures. All measures were positively associated with postmenstrual age (r = 0.11-0.94; R² = 0.01-0.89). Negative and positive associations were found with gestational age at birth (r = -0.26-0.71; R² = 0.05-0.52) and birth weight (r = -0.25-0.75; R² = 0.06-0.56). Automated measures were successfully extracted for 80%-99% of suitable scans.

CONCLUSIONS

Measures of brain injury and impaired brain growth can be automatically extracted from neonatal MR imaging, which could assist with clinical reporting.

FRI0383 A RANDOMISED PLACEBO-CONTROLLED CLINICAL TRIAL OF CURCUMA LONGA EXTRACT FOR TREATING SYMPTOMS AND EFFUSION-SYNOVITIS OF KNEE OSTEOARTHRITIS (CURKOA TRIAL)

Background:

Pharmacological therapies are limited, associated with off-target effects, are frequently contraindicated, and only modestly effective for pain in osteoarthritis (OA). Effusion and synovitis are common in OA and are associated with symptomatic and structural progression of OA.Curcuma longa(Turmeric) extract has anti-inflammatory effects and is gaining popularity in the treatment of OA despite the lack of high-quality evidence.

Objectives:

The CurKOA trial aimed to determine the efficacy ofCurcuma longaextract for reducing knee symptoms and effusion-synovitis in patients with symptomatic knee OA and knee effusion-synovitis.

Methods:

In this randomised, double-blind, placebo-controlled trial, participants with significant knee pain (≥ 40 mm on a 100-mm visual analog scale [VAS]), symptomatic knee OA (by ACR criteria) and ultrasound defined effusion-synovitis were randomised to receiveCurcuma longaextract (80% aqueous based extract standardized to turmerosaccharides + 20% curcuminoids, 2 × 500 mg capsules/day) or identical placebo for 12 weeks. Knee MRI scans were obtained at baseline and 12 weeks. Coprimary outcomes were changes in knee pain assessed by VAS and change in knee effusion-synovitis volume assessed by MRI over 12 weeks.

Results:

Among 70 participants (36 receivedCurcuma longa, 34 received placebo, age 61.8±8.6 years, 56% female),Curcuma longasignificantly improved VAS knee pain compared to placebo (-9.11mm, 95% confidence interval [CI] [- 17.79 to -0.44]) over 12 weeks, equivalent to a standardised effect size of 0.50. There was no significant between group difference in change in effusion-synovitis volume (3.24 mL [-0.33, 6.82]). There were significantly greater reductions in WOMAC knee pain (-47.22mm [-81.22, -13.22]), WOMAC function (-112.26mm [-222.79 to -1.74]) and significantly more OARSI-OMERACT treatment responders (63% treatment vs. 38% placebo [Risk Ratio=1.64 (1.00 to 2.70)]) in theCurcuma longagroup compared to the placebo group. There was no significant between-group difference in lateral femoral cartilage T2 relaxation time (-0.38 ms [- 1.10 to 0.34]) assessed from compositional MRI. The incidence of adverse events was similar in theCurcuma longa(n=14 (39%)) and placebo (n=18 (53%)) groups over 12 weeks (P=0.24).

Conclusion:

An extract ofCurcuma longasignificantly improved knee pain in an inflammatory phenotype of knee OA patients over 12 weeks compared to placebo but had no effect on knee effusion-synovitis and cartilage composition assessed using MRI. The moderate effect size of the treatment supports the use ofCurcuma longaextract for the symptomatic management of knee OA.

Figure 1.

Disclosure of Interests:

None declared

Multi T1-weighted contrast MRI with fluid and white matter suppression at 1.5 T

INTRODUCTION

The fluid and white matter suppression sequence (FLAWS) provides two T1-weighted co-registered datasets: a white matter (WM) suppressed contrast (FLAWS1) and a cerebrospinal fluid (CSF) suppressed contrast (FLAWS2). FLAWS has the potential to improve the contrast of the subcortical brain regions that are important for Deep Brain Stimulation surgery planning. However, to date FLAWS has not been optimized for 1.5 T. In this study, the FLAWS sequence was optimized for use at 1.5 T. In addition, the contrast-enhancement properties of FLAWS image combinations were investigated using two voxel-wise FLAWS combined images: the division (FLAWS-div) and the high contrast (FLAWS-hc) image.

METHODS

FLAWS sequence parameters were optimized for 1.5 T imaging using an approach based on the use of a profit function under constraints for brain tissue signal and contrast maximization. MR experiments were performed on eleven healthy volunteers (age 18-30). Contrast (CN) and contrast to noise ratio (CNR) between brain tissues were measured in each volunteer. Furthermore, a qualitative assessment was performed to ensure that the separation between the internal globus pallidus (GPi) and the external globus pallidus (GPe) is identifiable in FLAWS1.

RESULTS

The optimized set of sequence parameters for FLAWS at 1.5 T provided contrasts similar to those obtained in a previous study at 3 T. The separation between the GPi and the GPe was clearly identified in FLAWS1. The CN of FLAWS-hc was higher than that of FLAWS1 and FLAWS2, but was not different from the CN of FLAWS-div. The CNR of FLAWS-hc was higher than that of FLAWS-div.

CONCLUSION

Both qualitative and quantitative assessments validated the optimization of the FLAWS sequence at 1.5 T. Quantitative assessments also showed that FLAWS-hc provides an enhanced contrast compared to FLAWS1 and FLAWS2, with a higher CNR than FLAWS-div.

Validation of an MRI Brain Injury and Growth Scoring System in Very Preterm Infants Scanned at 29- to 35-Week Postmenstrual Age

BACKGROUND AND PURPOSE

The diagnostic and prognostic potential of brain MR imaging before term-equivalent age is limited until valid MR imaging scoring systems are available. This study aimed to validate an MR imaging scoring system of brain injury and impaired growth for use at 29 to 35 weeks postmenstrual age in infants born at <31 weeks gestational age.

MATERIALS AND METHODS

Eighty-three infants in a prospective cohort study underwent early 3T MR imaging between 29 and 35 weeks' postmenstrual age (mean, 32⁺² ± 1⁺³ weeks; 49 males, born at median gestation of 28⁺⁴ weeks; range, 23⁺⁶-30⁺⁶ weeks; mean birthweight, 1068 ± 312 g). Seventy-seven infants had a second MR scan at term-equivalent age (mean, 40⁺⁶ ± 1⁺³ weeks). Structural images were scored using a modified scoring system which generated WM, cortical gray matter, deep gray matter, cerebellar, and global scores. Outcome at 12-months corrected age (mean, 12 months 4 days ± 1⁺² weeks) consisted of the Bayley Scales of Infant and Toddler Development, 3rd ed. (Bayley III), and the Neuro-Sensory Motor Developmental Assessment.

RESULTS

Early MR imaging global, WM, and deep gray matter scores were negatively associated with Bayley III motor (regression coefficient for global score β = -1.31; 95% CI, -2.39 to -0.23; P = .02), cognitive (β = -1.52; 95% CI, -2.39 to -0.65; P < .01) and the Neuro-Sensory Motor Developmental Assessment outcomes (β = -1.73; 95% CI, -3.19 to -0.28; P = .02). Early MR imaging cerebellar scores were negatively associated with the Neuro-Sensory Motor Developmental Assessment (β = -5.99; 95% CI, -11.82 to -0.16; P = .04). Results were reconfirmed at term-equivalent-age MR imaging.

CONCLUSIONS

This clinically accessible MR imaging scoring system is valid for use at 29 to 35 weeks postmenstrual age in infants born very preterm. It enables identification of infants at risk of adverse outcomes before the current standard of term-equivalent age.

Basal forebrain atrophy correlates with amyloid β burden in Alzheimer's disease

The brains of patients suffering from Alzheimer's disease (AD) have three classical pathological hallmarks: amyloid-beta (Aβ) plaques, tau tangles, and neurodegeneration, including that of cholinergic neurons of the basal forebrain. However the relationship between Aβ burden and basal forebrain degeneration has not been extensively studied. To investigate this association, basal forebrain volumes were determined from magnetic resonance images of controls, subjects with amnestic mild cognitive impairment (aMCI) and AD patients enrolled in the longitudinal Alzheimer's Disease Neuroimaging Initiative (ADNI) and Australian Imaging, Biomarkers and Lifestyle (AIBL) studies. In the AIBL cohort, these volumes were correlated within groups to neocortical gray matter retention of Pittsburgh compound B (PiB) from positron emission tomography images as a measure of Aβ load. The basal forebrain volumes of AD and aMCI subjects were significantly reduced compared to those of control subjects. Anterior basal forebrain volume was significantly correlated to neocortical PiB retention in AD subjects and aMCI subjects with high Aβ burden, whereas posterior basal forebrain volume was significantly correlated to neocortical PiB retention in control subjects with high Aβ burden. Therefore this study provides new evidence for a correlation between neocortical Aβ accumulation and basal forebrain degeneration. In addition, cluster analysis showed that subjects with a whole basal forebrain volume below a determined cut-off value had a 7 times higher risk of having a worse diagnosis within ~18 months.

•

The link between amyloid (Aβ) and basal forebrain degeneration in AD is unclear.

•

We find that basal forebrain volumes are correlated with neocortical Aβ burden.

•

Basal forebrain volume correlates with Aβ burden in at-risk control subjects.

•

Basal forebrain atrophy delineates subjects at increased risk of progressing to AD.

Automated segmentation and analysis of normal and osteoarthritic knee menisci from magnetic resonance images--data from the Osteoarthritis Initiative

OBJECTIVE

To validate an automatic scheme for the segmentation and quantitative analysis of the medial meniscus (MM) and lateral meniscus (LM) in magnetic resonance (MR) images of the knee.

METHOD

We analysed sagittal water-excited double-echo steady-state MR images of the knee from a subset of the Osteoarthritis Initiative (OAI) cohort. The MM and LM were automatically segmented in the MR images based on a deformable model approach. Quantitative parameters including volume, subluxation and tibial-coverage were automatically calculated for comparison (Wilcoxon tests) between knees with variable radiographic osteoarthritis (rOA), medial and lateral joint space narrowing (mJSN, lJSN) and pain. Automatic segmentations and estimated parameters were evaluated for accuracy using manual delineations of the menisci in 88 pathological knee MR examinations at baseline and 12 months time-points.

RESULTS

The median (95% confidence-interval (CI)) Dice similarity index (DSI) (2 ∗|Auto ∩ Manual|/(|Auto|+|Manual|)∗ 100) between manual and automated segmentations for the MM and LM volumes were 78.3% (75.0-78.7), 83.9% (82.1-83.9) at baseline and 75.3% (72.8-76.9), 83.0% (81.6-83.5) at 12 months. Pearson coefficients between automatic and manual segmentation parameters ranged from r = 0.70 to r = 0.92. MM in rOA/mJSN knees had significantly greater subluxation and smaller tibial-coverage than no-rOA/no-mJSN knees. LM in rOA knees had significantly greater volumes and tibial-coverage than no-rOA knees.

CONCLUSION

Our automated method successfully segmented the menisci in normal and osteoarthritic knee MR images and detected meaningful morphological differences with respect to rOA and joint space narrowing (JSN). Our approach will facilitate analyses of the menisci in prospective MR cohorts such as the OAI for investigations into pathophysiological changes occurring in early osteoarthritis (OA) development.

Three-dimensional morphological and signal intensity features for detection of intervertebral disc degeneration from magnetic resonance images

BACKGROUND AND OBJECTIVES

Advances in MRI hardware and sequences are continually increasing the amount and complexity of data such as those generated in high-resolution three-dimensional (3D) scanning of the spine. Efficient informatics tools offer considerable opportunities for research and clinically based analyses of magnetic resonance studies. In this work, we present and validate a suite of informatics tools for automated detection of degenerative changes in lumbar intervertebral discs (IVD) from both 3D isotropic and routine two-dimensional (2D) clinical T2-weighted MRI.

MATERIALS AND METHODS

An automated segmentation approach was used to extract morphological (traditional 2D radiological measures and novel 3D shape descriptors) and signal appearance (extracted from signal intensity histograms) features. The features were validated against manual reference, compared between 2D and 3D MRI scans and used for quantification and classification of IVD degeneration across magnetic resonance datasets containing IVD with early and advanced stages of degeneration.

RESULTS AND CONCLUSIONS

Combination of the novel 3D-based shape and signal intensity features on 3D (area under receiver operating curve (AUC) 0.984) and 2D (AUC 0.988) magnetic resonance data deliver a significant improvement in automated classification of IVD degeneration, compared to the combination of previously used 2D radiological measurement and signal intensity features (AUC 0.976 and 0.983, respectively). Further work is required regarding the usefulness of 2D and 3D shape data in relation to clinical scores of lower back pain. The results reveal the potential of the proposed informatics system for computer-aided IVD diagnosis from MRI in large-scale research studies and as a possible adjunct for clinical diagnosis.

MilxXplore: a web-based system to explore large imaging datasets

OBJECTIVE

As large-scale medical imaging studies are becoming more common, there is an increasing reliance on automated software to extract quantitative information from these images. As the size of the cohorts keeps increasing with large studies, there is a also a need for tools that allow results from automated image processing and analysis to be presented in a way that enables fast and efficient quality checking, tagging and reporting on cases in which automatic processing failed or was problematic.

MATERIALS AND METHODS

MilxXplore is an open source visualization platform, which provides an interface to navigate and explore imaging data in a web browser, giving the end user the opportunity to perform quality control and reporting in a user friendly, collaborative and efficient way.

DISCUSSION

Compared to existing software solutions that often provide an overview of the results at the subject's level, MilxXplore pools the results of individual subjects and time points together, allowing easy and efficient navigation and browsing through the different acquisitions of a subject over time, and comparing the results against the rest of the population.

CONCLUSIONS

MilxXplore is fast, flexible and allows remote quality checks of processed imaging data, facilitating data sharing and collaboration across multiple locations, and can be easily integrated into a cloud computing pipeline. With the growing trend of open data and open science, such a tool will become increasingly important to share and publish results of imaging analysis.

Automated detection, 3D segmentation and analysis of high resolution spine MR images using statistical shape models

Recent advances in high resolution magnetic resonance (MR) imaging of the spine provide a basis for the automated assessment of intervertebral disc (IVD) and vertebral body (VB) anatomy. High resolution three-dimensional (3D) morphological information contained in these images may be useful for early detection and monitoring of common spine disorders, such as disc degeneration. This work proposes an automated approach to extract the 3D segmentations of lumbar and thoracic IVDs and VBs from MR images using statistical shape analysis and registration of grey level intensity profiles. The algorithm was validated on a dataset of volumetric scans of the thoracolumbar spine of asymptomatic volunteers obtained on a 3T scanner using the relatively new 3D T2-weighted SPACE pulse sequence. Manual segmentations and expert radiological findings of early signs of disc degeneration were used in the validation. There was good agreement between manual and automated segmentation of the IVD and VB volumes with the mean Dice scores of 0.89 ± 0.04 and 0.91 ± 0.02 and mean absolute surface distances of 0.55 ± 0.18 mm and 0.67 ± 0.17 mm respectively. The method compares favourably to existing 3D MR segmentation techniques for VBs. This is the first time IVDs have been automatically segmented from 3D volumetric scans and shape parameters obtained were used in preliminary analyses to accurately classify (100% sensitivity, 98.3% specificity) disc abnormalities associated with early degenerative changes.

Beta-amyloid burden in the temporal neocortex is related to hippocampal atrophy in elderly subjects without dementia

OBJECTIVE

To investigate whether global and regional beta-amyloid (Abeta) burden as measured with 11C Pittsburgh compound B (PIB) PET is associated with hippocampal atrophy characterized using MRI in healthy controls and patients with amnestic mild cognitive impairment (aMCI) or Alzheimer disease (AD).

METHODS

Ninety-two elderly healthy controls, 32 subjects with aMCI, and 35 patients with AD were imaged using 11C-PIB PET and MRI. Hippocampal volume was measured and PIB standardized uptake value ratio was extracted after partial volume correction within 41 regions of interest. Global, regional, and voxel-based correlations between PIB and hippocampal volume were computed for each group.

RESULTS

In healthy control participants with elevated neocortex PIB retention, significant correlation was found between PIB retention in the inferior temporal region and hippocampal volume using both region-based and voxel-based approaches. No correlation was found in any other group.

CONCLUSIONS

The strong correlation between hippocampal atrophy and beta-amyloid (Abeta) burden in the Pittsburgh compound B-positive healthy control group suggests that Abeta deposition in the inferior temporal neocortex is related to hippocampal synaptic and neuronal degeneration.

Automated segmentation of the quadratus lumborum muscle from magnetic resonance images using a hybrid atlas based - geodesic active contour scheme

This study presents a novel method for the automatic segmentation of the quadratus lumborum (QL) muscle from axial magnetic resonance (MR) images using a hybrid scheme incorporating the use of non-rigid registration with probabilistic atlases (PAs) and geodesic active contours (GACs). The scheme was evaluated on an MR database of 7mm axial images of the lumbar spine from 20 subjects (fast bowlers and athletic controls). This scheme involved several steps, including (i) image pre-processing, (ii) generation of PAs for the QL, psoas (PS) and erector spinae+multifidus (ES+MT) muscles and (iii) segmentation, using 3D GACs initialized and constrained by the propagation of the PAs using non-rigid registration. Pre-processing of the images involved bias field correction based on local entropy minimization with a bicubic spline model and a reverse diffusion interpolation algorithm to increase the slice resolution to 0.98 x 0.98 x 1.75mm. The processed images were then registered (affine and non-rigid) and used to generate an average atlas. The PAs for the QL, PS and ES+MT were then generated by propagation of manual segmentations. These atlases were further analysed with specialised filtering to constrain the QL segmentation from adjacent non-muscle tissues (kidney, fat). This information was then used in 3D GACs to obtain the final segmentation of the QL. The automatic segmentation results were compared with the manual segmentations using the Dice similarity metric (DSC), with a median DSC for the right and left QL muscles of 0.78 (mean = 0.77, sd=0.07) and 0.75 (mean =0.74, sd=0.07), respectively.