Richard G. Boyes

3D characterization of brain atrophy in Alzheimer's disease and mild cognitive impairment using tensor-based morphometry

Tensor-based morphometry (TBM) creates three-dimensional maps of disease-related differences in brain structure, based on nonlinearly registering brain MRI scans to a common image template. Using two different TBM designs (averaging individual differences versus aligning group average templates), we compared the anatomical distribution of brain atrophy in 40 patients with Alzheimers disease (AD), 40 healthy elderly controls, and 40 individuals with amnestic mild cognitive impairment (aMCI), a condition conferring increased risk for AD. We created an unbiased geometrical average image template for each of the three groups, which were matched for sex and age (mean age: 76.1 years+/-7.7 SD). We warped each individual brain image (N=120) to the control group average template to create Jacobian maps, which show the local expansion or compression factor at each point in the image, reflecting individual volumetric differences. Statistical maps of group differences revealed widespread medial temporal and limbic atrophy in AD, with a lesser, more restricted distribution in MCI. Atrophy and CSF space expansion both correlated strongly with Mini-Mental State Exam (MMSE) scores and Clinical Dementia Rating (CDR). Using cumulative p-value plots, we investigated how detection sensitivity was influenced by the sample size, the choice of search region (whole brain, temporal lobe, hippocampus), the initial linear registration method (9- versus 12-parameter), and the type of TBM design. In the future, TBM may help to (1) identify factors that resist or accelerate the disease process, and (2) measure disease burden in treatment trials.

Volumetric MRI and cognitive measures in Alzheimer disease : comparison of markers of progression.

BackgroundBoth cognitive tests and MRI-based measures have been suggested as outcomes in trials assessing disease-modifying therapies in Alzheimers disease (AD).ObjectiveTo compare changes in longitudinal MRI measures with changes in performance on cognitive tests routinely used in AD clinical trials.MethodFifty-two subjects from the placebo-arm of a clinical trial in mild-to-moderate AD had volumetric T1-weighted scans and cognitive tests including the Mini-Mental State Examination (MMSE), AD Assessment Scale-Cognitive Subscale, Disability Assessment for Dementia, AD Cooperative Study-Clinical Global Impression of Change and Clinical Dementia Rating at baseline and one-year later. Rates of brain atrophy and ventricular enlargement were measured using the boundary shift integral. Hippocampal (Hc) atrophy was calculated from manual volume measurements. The relationships between MRI and cognitive measures were investigated.ResultsRates of brain atrophy and/or ventricular enlargement were correlated with declining performance on cognitive scales. The strongest association was between brain atrophy rate and MMSE decline (r = 0.59, p < 0.0001). Hc atrophy rate was not significantly correlated with any of the cognitive scales.ConclusionThe lack of correlation between Hc atrophy and cognitive scales may reflect a combination of: the extensive functional damage to the Hc by the time AD is clinically established, the greater influence of ongoing cortical degeneration, and errors in Hc outlining. The strong correlations between brain atrophy and ventricular enlargement, and cognitive scales probably reflect the correspondence between these measures of overall cerebral loss and global cognitive measures in the moderate stages of AD.

A comparison of methods for the automated calculation of volumes and atrophy rates in the hippocampus

Hippocampal atrophy rates have been used in a number of studies in Alzheimers disease (AD) to assess disease progression and are being increasingly utilized as an outcome measure in clinical trials of new pharmaceutical agents. Owing to the labor-intensive nature of hippocampal segmentation, more automated approaches are required for such analysis. In this study we compared methods of automatically segmenting the hippocampus (single-person template and template library) on the baseline image in a group of probable AD (n=36) and control (n=19) subjects with serial images. Using the method that gave most similar results to manual, three automated methods of calculating change within the hippocampal region were compared: fluid change calculated using (1) Jacobian change or (2) region propagation and (3) boundary shift. Rates were compared with manual measures. We found that segmentation of baseline hippocampus was most accurate using a template library combined with morphological operations (intensity thresholding plus one conditional dilation). This gave a voxel similarity of 0.69 (0.05) and 0.72 (0.06) in controls and probable AD subjects respectively compared with manual measures. Atrophy rates within these regions were most similar to the manual rates using the boundary shift integral (mean difference from manual rate 0.03% (1.29) in controls and 0.48% (2.44) in AD). A template library segmentation approach, together with morphological operations, provides a segmentation accurate enough to quantify relative change over time. The change over time can then be calculated automatically using boundary shift or fluid measures, with boundary shift giving most similar results to manual.

Intensity non-uniformity correction using N3 on 3-T scanners with multichannel phased array coils

Measures of structural brain change based on longitudinal MR imaging are increasingly important but can be degraded by intensity non-uniformity. This non-uniformity can be more pronounced at higher field strengths, or when using multichannel receiver coils. We assessed the ability of the non-parametric non-uniform intensity normalization (N3) technique to correct non-uniformity in 72 volumetric brain MR scans from the preparatory phase of the Alzheimers Disease Neuroimaging Initiative (ADNI). Normal elderly subjects (n=18) were scanned on different 3-T scanners with a multichannel phased array receiver coil at baseline, using magnetization prepared rapid gradient echo (MP-RAGE) and spoiled gradient echo (SPGR) pulse sequences, and again 2 weeks later. When applying N3, we used five brain masks of varying accuracy and four spline smoothing distances (d=50, 100, 150 and 200 mm) to ascertain which combination of parameters optimally reduces the non-uniformity. We used the normalized white matter intensity variance (standard deviation/mean) to ascertain quantitatively the correction for a single scan; we used the variance of the normalized difference image to assess quantitatively the consistency of the correction over time from registered scan pairs. Our results showed statistically significant (p<0.01) improvement in uniformity for individual scans and reduction in the normalized difference image variance when using masks that identified distinct brain tissue classes, and when using smaller spline smoothing distances (e.g., 50-100 mm) for both MP-RAGE and SPGR pulse sequences. These optimized settings may assist future large-scale studies where 3-T scanners and phased array receiver coils are used, such as ADNI, so that intensity non-uniformity does not influence the power of MR imaging to detect disease progression and the factors that influence it.

Differentiating AD from aging using semiautomated measurement of hippocampal atrophy rates

Manual segmentation of the hippocampus is the gold standard in volumetric hippocampal magnetic resonance imaging (MRI) analysis; however, this is difficult to achieve reproducibly. This study explores whether application of local registration and calculation of the hippocampal boundary shift integral (HBSI) can reduce random variation compared with manual measures. Hippocampi were outlined on the baseline and registered-repeat MRIs of 32 clinically diagnosed Alzheimers disease (AD) patients and 47 matched controls (37-86 years) with a wide range of scanning intervals (175-1173 days). The scans were globally registered using 9 degrees of freedom and subsequently locally registered using 6 degrees of freedom and HBSI was then calculated automatically. HBSI significantly reduced the mean rate (P < 0.01) and variation in controls (P < 0.001) and increased group separation between AD cases and controls. When comparing HBSI atrophy rates with manually derived atrophy rates at 90% sensitivity, specificities were 98% and 81%, respectively. From logistic regression models, a 1% increase in HBSI atrophy rates was associated with an 11-fold (CI 3, 36) increase in the odds of a diagnosis of AD. For manually derived atrophy rates, the equivalent odds ratio was 3 (CI 2,4). We conclude that HBSI-derived atrophy rates reduce operator time and error, and are at least as effective as the manual equivalent as a diagnostic marker and are a potential marker of progression in longitudinal studies and trials.

Atrophy rates of the cingulate gyrus and hippocampus in AD and FTLD

This study explores the diagnostic utility of atrophy rates of the cingulate gyrus, its subdivisions and the hippocampus in Alzheimers disease (AD) and frontotemporal lobar degeneration (FTLD). Regions were manually outlined on MR images of a group of pathologically or genetically confirmed patients with AD (n=19), FTLD (n=8) and age-matched controls (n=11). Mean (S.D.) atrophy rates (%year(-1)) in the cingulate in controls, AD and FTLD were -0.3 (1.2), 5.9 (3.5), and 8.6 (4.1), respectively. Hippocampal atrophy rates in controls, AD and FTLD were -0.1 (0.8), 3.4 (2.2), and 5.2 (5.4), respectively. Atrophy rates were significantly higher in the cingulate and hippocampi in AD and FTLD compared with controls (p<0.01). There was evidence of a difference in trends of atrophy in the cingulate (more anterior in FTLD and more posterior in AD) between the disease groups (p=0.03). Cingulate atrophy rates discriminated perfectly between FTLD and controls. Significantly better discrimination between AD and controls was obtained by hippocampal rather than cingulate rates. In conclusion, cingulate atrophy is as significant a feature of AD and FTLD as hippocampal atrophy.

Cerebral atrophy measurements using Jacobian integration: Comparison with the boundary shift integral

We compared two methods of measuring cerebral atrophy in a cohort of 38 clinically probable Alzheimers disease (AD) subjects and 22 age-matched normal controls, using metrics of zero atrophy, consistency, scaled atrophy and AD/control group separation. The two methods compared were the boundary shift integral (BSI) and a technique based on the integration of Jacobian determinants from non-rigid registration. For each subject, we used two volumetric magnetic resonance (MR) scans at baseline and a third obtained 1 year later. The case of zero atrophy was established by registering the same-day baseline scan pair, which should approximate zero change. Consistency was established by registering the 1-year follow-up scan to each of the baseline scans, giving two measurements of atrophy that should be very similar, while scaled atrophy was established by reducing one of the same-day scans by a fixed amount, and rigidly registering this to the other same-day scan. Group separation was ascertained by calculating atrophy rates over the two 1-year measures for the control and AD subjects. The results showed the Jacobian integration technique was significantly more accurate in calculating scaled atrophy (P < 0.001) and was able to distinguish between control and AD subjects more clearly (P < 0.01).

Automatic calculation of hippocampal atrophy rates using a hippocampal template and the boundary shift integral.

We describe a method of automatically calculating hippocampal atrophy rates on T1-weighted MR images without manual delineation of hippocampi. This method was applied to a group of Alzheimers disease (AD) (n=36) and control (n=19) subjects and compared with manual methods (manual segmentation of baseline and repeat-image hippocampi) and semi-automated methods (manual segmentation of baseline hippocampi only). In controls, mean (S.D.) atrophy rates for manual, semi-automated, and automated methods were 18.1 (53.5), 15.3 (50.2) and 11.3 (50.4) mm3 loss per year, respectively. In AD patients these rates were 174.6 (106.5) 159.4 (101.2) and 172.1 (123.1) mm3 loss per year, respectively. The automated method was a significant predictor of disease (p=0.001) and gave similar group discrimination compared with both semi-automated and manual methods. The automated hippocampal analysis in this small study took approximately 20 min per hippocampal pair on a 3.4 GHz Intel Xeon server, whereas manual delineation of each hippocampal pair took approximately 90 min of operator-intensive labour. This method may be useful diagnostically or in studies where analysis of many scans may be required.

Combining short interval MRI in Alzheimer’s disease

Cerebral atrophy calculated from serial MRI is a marker of Alzheimer’s disease (AD) progression, and a potential outcome measure for therapeutic trials. Reducing within-subject variability in cerebral atrophy rates by acquiring more than two serial scans could allow for shorter clinical trials requiring smaller patient numbers. Forty-six patients with AD and 23 controls each had up to 10 serial MR brain scans over two years. Whole brain atrophy was calculated for each subject from every scan-pair. 708 volumetric MRI scans were acquired: 2199 measures of atrophy were made for patients, and 1182 for controls. A linear mixed model was used to characterise between and within-individual variability. These results were used to investigate the power of combining multiple serial scans in treatment trials of varying lengths.In AD, the mean whole brain atrophy rate was 2.23%/year (95% CI: 1.90–2.56%/year). The linear mixed model was shown to fit the data well and led to a formula (0.992+(0.82/t)2) for the variance of atrophy rates calculated from two scans “t” years apart. Utilising five optimally timed scans with repeat scans at each visit reduced the component of atrophy rate variance attributable to within-subject variability by ~ 56%, equating to a ~ 40% sample size reduction (228 vs 387 patients per arm to detect 20% reduction in atrophy rate) in a six-month placebo-controlled trial. This benefit in terms of sample size is relatively reduced in longer trials, although adding extra scanning visits may have benefits when patient drop-outs are accounted for. We conclude that sample sizes required in short interval therapeutic trials using cerebral atrophy as an outcome measure may be reduced if multiple serial MRI is performed

Improved reliability of hippocampal atrophy rate measurement in mild cognitive impairment using fluid registration.

MRI-derived rates of hippocampal atrophy may serve as surrogate markers of disease progression in mild cognitive impairment (MCI). Manual delineation is the gold standard in hippocampal volumetry; however, this technique is time-consuming and subject to errors. We aimed to compare regional non-linear (fluid) registration measurement of hippocampal atrophy rates against manual delineation in MCI. Hippocampi of 18 subjects were manually outlined twice on MRI scan-pairs (interval+/-SD: 2.01+/-0.11 years), and volumes were subtracted to calculate change over time. Following global affine and local rigid registration, regional fluid registration was performed from which atrophy rates were derived from the Jacobian determinants over the hippocampal region. Atrophy rates as derived by fluid registration were computed using both forward (repeat onto baseline) and backward (baseline onto repeat) registration. Reliability for both methods and agreement between methods was assessed. Mean+/-SD hippocampal atrophy rates (%/year) derived by manual delineation were: left: 2.13+/-1.62; right: 2.36+/-1.78 and for regional fluid registration: forward: left: 2.39+/-1.68; right: 2.49+/-1.52 and backward: left: 2.21+/-1.51; right: 2.42+/-1.49. Mean hippocampal atrophy rates did not differ between both methods. Reliability for manual hippocampal volume measurements (cross-sectional) was high (intraclass correlation coefficient (ICC): baseline and follow-up, left and right, >0.99). However, the resulting ICC for manual measurements of hippocampal volume change (longitudinal) was considerably lower (left: 0.798; right: 0.850) compared with regional fluid registration (forward: left: 0.985; right: 0.988 and backward: left: 0.975; right: 0.989). We conclude that regional fluid registration is more reliable than manual delineation in assessing hippocampal atrophy rates, without sacrificing sensitivity to change. This method may be useful to quantify hippocampal volume change, given the reduction in operator time and improved precision.