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Objective: To investigate whether baseline CSF biomarkers are associated with hippocampal atrophy rate as a measure of disease progression in patients with Alzheimer disease (AD), patients with mild cognitive impairment (MCI), and controls, controlling for baseline neuropsychological and MRI findings., Methods: We assessed data from 31 patients with AD, 25 patients with MCI, and 19 controls (mean age 68 +/- 8 years; 39 [52%] female) who visited our memory clinic and had received serial MRI scanning (scan interval 1.7 +/- 0.7 years). At baseline, CSF biomarkers (amyloid beta 1-42, tau, and tau phosphorylated at threonine 181 [p-tau]) were obtained, as well as neuropsychological data. Baseline MRI scans were assessed using visual rating scales for medial temporal lobe atrophy (MTA), global cortical atrophy, and white matter hyperintensities. Hippocampal atrophy rates were estimated using regional nonlinear "fluid" registration of follow-up scan to baseline scan., Results: Stepwise multiple linear regression, adjusted for age and sex, showed that increased CSF p-tau levels (beta [standard error]: -0.79 [0.35]) at baseline was independently associated with higher subsequent hippocampal atrophy rates (p < 0.05), together with poorer memory performance (0.09 [0.04]) and more severe MTA (-0.60 [0.21]). The association of memory function with hippocampal atrophy rate was explained by the link with diagnosis, because it disappeared from the model after we additionally corrected for diagnosis., Conclusions: Baseline CSF levels of tau phosphorylated at threonine 181 are independently associated with subsequent disease progression, as reflected by hippocampal atrophy rate. This effect is independent of baseline neuropsychological and MRI predictors. Our results imply that predicting disease progression can best be achieved by combining information from different modalities.

Objective: To investigate the added value of hippocampal atrophy rates over whole brain volume measurements on MRI in patients with Alzheimer disease (AD), patients with mild cognitive impairment (MCI), and controls., Methods: We included 64 patients with AD (67 +/- 9 years; F/M 38/26), 44 patients with MCI (71 +/- 6 years; 21/23), and 34 controls (67 +/- 9 years; 16/18). Two MR scans were performed (scan interval: 1.8 +/- 0.7 years; 1.0 T), using a coronal three-dimensional T1-weighted gradient echo sequence. At follow-up, 3 controls and 23 patients with MCI had progressed to AD. Hippocampi were manually delineated at baseline. Hippocampal atrophy rates were calculated using regional, nonlinear fluid registration. Whole brain baseline volumes and atrophy rates were determined using automated segmentation and registration tools., Results: All MRI measures differed between groups (p < 0.005). For the distinction of MCI from controls, larger effect sizes of hippocampal measures were found compared to whole brain measures. Between MCI and AD, only whole brain atrophy rate differed significantly. Cox proportional hazards models (variables dichotomized by median) showed that within all patients without dementia, hippocampal baseline volume (hazard ratio [HR]: 5.7 [95% confidence interval: 1.5-22.2]), hippocampal atrophy rate (5.2 [1.9-14.3]), and whole brain atrophy rate (2.8 [1.1-7.2]) independently predicted progression to AD; the combination of low hippocampal volume and high atrophy rate yielded a HR of 61.1 (6.1-606.8). Within patients with MCI, only hippocampal baseline volume and atrophy rate predicted progression., Conclusion: Hippocampal measures, especially hippocampal atrophy rate, best discriminate mild cognitive impairment (MCI) from controls. Whole brain atrophy rate discriminates Alzheimer disease (AD) from MCI. Regional measures of hippocampal atrophy are the strongest predictors of progression to AD.

We measured hippocampi on baseline-, 6- and 12-month scans in a group of AD (n=36) and control subjects (n=20). We found that mean annualised atrophy rates using 6-month intervals were comparable at a group level to those generated from a 12-month interval. Higher variance was seen using shorter intervals, although this was only significant in the control group. This has implications where shorter inter-scan intervals may be advantageous, such as rapid diagnosis, and tracking of disease progression including in a clinical trial.

Hippocampal atrophy rates have been used in a number of studies in Alzheimer's 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.

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 Alzheimer's 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.

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.