The anteroposterior and primary-to-posterior limbic ratios as MRI-derived volumetric markers of Alzheimer's disease

Adapting UK Biobank imaging for use in a routine memory clinic setting: The Oxford Brain Health Clinic

The Oxford Brain Health Clinic (BHC) is a joint clinical-research service that provides memory clinic patients and clinicians access to high-quality assessments not routinely available, including brain MRI aligned with the UK Biobank imaging study (UKB). In this work we present how we 1) adapted the UKB MRI acquisition protocol to be suitable for memory clinic patients, 2) modified the imaging analysis pipeline to extract measures that are in line with radiology reports and 3) explored the alignment of measures from BHC patients to the largest brain MRI study in the world (ultimately 100,000 participants). Adaptations of the UKB acquisition protocol for BHC patients include dividing the scan into core and optional sequences (i.e., additional imaging modalities) to improve patients' tolerance for the MRI assessment. We adapted the UKB structural MRI analysis pipeline to take into account the characteristics of a memory clinic population (e.g., high amount of white matter hyperintensities and hippocampal atrophy). We then compared the imaging derived phenotypes (IDPs) extracted from the structural scans to visual ratings from radiology reports, non-imaging factors (age, cognition) and to reference distributions derived from UKB data. Of the first 108 BHC attendees (August 2020-November 2021), 92.5 % completed the clinical scans, 88.0 % consented to use of data for research, and 43.5 % completed the additional research sequences, demonstrating that the protocol is well tolerated. The high rates of consent to research makes this a valuable real-world quality research dataset routinely captured in a clinical service. Modified tissue-type segmentation with lesion masking greatly improved grey matter volume estimation. CSF-masking marginally improved hippocampal segmentation. The IDPs were in line with radiology reports and showed significant associations with age and cognitive performance, in line with the literature. Due to the age difference between memory clinic patients of the BHC (age range 65-101 years, average 78.3 years) and UKB participants (44-82 years, average 64 years), additional scans on elderly healthy controls are needed to improve reference distributions. Current and future work aims to integrate automated quantitative measures in the radiology reports and evaluate their clinical utility.

Comparative analysis of methods of volume adjustment in hippocampal volumetry for the diagnosis of Alzheimer disease

INTRODUCTION

Hippocampal volumetry can discriminate normal subjects from patients with amnestic mild cognitive impairment (MCI) or Alzheimer disease (AD). We have analyzed the effects of different methods of hippocampal volume (HV) adjustment on the diagnostic accuracy of this technique.

METHODS

Cross-sectional analysis of 148 subjects of the ADNI database (48 normal, 66 MCI, 34 AD). Brain volumes were calculated from 3T MRI scans with gm extractor, a fully automated script based on FSL. A series of logistic regression models was obtained using 9 volumes of reference and 3 methods of adjustment (normalization, covariance, bilinear regression). Diagnostic accuracy was evaluated with the receiver operating characteristic curve method. External validity was assessed with 10-fold cross-validation.

RESULTS

The models with the highest area under the curve (AUC) were those including the HV normalized by total intracranial volume (TIV). The differences with bilinear regression and the covariance method adjusted by TIV were minor and not statistically significant. The lowest AUCs corresponded to the models based on raw (unadjusted) HVs. The results were qualitatively similar in two clinical settings (normal versus MCI, and normal versus AD), but the differences were higher in the normal versus MCI context.

CONCLUSION

The accuracy of hippocampal volumetry for the differential diagnosis between normal subjects and patients with MCI or AD was maximized by normalizing the HV by the TIV. Our results do not exclude the potential superiority of non-linear models.