Voxel-based investigations of regional cerebral blood flow abnormalities in Alzheimer's disease using a single-detector SPECT system

Altered cerebral blood flow in older adults with Alzheimer's disease: a systematic review

The prevalence of Alzheimer's disease is projected to reach 13 million in the U.S. by 2050. Although major efforts have been made to avoid this outcome, so far there are no treatments that can stop or reverse the progressive cognitive decline that defines Alzheimer's disease. The utilization of preventative treatment before significant cognitive decline has occurred may ultimately be the solution, necessitating a reliable biomarker of preclinical/prodromal disease stages to determine which older adults are most at risk. Quantitative cerebral blood flow is a promising potential early biomarker for Alzheimer's disease, but the spatiotemporal patterns of altered cerebral blood flow in Alzheimer's disease are not fully understood. The current systematic review compiles the findings of 81 original studies that compared resting gray matter cerebral blood flow in older adults with mild cognitive impairment or Alzheimer's disease and that of cognitively normal older adults and/or assessed the relationship between cerebral blood flow and objective cognitive function. Individuals with Alzheimer's disease had relatively decreased cerebral blood flow in all brain regions investigated, especially the temporoparietal and posterior cingulate, while individuals with mild cognitive impairment had consistent results of decreased cerebral blood flow in the posterior cingulate but more mixed results in other regions, especially the frontal lobe. Most papers reported a positive correlation between regional cerebral blood flow and cognitive function. This review highlights the need for more studies assessing cerebral blood flow changes both spatially and temporally over the course of Alzheimer's disease, as well as the importance of including potential confounding factors in these analyses.

Topography of 11C-Pittsburgh compound B uptake in Alzheimer's disease: a voxel-based investigation of cortical and white matter regions

Objective:

To compare results of positron emission tomography (PET) with carbon-11-labeled Pittsburgh compound B (¹¹C-PIB) obtained with cerebellar or global brain uptake for voxel intensity normalization, describe the cortical sites with highest tracer uptake in subjects with mild Alzheimer’s disease (AD), and explore possible group differences in ¹¹C-PIB binding to white matter.

Methods:

¹¹C-PIB PET scans were acquired from subjects with AD (n=17) and healthy elderly controls (n=19). Voxel-based analysis was performed with statistical parametric mapping (SPM).

Results:

Cerebellar normalization showed higher ¹¹C-PIB uptake in the AD group relative to controls throughout the cerebral cortex, involving the lateral temporal, orbitofrontal, and superior parietal cortices. With global uptake normalization, greatest cortical binding was detected in the orbitofrontal cortex; decreased ¹¹C-PIB uptake in white matter was found in the posterior hippocampal region, corpus callosum, pons, and internal capsule.

Conclusion:

The present case-control voxelwise ¹¹C-PIB PET comparison highlighted the regional distribution of amyloid deposition in the cerebral cortex of mildly demented AD patients. Tracer uptake was highest in the orbitofrontal cortex. Decreased ¹¹C-PIB uptake in white-matter regions in this patient population may be a marker of white-matter damage in AD.

Selecting the most relevant brain regions to discriminate Alzheimer's disease patients from healthy controls using multiple kernel learning: A comparison across functional and structural imaging modalities and atlases

BACKGROUND

Machine learning techniques such as support vector machine (SVM) have been applied recently in order to accurately classify individuals with neuropsychiatric disorders such as Alzheimer's disease (AD) based on neuroimaging data. However, the multivariate nature of the SVM approach often precludes the identification of the brain regions that contribute most to classification accuracy. Multiple kernel learning (MKL) is a sparse machine learning method that allows the identification of the most relevant sources for the classification. By parcelating the brain into regions of interest (ROI) it is possible to use each ROI as a source to MKL (ROI-MKL).

METHODS

We applied MKL to multimodal neuroimaging data in order to: 1) compare the diagnostic performance of ROI-MKL and whole-brain SVM in discriminating patients with AD from demographically matched healthy controls and 2) identify the most relevant brain regions to the classification. We used two atlases (AAL and Brodmann's) to parcelate the brain into ROIs and applied ROI-MKL to structural (T1) MRI, 18F-FDG-PET and regional cerebral blood flow SPECT (rCBF-SPECT) data acquired from the same subjects (20 patients with early AD and 18 controls). In ROI-MKL, each ROI received a weight (ROI-weight) that indicated the region's relevance to the classification. For each ROI, we also calculated whether there was a predominance of voxels indicating decreased or increased regional activity (for 18F-FDG-PET and rCBF-SPECT) or volume (for T1-MRI) in AD patients.

RESULTS

Compared to whole-brain SVM, the ROI-MKL approach resulted in better accuracies (with either atlas) for classification using 18F-FDG-PET (92.5% accuracy for ROI-MKL versus 84% for whole-brain), but not when using rCBF-SPECT or T1-MRI. Although several cortical and subcortical regions contributed to discrimination, high ROI-weights and predominance of hypometabolism and atrophy were identified specially in medial parietal and temporo-limbic cortical regions. Also, the weight of discrimination due to a pattern of increased voxel-weight values in AD individuals was surprisingly high (ranging from approximately 20% to 40% depending on the imaging modality), located mainly in primary sensorimotor and visual cortices and subcortical nuclei.

CONCLUSION

The MKL-ROI approach highlights the high discriminative weight of a subset of brain regions of known relevance to AD, the selection of which contributes to increased classification accuracy when applied to 18F-FDG-PET data. Moreover, the MKL-ROI approach demonstrates that brain regions typically spared in mild stages of AD also contribute substantially in the individual discrimination of AD patients from controls.

Support vector machine-based classification of neuroimages in Alzheimer's disease: direct comparison of FDG-PET, rCBF-SPECT and MRI data acquired from the same individuals

Objective:

To conduct the first support vector machine (SVM)-based study comparing the diagnostic accuracy of T1-weighted magnetic resonance imaging (T1-MRI), F-fluorodeoxyglucose-positron emission tomography (FDG-PET) and regional cerebral blood flow single-photon emission computed tomography (rCBF-SPECT) in Alzheimer’s disease (AD).

Method:

Brain T1-MRI, FDG-PET and rCBF-SPECT scans were acquired from a sample of mild AD patients (n=20) and healthy elderly controls (n=18). SVM-based diagnostic accuracy indices were calculated using whole-brain information and leave-one-out cross-validation.

Results:

The accuracy obtained using PET and SPECT data were similar. PET accuracy was 68∼71% and area under curve (AUC) 0.77∼0.81; SPECT accuracy was 68∼74% and AUC 0.75∼0.79, and both had better performance than analysis with T1-MRI data (accuracy of 58%, AUC 0.67). The addition of PET or SPECT to MRI produced higher accuracy indices (68∼74%; AUC: 0.74∼0.82) than T1-MRI alone, but these were not clearly superior to the isolated neurofunctional modalities.

Conclusion:

In line with previous evidence, FDG-PET and rCBF-SPECT more accurately identified patients with AD than T1-MRI, and the addition of either PET or SPECT to T1-MRI data yielded increased accuracy. The comparable SPECT and PET performances, directly demonstrated for the first time in the present study, support the view that rCBF-SPECT still has a role to play in AD diagnosis.

Absolute SPECT/CT quantification of cerebral uptake of 99mTc-HMPAO for patients with neurocognitive disorders

It was reported from planar imaging studies that the cerebral uptake of injected 99mTc-HMPAO activity is about 4-7% in humans. Recent work has shown that modern SPECT/CT devices are able to quantify the tissue concentration of radioactivity in vivo in absolute units (Bq/ml), while avoiding the limitations of planar techniques. The aims of this study were (a) to determine the cerebral uptake of 99mTc-HMPAO in absolute units in SPECT/CT, (b) to investigate potential differences in absolute tracer uptake for patients suspected of dementia.

PATIENTS, METHODS

We performed 99mTc-HMPAO SPECT/CT in 65 patients with suspected dementia. 99mTc-HMPAO uptake was determined using a previously published quantitative SPECT/CT protocol. The absolute HMPAO uptake and the results of a regionalized analysis were compared for MMSE and NINCDS-ADRDA based patient groups.

RESULTS

The mean absolute uptake of 99mTc-HMPAO for our patient population was 4.3 ± 0.8% of the injected dose. The uptake, as well as the regionalized analysis yielded significantly different results for low (≤23) and high (>23) MMSE groups and also for some of the NINCDS-ADRDA groups.

CONCLUSION

Our results show that the absolute cerebral uptake of 99mTc-HMPAO is in the range of previously reported results, obtained by planar techniques. Absolute uptake is significantly different between the patient groups.

Activity of P-Glycoprotein, a β-Amyloid Transporter at the Blood-Brain Barrier, Is Compromised in Patients with Mild Alzheimer Disease

Studies in animals and postmortem human brain tissue support a role for P-glycoprotein in clearance of cerebral β-amyloid across the blood-brain barrier (BBB). We tested the hypothesis that BBB P-glycoprotein activity is diminished in Alzheimer disease (AD) by accounting for an AD-related reduction in regional cerebral blood flow (rCBF).

METHODS

We compared P-glycoprotein activity in mild-AD patients (n = 9) and cognitively normal, age-matched controls (n = 9) using PET with a labeled P-glycoprotein substrate, (11)C-verapamil, and (15)O-water to measure rCBF. BBB P-glycoprotein activity was expressed as the (11)C-verapamil radioactivity extraction ratio ((11)C-verapamil brain distributional clearance, K1/rCBF).

RESULTS

Compared with controls, BBB P-glycoprotein activity was significantly lower in the parietotemporal, frontal, and posterior cingulate cortices and hippocampus of mild AD subjects.

CONCLUSION

BBB P-glycoprotein activity in brain regions affected by AD is reduced and is independent of rCBF. This study improves on prior work by eliminating the confounding effect that reduced rCBF has on assessment of BBB P-glycoprotein activity and suggests that impaired P-glycoprotein activity may contribute to cerebral β-amyloid accumulation in AD. P-glycoprotein induction or activation to increase cerebral β-amyloid clearance could constitute a novel preventive or therapeutic strategy for AD.

Cerebral perfusion (HMPAO-SPECT) in patients with depression with cognitive impairment versus those with mild cognitive impairment and dementia of Alzheimer's type: a semiquantitative and automated evaluation

PURPOSE

Comparative evaluation of regional brain perfusion measured by HMPAO-SPECT of patients with mild cognitive impairment (MCI), dementia of Alzheimer's type (DAT) and depression with cognitive impairment (DCI).

METHODS

A total of 736 patients were investigated because of suspected cognitive dysfunction. After exclusion of patients with other forms of dementia than DAT or relevant accompanying disorders, SPECT data from 149 MCI, 131 DAT and 127 DCI patients, and 123 controls without any cognitive impairment, were analysed. Relative cerebral blood flow of 34 anatomical regions was assessed with automated analysis software (BRASS).

RESULTS

Calculation of global forebrain perfusion discriminated demented from nondemented patients. Compared to controls DCI patients showed hypoperfusion of the thalamus, lentiform nucleus and medial temporal cortex. MCI patients differed significantly from controls concerning perfusion in both hemispheric temporal and parietal areas, and in the (right hemispheric) posterior part of the cingulate gyrus. MCI and DCI patients differed in the parietal, temporal superior and right hemispheric cingulate gyrus posterior cortices. Global forebrain and regional perfusion was more extensively reduced in DAT patients and discriminated them from controls, and MCI and DCI patients. Frontal perfusion disturbance was only present in DAT patients.

CONCLUSION

Automated analysis of HMPAO-SPECT data from MCI patients showed significant perfusion deficits in regions also involved in DAT patients, but ROC analysis demonstrated only moderate sensitivity and specificity for differentiating DAT patients from controls and DCI patients. Frontal hypoperfusion seems to correspond with conversion from MCI to DAT. Finally, the results in DCI patients again raise the question of depression as an early symptom of neurodegeneration.

Combining cognitive screening tests for the evaluation of mild cognitive impairment in the elderly

OBJECTIVE

To determine the accuracy of the Mini-Mental State Examination combined with the Verbal Fluency Test and Clock Drawing Test for the identification of patients with mild cognitive impairment and Alzheimer's disease (AD).

METHOD

These tests were used to evaluate cognitive function in 247 older adults. Subjects were divided into three groups according to their cognitive state: mild cognitive impairment (n=83), AD (n=81), cognitively unimpaired controls (n=83), based on clinical and neuropsychological data. The diagnostic accuracy of each test for discriminating between these diagnostic groups (mild cognitive impairment or AD vs. controls) was examined with the aid of Receiver Operating Characteristic (ROC) curves. Additionally, we evaluated the benefit of the combination of tests on diagnostic accuracy.

RESULTS

Although they were accurate enough for the identification of Alzheimer's disease, neither test alone proved adequate for the correct separation of patients with mild cognitive impairment from healthy subjects. Combining these tests did not improve diagnostic accuracy, as compared to the Mini-Mental State Examination alone, in the identification of patients with mild cognitive impairment or Alzheimer's disease.

CONCLUSIONS

The present data do not warrant the combined use of the Mini-Mental State Examination, the Verbal Fluency Test and the Clock Drawing Test as a sufficient diagnostic schedule in screening for mild cognitive impairment. The present data do not support the notion that the combination of test scores is better that the use of Mini-Mental State Examination scores alone in the screening for Alzheimer's disease.