Local MRI analysis approach in the diagnosis of early and prodromal Alzheimer's disease.

BACKGROUND: Medial temporal lobe (MTL) atrophy is one of the key biomarkers to detect early neurodegenerative changes in the course of Alzheimer's disease (AD). There is active research aimed at identifying automated methodologies able to extract accurate classification indexes from T1-weighted magnetic resonance images (MRI). Such indexes should be fit for identifying AD patients as early as possible. SUBJECTS: A reference group composed of 144AD patients and 189 age-matched controls was used to train and test the procedure. It was then applied on a study group composed of 302 MCI subjects, 136 having progressed to clinically probable AD (MCI-converters) and 166 having remained stable or recovered to normal condition after a 24month follow-up (MCI-non converters). All subjects came from the ADNI database. METHODS: We sampled the brain with 7 relatively small volumes, mainly centered on the MTL, and 2 control regions. These volumes were filtered to give intensity and textural MRI-based features. Each filtered region was analyzed with a Random Forest (RF) classifier to extract relevant features, which were subsequently processed with a Support Vector Machine (SVM) classifier. Once a prediction model was trained and tested on the reference group, it was used to compute a classification index (CI) on the MCI cohort and to assess its accuracy in predicting AD conversion in MCI patients. The performance of the classification based on the features extracted by the whole 9 volumes is compared with that derived from each single volume. All experiments were performed using a bootstrap sampling estimation, and classifier performance was cross-validated with a 20-fold paradigm. RESULTS: We identified a restricted set of image features correlated with the conversion to AD. It is shown that most information originate from a small subset of the total available features, and that it is enough to give a reliable assessment. We found multiple, highly localized image-based features which alone are responsible for the overall clinical diagnosis and prognosis. The classification index is able to discriminate Controls from AD with an Area Under Curve (AUC)=0.97 (sensitivity ≃89% at specificity ≃94%) and Controls from MCI-converters with an AUC=0.92 (sensitivity ≃89% at specificity ≃80%). MCI-converters are separated from MCI-non converters with AUC=0.74(sensitivity ≃72% at specificity ≃65%). FINDINGS: The present automated MRI-based technique revealed a strong relationship between highly localized baseline-MRI features and the baseline clinical assessment. In addition, the classification index was also used to predict the probability of AD conversion within a time frame of two years. The definition of a single index combining local analysis of several regions can be useful to detect AD neurodegeneration in a typical MCI population.

Automatic lung segmentation in CT images with accurate handling of the hilar region.

A fully automated and three-dimensional (3D) segmentation method for the identification of the pulmonary parenchyma in thorax X-ray computed tomography (CT) datasets is proposed. It is meant to be used as pre-processing step in the computer-assisted detection (CAD) system for malignant lung nodule detection that is being developed by the Medical Applications in a Grid Infrastructure Connection (MAGIC-5) Project. In this new approach the segmentation of the external airways (trachea and bronchi), is obtained by 3D region growing with wavefront simulation and suitable stop conditions, thus allowing an accurate handling of the hilar region, notoriously difficult to be segmented. Particular attention was also devoted to checking and solving the problem of the apparent 'fusion' between the lungs, caused by partial-volume effects, while 3D morphology operations ensure the accurate inclusion of all the nodules (internal, pleural, and vascular) in the segmented volume. The new algorithm was initially developed and tested on a dataset of 130 CT scans from the Italung-CT trial, and was then applied to the ANODE09-competition images (55 scans) and to the LIDC database (84 scans), giving very satisfactory results. In particular, the lung contour was adequately located in 96% of the CT scans, with incorrect segmentation of the external airways in the remaining cases. Segmentation metrics were calculated that quantitatively express the consistency between automatic and manual segmentations: the mean overlap degree of the segmentation masks is 0.96 ± 0.02, and the mean and the maximum distance between the mask borders (averaged on the whole dataset) are 0.74 ± 0.05 and 4.5 ± 1.5, respectively, which confirms that the automatic segmentations quite correctly reproduce the borders traced by the radiologist. Moreover, no tissue containing internal and pleural nodules was removed in the segmentation process, so that this method proved to be fit for the use in the framework of a CAD system. Finally, in the comparison with a two-dimensional segmentation procedure, inter-slice smoothness was calculated, showing that the masks created by the 3D algorithm are significantly smoother than those calculated by the 2D-only procedure.

Automatic analysis of medial temporal lobe atrophy from structural MRIs for the early assessment of Alzheimer disease.

The purpose of this study is to develop a software for the extraction of the hippocampus and surrounding medial temporal lobe (MTL) regions from T1-weighted magnetic resonance (MR) images with no interactive input from the user, to introduce a novel statistical indicator, computed on the intensities in the automatically extracted MTL regions, which measures atrophy, and to evaluate the accuracy of the newly developed intensity-based measure of MTL atrophy to (a) distinguish between patients with Alzheimer disease (AD), patients with amnestic mild cognitive impairment (aMCI), and elderly controls by using established criteria for patients with AD and aMCI as the reference standard and (b) infer about the clinical outcome of aMCI patients. For the development of the software, the study included 61 patients with mild AD (17 men, 44 women; mean age +/- standard deviation (SD), 75.8 years +/- 7.8; Mini Mental State Examination (MMSE) score, 24.1 +/- 3.1), 42 patients with aMCI (11 men, 31 women; mean age +/- SD, 75.2 years +/- 4.9; MMSE score, 27.9 +/- 1.9), and 30 elderly healthy controls (10 men, 20 women; mean age +/- SD, 74.7 years +/- 5.2; MMSE score, 29.1 +/- 0.8). For the evaluation of the statistical indicator, 150 patients with mild AD (62 men, 88 women; mean age +/- SD, 76.3 years +/- 5.8; MMSE score, 23.2 +/- 4.1), 247 patients with aMCI (143 men, 104 women; mean age +/- SD, 75.3 years +/- 6.7; MMSE score, 27.0 +/- 1.8), and 135 elderly healthy controls (61 men, 74 women; mean age +/- SD, 76.4 years +/- 6.1). Fifty aMCI patients were evaluated every 6 months over a 3 year period to assess conversion to AD. For each participant, two subimages of the MTL regions were automatically extracted from T1-weighted MR images with high spatial resolution. An intensity-based MTL atrophy measure was found to separate control, MCI, and AD cohorts. Group differences were assessed by using two-sample t test. Individual classification was analyzed by using receiver operating characteristic (ROC) curves. Compared to controls, significant differences in the intensity-based MTL atrophy measure were detected in both groups of patients (AD vs controls, 0.28 +/- 0.03 vs 0.34 +/- 0.03, P < 0.001; aMCI vs controls, 0.31 +/- 0.03 vs 0.34 +/- 0.03, P < 0.001). Moreover, the subgroup of aMCI converters was significantly different from controls (0.27 +/- 0.034 vs 0.34 +/- 0.03, P < 0.001). Regarding the ROC curve for intergroup discrimination, the area under the curve was 0.863 for AD patients vs controls, 0.746 for all aMCI patients vs controls, and 0.880 for aMCI converters vs controls. With specificity set at 85%, the sensitivity was 74% for AD vs controls, 45% for aMCI vs controls, and 83% for aMCI converters vs controls. The automated analysis of MTL atrophy in the segmented volume is applied to the early assessment of AD, leading to the discrimination of aMCI converters with an average 3 year follow-up. This procedure can provide additional useful information in the early diagnosis of AD.

Brain SPECT in subtypes of mild cognitive impairment. Findings from the DESCRIPA multicenter study.

The Development of Screening Guidelines and Clinical Criteria of Predementia Alzheimer's Disease (DESCRIPA) multicenter study enrolled patients with MCI or subjective cognitive complaints (SUBJ), a part of whom underwent optional brain perfusion SPECT. These patients were classified as SUBJ (n = 23), nonamnestic MCI (naMCI; n = 17) and amnestic MCI (aMCI; n = 40) based on neuropsychology. Twenty healthy subjects formed the control (CTR) group. Volumetric regions of interest (VROI) analysis was performed in six associative cortical areas in each hemisphere. ANOVA for repeated measures, corrected for age and center, showed significant differences between groups (p = 0.01) and VROI (p < 0.0001) with a significant group-region interaction (p = 0.029). In the post hoc comparison, SUBJ did not differ from CTR. aMCI disclosed reduced uptake in the left hippocampus and bilateral temporal cortex (compared with CTR) or in the left hippocampus and bilateral parietal cortex (compared with SUBJ). In the naMCI group, reduced VROI values were found in the bilateral temporal cortex and right frontal cortex. In the comparison between aMCI and naMCI, the former had lower values in the left parietal cortex and precuneus. Discriminant analysis between SUBJ/CTR versus all MCI patients allowed correct allocations in 73 % of cases. Mean VROI values were highly correlated (p < 0.0001) with the learning measure of a verbal memory test, especially in the bilateral precunei and parietal cortex and in the left hippocampus. In a subset of 70 patients, mean VROI values showed a significant correlation (p < 0.05) with the white matter hyperintensities score on MRI. In conclusion, MCI subtypes have different perfusion patterns. The aMCI group exhibited a pattern that is typical of early Alzheimer's disease, while the naMCI group showed a more anterior pattern of hypoperfusion. Instead, a homogeneous group effect was lacking in SUBJ.

The basal ganglia matching tools package for striatal uptake semi-quantification: description and validation.

PURPOSE: To design a novel algorithm (BasGan) for automatic segmentation of striatal (123)I-FP-CIT SPECT. METHODS: The BasGan algorithm is based on a high-definition, three-dimensional (3D) striatal template, derived from Talairach's atlas. A blurred template, obtained by convolving the former with a 3D Gaussian kernel (FWHM = 10 mm), approximates striatal activity distribution. The algorithm performs translations and scale transformation on the bicommissural aligned image to set the striatal templates with standard size in an appropriate initial position. An optimization protocol automatically performs fine adjustments in the positioning of blurred templates to best match the radioactive counts, and locates an occipital ROI for background evaluation. Partial volume effect correction is included in the process of uptake computation of caudate, putamen and background. Experimental validation was carried out by means of six acquisitions of an anthropomorphic striatal phantom. The BasGan software was applied to a first set of patients with Parkinson's disease (PD) versus patients affected by essential tremor. RESULTS: A highly significant correlation was achieved between true binding potential and measured (123)I activity from the phantom. (123)I-FP-CIT uptake was significantly lower in all basal ganglia in the PD group versus controls with both BasGan and a conventional ROI method used for comparison, but particularly with the former. Correlations with the motor UPDRS score were far more significant with the BasGan. CONCLUSION: The novel BasGan algorithm automatically performs the 3D segmentation of striata. Because co-registered MRI is not needed, it can be used by all nuclear medicine departments, since it is freely available on the Web.

Resting SPECT-neuropsychology correlation in very mild Alzheimer's disease.

OBJECTIVE: To investigate the relationships between brain function and some of the most frequently impaired cognitive domains in the first stages of Alzheimer's disease (AD), we searched for correlation between the scores on 3 neuropsychological tests and brain perfusion, assessed by single photon emission computed tomography (SPECT) in patients with very mild AD. METHODS: Twenty-nine consecutive outpatients (mean age 78.2+/-5.5) affected by probable AD in the very mild phase (i.e. with a score > or =20 on the mini-mental state examination, MMSE) underwent brain SPECT with (99m)Tc-ethylcisteinate dimer. For correlative purposes, word list learning (by the selective reminding test, SRT), constructional praxis test (CPT) and visual search test (VST) were chosen a priori out of an extended battery employed to diagnose AD at first patient evaluation. Voxel-based correlation analysis was achieved by statistical parametric mapping (SPM99) with a height threshold of P=0.005. Age, years of education and the MMSE score were inserted in the correlative analysis as confounding variables. RESULTS: The SRT score showed correlation with brain perfusion in 3 clusters of the left hemisphere, including the post-central gyrus, the parietal precuneus, the inferior parietal lobule and the middle temporal gyrus, and in one cluster in the right hemisphere including the middle temporal gyrus and the middle occipital gyrus. The CPT score was significantly correlated with brain perfusion in the parietal precuneus and the posterior cingulate gyrus in the left hemisphere, whereas the VST score gave a significant correlation with brain perfusion in a left cluster including the parietal precuneus and the superior temporal gyrus. CONCLUSIONS: Cognitive impairment in very mild AD is reflected by brain dysfunction in posterior associative areas, with peculiar topographical differences proper of each domain. The parietal precuneus was a common site of correlation of all 3 neuropsychological tests. This region, together with the posterior cingulate and the superficial posterior temporal-parietal cortex, is thought to be affected by disconnection from the mesial temporal lobe, besides being directly affected by increased oxidative stress and by atrophy as well. The impairment of these areas is thought to contribute to cognitive decline in verbal memory, constructional praxis and visual sustained attention which are indeed among the earliest signs of cognitive impairment in AD. SIGNIFICANCE: Assessing the relationships between neuropsychology and brain functional imaging is a key approach to clarify the pathophysiology of cognitive failure in AD; the specificity of these findings in AD remains to be proven through comparison with correlation achieved in matched controls.

Right hemispheric dysfunction in a case of pure progressive aphemia: fusion of multimodal neuroimaging.

This article describes the unusual case of a 60-year-old woman suffering from pure progressive aphemia. The fusion of multimodal neuroimaging (MRI, perfusion SPECT) implicated the right frontal lobe, especially the inferior frontal gyrus. This area also showed the greatest functional MRI activation during the performance of a covert phonemic fluency task. Results are discussed in terms of bihemispheric language representation. The fusion of three sets of neuroimages has aided in the interpretation of the patient's cognitive brain dysfunction.

Quantitative EEG and perfusional single photon emission computed tomography correlation during long-term donepezil therapy in Alzheimer's disease.

OBJECTIVE: There is an increasing interest in the effects of the acetylcholinesterase inhibitors (AChEIs) in Alzheimer's disease (AD), as investigated by means of objective, neurophysiological tools. In an open-label study, we evaluated the neurophysiological effects of chronic administration of donepezil to AD patients, by means of a correlative approach between quantitative EEG (qEEG) and perfusional brain single photon emission computed tomography (SPECT). METHODS: Sixteen patients (mean age: 74.8+/-7.9 years) with mild to moderate AD (MMSE score >13, mean: 20.7+/-4.6) underwent qEEG and SPECT examinations at the time of diagnosis (t0) and after approximately 1 year of donepezil therapy (t1). The brain SPECT (99mTc-hexamethylpropyleneamine oxime) was performed by means of a high-resolution SPECT camera; the qEEG was recorded from 19 scalp electrodes by average reference and digitized at 512 Hz. The mean frequency (MF) value of the mean power spectrum (fast Fourier transform) from 4 brain regions (one frontal and one temporal-parietal in each hemisphere) was chosen for statistical analysis. Changes in MMSE score and qEEG-MF values between t0 and t1 were assessed by analysis of variance. SPECT differences between t0 and t1, as well as the relationships between SPECT and qEEG changes, were assessed by statistical parametric mapping (SPM 99; height threshold: P=0.001 at cluster level). RESULTS: Between t0 and t1, the MMSE score significantly (P<0.05) decreased (from 20.7+/-4.64 to 19.1+/-5.09; 95% confidence interval: 1.14) and qEEG was unchanged. There was no regional perfusion decrease; a small area of relative perfusion increase was observed, including the right occipital cuneus and the left lingual gyrus. A positive correlation was found between the right frontal MF and brain perfusion in the left superior parietal lobule. A post hoc SPM analysis (height threshold: P=0.01) showed a positive correlation between brain perfusion and each of the 4 qEEG MF values in the left parietal lobe, including the precuneus, the superior parietal lobule, and the post-central gyrus. CONCLUSIONS: The posterior parietal region, which is involved in memory and attention, is often affected by hypoperfusion in AD, as a likely consequence of disconnection from the atrophic mesial temporal cortex. Metabolic activation induced by AChEIs may especially influence this disconnected but still not grossly impaired area, which could be one of the pathophysiological substrates of the cognitive effects of AChEIs. The modest topographical sensitivity of qEEG, reflecting the rather diffuse changes in AD, is further confirmed.