Search

Purpose: The aim of this study was to verify the reliability and generalizability of an automatic tool for the detection of Alzheimer-related hypometabolic pattern based on a Support-Vector-Machine (SVM) model analyzing 18 F-fluorodeoxyglucose (FDG) PET data., Methods: The SVM model processed metabolic data from anatomical volumes of interest also considering interhemispheric asymmetries. It was trained on a homogeneous dataset from a memory clinic center and tested on an independent multicentric dataset drawn from the Alzheimer's Disease Neuroimaging Initiative. Subjects were included in the study and classified based on a diagnosis confirmed after an adequate follow-up time., Results: The accuracy of the discrimination between patients with Alzheimer Disease (AD), in either prodromal or dementia stage, and normal aging subjects was 95.8%, after cross-validation, in the training set. The accuracy of the same model in the testing set was 86.5%. The role of the two datasets was then reversed, and the accuracy was 89.8% in the multicentric training set and 88.0% in the monocentric testing set. The classification rate was also evaluated in different subgroups, including non-converter mild cognitive impairment (MCI) patients, subjects with MCI reverted to normal conditions and subjects with non-confirmed memory concern. The percent of pattern detections increased from 77% in early prodromal AD to 91% in AD dementia, while it was about 10% for healthy controls and non-AD patients., Conclusions: The present findings show a good level of reproducibility and generalizability of a model for detecting the hypometabolic pattern in AD and confirm the accuracy of FDG-PET in Alzheimer disease.

Purpose: Mild cognitive impairment (MCI) is a transitional pathological stage between normal ageing (NA) and Alzheimer's disease (AD). Although subjects with MCI show a decline at different rates, some individuals remain stable or even show an improvement in their cognitive level after some years. We assessed the accuracy of FDG PET in discriminating MCI patients who converted to AD from those who did not., Methods: FDG PET was performed in 42 NA subjects, 27 MCI patients who had not converted to AD at 5 years (nc-MCI; mean follow-up time 7.5 ± 1.5 years), and 95 MCI patients who converted to AD within 5 years (MCI-AD; mean conversion time 1.8 ± 1.1 years). Relative FDG uptake values in 26 meta-volumes of interest were submitted to ANCOVA and support vector machine analyses to evaluate regional differences and discrimination accuracy., Results: The MCI-AD group showed significantly lower FDG uptake values in the temporoparietal cortex than the other two groups. FDG uptake values in the nc-MCI group were similar to those in the NA group. Support vector machine analysis discriminated nc-MCI from MCI-AD patients with an accuracy of 89% (AUC 0.91), correctly detecting 93% of the nc-MCI patients., Conclusion: In MCI patients not converting to AD within a minimum follow-up time of 5 years and MCI patients converting within 5 years, baseline FDG PET and volume-based analysis identified those who converted with an accuracy of 89%. However, further analysis is needed in patients with amnestic MCI who convert to a dementia other than AD.

Purpose: At (18)F-2-fluoro-2-deoxy-D-glucose (FDG) positron emission tomography (PET) examinations a high tracer uptake of the skeletal muscles is sometimes encountered which can lead to reduced uptake in pathological lesions. This was evaluated in retrospect in patients being recalled for a repeat examination after reducing the muscular uptake., Methods: Ten patients with increased muscular tracer uptake were examined with FDG PET/CT on two occasions with a mean of 6 days. All patients showed at least one pathological lesion with increased tracer uptake. The muscular uptake was reduced at the second examination by informing the patient to refrain from physical activity together with pretreatment with diazepam. The maximum standardized uptake value (SUV(max)) of the pathological lesion and SUV(mean) of certain skeletal muscles, liver, spleen, lungs, blood and certain bone marrow portions were calculated., Results: In all patients, the muscular uptake was reduced to a normal level at visual evaluation as well as at comparison of SUVs with 25 consecutive clinical patients exhibiting a normal FDG distribution (p < 0.001). The mean lesion SUV(max) increased from 2.4 to 3.7 (54 %) between the examinations (p < 0.05). All reference tissues/organs showed a significant increase of SUV at the second examination. Relating lesion SUV(max) to the activity of any of the reference tissues/organs there was no significant difference between the studies., Conclusion: The distribution of FDG constitutes a relative mechanism. This must be especially considered at longitudinal examinations in the same patient at therapy evaluations. In examinations with a somehow distorted general distribution of the activity, it may be more relevant to relate the lesion activity to a reference tissue/organ than relying on SUV assessments.

Purpose: Multi-centre trials are an important part of proving the efficacy of procedures, drugs and interventions. Imaging components in such trials are becoming increasingly common; however, without sufficient control measures the usefulness of these data can be compromised. This paper describes a framework for performing high-quality multi-centre trials with single photon emission computed tomography (SPECT), using a pan-European initiative to acquire a normal control dopamine transporter brain scan database as an example., Methods: A framework to produce high-quality and consistent SPECT imaging data was based on three key areas: quality assurance, the imaging protocol and system characterisation. Quality assurance was important to ensure that the quality of the equipment and local techniques was good and consistently high; system characterisation helped understand and where possible match the performance of the systems involved, whereas the imaging protocol was designed to allow a degree of flexibility to best match the characteristics of each imaging device., Results: A total of 24 cameras on 15 sites from 8 different manufacturers were evaluated for inclusion in our multi-centre initiative. All results matched the required level of specification and each had their performance characterised. Differences in performance were found between different system types and cameras of the same type. Imaging protocols for each site were modified to match their individual characteristics to produce comparable high-quality SPECT images., Conclusion: A framework has been designed to produce high-quality data for multi-centre SPECT studies. This framework has been successfully applied to a pan-European initiative to acquire a healthy control dopamine transporter image database.

Purpose: [(18)F]FEDAA1106 is a recently developed positron emission tomography (PET) radioligand for in vivo quantification of the 18 kDa translocator protein [TSPO or, as earlier called, the peripheral benzodiazepine receptor (PBR)]. TSPO imaging is expected to be useful for the clinical evaluation of neuroinflammatory diseases. The aim of this study was to provide dosimetry estimates for [(18)F]FEDAA1106 based on human whole-body PET measurements., Methods: PET scans were performed for a total of 6.6 h after the injection of 183.8 ± 9.1 MBq of [(18)F]FEDAA1106 in six healthy subjects. Regions of interest were drawn on coronal images. Estimates of the absorbed doses of radiation were calculated using the OLINDA software., Results: Peak uptake was largest in lungs, followed by liver, small intestine, kidney, spleen and other organs. Peak values of the percent injected dose (%ID) at a time after radioligand injection were calculated for the lungs (27.1%ID at 0.2 h), liver (21.1%ID at 0.6 h), small intestine (10.4%ID at 6.3 h), kidney (4.9%ID at 1.8 h) and spleen (4.6%ID at 0.6 h). The largest absorbed dose was found in the spleen (0.12 mSv/MBq), followed by kidneys (0.094 mSv/MBq). The calculated mean effective dose was 0.036 mSv/MBq., Conclusion: Based on the distribution and dose estimates, the estimated radiation burden of [(18)F]FEDAA1106 is moderately higher than that of [(18)F]fluorodeoxyglucose (FDG). In clinical studies, the administered activity of this radioligand ought to be adjusted in line with regional regulations. This result would be helpful for further clinical TSPO imaging studies.

Purpose: Neurobiological abnormalities underlying atypical depression have previously been suggested. The purpose of this study was to explore differences at functional brain imaging between depressed patients with and without atypical features and healthy controls., Methods: Twenty-three out-patients with chronic depressive disorder recruited from a service for patients with audiological symptoms were investigated. Eleven fulfilled the DSM-IV criteria for atypical depression (mood reactivity and at least two of the following: weight gain, hypersomnia, leaden paralysis and interpersonal rejection sensitivity). Twenty-three healthy subjects served as controls. Voxel-based analysis was applied to explore differences in (99m)Tc-HMPAO uptake between groups., Results: Patients in the atypical group had a higher prevalence of bilateral hearing impairment and higher depression and somatic distress ratings at the time of SPECT. Significantly higher tracer uptake was found bilaterally in the atypical group as compared with the non-atypicals in the sensorimotor (Brodmann areas, BA1-3) and premotor cortex in the superior frontal gyri (BA6), in the middle frontal cortex (BA8), in the parietal associative cortex (BA5, BA7) and in the inferior parietal lobule (BA40). Significantly lower tracer distribution was found in the right hemisphere in the non-atypicals compared with the controls in BA6, BA8, BA44, BA45 and BA46 in the frontal cortex, in the orbito-frontal cortex (BA11, BA47), in the postcentral parietal cortex (BA2) and in the multimodal association parietal cortex (BA40)., Conclusion: The differences found between atypical and non-atypical depressed patients suggest different neurobiological substrates in these patient groups. The putative links with the clinical features of atypical depression are discussed. These findings encourage the use of functional neuroimaging in psychiatric disorders.

Previous regional cerebral blood flow (rCBF) studies on patients with unipolar major depressive disorder (MDD) have analysed clusters of voxels or single regions and yielded conflicting results, showing either higher or lower rCBF in MDD as compared to normal controls (CTR). The aim of this study was to assess rCBF distribution changes in 68 MDD patients, investigating the data set with both volume of interest (VOI) analysis and principal component analysis (PCA). The rCBF distribution in 68 MDD and 66 CTR, at rest, was compared. Technetium-99m d, l-hexamethylpropylene amine oxime single-photon emission tomography was performed and the uptake in 27 VOIs, bilaterally, was assessed using a standardising brain atlas. Data were then grouped into factors by means of PCA performed on rCBF of all 134 subjects and based on all 54 VOIs. VOI analysis showed a significant group x VOI x hemisphere interaction ( P<0.001). rCBF in eight VOIs (in the prefrontal, temporal, occipital and central structures) differed significantly between groups at the P<0.05 level. PCA identified 11 anatomo-functional regions that interacted with groups ( P<0.001). As compared to CTR, MDD rCBF was relatively higher in right associative temporo-parietal-occipital cortex ( P<0.01) and bilaterally in prefrontal ( P<0.005) and frontal cortex ( P<0.025), anterior temporal cortex and central structures ( P<0.05 and P<0.001 respectively). Higher rCBF in a selected group of MDD as compared to CTR at rest was found using PCA in five clusters of regions sharing close anatomical and functional relationships. At the single VOI level, all eight regions showing group differences were included in such clusters. PCA is a data-driven method for recasting VOIs to be used for group evaluation and comparison. The appearance of significant differences absent at the VOI level emphasises the value of analysing the relationships among brain regions for the investigation of psychiatric disease.

The increasing implementation of standardisation techniques in brain research and clinical diagnosis has highlighted the importance of reliable baseline data from normal control subjects for inter-subject analysis. In this context, knowledge of the regional cerebral blood flow (rCBF) distribution in normal ageing is a factor of the utmost importance. In the present study, rCBF was investigated in 50 healthy volunteers (25 men, 25 women), aged 31-78 years, who were examined at rest by means of single-photon emission tomography (SPET) using technetium-99m d, l-hexamethylpropylene amine oxime (HMPAO). After normalising the CBF data, 27 left and 27 right volumes of interest (VOIs) were selected and automatically outlined by standardisation software (computerised brain atlas). The heavy load of flow data thus obtained was reduced in number and grouped in factors by means of principal component analysis (PCA). PCA extracted 12 components explaining 81% of the variance and including the vast majority of cortical and subcortical regions. Analysis of variance and regression analyses were performed for rCBF, age and gender before PCA was applied and subsequently for each single extracted factor. There was a significantly higher CBF on the right side than on the left side ( P<0.001). In the overall analysis, a significant decrease was found in CBF ( P=0.05) with increasing age, and this decrease was particularly evident in the left hemisphere ( P=0.006). When gender was specifically analysed, CBF was found to decrease significantly with increasing age in females ( P=0.037) but not in males. Furthermore, a significant decrease in rCBF with increasing age was found in the brain vertex ( P=0.05), left frontotemporal cortex ( P=0.012) and temporocingulate cortex ( P=0.003). By contrast, relative rCBF in central structures increased with age ( P=0.001). The ability of standardisation software and PCA to identify functionally connected brain regions might contribute to a better understanding of the relationships between rCBF at rest, anatomically defined brain structures, ageing and gender.