Quantification of dopaminergic neurotransmission SPECT studies with 123 l-labelled radioligands

Dopaminergic neurotransmission SPECT studies with 123I-labelled radioligands can help in the diagnosis of neurological and psychiatric disorders such as Parkinson¿s disease and schizophrenia. Nowadays, interpretation of SPECT images is based mainly on visual assessment by experienced observers. However, a quantitative evaluation of the images is recommended in current clinical guidelines. Quantitative information can help diagnose the disease at the early pre-clinical stages, follow its progression and assess the effects of treatment strategies. SPECT images are affected by a number of effects that are inherent in the image formation: attenuation and scattering of photons, system response and partial volume effect. These effects degrade the contrast and resolution of the images and, as a consequence, the real activity distribution of the radiotracer is distorted. Whilst the photon emission of 123I is dominated by a low-energy line of 159 keV, it also emits several high-energy lines. When 123I-labelled radioligands are used, a non-negligible fraction of high-energy photons undergoes backscattering in the detector and the gantry and reaches the detector within the energy window. In this work, a complete methodology for the compensation of all the degrading effects involved in dopaminergic neurotransmission SPECT imaging with 123I is presented. The proposed method uses Monte Carlo simulation to estimate the scattered photons detected in the projections. For this purpose, the SimSET Monte Carlo code was modified so as to adapt it to the more complex simulation of high-energy photons emitted by 123I. Once validated, the modified SimSET code was used to simulate 123I SPECT studies of an anthropomorphic striatal phantom using different imaging systems. The projections obtained showed that scatter is strongly dependent on the imaging system and comprises at least 40% of the detected photons. Applying the new methodology demonstrated that absolute quantification can be achieved when the method includes accurate compensations for all the degrading effects. When the method did not include correction for all degradations, calculated values depended on the imaging system, although a linear relationship was found between calculated and true values. It was also found that partial volume effect and scatter corrections play a major role in the recovery of nominal values. Despite the advantages of absolute quantification, the computational and methodological requirements needed severely limit the possibility of application in clinical routine. Thus, for the time being, absolute quantification is limited to academic studies and research trials. In a clinical context, reliable, simple and rapid methods are needed, thus, semi-quantitative methods are used. Diagnosis also requires the establishment of robust reference values for healthy controls. These values are usually derived from a large data pool obtained in multicentre clinical trials. The comparison between the semi-quantitative values obtained from a patient and the reference is only feasible if the quantitative values have been previously standardised, i.e. they are independent of the gamma camera, acquisition protocol, reconstruction parameters and quantification procedure applied. Thus, standardisation requires that the calculated values are compensated somehow for all the image-degrading phenomena. In this thesis dissertation, a methodology for the standardisation of the quantitative values extracted from dopaminergic neurotransmission SPECT studies with 123I is evaluated using Monte Carlo simulation. This methodology is based on the linear relationship found between calculated and true values for a group of studies corresponding to different subjects with non-negligible anatomical and tracer uptake differences. Reconstruction and quantification methods were found to have a high impact on the linearity of the relationship and on the accuracy of the standardised results

D2/D3 dopamine receptor binding with [F-18]fallypride correlates of executive function in medication-naïve patients with schizophrenia

Converging evidence indicates that the prefrontal cortex is critically involved in executive control and that executive dysfunction is implicated in schizophrenia. Reduced dopamine D2/D3 receptor binding potential has been reported in schizophrenia, and the correlations with neuropsychological test scores have been positive and negative for different tasks. The aim of this study was to examine the relation between dopamine D2/D3 receptor levels with frontal and temporal neurocognitive performance in schizophrenia. Resting-state 18F-fallypride positron emission tomography was performed on 20 medication-naïve and 5 previously medicated for brief earlier periods patients with schizophrenia and 19 age- and sex-matched healthy volunteers. Striatal and extra-striatal dopamine D2/D3 receptor levels were quantified as binding potential using fallypride imaging. Magnetic resonance images in standard Talairach position and segmented into gray and white matter were co-registered to the fallypride images, and the AFNI stereotaxic atlas was applied. Two neuropsychological tasks known to activate frontal and temporal lobe function were chosen, specifically the Wisconsin Card Sorting Test (WCST) and the California Verbal Learning Test (CVLT). Images of the correlation coefficient between fallypride binding and WCST and CVLT performance showed a negative correlation in contrast to positive correlations in healthy volunteers. The results of this study demonstrate that lower fallypride binding potential in patients with schizophrenia may be associated with better performance. Our findings are consistent with previous studies that failed to find cognitive improvements with typical dopamine-blocking medications

Image databases in medical applications

The number of medical images acquired yearly in hospitals increases all the time. These imaging data contain lots of information on the characteristics of anatomical structures and on their variations. This information can be utilized in numerous medical applications. In deformable model-based segmentation and registration methods, the information in the image databases can be used to give a priori information on the shape of the object studied and the gray-level values in the image, and on their variations. On the other hand, by studying the variations of the object of interest in different populations, the effects of, for example, aging, gender, and diseases on anatomical structures can be detected. In the work described in this Thesis, methods that utilize image databases in medical applications were studied. Methods were developed and compared for deformable model-based segmentation and registration. Model selection procedure, mean models, and combination of classifiers were studied for the construction of a good a priori model. Statistical and probabilistic shape models were generated to constrain the deformations in segmentation and registration so that only the shapes typical to the object studied were accepted. In the shape analysis of the striatum, both volume and local shape changes were studied. The effects of aging and gender, and also the asymmetries were examined. The results proved that the segmentation and registration accuracy of deformable model-based methods can be improved by utilizing the information in image databases. The databases used were relatively small. Therefore, the statistical and probabilistic methods were not able to model all the population-specific variation. On the other hand, the simpler methods, the model selection procedure, mean models, and combination of classifiers, gave good results also with the small image databases. Two main applications were the reconstruction of 3-D geometry from incomplete data and the segmentation of heart ventricles and atria from short- and long-axis magnetic resonance images. In both applications, the methods studied provided promising results. The shape analysis of the striatum showed that the volume of the striatum decreases in aging. Also, the shape of the striatum changes locally. Asymmetries in the shape were found, too, but any gender-related local shape differences were not found.reviewe

Aberrant Effective Connectivity in Schizophrenia Patients during Appetitive Conditioning

It has recently been suggested that schizophrenia involves dysfunction in brain connectivity at a neural level, and a dysfunction in reward processing at a behavioral level. The purpose of the present study was to link these two levels of analyses by examining effective connectivity patterns between brain regions mediating reward learning in patients with schizophrenia and healthy, age-matched controls. To this aim, we used functional magnetic resonance imaging and galvanic skin recordings (GSR) while patients and controls performed an appetitive conditioning experiment with visual cues as the conditioned (CS) stimuli, and monetary reward as the appetitive unconditioned stimulus (US). Based on explicit stimulus contingency ratings, conditioning occurred in both groups; however, based on implicit, physiological GSR measures, patients failed to show differences between CS+ and CS− conditions. Healthy controls exhibited increased blood-oxygen-level dependent (BOLD) activity across striatal, hippocampal, and prefrontal regions and increased effective connectivity from the ventral striatum to the orbitofrontal cortex (OFC BA 11) in the CS+ compared to the CS− condition. Compared to controls, patients showed increased BOLD activity across a similar network of brain regions, and increased effective connectivity from the striatum to hippocampus and prefrontal regions in the CS− compared to the CS+ condition. The findings of increased BOLD activity and effective connectivity in response to the CS− in patients with schizophrenia offer insight into the aberrant assignment of motivational salience to non-reinforced stimuli during conditioning that is thought to accompany schizophrenia

Understanding mechanisms related to psychosis in Motor Neurone Disease

Psychosis is a challenging feature of the syndromes of motor neurone disease (MND), frontotemporal dementia (FTD) and their overlap (FTD-MND). Clinically evident psychosis is not common, except in those with C9orf72+ expansions. However, subthreshold psychosis or pre-psychosis processes are common and provide the opportunity to study the mechanisms of psychosis in MND and FTD-MND. My aim was to identify the prevalence and the cognitive and neural correlates of psychosis, and related processes, in MND. I used a tiered cohort study approach. Tier 1 introduced screening as standard in a regional MND clinic (N=111) using the Edinburgh Cognitive and Behavioural ALS Screen and Cambridge Behavioural Inventory-Revised (CBI-R). In Tier 2, 60 patients and 30 controls underwent neuropsychological assessment, including (i) evidence-based decision-making, to quantify jumping to conclusions (JTC), (ii) attentional control and associative learning, (iii) perceptual inference, and (iv) psychiatric screening with Neuropsychiatric Inventory (NPI), Brief Psychiatric Rating Scale (BRPS), and the Comprehensive Assessment of At-Risk Mental States (CAARMS). Tier 3 included magnetic resonance imaging of 30 patients and 20 controls. Carer reports in Tier 1 indicated that 10% of patients exhibited features suggestive of psychosis and 40% exhibited behavioural change. In Tier 2, many patients manifested abnormal behaviours (CBI-R 41%; NPI showed 19%; BPRS 24%), with 12-16% showing psychosis-specific symptoms (CBI-R and NPI psychosis index scores). In the jumping to conclusions task, patients made decisions based on less evidence than controls and were insensitive to negative feedback. Carer ratings of patient behaviour correlated with performance on the jumping to conclusions task when decisions were rewarded or costs fixed. Attentional shifting and perceptual inference were normal in MND. A principal component analysis (PCA) of questionnaires revealed two component scores, reflecting distinct patients’ and carers’ perspectives. The imaging analyses focused on the correlates of jumping to conclusions and insensitivity to negative feedback, as a potential risk profile for psychosis, with exploratory analyses of the correlates of the CBI-R psychosis index, and carers’ ratings of behaviour from the PCA. Using a Freesurfer regions-of-interest approach, grey matter volume correlated inversely with CBI-R psychosis index in the caudate, amygdala, cingulate and hippocampus. Using tract-based spatial statistics, increased mean diffusivity (MD) of diffusion weighted imaging correlated with the CBI-R psychosis responses in inferior longitudinal and uncinate fasciculi. Cost sensitivity in the JTC task correlated with cingulate and cerebellar grey matter volumes. White matter correlates of cost sensitivity included reduced FA with increasing cost sensitivity in white matter connecting the inferior frontal lobe in controls and patients. Although overt psychosis is uncommon in MND, many patients displayed abnormal behaviour or cognitive symptoms, including suboptimal reasoning biases and inferential impulsivity. Degeneration of cerebellar, cingulate and striatal grey matter, and adjacent major white matter tracts, may underlie these cognitive impairments and together represent a vulnerability to develop psychosis. Compromised reasoning and inference have implications for clinical management, including decisions around treatment options and management of well-being in MND.This research was funded by Alzheimer’s Research UK Studentship (PhD2017-26); Medical Research Council (SUAG 051/ G101400); and the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care

Neurobiological markers for remission and persistence of childhood attention-deficit/hyperactivity disorder

Attention-deficit/hyperactivity disorder (ADHD) is one of the most prevalent neurodevelopmental disorders in children. Symptoms of childhood ADHD persist into adulthood in around 65% of patients, which elevates the risk for a number of adverse outcomes, resulting in substantial individual and societal burden. A neurodevelopmental double dissociation model is proposed based on existing studies in which the early onset of childhood ADHD is suggested to associate with dysfunctional subcortical structures that remain static throughout the lifetime; while diminution of symptoms over development could link to optimal development of prefrontal cortex. Current existing studies only assess basic measures including regional brain activation and connectivity, which have limited capacity to characterize the functional brain as a high performance parallel information processing system, the field lacks systems-level investigations of the structural and functional patterns that significantly contribute to the symptom remission and persistence in adults with childhood ADHD. Furthermore, traditional statistical methods estimate group differences only within a voxel or region of interest (ROI) at a time without having the capacity to explore how ROIs interact in linear and/or non-linear ways, as they quickly become overburdened when attempting to combine predictors and their interactions from high-dimensional imaging data set. This dissertation is the first study to apply ensemble learning techniques (ELT) in multimodal neuroimaging features from a sample of adults with childhood ADHD and controls, who have been clinically followed up since childhood. A total of 36 adult probands who were diagnosed with ADHD combined-type during childhood and 36 matched normal controls (NCs) are involved in this dissertation research. Thirty-six adult probands are further split into 18 remitters (ADHD-R) and 18 persisters (ADHD-P) based on the symptoms in their adulthood from DSM-IV ADHD criteria. Cued attention task-based fMRI, structural MRI, and diffusion tensor imaging data from each individual are analyzed. The high-dimensional neuroimaging features, including pair-wise regional connectivity and global/nodal topological properties of the functional brain network for cue-evoked attention process, regional cortical thickness and surface area, subcortical volume, volume and fractional anisotropy of major white matter fiber tract for each subject are calculated. In addition, all the currently available optimization strategies for ensemble learning techniques (i.e., voting, bagging, boosting and stacking techniques) are tested in a pool of semi-final classification results generated by seven basic classifiers, including K-Nearest Neighbors, support vector machine (SVM), logistic regression, Naïve Bayes, linear discriminant analysis, random forest, and multilayer perceptron. As hypothesized, results indicate that the features of nodal efficiency in right inferior frontal gyrus, right middle frontal (MFG)-inferior parietal (IPL) functional connectivity, and right amygdala volume significantly contributed to accurate discrimination between ADHD probands and controls; higher nodal efficiency of right MFG greatly contributed to inattentive and hyperactive/impulsive symptom remission, while higher right MFG-IPL functional connectivity strongly linked to symptom persistence in adults with childhood ADHD. The utilization of ELTs indicates that the bagging-based ELT with the base model of SVM achieves the best results, with the most significant improvement of the area under the receiver of operating characteristic curve (0.89 for ADHD probands vs. NCs, and 0.9 for ADHD-P vs. ADHD-R). The outcomes of this dissertation research have considerable value for the development of novel interventions that target mechanisms associated with recovery

Quantitation in MRI : application to ageing and epilepsy

Multi-atlas propagation and label fusion techniques have recently been developed for segmenting the human brain into multiple anatomical regions. In this thesis, I investigate possible adaptations of these current state-of-the-art methods. The aim is to study ageing on the one hand, and on the other hand temporal lobe epilepsy as an example for a neurological disease. Overall effects are a confounding factor in such anatomical analyses. Intracranial volume (ICV) is often preferred to normalize for global effects as it allows to normalize for estimated maximum brain size and is hence independent of global brain volume loss, as seen in ageing and disease. I describe systematic differences in ICV measures obtained at 1.5T versus 3T, and present an automated method of measuring intracranial volume, Reverse MNI Brain Masking (RBM), based on tissue probability maps in MNI standard space. I show that this is comparable to manual measurements and robust against field strength differences. Correct and robust segmentation of target brains which show gross abnormalities, such as ventriculomegaly, is important for the study of ageing and disease. We achieved this with incorporating tissue classification information into the image registration process. The best results in elderly subjects, patients with TLE and healthy controls were achieved using a new approach using multi-atlas propagation with enhanced registration (MAPER). I then applied MAPER to the problem of automatically distinguishing patients with TLE with (TLE-HA) and without (TLE-N) hippocampal atrophy on MRI from controls, and determine the side of seizure onset. MAPER-derived structural volumes were used for a classification step consisting of selecting a set of discriminatory structures and applying support vector machine on the structural volumes as well as morphological similarity information such as volume difference obtained with spectral analysis. Acccuracies were 91-100 %, indicating that the method might be clinically useful. Finally, I used the methods developed in the previous chapters to investigate brain regional volume changes across the human lifespan in over 500 healthy subjects between 20 to 90 years of age, using data from three different scanners (2x 1.5T, 1x 3T), using the IXI database. We were able to confirm several known changes, indicating the veracity of the method. In addition, we describe the first multi-region, whole-brain database of normal ageing

Striatal and extrastriatal dopamine D2/3 receptors studied with [11C]raclopride and high-resolution PET

The human striatum is a heterogeneous structure representing a major part of the dopamine (DA) system’s basal ganglia input and output. Positron emission tomography (PET) is a powerful tool for imaging DA neurotransmission. However, PET measurements suffer from bias caused by the low spatial resolution, especially when imaging small, D2/3 -rich structures such as the ventral striatum (VST). The brain dedicated high-resolution PET scanner, ECAT HRRT (Siemens Medical Solutions, Knoxville, TN, USA) has superior resolution capabilities than its predecessors. In the quantification of striatal D2/3 binding, the in vivo highly selective D2/3 antagonist [11C] raclopride is recognized as a well-validated tracer. The aim of this thesis was to use a traditional test-retest setting to evaluate the feasibility of utilizing the HRRT scanner for exploring not only small brain regions such as the VST but also low density D2/3 areas such as cortex. It was demonstrated that the measurement of striatal D2/3 binding was very reliable, even when studying small brain structures or prolonging the scanning interval. Furthermore, the cortical test-retest parameters displayed good to moderate reproducibility. For the first time in vivo, it was revealed that there are significant divergent rostrocaudal gradients of [11C]raclopride binding in striatal subregions. These results indicate that high-resolution [11C]raclopride PET is very reliable and its improved sensitivity means that it should be possible to detect the often very subtle changes occurring in DA transmission. Another major advantage is the possibility to measure simultaneously striatal and cortical areas. The divergent gradients of D2/3 binding may have functional significance and the average distribution binding could serve as the basis for a future database. Key words: dopamine, PET, HRRT, [11C]raclopride, striatum, VST, gradients, test-retest.Dopamiini D2/3 reseptorien kuvantaminen korkean resoluution PET kameralla ja [11C]raclopridi merkkiaineella. Aivojen tyvitumakkeisiin kuuluva aivojuovio on keskeinen dopamiiniaineenvaihdunnan kannalta. PET menetelmällä voidaan tutkia dopamiiniaineenvaihduntaa reseptoritasolla, mutta sen heikkous on huono spatiaalinen resoluutio, etenkin tutkittaessa pieniä aivoalueita kuten aivojuovion ventraalista osaa (VST). Tässä väitöskirjatutkimuksessa on käytetty aivotutkimukseen suunniteltua korkean resoluution PET-kameraa (ECAT HRRT, Siemens Medical Solutions, Knoxville, TN, USA) ja D2/3 dopamiinireseptoreihin spesifisesti sitoutuvaa [11C]raclopridi PET-merkkiainetta. Tämän väitöskirjatutkimuksen tarkoituksena on selvittää toistomittauksella HRRT kameran soveltuvuutta pienten (VST) ja toisaalta vähän D2/3 reseptoreita sisältävien (aivojen kuorikerros) aivoalueiden kuvantamiseen. HRRT-kameran käyttökelpoisuus osoittautui erittäin hyväksi pienempien aivoalueiden tutkimisessa eikä luotettavuus kärsinyt vaikka kahden mittauksen välistä intervallia pidennettiin. Kuorikerroksen mittauksen luotettavuus oli myös tyydyttävä/hyvä. Lisäksi ensimmäistä kertaa PET menetelmää käyttäen pystyttiin havaitsemaan erisuuntaisia gradientteja [11C]raclopridin sitoutumisessa D2/3 reseptoreihin. Löydösten perusteella korkean resoluution [11C]raclopridi PET menetelmä on erittäin luotettava ja se mahdollisesti lisää mittauksen sensitiivisyyttä havaita hienovaraisia dopamiiniaineenvaihdunnan muutoksia. [11C]raclopridia voisi tulevaisuudessa mahdollisesti käyttää samanaikaisesti sekä aivojuovion että aivojen kuorikerroksen tutkimiseen, joka toisi lisäinformaatiota dopamiinijärjestestelmän toiminnallisesta järjestäytymisestä aivoissa. Havaituilla erilaisilla gradienteilla [11C]raclopridin sitoutumisessa voi olla funktionaalista merkitystä ja keskimääräistä sitoutumista voitaisiin käyttää myös tietokannan pohjana.Siirretty Doriast