ABSTRACT
A significant progress has been made in the understanding of the neurobiology of Alzheimer's disease. The post-mortem studies are the gold standard for a correct histopathological diagnosis, contributing to clarify the correlation with cognitive, behavioral and extra-cognitive domains. However, the relationship between pathological staging and clinical involvement remains challenging. Neuroimaging, including positron emission tomography (PET) and magnetic resonance, could help to bridge the gap by providing in vivo information about disease staging. In the last decade, advances in the sensitivity of neuroimaging techniques have been described, in order to accurately distinguish AD from other causes of dementia. Fluorodeoxyglucose-traced PET (FDG-PET) is able to measure cerebral metabolic rates of glucose, a proxy for neuronal activity, theoretically allowing detection of AD. Many studies have shown that this technique could be used in early AD, where reduced metabolic activity correlates with disease progression and predicts histopathological diagnosis. More recently, molecular imaging has made possible to detect brain deposition of histopathology-confirmed neuritic ß-amyloid plaques (Aß) using PET. Although Aß plaques are one of the defining pathological features of AD, elevated levels of Aß can be detected with this technique also in older individuals without dementia. This raises doubts on the utility of Aß PET to identify persons at high risk of developing AD. In the present case-series, we sought to combine metabolic information (from FDG-PET) and amyloid plaque load (from Aß PET) in order to correctly distinguish AD from other forms of dementia. By selecting patients with Aß PET + / FDG-PET + and Aß PET - / FDG-PET +, we propose an integrated algorithm of clinical and molecular imaging information to better define type of dementia in older persons.
ABSTRACT
Although iterative reconstruction is widely applied in SPECT/PET, its introduction in clinical CT is quite recent, in the past the demand for extensive computer power and long image reconstruction times have stopped the diffusion of this technique. Recently Iterative Reconstruction in Image Space (IRIS) has been introduced on Siemens top CT scanners. This recon method works on image data area, reducing the time-consuming loops on raw data and noise removal is obtained in subsequent iterative steps with a smoothing process. We evaluated image noise, low contrast resolution, CT number linearity and accuracy, transverse and z-axis spatial resolution using some dedicated phantoms in single, dual source and cardiac mode. We reconstructed images with a traditional filtered back-projection algorithm and with IRIS. The iterative procedure preserves spatial resolution, CT number accuracy and linearity moreover decreases image noise. These preliminary results support the idea that dose reduction with preserved image quality is possible with IRIS, even if studies on patients are necessary to confirm these data.
