The hazards of lack of co-registration of ictal brain SPECT with MRI: A case report of sinusitis mimicking a brainstem seizure focus

BACKGROUND: Single photon emission computed tomography (SPECT) following injection of radiotracer during a seizure is known as ictal SPECT. Comparison of an ictal SPECT study to a baseline or interictal study can aid identification of a seizure focus. CASE PRESENTATION: A young woman with encephalitis and refractory seizures underwent brain SPECT during a period of frequent seizure-like episodes, and during a seizure-free period. A focal area of increased radiotracer uptake present only when she was experiencing frequent seizure-like episodes was originally localized to the brainstem, but with later computerized co-registration of SPECT to MRI, was found to lie outside the brain, in the region of the sphenoid sinus. CONCLUSION: Low-resolution SPECT images present difficulties in interpretation, which can be overcome through co-registration to higher-resolution structural images

Image-Derived Input Function for Human Brain Using High Resolution PET Imaging with [11C](R)-rolipram and [11C]PBR28

The aim of this study was to test seven previously published image-input methods in state-of-the-art high resolution PET brain images. Images were obtained with a High Resolution Research Tomograph plus a resolution-recovery reconstruction algorithm using two different radioligands with different radiometabolite fractions. Three of the methods required arterial blood samples to scale the image-input, and four were blood-free methods. values was quantified using a scoring system. Using the image input methods that gave the most accurate results with Logan analysis, we also performed kinetic modelling with a two-tissue compartment model.)-rolipram, which has a lower metabolite fraction. Compartment modeling gave less reliable results, especially for the estimation of individual rate constants.C]PBR28), the more difficult it is to obtain a reliable image-derived input function; and 4) in association with image inputs, graphical analyses should be preferred over compartmental modelling

Single incision laparoscopic surgery transabdominal pre-peritoneal hernia repair –

Volume rendering with texture mapping hardware is a fast volume rendering method available on high-end workstations. However, limited texture memory often prevents the method from being used to render large volume data efficiently. In this paper, we propose a new approach to fast rendering of large volume data with texture mapping hardware. Based on a new volume-loading pipeline, the volume data is preprocessed in such a way that only the volume data that contains object voxels are loaded into texture memory and resampled for rendering. Moreover, if classification threshold is changed, our algorithm classifies and processes the raw volume data accordingly nearly in real time. Our tests show that about 40% to 60% rendering time is saved in our method for large volume data.published_or_final_versio