Hans-Juergen Kaiser

Cardiac resynchronization therapyhomogenizes myocardial glucosemetabolism and perfusion in dilatedcardiomyopathy and left bundle branch block

Abstract Objectives We investigated whether cardiac resynchronization therapy (CRT) affects myocardial glucose metabolism and perfusion in dilated cardiomyopathy (DCM) and left bundle branch block (LBBB). Background Patients with DCM and LBBB present with asynchronous left ventricular (LV) activation, leading to reduced septal glucose metabolism. Cardiac resynchronization therapy recoordinates LV activation, but its effects on myocardial glucose metabolism and perfusion remain unknown. Methods In 15 patients (10 females; 61 ± 13 years) with DCM and LBBB (QRS width 165 ± 15 ms), gated 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET) and technetium-99m ( 99m Tc)-sestamibi single-photon emission computed tomography were performed before and after two weeks of CRT. Uptake of FDG and 99m Tc-sestamibi was determined in four LV wall areas. Ejection fraction and volumes were calculated from gated PET. Results Baseline FDG uptake was heterogeneous (p 99m Tc-sestamibi uptake was modest (lowest septal 65 ± 10%; maximum lateral 84 ± 5%) and also reduced with CRT, although some heterogeneity (p 99m Tc-sestamibi uptake (0.77 ± 0.13 to 0.85 ± 0.16, p Conclusions Glucose metabolism is reduced more than perfusion in the septal compared with LV lateral wall in patients with DCM and LBBB. Cardiac resynchronization therapy restores homogeneous myocardial glucose metabolism with less influence on perfusion.

Influence of diabetes mellitus on regional cerebral glucose metabolism and regional cerebral blood flow.

Previous studies have shown both increased and decreased regional cerebral glucose metabolism-blood flow (rMRGlu-rCBF) values in diabetes. We sought to elucidate the influence of diabetes on rMRGlu-rCBF in 57 patients with pure cerebral microangiopathy. Sixteen of 57 patients had diabetes requiring therapy (11 NIDDM, 5 IDDM). Using a special head-holder for exact repositioning, rMRGlu (PET) and rCBF (SPET) were imaged and measured in slices, followed by MRI. White matter and cortex were defined within regions of interest taken topographically from MRI (overlay). Diabetic and non-diabetic microangiopathy patients were compared to 19 age-matched controls. The diabetic patients showed significantly lower rMRGlu-rCBF values in all regions than controls, whereas non-diabetic patients did not. There were no significant NIDDM-IDDM differences. rMRGlu-rCBF did not depend on venous blood glucose levels at the time of the PET examination. However, analysis of variance with the factors diabetes, atrophy and morphological severity of microangiopathy showed that lowered rMRGlu-rCBF in the diabetic group was due to concomitant atrophy only (P<0.005), while neither diabetes nor microangiopathy had any influence on rMRGlu-rCBF (all P>0.2). These results were confirmed by multivariate factor analysis. It can thus be concluded that a supposed decrease in rMRGlu-rCBF in diabetes mellitus is in fact only an artefact produced by the concomitant atrophy. All previous studies failed to correct for atrophy, and a critical reappraisal is required.

The quantification of dynamic FET PET imaging and correlation with the clinical outcome in patients with glioblastoma

The PET tracer O-(2-[18F]Fluoroethyl)-l-tyrosine (FET) has been shown to be valuable for different roles in the management of brain tumours. The aim of this study was to evaluate several quantitative measures of dynamic FET PET imaging in patients with resected glioblastoma. We evaluated dynamic FET PET in nine patients with histologically confirmed glioblastoma. Following FET PET, all subjects had radiation and chemotherapy. Tumour ROIs were defined by a threshold-based region-growing algorithm. We compared several standard measures of tumour uptake and uptake kinetics: SUV, SUV/background, distribution volume ratio (DVR), weighted frame differences and compartment model parameters. These measures were correlated with disease-free and overall survival, and analysed for statistical significance. We found that several measures allowed robust quantification. SUV and distribution volume did not correlate with clinical outcome. Measures that are based on a background region (SUV/BG, Logan-DVR) highly correlated with disease-free survival (r = -0.95, p < 0.0001), but not overall survival. Some advanced measures also showed a prognostic value but no improvement over the simpler methods. We conclude that FET PET probably has a prognostic value in patients with resected glioblastoma. The ratio of SUV to background may provide a simple and valuable predictive measure of the clinical outcome. Further studies are needed to confirm these explorative results.

Imaging of β-oxidation by static PET with 14(R,S)-[18F]-fluoro-6-thiaheptadecanoic acid (FTHA) in patients with advanced coronary heart disease : A comparison with 18FDG-PET and 99Tcm-MIBI SPET

14(R,S)-[18F]-fluoro-6-thiaheptadecanoic acid (FTHA) has been proposed as a PET tracer of the beta-oxidation pathway. The aim of this study was to investigate the diagnostic value of FTHA using static PET imaging in patients with ischaemically reduced left ventricular function. Twenty-one patients with angiographically proven advanced coronary heart disease were examined. All patients underwent SPET with 400 MBq [99Tcm]-2-methoxy-isobutyl-isonitrile (MIBI) for perfusion assessment and PET with 250 MBq FTHA under fasting conditions and with 150 MBq 2-[18F]-fluoro-2-deoxyglucose (FDG) following an oral glucose load. The uptake of FTHA and FDG was analysed quantitatively in 33 regions. Regional uptake was normalized to the region with highest MIBI uptake and expressed as a percentage. FTHA uptake paralleled MIBI uptake (r = 0.80) but not FDG uptake (r = 0.57). Mean FTHA uptake (38.1 +/- 16.3%) in 190 regions with severely reduced perfusion (MIBI uptake < 50%, mean uptake 36.8 +/- 9.4%) was significantly lower compared to FDG uptake (54.6 +/- 25.0%). FTHA uptake was preserved (> or = 70%) in 8 of 52 (13%) regions only with severely reduced perfusion but preserved glucose metabolism (FDG uptake > or = 70%). The similarity between FTHA and MIBI uptake suggests that static PET imaging with FTHA is of limited value when distinguishing between ischaemic or hibernating myocardium and scar. The underestimation of viability may be caused both by the dependence of uptake on flow and the suppression of beta-oxidation in regional chronic ischaemia under fasting conditions.

”Ecstasy”-induced changes of cerebral glucose metabolism and their correlation to acute psychopathology

Abstract. The aim of this study was to determine the acute effects of the ”Ecstasy” analogue MDE (3,4-methylene dioxyethamphetamine) on cerebral glucose metabolism (rMRGlu) of healthy volunteers and to correlate neurometabolism with acute psychopathology. In a randomized double-blind trial, 15 healthy volunteers without a history of drug abuse were examined with fluorine-18-deoxyglucose (18FDG) positron emission tomography (PET) 110–120 min after oral administration of 2 mg/kg MDE (n=7) or placebo (n=8). Two minutes prior to radiotracer injection, constant cognitive stimulation was started and maintained for 32 min using a word repetition paradigm to ensure constant and comparable mental conditions during cerebral glucose uptake. Individual brain anatomy was represented using T1-weighted 3D flash magnetic resonance imaging (MRI), followed by manual regionalization into 108 regions of interest and PET/MRI overlay. After absolute quantification of rMRGlu and normalization to global metabolism, normalized rMRGlu under MDE was compared to placebo using the Mann-Whitney U-test. Acute psychopathology was assessed using the Positive and Negative Syndrome Scale (PANSS) and rMRGlu was correlated to PANSS scores according to Spearman. MDE subjects showed significantly decreased rMRGlu in the bilateral frontal cortex: left frontal posterior (–7.1%, P<0.05) and right prefrontal superior (–4.6%, P<0.05). On the other hand, rMRGlu was significantly increased in the bilateral cerebellum (right: +10.1%, P<0.05; left: +7.6%, P<0.05) and in the right putamen (+6.2%, P<0.05). There were positive correlations between rMRGlu in the middle right cingulate and grandiosity (r=0.87, P<0.05), both the right amygdala (r=0.90, P<0.01) and the left posterior cingulate (r=0.90, P<0.01) to difficulties in abstract thinking, and the right frontal inferior (r=0.85, P<0.05), right anterior cingulate (r=0.93, P<0.01), and left anterior cingulate (r=0.85, P<0.05) to attentional deficits. A negative correlation was found between the left frontal operculum (Broca’s area) and attentional deficits (r=–0.85, P<0.05). The present study revealed acute neurometabolic changes under the ”Ecstasy” analogue MDE, indicating a frontostriatocerebellar imbalance paralleling other psychotropic substances or various psychiatric disorders.

Cerebral interregional correlations of associative language processing: a positron emission tomography activation study using fluorine-18 fluorodeoxyglucose.

Abstract. Even though there have been numerous positron emission tomography (PET) activation studies on the perfusional and metabolic bases of language processing, little is known about the intracerebral functional network of language and cognitive processes. It was the aim of this study to investigate the cerebral interregional correlations during voluntary word association versus word repetition in healthy subjects to gain insight into the functional connectivity of associative speech processing. Due to individual variability in functional anatomy, the study protocol was designed as an averaged single-subject study. Eight healthy volunteers performed a verbal association task during fluorine-18 fluorodeoxyglucose (18F-FDG) PET scanning. Two different tasks were performed in randomized order: (a) word repetition (after auditory presentation of nouns) as a control condition, and (b) word association (after auditory presentation of nouns) as a specific semantic activation. The regional metabolic rate of glucose (rMRGlu) was calculated after brain regionalization [112 regions of interest on individual 3D flash magnetic resonance imaging (MRI)] and PET/MRI realignment. Statistical analysis was performed for comparison of association and repetition and for calculation of interregional correlation coefficients during both tasks. Compared with word repetition, word association was associated with significant increases in rMRGlu in the left prefrontal cortex, the left frontal operculum (Broca’s area) and the left insula, indicating involvement of these areas in associative language processing. Decreased rMRGlu was found in the left posterior cingulum during word association. During word repetition, highly significant negative correlations were found between the left prefrontal cortex, the contralateral cortex areas and the ipsilateral posterior cingulum. These negative correlations were almost completely eliminated during the association task, suggesting a functional decoupling of the strict intercorrelation pattern.

Simulation of 3D MRI brain images for quantitative evaluation of image segmentation algorithms

To model the true shape of MRI brain images, automatically classified T1-weighted 3D MRI images (gray matter, white matter, cerebrospinal fluid, scalp/bone and background) are utilized for simulation of grayscale data and imaging artifacts. For each class, Gaussian distribution of grayscale values is assumed, and mean and variance are computed from grayscale images. A random generator fills up the class images with Gauss-distributed grayscale values. Since grayscale values of neighboring voxels are not correlated, a Gaussian low-pass filtering is done, preserving class region borders. To simulate anatomical variability, a Gaussian distribution in space with user-defined mean and variance can be added at any user-defined position. Several imaging artifacts can be added: (1) to simulate partial volume effects, every voxel is averaged with neighboring voxels if they have a different class label; (2) a linear or quadratic bias field can be added with user-defined strength and orientation; (3) additional background noise can be added; and (4) artifacts left over after spoiling can be simulated by adding a band with increasing/decreasing grayscale values. With this method, realistic-looking simulated MRI images can be produced to test classification and segmentation algorithms regarding accuracy and robustness even in the presence of artifacts.

Dual addressing of thymidine synthesis pathways for effective targeting of proliferating melanoma

Here, we examined the potential of blocking the thymidine de novo synthesis pathways for sensitizing melanoma cells to the nucleoside salvage pathway targeting endogenous DNA irradiation. Expression of key nucleotide synthesis and proliferation enzymes thymidylate synthase (TS) and thymidine kinase 1 (TK1) was evaluated in differentiated (MITFhigh [microphthalmia‐associated transcription factor] IGR1) and invasive (MITFmedium IGR37) melanoma cells. For inhibition of de novo pathways cells were incubated either with an irreversible TS inhibitor 5‐fluoro‐2′‐deoxyuridine (FdUrd) or with a competitive dihydrofolate‐reductase (DHFR) inhibitor methotrexate (MTX). Salvage pathway was addressed by irradiation‐emitting thymidine analog [123/125I]‐5‐iodo‐4′‐thio‐2′‐deoxyuridine (123/125I‐ITdU). The in vivo targeting efficiency was visualized by single‐photon emission computed tomography. Pretreatment with FdUrd strongly increased the cellular uptake and the DNA incorporation of 125I‐ITdU into the mitotically active IGR37 cells. This effect was less pronounced in the differentiated IGR1 cells. In vivo, inhibition of TS led to a high and preferential accumulation of 123I‐ITdU in tumor tissue. This preclinical study presents profound rationale for development of therapeutic approach by highly efficient and selective radioactive targeting one of the crucial salvage pathways in melanomas.

Individual 3D region-of-interest atlas of the human brain: knowledge-based class image analysis for extraction of anatomical objects

After neural network-based classification of tissue types, the second step of atlas extraction is knowledge-based class image analysis to get anatomically meaningful objects. Basic algorithms are region growing, mathematical morphology operations, and template matching. A special algorithm was designed for each object. The class label of each voxel and the knowledge about the relative position of anatomical objects to each other and to the sagittal midplane of the brain can be utilized for object extraction. User interaction is only necessary to define starting, mid- and end planes for most object extractions and to determine the number of iterations for erosion and dilation operations. Extraction can be done for the following anatomical brain regions: cerebrum; cerebral hemispheres; cerebellum; brain stem; white matter (e.g., centrum semiovale); gray matter [cortex, frontal, parietal, occipital, temporal lobes, cingulum, insula, basal ganglia (nuclei caudati, putamen, thalami)]. For atlas- based quantification of functional data, anatomical objects can be convoluted with the point spread function of functional data to take into account the different resolutions of morphological and functional modalities. This method allows individual atlas extraction from MRI image data of a patient without the need of warping individual data to an anatomical or statistical MRI brain atlas.© (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Individual 3D region-of-interest atlas of the human brain: automatic training point extraction for neural-network-based classification of brain tissue types

Individual region-of-interest atlas extraction consists of two main parts: T1-weighted MRI grayscale images are classified into brain tissues types (gray matter (GM), white matter (WM), cerebrospinal fluid (CSF), scalp/bone (SB), background (BG)), followed by class image analysis to define automatically meaningful ROIs (e.g., cerebellum, cerebral lobes, etc.). The purpose of this algorithm is the automatic detection of training points for neural network-based classification of brain tissue types. One transaxial slice of the patient data set is analyzed. Background separation is done by simple region growing. A random generator extracts spatially uniformly distributed training points of class BG from that region. For WM training point extraction (TPE), the homogeneity operator is the most important. The most homogeneous voxels define the region for WM TPE. They are extracted by analyzing the cumulative histogram of the homogeneity operator response. Assuming a Gaussian gray value distribution in WM, a random number is used as a probabilistic threshold for TPE. Similarly, non-white matter and non-background regions are analyzed for GM and CSF training points. For SB TPE, the distance from the BG region is an additional feature. Simulated and real 3D MRI images are analyzed and error rates for TPE and classification calculated.