Gudrun Wagenknecht

MRI for attenuation correction in PET: methods and challenges

In current combined PET/MR systems, PET attenuation correction is based on MRI, since the small bore inside MRI systems and the strong magnetic field do not permit a rotating PET transmission source or a CT device to be integrated. Unlike CT measurements in PET/CT scanners, the MR signal is not directly correlated to tissue density and thus cannot be converted by a simple transformation of intensity values. Various approaches have been developed based on templates, atlas information, direct segmentation of T1-weighted MR images, or segmentation of images from special MR sequences. The advantages and disadvantages of these approaches as well as additional challenges will be discussed in this review.

A contour tracing and coding algorithm for generating 2D contour codes from 3D classified objects

In 3D image data sets generated by voxel-based classification, each voxel is marked with a specific class label. Voxels of the same class label can form 3D objects of extremely complex shape. Interactively drawn regions are usually represented by their 2D region borders. In order to combine automatically classified with interactively drawn regions, a contour tracing and coding algorithm for generating optimized 2D contours from 3D classified objects is presented. A special conversion algorithm allows a chain or a crack code representation. An application to medical images shows the methods necessity and usefulness in dealing with highly complex regions.

Attenuation correction in MR-PET scanners with segmented T1-weighted MR images

Attenuation correction of PET data acquired in new hybrid MR-PET scanners which do not offer the possibility of a measured attenuation correction can be done in different ways. A previous report of our group described a method which used attenuation templates. The present study utilizes a new knowledge-based segmentation approach applied on T1-weighted MR images. It examines the position and the tissue membership of each voxel and segments the head volume into attenuation-differing regions: brain tissue, extracerebral soft tissue, skull, air-filled nasal and paranasal cavities as well as the mastoid process. To examine this new approach three groups of subjects having MRI and PET were chosen, the selection criterion being the different MR scanners, while the PET scanner was the ECAT HR+ in all cases: 1) four subjects with 1.5T MR images and CPFPX PET scans, 2) four subjects with 3T MR images and Altanserin PET scans, and 3) three brain tumor patients with 3T MR images from the hybrid MR-BrainPET scanner and FET PET scans. Furthermore, a single subject had 3T MR images, a FDG PET scan, and an additional CT scan. All segmented T1-weighted MR images were converted into attenuation maps for 511 KeV photons with coefficients of 0.096 1/cm for brain tissue, 0.146 1/cm for skull, 0.095 1/cm for soft tissue, 0.054 1/cm for the mastoid process, and 0.0 1/cm for nasal and paranasal cavities. The CT volume was also converted from the Hounsfield units into attenuation coefficients valid for 511 keV photons. The 12 segmented-based attenuation (SBA) maps as well as the CT-based attenuation (CBA) map were first filtered by a 3D Gaussian kernel of 10 mm filter width and then used to reconstruct the corresponding PET emission data. These were compared to the PET images attenuation corrected using the conventional PET-based transmission data (PBA). Relative differences (RD) were calculated from ROIs. For the single subject the RD of CBA data exhibit a mean of 1.66%?0.84% with a range from -0.88% to 3.42%, while the RDs mean of SBA data is 1.42%?2.61% (range from -4.12% to 4.66%). Comparing the results obtained with the SBA correction only, the RD for 1) range from -6.10% to 2.56% for cortical regions and from -6.99% to 5.64% for subcortical regions; for 2) they range from -7.33% to 2.33% for the cortical regions, subcortical ones being not drawn due to the not significant tracer uptake; for 3) the mean over the three subjects resulted in 0.89%?1.10% for ROIs at 48% threshold of the images maximum and in 2.25%?1.50% for ROIs at 72% threshold. ROIs on the healthy contra-lateral grey matter show a mean of -3.24%?0.87%. In conclusion, the first attenuation correction results obtained with the new segmented-based method on a strongly heterogeneous collective are very promising. Further improvements of the method will be focused on the delineation of the skull.

Fully automated radiosynthesis of both enantiomers of [18F]Flubatine under GMP conditions for human application

A fully automatized radiosynthesis of (+)- and (-)-[(18)F]Flubatine ((+)- and (-)NCFHEB) by means of a commercially available synthesis module (TRACERlab FX FN) under GMP conditions is reported. Radiochemical yields of 30% within an overall synthesis time of 40 min were achieved in more than 70 individual syntheses. Specific activities were approximately 3000 GBq/μmol and radiochemical purity was determined to be at least 97%.

Evaluation of metabolism, plasma protein binding and other biological parameters after administration of (−)-( 18 F)Flubatine in humans

INTRODUCTION (-)-[(18)F]Flubatine is a PET tracer with high affinity and selectivity for the nicotinic acetylcholine α4β2 receptor subtype. A clinical trial assessing the availability of this subtype of nAChRs was performed. From a total participant number of 21 Alzheimers disease (AD) patients and 20 healthy controls (HCs), the following parameters were determined: plasma protein binding, metabolism and activity distribution between plasma and whole blood. METHODS Plasma protein binding and fraction of unchanged parent compound were assessed by ultracentrifugation and HPLC, respectively. The distribution of radioactivity (parent compound+metabolites) between plasma and whole blood was determined ex vivo at different time-points after injection by gamma counting after separation of whole blood by centrifugation into the cellular and non-cellular components. In additional experiments in vitro, tracer distribution between these blood components was assessed for up to 90min. RESULTS A fraction of 15%±2% of (-)-[(18)F]Flubatine was found to be bound to plasma proteins. Metabolic degradation of (-)-[(18)F]Flubatine was very low, resulting in almost 90% unchanged parent compound at 90min p.i. with no significant difference between AD and HC. The radioactivity distribution between plasma and whole blood changed in vivo only slightly over time from 0.82±0.03 at 3min p.i. to 0.87±0.03 at 270min p.i. indicating the contribution of only a small amount of metabolites. In vitro studies revealed that (-)-[(18)F]Flubatine was instantaneously distributed between cellular and non-cellular blood parts. DISCUSSION (-)-[(18)F]Flubatine exhibits very favourable characteristics for a PET radiotracer such as slow metabolic degradation and moderate plasma protein binding. Equilibrium of radioactivity distribution between plasma and whole blood is reached instantaneously and remains almost constant over time allowing both convenient sample handling and facilitated fractional blood volume contribution assessment.

CT-based evaluation of segmented head regions for attenuation correction in MR-PET systems

Attenuation correction (AC) is an important prerequisite for quantitative brain PET in MR-BrainPET systems. The new knowledge-based method segments attenuation-differing head regions solely based on the routinely acquired T1-weighted MR data set of the patients head. The original approach (O) was extended (E1-E3) with regard to the MR image quality at different bandwidth/voxel (130 HZ/voxel, 610 Hz/voxel) obtained at a 3T MR TimTrio system with BrainPET insert installed. Based on the Dice coefficient, the automatically obtained MR-based segmentation results for bone and soft tissue were compared with segmented CT data as gold standard modality data. So far, registered multi-modality data (MR, CT, PET) are available for one female volunteer F and two tumor patients T1, T2 with CT data of different image quality. Best results were obtained for BW130-E3 and BW610-E2. For F, the Dice coefficient for bone is up to 0.776 for BW130-E3 and up to 0.723 for BW610-E2 in the best part of the cranial region. The Dice coefficient for soft tissue is 0.867 for BW130-E3 and 0.868 for BW610-E2 in the whole data set used for AC. The SegMR-(SBA) and CT-based AC (CBA) were compared w.r.t. PET-based AC (PBA) for a HR+ PET device. AC with SBA yields very similar results to the gold standard CBA.

Attenuation correction in MR-BrainPET with segmented T1-weighted MR images of the patient's head — A comparative study with CT

Our method for attenuation correction (AC) in MR-BrainPET with segmented T1-weighted MR images of the pa-tients head was applied to data from different MR-BrainPET scanners (Jülich, Tübingen) and compared to CT-based results.

Automated topology correction for human brain segmentation

We describe a new method to reconstruct human brain structures from 3D magnetic resonance brain images. Our method provides a fully automatic topology correction mechanism, thus avoiding tedious manual correction. Topological correctness is important because it is an essential prerequisite for brain atlas deformation and surface flattening. Our method uses an axis-aligned sweep through the volume to locate handles. Handles are detected by successively constructing and analyzing a directed graph. A multiple local region-growing process is used which simultaneously acts on the foreground and the background to isolate handles and tunnels. The sizes of handles and tunnels are measured, then handles are removed or tunnels filled based on their sizes. This process was used for 256 T1-weighted MR volumes.

Viewpoints on Medical Image Processing: From Science to Application

Medical image processing provides core innovation for medical imaging. This paper is focused on recent developments from science to applications analyzing the past fifteen years of history of the proceedings of the German annual meeting on medical image processing (BVM). Furthermore, some members of the program committee present their personal points of views: (i) multi-modality for imaging and diagnosis, (ii) analysis of diffusion-weighted imaging, (iii) model-based image analysis, (iv) registration of section images, (v) from images to information in digital endoscopy, and (vi) virtual reality and robotics. Medical imaging and medical image computing is seen as field of rapid development with clear trends to integrated applications in diagnostics, treatment planning and treatment.

Volume-of-interest segmentation of cortical regions for multimodal brain analysis

Multimodal tomographic images (e.g., MRI, PET images) provide important information for research, diagnosis and therapy of brain diseases. Structural and functional properties and changes in cortical brain regions are often examined quantitatvely in certain volumes of interest (VOIs) bounded by tissue borders and cortical sulci as important VOI borders. Thus, VOI segmentation is an important prerequisite for this kind of brain analysis. In order to avoid time-consuming slice-by-slice segmentation of VOIs, the new semi-automatic method aims at segmenting cortical VOIs based on 3D brain surface visualization and thus defining VOI borders along cortical sulci much easily than in successive 2D slices. The method was evaluated based on phantoms with simulated sulcus and class properties and real brain data sets. Promising results were obtained regarding segmentation accuracy and computation time.