Understanding fiber mixture by simulation in 3D Polarized Light Imaging.

3D Polarized Light Imaging (3D-PLI) is a neuroimaging technique that has opened up new avenues to study the complex architecture of nerve fibers in postmortem brains. The spatial orientations of the fibers are derived from birefringence measurements of unstained histological brain sections that are interpreted by a voxel-based analysis. This, however, implies that a single fiber orientation vector is obtained for each voxel and reflects the net effect of all comprised fibers. The mixture of various fiber orientations within an individual voxel is a priori not accessible by a standard 3D-PLI measurement. In order to better understand the effects of fiber mixture on the measured 3D-PLI signal and to improve the interpretation of real data, we have developed a simulation method referred to as SimPLI. By means of SimPLI, it is possible to reproduce the entire 3D-PLI analysis starting from synthetic fiber models in user-defined arrangements and ending with measurement-like tissue images. For the simulation, each synthetic fiber is considered as an optical retarder, i.e., multiple fibers within one voxel are described by multiple retarder elements. The investigation of different synthetic crossing fiber arrangements generated with SimPLI demonstrated that the derived fiber orientations are strongly influenced by the relative mixture of crossing fibers. In case of perpendicularly crossing fibers, for example, the derived fiber direction corresponds to the predominant fiber direction. The derived fiber inclination turned out to be not only influenced by myelin density but also systematically overestimated due to signal attenuation. Similar observations were made for synthetic models of optic chiasms of a human and a hooded seal which were opposed to experimental 3D-PLI data sets obtained from the chiasms of both species. Our study showed that SimPLI is a powerful method able to test hypotheses on the underlying fiber structure of brain tissue and, therefore, to improve the reliability of the extraction of nerve fiber orientations with 3D-PLI.

Does PET/MR in human brain imaging provide optimal co-registration? A critical reflection.

The introduction of hybrid positron emission/magnetic resonance tomography (PET/MR) in diagnostic clinical imaging was a major step in the evolution of ever-more sophisticated imaging systems combining two strategies formerly regarded as technically incompatible in a single device. The advent of PET/MR opened up many new avenues in clinical and research environments, mainly by providing multi-modality images obtained during a single examination. Ideally, simultaneous data acquisition with hybrid PET/MR should warrant exact image co-registration of all multi-modality image volumes provided by both systems. This assumes that there is negligible mutual electronic, technical and logistical interference on the respective simultaneous measurements. Recently, such hybrid dedicated head and whole-body systems were successfully applied in an increasing number of cases. When employed for brain imaging, PET/MR has the potential to provide high-resolution multi-modality datasets. However, it also demands careful consideration of the multitude of features offered, as well as the limitations. There are open issues that have to be considered, such as the handling of patient motion during extended periods of data acquisition, optimized sampling of derived images to ease the visual interpretation and quantitative evaluation of co-registered images. This paper will briefly summarize the current status of PET/MR within the framework of developments for image co-registration and discuss current limitations and future perspectives.

Automatic identification of gray and white matter components in polarized light imaging.

Polarized light imaging (PLI) enables the visualization of fiber tracts with high spatial resolution in microtome sections of postmortem brains. Vectors of the fiber orientation defined by inclination and direction angles can directly be derived from the optical signals employed by PLI analysis. The polarization state of light propagating through a rotating polarimeter is varied in such a way that the detected signal of each spatial unit describes a sinusoidal signal. Noise, light scatter and filter inhomogeneities, however, interfere with the original sinusoidal PLI signals, which in turn have direct impact on the accuracy of subsequent fiber tracking. Recently we showed that the primary sinusoidal signals can effectively be restored after noise and artifact rejection utilizing independent component analysis (ICA). In particular, regions with weak intensities are greatly enhanced after ICA based artifact rejection and signal restoration. Here, we propose a user independent way of identifying the components of interest after decomposition; i.e., components that are related to gray and white matter. Depending on the size of the postmortem brain and the section thickness, the number of independent component maps can easily be in the range of a few ten thousand components for one brain. Therefore, we developed an automatic and, more importantly, user independent way of extracting the signal of interest. The automatic identification of gray and white matter components is based on the evaluation of the statistical properties of the so-called feature vectors of each individual component map, which, in the ideal case, shows a sinusoidal waveform. Our method enables large-scale analysis (i.e., the analysis of thousands of whole brain sections) of nerve fiber orientations in the human brain using polarized light imaging.

A novel approach to the human connectome: ultra-high resolution mapping of fiber tracts in the brain.

Signal transmission between different brain regions requires connecting fiber tracts, the structural basis of the human connectome. In contrast to animal brains, where a multitude of tract tracing methods can be used, magnetic resonance (MR)-based diffusion imaging is presently the only promising approach to study fiber tracts between specific human brain regions. However, this procedure has various inherent restrictions caused by its relatively low spatial resolution. Here, we introduce 3D-polarized light imaging (3D-PLI) to map the three-dimensional course of fiber tracts in the human brain with a resolution at a submillimeter scale based on a voxel size of 100 µm isotropic or less. 3D-PLI demonstrates nerve fibers by utilizing their intrinsic birefringence of myelin sheaths surrounding axons. This optical method enables the demonstration of 3D fiber orientations in serial microtome sections of entire human brains. Examples for the feasibility of this novel approach are given here. 3D-PLI enables the study of brain regions of intense fiber crossing in unprecedented detail, and provides an independent evaluation of fiber tracts derived from diffusion imaging data.

Advanced Monte Carlo simulations of emission tomography imaging systems with GATE.

Built on top of the Geant4 toolkit, GATE is collaboratively developed for more than 15 years to design Monte Carlo simulations of nuclear-based imaging systems. It is, in particular, used by researchers and industrials to design, optimize, understand and create innovative emission tomography systems. In this paper, we reviewed the recent developments that have been proposed to simulate modern detectors and provide a comprehensive report on imaging systems that have been simulated and evaluated in GATE. Additionally, some methodological developments that are not specific for imaging but that can improve detector modeling and provide computation time gains, such as Variance Reduction Techniques and Artificial Intelligence integration, are described and discussed.

The current state, challenges and perspectives of MR-PET.

Following the success of PET/CT during the last decade and the recent increasing proliferation of SPECT/CT, another hybrid imaging instrument has been gaining more and more interest: MR-PET. First combined, simultaneous PET and MR studies carried out in small animals demonstrated the feasibility of the new approach. Concurrently, some prototypes of an MR-PET scanner for simultaneous human brain studies have been built, their performance is being tested and preliminary applications have already been shown. Through this pioneering work, it has become clear that advances in the detector design are necessary for further optimization. Recently, the different issues related to the present state and future prospects of MR-PET were presented and discussed during an international 2-day workshop at the Forschungszentrum Jülich, Germany, held after, and in conjunction with, the 2008 IEEE Nuclear Science Symposium and Medical Imaging Conference in Dresden, Germany on October 27-28, 2008. The topics ranged from small animal MR-PET imaging to human MR-BrainPET imaging, new detector developments, challenges/opportunities for ultra-high field MR-PET imaging and considerations of possible future research and clinical applications. This report presents a critical summary of the contributions made to the workshop.

Signal enhancement in polarized light imaging by means of independent component analysis.

Polarized light imaging (PLI) enables the evaluation of fiber orientations in histological sections of human postmortem brains, with ultra-high spatial resolution. PLI is based on the birefringent properties of the myelin sheath of nerve fibers. As a result, the polarization state of light propagating through a rotating polarimeter is changed in such a way that the detected signal at each measurement unit of a charged-coupled device (CCD) camera describes a sinusoidal signal. Vectors of the fiber orientation defined by inclination and direction angles can then directly be derived from the optical signals employing PLI analysis. However, noise, light scatter and filter inhomogeneities interfere with the original sinusoidal PLI signals. We here introduce a novel method using independent component analysis (ICA) to decompose the PLI images into statistically independent component maps. After decomposition, gray and white matter structures can clearly be distinguished from noise and other artifacts. The signal enhancement after artifact rejection is quantitatively evaluated in 134 histological whole brain sections. Thus, the primary sinusoidal signals from polarized light imaging can be effectively restored after noise and artifact rejection utilizing ICA. Our method therefore contributes to the analysis of nerve fiber orientation in the human brain within a micrometer scale.

Scatter Correction Based on GPU-Accelerated Full Monte Carlo Simulation for Brain PET/MRI.

Accurate scatter correction is essential for qualitative and quantitative PET imaging. Until now, scatter correction based on Monte Carlo simulation (MCS) has been recognized as the most accurate method of scatter correction for PET. However, the major disadvantage of MCS is its long computational time, which makes it unfeasible for clinical usage. Meanwhile, single scatter simulation (SSS) is the most widely used method for scatter correction. Nevertheless, SSS has the disadvantage of limited robustness for dynamic measurements and for the measurement of large objects. In this work, a newly developed implementation of MCS using graphics processing unit (GPU) acceleration is employed, allowing full MCS-based scatter correction in clinical 3D brain PET imaging. Starting from the generation of annihilation photons to their detection in the simulated PET scanner, all relevant physical interactions and transport phenomena of the photons were simulated on GPUs. This resulted in an expected distribution of scattered events, which was subsequently used to correct the measured emission data. The accuracy of the approach was validated with simulations using GATE (Geant4 Application for Tomography Emission), and its performance was compared to SSS. The comparison of the computation time between a GPU and a single-threaded CPU showed an acceleration factor of 776 for a voxelized brain phantom study. The speedup of the MCS implemented on the GPU represents a major step toward the application of the more accurate MCS-based scatter correction for PET imaging in clinical routine.

Evaluation of registration strategies for multi-modality images of rat brain slices.

In neuroscience, small-animal studies frequently involve dealing with series of images from multiple modalities such as histology and autoradiography. The consistent and bias-free restacking of multi-modality image series is obligatory as a starting point for subsequent non-rigid registration procedures and for quantitative comparisons with positron emission tomography (PET) and other in vivo data. Up to now, consistency between 2D slices without cross validation using an inherent 3D modality is frequently presumed to be close to the true morphology due to the smooth appearance of the contours of anatomical structures. However, in multi-modality stacks consistency is difficult to assess. In this work, consistency is defined in terms of smoothness of neighboring slices within a single modality and between different modalities. Registration bias denotes the distortion of the registered stack in comparison to the true 3D morphology and shape. Based on these metrics, different restacking strategies of multi-modality rat brain slices are experimentally evaluated. Experiments based on MRI-simulated and real dual-tracer autoradiograms reveal a clear bias of the restacked volume despite quantitatively high consistency and qualitatively smooth brain structures. However, different registration strategies yield different inter-consistency metrics. If no genuine 3D modality is available, the use of the so-called SOP (slice-order preferred) or MOSOP (modality-and-slice-order preferred) strategy is recommended.

Resolution modeling in projection space using a factorized multi-block detector response function for PET image reconstruction.

Positron emission tomography (PET) images usually suffer from limited resolution and statistical uncertainties. However, a technique known as resolution modeling (RM) can be used to improve image quality by accurately modeling the system's detection process within the iterative reconstruction. In this study, we present an accurate RM method in projection space based on a simulated multi-block detector response function (DRF) and evaluate it on the Siemens hybrid MR-BrainPET system. The DRF is obtained using GATE simulations that consider nearly all the possible annihilation photons from the field-of-view (FOV). Intrinsically, the multi-block DRF allows the block crosstalk to be modeled. The RM blurring kernel is further generated by factorizing the blurring matrix of one line-of-response (LOR) into two independent detector responses, which can then be addressed with the DRF. Such a kernel is shift-variant in 4D projection space without any distance or angle compression, and is integrated into the image reconstruction for the BrainPET insert with single instruction multiple data (SIMD) and multi-thread support. Evaluation of simulations and measured data demonstrate that the reconstruction with RM yields significantly improved resolutions and reduced mean squared error (MSE) values at different locations of the FOV, compared with reconstruction without RM. Furthermore, the shift-variant RM kernel models the varying blurring intensity for different LORs due to the depth-of-interaction (DOI) dependencies, thus avoiding severe edge artifacts in the images. Additionally, compared to RM in single-block mode, the multi-block mode shows significantly improved resolution and edge recovery at locations beyond 10 cm from the center of BrainPET insert in the transverse plane. However, the differences have been observed to be low for patient data between single-block and multi-block mode RM, due to the brain size and location as well as the geometry of the BrainPET insert. In conclusion, the RM method proposed in this study can yield better reconstructed images in terms of resolution and MSE value, compared to conventional reconstruction without RM.

Whole-body PET/CT imaging: combining software- and hardware-based co-registration.

AIM: Combined whole-body (WB) PET/CT imaging provides better overall co-registration compared to separate CT and PET. However, in clinical routine local PET-CT mis-registration cannot be avoided. Thus, the reconstructed PET tracer distribution may be biased when using the misaligned CT transmission data for CT-based attenuation correction (CT-AC). We investigate the feasibility of retrospective co-registration techniques to align CT and PET images prior to CT-AC, thus improving potentially the quality of combined PET/CT imaging in clinical routine. METHODS: First, using a commercial software registration package CT images were aligned to the uncorrected PET data by rigid and non-rigid registration methods. Co-registration accuracy of both alignment approaches was assessed by reviewing the PET tracer uptake patterns (visual, linked cursor display) following attenuation correction based on the original and co-registered CT. Second, we investigated non-rigid registration based on a prototype ITK implementation of the B-spline algorithm on a similar targeted MR-CT registration task, there showing promising results. RESULTS: Manual rigid, landmark-based co-registration introduced unacceptable misalignment, in particular in peripheral areas of the whole-body images. Manual, non-rigid landmark-based co-registration prior to CT-AC was successful with minor loco-regional distortions. Nevertheless, neither rigid nor non-rigid automatic co-registration based on the Mutual Information image to image metric succeeded in co-registering the CT and no AC-PET images. In contrast to widely available commercial software registration our implementation of an alternative automated, non-rigid B-spline co-registration technique yielded promising results in this setting with MR-CT data. CONCLUSION: In clinical PET/CT imaging, retrospective registration of CT and uncorrected PET images may improve the quality of the AC-PET images. As of today no validated and clinically viable commercial registration software is in routine use. This has triggered our efforts in pursuing new approaches to a validated, non-rigid co-registration algorithm applicable to whole-body PET/CT imaging of which first results are presented here. This approach appears suitable for applications in retrospective WB-PET/CT alignment.

Prediction of Alzheimer's Dementia in Patients with Amnestic Mild Cognitive Impairment in Clinical Routine: Incremental Value of Biomarkers of Neurodegeneration and Brain Amyloidosis Added Stepwise to Cognitive Status.

The aim of this study was to evaluate the incremental benefit of biomarkers for prediction of Alzheimer's disease dementia (ADD) in patients with mild cognitive impairment (MCI) when added stepwise in the order of their collection in clinical routine. The model started with cognitive status characterized by the ADAS-13 score. Hippocampus volume (HV), cerebrospinal fluid (CSF) phospho-tau (pTau), and the FDG t-sum score in an AD meta-region-of-interest were compared as neurodegeneration markers. CSF-Aß1-42 was used as amyloidosis marker. The incremental prognostic benefit from these markers was assessed by stepwise Kaplan-Meier survival analysis in 402 ADNI MCI subjects. Predefined cutoffs were used to dichotomize patients as 'negative' or 'positive' for AD characteristic alteration with respect to each marker. Among the neurodegeneration markers, CSF-pTau provided the best incremental risk stratification when added to ADAS-13. FDG PET outperformed HV only in MCI subjects with relatively preserved cognition. Adding CSF-Aß provided further risk stratification in pTau-positive subjects, independent of their cognitive status. Stepwise integration of biomarkers allows stepwise refinement of risk estimates for MCI-to-ADD progression. Incremental benefit strongly depends on the patient's status according to the preceding diagnostic steps. The stepwise Kaplan-Meier curves might be useful to optimize diagnostic workflow in individual patients.

PET attenuation correction for rigid MR Tx/Rx coils from 176Lu background activity.

One challenge for PET-MR hybrid imaging is the correction for attenuation of the 511 keV annihilation radiation by the required RF transmit and/or RF receive coils. Although there are strategies for building PET transparent Tx/Rx coils, such optimised coils still cause significant attenuation of the annihilation radiation leading to artefacts and biases in the reconstructed activity concentrations. We present a straightforward method to measure the attenuation of Tx/Rx coils in simultaneous MR-PET imaging based on the natural 176Lu background contained in the scintillator of the PET detector without the requirement of an external CT scanner or PET scanner with transmission source. The method was evaluated on a prototype 3T MR-BrainPET produced by Siemens Healthcare GmbH, both with phantom studies and with true emission images from patient/volunteer examinations. Furthermore, the count rate stability of the PET scanner and the x-ray properties of the Tx/Rx head coil were investigated. Even without energy extrapolation from the two dominant γ energies of 176Lu to 511 keV, the presented method for attenuation correction, based on the measurement of 176Lu background attenuation, shows slightly better performance than the coil attenuation correction currently used. The coil attenuation correction currently used is based on an external transmission scan with rotating 68Ge sources acquired on a Siemens ECAT HR + PET scanner. However, the main advantage of the presented approach is its straightforwardness and ready availability without the need for additional accessories.

Mental speed is associated with the shape irregularity of white matter MRI hyperintensity load.

Brain MRI white matter hyperintensities (WMHs) are common in elderly subjects. Their impact on cognition, however, appears highly variable. Complementing conventional scoring of WMH load (volume and location) by quantitative characterization of the shape irregularity of WMHs might improve the understanding of the relationship between WMH load and cognitive performance. Here we propose the "confluency sum score" (COSU) as a marker of the total shape irregularity of WMHs in the brain. The study included two independent patient samples: 87 cognitively impaired geriatric inpatients from a prospective neuroimaging study (iDSS) and 198 subjects from the National Alzheimer's Coordinating Center (NACC) database (132 with, 66 w/o cognitive impairment). After automatic segmentation and clustering of the WMHs on FLAIR (LST toolbox, SPM8), the confluency of the i-th contiguous WMH cluster was computed as confluencyi = [1/(36π)∙surfacei3/volumei2]1/3-1. The COSU was obtained by summing the confluency over all WMH clusters. COSU was tested for correlation with CERAD-plus subscores. Correlation analysis was restricted to subjects with at least moderate WMH load (≥ 13.5 ml; iDSS / NACC: n = 52 / 80). In the iDSS sample, among the 12 CERAD-plus subtests the trail making test A (TMT-A) was most strongly correlated with the COSU (Spearman rho = -0.345, p = 0.027). TMT-A performance was not associated with total WMH volume (rho = 0.147, p = 0.358). This finding was confirmed in the NACC sample (rho = -0.261, p = 0.023 versus rho = -0.040, p = 0.732). Cognitive performance in specific domains including mental speed and fluid abilities seems to be more strongly associated with the shape irregularity of white matter MRI hyperintensities than with their volume.

Concepts of registration and correction of head motion in positron emission tomography.

The long acquisition times (up to hours) in PET brain imaging bear a high risk of head motion, which results in artefacts like blurred images and may even lead to misinterpretation and useless data. With the increased resolution of high performance PET scanners, the influence of head movements becomes more and more relevant. Especially in the analysis of small brain structures, e.g. during ROI-analysis, head motion results in inaccuracies of quantified data. This may also influence the kinetic analysis and generate artifacts in parametric images calculated from a motion-affected image sequence. This work presents the feasibility of head motion registration using an external motion tracking system. The implementation of the multi acquisition frame method and an event-by-event method to correct PET data for motion are described. The effects of motion correction are demonstrated on the basis of phantom measurements and patient data. The influence of motion correction on parametric imaging is described in a receptor study.

On the use of positioning aids to reduce misregistration in the head and neck in whole-body PET/CT studies.

UNLABELLED: Involuntary patient motion from insufficient patient preparation may lead to local misregistration of PET/CT images and, thus, can invalidate the attempt to fuse the resulting images. We estimate the efficacy of selected patient support structures in reducing the likelihood of patient motion in the area of the head and neck during whole-body PET/CT studies. METHODS: Motion of the head and neck was estimated in 51 healthy volunteers during simulated whole-body PET/CT studies using an infrared camera-based tracking system. Four patient positioning schemes (arms down) were studied, with the neck placed on a standard PET head holder with no support at the sides (setup A), on a special head holder fitted with a subject-specific mold from construction foam (setup B), on a vacuum-lock bag (setup C), and on a special head holder fitted with a vacuum-lock bag (setup D). We report the average motion of the head and neck as the difference in the position of a set of target points between the simulated CT image and PET image of the head and neck. To estimate the efficacy of additional patient support measures in clinical practice, we reviewed the misregistration of the head and neck in whole-body PET/CT studies of 10 patients each who were imaged using setups A and C by comparing the mean translational and rotational alignment parameters from a semiautomatic linear registration approach needed to realign the CT and PET images. RESULTS: Average translational and rotational misalignment of the head and neck was highest for setup A, at 7 mm and 1 degrees , respectively. Misalignment was reduced to a minimum of 1.4 mm and 0.3 degrees for setup D. Setup B resulted in a similar reduction in patient motion of the head and neck: 2.4 mm and 0.4 degrees , whereas setup C provided only somewhat improved support, with a resulting average misalignment of 4.5 mm and 0.7 degrees. In clinical PET/CT, we found setup C to reduce translational misalignment of the CT and PET images of the head and neck to 2 mm, compared with 6 mm for setup A, whereas no significant reduction of rotational misalignment was observed. CONCLUSION: Average motion of the head and neck in unrestrained subjects during whole-body PET/CT examinations can be reduced by use of rigid positioning aids, such as foam molds, or vacuum-lock bags. Vacuum-lock bags are reusable, quickly adaptable, and olfactory neutral and can be used routinely, either alone or in combination with a head holder, in whole-body PET/CT for high-quality examinations.

Motion artifact reduction on parametric PET images of neuroreceptor binding.

UNLABELLED: PET studies of cerebral neuroreceptors are often recorded over periods ranging from 1 to 2 h, and head movements during the studies not only lead to blurred images but also may seriously disturb the kinetic analysis. We report the effect of motion on parametric images of the distribution volume ratio (DVR), as well as possible improvements if the dynamic PET data are corrected for head movements. METHODS: The study was performed with the 5-hydroxytryptamine 2A receptor ligand (18)F-altanserin. During PET scanning, which was performed in list mode for 1 h, the position of the head was monitored by an infrared motion-tracking system. The list mode data were sorted into time frames of between 10 s and 2 min. Motion was corrected using the multiple-acquisition-frame (MAF) approach, which calculates individual attenuation files for each emission frame and its corresponding head position to avoid misalignment of transmission and emission data. After reconstruction of attenuation-corrected emission frames, each image frame was realigned to match the head position of the first frame of the emission scan. The resulting motion-corrected dynamic images were evaluated using the noninvasive Logan plot to obtain parametric images of DVR. RESULTS: DVR images of motion-affected (18)F-altanserin scans showed artifacts whose extent depended on the amount of movement. The artifacts were mainly at the border between gray matter and white matter and at the outer border of gray matter. They were seen as discontinuities and small spots whose values exceeded the expected DVR values or were even negative and that disappeared when motion correction was applied. These effects in human data were also seen on simulated (18)F-altanserin images that contained no statistical noise. CONCLUSION: Whereas the native PET images looked just blurred if the patient moved during the PET scan, parametric images of the Logan DVR, which are calculated by pixelwise linear regression, contained severe discontinuities primarily at the cortical edge. MAF-based motion correction was able to avoid these errors.

A multiscale approach for the reconstruction of the fiber architecture of the human brain based on 3D-PLI.

Structural connectivity of the brain can be conceptionalized as a multiscale organization. The present study is built on 3D-Polarized Light Imaging (3D-PLI), a neuroimaging technique targeting the reconstruction of nerve fiber orientations and therefore contributing to the analysis of brain connectivity. Spatial orientations of the fibers are derived from birefringence measurements of unstained histological sections that are interpreted by means of a voxel-based analysis. This implies that a single fiber orientation vector is obtained for each voxel, which reflects the net effect of all comprised fibers. We have utilized two polarimetric setups providing an object space resolution of 1.3 µm/px (microscopic setup) and 64 µm/px (macroscopic setup) to carry out 3D-PLI and retrieve fiber orientations of the same tissue samples, but at complementary voxel sizes (i.e., scales). The present study identifies the main sources which cause a discrepancy of the measured fiber orientations observed when measuring the same sample with the two polarimetric systems. As such sources the differing optical resolutions and diverging retardances of the implemented waveplates were identified. A methodology was implemented that enables the compensation of measured different systems' responses to the same birefringent sample. This opens up new ways to conduct multiscale analysis in brains by means of 3D-PLI and to provide a reliable basis for the transition between different scales of the nerve fiber architecture.

Model-based verification of a non-linear separation scheme for ballistocardiography.

The current rise in popularity of ballisto-cardiography-related research has led to the development of new sensor concepts and recording methods. Measuring the ballistocardiogram using bed mounted pressure sensors opens up new possibilities for home monitoring applications. The signals measured with these sensors contain a mixture of cardiac and respiratory components, which can be used for detection of comorbidities of heart failure like apnea or arrhythmia. However, the separation of the cardiac and respiratory components has proven to be difficult, since there is significant overlap in the spectra of both components. In this paper, an algorithm for the separation task is presented, which can overcome the problem of overlapping spectra. Additionally, a model has been developed for the generation of artificial ballistocardiograms, which are used to analyze the separation performance. Furthermore, the algorithm is tested on preliminary data from a clinical study.

A review of the use and potential of the GATE Monte Carlo simulation code for radiation therapy and dosimetry applications.

In this paper, the authors' review the applicability of the open-source GATE Monte Carlo simulation platform based on the GEANT4 toolkit for radiation therapy and dosimetry applications. The many applications of GATE for state-of-the-art radiotherapy simulations are described including external beam radiotherapy, brachytherapy, intraoperative radiotherapy, hadrontherapy, molecular radiotherapy, and in vivo dose monitoring. Investigations that have been performed using GEANT4 only are also mentioned to illustrate the potential of GATE. The very practical feature of GATE making it easy to model both a treatment and an imaging acquisition within the same framework is emphasized. The computational times associated with several applications are provided to illustrate the practical feasibility of the simulations using current computing facilities.