Respiratory gating is used for reducing the effects of breathing motion in a wide range of applications from radiotherapy treatment to diagnostical imaging. Different methods are feasible for respiratory gating. In this study seven gating methods were developed and tested on positron emission tomography (PET) listmode data. The results of seven patient studies were compared quantitatively with respect to motion and noise. (1) Equal and (2) variable time-based gating methods use only the time information of the breathing cycle to define respiratory gates. (3) Equal and (4) variable amplitude-based gating approaches utilize the amplitude of the respiratory signal. (5) Cycle-based amplitude gating is a combination of time and amplitude-based techniques. A baseline correction was applied to methods (3) and (4) resulting in two new approaches: Baseline corrected (6) equal and (7) variable amplitude-based gating. Listmode PET data from seven patients were acquired together with a respiratory signal. Images were reconstructed applying the seven gating methods. Two parameters were used to quantify the results: Motion was measured as the displacement of the heart due to respiration and noise was defined as the standard deviation of pixel intensities in a background region. The amplitude-based approaches (3) and (4) were superior to the time-based methods (1) and (2). The improvement in capturing the motion was more than 30% (up to 130%) in all subjects. The variable time (2) and amplitude (4) methods had a more uniform noise distribution among all respiratory gates compared to equal time (1) and amplitude (3) methods. Baseline correction did not improve the results. Out of seven different respiratory gating approaches, the variable amplitude method (4) captures the respiratory motion best while keeping a constant noise level among all respiratory phases.

Motion is a source of degradation in positron emission tomography (PET)/computed tomography (CT) images. As the PET images represent the sum of information over the whole respiratory cycle, attenuation correction with the help of CT images may lead to false staging or quantification of the radioactive uptake especially in the case of small tumors. We present an approach avoiding these difficulties by respiratory-gating the PET data and correcting it for motion with optical flow algorithms. The resulting dataset contains all the PET information and minimal motion and, thus, allows more accurate attenuation correction and quantification.

The motion of lung tumors with respiration causes difficulties in the imaging with computed tomography (CT) and positronemitted tomography (PET). Since an accurate knowledge of the position of the tumor and the surrounding tissues is needed for radiation treatment planning, it is important to improve CT/PET image acquisition. The purpose of this study was to evaluate the potential to improve image acquisition using phased attenuation correction in respiration correlated CT/PET, where data of both modalities were binned retrospectively. Respiration correlated scans were made on a Siemens Biograph Sensation 16 CT/PET scanner which was modified to make a low pitch CT scan and list mode PET scan possible. A lollipop phantom was used in the experiments. The sphere with a diameter of 3.1 cm was filled with approximately 20 MBq 18F-FDG. Three longitudinal movement amplitudes were tested: 2.5, 3.9, and 4.8 cm. After collection of the raw CT data, list mode PET data, and the respiratory signal CT/PET images were binned to ten phases with the help of in-house-built software. Each PET phase was corrected for attenuation with CT data of the corresponding phase. For comparison, the attenuation correction was also performed with nonrespiration correlated (non-RC) CT data. The volume and the amplitude of the movement were calculated for every phaseof both the CT and PET data (with phased attenuation correction). Maximum and average activity concentrations were compared between the phased and nonphased attenuation corrected PET. With a standard non-RC CT/PET scan, the volume was underestimated by as much as 46% in CT and the PET volume was overestimated to 370%. The volumes found with RC-CT/PET scanning had average deviations of 1.9% (+/- 4.8%) and 1.5% (+/- 3.4%) from the actual volume, for the CT and PET volumes, respectively. Evaluation of the maximum activity concentration showed a clear displacement in the images with non-RC attenuation correction, and activity values were on average14% (+/- 12%) lower than with phased attenuation correction. The standard deviation of the maximum activity values found in the different phases was a factor of 10 smaller when phased attenuation correction was applied. In this phantom study, we have shown that a combination of respiration correlated CT/PET scanning with application of phased attenuation correction can improve the imaging of moving objects and can lead to improved volume estimation and a more precise localization and quantification of the activity.

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Deep Brain Stimulation (DBS) is a surgical intervention that is known to reduce or eliminate the symptoms of common movement disorders, such as Parkinson's disease, dystonia, or tremor. During the intervention the surgeon places electrodes inside of the patient's brain to stimulate specific regions. Since these regions span only a couple of millimeters, and electrode misplacement has severe consequences, reliable and accurate navigation is of great importance. Usually the surgeon relies on fused CT and MRI data sets, as well as direct feedback from the patient. More recently Microelectrode Recordings (MER), which support navigation by measuring the electric field of the patient's brain, are also used. We propose a visualization system that fuses the different modalities: imaging data, MER and patient checks, as well as the related uncertainties, in an intuitive way to present placement-related information in a consistent view with the goal of supporting the surgeon in the final placement of the stimulating electrode. We will describe the design considerations for our system, the technical realization, present the outcome of the proposed system, and provide an evaluation.

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