No description available.

Accurate attenuation correction is essential for quantitative positron emission tomography. Typically, this correction is based on a coincidence transmission measurement using an external source of positron emitter, which is positioned close to the detectors. This technique suffers from poor statistical quality and high dead time losses, especially with a high transmission source strength. We have proposed and tested the use of single photon transmission measurement with a rotating rod source, to measure the attenuation correction factors (ACFs). The singles projections are resampled into the coincidence geometry using the detector positions and the r,)d source location. A nonparalyzable dead time correction algorithm was developed for the block detectors used in the McMaster PET scanner. Transaxial resolution is approximately 6 mm, which is comparable to emission scanning performance. Axial resolution is about 25 mm, with only crude source collimation. ACFs are underestimated by approximately 10% due to increased crossplane scatter, compared to coincidence transmission scanning. Effective source collimation is necessary to obtain suitable axial resolution and improved accuracy. The response of the correction factors to object density is linear to within 15%, when comparing singles transmission measurement to current coincidence transmission measurement. The major advantage of using singles transmission measurement IS a dramatically increased count rate. A factor of seven increase in count rate over coincidence scanning is possible with a 2 mCi transmission rod source. There are no randoms counted in singles transmission scans, which makes the measured count rate nearly linearly proportional with source activity. Singles detector dead time is approximately 6% in the detectors opposite a 2 mCi rod source. Present hardware and software precludes the application of this technique in a clinical environment. We anticipate that real time acquisition of detector singles can reduce the transmission scanning time to under 2 minutes, and produce attenuation coefficient images with under 2% noise. This is a significant improvement compared to the current coincidence transmission technique. / Thesis / Master of Science (MS)

Background: In PET/MRI, linear photon attenuation coefficients for attenuation correction (AC) cannot be directly derived, and cortical bone is, so far, usually not considered. This results in an underestimation of the average PET signal in PET/MRI. Recently introduced MR-AC methods predicting bone information from anatomic MRI or proton density weighted zero-time imaging may solve this problem in the future. However, there is an ongoing debate if the current error is acceptable for clinical use and/or research. Methods: We examined this feature for [18F] fluorodeoxyglucose (FDG) brain PET in 13 patients with clinical signs of dementia or movement disorders who subsequently underwent PET/CT and PET/MRI on the same day. Multiple MR-AC approaches including a CT-derived AC were applied. Results: The resulting PET data was compared to the CT-derived standard regarding the quantification error and its clinical impact. On a quantitative level, −11.9 to +2 % deviations from the CT-AC standard were found. These deviations, however, did not translate into a systematic diagnostic error. This, as overall patterns of hypometabolism (which are decisive for clinical diagnostics), remained largely unchanged. Conclusions: Despite a quantitative error by the omission of bone in MR-AC, clinical quality of brain [18F]FDG is not relevantly affected. Thus, brain [18F]FDG PET can already, even now with suboptimal MR-AC, be utilized for clinical routine purposes, even though the MR-AC warrants improvement.

Networks of small, often mobile, polarimetric radars are gaining popularity in the hydrometeorology community due to their rainfall observing capabilities and relative low purchase cost. In recent years, a number of installations have become operational around the globe. The problem of signal attenuation by intervening rainfall has been recognized as the major source of error in rainfall estimation by short-wavelength (C-, X, K-band) radars. The simultaneous observation of precipitation by multiple radars creates new prospects for better and more robust attenuation correction algorithms and, consequently, yields more accurate rainfall estimation. The University of Iowa hydrometeorology group's acquisition of a network of four mobile, polarimetric, X-band radars has resulted in the need for a thoughtful evaluation of the instrument. In this work, we use computer simulations and the data collected by The University of Iowa Polarimetric Radar Network to study the performance of attenuation correction methods in single-radar and network-based arrangements. To support the computer simulations, we developed a comprehensive polarimetric radar network simulator, which replicates the essential aspects of the radar network rainfall observing process. The simulations are based on a series of physics- and stochastic-based simulated rainfall events occurring over the area of interest. The characteristics of the simulated radars are those of The University of Iowa Polarimetric Radar Network. We assess the correction methods by analyzing the errors in reflectivity and rainfall rate over the area of interest covered by the network's radars. To enable the implementation of the attenuation correction methods to the data collected by The University of Iowa Polarimetric Radar Network, we first developed a set of utilities to assist with efficient data collection and analysis. Next, we conducted a series of calibration tests to evaluate the relative calibration and channel balance of the 2 network's radars. Finally, in an attempt to verify the results obtained via computer simulations, we applied the set of attenuation correction algorithms to the data collected by The University of Iowa Polarimetric Radar Network.

The images in positron emission tomography (PET) represent three dimensional dynamic distributions of biologically interesting molecules labelled with positron emitting radionuclides (radiotracers). Spatial localisation of the radio-tracers is achieved by detecting in coincidence two collinear photons which are emitted when the positron annihilates with an ordinary electron. In order to obtain quantitatively accurate images in PET, it is necessary to correct for the effects of photon attenuation within the subject being imaged. These corrections can be obtained using singles-mode photon transmission scanning. Although suitable for small animal PET, these scans are subject to high amounts of contamination from scattered photons. Currently, no accurate correction exists to account for scatter in these data. The primary purpose of this work was to implement and validate an analytical scatter correction for PET transmission scanning. In order to isolate the effects of scatter, we developed a simulation tool which was validated using experimental transmission data. We then presented an analytical scatter correction for singles-mode transmission data in PET. We compared our scatter correction data with the previously validated simulation data for uniform and non-uniform phantoms and for two different transmission source radionuclides. Our scatter calculation correctly predicted the contribution from scattered photons to the simulated data for all phantoms and both transmission sources. We then applied our scatter correction as part of an iterative reconstruction algorithm for simulated and experimental PET transmission data for uniform and non-uniform phantoms. We also tested our reconstruction and scatter correction procedure using transmission data for several animal studies (mice, rats and primates). For all studies considered, we found that the average reconstructed linear attenuation coefficients for water or soft-tissue regions of interest agreed with expected values to within 4%. Using a 2.2 GHz processor, the scatter correction required between 6 to 27 minutes of CPU time (without any code optimisation) depending on the phantom size and source used. This extra calculation time does not seem unreasonable considering that, without scatter corrections, errors in the reconstructed attenuation coefficients were between 18 to 45% depending on the phantom size and transmission source used.

The images in positron emission tomography (PET) represent three dimensional dynamic distributions of biologically interesting molecules labelled with positron emitting radionuclides (radiotracers). Spatial localisation of the radio-tracers is achieved by detecting in coincidence two collinear photons which are emitted when the positron annihilates with an ordinary electron. In order to obtain quantitatively accurate images in PET, it is necessary to correct for the effects of photon attenuation within the subject being imaged. These corrections can be obtained using singles-mode photon transmission scanning. Although suitable for small animal PET, these scans are subject to high amounts of contamination from scattered photons. Currently, no accurate correction exists to account for scatter in these data. The primary purpose of this work was to implement and validate an analytical scatter correction for PET transmission scanning. In order to isolate the effects of scatter, we developed a simulation tool which was validated using experimental transmission data. We then presented an analytical scatter correction for singles-mode transmission data in PET. We compared our scatter correction data with the previously validated simulation data for uniform and non-uniform phantoms and for two different transmission source radionuclides. Our scatter calculation correctly predicted the contribution from scattered photons to the simulated data for all phantoms and both transmission sources. We then applied our scatter correction as part of an iterative reconstruction algorithm for simulated and experimental PET transmission data for uniform and non-uniform phantoms. We also tested our reconstruction and scatter correction procedure using transmission data for several animal studies (mice, rats and primates). For all studies considered, we found that the average reconstructed linear attenuation coefficients for water or soft-tissue regions of interest agreed with expected values to within 4%. Using a 2.2 GHz processor, the scatter correction required between 6 to 27 minutes of CPU time (without any code optimisation) depending on the phantom size and source used. This extra calculation time does not seem unreasonable considering that, without scatter corrections, errors in the reconstructed attenuation coefficients were between 18 to 45% depending on the phantom size and transmission source used.

The images in positron emission tomography (PET) represent three dimensional dynamic distributions of biologically interesting molecules labelled with positron emitting radionuclides (radiotracers). Spatial localisation of the radio-tracers is achieved by detecting in coincidence two collinear photons which are emitted when the positron annihilates with an ordinary electron. In order to obtain quantitatively accurate images in PET, it is necessary to correct for the effects of photon attenuation within the subject being imaged. These corrections can be obtained using singles-mode photon transmission scanning. Although suitable for small animal PET, these scans are subject to high amounts of contamination from scattered photons. Currently, no accurate correction exists to account for scatter in these data. The primary purpose of this work was to implement and validate an analytical scatter correction for PET transmission scanning. In order to isolate the effects of scatter, we developed a simulation tool which was validated using experimental transmission data. We then presented an analytical scatter correction for singles-mode transmission data in PET. We compared our scatter correction data with the previously validated simulation data for uniform and non-uniform phantoms and for two different transmission source radionuclides. Our scatter calculation correctly predicted the contribution from scattered photons to the simulated data for all phantoms and both transmission sources. We then applied our scatter correction as part of an iterative reconstruction algorithm for simulated and experimental PET transmission data for uniform and non-uniform phantoms. We also tested our reconstruction and scatter correction procedure using transmission data for several animal studies (mice, rats and primates). For all studies considered, we found that the average reconstructed linear attenuation coefficients for water or soft-tissue regions of interest agreed with expected values to within 4%. Using a 2.2 GHz processor, the scatter correction required between 6 to 27 minutes of CPU time (without any code optimisation) depending on the phantom size and source used. This extra calculation time does not seem unreasonable considering that, without scatter corrections, errors in the reconstructed attenuation coefficients were between 18 to 45% depending on the phantom size and transmission source used. / Science, Faculty of / Physics and Astronomy, Department of / Graduate

Introduction: Despite the relatively low dose (0.5 mSv – 1 mSv) generated by Attenuation Correction CT (ACCT) in PET examinations, the ALARA principle is still applicable. The currently used ACCT standard protocol at the Karolinska University Hospital in Solna uses 7.6 effective mAs (mAseff) and 120 kVp, but reducing mAseff and/or kVp would decrease patient dose as well as facilitate an increased number of research subjects. A CT reconstruction algorithm called Quantification Achieved Consistently (Q.AC.) (Lonn, 2012) has recently been developed to enable reduced doses from ACCT, while preserving quantitative PET data. The purposes of this study were to investigate possible limitations of the Q.AC. with respect to patient size, and to optimise protocols, aiming at minimising ACCT dose in terms of Volumetric Computer Tomography Dose Index CTDIvol. Methods: Measurements were performed with a GE PET/CT Discovery system, which offers Q.AC. reconstruction. The NEMA NU-2 protocol was followed to quantify PET quality, including evaluations of relative count error in the artificial lung in the phantom centre (lung), hot- and cold-sphere contrast (Q), and background variability (N). Two phantoms were used; the NEMA body phantom (elliptical cross section sized 30 cm laterally and 23 cm anterior-posterior (AP)), here representing paediatric patients and small-sized adults, and the same phantom with an additional (20 cm laterally and 4 cm AP) ellipsoid plastic (PMMA) extension ring, representing mid- and large-sized patients. ACCTs were acquired with 15 mAseff values, range [2.3 - 260], in combination with four kVp values [80, 100, 120, 140] and reconstructed with two algorithms (Q.AC. and a regular soft CT algorithm). Consequently, PET reconstructions were performed based on each mAseff, kVp and CT-reconstruction combination. Results: Quantitatively similar PET results to the standard protocol were achieved with the Q.AC. CT reconstruction algorithm using a CTDIvol = 0.06 mGy (2.3 mAseff and 80 kVp) for the NEMA body phantom, respectively a CTDIvol = 0.20 mGy (2.3 mAseff and 120 kVp) for the phantom with additional extension ring. Conclusions: This study indicates that the Q.AC. CT reconstruction algorithm enables accurate PET results at lower ACCT mAseff and kVp settings than the currently used clinical standard protocol. For paediatric patients and small-sized adults, a reduction of CTDIvol by approximately 90% may be achieved, while for mid- and large-sized patients, the CTDIvol can be reduced by approximately 70% without loss of quantitative PET data.

The goal of this study is the recovery of functions and finite parametric distributions from their spherical means over spheres and designing a general formula or algorithm for the reconstruction of a function f via its spherical mean transform. The theoretical study is and supported with a numerical implementation based on radar data. In this study, we approach the reconstruction problem in two different way. The first one is to show how the reconstruction problem could be converted to a Prony-type system of equations. After solving this Prony-type system of equations, one can extract the parameters that describe the corresponding functions or distributions efficiently. The second way is to solve this problem via a backprojection procedure.

Background: The combination of positron emission tomography (PET) and magnetic resonance imaging (MRI) (PET-MRI) is a unique hybrid imaging modality mainly used in oncology and neurology. The MRI-based attenuation correction (MRAC) is crucial for correct quantification of PET data. A suitable phantom to validate quantitative results in PET-MRI is currently missing. In particular, the correction of attenuation due to bone is usually not verified by commonly available phantoms. The aim of this work was, thus, the development of such a phantom and to explore whether such a phantom might be used to validate MRACs. Method: Various materials were investigated for their attenuation and MR properties. For the substitution of bone, water-saturated gypsum plaster was used. The attenuation of 511 keV annihilation photons was regulated by addition of iodine. Adipose tissue was imitated by silicone and brain tissue by agarose gel, respectively. The practicability with respect to the comparison of MRACs was checked as follows: A small flask inserted into the phantom and a large spherical phantom (serving as a reference with negligible error in MRAC) were filled with the very same activity concentration. The activity concentration was measured and compared using clinical protocols on PET-MRI and different built-in and offline MRACs. The same measurements were carried out using PET-CT for comparison. Results: The phantom imitates the human head in sufficient detail. All tissue types including bone were detected as such so that the phantom-based comparison of the quantification accuracy of PET-MRI was possible. Quantitatively, the activity concentration in the brain, which was determined using different MRACs, showed a deviation of about 5% on average and a maximum deviation of 11% compared to the spherical phantom. For PET-CT, the deviation was 5%. Conclusions: The comparatively small error in quantification indicates that it is possible to construct a brain PET-MRI phantom that leads to MR-based attenuation-corrected images with reasonable accuracy.