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Register a new userA projection-domain low-count quantitative SPECT method for alpha-particle emitting radiopharmaceutical therapy
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Reliable (accurate and precise) quantification of dose requires reliable absolute quantification of regional activity uptake. This is especially challenging for alpha-particle emitting radiopharmaceutical therapies ({alpha}-RPTs) due to the complex emission spectra, the very low number of detected counts, the impact of stray-radiation-related noise at these low counts, and other image-degrading processes such as attenuation, scatter, and collimator-detector response. The conventional reconstruction-based quantification methods are observed to be erroneous for {alpha}-RPT SPECT. To address these challenges, we developed an ultra-low-count quantitative SPECT (ULC-QSPECT) method that incorporates multiple strategies to perform reliable quantification. First, the method directly estimates the regional activity uptake from the projection data, obviating the reconstruction step. This makes the problem more well-posed and avoids reconstruction-related information loss. Next, the method compensates for radioisotope and SPECT physics, including the isotope spectra, scatter, attenuation, and collimator-detector response, using a Monte Carlo-based approach. Further, the method compensates for stray-radiation-related noise that becomes substantial at these low-count levels. The method was validated in the context of three-dimensional SPECT with 223Ra. Validation was performed using both realistic simulation studies, as well as synthetic and anthropomorphic physical-phantom studies. Across all studies, the ULC-QSPECT method yielded reliable estimates of regional uptake and outperformed conventional ordered subset expectation maximization (OSEM)-based reconstruction and geometric transfer matrix (GTM)-based partial-volume compensation methods. Further, the method yielded reliable estimates of mean uptake in lesions with varying intra-lesion heterogeneity in uptake.
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Reliable attenuation and scatter compensation (ASC) is a prerequisite for quantification and beneficial for visual interpretation tasks in SPECT. In this paper, we develop a reconstruction method that uses the entire SPECT emission data, i.e. data in both the photopeak and scatter windows, acquired in list-mode format and including the energy attribute of the detected photon, to perform ASC. We implemented a GPU-based version of this method using an ordered subsets expectation maximization (OSEM) algorithm. The method was objectively evaluated using realistic simulation studies on the task of estimating uptake in the striatal regions of the brain in a 2-D dopamine transporter (DaT)-scan SPECT study. We observed that inclusion of data from the scatter window and using list-mode data yielded improved quantification compared to using data only from the photopeak window or using binned data. These results motivate further development of list-mode-based ASC methods that include scatter-window data for SPECT.
Attenuation compensation (AC) is a pre-requisite for reliable quantification and beneficial for visual interpretation tasks in single-photon emission computed tomography (SPECT). Typical AC methods require the availability of an attenuation map obtained using a transmission scan, such as a CT scan. This has several disadvantages such as increased radiation dose, higher costs, and possible misalignment between SPECT and CT scans. Also, often a CT scan is unavailable. In this context, we and others are showing that scattered photons in SPECT contain information to estimate the attenuation distribution. To exploit this observation, we propose a physics and learning-based method that uses the SPECT emission data in the photopeak and scatter windows to perform transmission-less AC in SPECT. The proposed method uses data acquired in the scatter window to reconstruct an initial estimate of the attenuation map using a physics-based approach. A convolutional neural network is then trained to segment this initial estimate into different regions. Pre-defined attenuation coefficients are assigned to these regions, yielding the reconstructed attenuation map, which is then used to reconstruct the activity map using an ordered subsets expectation maximization-based reconstruction approach. We objectively evaluated the performance of this method using a highly realistic simulation study conducted on the clinically relevant task of detecting perfusion defects in myocardial perfusion SPECT. Our results showed no statistically significant differences between the performance achieved using the proposed method and that with the true attenuation maps. Visually, the images reconstructed using the proposed method looked similar to those with the true attenuation map. Overall, these results provide evidence of the capability of the proposed method to perform transmission-less AC and motivate further evaluation.
The use of engineered nanoscale magnetic materials in healthcare and biomedical technologies is rapidly growing. Two examples which have recently attracted significant attention are magnetic particle imaging (MPI) for biological monitoring, and magnetic field hyperthermia (MFH) for cancer therapy. Here for the first time, the capability of a Lissajous scanning MPI device to act as a standalone platform to support the application of MFH cancer treatment is presented. The platform is shown to offer functionalities for nanoparticle localization, focused hyperthermia therapy application, and non-invasive tissue thermometry in one device. Combined, these capabilities have the potential to significantly enhance the accuracy, effectiveness and safety of MFH therapy. Measurements of nanoparticle hyperthermia during protracted exposure to the MPI scanners 3D imaging field sequence revealed spatially focused heating, with a maximum that is significantly enhanced compared with a simple 1-dimensional sinusoidal excitation. The observed spatial heating behavior is qualitatively described based on a phenomenological model considering torques exerted in the Brownian regime. In-vitro cell studies using a human acute monocytic leukemia cell line (THP-1) demonstrated strong suppression of both structural integrity and metabolic activity within 24 h following a 40 min MFH treatment actuated within the Lissajous MPI scanner. Furthermore, reconstructed MPI images of the nanoparticles distributed among the cells, and the temperature-sensitivity of the MPI imaging signal obtained during treatment are demonstrated. In summary, combined Lissajous MPI and MFH technologies are presented; demonstrating for the first time their potential for cancer treatment with maximum effectiveness, and minimal collateral damage to surrounding tissues.
Monte Carlo simulation is an essential tool in emission tomography that can assist in the design of new medical imaging devices, the optimization of acquisition protocols, and the development or assessment of image reconstruction algorithms and correction techniques. GATE, the Geant4 Application for Tomographic Emission, encapsulates the Geant4 libraries to achieve a modular, versatile, scripted simulation toolkit adapted to the field of nuclear medicine. In particular, GATE allows the description of time-dependent phenomena such as source or detector movement, and source decay kinetics. This feature makes it possible to simulate time curves under realistic acquisition conditions and to test dynamic reconstruction algorithms. A public release of GATE licensed under the GNU Lesser General Public License can be downloaded at the address http://www-lphe.epfl.ch/GATE/.
Depth distributions of positron-emitting nuclei in PMMA phantoms are calculated within a Monte Carlo model for Heavy-Ion Therapy (MCHIT) based on the GEANT4 toolkit (version 8.0). The calculated total production rates of $^{11}$C, $^{10}$C and $^{15}$O nuclei are compared with experimental data and with corresponding results of the FLUKA and POSGEN codes. The distributions of e$^+$ annihilation points are obtained by simulating radioactive decay of unstable nuclei and transporting positrons in surrounding medium. A finite spatial resolution of the Positron Emission Tomography (PET) is taken into account in a simplified way. Depth distributions of $beta^+$-activity as seen by a PET scanner are calculated and compared to available data for PMMA phantoms. The calculated $beta^+$-activity profiles are in good agreement with PET data for proton and $^{12}$C beams at energies suitable for particle therapy. The MCHIT capability to predict the $beta^+$-activity and dose distributions in tissue-like materials of different chemical composition is demonstrated.
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