Robust Framework for PET Image Reconstruction Incorporating System and Measurement Uncertainties

In Positron Emission Tomography (PET), an optimal estimate of the radioactivity concentration is obtained from the measured emission data under certain criteria. So far, all the well-known statistical reconstruction algorithms require exactly known system probability matrix a priori, and the quality of such system model largely determines the quality of the reconstructed images. In this paper, we propose an algorithm for PET image reconstruction for the real world case where the PET system model is subject to uncertainties. The method counts PET reconstruction as a regularization problem and the image estimation is achieved by means of an uncertainty weighted least squares framework. The performance of our work is evaluated with the Shepp-Logan simulated and real phantom data, which demonstrates significant improvements in image quality over the least squares reconstruction efforts

Evaluation of yttrium-90 positron emission tomography dosimetry

Purpose: Radioembolization is a novel treatment which utilizes the liver\u27s unique dual system blood supply to trap yttrium-90 (90Y) microspheres in microvasculature near liver tumors. Radioembolization dose planning and dosimetry are based on crude, inaccurate assumptions due to the lack of knowledge of patient specific 90Y microsphere distribution. In recent years, the very small 3.1867e-5 internal pair production decay branch of 90Y has been shown to allow for positron emission tomography (PET) imaging following radioembolization. This work explores the accuracy and limitation of 90Y PET imaging due to the extremely low signal to noise (SNR) ratio associated with 90Y and verifies the accuracy of using these PET images for 3-dimensional (3D) dosimetry. ^ Material and Methods: PET acquisitions of a phantom containing 90Y filled cylindrical inserts were acquired to determine quantitative accuracy of the PET images to measure 90Y activity. Numerous reconstruction algorithms were used to determine the optimal protocol to balance image noise and accuracy. A GATE model of the PET scanner was used to evaluate the origin of prompt signal and random noise coincidence counts in these PET acquisitions. PET images were converted to dose maps using standard S-kernel convolution. Polymer gel dosimetry was used to validate the 3D dose map results. Furthermore, PET, with associated CT images, were used as input data into MC simulations to model dose rates surrounding patients for future patient release studies. A Siemens® Biograph 64 TruePoint PET/CT was used for all acquisitions and reconstructions. ^Results: The phantom study determined Siemens® OSEM-PSF algorithm, known as TrueX, with 2 iterations and 14 subsets had the optimal balance of noise and accuracy. Using this reconstruction algorithm, the PET images were found to accurately measure activity and calculated dose within 10% when 90Y concentration was above the minimum detectable concentrations (MDC) of 1 MBq/ml. However, this reconstruction algorithm was shown to have a positive bias in areas where concentration was below the MDC due to truncation of negative sinogram bin values caused by statistical noise in the random correction. Polymer gel dosimetry verified the accuracy of PET dose maps but also identified a limitation in cases of highly gradient distributions due to the PET spatial resolution spreading of measured activity. Additionally, external dose rates were found to be accurately predicted through use of 90Y PET/CT images as inputs into a MC simulation.Conclusion: Research in 90Y PET/CT has quickly been expanding over recent years as a feasible method to provide liver distribution of 90Y following radioembolization. This study demonstrates the accuracy and limitations of the use of these 90Y PET/CT images in patient specific qualitative dosimetry

Reconstrucción on-line con algoritmos Modo Lista para equipos PET de cristal continuo

En la presente memoria se estudia la obtención on-line de imágenes PET en equipos de cristal continuo a partir de algoritmos de reconstrucción Modo Lista. Estos algoritmos presentan una característica fundamental para conseguir el objetivo deseado, a saber, la capacidad de iniciar la reconstrucción una vez que ha sido adquirido el primer evento. Además, como están orientados al cálculo de las probabilidades de emisión ad-hoc, resultan especialmente atractivos para equipos PET de cristal continuo, permitiendo hacer uso de las reducidas dimensiones en el pixelado virtual sobre el detector. Para llevar a cabo el estudio, se realizó inicialmente una adaptación de las normativas NEMA NU 2-2007 y NU 4-2008 para el prototipo PET de cristal continuo dedicado a la exploración de mama, MAMMI (Mammography with molecular imaging). Con los resultados obtenidos se realizó una comparativa con los equipos dedicados a la exploración de este mismo órgano presentes en la literatura. Una vez contrastada su capacidad, se implementó el algoritmo LM-EM para el que se desarrolló un nuevo retroproyector, el método TOR, basado en la identificación de las probabilidades de emisión con las intersecciones volumétricas vóxel-TOR. El algoritmo LM-EM-TOR ha sido evaluado en profundidad midiendo su convergencia y sus parámetros geométricos óptimos en función de estudios de resolución espacial y calidad de imagen (uniformidad y contraste). Gracias al cálculo ad-hoc de las probabilidades de emisión no existen restricciones de almacenamiento, de manera que se pudieron realizar reconstrucciones con pixelados de hasta (0.4 x 0.4) mm2 junto con vóxeles de (0.25 x 0.25 x 0.25) mm3. A fin de realizar una única iteración sobre los datos y conseguir así imágenes on-line se introdujo la reconstrucción por subsets, es decir, el algoritmo LM-OS. Finalmente, se proponen correcciones de atenuación y de coincidencias aleatorias de manera on-line, es decir, se estiman y se aplican dentro del mismo proceso de reconstrucción. Los resultados obtenidos tras este estudio se han aplicado a 25 pacientes, demostrándose de manera práctica la capacidad de generación de imágenes on-line sin comprometer la calidad final de éstas. Adquisiciones típicas en pacientes de aproximadamente 1200 segundos de duración han sido reconstruidas entre 17 y 45 segundos.This thesis proposes on-line image reconstruction for continuous crystals PET systems by means of List Mode algorithms. These algorithms have a key feature to achieve our goal, namely they can start the reconstruction process as soon as the first event has been acquired. Also, they are especially attractive to continuous crystal PET systems, since they are oriented to calculate ad-hoc the emission probabilities, allowing the use of the reduced dimensions in the virtual pixelization process. To carry out the required tasks, we have adapted initially the NEMA Standards Publications NU 2-2007 and NU 4-2008 for their application to the MAMMI (Mammography with molecular imaguing) prototype, a continuous crystal PET system dedicated to breast exploration. The results obtained have been compared with those of other dedicated breast PET scanners found in the literature. Once its capacity has been proven, the LM-EM algorithm with a new backproyector, TOR method, has been implemented. This method proposes the emission probability identification with the volumetric intersections voxel-TOR. The LM-EM-TOR algorithm has been evaluated in depth by measuring the convergence and optimal geometric parameters based on spatial resolution and image quality (uniformity and contrast) studies. Thanks to the ad-hoc calculation of emission probabilities no storage restrictions arise, and therefore we perform reconstructions with pixelizations of up to (0.4 x 0.4) mm2 together with voxels of (0.25 x 0.25 x 0.25) mm3. In order to perform a single iteration over the data to obtain on-line images, we have introduced temporal subsets in the reconstruction process, i.e. , the LM-OS algorithm. Finally, we propose on-line attenuation and random coincidence corrections, meaning that these corrections are estimated and applied within the reconstruction process. The results obtained from these studies have been applied to 25 patients showing in a practical manner the capacity of generating on-line images without compromising their final quality. Typical data acquisitions in patients of about 1200 seconds duration have been reconstructed in 17 to 45 seconds