Master of Science

thesisPositron emission tomography (PET) images can be reconstructed using a wide variety of techniques. Two aspects of image reconstruction are addressed in this thesis: the number of subsets used for the block-iterative ordered-subsets expectation-maximization (OSEM) reconstruction algorithm, and using smaller in-plane pixels. Both of these aspects of PET image reconstruction affect image quality. Although image quality in PET is difficult to quantify, it can be evaluated objectively using task-basked assessments such as lesion detection studies. The objective of this work was to evaluate both the effect of the number of OSEM subsets and pixel size on general oncologic PET lesion detection. Experimental phantom data were taken from the Utah PET Lesion Detection Database Resource, modeling whole-body oncologic 18F-FDG PET imaging of a 92kg patient. The data comprised multiple scans on a Biograph mCT time-of-flight (TOF) scanner, with up to 23 sources modeling lesions (diam. 6-16 mm) distributed throughout the phantom for each scan. Two observer studies were performed as part of this thesis. In the first study, images were reconstructed with maximum-likelihood expectation-maximization (MLEM) and with OSEM using 12 different numbers of subsets (i.e., 2-84 subsets). Localization receiver operating characteristics (LROC) analysis was applied using a mathematical observer. The probability of correct localization (PLOC) and the area under the LROC (ALROC) curve were used as figures-of merit in order to quantify lesion detection performance. The results demonstrated an overall decline in lesion detection performance as the number of subsets increased. This loss of image quality can be controlled using a moderate number of subsets (i.e., 12-14 or fewer). In the second study, images were reconstructed with 2.036 mm and 4.073 mm in-plane pixels. Similar LROC analysis methods were applied to determine lesion detection performance for each pixel size. The results of this study demonstrated that images with ~2 mm pixels provided higher lesion detection performance than those with ~4 mm pixels. The primary drawback of using smaller pixels (i.e. ~2 mm) was a 4-fold increase in reconstruction time and data storage requirements. Overall, this work demonstrated that reconstructing with moderate subsets or with smaller voxel sizes may provide important benefits for general PET cancer imaging

Quantitative Techniques for PET/CT: A Clinical Assessment of the Impact of PSF and TOF

Tomographic reconstruction has been a challenge for many imaging applications, and it is particularly problematic for count-limited modalities such as Positron Emission Tomography (PET). Recent advances in PET, including the incorporation of time-of-flight (TOF) information and modeling the variation of the point response across the imaging field (PSF), have resulted in significant improvements in image quality. While the effects of these techniques have been characterized with simulations and mathematical modeling, there has been relatively little work investigating the potential impact of such methods in the clinical setting. The objective of this work is to quantify these techniques in the context of realistic lesion detection and localization tasks for a medical environment. Mathematical observers are used to first identify optimal reconstruction parameters and then later to evaluate the performance of the reconstructions. The effect on the reconstruction algorithms is then evaluated for various patient sizes and imaging conditions. The findings for the mathematical observers are compared to, and validated by, the performance of three experienced nuclear medicine physicians completing the same task

The future of hybrid imaging—part 2: PET/CT

Since the 1990s, hybrid imaging by means of software and hardware image fusion alike allows the intrinsic combination of functional and anatomical image information. This review summarises the state-of-the-art of dual-modality imaging with a focus on clinical applications. We highlight selected areas for potential improvement of combined imaging technologies and new applications. In the second part, we briefly review the background of dual-modality PET/CT imaging, discuss its main applications and attempt to predict technological and methodological improvements of combined PET/CT imaging. After a decade of clinical evaluation, PET/CT will continue to have a significant impact on patient management, mainly in the area of oncological diseases. By adopting more innovative acquisition schemes and data processing PET/CT will become a fast and dose-efficient imaging method and an integral part of state-of-the-art clinical patient management

Incorporating accurate statistical modeling in PET: reconstruction for whole-body imaging

Tese de doutoramento em Biofísica, apresentada à Universidade de Lisboa através da Faculdade de Ciências, 2007The thesis is devoted to image reconstruction in 3D whole-body PET imaging. OSEM ( Ordered Subsets Expectation maximization ) is a statistical algorithm that assumes Poisson data. However, corrections for physical effects (attenuation, scattered and random coincidences) and detector efficiency remove the Poisson characteristics of these data. The Fourier Rebinning (FORE), that combines 3D imaging with fast 2D reconstructions, requires corrected data. Thus, if it will be used or whenever data are corrected prior to OSEM, the need to restore the Poisson-like characteristics is present. Restoring Poisson-like data, i.e., making the variance equal to the mean, was achieved through the use of weighted OSEM algorithms. One of them is the NECOSEM, relying on the NEC weighting transformation. The distinctive feature of this algorithm is the NEC multiplicative factor, defined as the ratio between the mean and the variance. With real clinical data this is critical, since there is only one value collected for each bin the data value itself. For simulated data, if we keep track of the values for these two statistical moments, the exact values for the NEC weights can be calculated. We have compared the performance of five different weighted algorithms (FORE+AWOSEM, FORE+NECOSEM, ANWOSEM3D, SPOSEM3D and NECOSEM3D) on the basis of tumor detectablity. The comparison was done for simulated and clinical data. In the former case an analytical simulator was used. This is the ideal situation, since all the weighting factors can be exactly determined. For comparing the performance of the algorithms, we used the Non-Prewhitening Matched Filter (NPWMF) numerical observer. With some knowledge obtained from the simulation study we proceeded to the reconstruction of clinical data. In that case, it was necessary to devise a strategy for estimating the NEC weighting factors. The comparison between reconstructed images was done by a physician largely familiar with whole-body PET imaging

ASSESSMENT OF NEW INNOVATIONS IN PET/CT FOR RESPIRATORY MOTION CORRECTION

In oncological imaging, Positron Emission Tomography/Computed Tomography (PET/CT) is a vital tool used for stating and treatment response assessment of patients due to its ability to visualize and accurately quantify the bio-distribution of radiolabeled pharmaceuticals. However, due to the long acquisition times, respiratory motion blur is unavoidable in PET images especially in the lower lung and upper abdomen. This leads to reductions in measured radiotracer concentration and lesion detectability all of which can potentially result in incorrect management of patients. Multiple methods exist to correct for respiratory motion but are rarely used in the routine clinical setting because of: 1) increased image noise due to the rejection of motion blurred data; 2) burdensome workflows which require setup and troubleshooting of external hardware needed to track patient breathing; 3) and ineffective respiratory motion correction due to irregular patient breathing potentially caused by the abrupt bed transitions during step and shoot (SS) whole body PET acquisition. Our goal of this Ph.D. dissertation is to address these three issues by evaluating 1) a precommercial version of a vendor designed elastic motion correction (EMC) algorithm which uses all of the acquired PET data resulting in reduced image noise; 2) a pre-commercial version of a vendor designed data driven gating (DDG) algorithm, which determines the respiratory waveform from the PET data alone, thereby removing the need for and challenges of external hardware; 3) the effect of using continuous bed motion (CBM) as compared to SS as a means to minimize the irregularity of patient breathing. vii The results of these evaluations showed that the EMC algorithm performed similarly to conventional respiratory motion correction techniques with respect to radiotracer quantification, however, due to using all of the acquired PET data, the EMC algorithm showed improved performance resulting in the lowest amount of image noise, improved contrast to noise ratio, and had the highest overall image quality scores as assessed by independent observers. Evaluation of the CBM DDG algorithm showed that in comparison to an external device, the measured respiratory waveforms, radiotracer quantification, and assessment of the presence of respiratory motion blur were similar, demonstrating that the CBM DDG algorithm holds promise as a replacement to external hardware devices currently needed to measure respiratory waveforms and hence could potentially simplify the data acquisition workflow. Finally, we found no statistically significant differences between the CBM and SS PET acquisition modes with respect to the regularity of respiratory waveforms, radiotracer quantification, contrast to noise ratio and perceptions of respiratory motion blur. In conclusion, although no reductions of irregular breathing were found between CBM and SS, improvements in image quality through the use of EMC and reductions of workflow complexity through the use of DDG will hopefully facilitate the routine adoption of respiratory motion correction in PET/CT

Impact of respiratory motion correction and spatial resolution on lesion detection in PET: a simulation study based on real MR dynamic data

The aim of this study is to investigate the impact of respiratory motion correction and spatial resolution on lesion detectability in PET as a function of lesion size and tracer uptake. Real respiratory signals describing different breathing types are combined with a motion model formed from real dynamic MR data to simulate multiple dynamic PET datasets acquired from a continuously moving subject. Lung and liver lesions were simulated with diameters ranging from 6 to 12 mm and lesion to background ratio ranging from 3:1 to 6:1. Projection data for 6 and 3 mm PET scanner resolution were generated using analytic simulations and reconstructed without and with motion correction. Motion correction was achieved using motion compensated image reconstruction. The detectability performance was quantified by a receiver operating characteristic (ROC) analysis obtained using a channelized Hotelling observer and the area under the ROC curve (AUC) was calculated as the figure of merit. The results indicate that respiratory motion limits the detectability of lung and liver lesions, depending on the variation of the breathing cycle length and amplitude. Patients with large quiescent periods had a greater AUC than patients with regular breathing cycles and patients with long-term variability in respiratory cycle or higher motion amplitude. In addition, small (less than 10 mm diameter) or low contrast (3:1) lesions showed the greatest improvement in AUC as a result of applying motion correction. In particular, after applying motion correction the AUC is improved by up to 42% with current PET resolution (i.e. 6 mm) and up to 51% for higher PET resolution (i.e. 3 mm). Finally, the benefit of increasing the scanner resolution is small unless motion correction is applied. This investigation indicates high impact of respiratory motion correction on lesion detectability in PET and highlights the importance of motion correction in order to benefit from the increased resolution of future PET scanners

Development Of A Scintillation Detector And The Influence On Clinical Imaging

The detector is the functional unit within a Positron Emission Tomography (PET) scanner, serving to convert the energy of radiation emitted from a patient into positional information, and as such contributes significantly to the performance of the scanner. While modern whole-body scanners use detectors composed of very many (i.e., 20000-30000) small pixels, typically ~4x4x20mm3 in size, several groups are actively investigating the performance of continuous crystals coupled to position sensitive photodetectors as an alternative detector design with a number of potential advantages, including improved spatial resolution and position sampling. This work in particular focuses on thick (≥14mm) continuous crystals in order to maintain the sensitivity of modern scanners. Excellent spatial resolution in continuous detectors that are thick, however, has proven difficult to achieve using simple positioning algorithms, leading to research in the field to improve performance. This thesis aims to investigate the effect of modifications to the scintillation light spread within the bulk of the scintillator to improve performance, focusing on the use of laser induced optical barriers (LIOBs) etched within thick continuous crystals, and furthermore aims to translate the effect on detector performance to scanner quantitation in patient studies. The conventional continuous detector is first investigated by analyzing the various components of the detector as well as its limitations. It is seen that the performance of the detector is affected by a number of variables that either cannot be improved or may be improved only at the expense of greater complexity or computing time; these include the photodetector, the positioning algorithm, and Compton scatter in the detector. The performance of the detectors, however, is fundamentally determined by the light spread within the detector, and limited by the depth-dependence of the light spread and poor performance in the entrance region, motivating efforts to modify this aspect of the detector. The feasibility and potential of LIOBs to fine-tune this light spread and improve these limitations is then studied using both experiments and simulations. The behavior of the LIOBs in response to optical light is investigated, and the opacity of the etchings is shown to be dependent on the parameters of the etching procedure. Thick crystals were also etched with LIOBs in their entrance region in a grid pattern in order to improve the resolution in the entrance region. Measurements show an overall improvement in spatial resolution: the resolution in the etched region of the crystals is slightly improved (e.g., ~0.8mm for a 25mm thick crystal), though in the unetched region, it is slightly degraded (e.g., ~0.4mm for a 25mm thick crystal). While the depth-dependence of the response of the crystal is decreased, the depth-of-interaction (DOI) performance is degraded as well. Simulation studies informed by these measurements show that the properties of the LIOBs strongly affect the performance of the crystal, and ultimately further illustrate that trade-offs in spatial resolution, position sampling, and DOI resolution are inherent in varying the light spread using LIOBs in this manner; these may be used as a guide for future experiments. System Monte Carlo simulations were used to investigate the added benefit of improved detector spatial resolution and position sampling to the imaging performance of a whole-body scanner. These simulations compared the performance of scanners composed of conventional pixelated detectors to that of scanners using continuous crystals. Results showed that the improved performance (relative to that of 4-mm pixelated detectors) of continuous crystals with a 2-mm resolution, pertinent to both the etched 14mm thick crystal studied as well as potential designs with the etched 25mm thick crystal, increased the mean contrast recovery coefficient (CRC) of images by ~22% for 5.5mm spheres. Last, a set of experiments aimed to test the correspondence between quantification in phantom and patient images using a lesion embedding methodology, so that any improvements determined using phantom studies may be understood clinically. The results show that the average CRC values for lesions embedded in the lung and liver agree well with those for lesions embedded in the phantom for all lesion sizes. In addition, the relative changes in CRC resulting from application of post-filters on the subject and phantom images are consistent within measurement uncertainty. This study shows that the improvements in CRC resulting from improved spatial resolution, measured using phantom studies in the simulations, are representative of improvements in quantitative accuracy in patient studies. While unmodified thick continuous detectors hold promise for both improved image quality and quantitation in whole-body imaging, excellent performance requires intensive hardware and computational solutions. Laser induced optical barriers offer the ability to modify the light spread within the scintillator to improve the intrinsic performance of the detector: while measurements with crystals etched with relatively transmissive etchings show a slight improvement in resolution, simulations show that the LIOBs may be fine-tuned to result in improved performance using relatively simple positioning algorithms. For systems in which DOI information is less important, and transverse resolution and sensitivity are paramount, etching thick detectors with this design, fine-tuned to the particular thickness of the crystal and application, is an interesting alternative to the standard detector design

Optical simulation study for high resolution monolithic detector design for TB-PET

Background The main limitations in positron emission tomography (PET) are the limited sensitivity and relatively poor spatial resolution. The administered radioactive dose and scan time could be reduced by increasing system sensitivity with a total-body (TB) PET design. The second limitation, spatial resolution, mainly originates from the specific design of the detectors that are implemented. In state-of-the-art scanners, the detectors consist of pixelated crystal arrays, where each individual crystal is isolated from its neighbors with reflector material. To obtain higher spatial resolution the crystals can be made narrower which inevitably leads to more inter-crystal scatter and larger dead space between the crystals. A monolithic detector design shows superior characteristics in (i) light collection efficiency (no gaps), (ii) timing, as it significantly reduces the number of reflections and therefore the path length of each scintillation photon and (iii) spatial resolution (including better depth-of-interaction (DOI)). The aim of this work is to develop a precise simulation model based on measured crystal data and use this powerful tool to find the limits in spatial resolution for a monolithic detector for the use in TB-PET. Materials and methods A detector (Fig. 1) based on a monolithic 50x50x16 mm3 lutetium-(yttrium) oxyorthosilicate (L(Y)SO) scintillation crystal coupled to an 8x8 array of 6x6mm2 silicon photomultipliers (SiPMs) is simulated with GATE. A recently implemented reflection model for scintillation light allows simulations based on measured surface data (1). The modeled surfaces include black painted rough finishing on the crystal sides (16x50mm2) and a specular reflector attached to a polished crystal top (50x50mm2). Maximum Likelihood estimation (MLE) is used for positioning the events. Therefore, calibration data is obtained by generating 3.000 photo-electric events at given calibration positions (Fig. 1). Compton scatter is not (yet) included. In a next step, the calibration data is organized in three layers based on the exact depth coordinate in the crystal (i.e. DOI assumed to be known). For evaluating the resolution, the full width at half maximum (FWHM) is estimated at the irradiated positions of Fig. 2 as a mean of all profiles in vertical and horizontal direction. Next, uniformity is evaluated by simulating 200k events from a flood source, placed in the calibrated area. Results For the irradiation pattern in Fig. 2 the resolution in terms of FWHM when applying MLE is: 0.86±0.13mm (Fig. 3a). Nevertheless, there are major artifacts also at non-irradiated positions. By positioning the events based on three DOI-based layers it can be seen that the events closest to the photodetector introduce the largest artifacts (Fig. 3b-d). The FWHM improves for Layer 1 and 2, to 0.69±0.04mm and 0.59±0.02mm, respectively. Layer 3 introduces major artifacts to the flood map, as events are positioned at completely different locations as the initial irradiation. A FWHM estimation is thus not useful. The uniformity (Fig. 4) degrades with proximity to the photodetector. The map in Fig. 4c shows that the positioning accuracy depends not only on DOI but also the position in the plane parallel to the photodetector array. Conclusions A simulation model for a monolithic PET detector with good characteristics for TB-PET systems was developed with GATE. A first estimate of the spatial resolution and uniformity was given, pointing out the importance of depth-dependent effects. Future studies will include several steps towards more realistic simulations e.g. surface measurements of our specific crystals for the optical surface model and inclusion of the Compton effect