Simulación de rango del positrón y emisiones gamma adicionales en PET

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Físicas, Departamento de Física Atómica, Molecular y Nuclear, leída el 03-04-2014Depto. de Estructura de la Materia, Física Térmica y ElectrónicaFac. de Ciencias FísicasTRUEunpu

The Importance of Dosimetry and Radiobiology in Nuclear Medicine : Quantitative methods and modelling

Nuclear medicine uses radioactive pharmaceuticals for diagnostic or therapeutic purposes. The ionizing radiation emitted from the radiopharmaceutical is partially absorbed within the patient's body and internal dosimetry is the method to estimate the absorbed dose to a tumour or risk organ. This is of special importance in radiopharmaceutical therapy (RPT), where particle-emitting radionuclides are utilized for their therapeutic effect. A better understanding of where and to what extent the radiation energy is deposited, i.e. dosimetry, in combination with a better understanding of the irradiation-induced biological processes in tissues and tumours, i.e., radiobiology, is the foundation to establish an absorbed dose-effect relationship. This thesis comprises quantitative methods and modelling within dosimetry and radiobiology, with a special focus on quantitative methods for activity concentration, absorbed dose calculation and quantification of biological effects after nuclear medicine exposures. Nonuniformity of activity distribution and the biological effect of internal irradiation is considered in Paper I and Paper II. When a radiopharmaceutical primarily localizes within specific tissue substructures of an organ, the average absorbed dose to the whole organ may become insufficient for dosimetric analysis. Hence, the nonuniformities of the distribution of activity need to be considered and absorbed dose calculations to part of an organ, cellular, or a sub-cellular structure may be a better predictor of the therapy outcome or normal tissue toxicity. In Paper I, a small-scale anatomical dosimetry model of the liver tissue structure addressed the issue of activity nonuniformity. Monte Carlo simulations were performed to simulate the particle transport from various substructure sources within the organ model for some clinically available radionuclides. The model enabled comparison between the average absorbed dose to the entire organ and the local absorbed dose close to the source region, which for particle emitting radionuclides differed significantly. To address the resulting biological effect after internal irradiation, an ex vivo method using the γH2AX surrogate marker to visualize and quantify DNA double-strand breaks in in vivo-irradiated tissues was developed. The method was demonstrated to be useful for γH2AX-foci quantification in both the fast proliferating, radiosensitive testis tissue and the slow proliferating and more radioresistant liver tissue. Image-based activity quantification and absorbed dose estimation are considered in Paper III and Paper IV, using somatostatin receptor targeting agents for both diagnostic and therapeutic applications for neuroendocrine tumours. In Paper III, the quantitative accuracy of pre-therapeutic 111In-Octreoscan® SPECT/CT and [68Ga]Ga-DOTA-TATE PET/CT images was investigated due to the change in clinical method to use PET- instead of SPECT-imaging. Further, the quantitative relationship between the theragnostic pair of DOTA-TATE was investigated in Paper IV. The relationship between activity uptakes observed at [68Ga]Ga-DOTA-TATE PET imaging and absorbed doses at subsequent [177Lu]Lu-DOTA-TATE therapy was studied. The study demonstrated that on a group level, a higher tumour uptake measured from pretherapeutic PET images is associated with higher absorbed doses in subsequent therapy with [177Lu]Lu-DOTA-TATE. However, on the individual level, there are limitations of using the 68Ga PET as a predictor for therapy absorbed dose

4-D Tomographic Inference: Application to SPECT and MR-driven PET

Emission tomographic imaging is framed in the Bayesian and information theoretic framework. The first part of the thesis is inspired by the new possibilities offered by PET-MR systems, formulating models and algorithms for 4-D tomography and for the integration of information from multiple imaging modalities. The second part of the thesis extends the models described in the first part, focusing on the imaging hardware. Three key aspects for the design of new imaging systems are investigated: criteria and efficient algorithms for the optimisation and real-time adaptation of the parameters of the imaging hardware; learning the characteristics of the imaging hardware; exploiting the rich information provided by depthof- interaction (DOI) and energy resolving devices. The document concludes with the description of the NiftyRec software toolkit, developed to enable 4-D multi-modal tomographic inference

Improving Quantification in Lung PET/CT for the Evaluation of Disease Progression and Treatment Effectiveness

Positron Emission Tomography (PET) allows imaging of functional processes in vivo by measuring the distribution of an administered radiotracer. Whilst one of its main uses is directed towards lung cancer, there is an increased interest in diffuse lung diseases, for which the incidences rise every year, mainly due to environmental reasons and population ageing. However, PET acquisitions in the lung are particularly challenging due to several effects, including the inevitable cardiac and respiratory motion and the loss of spatial resolution due to low density, causing increased positron range. This thesis will focus on Idiopathic Pulmonary Fibrosis (IPF), a disease whose aetiology is poorly understood while patient survival is limited to a few years only. Contrary to lung tumours, this diffuse lung disease modifies the lung architecture more globally. The changes result in small structures with varying densities. Previous work has developed data analysis techniques addressing some of the challenges of imaging patients with IPF. However, robust reconstruction techniques are still necessary to obtain quantitative measures for such data, where it should be beneficial to exploit recent advances in PET scanner hardware such as Time of Flight (TOF) and respiratory motion monitoring. Firstly, positron range in the lung will be discussed, evaluating its effect in density-varying media, such as fibrotic lung. Secondly, the general effect of using incorrect attenuation data in lung PET reconstructions will be assessed. The study will compare TOF and non-TOF reconstructions and quantify the local and global artefacts created by data inconsistencies and respiratory motion. Then, motion compensation will be addressed by proposing a method which takes into account the changes of density and activity in the lungs during the respiration, via the estimation of the volume changes using the deformation fields. The method is evaluated on late time frame PET acquisitions using ¹⁸F-FDG where the radiotracer distribution has stabilised. It is then used as the basis for a method for motion compensation of the early time frames (starting with the administration of the radiotracer), leading to a technique that could be used for motion compensation of kinetic measures. Preliminary results are provided for kinetic parameters extracted from short dynamic data using ¹⁸F-FDG

An investigation into the limitations of myocardial perfusion imaging

Myocardial Perfusion Imaging (MPI) plays a very important role in the management of patients with suspected Coronary Artery Disease and its use has grown despite the shortcomings of the technique. Significant progress has been made in identifying the causes of these shortcomings and many solutions been suggested in the literature but the clinical sensitivity and specificity of the technique is still well below optimum. Monte Carlo Simulation is a very useful tool in identifying and guiding the understanding of the existing problems in MPI and this present study utilised this method to establish the basis of the simulations to be used and the way to analyse the results so that many of the causes of the attenuation defects, when using MPI, could be identified. This was achieved by investigating the effect that the different anatomical parts of the thorax have on the attenuation defects caused. A further aspect investigated was the impact that self-absorption in the heart has on these defects. The variability of these defects were further investigated by altering the position and orientation of the heart itself within the thorax and determining the effect it has on the attenuation defects caused. Results indicate that the attenuation caused is a very complicated process, that the self-absorption of the heart plays an extremely important role and the impact of the different positions and orientation of the heart inside the thorax are also significant. The distortion caused on the images by these factors was demonstrated by the intensity losses in the basal part and an over-estimation in the apical parts, which were clearly observable on the final clinical images, with the potential to affect clinical interpretation. Attenuation correction procedures using transmission sources, have been available for some time, but have not been adopted widely, amidst concern that they introduce additional artefacts. This study determined the effectiveness of these methods by establishing the level of correction obtained and whether additional artefacts were introduced. This included the effectiveness of the compensation achieved with the use of the latest commercially available comprehensive correction techniques. The technique investigated was “Flash3D" from Siemens providing transmission based attenuation correction, depth-dependent resolution recovery and scatter correction. The comparison between the defects and intensity losses predicted by the Monte Carlo Simulations and the corrections provided by this commercial correction technique revealed that solution is compensating almost entirely for these problems and therefore do provide substantial progress in overcoming the limitations of MPI. As a result of the improvements gained from applying these commercially available techniques and the accuracy established in this study for the mentioned technique it is strongly recommended that these new techniques be embraced by the wider Nuclear Medicine community so that the limitations in MPI can be reduced in clinical environment. Non-withstanding the above gains made there remains room for improvement by overcoming the of use transmission attenuation correction techniques by replacing them with emission based techniques. In this study two new related emission based attenuation correction techniques have been suggested and investigated and provide a promising prospect of overcoming these limitations

Investigation of accuracy in quantitation of 18F-FDG concentration of PET/CT

The PET/CT scanner has been recognized as a powerful diagnostic imaging modality in oncology and radiation treatment planning. Traditionally, PET has been used for quantitative analysis, and diagnostic interpretations of PET images greatly relied on a nuclear medicine physician’s experience and knowledge. The PET data set represents a positron emitter’s activity concentration as a gray scale in each pixel. The assurance of the quantitative accuracy of the PET data is critical for diagnosis and staging of disease and evaluation of treatment. The standard uptake value (SUV) is a widely employed parameter in clinical settings to distinguish malignant lesions from others. SUV is a rough normalization of radioactive tracer uptake where normal tissue uptake is unity. The PET scanner is a sensitive diagnostic method to detect small lesions such as lymph node metastasis less than 1 cm in diameter, whereas the CT scanner may be limited in detecting these lesions. The accuracy of quantitation of small lesions is critical for predicting prognosis or planning a treatment of the patient. PET/CT uses attenuation correction factors obtained from CT scanner data sets. Non-biological materials such as metals and contrast agents are recognized as a factor that leads to a wrong scaling factor in the PET image. We challenge the accuracy of the quantitative method that physicians routinely use as a parameter to distinguish malignant lesions from others under clinical settings in commercially available CT/PET scanners. First, we verified if we could recover constant activity concentration throughout the field of view for small identical activity concentration sources. Second, we tested how much the CT-based attenuation correction factor could be influenced by contrast agents. Third, we tested how much error in quantitation could be introduced by object size. Our data suggest that the routine normalization process of the PET scanner does not guarantee an accurate quantitation of discrete uniform activity sources in the PET/CT scanner. Also, activity concentrations greatly rely on an object’s dimensions and object size. A recovery correction factor is necessary on these quantitative data for oncological evaluation to assure accurate interpretation of the activity concentration. Development of parameters for quantitation other than SUV may overcome SUV’s inherent limitations reflecting patient-specific physiology and the imaging characteristics of individual scanners

Investigation and Correction for the Partial Volume Spill in Effects in Positron Emission Tomography

Positron emission tomography (PET) imaging has a wide applicability in oncology, cardiology and neurology. However, a major drawback when imaging very active regions such as the bladder and the bone is the spill in effect, leading to inaccurate quantification and obscured visualisation of nearby lesions. Therefore, this thesis aims at investigating and correcting for the spill in effect from high activity regions to the surroundings, as a function of activity in the hot region, lesion size and location, system resolution as well as application of post-filtering, using the background correction technique. This thesis involved analytical simulations for the digital XCAT2 phantom, and validation acquiring data from NEMA phantoms and patient datasets with the GE Signa PET/MR and Siemens Biograph mMR/mCT scanners. Reconstructions were done using the ordered subset expectation maximisation (OSEM) algorithm. Dedicated point spread function (OSEM+PSF) and the background correction (OSEM+PSF+BC) were incorporated into the reconstruction for spill in correction. For region of interest (ROI) analysis, a semi-automated ellipsoidal ROIs were drawn on the exact location of the lesions, and these were used to extract the standardized uptake value (SUV). The bias, recovery coefficient (RC), coefficient of variation (CoV) and contrast-to-noise ratio (CNR) were computed from the SUVs, and these were used as figures of merit to compare the performances of all the reconstruction algorithms. The thesis revealed that: (i) lesions within 15-20 mm from the hot region are predominantly affected by the spill in effect, leading to an increased bias and impaired lesion visualisation within the region; (ii) the spill in effect is further influenced by the ROI selection, increasing activity in the hot region, reduced resolution and application of post-filter; (iii) the spill in effect is more evident for the SUVmax than the SUVmean; (iv) for proximal lesions (within 2 voxels around the hot region), PSF has no major improvement over OSEM because of the spill in effect, coupled with the Gibbs effect; (v) with OSEM+PSF+BC, the spill in contribution from the hot region was removed in all cases (irrespective of ROI-selection, proximity of lesion to hot source, or application of post-filter), thereby facilitating stability in quantification and enhancing the contrast in lesions with low uptake. This thesis therefore concludes that the BC technique is effective in correcting for the spill in effect from hot regions to surrounding regions of interest. It is also robust to ROI-induced errors and post-filtering

Algorithmic Analysis Techniques for Molecular Imaging

This study addresses image processing techniques for two medical imaging modalities: Positron Emission Tomography (PET) and Magnetic Resonance Imaging (MRI), which can be used in studies of human body functions and anatomy in a non-invasive manner. In PET, the so-called Partial Volume Effect (PVE) is caused by low spatial resolution of the modality. The efficiency of a set of PVE-correction methods is evaluated in the present study. These methods use information about tissue borders which have been acquired with the MRI technique. As another technique, a novel method is proposed for MRI brain image segmen- tation. A standard way of brain MRI is to use spatial prior information in image segmentation. While this works for adults and healthy neonates, the large variations in premature infants preclude its direct application. The proposed technique can be applied to both healthy and non-healthy premature infant brain MR images. Diffusion Weighted Imaging (DWI) is a MRI-based technique that can be used to create images for measuring physiological properties of cells on the structural level. We optimise the scanning parameters of DWI so that the required acquisition time can be reduced while still maintaining good image quality. In the present work, PVE correction methods, and physiological DWI models are evaluated in terms of repeatabilityof the results. This gives in- formation on the reliability of the measures given by the methods. The evaluations are done using physical phantom objects, correlation measure- ments against expert segmentations, computer simulations with realistic noise modelling, and with repeated measurements conducted on real pa- tients. In PET, the applicability and selection of a suitable partial volume correction method was found to depend on the target application. For MRI, the data-driven segmentation offers an alternative when using spatial prior is not feasible. For DWI, the distribution of b-values turns out to be a central factor affecting the time-quality ratio of the DWI acquisition. An optimal b-value distribution was determined. This helps to shorten the imaging time without hampering the diagnostic accuracy.Siirretty Doriast

Advanced perfusion quantification methods for dynamic PET and MRI data modelling

The functionality of tissues is guaranteed by the capillaries, which supply the microvascular network providing a considerable surface area for exchanges between blood and tissues. Microcirculation is affected by any pathological condition and any change in the blood supply can be used as a biomarker for the diagnosis of lesions and the optimization of the treatment. Nowadays, a number of techniques for the study of perfusion in vivo and in vitro are available. Among the several imaging modalities developed for the study of microcirculation, the analysis of the tissue kinetics of intravenously injected contrast agents or tracers is the most widely used technique. Tissue kinetics can be studied using different modalities: the positive enhancement of the signal in the computed tomography and in the ultrasound dynamic contrast enhancement imaging; T1-weighted MRI or the negative enhancement of T2* weighted MRI signal for the dynamic susceptibility contrast imaging or, finally, the uptake of radiolabelled tracers in dynamic PET imaging. Here we will focus on the perfusion quantification of dynamic PET and MRI data. The kinetics of the contrast agent (or the tracer) can be analysed visually, to define qualitative criteria but, traditionally, quantitative physiological parameters are extracted with the implementation of mathematical models. Serial measurements of the concentration of the tracer (or of the contrast agent) in the tissue of interest, together with the knowledge of an arterial input function, are necessary for the calculation of blood flow or perfusion rates from the wash-in and/or wash-out kinetic rate constants. The results depend on the acquisition conditions (type of imaging device, imaging mode, frequency and total duration of the acquisition), the type of contrast agent or tracer used, the data pre-processing (motion correction, attenuation correction, correction of the signal into concentration) and the data analysis method. As for the MRI, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a non-invasive imaging technique that can be used to measure properties of tissue microvasculature. It is sensitive to differences in blood volume and vascular permeability that can be associated with tumour angiogenesis. DCE-MRI has been investigated for a range of clinical oncologic applications (breast, prostate, cervix, liver, lung, and rectum) including cancer detection, diagnosis, staging, and assessment of treatment response. Tumour microvascular measurements by DCE-MRI have been found to correlate with prognostic factors (such as tumour grade, microvessel density, and vascular endothelial growth factor expression) and with recurrence and survival outcomes. Furthermore, DCE-MRI changes measured during treatment have been shown to correlate with outcome, suggesting a role as a predictive marker. The accuracy of DCE-MRI relies on the ability to model the pharmacokinetics of an injected contrast agent using the signal intensity changes on sequential magnetic resonance images. DCE-MRI data are usually quantified with the application of the pharmacokinetic two-compartment Tofts model (also known as the standard model), which represents the system with the plasma and tissue (extravascular extracellular space) compartments and with the contrast reagent exchange rates between them. This model assumes a negligible contribution from the vascular space and considers the system in, what-is-known as, the fast exchange limit, assuming infinitely fast transcytolemmal water exchange kinetics. In general, the number, as well as any assumption about the compartments, depends on the properties of the contrast agent used (mainly gadolinium) together with the tissue physiology or pathology studied. For this reason, the choice of the model is crucial in the analysis of DCE-MRI data. The value of PET in clinical oncology has been demonstrated with studies in a variety of cancers including colorectal carcinomas, lung tumours, head and neck tumours, primary and metastatic brain tumours, breast carcinoma, lymphoma, melanoma, bone cancers, and other soft-tissue cancers. PET studies of tumours can be performed for several reasons including the quantification of tumour perfusion, the evaluation of tumour metabolism, the tracing of radiolabelled cytostatic agents. In particular, the kinetic analysis of PET imaging has showed, in the past few years, an increasing value in tumour diagnosis, as well as in tumour therapy, through providing additional indicative parameters. Many authors have showed the benefit of kinetic analysis of anticancer drugs after labelling with radionuclide in measuring the specific therapeutic effect bringing to light the feasibility of applying the kinetic analysis to the dynamic acquisition. Quantification methods can involve visual analysis together with compartmental modelling and can be applied to a wide range of different tracers. The increased glycolysis in the most malignancies makes 18F-FDG-PET the most common diagnostic method used in tumour imaging. But, PET metabolic alteration in the target tissue can depend by many other factors. For example, most types of cancer are characterized by increased choline transport and by the overexpression of choline kinase in highly proliferating cells in response to enhanced demand of phosphatidylcholine (prostate, breast, lung, ovarian and colon cancers). This effect can be diagnosed with choline-based tracers as the 18Ffluoromethylcholine (18F-FCH), or the even more stable 18F-D4-Choline. Cellular proliferation is also imaged with 18F-fluorothymidine (FLT), which is trapped within the cytosol after being mono phosphorylated by thymidine kinase-1 (TK1), a principal enzyme in the salvage pathway of DNA synthesis. 18F-FLT has been found to be useful for noninvasive assessment of the proliferation rate of several types of cancer and showed high reproducibility and accuracy in breast and lung cancer tumours. The aim of this thesis is the perfusion quantification of dynamic PET and MRI data of patients with lung, brain, liver, prostate and breast lesions with the application of advanced models. This study covers a wide range of imaging methods and applications, presenting a novel combination of MRI-based perfusion measures with PET kinetic modelling parameters in oncology. It assesses the applicability and stability of perfusion quantification methods, which are not currently used in the routine clinical practice. The main achievements of this work include: 1) the assessment of the stability of perfusion quantification of D4-Choline and 18F-FLT dynamic PET data in lung and liver lesions, respectively (first applications in the literature); 2) the development of a model selection in the analysis of DCE-MRI data of primary brain tumours (first application of the extended shutter speed model); 3) the multiparametric analysis of PET and MRI derived perfusion measurements of primary brain tumour and breast cancer together with the integration of immuohistochemical markers in the prediction of breast cancer subtype (analysis of data acquired on the hybrid PET/MRI scanner). The thesis is structured as follows: - Chapter 1 is an introductive chapter on cancer biology. Basic concepts, including the causes of cancer, cancer hallmarks, available cancer treatments, are described in this first chapter. Furthermore, there are basic concepts of brain, breast, prostate and lung cancers (which are the lesions that have been analysed in this work). - Chapter 2 is about Positron Emission Tomography. After a brief introduction on the basics of PET imaging, together with data acquisition and reconstruction methods, the chapter focuses on PET in the clinical settings. In particular, it shows the quantification techniques of static and dynamic PET data and my results of the application of graphical methods, spectral analysis and compartmental models on dynamic 18F-FDG, 18F-FLT and 18F-D4- Choline PET data of patients with breast, lung cancer and hepatocellular carcinoma. - Chapter 3 is about Magnetic Resonance Imaging. After a brief introduction on the basics of MRI, the chapter focuses on the quantification of perfusion weighted MRI data. In particular, it shows the pharmacokinetic models for the quantification of dynamic contrast enhanced MRI data and my results of the application of the Tofts, the extended Tofts, the shutter speed and the extended shutter speed models on a dataset of patients with brain glioma. - Chapter 4 introduces the multiparametric imaging techniques, in particular the combined PET/CT and the hybrid PET/MRI systems. The last part of the chapter shows the applications of perfusion quantification techniques on a multiparametric study of breast tumour patients, who simultaneously underwent DCE-MRI and 18F-FDG PET on a hybrid PET/MRI scanner. Then the results of a predictive study on the same dataset of breast tumour patients integrated with immunohistochemical markers. Furthermore, the results of a multiparametric study on DCE-MRI and 18F-FCM brain data acquired both on a PET/CT scanner and on an MR scanner, separately. Finally, it will show the application of kinetic analysis in a radiomic study of patients with prostate cancer