Improvements in the registration of multimodal medical imaging : application to intensity inhomogeneity and partial volume corrections

Alignment or registration of medical images has a relevant role on clinical diagnostic and treatment decisions as well as in research settings. With the advent of new technologies for multimodal imaging, robust registration of functional and anatomical information is still a challenge, particular in small-animal imaging given the lesser structural content of certain anatomical parts, such as the brain, than in humans. Besides, patient-dependent and acquisition artefacts affecting the images information content further complicate registration, as is the case of intensity inhomogeneities (IIH) showing in MRI and the partial volume effect (PVE) attached to PET imaging. Reference methods exist for accurate image registration but their performance is severely deteriorated in situations involving little images Overlap. While several approaches to IIH and PVE correction exist these methods still do not guarantee or rely on robust registration. This Thesis focuses on overcoming current limitations af registration to enable novel IIH and PVE correction methods.El registre d'imatges mèdiques té un paper rellevant en les decisions de diagnòstic i tractament clíniques així com en la recerca. Amb el desenvolupament de noves tecnologies d'imatge multimodal, el registre robust d'informació funcional i anatòmica és encara avui un repte, en particular, en imatge de petit animal amb un menor contingut estructural que en humans de certes parts anatòmiques com el cervell. A més, els artefactes induïts pel propi pacient i per la tècnica d'adquisició que afecten el contingut d'informació de les imatges complica encara més el procés de registre. És el cas de les inhomogeneïtats d'intensitat (IIH) que apareixen a les RM i de l'efecte de volum parcial (PVE) característic en PET. Tot i que existeixen mètodes de referència pel registre acurat d'imatges la seva eficàcia es veu greument minvada en casos de poc solapament entre les imatges. De la mateixa manera, també existeixen mètodes per la correcció d'IIH i de PVE però que no garanteixen o que requereixen un registre robust. Aquesta tesi es centra en superar aquestes limitacions sobre el registre per habilitar nous mètodes per la correcció d'IIH i de PVE

Iterative Structural and Functional Synergistic Resolution Recovery (iSFS-RR) Applied to PET-MR Images in Epilepsy

Structural Functional Synergistic Resolution Recovery (SFS-RR) is a technique that uses supplementary structural information from MR or CT to improve the spatial resolution of PET or SPECT images. This wavelet-based method may have a potential impact on the clinical decision-making of brain focal disorders such as refractory epilepsy, since it can produce images with better quantitative accuracy and enhanced detectability. In this work, a method for the iterative application of SFS-RR (iSFS-RR) was firstly developed and optimized in terms of convergence and input voxel size, and the corrected images were used for the diagnosis of 18 patients with refractory epilepsy. To this end, PET/MR images were clinically evaluated through visual inspection, atlas-based asymmetry indices (AIs) and SPM (Statistical Parametric Mapping) analysis, using uncorrected images and images corrected with SFS-RR and iSFS-RR. Our results showed that the sensitivity can be increased from 78% for uncorrected images, to 84% for SFS-RR and 94% for the proposed iSFS-RR. Thus, the proposed methodology has demonstrated the potential to improve the management of refractory epilepsy patients in the clinical routine

Partial volume correction of brain PET studies using iterative deconvolution in combination with HYPR denoising

Background: Accurate quantification of PET studies depends on the spatial resolution of the PET data. The commonly limited PET resolution results in partial volume effects (PVE). Iterative deconvolution methods (IDM) have been proposed as a means to correct for PVE. IDM improves spatial resolution of PET studies without the need for structural information (e.g. MR scans). On the other hand, deconvolution also increases noise, which results in lower signal-to-noise ratios (SNR). The aim of this study was to implement IDM in combination with HighlY constrained back-PRojection (HYPR) denoising to mitigate poor SNR properties of conventional IDM.Methods: An anthropomorphic Hoffman brain phantom was filled with an [F-18]FDG solution of similar to 25 kBq mL(-1) and scanned for 30 min on a Philips Ingenuity TF PET/CT scanner (Philips, Cleveland, USA) using a dynamic brain protocol with various frame durations ranging from 10 to 300 s. Van Cittert IDM was used for PVC of the scans. In addition, HYPR was used to improve SNR of the dynamic PET images, applying it both before and/or after IDM. The Hoffman phantom dataset was used to optimise IDM parameters (number of iterations, type of algorithm, with/without HYPR) and the order of HYPR implementation based on the best average agreement of measured and actual activity concentrations in the regions. Next, dynamic [C-11]flumazenil (five healthy subjects) and [C-11]PIB (four healthy subjects and four patients with Alzheimer's disease) scans were used to assess the impact of IDM with and without HYPR on plasma input-derived distribution volumes (V-T) across various regions of the brain.Results: In the case of [C-11]flumazenil scans, Hypr-IDM-Hypr showed an increase of 5 to 20% in the regional V-T whereas a 0 to 10% increase or decrease was seen in the case of [C-11]PIB depending on the volume of interest or type of subject (healthy or patient). References for these comparisons were the V(T)s from the PVE-uncorrected scans.Conclusions: IDM improved quantitative accuracy of measured activity concentrations. Moreover, the use of IDM in combination with HYPR (Hypr-IDM-Hypr) was able to correct for PVE without increasing noise.</p

Quantification of dopaminergic neurotransmission SPECT studies with 123 l-labelled radioligands

Dopaminergic neurotransmission SPECT studies with 123I-labelled radioligands can help in the diagnosis of neurological and psychiatric disorders such as Parkinson¿s disease and schizophrenia. Nowadays, interpretation of SPECT images is based mainly on visual assessment by experienced observers. However, a quantitative evaluation of the images is recommended in current clinical guidelines. Quantitative information can help diagnose the disease at the early pre-clinical stages, follow its progression and assess the effects of treatment strategies. SPECT images are affected by a number of effects that are inherent in the image formation: attenuation and scattering of photons, system response and partial volume effect. These effects degrade the contrast and resolution of the images and, as a consequence, the real activity distribution of the radiotracer is distorted. Whilst the photon emission of 123I is dominated by a low-energy line of 159 keV, it also emits several high-energy lines. When 123I-labelled radioligands are used, a non-negligible fraction of high-energy photons undergoes backscattering in the detector and the gantry and reaches the detector within the energy window. In this work, a complete methodology for the compensation of all the degrading effects involved in dopaminergic neurotransmission SPECT imaging with 123I is presented. The proposed method uses Monte Carlo simulation to estimate the scattered photons detected in the projections. For this purpose, the SimSET Monte Carlo code was modified so as to adapt it to the more complex simulation of high-energy photons emitted by 123I. Once validated, the modified SimSET code was used to simulate 123I SPECT studies of an anthropomorphic striatal phantom using different imaging systems. The projections obtained showed that scatter is strongly dependent on the imaging system and comprises at least 40% of the detected photons. Applying the new methodology demonstrated that absolute quantification can be achieved when the method includes accurate compensations for all the degrading effects. When the method did not include correction for all degradations, calculated values depended on the imaging system, although a linear relationship was found between calculated and true values. It was also found that partial volume effect and scatter corrections play a major role in the recovery of nominal values. Despite the advantages of absolute quantification, the computational and methodological requirements needed severely limit the possibility of application in clinical routine. Thus, for the time being, absolute quantification is limited to academic studies and research trials. In a clinical context, reliable, simple and rapid methods are needed, thus, semi-quantitative methods are used. Diagnosis also requires the establishment of robust reference values for healthy controls. These values are usually derived from a large data pool obtained in multicentre clinical trials. The comparison between the semi-quantitative values obtained from a patient and the reference is only feasible if the quantitative values have been previously standardised, i.e. they are independent of the gamma camera, acquisition protocol, reconstruction parameters and quantification procedure applied. Thus, standardisation requires that the calculated values are compensated somehow for all the image-degrading phenomena. In this thesis dissertation, a methodology for the standardisation of the quantitative values extracted from dopaminergic neurotransmission SPECT studies with 123I is evaluated using Monte Carlo simulation. This methodology is based on the linear relationship found between calculated and true values for a group of studies corresponding to different subjects with non-negligible anatomical and tracer uptake differences. Reconstruction and quantification methods were found to have a high impact on the linearity of the relationship and on the accuracy of the standardised results

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

Triple modality image reconstruction of PET data using SPECT, PET, CT information increases lesion uptake in images of patients treated with radioembolization with [Formula: see text] micro-spheres.

PURPOSE: Nuclear medicine imaging modalities like computed tomography (CT), single photon emission CT (SPECT) and positron emission tomography (PET) are employed in the field of theranostics to estimate and plan the dose delivered to tumors and the surrounding tissues and to monitor the effect of the therapy. However, therapeutic radionuclides often provide poor images, which translate to inaccurate treatment planning and inadequate monitoring images. Multimodality information can be exploited in the reconstruction to enhance image quality. Triple modality PET/SPECT/CT scanners are particularly useful in this context due to the easier registration process between images. In this study, we propose to include PET, SPECT and CT information in the reconstruction of PET data. The method is applied to Yttrium-90 ([Formula: see text]Y) data. METHODS: Data from a NEMA phantom filled with [Formula: see text]Y were used for validation. PET, SPECT and CT data from 10 patients treated with Selective Internal Radiation Therapy (SIRT) were used. Different combinations of prior images using the Hybrid kernelized expectation maximization were investigated in terms of VOI activity and noise suppression. RESULTS: Our results show that triple modality PET reconstruction provides significantly higher uptake when compared to the method used as standard in the hospital and OSEM. In particular, using CT-guided SPECT images, as guiding information in the PET reconstruction significantly increases uptake quantification on tumoral lesions. CONCLUSION: This work proposes the first triple modality reconstruction method and demonstrates up to 69% lesion uptake increase over standard methods with SIRT [Formula: see text]Y patient data. Promising results are expected for other radionuclide combination used in theranostic applications using PET and SPECT

Development of a simulation platform for the evaluation of PET neuroimaging protocols in epilepsy

Monte Carlo simulation of PET studies is a reference tool for the evaluation and standardization of PET protocols. However, current Monte Carlo software codes require a high degree of knowledge in physics, mathematics and programming languages, in addition to a high cost of time and computational resources. These drawbacks make their use difficult for a large part of the scientific community. In order to overcome these limitations, a free and an efficient web-based platform was designed, implemented and validated for the simulation of realistic brain PET studies, and specifically employed for the generation of a wellvalidated large database of brain FDG-PET studies of patients with refractory epilepsy

Scatter modelling and compensation in emission tomography

In nuclear medicine, clinical assessment and diagnosis are generally based on qualitative assessment of the distribution pattern of radiotracers used. In addition, emission tomography (SPECT and PET) imaging methods offer the possibility of quantitative assessment of tracer concentration in vivo to quantify relevant parameters in clinical and research settings, provided accurate correction for the physical degrading factors (e.g. attenuation, scatter, partial volume effects) hampering their quantitative accuracy are applied. This review addresses the problem of Compton scattering as the dominant photon interaction phenomenon in emission tomography and discusses its impact on both the quality of reconstructed clinical images and the accuracy of quantitative analysis. After a general introduction, there is a section in which scatter modelling in uniform and non-uniform media is described in detail. This is followed by an overview of scatter compensation techniques and evaluation strategies used for the assessment of these correction methods. In the process, emphasis is placed on the clinical impact of image degradation due to Compton scattering. This, in turn, stresses the need for implementation of more accurate algorithms in software supplied by scanner manufacturers, although the choice of a general-purpose algorithm or algorithms may be difficul