Development of multispectral scatter correction techniques for high resolution positron emission tomography

En tomographie d'émission par positrons (TEP), les images de très haute résolution spatiale acquises à l'aide d'une caméra basée sur de petits détecteurs discrets sont obtenues au prix d'une faible sensibilité et d'une fraction élevée d'événements diffusés dans les détecteurs. Il est proposé que ces limitations peuvent être surmontées à l'aide de l'acquisition multispectrale des événements où l'énergie des photons est enregistrée de concert avec leurs coordonnées spatiales. Cette étude porte donc sur l'établissement des outils nécessaires à l'exploitation de cette information et sur l'exploration de différentes méthodes de traitement des données multispectrales pour la TEP à haute résolution. Un modèle de dégradation spectrale des photons est proposé pour fournir un support théorique applicable aux méthodes de correction du diffusé basées sur l'énergie. Ce modèle analytique fourni une description physique complète de la propagation de photon et des processus de la détection tant dans le domaine spatial que spectral Il permet aussi de faire le lien entre certaines approches heuristiques de correction du diffusé et les hypothèses physiques sous-jacentes. En particulier, il est démontré que les méthodes de correction du diffusé à double fenêtre d'énergie et à fenêtres multiples sont toutes deux affligées de limites inhérentes qui expliquent probablement leur succès mitigé. L'acquisition multispectrale offre la possibilité de développer des méthodes de correction du diffusé dépendante de l'énergie. Deux approches ont été évaluées pour solutionner ce problème. Dans la première, un lissage spectral des données est utilisé en combinaison avec l'équilibrage multispectral de l'efficacité des détecteurs, dans une séquence de prétraitement optimale, de façon à permettre une véritable analyse dépendante de l'énergie, fenêtre par fenêtre, des données multispectrale. Dans la seconde approche, un traitement global de l'ensemble multispectral est effectué a l'aide de l'analyse des composantes principales pour à la fois réduire la variance et la dimensionalité des données. Les deux approches fournissent un ensemble de donnés adéquates pour Je traitement ultérieur du rayonnement diffusé.Abstract: PET images acquired with a high resolution scanner based on arrays of small discrete detectors are obtained at the cost of low sensitivity and increased detector scatter. It has been postulated that these limitations can be overcome by using multispectral acquisition whereby the energy information is registered together with the spatial coordinates of detected events. This work is an investigation of multispectral data processing methods for high resolution PET. A photon spectral degradation model is proposed to provide theoretical support for energy-based scatter correction methods. This analytical model supplies a complete physical description of the photon propagation and detection processes in both the spatial and spectral domain. It also helps to bridge the gap between a number of heuristic scatter correction approaches and the underlying physical assumptions. In particular, it is shown that such methods as the dual energy window and multispectral frame-by-frame scatter correction techniques have intrinsic deficiencies which may be responsible for their limited success. The potential of multispectral acquisition for developing energy-dependent scatter correction methods is severely impeded by stochastic fluctuations. Two approaches were investigated to overcome this drawback. In the first one, spectral smoothing is attempted in combination with multispectral normalization of detector efficiency and optimal data pre-processing sequence in order to allow truly energy-dependent data processing on a frame-by-frame basis. In the second approach, a global analysis of the multispectral data set is performed by the principal component analysis for reducing both the variance and dimensionality of the multispectral data. Both approaches provide improved data for further processing. The multispectral frame-by-frame convolution scatter correction protocol is shown to yield inferior performance to that of the convolution scatter correction in one broad window. It is concluded that the approximations made in each energy frame to implement the frame-by-frame approach accumulates errors in the final result. Consequently, the spectral smoothing technique and the implementation of the degradation model in the multiple window approach will have to be revisited to overcome this deficiency. A data processing protocol which combines the use of both spatial and spectral information into one scatter correction method is proposed to exploit multispectral data optimally. The method consists of two consecutive steps: first, optimal noise and data dimensionality reduction, as well as partial suppression of scatter, is achieved by performing the global analysis of the multispectral data set; second, a spatial scatter correction technique, the object scatter subtraction and detector scatter restoration algorithm in this study, is used to correct for the residual scatter contribution in the output of the first step. The relevance of such a correction scheme for multispectral data is demonstrated by its superior performance as compared to conventional spatial scatter correction methods. This global scatter correction approach is promising to fulfill the need for high resolution, high sensitivity and quantitative nuclear medicine imaging. All the techniques developed in this work are readily applicable to multiple energy window acquisition in scintigraphic or SPECT imaging

Multispectral imaging for preclinical assessment of rheumatoid arthritis models

Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune condition affecting multiple body systems. Murine models of RA are vital in progressing understanding of the disease. The severity of arthritis symptoms is currently assessed in vivo by observations and subjective scoring which are time-consuming and prone to bias and inaccuracy. The main aim of this thesis is to determine whether multispectral imaging of murine arthritis models has the potential to assess the severity of arthritis symptoms in vivo in an objective manner. Given that pathology can influence the optical properties of a tissue, changes may be detectable in the spectral response. Monte Carlo modelling of reflectance and transmittance for varying levels of blood volume fraction, blood oxygen saturation, and water percentage in the mouse paw tissue demonstrated spectral changes consistent with the reported/published physiological markers of arthritis. Subsequent reflectance and transmittance in vivo spectroscopy of the hind paw successfully detected significant spectral differences between normal and arthritic mice. Using a novel non-contact imaging system, multispectral reflectance and transmittance images were simultaneously collected, enabling investigation of arthritis symptoms at different anatomical paw locations. In a blind experiment, Principal Component (PC) analysis of four regions of the paw was successful in identifying all 6 arthritic mice in a total sample of 10. The first PC scores for the TNF dARE arthritis model were found to correlate significantly with bone erosion ratio results from microCT, histology scoring, and the manual scoring method. In a longitudinal study at 5, 7 and 9 weeks the PC scores identified changes in spectral responses at an early stage in arthritis development for the TNF dARE model, before clinical signs were manifest. Comparison of the multispectral image data with the Monte Carlo simulations suggest that in this study decreased oxygen saturation is likely to be the most significant factor differentiating arthritic mice from their normal littermates. The results of the experiments are indicative that multispectral imaging performs well as an assessor of arthritis for RA models and may outperform existing techniques. This has implications for better assessment of preclinical arthritis and hence for better experimental outcomes and improvement of animal welfare

Improvements in the robustness and accuracy of bioluminescence tomographic reconstructions of distributed sources within small animals

High quality three-dimensional bioluminescence tomographic (BLT) images, if available, would constitute a major advance and provide much more useful information than the two-dimensional bioluminescence images that are frequently used today. To-date, high quality BLT images have not been available, largely because of the poor quality of the data being input into the reconstruction process. Many significant confounds are not routinely corrected for and the noise in this data is unnecessarily large and poorly distributed. Moreover, many of the design choices affecting image quality are not well considered, including choices regarding the number and type of filters used when making multispectral measurements and choices regarding the frequency and uniformity of the sampling of both the range and domain of the BLT inverse problem. Finally, progress in BLT image quality is difficult to gauge owing to a lack of realistic gold-standard references that engage the full complexity and uncertainty within a small animal BLT imaging experiment. Within this dissertation, I address all of these issues. I develop a Cerenkov-based gold-standard wherein a Positron Emission Tomography (PET) image can be used to gauge improvements in the accuracy of BLT reconstruction algorithms. In the process of creating this reference, I discover and describe corrections for several confounds that if left uncorrected would introduce artifacts into the BLT images. This includes corrections for the angle of the animal’s skin surface relative to the camera, for the height of each point on the skin surface relative to the focal plane, and for the variation in bioluminescence intensity as a function of luciferin concentration over time. Once applied, I go on to derive equations and algorithms that when employed are able to minimize the noise in the final images under the constraints of a multispectral BLT data acquisition. These equations and algorithms allow for an optimal choice of filters to be made and for the acquisition time to be optimally distributed among those filtered measurements. These optimizations make use of Barrett’s and Moore-Penrose pseudoinverse matrices which also come into play in a paradigm I describe that can be used to guide choices regarding sampling of the domain and range

(An overview of) Synergistic reconstruction for multimodality/multichannel imaging methods

Imaging is omnipresent in modern society with imaging devices based on a zoo of physical principles, probing a specimen across different wavelengths, energies and time. Recent years have seen a change in the imaging landscape with more and more imaging devices combining that which previously was used separately. Motivated by these hardware developments, an ever increasing set of mathematical ideas is appearing regarding how data from different imaging modalities or channels can be synergistically combined in the image reconstruction process, exploiting structural and/or functional correlations between the multiple images. Here we review these developments, give pointers to important challenges and provide an outlook as to how the field may develop in the forthcoming years. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 1'

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

Towards multimodal nonlinear microscopy in clinics

Multimodal nonlinear microscopy combining two photon excited fluorescence (TPEF), second harmonic generation (SHG) and coherent anti-Stokes Raman scattering (CARS) represents a promising and powerful tool for biomedical diagnostics. The method enables label-free visualization of morphology and chemical composition of complex tissues as well as disease related changes and is as such as detailed as staining histologic methods. In this work a compact microscope utilizing novel fiber laser sources and a new approach for data analysis based on colocalization have been developed and tested for detecting various disease patterns, e.g., atherosclerosis and brain tumors.Mit Hilfe der nichtlinearen Multikontrast-Mikroskopie basierend auf den Prozessen Zweiphotonenfluoreszenz (TPEF), Frequenzverdopplung (SHG) und kohärente anti-Stokes Raman-Streuung (CARS), können Morphologie, chemische Zusammensetzung sowie krankheitsbedingte Veränderungen komplexer Gewebe label-frei analog zu histologischen Färbungen dargestellt werden. Potentiell eignet sich die Methode daher für die in vivo Bildgebung und könnte die medizinische Diagnostik entscheidend verbessern. Im Rahmen dieser Arbeit wurde ein kompaktes TPEF/SHG/CARS-Forschungsmikroskop unter Verwendung neuer Faserlaserquellen speziell für die Verwendung in der Klinik entwickelt. Dabei wurde erforscht, wie sich der Bildkontrast durch nahinfrarote Laser sowie eine hohe spektrale Auflösung verbessern lässt. Zusätzlich wurde an Methoden der Datenanalyse multispektraler CARS-Daten gearbeitet, um mittels der Kolokalisationsanalyse die Verteilung verschiedener molekularer Marker in komplexen Geweben zu visualisieren. Das Potential für klinische Anwendungen wurde an verschiedenen Krankheitsbildern wie Arteriosklerose und Tumoren des Hirns demonstriert

Spaceborne sensors (1983-2000 AD): A forecast of technology

A technical review and forecast of space technology as it applies to spaceborne sensors for future NASA missions is presented. A format for categorization of sensor systems covering the entire electromagnetic spectrum, including particles and fields is developed. Major generic sensor systems are related to their subsystems, components, and to basic research and development. General supporting technologies such as cryogenics, optical design, and data processing electronics are addressed where appropriate. The dependence of many classes of instruments on common components, basic R&D and support technologies is also illustrated. A forecast of important system designs and instrument and component performance parameters is provided for the 1983-2000 AD time frame. Some insight into the scientific and applications capabilities and goals of the sensor systems is also given

Two dimensional angular domain optical imaging in biological tissues

Optical imaging is a modality that can detect optical contrast within a biological sample that is not detectable with other conventional imaging techniques. Optical trans-illumination images of tissue samples are degraded by optical scatter. Angular Domain Imaging (ADI) is an optical imaging technique that filters scattered photons based on the trajectory of the photons. Previous angular filters were limited to one dimensional arrays, greatly limiting the imaging capability of the system. We have developed a 2D Angular Filter Array (AFA) that is capable of acquiring two dimensional projection images of a sample. The AFA was constructed using rapid prototyping techniques. The contrast and the resolution of the AFA was evaluated. The results suggest that a 2D AFA can be used to acquire two dimensional projection images of a sample with a reduced acquisition time compared to a scanning 1D AFA

Assessment and optimisation of 3D optical topography for brain imaging

Optical topography has recently evolved into a widespread research tool for non-invasively mapping blood flow and oxygenation changes in the adult and infant cortex. The work described in this thesis has focused on assessing the potential and limitations of this imaging technique, and developing means of obtaining images which are less artefactual and more quantitatively accurate. Due to the diffusive nature of biological tissue, the image reconstruction is an ill-posed problem, and typically under-determined, due to the limited number of optodes (sources and detectors). The problem must be regularised in order to provide meaningful solutions, and requires a regularisation parameter (\lambda), which has a large influence on the image quality. This work has focused on three-dimensional (3D) linear reconstruction using zero-order Tikhonov regularisation and analysis of different methods to select the regularisation parameter. The methods are summarised and applied to simulated data (deblurring problem) and experimental data obtained with the University College London (UCL) optical topography system. This thesis explores means of optimising the reconstruction algorithm to increase imaging performance by using spatially variant regularisation. The sensitivity and quantitative accuracy of the method is investigated using measurements on tissue-equivalent phantoms. Our optical topography system is based on continuous-wave (CW) measurements, and conventional image reconstruction methods cannot provide unique solutions, i.e., cannot separate tissue absorption and scattering simultaneously. Improved separation between absorption and scattering and between the contributions of different chromophores can be obtained by using multispectral image reconstruction. A method is proposed to select the optimal wavelength for optical topography based on the multispectral method that involves determining which wavelengths have overlapping sensitivities. Finally, we assess and validate the new three-dimensional imaging tools using in vivo measurements of evoked response in the infant brain

U-SPECT-BioFluo: an integrated radionuclide, bioluminescence, and fluorescence imaging platform

Background: In vivo bioluminescence, fluorescence, and single-photon emission computed tomography (SPECT) imaging provide complementary information about biological processes. However, to date these signatures are evaluated separately on individual preclinical systems. In this paper, we introduce a fully integrated bioluminescence-fluorescence-SPECT platform. Next to an optimization in logistics and image fusion, this integration can help improve understanding of the optical imaging (OI) results. Methods: An OI module was developed for a preclinical SPECT system (U-SPECT, MILabs, Utrecht, the Netherlands). The applicability of the module for bioluminescence and fluorescence imaging was evaluated in both a phantom and in an in vivo setting using mice implanted with a 4 T1-luc + tumor. A combination of a fluorescent dye and radioactive moiety was used to directly relate the optical images of the module to the SPECT findings. Bioluminescence imaging (BLI) was compared to the localization of the fluorescence signal in the tumors. Results: Both the phantom and in vivo mouse studies showed that superficial fluorescence signals could be imaged accurately. The SPECT and bioluminescence images could be used to place the fluorescence findings in perspective, e.g. by showing tracer accumulation in non-target organs such as the liver and kidneys (SPECT) and giving a semi-quantitative read-out for tumor spread (bioluminescence). Conclusions: We developed a fully integrated multimodal platform that provides complementary registered imaging of bioluminescent, fluorescent, and SPECT signatures in a single scanning session with a single dose of anesthesia. In our view, integration of these modalities helps to improve data interpretation of optical findings in relation to radionuclide images