SPECT-CT fusion: a new diagnostic tool for endocrinology

Wstęp: Wprowadzenie standardu DICOM do wszystkich urządzeń diagnostyki obrazowej umożliwiło fuzję obrazów tomografii emisyjnej pojedynczego fotonu (SPECT, single photon emission computed tomography), tomografii komputerowej (CT, computed tomography), magnetycznego rezonansu jądrowego (MRI, magnetic resonanse imaging) i innych typów danych obrazowania biomedycznego. Fuzję można wykonywanywać w dwojaki sposób, za pomocą dedykowanych skanerów hybrydowych lub przez oprogramowanie niezwiązane z konkretnym urządzeniem. Technologia fuzji posiada niezmierny potencjał w diagnostyce obrazowej do wykrywania licznych stanów, takich jak choroby nowotworowe, choroba Alzheimera oraz inne zaburzenia nerwowe. W ośrodku autorów ponad 2 lata temu stopniowo wprowadzono fuzję SPECT-CT w diagnostyce klinicznej wielu schorzeń endokrynologicznych oraz onkologicznych. Użyto danych obrazowych SPECT oraz CT wykonanych na oddzielnych i niezależnych urządzeniach (dwugłowicowej gamma-kamerze E.Cam-Duet firmy Siemens i szesnastorzędowym tomografie komputerowym Somatom Sensation firmy Siemens). Materiał i metody: Prosty i szybki algorytm o niskiej złożoności obliczeniowej zastosowano do wykonania fuzji kolejnych 81 przypadków. Trzydziestu dwóch pacjentów zakwalifikowano do fuzji SPECT-CT po terapeutycznym leczeniu 131I u chorych po amputacji tarczycy z powodu raka, 12 - po podaniu radioaktywnych analogów somatostatyny, 7 - po terapeutycznym podaniu 131 I MIBG, 6 - po diagnostycznym podaniu MIBG z 131I lub 123I, 3 - po scyntygrafii przytarczyc oraz 2 - po scyntygrafii kości. Najbardziej powszechnym wskazaniem do fuzji była potrzeba scharakteryzowania podejrzanych zmian wykrytych na skanach CT poprzez zachodzące w nich zmiany metaboliczne. Lokalizacja anatomiczna ognisk gromadzenia widzianych na obrazach SPECT oraz ocena efektów terapii radioizotopowej były kolejnymi najczęstszymi przyczynami wskazań. Wyniki: Obserwowane błędy nałożenia wynikały z tak zwanych czynników ludzkich: nieprecyzyjnego wyboru położenia markerów, ruchów oddechowych oraz przemieszczenia markerów między kolejnymi badaniami. Fuzję ponad 74% chorych określono jako "bardzo dobrą" lub "dobrą". Wnioski: Wybór chorych, wyszkolenie personelu (zwłaszcza techników i fizyków) oraz współpraca z radiologiem to najbardziej istotne czynniki, które umożliwiają właściwe zastosowanie oraz interpretację fuzji obrazów SPECT-CT.Introduction: The introduction of the DICOM format in all diagnostic imaging devices allowed coregistering SPECT, CT, MR and other types of biomedical imaging. Fusion can be performed by dedicated hybrid devices or by means of software. The fusion algorithm consists of two steps: coregistration and simultaneous visualization. Our center gradually implemented SPECT-CT fusion in clinical diagnostic work-up of several endocrinologic and oncologic diseases more than 2 years ago. Material and methods: An easy and fast algorithm in terms of computational complexity of image fusion was presented and applied to 81 consecutive cases. Thirty-two patients were scheduled to SPECT-CT fusion after thyroidectomy and 131I treatment for thyroid cancer, twelve after somatostatine receptor scintigraphy, seven after 131I MIBG therapy, six after diagnostic MIBG scintigraphy with 123I or 131I, three after parathyroid scintigraphy and two after bone scan. The most common indication to the fusion was the need of metabolic characterization of suspected lesions detected on CT scan. The anatomic localization of a focal uptake seen on SPECT and the evaluation of the radiometabolic therapy effect folloved. Results: A variance of error level observed was a result of human factor, decision on marker’s placement, respiratory movements and marker’s displacement between acquisitions. However, 74% of patients in our series have fusion results classified as "very good" or "good". Conclusions: The selection of patients, the training of the personel and the cooperation with radiologists are the most important factors for a correct application and interpretation of the SPECT-CT image fusion

Multi-Isotope Multi-Pinhole SPECT Bildgebung in kleinen Labortieren: Experimentelle Messungen und Monte Carlo Simulationen

Single photon emission computed tomography (SPECT) in small laboratory animals has become an integral part of translational medicine. It enables non-invasive validation of drug targeting, safety and efficacy in living organisms, which is progressively gaining importance in pharmaceutical industry. The increasing demand for efficiency in pharmaceutical research could be addressed by novel multitracer study designs. Multi-isotope multi-pinhole sampling allows validation of multiple tracers in a single experiment and consolidation of consecutive research trials. Due to physical and technical limitations, however, image quality and quantification can be substantially reduced. Advanced corrective procedures are required to establish multi-isotope multi-pinhole SPECT as a reliable and quantitative imaging technique for widespread use. For this purpose, the present work aimed to investigate the technical capabilities and physical limitations of multi-isotope multi-pinhole SPECT imaging in small laboratory animals. Based on experimental measurements and Monte Carlo simulations, specific error sources have been identified and procedures for quantitative image correction have been developed. A Monte Carlo simulation model of a state-of-the art SPECT/CT system has been established to provide a generalized framework for in-silico optimization of imaging hardware, acquisition protocols and reconstruction algorithms. The findings of this work can be used to improve image quality and quantification of SPECT in-vivo data for multi-isotope applications. They guide through the laborious process of multi-isotope protocol optimization and support the 3R welfare initiative that aims to replace, reduce and refine animal experimentation.Die Einzelphotonen-Emissionscomputertomographie (SPECT) in kleinen Labortieren hat sich als wichtiger Bestandteil der translationalen Medizin etabliert. Sie ermöglicht die nicht-invasive Validierung der Zielgenauigkeit, Wirksamkeit und Sicherheit von Wirkstoffen in lebenden Organismen und gewinnt zunehmend an Bedeutung in der pharmazeutischen Industrie. Die Forderung nach mehr Effizienz in der pharmazeutischen Forschung könnte durch neuartige Multitracer-Studien adressiert werden. Die Multi-Isotopen Akquisition mit Multi-Pinhole Kollimatoren ermöglicht die Validierung mehrerer Tracer in einem einzelnen Experiment und die Konsolidierung konsekutiver Bildgebungsstudien. Aufgrund physikalischer und technischer Limitationen ist die Bildqualität und Quantifizierbarkeit bei diesem Verfahren jedoch häufig reduziert. Um die Multi-Isotopen SPECT als zuverlässige und quantitative Bildgebungsmethode für den breiten Einsatz zu etablieren sind komplexe Korrekturverfahren erforderlich. Ziel der vorliegenden Arbeit war daher, die technischen Möglichkeiten und physikalischen Limitationen der Multi-Isotopen SPECT-Bildgebung in kleinen Labortieren systematisch zu untersuchen. Mithilfe von experimentellen Messungen und Monte Carlo Simulationen wurden spezifische Fehlerquellen identifiziert und Verfahren zur quantitativen Bildkorrektur entwickelt. Zudem wurde das Monte-Carlo Modell eines neuartigen SPECT/CT-Systems etabliert, um eine Plattform für die in-silico Optimierung von Bildgebungshardware, Aufnahmeprotokollen und Rekonstruktionsalgorithmen zu schaffen. Die Ergebnisse dieser Arbeit können die Bildqualität und Quantifizierbarkeit von SPECT in-vivo Daten für Multi-Isotopen Anwendungen verbessern. Sie führen beispielhaft durch den Prozess der Multi-Isotopen Protokolloptimierung und unterstützen die 3R-Initiative mit dem Ziel, experimentelle Tierversuche zu vermeiden (Replace), zu vermindern (Reduce) und zu verbessern (Refine)

Multi-Modality Imaging: A Software Fusion and Image-Guided Therapy Perspective

With the introduction of computers in medical imaging, which were popularized with the presentation of Hounsfield's ground-breaking work in 1971, numerical image reconstruction and analysis of medical images became a vital part of medical imaging research. While mathematical aspects of reconstruction dominated research in the beginning, a growing body of literature attests to the progress made over the past 30 years in image fusion. This article describes the historical development of non-deformable software-based image co-registration and it's role in the context of hybrid imaging and provides an outlook on future developments

MRI-Based Attenuation Correction in Emission Computed Tomography

The hybridization of magnetic resonance imaging (MRI) with positron emission tomography (PET) or single photon emission computed tomography (SPECT) enables the collection of an assortment of biological data in spatial and temporal register. However, both PET and SPECT are subject to photon attenuation, a process that degrades image quality and precludes quantification. To correct for the effects of attenuation, the spatial distribution of linear attenuation coefficients (μ-coefficients) within and about the patient must be available. Unfortunately, extracting μ-coefficients from MRI is non-trivial. In this thesis, I explore the problem of MRI-based attenuation correction (AC) in emission tomography. In particular, I began by asking whether MRI-based AC would be more reliable in PET or in SPECT. To this end, I implemented an MRI-based AC algorithm relying on image segmentation and applied it to phantom and canine emission data. The subsequent analysis revealed that MRI-based AC performed better in SPECT than PET, which is interesting since AC is more challenging in SPECT than PET. Given this result, I endeavoured to improve MRI-based AC in PET. One problem that required addressing was that the lungs yield very little signal in MRI, making it difficult to infer their μ-coefficients. By using a pulse sequence capable of visualizing lung parenchyma, I established a linear relationship between MRI signal and the lungs’ μ-coefficients. I showed that applying this mapping on a voxel-by-voxel basis improved quantification in PET reconstructions compared to conventional MRI-based AC techniques. Finally, I envisaged that a framework for MRI-based AC methods would potentiate further improvements. Accordingly, I identified three ways an MRI can be converted to μ-coefficients: 1) segmentation, wherein the MRI is divided into tissue types and each is assigned an μ-coefficient, 2) registration, wherein a template of μ-coefficients is aligned with the MRI, and 3) mapping, wherein a function maps MRI voxels to μ-coefficients. I constructed an algorithm for each method and catalogued their strengths and weaknesses. I concluded that a combination of approaches is desirable for MRI-based AC. Specifically, segmentation is appropriate for air, fat, and water, mapping is appropriate for lung, and registration is appropriate for bone

Use of Multicomponent Non-Rigid Registration to Improve Alignment of Serial Oncological PET/CT Studies

Non-rigid registration of serial head and neck FDG PET/CT images from a combined scanner can be problematic. Registration techniques typically rely on similarity measures calculated from voxel intensity values; CT-CT registration is superior to PET-PET registration due to the higher quality of anatomical information present in this modality. However, when metal artefacts from dental fillings are present in a pair of CT images, a nonrigid registration will incorrectly attempt to register the two artefacts together since they are strong features compared to the features that represent the actual anatomy. This leads to localised registration errors in the deformation field in the vicinity of the artefacts. Our objective was to develop a registration technique which overcomes these limitations by using combined information from both modalities. To study the effect of artefacts on registration, metal artefacts were simulated with one CT image rotated by a small angle in the sagittal plane. Image pairs containing these simulated artifacts were then registered to evaluate the resulting errors. To improve the registration in the vicinity where there were artefacts, intensity information from the PET images was incorporated using several techniques. A well-established B-splines based non-rigid registration code was reworked to allow multicomponent registration. A similarity measure with four possible weighted components relating to the ways in which the CT and PET information can be combined to drive the registration of a pair of these dual-valued images was employed. Several registration methods based on using this multicomponent similarity measure were implemented with the goal of effectively registering the images containing the simulated artifacts. A method was also developed to swap control point displacements from the PET-derived transformation in the vicinity of the artefact. This method yielded the best result on the simulated images and was evaluated on images where actual dental artifacts were present

Dosimétrie clinique en radiothérapie moléculaire

La radiothérapie moléculaire (RTM) est une radiothérapie systémique, où le produit radiopharmaceutique se lie spécifiquement sur les tumeurs pour détruire sélectivement les cibles cancéreuses tout en préservant les organes sains. Lutathera® (177Lu-DOTATATE) est un radiopharmaceutique récemment approuvé par la FDA/EMA pour le traitement des tumeurs neuroendocrines gastro-entéro-pancréatiques (GEP-NETs). Dans la pratique clinique, les patients reçoivent une activité fixe de Lutathera®, 4 cycles de 7,4 GBq, en supposant que la pharmacocinétique du radiopharmaceutique est même entre les patients. La dosimétrie spécifique au patient permet un changement de paradigme majeur dans l'administration de la RTM, passant d'une approche "taille unique" à une véritable médecine personnalisée où l'activité administrée est évaluée spécifiquement sur la base de l'irradiation délivrée à chaque patient. Pour ce faire, il faut généralement déterminer la distribution spatiale du radiopharmaceutique dans les organes par imagerie à différents moments (imagerie quantitative), estimer le nombre total de désintégrations radioactives en intégrant l'activité dans le temps (évaluation pharmacocinétique) et calculer la dose absorbée à partir des caractéristiques physiques du radionucléide et du transport de l'énergie dans les tissus du patient. Actuellement, il n'existe pas de procédures normalisées pour effectuer la dosimétrie clinique. En outre, l'évaluation des incertitudes associées à la procédure de dosimétrie n'est pas triviale. Le projet DosiTest a été lancé pour évaluer les incertitudes associées à chacune des étapes du flux de travail de la dosimétrie clinique, via une inter-comparaison multicentrique basée sur la modélisation de Monte Carlo (MC). La première phase de la thèse a consisté à comparer les analyses dosimétriques effectuées par différents centres utilisant le même logiciel et le même protocole sur le même ensemble de données de patients dans le cadre du projet IAEA-CRP E23005 afin d'évaluer la précision de la dosimétrie clinique. À notre connaissance, c'est la première fois qu'une comparaison dosimétrique multicentrique d'un seul ensemble de données cliniques sur un patient a été entreprise en utilisant le même protocole et le même logiciel par de nombreux centres dans le monde entier. Elle a mis en évidence le besoin crucial d'établir des points de contrôle et d'effectuer des vérifications de bon sens pour éliminer les disparités significatives entre les résultats et distinguer les pratiques erronées de la variabilité inter-opérateurs acceptable. Un résultat important de ce travail a été le manque d'assurance qualité en dosimétrie de médecine nucléaire clinique et la nécessité de développer des procédures de contrôle qualité. Alors que la dosimétrie gagne en popularité en médecine nucléaire, les meilleures pratiques doivent être adoptées pour garantir la fiabilité, la traçabilité et la reproductibilité des résultats. Cela met également en avant la nécessité de dispenser une formation suffisante après l'acquisition des progiciels relativement nouveaux, au-delà de quelques jours. Ceci est clairement insuffisant dans le contexte d'un domaine émergent où l'expérience professionnelle fait souvent défaut. Ensuite, l'étude de l'exactitude de la dosimétrie clinique nécessite de générer des ensembles de données de test, afin de définir la vérité de base par rapport à laquelle les procédures de dosimétrie clinique peuvent être comparées. La deuxième section de la thèse traite de la simulation de l'imagerie TEMP scintigraphique tridimensionnelle en implémentant le mouvement du détecteur d'auto-contournement dans la boîte à outils Monte Carlo GATE. Après la validation des projections TEMP/TDM sur des modèles anthropomorphes, une série d'images réalistes de patients cliniques a été générée. La dernière partie de la thèse a établi la preuve de concept du projet DosiTest, en utilisant un ensemble de données TEMP/TDM virtuelles (simulées) à différents moments, avec différentes gamma-caméras, permettant de comparer différentes techniques dosimétriques et d'évaluer la faisabilité clinique du projet dans certains départements de médecine nucléaire.Molecular radiotherapy (MRT) is a systemic radiotherapy where the radiopharmaceutical binds specifically to tumours to selectively destroy cancer targets while sparing healthy organs. Lutathera® (177Lu-DOTATATE) is a radiopharmaceutical that was recently FDA/EMA approved for the treatment of the GastroEnteroPancreatic NeuroEndocrine Tumours (GEP-NETs). In clinical practice, patients are administered with a fixed activity of Lutathera®, assuming that radiopharmaceutical distribution is the same for all patients. Patient-specific dosimetry allows for a major paradigm shift in the administration of MRT from "one-size-fits-all" approach, to real personalised medicine where administered activity is assessed specifically on the base of the irradiation delivered to each patient. This usually requires determining the spatial distribution of the radiopharmaceutical in various organs via imaging at different times (quantitative imaging), estimating the total number of radioactive decays by integrating activity over time (pharmacokinetic assessment) and calculating the absorbed dose using the physical characteristics of the radionuclide and implementing radiation transport in patient's tissues. Currently, there are no standardised procedures to perform clinical dosimetry. In addition, the assessment of the uncertainties associated with the dosimetry procedure is not trivial. The DosiTest project (http://www.dositest.org/) was initiated to evaluate uncertainties associated with each of the steps of the clinical dosimetry workflow, via a multicentric inter-comparison based on Monte Carlo (MC) modelling. The first phase of the thesis compared dosimetry analysis performed by various centres using the same software and protocol on the same patient dataset as a part of IAEA-CRP E23005 project in order to appraise the precision of clinical dosimetry. To our knowledge, this is the first time that a multi-centric dosimetry comparison of a single clinical patient dataset has been undertaken using the same protocol and software by many centres worldwide. It highlighted the critical need to establish checkpoints and conduct sanity checks to eliminate significant disparities among results, and distinguish erroneous practice with acceptable inter-operator variability. A significant outcome of this work was the lack of quality assurance in clinical nuclear medicine dosimetry and the need for the development of quality control procedures. While dosimetry is gaining popularity in nuclear medicine, best practices should be adopted to ensure that results are reliable, traceable, and reproducible. It also brings forward the need to deliver sufficient training after the acquisition of the relatively new software packages beyond a couple of days. This is clearly insufficient in a context of an emerging field where the professional experience is quite often lacking. Next, the study of clinical dosimetry accuracy requires generating test datasets, to define the ground truth against which clinical dosimetry procedures can be benchmarked. The second section of the thesis addressed the simulation of three-dimensional scintigraphic SPECT imaging by implementing auto-contouring detector motion in the GATE Monte Carlo toolkit. Following the validation of SPECT/CT projections on anthropomorphic models, a series of realistic clinical patient images were generated. The last part of the thesis established the proof of concept of the DosiTest project, using a virtual (simulated) SPECT/CT dataset at various time points, with various gamma cameras, enabling comparison of various dosimetric techniques and to assess the clinical feasibility of the project in selected nuclear medicine departments

Hybrid SPECT-CT for characterizing isolated vertebral lesions observed by bone scintigraphy: comparison with planar scintigraphy, SPECT, and CT

PURPOSEWe aimed to assess the role of single photon emission computed tomography-computed tomography (SPECT-CT) for characterizing isolated vertebral lesions observed by bone scintigraphy compared to planar scintigraphy, SPECT, and CT, and to evaluate the impact of SPECT-CT on patient management. MATERIALS AND METHODSData from 99 patients (mean age, 52.4±18.9 years; females, 58.5%) with 108 isolated vertebral lesions visible on planar bone scintigraphy, who had undergone SPECT-CT of a selected volume, were retrospectively analyzed. Planar scintigraphy, SPECT, CT, and SPECT-CT images were independently evaluated in separate sessions to minimize recall bias. A scoring scale of 1 to 5 was used, with 1 being definitely metastatic, 2 most likely metastatic, 3 indeterminate, 4 most likely benign, and 5 definitely benign. Sensitivity, specificity, and predictive values were calculated; a score ≤3 was defined as metastatic. The areas under the receiver operating characteristic curve were calculated and compared. Clinical and imaging followup with or without histopathology were used as a reference standard. RESULTSAmong the 108 lesions, 49 were indeterminate on planar scintigraphy, 16 on SPECT, and one each on SPECT-CT and CT. SPECT-CT was superior to both planar scintigraphy (P < 0.001) and SPECT alone (P = 0.014), but not to CT (P = 0.302). CT was superior to planar scintigraphy (P < 0.001) but only slightly superior to SPECT (P = 0.063). SPECT-CT correctly characterized 96% of the indeterminate lesions observed by planar scintigraphy. SPECT-CT had an impact on the clinical management of 60.6% patients compared to planar scintigraphy and 18.1% compared to SPECT. CONCLUSIONSPECT-CT is better than planar scintigraphy and SPECT alone, but not CT alone, for characterizing equivocal vertebral lesions that are observed by bone scintigraphy, thus SPECT-CT can have a significant impact on patient management

Perspectives on Nuclear Medicine for Molecular Diagnosis and Integrated Therapy

nuclear medicine; diagnostic radiolog

Evaluation of image quality and reconstruction parameters in recent PET-CT and PET-MR systems

In this PhD dissertation, we propose to evaluate the impact of using different PET isotopes for the National Electrical Manufacturers Association (NEMA) tests performance evaluation of the GE Signa integrated PET/MR. The methods were divided into three closely related categories: NEMA performance measurements, system modelling and evaluation of the image quality of the state-of-the-art of clinical PET scanners. NEMA performance measurements for characterizing spatial resolution, sensitivity, image quality, the accuracy of attenuation and scatter corrections, and noise equivalent count rate (NECR) were performed using clinically relevant and commercially available radioisotopes. Then we modelled the GE Signa integrated PET/MR system using a realistic GATE Monte Carlo simulation and validated it with the result of the NEMA measurements (sensitivity and NECR). Next, the effect of the 3T MR field on the positron range was evaluated for F-18, C-11, O-15, N-13, Ga-68 and Rb-82. Finally, to evaluate the image quality of the state-of-the-art clinical PET scanners, a noise reduction study was performed using a Bayesian Penalized-Likelihood reconstruction algorithm on a time-of-flight PET/CT scanner to investigate whether and to what extent noise can be reduced. The outcome of this thesis will allow clinicians to reduce the PET dose which is especially relevant for young patients. Besides, the Monte Carlo simulation platform for PET/MR developed for this thesis will allow physicists and engineers to better understand and design integrated PET/MR systems

Personalised advanced 3D dosimetry in peptide receptor radionuclide therapy

Peptide Receptor Radionuclide Therapy is one of the most efficient therapies against Neuro endocrine tumours. In clinical practice, absorbed dose calculations are computed based on the Medical Internal Radiation Dose (MIRD) schema which is not planned or optimised for patient-specific characteristics. This PhD project has aimed to assess the impact that advanced personalised 3D dosimetry can have within a Molecular Radiotherapy (MRT) treatment with an image-based dosimetry component. For this purpose, the impact of image registration algorithms has been studied, comparing rigid and non-rigid schemes. Results showed that nonrigid algorithms performed better than rigid equivalents in aligning images to the same frame of reference. The non-rigid algorithm was then used to investigate a workflow which involved dose maps instead of SPECT images, because such analysis has not previously been reported in the literature. Raydose, a Monte Carlo-based software package, was used to perform 3D personalised dosimetry; the results were compared against the calculations carried out with OLINDA/EXM, a MIRD-based software system. Differences were statistically significant only for kidneys and lesions (p-value<0.005). Finally, a new segmentation method for tumour delineation is described and its performance compared with a manual segmentation performed by expert 2 physicians. JACCARD analysis showed that the two methods do not have a good overlap (mean JACCARD coefficient = 0.29). From visual assessment, the proposed approach obtained better results than the manual segmentation according to the target tissue characteristics. Furthermore, quantitative analysis showed that the manual segmentation significantly overestimates the volume by 3.7 ± 13.3 cc (p-value<0.05), while it significantly underestimates the dose by -2.67 ± 6.8 Gy (p-value<0.05) compared to the proposed method. This study has demonstrated the importance of assessing accurate personalised 3D absorbed dose distribution to lesions and organs at risk. It also has the potentia