PET/MRI attenuation estimation in the lung: A review of past, present, and potential techniques

Positron emission tomography/magnetic resonance imaging (PET/MRI) potentially offers several advantages over positron emission tomography/computed tomography (PET/CT), for example, no CT radiation dose and soft tissue images from MR acquired at the same time as the PET. However, obtaining accurate linear attenuation correction (LAC) factors for the lung remains difficult in PET/MRI. LACs depend on electron density and in the lung, these vary significantly both within an individual and from person to person. Current commercial practice is to use a single-valued population-based lung LAC, and better estimation is needed to improve quantification. Given the under-appreciation of lung attenuation estimation as an issue, the inaccuracy of PET quantification due to the use of single-valued lung LACs, the unique challenges of lung estimation, and the emerging status of PET/MRI scanners in lung disease, a review is timely. This paper highlights past and present methods, categorizing them into segmentation, atlas/mapping, and emission-based schemes. Potential strategies for future developments are also presented

Developments in PET-MRI for Radiotherapy Planning Applications

The hybridization of magnetic resonance imaging (MRI) and positron emission tomography (PET) provides the benefit of soft-tissue contrast and specific molecular information in a simultaneous acquisition. The applications of PET-MRI in radiotherapy are only starting to be realised. However, quantitative accuracy of PET relies on accurate attenuation correction (AC) of, not only the patient anatomy but also MRI hardware and current methods, which are prone to artefacts caused by dense materials. Quantitative accuracy of PET also relies on full characterization of patient motion during the scan. The simultaneity of PET-MRI makes it especially suited for motion correction. However, quality assurance (QA) procedures for such corrections are lacking. Therefore, a dynamic phantom that is PET and MR compatible is required. Additionally, respiratory motion characterization is needed for conformal radiotherapy of lung. 4D-CT can provide 3D motion characterization but suffers from poor soft-tissue contrast. In this thesis, I examine these problems, and present solutions in the form of improved MR-hardware AC techniques, a PET/MRI/CT-compatible tumour respiratory motion phantom for QA measurements, and a retrospective 4D-PET-MRI technique to characterise respiratory motion. Chapter 2 presents two techniques to improve upon current AC methods that use a standard helical CT scan for MRI hardware in PET-MRI. One technique uses a dual-energy computed tomography (DECT) scan to construct virtual monoenergetic image volumes and the other uses a tomotherapy linear accelerator to create CT images at megavoltage energies (1.0 MV) of the RF coil. The DECT-based technique reduced artefacts in the images translating to improved μ-maps. The MVCT-based technique provided further improvements in artefact reduction, resulting in artefact free μ-maps. This led to more AC of the breast coil. In chapter 3, I present a PET-MR-CT motion phantom for QA of motion-correction protocols. This phantom is used to evaluate a clinically available real-time dynamic MR images and a respiratory-triggered PET-MRI protocol. The results show the protocol to perform well under motion conditions. Additionally, the phantom provided a good model for performing QA of respiratory-triggered PET-MRI. Chapter 4 presents a 4D-PET/MRI technique, using MR sequences and PET acquisition methods currently available on hybrid PET/MRI systems. This technique is validated using the motion phantom presented in chapter 3 with three motion profiles. I conclude that our 4D-PET-MRI technique provides information to characterise tumour respiratory motion while using a clinically available pulse sequence and PET acquisition method

Deep-JASC: joint attenuation and scatter correction in whole-body 18F-FDG PET using a deep residual network

Objective: We demonstrate the feasibility of direct generation of attenuation and scatter-corrected images from uncorrected images (PET-nonASC) using deep residual networks in whole-body 18F-FDG PET imaging. Methods: Two- and three-dimensional deep residual networks using 2D successive slices (DL-2DS), 3D slices (DL-3DS) and 3D patches (DL-3DP) as input were constructed to perform joint attenuation and scatter correction on uncorrected whole-body images in an end-to-end fashion. We included 1150 clinical whole-body 18F-FDG PET/CT studies, among which 900, 100 and 150 patients were randomly partitioned into training, validation and independent validation sets, respectively. The images generated by the proposed approach were assessed using various evaluation metrics, including the root-mean-squared-error (RMSE) and absolute relative error (ARE ) using CT-based attenuation and scatter-corrected (CTAC) PET images as reference. PET image quantification variability was also assessed through voxel-wise standardized uptake value (SUV) bias calculation in different regions of the body (head, neck, chest, liver-lung, abdomen and pelvis). Results: Our proposed attenuation and scatter correction (Deep-JASC) algorithm provided good image quality, comparable with those produced by CTAC. Across the 150 patients of the independent external validation set, the voxel-wise REs () were � 1.72 ± 4.22, 3.75 ± 6.91 and � 3.08 ± 5.64 for DL-2DS, DL-3DS and DL-3DP, respectively. Overall, the DL-2DS approach led to superior performance compared with the other two 3D approaches. The brain and neck regions had the highest and lowest RMSE values between Deep-JASC and CTAC images, respectively. However, the largest ARE was observed in the chest (15.16 ± 3.96) and liver/lung (11.18 ± 3.23) regions for DL-2DS. DL-3DS and DL-3DP performed slightly better in the chest region, leading to AREs of 11.16 ± 3.42 and 11.69 ± 2.71, respectively (p value < 0.05). The joint histogram analysis resulted in correlation coefficients of 0.985, 0.980 and 0.981 for DL-2DS, DL-3DS and DL-3DP approaches, respectively. Conclusion: This work demonstrated the feasibility of direct attenuation and scatter correction of whole-body 18F-FDG PET images using emission-only data via a deep residual network. The proposed approach achieved accurate attenuation and scatter correction without the need for anatomical images, such as CT and MRI. The technique is applicable in a clinical setting on standalone PET or PET/MRI systems. Nevertheless, Deep-JASC showing promising quantitative accuracy, vulnerability to noise was observed, leading to pseudo hot/cold spots and/or poor organ boundary definition in the resulting PET images. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature

MRI-based Correction for PET Photon Attenuation in Simultaneous PET/MRI Using Ultrashort Echo Time Methods

Positron emission tomography (PET) is a functional imaging modality that allows clinicians to visualize complex physiological processes such as metabolism, proliferation, perfusion, and receptor binding. Magnetic resonance imaging (MRI) is a versatile imaging modality that provides detailed anatomical images as well as functional information. Hybrid PET/MRI systems have been recently proposed as a means to combine the high-sensitivity functional information provided by PET with the high-resolution anatomical information provided by MRI. Furthermore, PET/MRI systems have the capability to provide complementary functional information acquired from both modalities. These systems have garnered significant clinical interest particularly in neurological imaging due to these capabilities. A major drawback of PET/MRI systems is the lack of an accurate, clinically feasible MRI-based method for performing PET photon attenuation correction. The current vendor-provided methods lack accuracy, and more accurate methods proposed in literature are not clinically feasible due to long computation times. The inaccuracies of the vendor-provided methods result from misidentification of tissues, particularly bone, or the assumption of homogenous attenuation coefficients inside each tissue. Therefore, the goal of this work was to develop an MR-based attenuation correction method that addresses both of these challenges in a clinically feasible framework. To achieve this goal, we propose an ultrashort echo-time method that acquires all necessary data using one sequence and produces the necessary attenuation maps quickly. The proposed sequence utilizes a dual flip-angle, dual echo-time ultrashort echo time (UTE) acquisition to segment all tissues of interest to attenuation correction in the head and neck. Next, continuous-valued attenuation coefficients are assigned to all imaging voxels through a conversion from MR relaxation rate R1. The capability of the method to generate accurate PET images was assessed by comparison to the gold standard CT-based method in a large number of subjects. The results show that the proposed method is significantly more accurate in the whole brain as well as in several smaller regions of interest when compared to the corresponding vendor-provided method. The proposed method has been fully automated and can be easily incorporated into the PET/MRI clinical work-flow.Doctor of Philosoph

MR-based attenuation correction for PET/MRI neurological studies with continuous-valued attenuation coefficients for bone through a conversion from R2* to CT-Hounsfield units

AIM: MR-based correction for photon attenuation in PET/MRI remains challenging, particularly for neurological applications requiring quantitation of data. Existing methods are either not sufficiently accurate or are limited by the computation time required. The goal of this study was to develop an MR-based attenuation correction method that accurately separates bone tissue from air and provides continuous-valued attenuation coefficients for bone. MATERIALS AND METHODS: PET/MRI and CT datasets were obtained from 98 subjects (mean age [±SD]: 66yrs [±9.8], 57 females) using an IRB-approved protocol and with informed consent. Subjects were injected with 352±29MBq of (18)F-Florbetapir tracer, and PET acquisitions were begun either immediately or 50min after injection. CT images of the head were acquired separately using a PET/CT system. Dual echo ultrashort echo-time (UTE) images and two-point Dixon images were acquired. Regions of air were segmented via a threshold of the voxel-wise multiplicative inverse of the UTE echo 1 image. Regions of bone were segmented via a threshold of the R2* image computed from the UTE echo 1 and UTE echo 2 images. Regions of fat and soft tissue were segmented using fat and water images decomposed from the Dixon images. Air, fat, and soft tissue were assigned linear attenuation coefficients (LACs) of 0, 0.092, and 0.1cm(-1), respectively. LACs for bone were derived from a regression analysis between corresponding R2* and CT values. PET images were reconstructed using the gold standard CT method and the proposed CAR-RiDR method. RESULTS: The RiDR segmentation method produces mean Dice coefficient±SD across subjects of 0.75±0.05 for bone and 0.60±0.08 for air. The CAR model for bone LACs greatly improves accuracy in estimating CT values (28.2%±3.0 mean error) compared to the use of a constant CT value (46.9%±5.8, p<10(-6)). Finally, the CAR-RiDR method provides a low whole-brain mean absolute percent-error (MAPE±SD) in PET reconstructions across subjects of 2.55%±0.86. Regional PET errors were also low and ranged from 0.88% to 3.79% in 24 brain ROIs. CONCLUSION: We propose an MR-based attenuation correction method (CAR-RiDR) for quantitative PET neurological imaging. The proposed method employs UTE and Dixon images and consists of two novel components: 1) accurate segmentation of air and bone using the inverse of the UTE1 image and the R2* image, respectively and 2) estimation of continuous LAC values for bone using a regression between R2* and CT-Hounsfield units. From our analysis, we conclude that the proposed method closely approaches (<3% error) the gold standard CT-scaled method in PET reconstruction accuracy

Magnetic Resonance Imaging Is More Sensitive Than PET for Detecting Treatment-Induced Cell Death-Dependent Changes in Glycolysis.

Metabolic imaging has been widely used to measure the early responses of tumors to treatment. Here, we assess the abilities of PET measurement of [18F]FDG uptake and MRI measurement of hyperpolarized [1-13C]pyruvate metabolism to detect early changes in glycolysis following treatment-induced cell death in human colorectal (Colo205) and breast adenocarcinoma (MDA-MB-231) xenografts in mice. A TRAIL agonist that binds to human but not mouse cells induced tumor-selective cell death. Tumor glycolysis was assessed by injecting [1,6-13C2]glucose and measuring 13C-labeled metabolites in tumor extracts. Injection of hyperpolarized [1-13C]pyruvate induced rapid reduction in lactate labeling. This decrease, which correlated with an increase in histologic markers of cell death and preceded decrease in tumor volume, reflected reduced flux from glucose to lactate and decreased lactate concentration. However, [18F]FDG uptake and phosphorylation were maintained following treatment, which has been attributed previously to increased [18F]FDG uptake by infiltrating immune cells. Quantification of [18F]FDG uptake in flow-sorted tumor and immune cells from disaggregated tumors identified CD11b+/CD45+ macrophages as the most [18F]FDG-avid cell type present, yet they represented <5% of the cells present in the tumors and could not explain the failure of [18F]FDG-PET to detect treatment response. MRI measurement of hyperpolarized [1-13C]pyruvate metabolism is therefore a more sensitive marker of the early decreases in glycolytic flux that occur following cell death than PET measurements of [18F]FDG uptake. SIGNIFICANCE: These findings demonstrate superior sensitivity of MRI measurement of hyperpolarized [1-13C]pyruvate metabolism versus PET measurement of 18F-FDG uptake for detecting early changes in glycolysis following treatment-induced tumor cell death

Improving resolution for the Siemens 3T MR-BrainPET

Tese de mestrado integrado em Engenharia Biomédica e Biofísica, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2015A tomografia por emissão de positrões (acrónimo em inglês: PET) consiste numa técnica imagiológica não invasiva que permite obter informação in vivo sobre a distribuição espácio-temporal das moléculas. Antes da aquisição de imagem é necessário que um radiofármaco seja administrado ao paciente para que posteriormente este se distribua ao longo do corpo de acordo com a estrutura química e a fisiologia da pessoa. O PET é uma modalidade de imagem médica que se destaca pela aquisição de informação fisiológica. No entanto a informação anatómica fornecida por esta técnica é bastante escassa. Para contrariar esta limitação foi proposta a fusão do PET com outra modalidade que permitisse este tipo de informação: tomografia computorizada (acrónimo em inglês: CT) ou ressonância magnética nuclear (acrónimo em inglês: MRI). Inicialmente a fusão das duas imagens médicas não permitia a aquisição simultânea, baseando-se no co-registo das imagens adquiridas. Contudo, devido a vários erros causados pelas diferenças no posicionamento do paciente, foi proposto o desenvolvimento de sistemas híbridos que permitem a aquisição simultânea das diferentes imagens. Em 1998 foi proposto o primeiro sistema hídrico (com PET), PET/CT. Como técnicas de CT envolvem radiação ionizante e apresentam um reduzido contraste entre os tecidos moles, o PET/CT foi recentemente substituído por PET/MRI, permitindo a conjugação de informação molecular do PET com informação anatómica, funcional e estrutural da MRI. No entanto, esta fusão apresentou algumas dificuldades, como por exemplo os detetores e a eletrónica do PET serem sensíveis aos campos magnéticos da MRI. Entretanto foram desenvolvidos os fotodíodos de avalanche (acrónimo em inglês: APD) permitindo a construção dos sistemas híbridos PET/MRI. O BrainPET foi o primeiro sistema híbrido de PET/MRI, existindo apenas quatro scanners em todo o mundo. O scanner 3TMR-BrainPET, desenvolvido pela Siemens Medical Solution Inc., foi construído para imagiologia cerebral. Este scanner permite a aquisição de imagens PET com alta resolução (3 mm). Alguns exames médicos como o PET apresentam uma aquisição muito longa (aproximadamente 1 hora), tornando-se difícil para o paciente permanecer imóvel durante toda a aquisição. Por conseguinte, na maioria dos casos, o movimento torna-se inevitável, introduzindo artefactos na imagem e consequentemente degradando-a. Assim, torna-se fundamental corrigir este movimento para assegurar a qualidade ótima das imagens, oferecendo a perspetiva de melhorar o diagnóstico e o tratamento. Ao longo dos anos foram propostos diversos métodos de correção do movimento. Uns corrigem-no no domínio da imagem, corrigindo apenas o movimento entre as frames mas não o que ocorre dentro de cada uma delas, e outros no domínio dos eventos, em que a correção do movimento consegue ser mais precisa uma vez que é feita diretamente nos eventos adquiridos. No contexto PET/MRI, ambas as imagens, PET e MRI, podem ser utilizadas para estimar o movimento e posteriormente corrigi-lo. Nesta tese focar-nos-emos apenas na correção do movimento da cabeça que é considerado um movimento rígido e os parâmetros que o representam, três rotações e três translações de acordo com os três eixos Cartesianos (x, y e z), podem ser estimados utilizando algoritmos de registo de imagens. Este trabalho apresenta e testa um software de código aberto que dispõe desses algoritmos de dados multidimensionais, o Insight Toolkit (ITK), permitindo a estimação do movimento no domínio da imagem. O ITK já foi aplicado, com sucesso, em estudos de correções do movimento em modalidades técnicas de imagem, tanto para movimentos rígidos como deformáveis, que é o caso do movimento provocado pela respiração ou pelo batimento cardíaco. Relativamente à metodologia aplicada neste trabalho, inicialmente foram adquiridas imagens MPRAGE (imagens adquiridas com MRI) com o intuito de descobrir o alcance máximo do movimento da cabeça dentro das bobines do scanner. De seguida foram simulados quatro alcances diferentes: 1, 5, 10 e 30 de translação (mm) e de rotação (º) considerando os três eixos (x, y e z). Com o objetivo de testar a versatilidade do software, estas simulações foram realizadas em diversos tipos de imagens como, imagens clinicas, [18F]-FDG (imagem adquirida com PET) e EPI (imagem adquirida com MRI), e imagens de fantomas simulados, fantoma Utah e fantoma cerebral. Ao longo da dissertação foram realizados diversos estudos, como por exemplo, o estudo da influência da estatística de aquisição e do número de iterações do método de reconstrução de imagem na estimação do movimento. A estatística de aquisição influencia qualitativamente as imagens de PET, uma vez que quanto maior a estatística menor é o ruido. Ao mesmo tempo esta também é influenciada pelo número de iterações, visto que à medida que se aumenta o número de iterações o ruído da imagem aumenta, no entanto quando a imagem contém um número de iterações menor esta apresenta um bias maior. O ITK estima o movimento a partir de uma comparação de valores de intensidade das imagens, por conseguinte estas alterações qualitativas na imagem levam a diferentes estimações dos parâmetros do mesmo movimento simulado. Como um dos objetivos da tese consiste em verificar se o ITK pode ser utilizado para estimar o movimento no Instituto Forschungszentrum Juelich (FZJ), foram, adicionalmente, testadas imagens de cinco exames diferentes adquiridos rotineiramente no scanner 3TMR-BrainPET deste instituto. Em todas as imagens o movimento foi estimado utilizando o ITK. Este software apresenta um método iterativo para estimação do movimento. O ITK necessita de duas imagens de input, uma imagem fixa e uma imagem movida, enquanto o output deste software consiste em três translações e três rotações de acordo com os eixos cartesianos (transformada de Euler) que correspondem aos parâmetros do movimento rígido da cabeça. Ulteriormente, para corrigir esses movimentos, foram aplicadas transformadas inversas nas imagens afetadas pelo movimento. Estas transformadas podem ser aplicadas por outro programa, como por exemplo o PRESTO (PET REconstruction Software Toolkit), um software de reconstrução constituído por bibliotecas desenvolvidas em programação C++. Neste trabalho, utilizou-se o PRESTO para a aplicação das transformadas, na correção do movimento e na simulação dos fantomas e dos movimentos nas imagens. Atualmente o FZJ utiliza um software diferente do ITK para corrigir o movimento, o PMOD (PMOD Technologies Ltd, Zurique, Suíça). No entanto este apresenta algumas limitações, como por exemplo, o facto de ser um software comercial e este não poder ser incorporado no script de reconstrução, sendo necessário um processo adicional trabalhoso, ao contrário do ITK que permite que a correção do movimento seja feita automaticamente durante a reconstrução, corrigindo o movimento diretamente nas linhas de resposta (acrónimo em inglês: LORs). Adicionalmente o PMOD requer um utilizador com conhecimento prévio sobre o software para conseguir manuseá-lo. Para confirmar a viabilidade do ITK e verificar se este pode substituir o PMOD na correção do movimento no instituto, foi feita uma comparação entre os resultados dos dois software. Os resultados obtidos revelaram-se muito semelhantes, exceto quando se utiliza imagens de PET com baixa estatística ou imagens com grandes movimentos. Como as imagens sem correção de atenuação apresentam maior diferença de intensidades entre as fronteiras do objeto em estudo e o fundo da imagem, pensou-se na hipótese de os parâmetros do movimento obtidos pelo ITK ou pelo PMOD poderem apresentar erros menores utilizando imagens sem correção de atenuação. Ao mesmo tempo, como a correção do movimento atualmente no instituto está a ser realizada depois da reconstrução, um mapa de atenuação errado (mapa que não considera o movimento) está a ser aplicado à imagem. Neste sentido, o impacto do mapa de atenuação aplicado às imagens afetadas pelo movimento foi também estudado nesta dissertação. Os maiores erros foram encontrados quando se utilizou imagens sem correção de atenuação. Os bons resultados do PMOD revelaram-se mais dependentes da aplicação do mapa de atenuação correto. Em conclusão o ITK apresentou melhores resultados que o PMOD e a diferença entre as três imagens testadas pelo ITK não se revelou muito significativa. Com o objetivo de melhorar os resultados obtidos, três métricas diferentes do ITK (Mutual Information, Mean Squares e Normalized Correlation) foram comparadas entre si, aplicando diferentes imagens de PET e de MRI como input. Este teste mostrou que a métrica é um parâmetro altamente dependente do problema que se tenta resolver. A métrica mutual information é a melhor métrica para corrigir o movimento utilizando imagens de diferentes modalidades, enquanto a métrica normalized correlation é a melhor nos estudos com imagens da mesma modalidade. De acordo com todos os resultados obtidos, pode-se afirmar que o ITK é um método viável para a estimação dos parâmetros do movimento rígido e tem capacidades de substituir o PMOD. Esses parâmetros, posteriormente, podem ser utilizados para a correção do movimento no pós-processamento de imagens de PET ou MRI.The Siemens 3TMR-BrainPET scanner is a hybrid system which allows simultaneous acquisition of MRI and PET. There are medical exams that have long acquisition time and then it is inevitable introducing blurring in images. Therefore motion correction strategies are mandatory. In PET/MRI context, both PET and MRI images can be used for this purpose. Head motion is considered as rigid motion and the motion parameters can be estimated with image registration algorithms. In this thesis a software which has available these algorithms, Insight Toolkit (ITK), will be presented and tested. First MPRAGE images were acquired to check the maximum motion range inside the scanner head coil during acquisition. Therefore four motion ranges were simulated in translation and rotation with respect to the three Cartesian axes. Testing the software versatility, these simulations were realized in different images: simulated and clinical data. Several studies were made with these images e.g. the influence of statistics and number of iterations in motion estimation. Additionally images from five different exams performed in FZJ were also used. The motion was estimated by ITK. The ITK output is three translations and three rotations which correspond to the rigid motion parameters. Subsequently, to correct the motion, inverse transformations were applied in moved images. Actually FZJ uses other software, PMOD (PMOD Technologies Ltd, Zurich, Switzerland) to motion correction. For the purpose of confirm the viability of ITK and to verify if it can replace the PMOD, ITK results were compared with PMOD results. Other tests were made with the aim to improve the results such as study the impact of the attenuation map in motion estimation and the comparison between ITK results using three different metrics. According to results, ITK is a viable method of motion parameter estimation which can be used for PET or MRI post-processing motion correction

Are Quantitative Errors Reduced with Time-of-Flight Reconstruction When Using Imperfect MR-Based Attenuation Maps for F-18-FDG PET/MR Neuroimaging?

We studied whether TOF reduces error propagation from attenuation correction to PET image reconstruction in PET/MR neuroimaging, by using imperfect attenuation maps in a clinical PET/MR system with 525 ps timing resolution. Ten subjects who had undergone F-18-FDG PET neuroimaging were included. Attenuation maps using a single value (0.100 cm(-1)) with and without air, and a 3-class attenuation map with soft tissue (0.096 cm(-1)), air and bone (0.151 cm(-1)) were used. CT-based attenuation correction was used as a reference. Volume-of-interest (VOI) analysis was conducted. Mean bias and standard deviation across the brain was studied. Regional correlations and concordance were evaluated. Statistical testing was conducted. Average bias and standard deviation were slightly reduced in the majority (23-26 out of 35) of the VOI with TOF. Bias was reduced near the cortex, nasal sinuses, and in the mid-brain with TOF. Bland-Altman and regression analysis showed small improvements with TOF. However, the overall effect of TOF to quantitative accuracy was small (3% at maximum) and significant only for two attenuation maps out of three at 525 ps timing resolution. In conclusion, TOF might reduce the quantitative errors due to attenuation correction in PET/MR neuroimaging, but this effect needs to be further investigated on systems with better timing resolution.</p