A comparative evaluation of 3 different free-form deformable image registration and contour propagation methods for head and neck MRI : the case of parotid changes radiotherapy

Purpose: To validate and compare the deformable image registration and parotid contour propagation process for head and neck magnetic resonance imaging in patients treated with radiotherapy using 3 different approachesthe commercial MIM, the open-source Elastix software, and an optimized version of it. Materials and Methods: Twelve patients with head and neck cancer previously treated with radiotherapy were considered. Deformable image registration and parotid contour propagation were evaluated by considering the magnetic resonance images acquired before and after the end of the treatment. Deformable image registration, based on free-form deformation method, and contour propagation available on MIM were compared to Elastix. Two different contour propagation approaches were implemented for Elastix software, a conventional one (DIR_Trx) and an optimized homemade version, based on mesh deformation (DIR_Mesh). The accuracy of these 3 approaches was estimated by comparing propagated to manual contours in terms of average symmetric distance, maximum symmetric distance, Dice similarity coefficient, sensitivity, and inclusiveness. Results: A good agreement was generally found between the manual contours and the propagated ones, without differences among the 3 methods; in few critical cases with complex deformations, DIR_Mesh proved to be more accurate, having the lowest values of average symmetric distance and maximum symmetric distance and the highest value of Dice similarity coefficient, although nonsignificant. The average propagation errors with respect to the reference contours are lower than the voxel diagonal (2 mm), and Dice similarity coefficient is around 0.8 for all 3 methods. Conclusion: The 3 free-form deformation approaches were not significantly different in terms of deformable image registration accuracy and can be safely adopted for the registration and parotid contour propagation during radiotherapy on magnetic resonance imaging. More optimized approaches (as DIR_Mesh) could be preferable for critical deformations

Cohort-based T-SSIM Visual Computing for Radiation Therapy Prediction and Exploration

We describe a visual computing approach to radiation therapy (RT) planning, based on spatial similarity within a patient cohort. In radiotherapy for head and neck cancer treatment, dosage to organs at risk surrounding a tumor is a large cause of treatment toxicity. Along with the availability of patient repositories, this situation has lead to clinician interest in understanding and predicting RT outcomes based on previously treated similar patients. To enable this type of analysis, we introduce a novel topology-based spatial similarity measure, T-SSIM, and a predictive algorithm based on this similarity measure. We couple the algorithm with a visual steering interface that intertwines visual encodings for the spatial data and statistical results, including a novel parallel-marker encoding that is spatially aware. We report quantitative results on a cohort of 165 patients, as well as a qualitative evaluation with domain experts in radiation oncology, data management, biostatistics, and medical imaging, who are collaborating remotely.Comment: IEEE VIS (SciVis) 201

Spinal involvement in mucopolysaccharidosis IVA (Morquio-Brailsford or Morquio A syndrome): presentation, diagnosis and management.

Mucopolysaccharidosis IVA (MPS IVA), also known as Morquio-Brailsford or Morquio A syndrome, is a lysosomal storage disorder caused by a deficiency of the enzyme N-acetyl-galactosamine-6-sulphate sulphatase (GALNS). MPS IVA is multisystemic but manifests primarily as a progressive skeletal dysplasia. Spinal involvement is a major cause of morbidity and mortality in MPS IVA. Early diagnosis and timely treatment of problems involving the spine are critical in preventing or arresting neurological deterioration and loss of function. This review details the spinal manifestations of MPS IVA and describes the tools used to diagnose and monitor spinal involvement. The relative utility of radiography, computed tomography (CT) and magnetic resonance imaging (MRI) for the evaluation of cervical spine instability, stenosis, and cord compression is discussed. Surgical interventions, anaesthetic considerations, and the use of neurophysiological monitoring during procedures performed under general anaesthesia are reviewed. Recommendations for regular radiological imaging and neurologic assessments are presented, and the need for a more standardized approach for evaluating and managing spinal involvement in MPS IVA is addressed

Proteomic analysis in nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is a particular type of head and neck cancer with a strong ethnic and enigmatic epidemiology that long puzzles the scientific society. Despite present all over the world, around 80% of all cases are in Asia where it is endemic, followed by low incidence regions in all other continents. Portugal has the second incidence in Europe for women, and third for men (Globocan 2012) among all European countries. Many efforts have been made to clarify and understand this unique geographic and epidemiologic distribution. The onset and evolution of nasopharyngeal carcinoma is a complex multi-stage process and may take a long time to occur. Although the molecular basis remains uncertain, we know that environmental factors, Epstein-Barr virus (EBV) infection and genetic susceptibility are considered to be the three major contributors. Further examination of these genes’ expression in each tumor revealed that around 93 oncogenes are up regulated in each tumor, while the mean number of TSGs down regulated was 109. In Portugal, the works of Souza & Breda have identified important polymorphism markers that may play a role in the onset and NPC development on the Portuguese northern region population. Despite the efforts made, the molecular mechanisms of NPC carcinogenesis and progression remains to be understood. In this regard, current omics methodologies offer a different approach to identify unique miRNAs and proteins that expression signatures associated with the cancer phenotype, reflecting the biological and pathological grade of the disease. Thus, the discovery of useful NPC biomarkers will lead to new diagnostic and prognostic tools. Meanwhile, the treatment of NPC has evolved in the past two decades. Since 2000, intensity modulated radiation therapy (IMRT) has been widely used to treat nasopharyngeal carcinoma. IMRT provides better dose delivery to the target while sparing the surrounding normal tissues while local control reaches 98% at 4 years24-28. At least one prospective randomized controlled trial showed its benefit in salivary protection in HNC. However, despite the excellent local control, 43% of patients will develop distant metastasis before 5 years and die25-26. In Portugal, IMRT is used at the Instituto Português de Oncologia de Lisboa (IPOLFG) since 2009 and represents the current standard of care for HNC RT, including NPC. Until now, several prognostic markers were identified and investigated for screening, and prognostic tools for NPC, have been purposed, particularly in Asia. However, to our knowledge, there are no validated identified markers to predict distant metastasis or outcome. Moreover, the studies exploring this subject have identified a population-based variety of biomarkers stressing an omic translation of NPC ethnic distribution. At the present work, this research explored formalin-fixed paraffin-embedded samples of biopsied nasopharyngeal carcinoma tumors via proteomic analysis. The aim is to describe a tumor profiling from the studied cohort and discover biomarkers to predict distant metastasis. Secondary endpoints are the discovery of biomarkers related to tumor radioresistance and treatment toxicity. Label-free quantitative mass spectrometry was able to identify 12 up-regulated proteins on early-stage primary tumors that were not present on advanced-stage primaries. Moreover, EBV and HSV co-infection was detected. No signs of HPV-related proteins were seen. Although the clinical outcomes of early and advanced primary tumors were identical, this can be attributed to the known effectiveness of intensive chemoradiation. Moreover, the difference in tumor profiling may reflect that those earlystage tumors could benefit from de-escalation protocols. We were able to detect the presence of a pool of 10 proteins related to distant metastases. Among them, the significant presence of interferon and tyrosine kinase proteins generates the hypothesis that they may represent therapeutic targets. Validation is needed.O carcinoma da nasofaringe (NPC) é um tipo particular de cancro da cabeça e pescoço com um epidemiologia enigmática e forte cariz étnico que há muito intriga a comunidade científica. Apesar de presente em todo o mundo, 805 dos casos encontram-se na Ásia, onde é endémico, seguido de regiões de media e baixa incidência em todos os outros continentes. Portugal tem a segunda incidência em mulheres e a terceira em homens dentre todos os países da Europa (Globocan 2012). Muitos esforços foram realizados para esclarecer e compreender esta distribuição epidemiológica e geográfica. A instalação e evolução do NPC é um processo com múltiplas fases e pode demorar um longo período de tempo para ocorrer. Apesar da base molecular da sua origem permanecer incerta, sabe-se que factores ambientais, a infecção pelo vírus Epstein-Barr e a susceptibilidade genética do hospedeiro são os três maiores contribuidores. Análise aprofundada da expressão genética revelou que cerca de 93 oncogenes estão sobre regulados enquanto que o número médio de genes supressores de tumor down regulated é de cerca de 109. Em Portugal, o trabalho de Souza & Breda identificaram um importante marcador de polimorfismo que pode estar relacionado com a instalação do NPC na população portuguesa na região norte. À despeito dos esforços realizados, o mecanismo molecular da carcinogênese do NPC e sua progressão permanecem por ser esclarecidos. A este respeito, as actuais tecnologias de ômica oferecem uma abordagem diferente capaz de identificar miRNAs e proteínas únicos que expressam assinatura com um fenótipo do cancro, refletindo o grau biológico e patológico da doença. Assim, a descoberta de biomarcadores úteis levará a novas ferramentas prognósticas. Ao mesmo tempo, o tratamento do NPC evoluiu consideravelmente nas últimas duas décadas. Desde 2000, a radioterapia com intensidade modulada do feixe (IMRT) tem sido amplamente utilizada para o tratamento do carcinoma da nasofaringe. IMRT fornece melhor entrega da dose ao alvo enquanto poupa os tecidos adjacentes sadios ao mesmo tempo que o controlo local alcança 98% aos 4 anos (Lee et al, 2002). Pelo menos uma meta-análise demonstrou o benefício na capacidade de proteção salivar em carcinomas da cabeça e pescoço. Entretanto, apesar do excelente controlo local, até 43% dos doentes vão morrer devido às metástases à distância antes dos 5 anos. Em Portugal, IMRT é utilizada no Instituto Português de Oncologia de Lisboa (IPOLFG) desde 2009 e representa o actual estado da arte no tratamento da maioria dos carcinomas da cabeça e pescoço incluindo NPC. Até o momento, diversos marcadores prognósticos de NPC foram propostos, particularmente na Ásia. Contudo, até o momento não são utilizados marcadores validades para predizer metástases ou evolução do doente. Estudos avaliando esta questão identificaram uma população variada de biomarcadores distintos a outras regiões geográficas, ressaltando a diversidade étnica da população dos doentes com NPC. Neste trabalho, esta pesquisa explorou amostras de carcinoma da nasofaringe provenientes de biopsias fixadas em formalina e embebidas em parafina através de análise proteómica. O objectivo é descrever o perfil tumoral da coorte estudada e descobrir biomarcadores capazes de predizer metástases à distância. Objectivos secundários é a descoberta de biomarcadores relacionados ao tumor que determinem radioresistência ou toxicidade ao tratamento. Espectroscopia de massa por ressonância magnética foi capaz de identificar 12 proteínas sobre expressadas nas em tumores primários iniciais que não estão presentes em tumores primários avançados. Além disso, foi detectada uma coinfecção EBV e HSV sem sinais de proteínas relacionadas ao HPV. Apesar dos resultados clínicos terem sido idênticos em ambos os grupos, isto pode ser explicado pela efectividade e intensidade do tratamento combinado. Além disso, a diferença em perfil tumorais podem refletir um perfil de doentes que poderia se beneficiar de protocolos de desintensificação. Esta pesquisa foi capaz de detectar a presença de 10 proteínas relacionadas aos doentes com metástases à distância. Entre elas, a presença de interferon e inibidores da tirosina cinase geram a hipótese de que podem representar potenciais alvos terapêuticos

Medical Image Analytics (Radiomics) with Machine/Deeping Learning for Outcome Modeling in Radiation Oncology

Image-based quantitative analysis (radiomics) has gained great attention recently. Radiomics possesses promising potentials to be applied in the clinical practice of radiotherapy and to provide personalized healthcare for cancer patients. However, there are several challenges along the way that this thesis will attempt to address. Specifically, this thesis focuses on the investigation of repeatability and reproducibility of radiomics features, the development of new machine/deep learning models, and combining these for robust outcomes modeling and their applications in radiotherapy. Radiomics features suffer from robustness issues when applied to outcome modeling problems, especially in head and neck computed tomography (CT) images. These images tend to contain streak artifacts due to patients’ dental implants. To investigate the influence of artifacts for radiomics modeling performance, we firstly developed an automatic artifact detection algorithm using gradient-based hand-crafted features. Then, comparing the radiomics models trained on ‘clean’ and ‘contaminated’ datasets. The second project focused on using hand-crafted radiomics features and conventional machine learning methods for the prediction of overall response and progression-free survival for Y90 treated liver cancer patients. By identifying robust features and embedding prior knowledge in the engineered radiomics features and using bootstrapped LASSO to select robust features, we trained imaging and dose based models for the desired clinical endpoints, highlighting the complementary nature of this information in Y90 outcomes prediction. Combining hand-crafted and machine learnt features can take advantage of both expert domain knowledge and advanced data-driven approaches (e.g., deep learning). Thus, we proposed a new variational autoencoder network framework that modeled radiomics features, clinical factors, and raw CT images for the prediction of intrahepatic recurrence-free and overall survival for hepatocellular carcinoma (HCC) patients in this third project. The proposed approach was compared with widely used Cox proportional hazard model for survival analysis. Our proposed methods achieved significant improvement in terms of the prediction using the c-index metric highlighting the value of advanced modeling techniques in learning from limited and heterogeneous information in actuarial prediction of outcomes. Advances in stereotactic radiation therapy (SBRT) has led to excellent local tumor control with limited toxicities for HCC patients, but intrahepatic recurrence still remains prevalent. As an extension of the third project, we not only hope to predict the time to intrahepatic recurrence, but also the location where the tumor might recur. This will be clinically beneficial for better intervention and optimizing decision making during the process of radiotherapy treatment planning. To address this challenging task, firstly, we proposed an unsupervised registration neural network to register atlas CT to patient simulation CT and obtain the liver’s Couinaud segments for the entire patient cohort. Secondly, a new attention convolutional neural network has been applied to utilize multimodality images (CT, MR and 3D dose distribution) for the prediction of high-risk segments. The results showed much improved efficiency for obtaining segments compared with conventional registration methods and the prediction performance showed promising accuracy for anticipating the recurrence location as well. Overall, this thesis contributed new methods and techniques to improve the utilization of radiomics for personalized radiotherapy. These contributions included new algorithm for detecting artifacts, a joint model of dose with image heterogeneity, combining hand-crafted features with machine learnt features for actuarial radiomics modeling, and a novel approach for predicting location of treatment failure.PHDApplied PhysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163092/1/liswei_1.pd

Two-step-fusion 18F-fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (FDG-PET/CT) based radiotherapy in locally advanced oropharyngeal cancer

Aims. To develop two-step-fusion 18F-fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (FDG-PET/CT) based radiotherapy in locally advanced oropharyngeal cancer at the Beatson West of Scotland Cancer Centre and evaluate the technical and clinical aspect of this multi-modality imaging methodology. Methods. I conducted a radiotherapy service development project at the Beatson. Contrast enhanced radiotherapy simulation CT (CTsim) and FDG-PET/CT were acquired separately with the same set-up and fused using an automatic rigid fusion algorithm (Eclipse, Varian). The fusion accuracy was assessed with the spatial reproducibility index (R=intersection/union ratio) of bony structures. Radiotherapy target volumes for both primary (T) and nodal disease (N) were defined separately on CTsim and FDG-PET/CT using visual assessment (PET/CT-vis) and segmentation with 50% SUVmax (PET/CT-50%). Volumes (cc) and spatial reproducibility (R) were calculated for the various volumes. Changes in TNM staging definition due to FDG-PET/CT were evaluated and compared with the staging based on morphological imaging (CT±MRI) and clinical information (endoscopy). SUVmax was calculated for T and N and correlated with the HPV-status and the oropharyngeal prognostic groups (low risk: HPV+, ≤10 pack years smoking history; intermediate risk: HPV+, >10 pack years smoking history; high risk: HPV-). Patients were treated using the target volumes defined with PET/CT-vis. Volumetric Modulated Arc Therapy (VMAT) was used with 65Gy and 54Gy in 30 fractions to high and low risk volumes respectively. Tumour outcome and late toxicity were recorded and compared with an internal non-PET/CT-based oropharyngeal series. Data were analysed using Stata v14.2 (StataCorp LLC, Texas). Data were summarised using medians (with range or inter-quartile range IQR). P-values were calculated to test for differences. All tests were 2-sided and a p-value <0.05 was considered statistically significant. Results. A total of 30 patients were enrolled. The fusion accuracy of FDG-PET/CT and CTsim was calculated in 14 patients and resulted 0.89 (0.83-0.92). SUVmax was recorded for both primary and nodal disease in 27 patients. Among these patients median SUVmax was significantly higher in the primary tumour compared to the nodal disease (19.0 versus 14.0 g/ml, p=0.0001). Median SUVmax was higher in HPV- compared to HPV+ patients for both primary tumour (21.0 vs 16.9 g/ml) and nodal disease (17.0 vs 10.0 g/ml), however these differences were not statistically significant. Nodal SUVmax was higher in the high risk (i.e. HPV-) compared to the intermediate and low risk (i.e. HPV+) group (17.0 vs 8.8 vs 15.o g/ml) although again these differences were not statistically significant. FDG-PET/CT down-staged and up-staged T and N in 6/30 (20%) and 17/30 (57%) patients. Unsuspected distant metastases were not detected in any of the patients at baseline. The median volume of T and N defined with PET/CTvis and CTsim was 11.5cc vs 16.5cc (p=0.31) and 13.8cc vs 11.1cc (p=0.42), with reproducibility index R=0.49 and R=0.47 respectively. PET/CT50% identified hyper-metabolic sub-volumes inside PET/CTvis for both T and N: 4.6cc vs 11.5cc (p=0.001) and 3.5cc vs 13.8cc (p=0.04), DICE index 1. At median follow-up time of 16 (1-44) months, 74% of the patients had complete response, whilst 22% had progressive disease with median time to progression of 6.1 (3.1-15.9) months. The estimated overall survival (OS) at 2 years was 74% (95%CI, 49%-88%). In the sub-group analysis, the estimated OS at 2 years was 83% (95%CI 27-97%), 87% (39-98%) and 67% (19-90%) in the low, intermediate and high risk category respectively. Grade≥2 late xerostomia, dysphagia, dysgeusia and fatigue were recorded in 36%, 35%, 0% and 14% of the patients. Grade≥2 dysphagia was recorded in 38% of the patients who presented with bilateral and unilateral neck nodes (p=1.0). Conclusions. I developed a 2-step-fusion methodology between FDG-PET/CT and CTsim. PET/CT fusion has been introduced in the routine radiotherapy planning at the Beatson for selected oropharyngeal cancer patients. My data suggest that HPV- are more metabolically active than HPV+ oropharyngeal cancers. My results support the hypothesis of treatment intensification in the high-risk group because more biologically aggressive. Dose intensification to hypermetabolic tumour sub-volumes may improve the outcome especially in the high-risk sub-group. FDG-PET/CT modified tumour staging and radiotherapy target volumes. My outcome and late toxicity results are similar to an internal non-PET-based series and other published studies. A prospective randomised study stratified by risk group would clarify if a true difference exists in outcome and late toxicity between PET-based and non-PET-based radiotherapy

Copy number of 8q24.3 drives HSF1 expression and patient outcome in cancer: an individual patient data meta-analysis

Background: The heat-shock transcription factor 1 (HSF1) has been linked to cell proliferation and survival in cancer and has been proposed as a biomarker for poor prognosis. Here, we assessed the role of HSF1 expression in relation to copy number alteration (CNA) and cancer prognosis. Methods: Using 10,287 cancer genomes from The Cancer Genome Atlas and Cbioportal databases, we assessed the association of HSF1 expression with CNA and cancer prognosis. CNA of 8q24.3 was categorized as diploid (reference), deletion (fewer copies), gain (+ 1 copy) and amplification (>= + 2 copies). Multivariate logistic regression modeling was used to assess 5-year survival among those with a first cancer diagnosis and complete follow-up data (N = 9568), categorized per anatomical location and histology, assessing interaction with tumor stage, and expressed as odds ratios and 95% confidence intervals. Results: We found that only 54.1% of all tumors have a normal predicted 8q24.3 copy number and that 8q24.3 located genes including HSF1 are mainly overexpressed due to increased copies number of 8q24.3 in different cancers. The tumor of patients having respectively gain (+ 1 copy) and amplification (>= + 2 copies) of 8q24.3 display a global increase of 5-year mortality (odds ratio = 1.98, 95% CI 1.22-3.21) and (OR = 2.19, 1.13-4.26) after full adjustment. For separate cancer types, tumor patients with 8q24.3 deletion showed a marked increase of 5-year mortality in uterine (OR = 4.84, [2.75-8.51]), colorectal (OR = 4.12, [1.15-14.82]), and ovarian (OR = 1.83, [1.39-2.41]) cancers; and decreased mortality in kidney cancer (OR = 0.41, [0.21-0.82]). Gain of 8q24.3 resulted in significant mortality changes in 5-year mortality for cancer of the uterus (OR = 3.67, [2.03-6.66]), lung (OR = 1.76, [1.24-2.51]), colorectal (OR = 1.75, [1.32-2.31]) cancers; and amplification for uterine (OR = 4.58, [1.43-14.65]), prostate (OR = 4.41 [3.41-5.71]), head and neck (OR = 2.68, [2.17-3.30]), and stomach (OR = 0.56, [0.36-0.87]) cancers. Conclusions: Here, we show that CNAs of 8q24.3 genes, including HSF1, are tightly linked to 8q24.3 copy number in tumor patients and can affect patient outcome. Our results indicate that the integration of 8q24.3 CNA detection may be a useful predictor for cancer prognosis

What went wrong? The flawed concept of cerebrospinal venous insufficiency

In 2006, Zamboni reintroduced the concept that chronic impaired venous outflow of the central nervous system is associated with multiple sclerosis (MS), coining the term of chronic cerebrospinal venous insufficiency ('CCSVI'). The diagnosis of 'CCSVI' is based on sonographic criteria, which he found exclusively fulfilled in MS. The concept proposes that chronic venous outflow failure is associated with venous reflux and congestion and leads to iron deposition, thereby inducing neuroinflammation and degeneration. The revival of this concept has generated major interest in media and patient groups, mainly driven by the hope that endovascular treatment of 'CCSVI' could alleviate MS. Many investigators tried to replicate Zamboni's results with duplex sonography, magnetic resonance imaging, and catheter angiography. The data obtained here do generally not support the 'CCSVI' concept. Moreover, there are no methodologically adequate studies to prove or disprove beneficial effects of endovascular treatment in MS. This review not only gives a comprehensive overview of the methodological flaws and pathophysiologic implausibility of the 'CCSVI' concept, but also summarizes the multimodality diagnostic validation studies and open-label trials of endovascular treatment. In our view, there is currently no basis to diagnose or treat 'CCSVI' in the care of MS patients, outside of the setting of scientific research

Gene expression profiling of head and neck cancer

MDThe purpose of this study was to classify oral squamous cell carcinomas (OSCCs) based on their gene expression profiles, to identify differentially expressed genes in these cancers, and to correlate genetic deregulation with clinical-histopathological data and patient outcome. After conducting proof of principle experiments utilizing six head and neck squamous cell carcinomas (HNSCCs) cell lines, the gene expression profiles of 20 OSCCs and subsequently an additional 8 OSCCs were determined using cDNA microarrays containing 19,200 sequences and the Binary Tree-Structured Vector Quantization (BTSVQ) method of data analysis. Two sample clusters were identified in the group of 20 tumors that correlated with T3-T4 category of disease (P=0.035) and nodal metastasis( p=0.035). Samplec lustering of 28 OSCCsa nd the 6 cell lines revealed a correlation with disease free survival. BTSVQ analysis identified a subset of 23 differentially expressed genes with the lowest quantization error scores in the cluster containing more advanceds taget umors from the 20 OSCC dataset.T he expressiono f six of these differentially expressedg enesw as validated by quantitative real-time RT-PCR. Statistical analysis of quantitative real-time RT-PCR data was performed and, after Bonferroni correction, CLDNI (p = 0.007) over-expressionw as significantly correlated with the cluster containing more advanced stage tumors. Despite the clinical heterogeneity of OSCC, molecular subtyping by cDNA microarray analysis was able to identify distinct patternso f genee xpressiona ssociatedw ith relevant clinical parameters. The application of this methodology represents an advance in the classification of oral cavity tumors, and may ultimately aid in the development of more tailored therapies for oral carcinoma