Facial soft tissue segmentation

The importance of the face for socio-ecological interaction is the cause for a high demand on any surgical intervention on the facial musculo-skeletal system. Bones and soft-tissues are of major importance for any facial surgical treatment to guarantee an optimal, functional and aesthetical result. For this reason, surgeons want to pre-operatively plan, simulate and predict the outcome of the surgery allowing for shorter operation times and improved quality. Accurate simulation requires exact segmentation knowledge of the facial tissues. Thus semi-automatic segmentation techniques are required. This thesis proposes semi-automatic methods for segmentation of the facial soft-tissues, such as muscles, skin and fat, from CT and MRI datasets, using a Markov Random Fields (MRF) framework. Due to image noise, artifacts, weak edges and multiple objects of similar appearance in close proximity, it is difficult to segment the object of interest by using image information alone. Segmentations would leak at weak edges into neighboring structures that have a similar intensity profile. To overcome this problem, additional shape knowledge is incorporated in the energy function which can then be minimized using Graph-Cuts (GC). Incremental approaches by incorporating additional prior shape knowledge are presented. The proposed approaches are not object specific and can be applied to segment any class of objects be that anatomical or non-anatomical from medical or non-medical image datasets, whenever a statistical model is present. In the first approach a 3D mean shape template is used as shape prior, which is integrated into the MRF based energy function. Here, the shape knowledge is encoded into the data and the smoothness terms of the energy function that constrains the segmented parts to a reasonable shape. In the second approach, to improve handling of shape variations naturally found in the population, the fixed shape template is replaced by a more robust 3D statistical shape model based on Probabilistic Principal Component Analysis (PPCA). The advantages of using the Probabilistic PCA are that it allows reconstructing the optimal shape and computing the remaining variance of the statistical model from partial information. By using an iterative method, the statistical shape model is then refined using image based cues to get a better fitting of the statistical model to the patient's muscle anatomy. These image cues are based on the segmented muscle, edge information and intensity likelihood of the muscle. Here, a linear shape update mechanism is used to fit the statistical model to the image based cues. In the third approach, the shape refinement step is further improved by using a non-linear shape update mechanism where vertices of the 3D mesh of the statistical model incur the non-linear penalty depending on the remaining variability of the vertex. The non-linear shape update mechanism provides a more accurate shape update and helps in a finer shape fitting of the statistical model to the image based cues in areas where the shape variability is high. Finally, a unified approach is presented to segment the relevant facial muscles and the remaining facial soft-tissues (skin and fat). One soft-tissue layer is removed at a time such as the head and non-head regions followed by the skin. In the next step, bones are removed from the dataset, followed by the separation of the brain and non-brain regions as well as the removal of air cavities. Afterwards, facial fat is segmented using the standard Graph-Cuts approach. After separating the important anatomical structures, finally, a 3D fixed shape template mesh of the facial muscles is used to segment the relevant facial muscles. The proposed methods are tested on the challenging example of segmenting the masseter muscle. The datasets were noisy with almost all possessing mild to severe imaging artifacts such as high-density artifacts caused by e.g. dental fillings and dental implants. Qualitative and quantitative experimental results show that by incorporating prior shape knowledge leaking can be effectively constrained to obtain better segmentation results

Nrg-1 effects on C2C12 differentiation: Towards generating Intrafusal muscle fibres in vitro

Intrafusal fibres are a specialised population in skeletal muscle, found within the muscle spindle. These fibres have a mechano-sensory capacity, they detect and mediate static and dynamic muscle stretch and monitor muscle position, forming a key contribution to proprioception. Impairment of proprioception and associated dysfunction of the muscle spindle is linked with multiple neuromuscular diseases, aging and nerve injuries. To date, there is a paucity of publications focussed on de novo generation and characterisation of intrafusal muscle fibres in vitro and current skeletal muscle models lack integration of the afferent functions of the muscle spindle. It was hypothesised that de novo intrafusal myotubes could be generated and characterised from differentiated C2C12 myoblasts, utilising addition of recombinant Neuregulin 1, an essential molecule for intrafusal fibre development. Intrafusal bag myotubes have a distinctive fusiform shape and were characterised using novel morphological parameters, immunofluorescent microscopy and western blot analysis, directed against an extensive list of putative intrafusal specific markers, as identified in vivo. Nrg-1 supplementation resulted in a 5-fold increase in intrafusal bag myotubes, increased expression of the intrafusal specific transcription factor, Egr3 and significantly altered the expression of myosin heavy chains. Nrg-1 also upregulated proliferation of C2C12s, resulting in increased nuclei per image field of view. Following this, siRNA was employed to knockdown Nrg-1 mediated Egr3 expression and Mitomycin-c was applied to mitigate Nrg-1 mediated proliferation. Results indicate generation of intrafusal bag like morphologies occurs independently of Nrg-1 initiated Egr3 expression and proliferation in vitro. Key assays from the 2D work were replicated in a biomimetic 3D collagen system. Bag fibre morphology and myonuclei clustering were detected and myotubes displayed evidence of increased maturity, however, the expression patterns for intrafusal specific markers mimicked the 2D results. Force outputs following electrical field stimulation of 3D constructs were not indicative of an intrafusal fibre phenotype, casting doubt over the suitability of a monocellular C2C12 model for intrafusal fibres. This research provides the most in-depth characterisation and the first tissue engineering approach toward generating de novo intrafusal skeletal muscle. Future iterations of this model will provide platforms for developmental or disease state studies, pre-clinical screening, or clinical applications, which will likely provide novel therapeutic strategies to enhance patient care

Segmentation of the Oral and Facial Regions from Imaging Modalities with Reduced or No Ionizing Radiation

Ph.DDOCTOR OF PHILOSOPH

Crosstalk between the myotome and muscle stem cells during the development of the skeletal muscles of the back

The deep back (or epaxial) muscles of amniotes derive from the transient myotomes, segmented embryonic muscles that develop from the delamination and differentiation of muscle stem cells (MuSCs) from the overlying dermomyotome. During embryonic development, myogenesis is ensured by the activation of key transcription factors: Myf5, Mrf4, MyoD and Myogenin. The main goal of this thesis was to investigate the role of the myotome in epaxial muscle development. In Chapter 2, a technique of culturing mouse embryo explants was developed, which allowed us to study the in vivo ex utero development of the epaxial myotome and its extracellular matrix (ECM). In Chapter 3, we analysed to what extent the myotome is necessary for later epaxial muscle development using the Myf5nlacZ/nlacZ mouse line, in which the absence of Myf5 and Mrf4 results in the lack of an early myotome. We show that one specific epaxial muscle group (the transversospinalis) is able to differentiate through MyoD, while the other three epaxial muscle groups fail to form. Moreover, we show that due to the lack of myotomal factors, the maintenance of the identity of delaminating dermomyotomal MuSCs fails. In Chapter 4, we described the organisation of laminins, fibronectin and tenascin-C ECMs during myotome development showing that each one of these ECMs potentially has a specific spatial relationship with MuSCs. Finally, Chapter 5 focuses on the role of the myotome in the organisation of these same ECMs and its role in tendon development, using Myf5nlacZ/nlacZ mouse embryos. We show that the myotome is necessary to assemble its own matrices, but these are not required for the development of the transversospinalis muscles. The results of this thesis suggest that the transversospinalis muscles have a distinct developmental mechanism from that of the remaining epaxial muscles and we propose that they are evolutionary more recent.Os músculos profundos das costas (ou epaxiais) dos amniotas derivam dos miótomos transientes, músculos embrionários segmentados que se desenvolvem a partir da delaminação e diferenciação das células estaminais musculares (CEMs) do dermomiótomo sobreposto. Durante o desenvolvimento embrionário, a miogénese é assegurada pela ativação de fatores de transcrição-chave miogénicos: Myf5, Mrf4, MyoD e Miogenina. Esta tese tem como principal objetivo perceber o papel do miótomo no desenvolvimento dos músculos epaxiais. No capítulo 2, descrevemos uma técnica de cultura de explantes de embrião de ratinho que nos permitiu estudar o desenvolvimento in vivo ex utero do miótomo epaxial e da sua matriz extracelular (MEC). No capítulo 3, analisamos até que ponto o miótomo é necessário para o desenvolvimento muscular epaxial que ocorre em fases mais tardias, recorrendo ao uso de embriões de ratinho Myf5nlacZ/nlacZ, cuja incapacidade de expressar Myf5 e Mrf4, leva a que não formem o miótomo embrionário. Aqui, demonstramos que um grupo muscular epaxial específico, nomeadamente o músculo transversospinalis é capaz de se diferenciar através da ativação de MyoD, ao passo que os restantes grupos musculares epaxiais não se formam. Mais ainda, demonstramos que a manutenção da identidade das CEMs do dermomiótomo que delaminam deste é comprometida devido à ausência de fatores parácrinos do miótomo. No capítulo 4, descrevemos a organização das matrizes de laminina, fibronectina e tenascina-C durante o desenvolvimento do miótomo, evidenciando que cada uma destas MECs tem uma potencial relação espacial com as CEMs. Por fim, o capítulo 5 atenta para a contribuição do miótomo na organização destas mesmas MECs e para desenvolvimento dos tendões recorrendo novamente aos embriões de ratinho Myf5nlacZ/nlacZ. Aqui, evidenciamos que o miótomo é apenas necessário para a montagem das suas próprias MECs, não sendo requerido para o desenvolvimento do músculo transversospinalis. Os resultados desta tese sugerem que o músculo transversospinalis tenha um mecanismo de desenvolvimento distinto dos restantes músculos epaxiais, e como tal, propomos que este músculo em particular seja evolutivamente mais recente

Mise en place de l'identité des muscles au cours de la spécification des myoblastes chez la drosophile

La formation des muscles squelettiques au cours de l'embryogenèse de la drosophile est un modèle d'étude du contrôle génétique de la différentiation cellulaire. La formation de chaque muscle comprend quatre étapes successives: spécification d'un groupe promusculaire, sélection d'un progéniteur (PC) à partir de ce groupe, division asymétrique de ce progéniteur pour donner des cellules fondatrices de muscles (FC) ; fusion de chaque FC avec des myoblastes compétents (FCM), suivie de la différenciation musculaire. Chaque muscle squelettique est composé d'une fibre. Chaque muscle présente des propriétés spécifiques de taille, forme, position, attachement, et patron d'innervation. Ces propriétés sont groupées sous le terme d'identité musculaire. Cette identité est conférée par l'expression dans chaque PC/FC d'une combinatoire de Facteurs de Transcription identitaires (FTi). Notre laboratoire étudie ce processus, en utilisant comme point d'entrée l'expression et les rôles du FTi Collier (Col) au cours du développement d'un muscle dorso-latéral, le muscle DA3 (Dorsal Acute 3). Au cours de la première partie de ma thèse, j'ai étudié la régulation transcriptionnelle de col durant les phases de spécification des groupes promusculaires et de sélection du PC à l'origine du muscle DA3. Partant de prédictions bioinformatiques j'ai caractérisé le module cis régulateur (CRM) de col actif durant ces phases (CRM précoce). Un CRM " tardif ", actif du stade progéniteur à la complétion de la formation du muscle DA3, avait été préalablement caractérisé dans l'équipe. Afin de déterminer plus précisément les fenêtres temporelles d'activité des deux CRM mésodermiques de col, j'ai mis au point un nouveau gène rapporteur comportant un intron permettant de détecter les transcrits primaires. Ceci m'a permis de montrer que les CRM précoce et tardif reproduisent ensemble l'expression endogène de col. La caractérisation du CRM précoce de col m'a aussi permis de suivre le destin des FCM du groupe promusculaire Col dans les embryons tardifs et de montrer que ces FCM contribuent uniquement à des muscles dorsaux-latéraux. Au cours de la deuxième partie de ma thèse, j'ai caractérisé le rôle, inconnu jusqu'alors, du FT à domaine LIM-Homeodomaine Tailup (Tup)/Islet1 dans la myogenèse. J'ai d'abord montré que Tup est spécifiquement exprimé dans les 4 muscles les plus dorsaux. L'analyse de mutants m'a permis de montrer qu'en absence de Tup, le muscle dorsal DA2 exprime Col et est transformé en muscle dorso-latéral de type DA3. J'ai ensuite montré que le PC du DA2 est à l'origine de la FC DA2 et d'un précurseur musculaire adulte (AMP). Ce PC est sélectionné à partir du groupe promusculaire Col quand les cellules de ce groupe expriment encore le FT à homéodomaine Tinman/NKx2.5. Tin active tup dans le PC DA2. Tup, en retour, réprime col et cette répression permet de distinguer les identités musculaires DA2 et DA3. En conclusion, mes travaux de thèse m'ont permis de proposer un nouveau modèle permettant de relier le processus de spécification des progéniteurs au contrôle temporel et spatial de l'expression des FTi. Une vision dynamique de ce processus de spécification permet de mieux comprendre le programme identitaire propre à chaque muscle. L'analyse des interactions entre Tin, Tup, et Col au cours de la formation des muscles dorsaux révèle de nouveaux parallèles avec les interactions entre Nkx2.5, Islet, EBF au cours de la formation des muscles pharyngaux chez les chordés.The somatic musculature of the Drosophila embryo is a classical model to study the regulatory processes that generate cellular diversity. Muscle formation is a multistep process: the first step is the specification, within the mesoderm, of a group of competent cells, called promuscular cluster. The second step is the selection of a progenitor cell (PC) from this cluster. Asymmetric division of each PC then generates muscle founder cells (FC). Finally, each FC undergoes a fusion process with fusion competent myoblasts (FCM) to generate a muscle fiber. Each muscle is formed of a single multinucleate fiber. Each Drosophila muscle has a specific identity, as it can be distinguished by its position, shape, orientation, attachment, and innervation pattern. Muscle identity reflects the expression by each PC/FC of a specific combination of identity Transcription Factors (iTF). In the laboratory, we study the control of muscle identity, using as entry point, the expression and requirement of the iTF Collier (Col) during development of a dorso-lateral (DA3) muscle. I started my PhD by characterizing col transcriptional regulation during early steps of DA3 muscle formation. Starting from computational predictions, I identified an early col cis regulatory module (Early CRM) responsible for col activation in a promuscular cluster. A late col CRM, active from the PC stage, had previously been characterized in the laboratory. To determine with more precision the temporal windows of activity of each of these CRM, I designed a novel intron-containing reporter gene in order to detect primary transcripts. This allowed me to show that the late and the early CRMs together reproduce precisely the endogenous col expression pattern. Characterization of the early mesodermal col CRM also allowed to do lineage experiments and determine the fate of FCMs that transiently express Col at the promuscular stage. I found that these myoblasts contribute mostly to dorso-lateral muscles. During the second part of my thesis, I described a new role of the LIM-homeodomain TF Tailup/Islet1 (Tup) in specifying dorsal muscles. I first showed that Tup is specifically expressed in the four dorsal muscles. In tup null mutants, on one hand, the dorsal musculature is severely disorganized and, on the other hand, the dorsal DA2 muscle ectopically expresses Col and is transformed into a dorso-lateral DA3-like muscle. I showed that the DA2 PC is singled out from the Col promuscular cluster when cells of this cluster still express (transitorily) the homeodomain TF Tinman/Nkx2.5 (Tin). The DA2 PC gives rise to the DA2 FC and a (dorso-lateral) adult muscle precursor (AMP). tup activation by Tin in the DA2 PC is required to repress col and establish a DA2 instead of DA3 identity. In conclusion, my work allowed to propose a model which connects a temporal sequence of transcriptional regulation of iTFs to the specification of muscle PC identity and final muscle pattern. It provides a novel, dynamic view of how muscle identity is specified. These findings also provide novel parallels with the specification of pharyngeal muscles in vertebrates

Oncologic Thermoradiotherapy: Need for Evidence, Harmonisation, and Innovation

The road of acceptance of oncologic thermotherapy/hyperthermia as a synergistic modality in combination with standard oncologic therapies is still bumpy. This is partially due to the lack of level I evidence from international, multicentric, randomized clinical trials including large patient numbers and a long term follow-up. Therefore we need more level I EVIDENCE from clinical trials, we need HARMONISATION and global acceptance for existing technologies and a common language understood by all stakeholders and we need INNOVATION in the fields of biology, clinics and technology to move thermotherapy/hyperthermia forward. This is the main focus of this reprint. In this reprintyou find carefully selected and peer-reviewed contributions from Africa, America, Asia, and Europe. The published papers from leading scientists from all over the world covering a broad range of timely research topics might also help to strengthen thermotherapy on a global level

A shape prior-based MRF model for 3D masseter muscle segmentation

Medical image segmentation is generally an ill-posed problem that can only be solved by incorporating prior knowledge. The ambiguities arise due to the presence of noise, weak edges, imaging artifacts, inhomogeneous interior and adjacent anatomical structures having similar intensity profile as the target structure. In this paper we propose a novel approach to segment the masseter muscle using the graph-cut incorporating additional 3D shape priors in CT datasets, which is robust to noise; artifacts; and shape deformations. The main contribution of this paper is in translating the 3D shape knowledge into both unary and pairwise potentials of the Markov Random Field (MRF). The segmentation task is casted as a Maximum-A-Posteriori (MAP) estimation of the MRF. Graph-cut is then used to obtain the global minimum which results in the segmentation of the masseter muscle. The method is tested on 21 CT datasets of the masseter muscle, which are noisy with almost all possessing mild to severe imaging artifacts such as high-density artifacts caused by e.g. the very common dental fillings and dental implants. We show that the proposed technique produces clinically acceptable results to the challenging problem of muscle segmentation, and further provide a quantitative and qualitative comparison with other methods. We statistically show that adding additional shape prior into both unary and pairwise potentials can increase the robustness of the proposed method in noisy datasets

Facial soft tissue segmentation

The importance of the face for socio-ecological interaction is the cause for a high demand on any surgical intervention on the facial musculo-skeletal system. Bones and soft-tissues are of major importance for any facial surgical treatment to guarantee an optimal, functional and aesthetical result. For this reason, surgeons want to pre-operatively plan, simulate and predict the outcome of the surgery allowing for shorter operation times and improved quality. Accurate simulation requires exact segmentation knowledge of the facial tissues. Thus semi-automatic segmentation techniques are required. This thesis proposes semi-automatic methods for segmentation of the facial soft-tissues, such as muscles, skin and fat, from CT and MRI datasets, using a Markov Random Fields (MRF) framework. Due to image noise, artifacts, weak edges and multiple objects of similar appearance in close proximity, it is difficult to segment the object of interest by using image information alone. Segmentations would leak at weak edges into neighboring structures that have a similar intensity profile. To overcome this problem, additional shape knowledge is incorporated in the energy function which can then be minimized using Graph-Cuts (GC). Incremental approaches by incorporating additional prior shape knowledge are presented. The proposed approaches are not object specific and can be applied to segment any class of objects be that anatomical or non-anatomical from medical or non-medical image datasets, whenever a statistical model is present. In the first approach a 3D mean shape template is used as shape prior, which is integrated into the MRF based energy function. Here, the shape knowledge is encoded into the data and the smoothness terms of the energy function that constrains the segmented parts to a reasonable shape. In the second approach, to improve handling of shape variations naturally found in the population, the fixed shape template is replaced by a more robust 3D statistical shape model based on Probabilistic Principal Component Analysis (PPCA). The advantages of using the Probabilistic PCA are that it allows reconstructing the optimal shape and computing the remaining variance of the statistical model from partial information. By using an iterative method, the statistical shape model is then refined using image based cues to get a better fitting of the statistical model to the patient's muscle anatomy. These image cues are based on the segmented muscle, edge information and intensity likelihood of the muscle. Here, a linear shape update mechanism is used to fit the statistical model to the image based cues. In the third approach, the shape refinement step is further improved by using a non-linear shape update mechanism where vertices of the 3D mesh of the statistical model incur the non-linear penalty depending on the remaining variability of the vertex. The non-linear shape update mechanism provides a more accurate shape update and helps in a finer shape fitting of the statistical model to the image based cues in areas where the shape variability is high. Finally, a unified approach is presented to segment the relevant facial muscles and the remaining facial soft-tissues (skin and fat). One soft-tissue layer is removed at a time such as the head and non-head regions followed by the skin. In the next step, bones are removed from the dataset, followed by the separation of the brain and non-brain regions as well as the removal of air cavities. Afterwards, facial fat is segmented using the standard Graph-Cuts approach. After separating the important anatomical structures, finally, a 3D fixed shape template mesh of the facial muscles is used to segment the relevant facial muscles. The proposed methods are tested on the challenging example of segmenting the masseter muscle. The datasets were noisy with almost all possessing mild to severe imaging artifacts such as high-density artifacts caused by e.g. dental fillings and dental implants. Qualitative and quantitative experimental results show that by incorporating prior shape knowledge leaking can be effectively constrained to obtain better segmentation results