Hybrid Simulation and Planning Platform for Cryosurgery with Microsoft HoloLens

Cryosurgery is a technique of growing popularity involving tissue ablation under controlled freezing. Technological advancement of devices along with surgical technique improvements have turned cryosurgery from an experimental to an established option for treating several diseases. However, cryosurgery is still limited by inaccurate planning based primarily on 2D visualization of the patient's preoperative images. Several works have been aimed at modelling cryoablation through heat transfer simulations; however, most software applications do not meet some key requirements for clinical routine use, such as high computational speed and user-friendliness. This work aims to develop an intuitive platform for anatomical understanding and pre-operative planning by integrating the information content of radiological images and cryoprobe specifications either in a 3D virtual environment (desktop application) or in a hybrid simulator, which exploits the potential of the 3D printing and augmented reality functionalities of Microsoft HoloLens. The proposed platform was preliminarily validated for the retrospective planning/simulation of two surgical cases. Results suggest that the platform is easy and quick to learn and could be used in clinical practice to improve anatomical understanding, to make surgical planning easier than the traditional method, and to strengthen the memorization of surgical planning

Heat Transfer Model for Cryosurgery

Cryosurgery is a surgical technique which employs extreme freezing to treat diseased or abnormal tissue. Here, a new numerical approach is devised to simulate the heat transfer process in cryosurgery in order to assess the propagation of ice front’s positions and thermal history inside the ice ball. The developed numerical code is validated against the published experimental results. The emphasis is placed on minimizing the computational time so that the devised approach can be used in planning of cryosurgery treatment. The phase change phenomenon is solved using finite volume method on a fixed multiblock structured grid. An enthalpy method in addition to two-dimensional axisymmetric model is used to approximate the process of cryoablation. The model has used constant thermal properties for both the unfrozen region and the frozen region. In this study, we predicted thermal profile of tissue simulating gel during freezing and holding after certain time duration, while considering various dependent parameters. In addition, effect of cryoprobe size on the propagation of ice front positions and thermal history inside the ice ball is studied. And, it is found that ice volume varies almost linearly with time as well as with cryoprobe size

Optimasi Posisi Cryoprobe pada Proses Cryosurgery Menggunakan Metode Bubble Packing

Cryosurgery adalah teknik operasi untuk memusnahkan jaringan kanker menggunakan nitrogen cair bersuhu ekstrim (sangat dingin) dengan menggunakan alat yang bernama cryoprobe. Tujuan dilakukannya cryosurgery adalah untuk memaksimalkan pembekuan di dalam jaringan kanker dan meminimumkan kerusakan pada jaringan sehat. Dalam Tugas Akhir ini dilakukan simulasi pengoptimasian cryoprobe pada proses cryosurgery kanker prostat menggunakan metode bubble packing. Metode bubble packing digunakan untuk mengoptimalkan letak cryoprobe pada proses cryosurgery kanker prostat. Penyebaran panas pada daerah kanker menggunakan metode beda hingga satu dan dua dimensi. Penyebaran panas satu dimensi dilakukan sampai tercapai kondisi steady state. Hasil dari solusi numerik satu dimensi dibandingkan dengan solusi eksak sebagai acuan sehingga didapatkan rata-rata error relatif. Dengan rata-rata error relatif terkecil sebesar 0.0106786%, solusi numerik satu dimensi tersebut dikatakan cukup akurat dan layak diterapkan pada sistem dua dimensi. Dengan menggunakan metode bubble packing pada simulasi dua dimensi didapatkan letak 10 cryoprobe yang optimal dengan penyebaran panas yang lebih cepat dibandingkan dengan 4, 5, 6, 7, 8, dan 9 cryoprobe yaitu selama 93 detik. Kata Kunci: cryosurgery, bubble packing, prostat, metode beda hingg

Effective treatment of solid tumors via Cryosurgery

Ph.DDOCTOR OF PHILOSOPH

Simulasi Bioheat Transfer Untuk Perencanaan Cryosurgery Pada Kanker Paru-paru

ABSTRAK Pada Tugas Akhir ini akan membahas simulasi pemusnahan sel kanker yang terjadi pada organ paru-paru menggunakan proses cryosurgery. Pemusnahan dilakukan dengan cara mengalirkan cairan nitrogen kemudian akan menyebarkan suhu yang sangat dingin. Distribusi suhu dilakukan dengan menggunakan pengembangan skema numerik Godunov dan metode volume hingga. Persamaan temperatur yang digunakan mengaplikasikan perubahan fase yang melibatkan batas bergerak. Persamaan numerik divalidasi dengan solusi eksak, sehingga memberikan hasil yang akurat dan dapat digunakan pada sistem dua dimensi. Pada analisa ini akan lebih detail pada pengembangan simulasi numerik satu dimensi dan dua dimensi untuk simulasi perpindahan panas. Hasil simulasi berupa gambar yang memberikan infomasi profil temperatur dan posisi interface, sehingga dapat terlihat jelas bagaimana proses cryosurgery dapat terjadi. Dengan simulasi ini diharapkan dapat menentukan waktu optimal dari proses cryosurgery itu sendiri, sehingga dapat mengetahui waktu yang dibutuhkan sedemikian hingga memaksimalkan jaringan kanker dan meminimalkan jaringan sehat disekitar akibat dari proses cryosurgery. Sehingga dengan melihat hasil simulasi, dokter dapat meminimalisasi resiko yang diakibatkan pada proses yang berjalan secara nyata. Kata Kunci : cryosurgery, perpindahan panas, metode godunov, metode volume hingga

Modeling Iced Bio-Bandage Design for Skin Burns

Over the years, many designs for biobandage were introduced for different types of burns but in most cases these designs are introduced as a protection means to cover and protect the burned tissue from the bacterial infection not as a treatment means. In this paper a new model for a burns biobandage is introduced not only as a protective means but also as a treatment technique by helping the tissue to rebuild itself as fast as possible. The main objective of this research is to develop a simple cryotherapeutic system to reduce the temperature of the burned tissues to normal temperature of the human body in order to facilitate the tissue healing and regeneration process. A biobandage is proposed to include an iced layer as a cooling source, a cotton layer and a water gel layer for comfort and temperature control, and a plastic layer to seal the ice layer. The optimal combination of these four layers physically work together to reduce inflammation, which in turn makes the heeling or recovery time shorter and reduces pain as a result of decreasing the nerve conductivity. The COMSOL Multiphysics was used to model the cooling process on burned tissue using the proposed iced-biobandage. The calculated temperature profiles along the depth biobandage and burned skin provide a clear vision of the heat flow within each layers. The history of temperature and heat transfer rate at the burned skin surface are monitored for an effective cooling and healing process. A modeling analysis was performed to examine the changes of temperature over a predetermined time and to help in identifying the optimal period for ice cooling process, the analysis shows that the ice layer is effective within a certain period of time and after this period it doesn't add any beneficial effect

NUMERICAL AND EXPERIMENTAL INVESTGIATION OF CRYO-FREEZING WITH LARGE BLOOD VESSELS

Ph.DDOCTOR OF PHILOSOPH

Modélisation de l’ablation radiofréquence pour la planification de la résection de tumeurs abdominales

The outcome of radiofrequency ablation (RFA) of abdominal tumors is challenged by the presence of blood vessels and time-varying thermal conductivity, which make patient-specific planning extremely difficult. By providing predictive tools, biophysical models may help clinicians to plan and guide the procedure for an effective treatment. We introduce a detailed computational model of the biophysical mechanisms involved in RFA of hepatic tumors such as heat diffusion and cellular necrosis. It simulates the extent of ablated tissue based on medical images, from which patient-specific models of the liver, visible vessels and tumors are segmented. In this thesis, a new approach for solving these partial differential equations based on the Lattice Boltzmann Method is introduced. The model is first evaluated against clinical data of patients who underwent RFA of liver tumors. Then, a comprehensive pre-clinical experiment that combines multi-modal, pre- and post-operative anatomical and functional images, as well as the interventional monitoring of the temperature and delivered power is presented. This enables an end-to-end validation framework that considers the most comprehensive data set for model validation. Then, we automatically estimate patient-specific parameters to better predict the ablated tissue. This personalization strategy has been validated on 7 ablations from 3 clinical cases. From the pre-clinical study, we can go further in the personalization by comparing the simulated temperature and delivered power with the actual measurements during the procedure. These contributions have led to promising results, and open new perspectives in RFA guidance and planning.L'ablation par radiofréquence (ARF) de tumeurs abdominales est rendue difficile par l’influence des vaisseaux sanguins et les variations de la conductivité thermique, compliquant la planification spécifique à un patient donné. En fournissant des outils prédictifs, les modèles biophysiques pourraient aider les cliniciens à planifier et guider efficacement la procédure. Nous introduisons un modèle mathématique détaillé des mécanismes impliqués dans l’ARF des tumeurs du foie comme la diffusion de la chaleur et la nécrose cellulaire. Il simule l’étendue de l’ablation à partir d’images médicales, d’après lesquelles des modèles personnalisés du foie, des vaisseaux visibles et des tumeurs sont segmentés. Dans cette thèse, une nouvelle approche pour résoudre ces équations basée sur la méthode de Lattice Boltzmann est introduite. Le modèle est d’abord évalué sur des données de patients qui ont subi une ARF de tumeurs du foie. Ensuite, un protocole expérimental combinant des images multi-modales, anatomiques et fonctionnelles pré- et post-opératoires, ainsi que le suivi de la température et de la puissance délivrée pendant l'intervention est présenté. Il permet une validation totale du modèle qui considère des données les plus complètes possibles. Enfin, nous estimons automatiquement des paramètres personnalisés pour mieux prédire l'étendu de l’ablation. Cette stratégie a été validée sur 7 ablations dans 3 cas cliniques. A partir de l'étude préclinique, la personnalisation est améliorée en comparant les simulations avec les mesures faites durant la procédure. Ces contributions ont abouti à des résultats prometteurs, et ouvrent de nouvelles perspectives pour planifier et guider l’ARF