Evaluation of a new virtual-reality training simulator for hysteroscopy

BACKGROUND: To determine realism and training capacity of HystSim, a new virtual-reality simulator for the training of hysteroscopic interventions. METHODS: Sixty-two gynaecological surgeons with various levels of expertise were interviewed at the 13(th) Practical Course in Gynaecologic Endoscopy in Davos, Switzerland. All participants received a 20-min hands-on training on the simulator and filled out a four-page questionnaire. Twenty-three questions with respect to the realism of the simulation and the training capacity were answered on a seven-point Likert scale along with 11 agree-disagree statements concerning the HystSim training in general. RESULTS: Twenty-six participants had performed more than 50 hysteroscopies ("experts") and 36 equal to or fewer than 50 ("novices"). Four of 60 (6.6%) responding participants judged the overall impression as "7 - absolutely realistic", 40 (66.6%) as "6 - realistic", and 16 (26.6%) as "5 - somewhat realistic". Novices (6.48; 95% confidence interval [CI] 6.28-6.7) rated the overall training capacity significantly higher than experts (6.08; 95% CI 5.85-6.3), however, high-grade acceptance was found in both groups. In response to the statements, 95.2% believe that HystSim allows procedural training of diagnostic and therapeutic hysteroscopy, and 85.5% suggest that HystSim training should be offered to all novices before performing surgery on real patients. CONCLUSION: Face validity has been established for a new hysteroscopic surgery simulator. Potential trainees and trainers assess it to be a realistic and useful tool for the training of hysteroscopy. Further systematic validation studies are needed to clarify how this system can be optimally integrated into the gynaecological curriculum

3D reconstruction for plastic surgery simulation based on statistical shape models

This thesis has been accomplished in Crisalix in collaboration with the Universitat Pompeu Fabra within the program of Doctorats Industrials. Crisalix has the mission of enhancing the communication between professionals of plastic surgery and patients by providing a solution to the most common question during the surgery planning process of ``How will I look after the surgery?''. The solution proposed by Crisalix is based in 3D imaging technology. This technology generates the 3D reconstruction that accurately represents the area of the patient that is going to be operated. This is followed by the possibility of creating multiple simulations of the plastic procedure, which results in the representation of the possible outcomes of the surgery. This thesis presents a framework capable to reconstruct 3D shapes of faces and breasts of plastic surgery patients from 2D images and 3D scans. The 3D reconstruction of an object is a challenging problem with many inherent ambiguities. Statistical model based methods are a powerful approach to overcome some of these ambiguities. We follow the intuition of maximizing the use of available prior information by introducing it into statistical model based methods to enhance their properties. First, we explore Active Shape Models (ASM) which are a well known method to perform 2D shapes alignment. However, it is challenging to maintain prior information (e.g. small set of given landmarks) unchanged once the statistical model constraints are applied. We propose a new weighted regularized projection into the parameter space which allows us to obtain shapes that at the same time fulfill the imposed shape constraints and are plausible according to the statistical model. Second, we extend this methodology to be applied to 3D Morphable Models (3DMM), which are a widespread method to perform 3D reconstruction. However, existing methods present some limitations. Some of them are based in non-linear optimizations computationally expensive that can get stuck in local minima. Another limitation is that not all the methods provide enough resolution to represent accurately the anatomy details needed for this application. Given the medical use of the application, the accuracy and robustness of the method, are important factors to take into consideration. We show how 3DMM initialization and 3DMM fitting can be improved using our weighted regularized projection. Finally, we present a framework capable to reconstruct 3D shapes of plastic surgery patients from two possible inputs: 2D images and 3D scans. Our method is used in different stages of the 3D reconstruction pipeline: shape alignment; 3DMM initialization and 3DMM fitting. The developed methods have been integrated in the production environment of Crisalix, proving their validity.Aquesta tesi ha estat realitzada a Crisalix amb la col·laboració de la Universitat Pompeu Fabra sota el pla de Doctorats Industrials. Crisalix té com a objectiu la millora de la comunicació entre els professionals de la cirurgia plàstica i els pacients, proporcionant una solució a la pregunta que sorgeix més freqüentment durant el procés de planificació d'una operació quirúrgica ``Com em veuré després de la cirurgia?''. La solució proposada per Crisalix està basada en la tecnologia d'imatge 3D. Aquesta tecnologia genera la reconstrucció 3D de la zona del pacient operada, seguit de la possibilitat de crear múltiples simulacions obtenint la representació dels possibles resultats de la cirurgia. Aquesta tesi presenta un sistema capaç de reconstruir cares i pits de pacients de cirurgia plàstica a partir de fotos 2D i escanegis. La reconstrucció en 3D d'un objecte és un problema complicat degut a la presència d'ambigüitats. Els mètodes basats en models estadístics son adequats per mitigar-les. En aquest treball, hem seguit la intuïció de maximitzar l'ús d'informació prèvia, introduint-la al model estadístic per millorar les seves propietats. En primer lloc, explorem els Active Shape Models (ASM) que són un conegut mètode fet servir per alinear contorns d'objectes 2D. No obstant, un cop aplicades les correccions de forma del model estadístic, es difícil de mantenir informació de la que es disposava a priori (per exemple, un petit conjunt de punts donat) inalterada. Proposem una nova projecció ponderada amb un terme de regularització, que permet obtenir formes que compleixen les restriccions de forma imposades i alhora són plausibles en concordança amb el model estadístic. En segon lloc, ampliem la metodologia per aplicar-la als anomenats 3D Morphable Models (3DMM) que són un mètode extensivament utilitzat per fer reconstrucció 3D. No obstant, els mètodes de 3DMM existents presenten algunes limitacions. Alguns estan basats en optimitzacions no lineals, computacionalment costoses i que poden quedar atrapades en mínims locals. Una altra limitació, és que no tots el mètodes proporcionen la resolució adequada per representar amb precisió els detalls de l'anatomia. Donat l'ús mèdic de l'aplicació, la precisió i la robustesa són factors molt importants a tenir en compte. Mostrem com la inicialització i l'ajustament de 3DMM poden ser millorats fent servir la projecció ponderada amb regularització proposada. Finalment, es presenta un sistema capaç de reconstruir models 3D de pacients de cirurgia plàstica a partir de dos possibles tipus de dades: imatges 2D i escaneigs en 3D. El nostre mètode es fa servir en diverses etapes del procés de reconstrucció: alineament de formes en imatge, la inicialització i l'ajustament de 3DMM. Els mètodes desenvolupats han estat integrats a l'entorn de producció de Crisalix provant la seva validesa

Kreiranje zapreminskog 3D modela karlične kosti čoveka u uslovima nepotpunih ulaznih volumetrijskih podataka

Human hip bone represents a very complex morphological structure of irregular shape, resulting from the fusion of three primarily stand-alone bones. So, obtaining an accurate 3D model is a complex process, with the condition that a sufficiently dense point cloud is provided. In the first phase of the research, the hip bone model is obtained in reverse engineering process. The procedure itself is time consuming and requires a dedicated CT scan. So, the method of parametric regions is developed. The method allows obtaining a 3D model, even in cases where the volumetric data are not complete or when obtaining data is only possible from a two-dimensional, 2D scans. Anatomical landmarks (a total of 34) were defined at the bones. These anatomical landmarks are interconnected by parameters. Therefore, 58 parameters were defined, classified in two groups: parameters whose values are measured (21), and parameters whose values are obtained on the basis of regression equations (37). The points on the curves obtained by cutting the polygonal model with planes that are passing through given parameters are defined. The points at the parts of the polygonal models which describe the edges of the hip bone and the points that belong to certain parts of the bone are also defined. Parts of the surface that are bound with parameters represent the regions. In order to automate the processes three VBA macros are developed. The results were tested at the arbitrarily selected hip bone, using the methodology for creating the prediction model, which allows the creation of complete polygonal model or each region separately. It is also possible to create parts of the region - sub-regions, on the external or internal side of the hip bone or on both of its sides. Neighboring regions may be brought together. Connecting the region with parts of the obtained polygonal surfaces which describe the edges of the hip bone is also enabled

The role of subchondral bone in osteoarthritis

Osteoarthritis (OA) is the most common form of arthritis. Affected individuals commonly suffer with chronic pain, joint dysfunction, and reduced quality of life. OA also confers an immense burden on health services and economies. Current OA therapies are symptomatic and there are no therapies that modify structural progression. The lack of validated, responsive and reliable biomarkers represents a major barrier to the development of structure-modifying therapies. MRI provides tremendous insight into OA structural disease and has highlighted the importance of subchondral bone in OA. The hypothesis underlying this thesis is that novel quantitative imaging biomarkers of subchondral bone will provide valid measures for OA clinical trials. The Osteoarthritis Initiative (OAI) provided a large natural history database of knee OA to enable testing of the validity of these novel biomarkers. A systematic literature review identified independent associations between subchondral bone features with structural progression, pain and total knee replacement in peripheral joint OA. However very few papers examined the association of 3D bone shape with these patient-centred outcomes. A cross-sectional analysis of the OAI established a significant association between 3D bone area and conventional radiographic OA severity scores, establishing construct validity of 3D bone shape. A nested case-control analysis within the OAI determined that 3D bone shape was associated with the outcome of future total knee replacement, establishing predictive validity for 3D bone shape. A regression analysis within the OAI identified that 3D bone shape was associated with current knee symptoms but not incident symptoms, establishing evidence of concurrent but not predictive validity for new symptoms. In summary, 3D bone shape is an important biomarker of OA which has construct and predictive validity in knee OA. This thesis, along with parallel work on reliability and responsiveness provides evidence supporting its suitability for use in clinical trials