Finite element model set-up of colorectal tissue for analyzing surgical scenarios

Finite Element Analysis (FEA) has gained an extensive application in the medical field, such as soft tissues simulations. In particular, colorectal simulations can be used to understand the interaction with the surrounding tissues, or with instruments used in surgical procedures. Although several works have been introduced considering small displacements, as a result of the forces exerted on adjacent tissues, FEA applied to colorectal surgical scenarios is still a challenge. Therefore, this work aims to provide a sensitivity analysis on three geometric models, taking in mind different bioengineering tasks. In this way, a set of simulations has been performed using three mechanical models named Linear Elastic, Hyper-Elastic with a Mooney-Rivlin material model, and Hyper-Elastic with a YEOH material model

Outlier identification in radiation therapy knowledge-based planning: A study of pelvic cases.

PURPOSE: The purpose of this study was to apply statistical metrics to identify outliers and to investigate the impact of outliers on knowledge-based planning in radiation therapy of pelvic cases. We also aimed to develop a systematic workflow for identifying and analyzing geometric and dosimetric outliers. METHODS: Four groups (G1-G4) of pelvic plans were sampled in this study. These include the following three groups of clinical IMRT cases: G1 (37 prostate cases), G2 (37 prostate plus lymph node cases) and G3 (37 prostate bed cases). Cases in G4 were planned in accordance with dynamic-arc radiation therapy procedure and include 10 prostate cases in addition to those from G1. The workflow was separated into two parts: 1. identifying geometric outliers, assessing outlier impact, and outlier cleaning; 2. identifying dosimetric outliers, assessing outlier impact, and outlier cleaning. G2 and G3 were used to analyze the effects of geometric outliers (first experiment outlined below) while G1 and G4 were used to analyze the effects of dosimetric outliers (second experiment outlined below). A baseline model was trained by regarding all G2 cases as inliers. G3 cases were then individually added to the baseline model as geometric outliers. The impact on the model was assessed by comparing leverages of inliers (G2) and outliers (G3). A receiver-operating-characteristic (ROC) analysis was performed to determine the optimal threshold. The experiment was repeated by training the baseline model with all G3 cases as inliers and perturbing the model with G2 cases as outliers. A separate baseline model was trained with 32 G1 cases. Each G4 case (dosimetric outlier) was subsequently added to perturb the model. Predictions of dose-volume histograms (DVHs) were made using these perturbed models for the remaining 5 G1 cases. A Weighted Sum of Absolute Residuals (WSAR) was used to evaluate the impact of the dosimetric outliers. RESULTS: The leverage of inliers and outliers was significantly different. The Area-Under-Curve (AUC) for differentiating G2 (outliers) from G3 (inliers) was 0.98 (threshold: 0.27) for the bladder and 0.81 (threshold: 0.11) for the rectum. For differentiating G3 (outlier) from G2 (inlier), the AUC (threshold) was 0.86 (0.11) for the bladder and 0.71 (0.11) for the rectum. Significant increase in WSAR was observed in the model with 3 dosimetric outliers for the bladder (P \u3c 0.005 with Bonferroni correction), and in the model with only 1 dosimetric outlier for the rectum (P \u3c 0.005). CONCLUSIONS: We established a systematic workflow for identifying and analyzing geometric and dosimetric outliers, and investigated statistical metrics for outlier detection. Results validated the necessity for outlier detection and clean-up to enhance model quality in clinical practice

Symbolic modeling of structural relationships in the Foundational Model of Anatomy

The need for a sharable resource that can provide deep anatomical knowledge and support inference for biomedical applications has recently been the driving force in the creation of biomedical ontologies. Previous attempts at the symbolic representation of anatomical relationships necessary for such ontologies have been largely limited to general partonomy and class subsumption. We propose an ontology of anatomical relationships beyond class assignments and generic part-whole relations and illustrate the inheritance of structural attributes in the Digital Anatomist Foundational Model of Anatomy. Our purpose is to generate a symbolic model that accommodates all structural relationships and physical properties required to comprehensively and explicitly describe the physical organization of the human body

A review of algorithms for medical image segmentation and their applications to the female pelvic cavity

This paper aims to make a review on the current segmentation algorithms used for medical images. Algorithms are classified according to their principal methodologies, namely the ones based on thresholds, the ones based on clustering techniques and the ones based on deformable models. The last type is focused on due to the intensive investigations into the deformable models that have been done in the last few decades. Typical algorithms of each type are discussed and the main ideas, application fields, advantages and disadvantages of each type are summarised. Experiments that apply these algorithms to segment the organs and tissues of the female pelvic cavity are presented to further illustrate their distinct characteristics. In the end, the main guidelines that should be considered for designing the segmentation algorithms of the pelvic cavity are proposed

Dosimetric comparison study between intensity modulated radiation therapy and three-dimensional conformal proton therapy for pelvic bone marrow sparing in the treatment of cervical cancer.

The objective was to compare intensity-modulated radiation therapy (IMRT) with 3D conformal proton therapy (3DCPT) in the treatment of cervical cancer. In particular, each technique's ability to spare pelvic bone marrow (PBM) was of primary interest in this study. A total of six cervical cancer patients (3 postoperative and 3 intact) were planned and analyzed. All plans had uniform 1.0 cm CTV-PTV margin and satisfied the 95% PTV with 100% isodose (prescription dose = 45 Gy) coverage. Dose-volume histograms (DVH) were analyzed for comparison. The overall PTV and PBM volumes were 1035.9 ± 192.2 cc and 1151.4 ± 198.3 cc, respectively. In terms of PTV dose conformity index (DCI) and dose homogeneity index (DHI), 3DCPT was slightly superior to IMRT with 1.00 ± 0.001, 1.01 ± 0.02, and 1.10 ± 0.02, 1.13 ± 0.01, respectively. In addition, 3DCPT demonstrated superiority in reducing lower doses (i.e., V30 or less) to PBM, small bowel and bladder. Particularly in PBM, average V10 and V20 reductions of 10.8% and 7.4% (p = 0.001 and 0.04), respectively, were observed. However, in the higher dose range, IMRT provided better sparing (> V30). For example, in small bowel and PBM, average reductions in V45 of 4.9% and 10.0% (p = 0.048 and 0.008), respectively, were observed. Due to its physical characteristics such as low entrance dose, spread-out Bragg peak and finite particle range of protons, 3DCPT illustrated superior target coverage uniformity and sparing of the lower doses in PBM and other organs. Further studies are, however, needed to fully exploit the benefits of protons for general use in cervical cancer

Towards a better understanding of pelvic system disorders using numerical simulation

International audienceGenital prolapse is a pathologic hyper-mobility of the organs that forms the pelvic system. Although this is common condition, the pathophysiology of this disorder is not well known. In order to improve the understanding of its origins, we recreate - virtually - this biomechanical pathology using numerical simulation. The approach builds on a finite element model with parameters measured on several fresh cadavers. The meshes are created from a MRI of a healthy woman and the simulation includes the mechanical interactions between organs (contacts, ligaments, adhesion...). The model is validated through comparison of functional mobilities of the pelvic system observed on a dynamic MRI. We then propose to modify, step by step, the model and its parameters to produce a pathologic situation and have a better understanding of the process. It is not a formal proof but the numerical experiments reinforce the clinical hypothesis on the multifactorial origins of the pathology

Image processing and analysis : applications and trends

The computational analysis of images is challenging as it usually involves tasks such as segmentation, extraction of representative features, matching, alignment, tracking, motion analysis, deformation estimation, and 3D reconstruction. To carry out each of these tasks in a fully automatic, efficient and robust manner is generally demanding.The quality of the input images plays a crucial role in the success of any image analysis task. The higher their quality, the easier and simpler the tasks are. Hence, suitable methods of image processing such as noise removal, geometric correction, edges and contrast enhancement or illumination correction are required.Despite the challenges, computational methods of image processing and analysis are suitable for a wide range of applications.In this paper, the methods that we have developed for processing and analyzing objects in images are introduced. Furthermore, their use in applications from medicine and biomechanics to engineering and materials sciences are presented

PTV margin for dose escalated radiation therapy of prostate cancer with daily on-line realignment using internal fiducial markers: Monte Carlo approach and dose population histogram (DPH) analysis.

Using internal fiducial markers and electronic portal imaging (EPID) to realign patients has been shown to significantly reduce positioning uncertainties in prostate radiation treatment. This creates the possibility of decreasing the planning target volume (PTV) margin added on the clinical target volume (CTV), which in turn may allow for dose escalation. We compared the outcome of two plans: 70Gy/35fx, 10 mm PTV margin without patient realignment (Reference Plan) vs. 78Gy/39fx, 5 mm PTV margin with patient realignment (Escalated Plan). Four-field-oblique (gantry angles 35 degrees, 90 degrees, 270 degrees, 176 degrees, 325 degrees) beam arrangement was used. Monte Carlo code was used to simulate the daily organ motion. Dose to each organ was calculated. Tumour control probability (TCP) and the effective dose to critical organ (Deff) were calculated using the biologically normalized dose-volume histograms. By comparing the biological factors, we found that the prescription dose can be escalated to 78Gy/39fx with a 5 mm PTV margin when using internal fiducial markers and EPID. Based on the available dose-response data for intermediate risk prostate patients, this will result in a 20% increase of local control and significantly reduced rectal complications provided that less serial dose-volume behaviour of rectum is proven

Virtual reality training and assessment in laparoscopic rectum surgery

Background: Virtual-reality (VR) based simulation techniques offer an efficient and low cost alternative to conventional surgery training. This article describes a VR training and assessment system in laparoscopic rectum surgery. Methods: To give a realistic visual performance of interaction between membrane tissue and surgery tools, a generalized cylinder based collision detection and a multi-layer mass-spring model are presented. A dynamic assessment model is also designed for hierarchy training evaluation. Results: With this simulator, trainees can operate on the virtual rectum with both visual and haptic sensation feedback simultaneously. The system also offers surgeons instructions in real time when improper manipulation happens. The simulator has been tested and evaluated by ten subjects. Conclusions: This prototype system has been verified by colorectal surgeons through a pilot study. They believe the visual performance and the tactile feedback are realistic. It exhibits the potential to effectively improve the surgical skills of trainee surgeons and significantly shorten their learning curve. © 2014 John Wiley & Sons, Ltd