Image-based vs. mesh-based statistical appearance models of the human femur: Implications for finite element simulations.

Statistical appearance models have recently been introduced in bone mechanics to investigate bone geometry and mechanical properties in population studies. The establishment of accurate anatomical correspondences is a critical aspect for the construction of reliable models. Depending on the representation of a bone as an image or a mesh, correspondences are detected using image registration or mesh morphing. The objective of this study was to compare image-based and mesh-based statistical appearance models of the femur for finite element (FE) simulations. To this aim, (i) we compared correspondence detection methods on bone surface and in bone volume; (ii) we created an image-based and a mesh-based statistical appearance models from 130 images, which we validated using compactness, representation and generalization, and we analyzed the FE results on 50 recreated bones vs. original bones; (iii) we created 1000 new instances, and we compared the quality of the FE meshes. Results showed that the image-based approach was more accurate in volume correspondence detection and quality of FE meshes, whereas the mesh-based approach was more accurate for surface correspondence detection and model compactness. Based on our results, we recommend the use of image-based statistical appearance models for FE simulations of the femur.

Assessment of patient setup errors in IGRT in combination with a six degrees of freedom couch

PURPOSE The range of patient setup errors in six dimensions detected in clinical routine for cranial as well as for extracranial treatments, were analyzed while performing linear accelerator based stereotactic treatments with frameless patient setup systems. Additionally, the need for re-verification of the patient setup for situations where couch rotations are involved was analyzed for patients treated in the cranial region. METHODS AND MATERIALS A total of 2185 initial (i.e. after pre-positioning the patient with the infrared system but before image guidance) patient setup errors (1705 in the cranial and 480 in the extracranial region) obtained by using ExacTrac (BrainLAB AG, Feldkirchen, Germany) were analyzed. Additionally, the patient setup errors as a function of the couch rotation angle were obtained by analyzing 242 setup errors in the cranial region. Before the couch was rotated, the patient setup error was corrected at couch rotation angle 0° with the aid of image guidance and the six degrees of freedom (6DoF) couch. For both situations attainment rates for two different tolerances (tolerance A: ± 0.5mm, ± 0.5°; tolerance B: ± 1.0 mm, ± 1.0°) were calculated. RESULTS The mean (± one standard deviation) initial patient setup errors for the cranial cases were -0.24 ± 1.21°, -0.23 ± 0.91° and -0.03 ± 1.07° for the pitch, roll and couch rotation axes and 0.10 ± 1.17 mm, 0.10 ± 1.62 mm and 0.11 ± 1.29 mm for the lateral, longitudinal and vertical axes, respectively. Attainment rate (all six axes simultaneously) for tolerance A was 0.6% and 13.1% for tolerance B, respectively. For the extracranial cases the corresponding values were -0.21 ± 0.95°, -0.05 ± 1.08° and -0.14 ± 1.02° for the pitch, roll and couch rotation axes and 0.15 ± 1.77 mm, 0.62 ± 1.94 mm and -0.40 ± 2.15 mm for the lateral, longitudinal and vertical axes. Attainment rate (all six axes simultaneously) for tolerance A was 0.0% and 3.1% for tolerance B, respectively. After initial setup correction and rotation of the couch to treatment position a re-correction has to be performed in 77.4% of all cases to fulfill tolerance A and in 15.6% of all cases to fulfill tolerance B. CONCLUSION The analysis of the data shows that all six axes of a 6DoF couch are used extensively for patient setup in clinical routine. In order to fulfill high patient setup accuracies (e.g. for stereotactic treatments), a 6DoF couch is recommended. Moreover, re-verification of the patient setup after rotating the couch is required in clinical routine.

Automatic estimation of noise parameters in Fourier-domain optical coherence tomography cross sectional images using statistical information

We present an application and sample independent method for the automatic discrimination of noise and signal in optical coherence tomography Bscans. The proposed algorithm models the observed noise probabilistically and allows for a dynamic determination of image noise parameters and the choice of appropriate image rendering parameters. This overcomes the observer variability and the need for a priori information about the content of sample images, both of which are challenging to estimate systematically with current systems. As such, our approach has the advantage of automatically determining crucial parameters for evaluating rendered image quality in a systematic and task independent way. We tested our algorithm on data from four different biological and nonbiological samples (index finger, lemon slices, sticky tape, and detector cards) acquired with three different experimental spectral domain optical coherence tomography (OCT) measurement systems including a swept source OCT. The results are compared to parameters determined manually by four experienced OCT users. Overall, our algorithm works reliably regardless of which system and sample are used and estimates noise parameters in all cases within the confidence interval of those found by observers.

Image-Guided Orthopaedic Surgery

Image-guided surgery systems are increasingly being used during orthopaedic interventions. The aim of this chapter is to present the basic elements of these image-guided orthopaedic surgery (IGOS) devices and to review examples of preoperative or intra-operative imaging modalities, of trackers for navigation systems, of different surgical robots, and of methods for registration as well as referencing. IGOS modules that have been realised for different surgical procedures will be presented.

A Novel Ultrasound-Based Registration for Image-Guided Laparoscopic Liver Ablation.

BACKGROUND Patient-to-image registration is a core process of image-guided surgery (IGS) systems. We present a novel registration approach for application in laparoscopic liver surgery, which reconstructs in real time an intraoperative volume of the underlying intrahepatic vessels through an ultrasound (US) sweep process. METHODS An existing IGS system for an open liver procedure was adapted, with suitable instrument tracking for laparoscopic equipment. Registration accuracy was evaluated on a realistic phantom by computing the target registration error (TRE) for 5 intrahepatic tumors. The registration work flow was evaluated by computing the time required for performing the registration. Additionally, a scheme for intraoperative accuracy assessment by visual overlay of the US image with preoperative image data was evaluated. RESULTS The proposed registration method achieved an average TRE of 7.2 mm in the left lobe and 9.7 mm in the right lobe. The average time required for performing the registration was 12 minutes. A positive correlation was found between the intraoperative accuracy assessment and the obtained TREs. CONCLUSIONS The registration accuracy of the proposed method is adequate for laparoscopic intrahepatic tumor targeting. The presented approach is feasible and fast and may, therefore, not be disruptive to the current surgical work flow.

Carbohydrate Estimation by a Mobile Phone-Based System Versus Self-Estimations of Individuals With Type 1 Diabetes Mellitus: A Comparative Study

Background: Diabetes mellitus is spreading throughout the world and diabetic individuals have been shown to often assess their food intake inaccurately; therefore, it is a matter of urgency to develop automated diet assessment tools. The recent availability of mobile phones with enhanced capabilities, together with the advances in computer vision, have permitted the development of image analysis apps for the automated assessment of meals. GoCARB is a mobile phone-based system designed to support individuals with type 1 diabetes during daily carbohydrate estimation. In a typical scenario, the user places a reference card next to the dish and acquires two images using a mobile phone. A series of computer vision modules detect the plate and automatically segment and recognize the different food items, while their 3D shape is reconstructed. Finally, the carbohydrate content is calculated by combining the volume of each food item with the nutritional information provided by the USDA Nutrient Database for Standard Reference. Objective: The main objective of this study is to assess the accuracy of the GoCARB prototype when used by individuals with type 1 diabetes and to compare it to their own performance in carbohydrate counting. In addition, the user experience and usability of the system is evaluated by questionnaires. Methods: The study was conducted at the Bern University Hospital, “Inselspital” (Bern, Switzerland) and involved 19 adult volunteers with type 1 diabetes, each participating once. Each study day, a total of six meals of broad diversity were taken from the hospital’s restaurant and presented to the participants. The food items were weighed on a standard balance and the true amount of carbohydrate was calculated from the USDA nutrient database. Participants were asked to count the carbohydrate content of each meal independently and then by using GoCARB. At the end of each session, a questionnaire was completed to assess the user’s experience with GoCARB. Results: The mean absolute error was 27.89 (SD 38.20) grams of carbohydrate for the estimation of participants, whereas the corresponding value for the GoCARB system was 12.28 (SD 9.56) grams of carbohydrate, which was a significantly better performance ( P=.001). In 75.4% (86/114) of the meals, the GoCARB automatic segmentation was successful and 85.1% (291/342) of individual food items were successfully recognized. Most participants found GoCARB easy to use. Conclusions: This study indicates that the system is able to estimate, on average, the carbohydrate content of meals with higher accuracy than individuals with type 1 diabetes can. The participants thought the app was useful and easy to use. GoCARB seems to be a well-accepted supportive mHealth tool for the assessment of served-on-a-plate meals.

Intraoperative image-guided navigation system: development and applicability in 65 patients undergoing liver surgery

Background Image-guided systems have recently been introduced for their application in liver surgery.We aimed to identify and propose suitable indications for image-guided navigation systems in the domain of open oncologic liver surgery and,more specifically, in the setting of liver resection with and without microwave ablation. Method Retrospective analysis was conducted in patients undergoing liver resection with and without microwave ablation using an intraoperative image-guided stereotactic system during three stages of technological development (accuracy: 8.4 ± 4.4 mm in phase I and 8.4 ± 6.5 mm in phase II versus 4.5 ± 3.6 mm in phase III). It was evaluated, in which indications image-guided surgery was used according to the different stages of technical development. Results Between 2009 and 2013, 65 patients underwent image-guided surgical treatment, resection alone (n=38), ablation alone (n =11), or a combination thereof (n =16). With increasing accuracy of the system, image guidance was progressively used for atypical resections and combined microwave ablation and resection instead of formal liver resection (p<0.0001). Conclusion Clinical application of image guidance is feasible, while its efficacy is subject to accuracy. The concept of image guidance has been shown to be increasingly efficient for selected indications in liver surgery. While accuracy of available technology is increasing pertaining to technological advancements, more and more previously untreatable scenarios such as multiple small, bilobar lesions and so-called vanishing lesions come within reach.

Ablation of ischemic ventricular tachycardia: evidence, techniques, results, and future directions

PURPOSE OF REVIEW This article summarizes current understanding of the arrhythmia substrate and effect of catheter ablation for infarct-related ventricular tachycardia, focusing on recent findings. RECENT FINDINGS Clinical studies support the use of catheter ablation earlier in the course of ischemic disease with moderate success in reducing arrhythmia recurrence and shocks from implantable defibrillators, although mortality remains unchanged. Ablation can be lifesaving for patients presenting with electrical storm. Advanced mapping systems with image integration facilitate identification of potential substrate, and several different approaches to manage hemodynamically unstable ventricular tachycardia have emerged. Novel ablation techniques that allow deeper lesion formation are in development. SUMMARY Catheter ablation is an important therapeutic option for preventing or reducing episodes of ventricular tachycardia in patients with ischemic cardiomyopathy. Present technologies allow successful ablation in the majority of patients, even when the arrhythmia is hemodynamically unstable. Failure of the procedure is often because of anatomic challenges that will hopefully be addressed with technological progress.