Quantification of Manipulation Forces Needed for Robot-Assisted Reduction of the Ankle Syndesmosis: An Initial Cadaveric Study

PURPOSE: Manual surgical manipulation of the tibia and fibula is necessary to properly align and reduce the space in ankle fractures involving sprain of the distal tibiofibular syndesmosis. However, manual reduction is highly variable and can result in malreduction in about half of the cases. Therefore, we are developing an image-guided robotic assistant to improve reduction accuracy. The purpose of this study is to quantify the forces associated with reduction of the ankle syndesmosis to define the requirements for our robot design. METHODS: Using a cadaveric specimen, we designed a fixture jig to fix the tibia securely on the operating table. We also designed a custom fibula grasping plate to which a force-torque measuring device is attached. The surgeon manually reduced the fibula utilizing this construct while translational and rotational forces along with displacement were being measured. This was first performed on an intact ankle without ligament injury and after the syndesmosis ligaments were cut. RESULTS: Six manipulation techniques were performed on the three principal directions of reduction at the cadaveric ankle. The results demonstrated the maximum force applied to the lateral direction to be 96.0 N with maximum displacement of 8.5 mm, applied to the anterior-posterior direction to be 71.6 N with maximum displacement of 10.7 mm, and the maximum torque applied to external-internal rotation to be 2.5 Nm with maximum rotation of 24.6°. CONCLUSIONS: The specific forces needed to perform the distal tibiofibular syndesmosis manipulation are not well understood. This study quantified these manipulation forces needed along with their displacement for accurate reduction of ankle syndesmosis. This is a necessary first step to help us define the design requirements of our robotic assistance from the aspects of forces and displacements

Oppositional defiant disorder/conduct disorder co-occurrence increases the risk of Internet addiction in adolescents with attention-deficit hyperactivity disorder

Objectives The aims of this cross-sectional study were to assess the prevalence of Internet addiction (IA) in a clinical sample of adolescents with attention-deficit hyperactivity disorder (ADHD) and to detect the moderating effects of co-occurring oppositional defiant disorder/conduct disorder (ODD/CD) on the association between ADHD and IA. Methods The study group comprised 119 adolescent subjects who were consecutively referred to our outpatient clinic with a diagnosis of ADHD. The Turgay DSM-IV-Based Child and Adolescent Disruptive Behavioral Disorders Screening and Rating Scale (T-DSM-IV-S) was completed by parents, and subjects were asked to complete the Internet Addiction Scale (IAS). Results The IAS results indicated that 63.9% of the participants (n = 76) fell into the IA group. Degree of IA was correlated with hyperactivity/impulsivity symptoms but not with inattention symptoms. As compared to the ADHD-only group (without comorbid ODD/CD), ADHD + ODD/CD subjects returned significantly higher scores on the IAS. Conclusions As adolescents with ADHD are at high risk of developing IA, early IA detection and intervention is of great importance for this group. In addition, adolescents with ADHD + ODD/CD may be more vulnerable to IA than those in the ADHD-only group and may need to be more carefully assessed for IA

Imaging and registration for surgical guidance: systems and algorithms for intraoperative C-arm 2D and 3D imaging

Advances in medical imaging, surgical navigation, and computing power over the past few decades have enabled the image guidance techniques that define the current state of the art in image-guided surgery. While modern navigation systems are an indispensable part of today’s surgical arsenal, they carry costs and workflow bottlenecks that have limited broad utilization. Originally conceptualized in the context of navigation relative to the preoperative data, among the most critical shortcomings is the assumption that the preoperative images accurately reflect the anatomy of the patient at the time of surgery. Intraoperative imaging offers the means to visualize such anatomical changes, as well as unexpected complications, and presents and important step to advancing the utility of image guidance across a broad spectrum of complex surgeries. Recognizing the potential of mobile C-arms capable of high-quality radiography, fluoroscopy, and cone-beam CT, this dissertation concerns the development of systems and algorithms to integrate C-arm imaging with other guidance technologies and present new methods to tackle current challenges in image guidance. The material includes work encompassing: (i) an extensible software platform for integrating navigational tools with cone-beam CT, including fast registration algorithms using parallel computation on general purpose GPU; (ii) a 3D-2D registration approach that leverages knowledge of interventional devices for surgical guidance and quality assurance; and (iii) a hybrid 3D deformable registration approach using image intensity and feature characteristics to resolve gross deformation in cone-beam CT guidance of thoracic surgery. Specific clinical challenges are presented, and the proposed solutions are subjected to rigorous quantitative evaluation to meet clinical requirements such as accuracy, precision, robustness, and computational efficiency (time constraints). The thesis realizes an image guidance framework that leverages the intraoperative imaging capabilities provided by modern C-arms and aims to show that their use, combined with advanced image registration algorithms, can overcome many of the limitations of conventional surgical navigation, streamline workflow, and enable novel applications in image-guided surgery

Imaging and registration for surgical guidance: systems and algorithms for intraoperative C-arm 2D and 3D imaging

Advances in medical imaging, surgical navigation, and computing power over the past few decades have enabled the image guidance techniques that define the current state of the art in image-guided surgery. While modern navigation systems are an indispensable part of today’s surgical arsenal, they carry costs and workflow bottlenecks that have limited broad utilization. Originally conceptualized in the context of navigation relative to the preoperative data, among the most critical shortcomings is the assumption that the preoperative images accurately reflect the anatomy of the patient at the time of surgery. Intraoperative imaging offers the means to visualize such anatomical changes, as well as unexpected complications, and presents and important step to advancing the utility of image guidance across a broad spectrum of complex surgeries. Recognizing the potential of mobile C-arms capable of high-quality radiography, fluoroscopy, and cone-beam CT, this dissertation concerns the development of systems and algorithms to integrate C-arm imaging with other guidance technologies and present new methods to tackle current challenges in image guidance. The material includes work encompassing: (i) an extensible software platform for integrating navigational tools with cone-beam CT, including fast registration algorithms using parallel computation on general purpose GPU; (ii) a 3D-2D registration approach that leverages knowledge of interventional devices for surgical guidance and quality assurance; and (iii) a hybrid 3D deformable registration approach using image intensity and feature characteristics to resolve gross deformation in cone-beam CT guidance of thoracic surgery. Specific clinical challenges are presented, and the proposed solutions are subjected to rigorous quantitative evaluation to meet clinical requirements such as accuracy, precision, robustness, and computational efficiency (time constraints). The thesis realizes an image guidance framework that leverages the intraoperative imaging capabilities provided by modern C-arms and aims to show that their use, combined with advanced image registration algorithms, can overcome many of the limitations of conventional surgical navigation, streamline workflow, and enable novel applications in image-guided surgery