Ultrasound Guided Needle Insertion Simulation Systems for The Training of Central Venous Catheterization Procedures

Brown, Dailen

Ultrasound Guided Needle Insertion Simulation Systems for The Training of Central Venous Catheterization Procedures

Restricted

Author:: Brown, Dailen
Graduate Program:: Mechanical Engineering
Degree:: Doctor of Philosophy
Document Type:: Dissertation
Date of Defense:: May 30, 2024
Committee Members:: Jason Moore, Chair & Dissertation Advisor
Scarlett Miller, Outside Unit & Field Member
Bo Cheng, Major Field Member
Daniel Cortes Correales, Major Field Member
Robert Kunz, Professor in Charge/Director of Graduate Studies
Keywords:: Medical Simulation
Catheterization
Ultrasound
Needle Insertion
Computer Vision
Sensors
Feedback
Training
Compliant Mechanisms
Abstract:: The primary goal of this dissertation research is to develop more efficient, effective, and authentic simulation methods for medical training, specifically for the training of Central Venous Catheterization (CVC). State-of-the-art simulation-based training methods for CVC utilize manikin simulators which are lacking in 3 critical areas, 1) Residents cannot use CVC tools to practice post-needle insertion steps without destroying the manikin simulator, 2) Feedback and assessment methods lack quantitative robustness and must be given by an expert on-site during training, and 3) manikin simulators are limited to the presentation of a single patient anatomy. Thus, the primary goals of this research are directly linked to addressing these 3 limitations. This is accomplished through the investigation of various automated feedback and assessment methods for Central Venous Catheterization training, the development of Computer Vision (CV) and sensorization techniques for tracking medical tools, the investigation of true anatomical variation amongst patients for use in the creation of simulated patient scenarios, and the development of low-cost, high fidelity, dynamic haptic systems for needle insertion simulation. This includes the redesign of a CVC simulation system known as the Dynamic Haptic Robotic Trainer (DHRT), its replication into 5 systems deployed at 2 major hospitals for training and research, the design of two submodules for a post needle insertion training device denoted as the DHRT+, the development of a new ultrasound skill assessment metric, the development of a semi-automated vessel detection algorithm for the investigation of patient anatomy, and the development of a low-cost Dynamic Haptic Syringe (DHS) using novel Slip Flexures to generate accurate force-displacement profiles in needle insertion simulations. CVC is a common medical procedure used to access the central venous system for the purpose of rapid administration of medications and blood related measurements. The procedure is known for its high rate of both mechanical and infectious complications, some of which can have drastic effects on patient health. Training methods for CVC are not standardized and vary widely, with some hospitals continuing to use the learning by doing model. The current state of the art method for CVC training uses manikin simulators. The majority of CVC related tools cannot be used on these manikins, which prevents residents from practicing essential skills related to CVC which are needed to prevent serious complications. Additionally, these manikins are incapable of giving feedback or assessment of skills and thus require expert oversight for training to be effective. Valuable time and money could be reallocated if CVC training methods were more automated and efficient. Finally, these manikins present a single anatomy to the user which limits the scenarios that residents are exposed to in training which can be problematic when they move on to clinical practice. The original DHRT prototype was previously developed to provide high-fidelity simulation of ultrasound guided needle insertion. This research builds upon those efforts. The DHRT was first redesigned and replicated into 5 fully deployable systems which were more transportable and aesthetic than the original design. Next, to address the first limitation of current manikins, two modules for a full procedure training device known as the DHRT+ were developed to track CVC tool usage and assess procedural skills including step order, sharps management, and sterile technique. These efforts included the development of a CV algorithm and sensorization methods to track the usage of CVC tools during post-needle insertion steps. These modules have since been iteratively refined and integrated into the DHRT system to create the DHRT+. To address the second limitation of manikin simulators, the redesigned DHRT was deployed in 2 hospitals in a study involving the training of 163 medical residents in 2021. The study investigated the learning gains of medical residents and found that mechanical complications were less likely when proper aspiration and needle visualization were performed. However, understanding of proper ultrasound utilization for needle visualization were significantly lacking. A follow up study was conducted comparing improvements to the training and feedback systems on the DHRT in 2022 and 2023 and included the training of 182 residents during those years. The study confirmed the previous findings and illustrated the effectiveness of enhanced training methods. However, the new feedback method, developed using common and recommended methods, was ineffective in improving needle visualization performance, indicating that common simulation feedback may be insufficient for more complicated tasks. Finally, to address the third limitation of CVC manikins, a semi-automated vessel detection algorithm was developed and used to assess vessel anatomy shown in clinical ultrasound recordings from 50 patients at Milton S. Hershey Medical Center (HMC). The study showed typical anatomical variations of the vein and artery, with the artery being more circular and posterior to the vein in most cases. Notably, two cases revealed atypical artery positions, emphasizing the algorithm's precision in detecting anomalies. Dynamic vessel properties were analyzed, including venous compression and arterial pulsation. Finally, the DHS was developed using compliant mechanisms utilizing novel Slip Flexures to generate 4 realistic haptic profiles in cartridges which can be rotated by a selector knob to enable dynamic haptic feedback in a low-cost, untethered form. An important overall benefit of this research is the improvement of patient outcomes which is accomplished by the development of better simulation-based training methods for CVC, which will ultimately reduce complication rates in the clinic. Other benefits from this research include the development of simulation methods which produce more authentic training experiences, decreased cost to hospitals by reducing the need for expert oversight, and the creation of a novel high-fidelity mechanism for needle insertion simulation at low cost. Additionally, this research develops methods for automatically assessing anatomical variation from collections of recorded clinical ultrasound videos. These methods can be applied to other procedures and other image types and may lead to greater understanding of human anatomy. Finally, this research developed a novel component for compliant mechanism systems known as Slip Flexures which leverage compliance and controlled friction to develop negative slopes in force-displacement curves and enables the creation of haptic compliant mechanisms capable of infinite displacement range. Slip Flexures have the potential to improve haptic simulation systems, but could also be used in many industries to improve compliant mechanism designs that are currently limited in range.

Tools