07 Fakultät Konstruktions-, Produktions- und Fahrzeugtechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/8
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Item Open Access Electrical impedance imaging technology for needle guidance during medical needle insertion procedures(2024) Liu, Jan; Pott, Peter P. (Prof. Dr. rer. nat. habil.)Although performed on a daily basis, medical needle insertion procedures are often associated with complications due to incorrect needle positioning. The most common needle insertion procedure is venipuncture for blood collection. In a study of 4,050 patients, bruising and hematoma occurred in 12.3 % of cases. These are the result of only partial penetration of the blood vessel or complete perforation (needle overshoot). Needle insertion is usually performed manually, highly dependent on the clinician's skill and the patient's physiology. Existing needle guidance methods are either cumbersome and inadequate for routine procedures, or prone to error. This dissertation aims to explore a new imaging technology based on electrical impedance measurements as an alternative to current guidance systems. It is hypothesized that the integration of multiple localized impedance measurements on a needle enables successful tissue identification and spatial localization. This information can be exploited to develop a 3D imaging system that can be used for needle guidance during medical needle insertion procedures. In this dissertation, the hypothesis is investigated through the exploration of three aspects. The first aspect involves impedance-based tissue identification using medical needles. A bipolar, multi-local (bipolar), and monopolar approach were established and tested. In the bipolar approach, two concentrically placed needles were used as part of a measurement system. Successful tissue identification based on conductivity values was achieved for fat, skin, and blood phantoms. The multi-local approach involved the modification of a hypodermic needle with 12 stainless steel wire electrodes. A system was established to sequentially switch the active measurement electrodes on the needle. The measured impedance values were assigned to the corresponding tissue types using a k-nearest neighbors classification algorithm. Additionally, the monopolar approach was tested in the context of epidural anesthesia. A setup comprising a Tuohy needle and an ECG electrode successfully discriminated between fat and sodium chloride solution, which was used as a substitute for cerebrospinal fluid. The second aspect deals with the simulative assessment of needle-based impedance measurements. The above configurations were translated into CAD models and integrated into an FEM environment. The FEM simulations were performed to generate impedance data as a potential basis for a classification task. Also, the current density distribution was investigated to define a region of relevant spatial measurement sensitivity. The so-called sensitive volumes could be successfully integrated into the third aspect, which is the development of the needle guidance system. For the needle guidance system, a graphical user interface was implemented to serve as the user's control and visualization interface. The user interface can be used to control hardware components responsible for switching electrode pairs and measuring impedance. The visualization environment displays the needle during insertion and shows the surrounding tissue types corresponding to the shape of the sensitive volumes. Eventually, the developed system was evaluated for needle guidance effectiveness. An initial study comparing ultrasound guidance with impedance-based guidance was performed with three subjects. Despite the small sample size, the study found that impedance-based needle guidance was preferred due to its intuitiveness and handling, and the efficacy was highly dependent on the classification success rate.