Browsing by Author "Liu, Jan"

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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.
Open Access
Needle-based electrical impedance imaging technology for needle navigation
(2023) Liu, Jan; Atmaca, Ömer; Pott, Peter Paul
Needle insertion is a common procedure in modern healthcare practices, such as blood sampling, tissue biopsy, and cancer treatment. Various guidance systems have been developed to reduce the risk of incorrect needle positioning. While ultrasound imaging is considered the gold standard, it has limitations such as a lack of spatial resolution and subjective interpretation of 2D images. As an alternative to conventional imaging techniques, we have developed a needle-based electrical impedance imaging system. The system involves the classification of different tissue types using impedance measurements taken with a modified needle and the visualization in a MATLAB Graphical User Interface (GUI) based on the spatial sensitivity distribution of the needle. The needle was equipped with 12 stainless steel wire electrodes, and the sensitive volumes were determined using Finite Element Method (FEM) simulation. A k-Nearest Neighbors (k-NN) algorithm was used to classify different types of tissue phantoms with an average success rate of 70.56% for individual tissue phantoms. The results showed that the classification of the fat tissue phantom was the most successful (60 out of 60 attempts correct), while the success rate decreased for layered tissue structures. The measurement can be controlled in the GUI, and the identified tissues around the needle are displayed in 3D. The average latency between measurement and visualization was 112.1 ms. This work demonstrates the feasibility of using needle-based electrical impedance imaging as an alternative to conventional imaging techniques. Further improvements to the hardware and the algorithm as well as usability testing are required to evaluate the effectiveness of the needle navigation system.