Spatial sensitivity distribution assessment and Monte Carlo simulations for needle-based bioimpedance imaging during venipuncture using the finite element method.

Despite being among the most common medical procedures, needle insertions suffer from a high error rate. Impedance measurements using electrode-equipped needles offer promise for improved tissue targeting and reduced errors. Impedance visualization usually requires an extensive pre-measured impedance dataset for tissue differentiation and knowledge of the electric fields contributing to the resulting impedances. This work presents two finite element simulation approaches for both problems. The first approach describes the generation of a multitude of impedances with Monte Carlo simulations for both, homogeneous and inhomogeneous tissue to circumvent the need to rely on previously measured data. These datasets could be used for tissue discrimination. The second method describes the simulation of the spatial sensitivity distribution of an electrode layout. Two singularity analysis methods were employed to determine the bulk of the sensitivity within a finite volume, which in turn enables consistent 3D visualization. The modeled electrode layout consists of 12 electrodes radially placed around a hypodermic needle. Electrical excitation was simulated using two neighboring electrodes for current carriage and voltage pickup, which resulted in 12 distinct bipolar excitation states. Both, the impedance simulations and the respective singularity analysis methods were compared with each other. The results show that the statistical spread of impedances is highly dependent on the tissue type and its inhomogeneities. The bounded bulk of sensitivities of both methods are of similar extent and symmetry. Future models should incorporate more detailed tissue properties such as anisotropy or changing material properties due to tissue deformation to gain more accurate predictions.

Needle-Based Electrical Impedance Imaging Technology for Needle Navigation.

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.

Physicochemical Quality Characteristics of Southeastern Anatolia Honey, Turkey.

This study was performed to investigate the physicochemical quality characteristics of honey produced in Southeastern Anatolia of Turkey. A total of 68 honey samples collected from different beekeepers were analyzed for sugar components, moisture, pH, HMF, electrical conductivity, free acidity, proline values, and diastase number using the methods recommended by the International Honey Commission. The color value was determined by the Hanna HI 96785 color identification device using the Pfund scale. The mean values of fructose + glucose, fructose/glucose ratio, sucrose, and maltose were 70.97 ± 3.27%, 1.21 ± 0.15, 0.90 ± 1.35%, and 2.88 ± 1.42%, respectively. The moisture, pH, electrical conductivity, free acidity, diastase number, proline, and HMF values were 15.91 ± 1.05%, 4.10 ± 0.73, 0.21 ± 0.04 mS/cm, 14.94 ± 6.81 meq/kg, 10.68 ± 4.61, 420±, 174 mg/kg, and 18.5 ± 31.43 mg/kg, respectively. All of the samples met the international standards and legal limits set in Turkey for fructose + glucose, sucrose, moisture, electrical conductivity, and free acidity, whereas 20.58%, 25%, 10.29%, and 8.82% of the samples did not meet the standards and legal limits for the diastase number, proline value, HMF value, and fructose/glucose ratio, respectively. It has been considered to be important to raise awareness of the producer about good production practices and to ensure continuity of inspections for high-quality honey production.