Dielectric Properties of Human Active Liver, Kidney and Spleen Compared to Those of Respective Inactive Tissues, Porcine Tissues and the Data Provided by a Database in the Frequency Range of 10 Hz to 100 MHz

Design of the distribution of iron oxide (Fe3O4) nano-particle drug in realistic cholangiocarcinoma model and the simulation of temperature increase during magnetic induction hyperthermia

The prognosis for Cholangiocarcinoma (CCA) is unfavorable, necessitating the development of new therapeutic approach such as magnetic hyperthermia therapy (MHT) which is induced by magnetic nano-particle (MNPs) drug to bridge the treatment gap. Given the deep location of CCA within the abdominal cavity and proximity to vital organs, accurately predict the individualized treatment effects and safety brought by the distribution of MNPs in tumor will be crucial for the advancement of MHT in CCA. The Mimics software was used in this study to conduct three-dimensional reconstruction of abdominal computed tomography (CT) and magnetic reso-nance imaging images from clinical patients, resulting in the generation of a realistic digital geometric model representing the human biliary tract and its adjacent structures. Subsequently, The COMSOL Multiphysics software was utilized for modeling CCA and calculating the heat transfer law resulting from the multi-regional distribution of MNPs in CCA. The temperature within the central region of irregular CCA measured approximately 46°C, and most areas within the tumor displayed temperatures surpassing 41°C. The temperature of the inner edge of CCA is only 39 ∼ 41℃, however, it can be ameliorated by adjusting the local drug concentration through simulation system. For CCA with diverse morphologies and anatomical locations, the multi-regional distribution patterns of intratumoral MNPs and a slight overlap of drug distribution areas synergistically enhance intratumoral temperature while ensuring treatment safety. The present study highlights the practicality and imperative of incorporating personalized intratumoral MNPs distribution strategy into clinical practice for MHT, which can be achieved through the development of an integrated simulation system which incorporates medical image data and numerical calculations.

Electrical Conductivity Measurement in Human Liver Tissue: Assessment on Normal vs. Tumor Tissue and under In Vivo vs. Ex Vivo Conditions

BACKGROUND

This study evaluated electrical conductivity in human liver tissue in the 3-1000 kHz frequency range to compare normal versus tumor tissues under in vivo versus ex vivo conditions.

METHODS

Previous informed consent was obtained from twenty patients undergoing liver resection in whom liver electrical conductivity was measured during surgery and after resection.

RESULT

We found higher electrical conductivity values in tumor tissues than in normal tissue in both in vivo (0.41 ± 0.10 vs. 0.13 ± 0.06 S/m) and ex vivo (0.27 ± 0.09 vs. 0.12 ± 0.07 S/m) conditions (at 3 kHz). The electric properties also showed a promising potential for distinguishing between different tissue types including metastasis, cholangiocarcinoma (CCA), hepatocellular carcinoma (HCC), hepatic cirrhosis, and normal liver (both in vivo and ex vivo). At 3 kHz, in vivo electrical conductivity for cholangiocarcinoma, HCC, and metastasis were 0.35, 0.42 ± 0.13, and 0.41 ± 0.08 S/m, respectively, which differed significantly from each other (p < 0.05).

CONCLUSIONS

These findings could potentially improve liver disease diagnostics through electrical conductivity measurements and treatment techniques involving electric fields. Future research should focus on expanding the sample size to refine the categorization and comparison processes across diverse human liver tissue types.

Dynamic cerebral blood flow assessment based on electromagnetic coupling sensing and image feature analysis

Dynamic assessment of cerebral blood flow (CBF) is crucial for guiding personalized management and treatment strategies, and improving the prognosis of stroke. However, a safe, reliable, and effective method for dynamic CBF evaluation is currently lacking in clinical practice. In this study, we developed a CBF monitoring system utilizing electromagnetic coupling sensing (ECS). This system detects variations in brain conductivity and dielectric constant by identifying the resonant frequency (RF) in an equivalent circuit containing both magnetic induction and electrical coupling. We evaluated the performance of the system using a self-made physical model of blood vessel pulsation to test pulsatile CBF. Additionally, we recruited 29 healthy volunteers to monitor cerebral oxygen (CO), cerebral blood flow velocity (CBFV) data and RF data before and after caffeine consumption. We analyzed RF and CBFV trends during immediate responses to abnormal intracranial blood supply, induced by changes in vascular stiffness, and compared them with CO data. Furthermore, we explored a method of dynamically assessing the overall level of CBF by leveraging image feature analysis. Experimental testing substantiates that this system provides a detection range and depth enhanced by three to four times compared to conventional electromagnetic detection techniques, thereby comprehensively covering the principal intracranial blood supply areas. And the system effectively captures CBF responses under different intravascular pressure stimulations. In healthy volunteers, as cerebral vascular stiffness increases and CO decreases due to caffeine intake, the RF pulsation amplitude diminishes progressively. Upon extraction and selection of image features, widely used machine learning algorithms exhibit commendable performance in classifying overall CBF levels. These results highlight that our proposed methodology, predicated on ECS and image feature analysis, enables the capture of immediate responses of abnormal intracranial blood supply triggered by alterations in vascular stiffness. Moreover, it provides an accurate diagnosis of the overall CBF level under varying physiological conditions.