The Resistivity of Human Brain Tumours In Vivo

Electric Bioimpedance Sensing for the Detection of Head and Neck Squamous Cell Carcinoma

The early detection of head and neck squamous cell carcinoma (HNSCC) is essential to improve patient prognosis and enable organ and function preservation treatments. The objective of this study is to assess the feasibility of using electrical bioimpedance (EBI) sensing technology to detect HNSCC tissue. A prospective study was carried out analyzing tissue from 46 patients undergoing surgery for HNSCC. The goal was the correct identification of pathologic tissue using a novel needle-based EBI sensing device and AI-based classifiers. Considering the data from the overall patient cohort, the system achieved accuracies between 0.67 and 0.93 when tested on tissues from the mucosa, skin, muscle, lymph node, and cartilage. Furthermore, when considering a patient-specific setting, the accuracy range increased to values between 0.82 and 0.95. This indicates that more reliable results may be achieved when considering a tissue-specific and patient-specific tissue assessment approach. Overall, this study shows that EBI sensing may be a reliable technology to distinguish pathologic from healthy tissue in the head and neck region. This observation supports the continuation of this research on the clinical use of EBI-based devices for early detection and margin assessment of HNSCC.

PIRET-A Platform for Treatment Planning in Electroporation-Based Therapies

Tissue electroporation is the basis of several therapies. Electroporation is performed by briefly exposing tissues to high electric fields. It is generally accepted that electroporation is effective where an electric field magnitude threshold is overreached. However, it is difficult to preoperatively estimate the field distribution because it is highly dependent on anatomy and treatment parameters.

OBJECTIVE

We developed PIRET, a platform to predict the treatment volume in electroporation-based therapies.

METHODS

The platform seamlessly integrates tools to build patient-specific models where the electric field is simulated to predict the treatment volume. Patient anatomy is segmented from medical images and 3D reconstruction aids in placing the electrodes and setting up treatment parameters.

RESULTS

Four canine patients that had been treated with high-frequency irreversible electroporation were retrospectively planned with PIRET and with a workflow commonly used in previous studies, which uses different general-purpose segmentation (3D Slicer) and modeling software (3Matic and COMSOL Multiphysics). PIRET outperformed the other workflow by 65 minutes (× 1.7 faster), thanks to the improved user experience during treatment setup and model building. Both approaches computed similarly accurate electric field distributions, with average Dice scores higher than 0.93.

CONCLUSION

A platform which integrates all the required tools for electroporation treatment planning is presented. Treatment plan can be performed rapidly with minimal user interaction in a stand-alone platform.

SIGNIFICANCE

This platform is, to the best of our knowledge, the most complete software for treatment planning of irreversible electroporation. It can potentially be used for other electroporation applications.

A System-based Approach for the Evaluation of Electromechanical Properties of Brain Tumors

We have developed a semi-automated system integrated with MEMS-based electromechanical sensors to characterize human brain tumors. The electrical impedance and elastic moduli of three types of brain tumors and six normal brain regions were evaluated using the system. The impedance and elastic modulus of glioma was found to be significantly lower than the normal region. It was also observed that the white matter tissues had higher impedance and elastic moduli compared with the grey matter of the same neuroanatomic location. There were observable differences in the electromechanical behavior of gliomas, which originate from glial cells to that of schwannoma and meningioma of different cellular origins. Clinical Relevance- The observations suggest that simultaneous electromechanical characterization of brain tumors can serve as an effective tool for tumor delineation. The developed tool can be used alongside gold standard histopathological analysis to better understand human brain tumors.

Evaluating the therapeutic effect of tumor treating fields (TTFields) by monitoring the impedance across TTFields electrode arrays

BACKGROUND

Tumor Treating Fields (TTFields), are a novel, non-invasive tissue ablation technology for treatment of cancer. Tissue ablation is achieved through the continuous delivery of a narrow range of electromagnetic fields across a tumor, for a period of months. TTFields are designed to affect only cells that divide and to interfere with the cell division process. The therapy is monitored with MRI imaging, performed every couple of months. Current technology is unable to assess the treatment effectiveness in real time.

METHODS

We propose that the effect of the treatment can be assessed, in real time, by continuously measuring the change in electrical impedance across the TTFields delivery electrode arrays. An in vitro anatomic skull experimental study, with brain and tumor mimics phantom tissues was conducted to confirm the potential value of the proposed monitoring system.

RESULTS

Experiments show that measuring the change in the impedance amplitude between opposite TTFields electrode arrays, at a typical TTFields treatment frequency of (200 kHz), can detect changes in the tumor radius with a sensitivity that increases with the radius of the tumor. The study shows that TTFields electrode arrays can be used to assess the effectiveness of TTFields treatment on changes in the tumor dimensions in real time, throughout the treatement. This monitoring system may become a valuable addition to the TTFields cancer treatment technology. It could provide the means to continuously assess the effectiveness of the treatment, and thereby optimize the design of the treatment protocol.

Biopsy Needle System With a Steerable Concentric Tube and Online Monitoring of Electrical Resistivity and Insertion Forces

OBJECTIVE

Biopsies are the gold standard for clinical diagnosis. However, a discrepancy between the biopsy sample and target tissue because of misplacement of the biopsy spoon can lead to errors in the diagnosis and subsequent treatment. Thus, correctly determining whether the needle tip is in the tumor is crucial for accurate biopsy results.

METHODS

A biopsy needle system was designed with a steerable, flexible, and superelastic concentric tube; electrodes to monitor the electrical resistivity; and load cells to monitor the insertion force. The degrees of freedom were analyzed for two working modes: straight-line and deflection.

RESULTS

Experimental results showed that the system could perceive the tissue type in online based on the electrical resistivity. In addition, changes in the insertion force indicated transitions between the interfaces of adjacent tissue layers.

CONCLUSION

The two monitoring methods guarantee that the biopsy spoon is at the desired position inside the tumor during an operation.

SIGNIFICANCE

The proposed biopsy needle system can be integrated into an autonomous robotic biopsy system.

Preoperative Transcranial Direct Current Stimulation in Glioma Patients: A Proof of Concept Pilot Study

Background: Transcranial direct current stimulation (tDCS) has been used extensively in patient populations to facilitate motor network plasticity. However, it has not been studied in patients with brain tumors. We aimed to determine the feasibility of a preoperative motor training and tDCS intervention in patients with glioma. In an exploratory manner, we assessed changes in motor network connectivity following this intervention and related these changes to predicted electrical field strength from the stimulated motor cortex.

Methods: Patients with left-sided glioma (n=8) were recruited in an open label proof of concept pilot trial and participated in four consecutive days of motor training combined with tDCS. The motor training consisted of a 60-min period where the subject learned to play the piano with their right hand. Concurrently, they received 40 min of 2 mA anodal tDCS of the left motor cortex. Patients underwent task and resting state fMRI before and after this intervention. Changes in both the connectivity of primary motor cortex (M1) and general connectivity across the brain were assessed. Patient specific finite element models were created and the predicted electrical field (EF) resulting from stimulation was computed. The magnitude of the EF was extracted from left M1 and correlated to the observed changes in functional connectivity.

Results: There were no adverse events and all subjects successfully completed the study protocol. Left M1 increased both local and global connectivity. Voxel-wide measures, not constrained by a specific region, revealed increased global connectivity of the frontal pole and decreased global connectivity of the supplementary motor area. The magnitude of EF applied to the left M1 correlated with changes in global connectivity of the right M1.

Conclusion: In this proof of concept pilot study, we demonstrate for the first time that tDCS appears to be feasible in glioma patients. In our exploratory analysis, we show preoperative motor training combined with tDCS may alter sensorimotor network connectivity. Patient specific modeling of EF in the presence of tumor may contribute to understanding the dose-response relationship of this intervention. Overall, this suggests the possibility of modulating neural networks in glioma patients.

Impact of Peritumoral Edema During Tumor Treatment Field Therapy: A Computational Modelling Study

BACKGROUND

Tumor treatment fields (TTFie-lds) are an approved adjuvant therapy for glioblastoma (GBM). The magnitude of applied electrical field has been shown to be related to the anti-tumoral response. However, peritumoral edema may result in shunting of electrical current around the tumor, thereby reducing the intra-tumoral electric field. In this study, we systematically address this issue with computational simulations.

METHODS

Finite element models are created of a human head with varying amounts of peritumoral edema surrounding a virtual tumor. The electric field distribution was simulated using the standard TTFields electrode montage. Electric field magnitude was extracted from the tumor and related to edema thickness. Two patient specific models were created to confirm these results.

RESULTS

The inclusion of peritumoral edema decreased the average magnitude of the electric field within the tumor. In the model considering a frontal tumor and an anterior-posterior electrode configuration, ≥6 mm of peritumoral edema decreased the electric field by 52%. In the patient specific models, peritumoral edema decreased the electric field magnitude within the tumor by an average of 26%. The effect of peritumoral edema on the electric field distribution was spatially heterogenous, being most significant at the tissue interface between edema and tumor.

CONCLUSIONS

The inclusion of peritumoral edema during TTFields modelling may have a dramatic effect on the predicted electric field magnitude within the tumor. Given the importance of electric field magnitude for the anti-tumoral effects of TTFields, the presence of edema should be considered both in future modelling studies and when planning TTField therapy.

Optimization of multi-electrode implant configurations and programming for the delivery of non-ablative electric fields in intratumoral modulation therapy

PURPOSE

Application of low intensity electric fields to interfere with tumor growth is being increasingly recognized as a promising new cancer treatment modality. Intratumoral modulation therapy (IMT) is a developing technology that uses multiple electrodes implanted within or adjacent tumor regions to deliver electric fields to treat cancer. In this study, the determination of optimal IMT parameters was cast as a mathematical optimization problem, and electrode configurations, programming, optimization, and maximum treatable tumor size were evaluated in the simplest and easiest to understand spherical tumor model. The establishment of electrode placement and programming rules to maximize electric field tumor coverage designed specifically for IMT is the first step in developing an effective IMT treatment planning system.

METHODS

Finite element method electric field computer simulations for tumor models with 2 to 7 implanted electrodes were performed to quantify the electric field over time with various parameters, including number of electrodes (2 to 7), number of contacts per electrode (1 to 3), location within tumor volume, and input waveform with relative phase shift between 0 and 2π radians. Homogeneous tissue specific conductivity and dielectric values were assigned to the spherical tumor and surrounding tissue volume. In order to achieve the goal of covering the tumor volume with a uniform threshold of 1 V/cm electric field, a custom least square objective function was used to maximize the tumor volume covered by 1 V/cm time averaged field, while maximizing the electric field in voxels receiving less than this threshold. An additional term in the objective function was investigated with a weighted tissue sparing term, to minimize the field to surrounding tissues. The positions of the electrodes were also optimized to maximize target coverage with the fewest number of electrodes. The complexity of this optimization problem including its non-convexity, the presence of many local minima, and the computational load associated with these stochastic based optimizations led to the use of a custom pattern search algorithm. Optimization parameters were bounded between 0 and 2π radians for phase shift, and anywhere within the tumor volume for location. The robustness of the pattern search method was then evaluated with 50 random initial parameter values.

RESULTS

The optimization algorithm was successfully implemented, and for 2 to 4 electrodes, equally spaced relative phase shifts and electrodes placed equidistant from each other was optimal. For 5 electrodes, up to 2.5 cm diameter tumors with 2.0 V, and 4.1 cm with 4.0 V could be treated with the optimal configuration of a centrally placed electrode and 4 surrounding electrodes. The use of 7 electrodes allow for 3.4 cm diameter coverage at 2.0 V and 5.5 cm at 4.0 V. The evaluation of the optimization method using 50 random initial parameter values found the method to be robust in finding the optimal solution.

CONCLUSIONS

This study has established a robust optimization method for temporally optimizing electric field tumor coverage for IMT, with the adaptability to optimize a variety of parameters including geometrical and relative phase shift configurations.