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The Clinical Application of Tumor Treating Fields Therapy in Glioblastoma
Published on: April 16, 2019
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A theoretical study on evaluating brain tumor changes in tumor treating fields therapy by impedance detection
Xing Li1, Kaida Liu1, Haohan Fang1
1College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nan Jing, Jiang Su, China.
Frontiers in Oncology
|September 19, 2024
Summary
Tumor Treating Fields (TTFields) may continuously monitor glioblastoma treatment effectiveness. Electrodes used for therapy can also measure electrical impedance changes, offering real-time assessment of tumor size and treatment efficacy.
Area of Science:
- Biomedical Engineering
- Oncology
- Medical Physics
Background:
- Tumor Treating Fields (TTFields) is an FDA-approved therapy for glioblastoma multiforme (GBM).
- Current efficacy assessment relies on infrequent MRI scans (two-month intervals).
- Electrical impedance changes reflect tissue property alterations, crucial for monitoring tumor status.
Purpose of the Study:
- To investigate the feasibility of using TTFields electrodes as sensors for real-time impedance monitoring during GBM treatment.
- To determine if impedance measurements can continuously assess treatment effectiveness.
Main Methods:
- An in silico study was conducted to validate the hypothesis.
- Electrical impedance was measured between opposing TTFields electrode arrays.
- Simulated TTFields treatment parameters (50 V, 200 kHz) were utilized.
Main Results:
- The proposed impedance detection technique demonstrated sufficient resolution (> 1mm) to detect tumor size changes.
- A high Signal-to-Noise Ratio (> 40 dB) was achieved, indicating reliable measurements.
- The feasibility of using TTFields electrodes for continuous monitoring was confirmed.
Conclusions:
- Impedance measurement using TTFields electrodes is a viable method for real-time assessment of GBM treatment.
- This technique can potentially augment TTFields therapy by providing continuous safety and efficacy evaluation.
- This approach may lead to more adaptive and personalized cancer treatment strategies.

