Related Experiment Video
Updated: Aug 28, 2025

07:54
Surface-enhanced Resonance Raman Scattering Nanoprobe Ratiometry for Detecting Microscopic Ovarian Cancer via Folate Receptor Targeting
Published on: March 25, 2019
8.3K
Rapid Characterization of Solid Tumors Using Resonant Sensors
Andee M Beierle1, Colin H Quinn2, Hooper R Markert2
1Department of Radiation Oncology, University of Alabama at Birmingham, Birmingham, Alabama 35233, United States.
ACS Omega
|September 19, 2022
Summary
A novel wireless sensor accurately detects differences in pediatric tumor tissues, distinguishing between live and dead cells, primary and metastatic tumors, and treated versus untreated samples for improved cancer diagnosis.
Area of Science:
- Biomedical Engineering
- Pediatric Oncology
- Medical Diagnostics
Background:
- Pediatric solid tumors are a major cause of mortality in children.
- Accurate diagnosis is crucial for effective treatment planning.
- Non-invasive methods for obtaining viable tumor tissue are needed.
Purpose of the Study:
- To evaluate a wireless inductor-capacitor (LC) sensor for detecting relative permittivity of pediatric tumor tissues.
- To assess the sensor's ability to differentiate between various tissue conditions.
Main Methods:
- Utilized a wireless LC sensor to measure the resonant frequencies of pediatric tumor tissues.
- Compared resonant frequencies of live versus dead tissues.
- Compared primary tumor tissues with normal tissues and metastatic tissues.
- Compared treated versus untreated tumor tissues.
Main Results:
- Significant shifts in resonant frequencies were observed between all comparison groups.
- Dead tissues showed a significant resonant frequency shift compared to live tissues.
- Distinct resonant frequencies differentiated normal tissues from tumor tissues.
- Primary tumors exhibited different resonant frequencies compared to their metastases.
Conclusions:
- LC sensor technology shows potential for non-invasive detection and diagnosis of pediatric solid tumors.
- Relative permittivity measurements can distinguish between different tumor states and normal tissues.
- This technology could aid in clinical decision-making for pediatric cancer.

