Investigation toward Diagnosis of Deep Cancer by Laser Resonance Frequency Analysis

This study investigates the feasibility of laser resonance frequency analysis (L-RFA) for noninvasive cancer diagnosis, with a focus on detecting deep lesions. L-RFA utilizes a coherent light source to induce microvibrations on the tissue surface and analyzes the resulting resonance spectrum to estimate tissue stiffness. In our previous study, experimental validation using excised gastric cancer specimens demonstrated the method's ability to differentiate between cancerous and normal tissue based on stiffness. Further analysis using pathological images revealed that L-RFA scores remain high in tumors regardless of the presence of fibrotic tissue, suggesting robustness against false positives. In phantom experiments, we simulated buried tumors using agarose gel and copper plates, confirming L-RFA's capacity to detect stiffness changes at depth. Additionally, prior clinical applications in orthopedics showed that L-RFA could assess bone quality and implant fixation strength intraoperatively, supporting its real-world applicability. These results suggest that L-RFA offers a novel diagnostic axis based on tissue elasticity, with potential integration into endoscopic systems for early cancer detection and intraoperative evaluation.

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Publication Details

Journal
IEEJ Transactions on Electronics Information and Systems
Published
2026-03-31
DOI
https://doi.org/10.1541/ieejeiss.146.295
Primary Topic
Bone health and osteoporosis research
Type
article
Field-Weighted Citation Impact
0.00
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article

Investigation toward Diagnosis of Deep Cancer by Laser Resonance Frequency Analysis

Yuka Matsumoto, Katsuhiro Mikami, Satoshi Ikeda
IEEJ Transactions on Electronics Information and Systems
Bone health and osteoporosis research
article

Investigation toward Diagnosis of Deep Cancer by Laser Resonance Frequency Analysis

Yuka Matsumoto, Katsuhiro Mikami, Satoshi Ikeda
article en

Abstract

This study investigates the feasibility of laser resonance frequency analysis (L-RFA) for noninvasive cancer diagnosis, with a focus on detecting deep lesions. L-RFA utilizes a coherent light source to induce microvibrations on the tissue surface and analyzes the resulting resonance spectrum to estimate tissue stiffness. In our previous study, experimental validation using excised gastric cancer specimens demonstrated the method's ability to differentiate between cancerous and normal tissue based on stiffness. Further analysis using pathological images revealed that L-RFA scores remain high in tumors regardless of the presence of fibrotic tissue, suggesting robustness against false positives. In phantom experiments, we simulated buried tumors using agarose gel and copper plates, confirming L-RFA's capacity to detect stiffness changes at depth. Additionally, prior clinical applications in orthopedics showed that L-RFA could assess bone quality and implant fixation strength intraoperatively, supporting its real-world applicability. These results suggest that L-RFA offers a novel diagnostic axis based on tissue elasticity, with potential integration into endoscopic systems for early cancer detection and intraoperative evaluation.

IEEJ Transactions on Electronics Information and SystemsVol. 146(4)
Bio-oriented Technology Research Advancement Institution (JP)
Good health and well-being
Openalex Percentile: Top 4%
Bone health and osteoporosis research
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