Development and characterization of a dual-fiber Raman probe for accurate and rapid endometrial carcinoma detection

We report on the development and characterization of a dual-fiber optic Raman probe for enhancing real-time endometrial carcinoma biopsy. The fiber optic probe was designed with two miniaturized coating fibers with an outer diameter (OD) of 3.1 mm. We demonstrate that with the use of the Raman probe associated with the background subtraction algorithms, high-quality tissue Raman spectra covering the fingerprint (FP) (500-1800cm<sup>-1</sup>) can be acquired from different tissue types (e.g., muscle, fat, parathyroid gland, and thyroid gland). Using an anti-reflection coating filter and background subtraction algorithms, our probe has better signal-to-noise (SNR) than a conventional coating probe with a comparable OD. Meanwhile, our probe has less OD and 58% SNR compared with the handheld probe (OD = 10 mm). We developed a Raman fiber probe with a small outer diameter and high SNR (>90 in fat) simultaneously and used the small-size probe for accurate and rapid endometrial carcinoma detection. Specifically, a total of 220 fingerprint Raman spectra was obtained from 22 endometrial carcinoma (EC) patients (benign: 10, malignant: 12) and divided into two batches (110 spectra from 11 patients for each) from different patients for robustness test. The mean area under the receiver operating characteristic curves (AUC) for differentiating benign and malignant EC reached 0.946, with a mean accuracy of 93.1% and a mean time expense of 5 seconds by the ResNet model. Furthermore, the specific Raman features corresponding to biomolecules (e.g., amide I II, lipid, and collagen) were found to contribute to the accurate classification.

Authors

Institutions

Publication Details

Journal
Biomedical Optics Express
Published
2025-06-17
DOI
https://doi.org/10.1364/boe.568647
Primary Topic
Spectroscopy Techniques in Biomedical and Chemical Research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development and characterization of a dual-fiber Raman probe for accurate and rapid endometrial carcinoma detection

Shijie Zhu, Rongxin Fu, Zhiwei Huang, Shangran Xie et al.
Biomedical Optics Express
Spectroscopy Techniques in Biomedical and Chemical Research
article

Development and characterization of a dual-fiber Raman probe for accurate and rapid endometrial carcinoma detection

Shijie Zhu, Rongxin Fu, Zhiwei Huang, Shangran Xie, Zhaoqin Yang, Limin Feng, Shuhua Yue, Zhichao Wang, Luping Zhang, Xun Chen, Jing Chen
article en

Abstract

We report on the development and characterization of a dual-fiber optic Raman probe for enhancing real-time endometrial carcinoma biopsy. The fiber optic probe was designed with two miniaturized coating fibers with an outer diameter (OD) of 3.1 mm. We demonstrate that with the use of the Raman probe associated with the background subtraction algorithms, high-quality tissue Raman spectra covering the fingerprint (FP) (500-1800cm<sup>-1</sup>) can be acquired from different tissue types (e.g., muscle, fat, parathyroid gland, and thyroid gland). Using an anti-reflection coating filter and background subtraction algorithms, our probe has better signal-to-noise (SNR) than a conventional coating probe with a comparable OD. Meanwhile, our probe has less OD and 58% SNR compared with the handheld probe (OD = 10 mm). We developed a Raman fiber probe with a small outer diameter and high SNR (>90 in fat) simultaneously and used the small-size probe for accurate and rapid endometrial carcinoma detection. Specifically, a total of 220 fingerprint Raman spectra was obtained from 22 endometrial carcinoma (EC) patients (benign: 10, malignant: 12) and divided into two batches (110 spectra from 11 patients for each) from different patients for robustness test. The mean area under the receiver operating characteristic curves (AUC) for differentiating benign and malignant EC reached 0.946, with a mean accuracy of 93.1% and a mean time expense of 5 seconds by the ResNet model. Furthermore, the specific Raman features corresponding to biomolecules (e.g., amide I II, lipid, and collagen) were found to contribute to the accurate classification.

Biomedical Optics ExpressVol. 16(7)
Beijing Institute of Technology (CN), Capital University (US), National University of Singapore (SG), Capital Medical University (CN), Institute of Microelectronics (CN), Botswana Geoscience Institute (BW), Ministry of Industry and Information Technology (CN)
Ministry of Education - Singapore, National Natural Science Foundation of China, National Medical Research Council, Science and Technology Support Program of Jiangsu Province, Beijing Municipal Natural Science Foundation, Fundamental Research Funds for the Central Universities
Good health and well-being
Openalex Percentile: Top 90%
Spectroscopy Techniques in Biomedical and Chemical Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.