ArticleInternational journal of clinical and experimental medicine2015
Intraoperative diagnosis of benign and malignant breast tissues by fourier transform infrared spectroscopy and support vector machine classification.
Article in International journal of clinical and experimental medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 28 citations in OpenAlex.
- Comparative FT-IR Spectroscopy Salivary Profiles of University Students: E‑Cigarette Users vs Nonusers.ACS omega · 2026Article
- Effective transfer of tumor annotations from hematoxylin and eosin to fluorescence images of breast and lung tissues.Journal of biomedical optics · 2026Article
- Toward Informative Representations of Blood-Based Infrared Spectra via Unsupervised Deep Learning.Journal of biophotonics · 2025Article
- Bridging Spectral Gaps: Cross-Device Model Generalization in Blood-Based Infrared Spectroscopy.Analytical chemistry · 2025Article
- Multiscale Spectral Analysis on Lysozyme Aqueous Solutions in the Presence of PolyEthyleneGlycol.Molecules (Basel, Switzerland) · 2022Article
- Vibrational Biospectroscopy: An Alternative Approach to Endometrial Cancer Diagnosis and Screening.International journal of molecular sciences · 2022Review
- Classification of target tissues of Eisenia fetida using sequential multimodal chemical analysis and machine learning.Histochemistry and cell biology · 2022Article
- Metabolic Profile Characterization of Different Thyroid Nodules Using FTIR Spectroscopy: A Review.Metabolites · 2022Review
- Artificial neural network in the discrimination of lung cancer based on infrared spectroscopy.PloS one · 2022Article
- Detection of breast cancer by ATR-FTIR spectroscopy using artificial neural networks.PloS one · 2022Article
- A New Look into Cancer-A Review on the Contribution of Vibrational Spectroscopy on Early Diagnosis and Surgery Guidance.Cancers · 2021Review
- Vibrational Spectroscopy for Identification of Metabolites in Biologic Samples.Molecules (Basel, Switzerland) · 2020Review
- A New Artificial Urine Protocol to Better Imitate Human Urine.Scientific reports · 2019Article
- Digital Staining of High-Definition Fourier Transform Infrared (FT-IR) Images Using Deep Learning.Applied spectroscopy · 2019Article
- Simultaneous cancer and tumor microenvironment subtyping using confocal infrared microscopy for all-digital molecular histopathology.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- Colorectal Cancer and Colitis Diagnosis Using Fourier Transform Infrared Spectroscopy and an Improved K-Nearest-Neighbour Classifier.Sensors (Basel, Switzerland) · 2017Article
- Label Free Detection of Sensitive Mid-Infrared Biomarkers of Glomerulonephritis in Urine Using Fourier Transform Infrared Spectroscopy.Scientific reports · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundFourier transform infrared (FTIR) spectroscopy has shown its unique advantages in distinguishing cancerous tissue from normal one. The aim of this study was to establish a quick and accurate diagnostic method of FTIR spectroscopy to differentiate malignancies from benign breast tissues intraoperatively. MATERIALS AND
methodsIn this study, a total of 100 breast tissue samples obtained from 100 patients were taken on surgery. All tissue samples were scanned for spectra intraoperatively before being processed for histopathological diagnosis. Standard normal variate (SNV) method was adopted to reduce scatter effects. Support vector machine (SVM) classification was used to discriminate spectra between malignant and benign breast tissues. Leave-one-out cross validation (LOOCV) was used to evaluate the discrimination.
resultsAccording to histopathological examination, 50 cases were diagnosed as fibroadenoma and 50 cases as invasive ductal carcinoma. The results of SVM algorithm showed that the sensitivity, specificity and accuracy rate of this method are 90.0%, 98.0% and 94.0%, respectively.
conclusionsFTIR spectroscopy technique in combination with SVM classification could be an accurate, rapid and objective tool to differentiate malignant from benign tumors during operation. Our studies establish the feasibility of FTIR spectroscopy with chemometrics method to guide surgeons during the surgery as an effective supplement for pathological diagnosis on frozen section.
Indexed as
Identifiers
25785083PMC4358538W100604289What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.