ArticleBiomedical optics express2018
Discrimination of lymphoma using laser-induced breakdown spectroscopy conducted on whole blood samples.
Article in Biomedical optics express, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 63 citations in OpenAlex.
- From Fundamentals of Laser-Induced Breakdown Spectroscopy to Recent Advancements in Cancer Detection and Calcified Tissues Analysis: An Overview (2015-2025).Molecules (Basel, Switzerland) · 2025Review
- Elemental composition analysis of calcium-based urinary stones via laser-induced breakdown spectroscopy for enhanced clinical insights.Scientific reports · 2025Article
- Advanced automated classification and segmentation of leukemic cells using simulated optical scanning holography and active contour methods.Journal of biomedical optics · 2025Article
- Article
- Expanding the boundaries of atomic spectroscopy at the single-cell level: critical review of SP-ICP-MS, LIBS and LA-ICP-MS advances for the elemental analysis of tissues and single cells.Analytical and bioanalytical chemistry · 2023Review
- Comparison of whole blood and serum samples of breast cancer based on laser-induced breakdown spectroscopy with machine learning.Biomedical optics express · 2023Article
- Detection and Classification of Bacterial Cells After Centrifugation and Filtration of Liquid Specimens Using Laser-Induced Breakdown Spectroscopy.Applied spectroscopy · 2022Article
- Laser-Induced Breakdown Spectroscopy Combined with Nonlinear Manifold Learning for Improvement Aluminum Alloy Classification Accuracy.Sensors (Basel, Switzerland) · 2022Article
- Detection of hypokalemia disorder and its relation with hypercalcemia in blood serum using LIBS technique for patients of colorectal cancer grade I and grade II.Lasers in medical science · 2022Article
- Laser induced breakdown spectroscopy for the rapid detection of SARS-CoV-2 immune response in plasma.Scientific reports · 2022Article
- In-vitro study on the identification of gastrointestinal stromal tumor tissues using laser-induced breakdown spectroscopy with chemometric methods.Biomedical optics express · 2022Article
- Diagnosis and staging of multiple myeloma using serum-based laser-induced breakdown spectroscopy combined with machine learning methods.Biomedical optics express · 2021Article
- Machine learning-based LIBS spectrum analysis of human blood plasma allows ovarian cancer diagnosis.Biomedical optics express · 2021Article
- Diagnosis of Alzheimer's disease using laser-induced breakdown spectroscopy and machine learning.Spectrochimica acta. Part B, Atomic spectroscopy · 2020Article
- Blood cancer diagnosis using ensemble learning based on a random subspace method in laser-induced breakdown spectroscopy.Biomedical optics express · 2020Article
- Combined Nd:YAG and Er:YAG lasers for real-time closed-loop tissue-specific laser osteotomy.Biomedical optics express · 2020Article
- Feasibility Study on Discrimination of Neo-plastic and Non-Neoplastic Gastric Tissues Using Spark Discharge Assisted Laser Induced Breakdown Spectroscopy.Journal of lasers in medical sciences · 2019Article
- Importance evaluation of spectral lines in Laser-induced breakdown spectroscopy for classification of pathogenic bacteria.Biomedical optics express · 2018Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lymphoma is a significant cancer that affects the human lymphatic and hematopoietic systems. In this work, discrimination of lymphoma using laser-induced breakdown spectroscopy (LIBS) conducted on whole blood samples is presented. The whole blood samples collected from lymphoma patients and healthy controls are deposited onto standard quantitative filter papers and ablated with a 1064 nm Q-switched Nd:YAG laser. 16 atomic and ionic emission lines of calcium (Ca), iron (Fe), magnesium (Mg), potassium (K) and sodium (Na) are selected to discriminate the cancer disease. Chemometric methods, including principal component analysis (PCA), linear discriminant analysis (LDA) classification, and k nearest neighbor (kNN) classification are used to build the discrimination models. Both LDA and kNN models have achieved very good discrimination performances for lymphoma, with an accuracy of over 99.7%, a sensitivity of over 0.996, and a specificity of over 0.997. These results demonstrate that the whole-blood-based LIBS technique in combination with chemometric methods can serve as a fast, less invasive, and accurate method for detection and discrimination of human malignancies.
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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.