Rapid differentiation of patients with lung cancers from benign lung nodule based on dried serum Fourier-transform infrared spectroscopy combined with machine learning algorithms.

Journal: Photodiagnosis and photodynamic therapy
Published Date:

Abstract

Lung cancer (LC) is associated with poor 5-year survival rates when diagnosed at advanced stages. While low-dose computed tomography (LDCT) screening enables earlier detection, its high false-positive rate, primarily due to benign lung nodules (BLN), necessitates more accurate diagnostic tools. This study developed a rapid and precise LC discrimination method by integrating Fourier transform infrared (FTIR) spectroscopy of dried serum samples with machine learning algorithms. We analyzed dried serum from 58 LC patients, 37 BLN patients, and 36 healthy controls. Five machine learning models, linear discriminant analysis (LDA), support vector machine (SVM), random forest, multilayer perceptron (MLP), and LightGBM, were optimized using FTIR spectral data (1800-900 cm cm band). All algorithms successfully differentiated the three groups, with LDA achieving the highest accuracy (93.9%). These results demonstrate that dried serum FTIR spectroscopy coupled with machine learning, particularly LDA, offers a promising approach for distinguishing LC from BLN, potentially augmenting LDCT screening to reduce unnecessary interventions.

Authors

  • Huanyu Li
    Department of Computer and Information Science and Swedish e-Science Research Centre, Linköping University, Linköping, Sweden.
  • LiXue Dai
    The Second Department of Respiratory Disease, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi 330006, China.
  • Shaomei Guo
    Second Department of Pulmonary and Critical Care Medicine, Jiangxi Provincial People's Hospital, the First Affiliated Hospital of Nanchang Medical College, Nanchang 330006, China.
  • Hongluan Wang
    Second Department of Pulmonary and Critical Care Medicine, Jiangxi Provincial People's Hospital, the First Affiliated Hospital of Nanchang Medical College, Nanchang 330006, China.
  • Lei Lei
    Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Jie Yu
    Institute of Animal Nutrition, Sichuan Agricultural University, Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Key Laboratory of Animal Disease-resistant Nutrition and Feed of China Ministry of Agriculture and Rural Affairs, Key Laboratory of Animal Disease-resistant Nutrition of Sichuan Province, Ya'an, 625014, China.
  • Xiaoyun Li
    Second Department of Pulmonary and Critical Care Medicine, Jiangxi Provincial People's Hospital, the First Affiliated Hospital of Nanchang Medical College, Nanchang 330006, China.
  • Jun Wang
    Department of Speech, Language, and Hearing Sciences and the Department of Neurology, The University of Texas at Austin, Austin, TX 78712, USA.

Keywords

No keywords available for this article.