Discrimination of Melanoma Using Laser-Induced Breakdown Spectroscopy Conducted on Human Tissue Samples
Discrimination and identification of melanoma (a kind of skin cancer) by using laser-induced breakdown spectroscopy (LIBS) combined with chemometrics methods are reported. The human melanoma and normal tissues are used in the form of formalin-fixed paraffin-embedded (FFPE) blocks as samples. The res...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
|
| Series: | Journal of Spectroscopy |
| Online Access: | http://dx.doi.org/10.1155/2020/8826243 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832554069040824320 |
|---|---|
| author | Muhammad Nouman Khan Qianqian Wang Bushra Sana Idrees Geer Teng Xutai Cui Kai Wei |
| author_facet | Muhammad Nouman Khan Qianqian Wang Bushra Sana Idrees Geer Teng Xutai Cui Kai Wei |
| author_sort | Muhammad Nouman Khan |
| collection | DOAJ |
| description | Discrimination and identification of melanoma (a kind of skin cancer) by using laser-induced breakdown spectroscopy (LIBS) combined with chemometrics methods are reported. The human melanoma and normal tissues are used in the form of formalin-fixed paraffin-embedded (FFPE) blocks as samples. The results demonstrated higher LIBS signal intensities of phosphorus (P), potassium (K), sodium (Na), magnesium (Mg), and calcium (Ca) in melanoma FFPE samples while lower signal intensities in normal FFPE tissue samples. Chemometric methods, artificial neural network (ANN), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and partial least square discriminant analysis (PLS-DA) are used to build the classification models. Different preprocessing methods, standard normal variate (SNV), mean-centering, normalization by total area, and autoscaling, were compared. A good performance of the model (sensitivity, specificity, and accuracy) for melanoma and normal FFPE tissues has been achieved by the ANN and PLS-DA models (all were 100%). The results revealed that LIBS combined with chemometric methods for detection and discrimination of human malignancies is a reliable, accurate, and precise technique. |
| format | Article |
| id | doaj-art-2217f10ae1634db896b368c0c196aad6 |
| institution | Kabale University |
| issn | 2314-4920 2314-4939 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Spectroscopy |
| spelling | doaj-art-2217f10ae1634db896b368c0c196aad62025-02-03T05:52:30ZengWileyJournal of Spectroscopy2314-49202314-49392020-01-01202010.1155/2020/88262438826243Discrimination of Melanoma Using Laser-Induced Breakdown Spectroscopy Conducted on Human Tissue SamplesMuhammad Nouman Khan0Qianqian Wang1Bushra Sana Idrees2Geer Teng3Xutai Cui4Kai Wei5School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, ChinaDiscrimination and identification of melanoma (a kind of skin cancer) by using laser-induced breakdown spectroscopy (LIBS) combined with chemometrics methods are reported. The human melanoma and normal tissues are used in the form of formalin-fixed paraffin-embedded (FFPE) blocks as samples. The results demonstrated higher LIBS signal intensities of phosphorus (P), potassium (K), sodium (Na), magnesium (Mg), and calcium (Ca) in melanoma FFPE samples while lower signal intensities in normal FFPE tissue samples. Chemometric methods, artificial neural network (ANN), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and partial least square discriminant analysis (PLS-DA) are used to build the classification models. Different preprocessing methods, standard normal variate (SNV), mean-centering, normalization by total area, and autoscaling, were compared. A good performance of the model (sensitivity, specificity, and accuracy) for melanoma and normal FFPE tissues has been achieved by the ANN and PLS-DA models (all were 100%). The results revealed that LIBS combined with chemometric methods for detection and discrimination of human malignancies is a reliable, accurate, and precise technique.http://dx.doi.org/10.1155/2020/8826243 |
| spellingShingle | Muhammad Nouman Khan Qianqian Wang Bushra Sana Idrees Geer Teng Xutai Cui Kai Wei Discrimination of Melanoma Using Laser-Induced Breakdown Spectroscopy Conducted on Human Tissue Samples Journal of Spectroscopy |
| title | Discrimination of Melanoma Using Laser-Induced Breakdown Spectroscopy Conducted on Human Tissue Samples |
| title_full | Discrimination of Melanoma Using Laser-Induced Breakdown Spectroscopy Conducted on Human Tissue Samples |
| title_fullStr | Discrimination of Melanoma Using Laser-Induced Breakdown Spectroscopy Conducted on Human Tissue Samples |
| title_full_unstemmed | Discrimination of Melanoma Using Laser-Induced Breakdown Spectroscopy Conducted on Human Tissue Samples |
| title_short | Discrimination of Melanoma Using Laser-Induced Breakdown Spectroscopy Conducted on Human Tissue Samples |
| title_sort | discrimination of melanoma using laser induced breakdown spectroscopy conducted on human tissue samples |
| url | http://dx.doi.org/10.1155/2020/8826243 |
| work_keys_str_mv | AT muhammadnoumankhan discriminationofmelanomausinglaserinducedbreakdownspectroscopyconductedonhumantissuesamples AT qianqianwang discriminationofmelanomausinglaserinducedbreakdownspectroscopyconductedonhumantissuesamples AT bushrasanaidrees discriminationofmelanomausinglaserinducedbreakdownspectroscopyconductedonhumantissuesamples AT geerteng discriminationofmelanomausinglaserinducedbreakdownspectroscopyconductedonhumantissuesamples AT xutaicui discriminationofmelanomausinglaserinducedbreakdownspectroscopyconductedonhumantissuesamples AT kaiwei discriminationofmelanomausinglaserinducedbreakdownspectroscopyconductedonhumantissuesamples |