Differentiating Between Malignant Mesothelioma and Other Pleural Lesions Using Fourier Transform Infrared Spectroscopy

Author:

Sadiku-Zehri Fatlinda12,Gamulin Ozren34ORCID,Škrabić Marko34ORCID,Qerimi-Krasniqi Ardita12,Sedlić Filip5,Šepac Ana6,Brčić Luka7ORCID,Vuletić Lovorka Batelja68,Seiwerth Sven68

Affiliation:

1. Department of Histology and Embriology, School of Medicine, University of Prishtina, Prishtina, Kosovo

2. Institute of Pathology, University Clinical Center of Kosovo, Prishtina, Kosovo

3. Department of Physics and Biophysics, School of Medicine, University of Zagreb, Zagreb, Croatia

4. Center of Excellence for Advanced Materials and Sensing Devices, Research Unit New Functional Materials, Zagreb, Croatia

5. Department of Pathophysiology, School of Medicine, University of Zagreb, Zagreb, Croatia

6. Department of Pathology, School of Medicine, University of Zagreb, Zagreb, Croatia

7. Institute of Pathology, Medical University of Graz, Graz, Austria

8. Clinical Department of Pathology and Cytology, KBC Zagreb, Zagreb, Croatia

Abstract

Histopathology, despite being the gold standard as a diagnostic tool, does not always provide a correct diagnosis for different pleural lesions. Although great progress was made in this field, the problem to differentiate between reactive and malignant pleural lesions still stimulates the search for additional diagnostic tools. Our research using vibrational spectroscopy and principal component analysis (PCA) statistical modeling represents a potentially useful tool to approach the problem. The objective method this paper explores is based on the correlation between different types of pleural lesions and their vibrational spectra. Obtained tissue spectra recorded by infrared spectroscopy allowed us to categorize spectra in different groups using a created PCA statistical model. The PCA model was built using tissues of known pathology as the model group. The validation samples were then used to confirm the functionality of our PCA model. Student’s t-test was also used for comparing samples in paired groups. The PCA model was able to clearly differentiate the spectra of mesothelioma, metastasis and reactive changes (inflammation), and place them in discrete groups. Thus, we showed that Fourier transform infrared spectroscopy combined with PCA can differentiate pleural lesions with high sensitivity and specificity. This new approach could contribute in objectively differentiating specific pleural lesions, thus helping pathologists to better diagnose difficult pleural samples but also could shed additional light into the biology of malignant pleural mesothelioma.

Funder

Ministry of Science and Technology, Croatia

Publisher

SAGE Publications

Subject

Spectroscopy,Instrumentation

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