Differentiating Between Malignant Mesothelioma and Other Pleural Lesions Using Fourier Transform Infrared Spectroscopy
| Autor: | Ana Sepac, Fatlinda Sadiku-Zehri, Filip Sedlic, Ozren Gamulin, Lovorka Batelja Vuletic, Marko Škrabić, Ardita Qerimi-Krasniqi, Sven Seiwerth, Luka Brcic |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Pathology
medicine.medical_specialty Adenocarcinoma of Lung Diagnostic tools 03 medical and health sciences 0302 clinical medicine Spectroscopy Fourier Transform Infrared medicine Humans Mesothelioma Fourier transform infrared spectroscopy Pleura inflammation mesothelioma metastatic adenocarcinoma principal component analysis Instrumentation Spectroscopy Mesothelioma Malignant / diagnostic imaging 030304 developmental biology Inflammation / diagnostic imaging Inflammation 0303 health sciences Pleural mesothelioma business.industry Pleura / pathology Mesothelioma Malignant Objective method Gold standard (test) medicine.disease Pleura / diagnostic imaging 030220 oncology & carcinogenesis Principal component analysis business Adenocarcinoma of Lung / diagnostic imaging Vibrational spectra |
| DOI: | 10.1177/0003702820924726 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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