Identification of fluoroquinolone-resistant Mycobacterium tuberculosis through high-level data fusion of Raman and laser-induced breakdown spectroscopy.

Autor:	Jeon G; Industrial Transformation Technology Department, Research Institute of Sustainable Development Technology, Korea Institute of Industrial Technology, 89, Yangdaegiro-gil, Ipjang-myeon, Seobuk-gu, Cheonan-Si, Chungcheongnam-do 31056, Republic of Korea. cjh@kitech.re.kr.; Photonic Device Physics Laboratory, Institute of Physics and Applied Physics, Yonsei University, 50, Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea., Kim S; Advanced Photonics Research Institute (APRI), Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Republic of Korea., Kim YJ; Department of Laboratory Medicine, Kyung Hee University College of Medicine, Kyung Hee University Hospital, Seoul, Republic of Korea., Kim S; Laboratory Medicine Center, Korean National Tuberculosis Association, The Korean Institute of Tuberculosis, Cheongju, Republic of Korea., Han K; Clinical Laboratory Medicine Center, Korean National Tuberculosis Association, Seoul, Republic of Korea. leehejo@gmail.com., Oh K; Photonic Device Physics Laboratory, Institute of Physics and Applied Physics, Yonsei University, 50, Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea., Lee HJ; Clinical Laboratory Medicine Center, Korean National Tuberculosis Association, Seoul, Republic of Korea. leehejo@gmail.com., Choi J; Industrial Transformation Technology Department, Research Institute of Sustainable Development Technology, Korea Institute of Industrial Technology, 89, Yangdaegiro-gil, Ipjang-myeon, Seobuk-gu, Cheonan-Si, Chungcheongnam-do 31056, Republic of Korea. cjh@kitech.re.kr.
Jazyk:	angličtina
Zdroj:	Analytical methods : advancing methods and applications [Anal Methods] 2024 Sep 26; Vol. 16 (37), pp. 6349-6355. Date of Electronic Publication: 2024 Sep 26.
DOI:	10.1039/d4ay01331j
Abstrakt:	Accurate and rapid diagnosis of drug susceptibility of Mycobacterium tuberculosis is crucial for the successful treatment of tuberculosis, a persistent global public health threat. To shorten diagnosis times and enhance accuracy, this study introduces a fusion model combining laser-induced breakdown spectroscopy (LIBS) and Raman spectroscopy. This model offers a rapid and accurate method for diagnosing drug-resistance. LIBS and Raman spectroscopy provide complementary information, enabling accurate identification of drug resistance in tuberculosis. Although individual use of LIBS or Raman spectroscopy achieved approximately 90% accuracy in identifying drug resistance, the fusion model significantly improved identification accuracy to 98.3%. Given the fast measurement capabilities of both techniques, this fusion approach is expected to markedly decrease the time required for diagnosis.
Databáze:	MEDLINE
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