دورية أكاديمية
Screening of malaria infections in human blood samples with varying parasite densities and anaemic conditions using AI-Powered mid-infrared spectroscopy.
العنوان: | Screening of malaria infections in human blood samples with varying parasite densities and anaemic conditions using AI-Powered mid-infrared spectroscopy. |
---|---|
المؤلفون: | Mshani IH; Environmental Health, and Ecological Sciences Department, Ifakara Health Institute, Morogoro, United Republic of Tanzania. imshani@ihi.or.tz.; School of Biodiversity, One Health and Veterinary Medicine, The University of Glasgow, Glasgow, UK. imshani@ihi.or.tz., Jackson FM; Environmental Health, and Ecological Sciences Department, Ifakara Health Institute, Morogoro, United Republic of Tanzania., Mwanga RY; Environmental Health, and Ecological Sciences Department, Ifakara Health Institute, Morogoro, United Republic of Tanzania., Kweyamba PA; Environmental Health, and Ecological Sciences Department, Ifakara Health Institute, Morogoro, United Republic of Tanzania.; Swiss Tropical and Public Health Institute, Kreuzstrasse 2, 4123, Allschwil, Switzerland.; University of Basel, Petersplatz 1, 4001, Basel, Switzerland., Mwanga EP; Environmental Health, and Ecological Sciences Department, Ifakara Health Institute, Morogoro, United Republic of Tanzania.; School of Biodiversity, One Health and Veterinary Medicine, The University of Glasgow, Glasgow, UK., Tambwe MM; Environmental Health, and Ecological Sciences Department, Ifakara Health Institute, Morogoro, United Republic of Tanzania., Hofer LM; Environmental Health, and Ecological Sciences Department, Ifakara Health Institute, Morogoro, United Republic of Tanzania.; Swiss Tropical and Public Health Institute, Kreuzstrasse 2, 4123, Allschwil, Switzerland.; University of Basel, Petersplatz 1, 4001, Basel, Switzerland., Siria DJ; Environmental Health, and Ecological Sciences Department, Ifakara Health Institute, Morogoro, United Republic of Tanzania.; School of Biodiversity, One Health and Veterinary Medicine, The University of Glasgow, Glasgow, UK., González-Jiménez M; School of Biodiversity, One Health and Veterinary Medicine, The University of Glasgow, Glasgow, UK.; School of Chemistry, The University of Glasgow, Glasgow, G128QQ, UK., Wynne K; School of Chemistry, The University of Glasgow, Glasgow, G128QQ, UK., Moore SJ; Environmental Health, and Ecological Sciences Department, Ifakara Health Institute, Morogoro, United Republic of Tanzania.; Swiss Tropical and Public Health Institute, Kreuzstrasse 2, 4123, Allschwil, Switzerland.; University of Basel, Petersplatz 1, 4001, Basel, Switzerland.; School of Life Sciences and Biotechnology, Nelson Mandela African Institution of Science and Technology, Arusha, United Republic of Tanzania., Okumu F; Environmental Health, and Ecological Sciences Department, Ifakara Health Institute, Morogoro, United Republic of Tanzania.; School of Biodiversity, One Health and Veterinary Medicine, The University of Glasgow, Glasgow, UK.; School of Life Sciences and Biotechnology, Nelson Mandela African Institution of Science and Technology, Arusha, United Republic of Tanzania.; School of Public Health, The University of the Witwatersrand, Park Town, Johannesburg, South Africa., Babayan SA; School of Biodiversity, One Health and Veterinary Medicine, The University of Glasgow, Glasgow, UK., Baldini F; Environmental Health, and Ecological Sciences Department, Ifakara Health Institute, Morogoro, United Republic of Tanzania.; School of Biodiversity, One Health and Veterinary Medicine, The University of Glasgow, Glasgow, UK. |
المصدر: | Malaria journal [Malar J] 2024 Jun 17; Vol. 23 (1), pp. 188. Date of Electronic Publication: 2024 Jun 17. |
نوع المنشور: | Journal Article |
اللغة: | English |
بيانات الدورية: | Publisher: BioMed Central Country of Publication: England NLM ID: 101139802 Publication Model: Electronic Cited Medium: Internet ISSN: 1475-2875 (Electronic) Linking ISSN: 14752875 NLM ISO Abbreviation: Malar J Subsets: MEDLINE |
أسماء مطبوعة: | Original Publication: London : BioMed Central, [2002- |
مواضيع طبية MeSH: | Malaria, Falciparum*/diagnosis , Malaria, Falciparum*/blood , Malaria, Falciparum*/parasitology , Plasmodium falciparum*/isolation & purification, Humans ; Parasitemia/diagnosis ; Parasitemia/parasitology ; Anemia/diagnosis ; Anemia/blood ; Anemia/parasitology ; Spectrophotometry, Infrared/methods ; Machine Learning ; Parasite Load ; Adult ; Artificial Intelligence ; Sensitivity and Specificity ; Female ; Young Adult ; Spectroscopy, Fourier Transform Infrared/methods ; Adolescent ; Male ; Middle Aged ; Mass Screening/methods |
مستخلص: | Background: Effective testing for malaria, including the detection of infections at very low densities, is vital for the successful elimination of the disease. Unfortunately, existing methods are either inexpensive but poorly sensitive or sensitive but costly. Recent studies have shown that mid-infrared spectroscopy coupled with machine learning (MIRs-ML) has potential for rapidly detecting malaria infections but requires further evaluation on diverse samples representative of natural infections in endemic areas. The aim of this study was, therefore, to demonstrate a simple AI-powered, reagent-free, and user-friendly approach that uses mid-infrared spectra from dried blood spots to accurately detect malaria infections across varying parasite densities and anaemic conditions. Methods: Plasmodium falciparum strains NF54 and FCR3 were cultured and mixed with blood from 70 malaria-free individuals to create various malaria parasitaemia and anaemic conditions. Blood dilutions produced three haematocrit ratios (50%, 25%, 12.5%) and five parasitaemia levels (6%, 0.1%, 0.002%, 0.00003%, 0%). Dried blood spots were prepared on Whatman ™ filter papers and scanned using attenuated total reflection-Fourier Transform Infrared (ATR-FTIR) for machine-learning analysis. Three classifiers were trained on an 80%/20% split of 4655 spectra: (I) high contrast (6% parasitaemia vs. negative), (II) low contrast (0.00003% vs. negative) and (III) all concentrations (all positive levels vs. negative). The classifiers were validated with unseen datasets to detect malaria at various parasitaemia levels and anaemic conditions. Additionally, these classifiers were tested on samples from a population survey in malaria-endemic villages of southeastern Tanzania. Results: The AI classifiers attained over 90% accuracy in detecting malaria infections as low as one parasite per microlitre of blood, a sensitivity unattainable by conventional RDTs and microscopy. These laboratory-developed classifiers seamlessly transitioned to field applicability, achieving over 80% accuracy in predicting natural P. falciparum infections in blood samples collected during the field survey. Crucially, the performance remained unaffected by various levels of anaemia, a common complication in malaria patients. Conclusion: These findings suggest that the AI-driven mid-infrared spectroscopy approach holds promise as a simplified, sensitive and cost-effective method for malaria screening, consistently performing well despite variations in parasite densities and anaemic conditions. The technique simply involves scanning dried blood spots with a desktop mid-infrared scanner and analysing the spectra using pre-trained AI classifiers, making it readily adaptable to field conditions in low-resource settings. In this study, the approach was successfully adapted to field use, effectively predicting natural malaria infections in blood samples from a population-level survey in Tanzania. With additional field trials and validation, this technique could significantly enhance malaria surveillance and contribute to accelerating malaria elimination efforts. (© 2024. The Author(s).) |
References: | Malar J. 2018 Oct 19;17(1):371. (PMID: 30340592) PNAS Nexus. 2022 Dec 07;1(5):pgac272. (PMID: 36712329) Chem Soc Rev. 2016 Apr 7;45(7):1980-98. (PMID: 26403652) PLoS Negl Trop Dis. 2021 Apr 22;15(4):e0009218. (PMID: 33886567) Anal Chem. 2021 Oct 5;93(39):13302-13310. (PMID: 34558904) Cytokine. 2024 May;177:156559. (PMID: 38412767) J Parasitol. 1979 Jun;65(3):418-20. (PMID: 383936) Am J Trop Med Hyg. 2004 Aug;71(2 Suppl):25-34. (PMID: 15331816) Nat Commun. 2022 Mar 21;13(1):1501. (PMID: 35314683) Malar J. 2020 Nov 4;19(1):392. (PMID: 33148265) J Parasitol. 2005 Jun;91(3):484-6. (PMID: 16108535) Wellcome Open Res. 2019 May 1;4:76. (PMID: 31544155) Sci Rep. 2022 Apr 6;12(1):5802. (PMID: 35388127) Malar J. 2019 Oct 7;18(1):341. (PMID: 31590669) Clin Infect Dis. 2017 May 1;64(9):1221-1227. (PMID: 28369268) BMC Bioinformatics. 2023 Jan 9;24(1):11. (PMID: 36624386) N Engl J Med. 2008 Feb 28;358(9):888-99. (PMID: 18305266) Bull World Health Organ. 1988;66(5):621-6. (PMID: 2463112) Am J Trop Med Hyg. 1999 Sep;61(3):431-8. (PMID: 10497986) Malar J. 2019 Dec 2;18(1):387. (PMID: 31791354) Trop Med Int Health. 2002 Oct;7(10):823-30. (PMID: 12358616) Nat Commun. 2012;3:1237. (PMID: 23212366) Commun Chem. 2021 Sep 9;4(1):129. (PMID: 36697584) Commun Chem. 2020 Dec 10;3(1):178. (PMID: 36703343) medRxiv. 2023 Sep 13;:. (PMID: 37745576) Malar J. 2017 Sep 13;16(1):371. (PMID: 28903758) BMC Public Health. 2021 Jan 28;21(1):239. (PMID: 33509161) Infect Dis Poverty. 2023 Apr 6;12(1):29. (PMID: 37024969) Anal Chem. 2014 May 6;86(9):4379-86. (PMID: 24694036) Clin Microbiol Rev. 2008 Jan;21(1):97-110. (PMID: 18202438) Malar J. 2019 Oct 16;18(1):348. (PMID: 31619246) Malar J. 2023 Nov 10;22(1):346. (PMID: 37950315) Analyst. 2014 Oct 7;139(19):4769-74. (PMID: 25055796) Diseases. 2020 May 20;8(2):. (PMID: 32443811) Anal Chem. 2009 Apr 1;81(7):2516-24. (PMID: 19278236) Clin Microbiol Rev. 2002 Jan;15(1):66-78. (PMID: 11781267) J Clin Pathol. 1994 Aug;47(8):740-2. (PMID: 7962629) J Biomed Opt. 2019 Mar;24(3):1-5. (PMID: 30848110) Sci Rep. 2020 Jul 17;10(1):11930. (PMID: 32681115) |
معلومات مُعتمدة: | Through Swiss TPH Rudolf Geigy Foundation; Through Swiss TPH Rudolf Geigy Foundation; OPP1099295 Bill and Melinda Gates Foundation; ICA/R1/191238 Royal Society; ICA/R1/191238 Royal Society; ref: SBF007\100094 United Kingdom AMS_ Academy of Medical Sciences |
تواريخ الأحداث: | Date Created: 20240616 Date Completed: 20240616 Latest Revision: 20240619 |
رمز التحديث: | 20240619 |
مُعرف محوري في PubMed: | PMC11181574 |
DOI: | 10.1186/s12936-024-05011-z |
PMID: | 38880870 |
قاعدة البيانات: | MEDLINE |
تدمد: | 1475-2875 |
---|---|
DOI: | 10.1186/s12936-024-05011-z |