{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T16:29:45Z","timestamp":1768408185037,"version":"3.49.0"},"reference-count":70,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2025,1,27]],"date-time":"2025-01-27T00:00:00Z","timestamp":1737936000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia, Portugal","doi-asserted-by":"publisher","award":["DSAIPA\/DS\/0117\/2020"],"award-info":[{"award-number":["DSAIPA\/DS\/0117\/2020"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia, Portugal","doi-asserted-by":"publisher","award":["NeproMD\/ISEL\/2020"],"award-info":[{"award-number":["NeproMD\/ISEL\/2020"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Instituto Polit\u00e9cnico de Lisboa (IPL)","award":["DSAIPA\/DS\/0117\/2020"],"award-info":[{"award-number":["DSAIPA\/DS\/0117\/2020"]}]},{"name":"Instituto Polit\u00e9cnico de Lisboa (IPL)","award":["NeproMD\/ISEL\/2020"],"award-info":[{"award-number":["NeproMD\/ISEL\/2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"abstract":"<jats:p>Background: Kidney transplantation is a life-saving treatment for end-stage kidney disease, but allograft rejection remains a critical challenge, requiring accurate and timely diagnosis. The study aims to evaluate the integration of Fourier Transform Infrared (FTIR) spectroscopy and machine learning algorithms as a minimally invasive method to detect kidney allograft rejection and differentiate between T Cell-Mediated Rejection (TCMR) and Antibody-Mediated Rejection (AMR). Additionally, the goal is to discriminate these rejection types aiming to develop a reliable decision-making support tool. Methods: This retrospective study included 41 kidney transplant recipients and analyzed 81 serum samples matched to corresponding allograft biopsies. FTIR spectroscopy was applied to pre-biopsy serum samples, and Na\u00efve Bayes classification models were developed to distinguish rejection from non-rejection and classify rejection types. Data preprocessing involved, e.g., atmospheric compensation, second derivative, and feature selection using Fast Correlation-Based Filter for spectral regions 600\u20131900 cm\u22121 and 2800\u20133400 cm\u22121. Model performance was assessed via area under the receiver operating characteristic curve (AUC-ROC), sensitivity, specificity, and accuracy. Results: The Na\u00efve Bayes model achieved an AUC-ROC of 0.945 in classifying rejection versus non-rejection and AUC-ROC of 0.989 in distinguishing TCMR from AMR. Feature selection significantly improved model performance, identifying key spectral wavenumbers associated with rejection mechanisms. This approach demonstrated high sensitivity and specificity for both classification tasks. Conclusions: The integration of FTIR spectroscopy with machine learning may provide a promising, minimally invasive method for early detection and precise classification of kidney allograft rejection. Further validation in larger, more diverse populations is needed to confirm these findings\u2019 reliability.<\/jats:p>","DOI":"10.3390\/jcm14030846","type":"journal-article","created":{"date-parts":[[2025,1,28]],"date-time":"2025-01-28T08:57:48Z","timestamp":1738054668000},"page":"846","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Integration of FTIR Spectroscopy and Machine Learning for Kidney Allograft Rejection: A Complementary Diagnostic Tool"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8911-3380","authenticated-orcid":false,"given":"Lu\u00eds","family":"Ramalhete","sequence":"first","affiliation":[{"name":"Blood and Transplantation Center of Lisbon, Instituto Portugu\u00eas do Sangue e da Transplanta\u00e7\u00e3o, Alameda das Linhas de Torres, No. 117, 1769-001 Lisbon, Portugal"},{"name":"NOVA Medical School, Universidade NOVA de Lisboa, 1169-056 Lisbon, Portugal"},{"name":"iNOVA4Health\u2014Advancing Precision Medicine, RG11: Reno-Vascular Diseases Group, NOVA Medical School, Faculdade de Ci\u00eancias M\u00e9dicas, Universidade NOVA de Lisboa, 1169-056 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9369-6486","authenticated-orcid":false,"given":"R\u00faben","family":"Ara\u00fajo","sequence":"additional","affiliation":[{"name":"NOVA Medical School, Universidade NOVA de Lisboa, 1169-056 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0528-2716","authenticated-orcid":false,"given":"Miguel Bigotte","family":"Vieira","sequence":"additional","affiliation":[{"name":"NOVA Medical School, Universidade NOVA de Lisboa, 1169-056 Lisbon, Portugal"},{"name":"Nephrology Department, Hospital Curry Cabral, Unidade Local de Sa\u00fade S\u00e3o Jos\u00e9, 1049-001 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4525-9062","authenticated-orcid":false,"given":"Emanuel","family":"Vigia","sequence":"additional","affiliation":[{"name":"NOVA Medical School, Universidade NOVA de Lisboa, 1169-056 Lisbon, Portugal"},{"name":"Centro Hospitalar Universit\u00e1rio de Lisboa Central, Hepatobiliopancreatic and Transplantation Center\u2014Curry Cabral Hospital, 1069-166 Lisbon, Portugal"}]},{"given":"In\u00eas","family":"Aires","sequence":"additional","affiliation":[{"name":"Nephrology Department, Hospital Curry Cabral, Unidade Local de Sa\u00fade S\u00e3o Jos\u00e9, 1049-001 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3300-6033","authenticated-orcid":false,"given":"An\u00edbal","family":"Ferreira","sequence":"additional","affiliation":[{"name":"NOVA Medical School, Universidade NOVA de Lisboa, 1169-056 Lisbon, Portugal"},{"name":"Nephrology Department, Hospital Curry Cabral, Unidade Local de Sa\u00fade S\u00e3o Jos\u00e9, 1049-001 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5264-9755","authenticated-orcid":false,"given":"Cec\u00edlia R. C.","family":"Calado","sequence":"additional","affiliation":[{"name":"ISEL\u2014Instituto Superior de Engenharia de Lisboa, Instituto Polit\u00e9cnico de Lisboa, R. Conselheiro Em\u00eddio Navarro 1, 1959-007 Lisbon, Portugal"},{"name":"Institute for Bioengineering and Biosciences (iBB), The Associate Laboratory Institute for Health and Bioeconomy\u2013i4HB, Instituto Superior T\u00e9cnico (IST), Universidade de Lisboa (UL), Av. Rovisco Pais, 1049-001 Lisbon, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2025,1,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"471","DOI":"10.2215\/CJN.05021107","article-title":"Kidney Transplantation as Primary Therapy for End-Stage Renal Disease: A National Kidney Foundation\/Kidney Disease Outcomes Quality Initiative (NKF\/KDOQITM) Conference","volume":"3","author":"Abecassis","year":"2008","journal-title":"Clin. J. Am. Soc. 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