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L’Imperio V, Ceola S, Cerbelli B, Barreca A, Pagni F. Systemic vasculitis involving the kidney: the nephropathologist's point of view. Pathologica 2024; 116:104-118. [PMID: 38767543 PMCID: PMC11138762 DOI: 10.32074/1591-951x-990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Accepted: 03/01/2024] [Indexed: 05/22/2024] Open
Abstract
Kidneys are often targets of systemic vasculitis (SVs), being affected in many different forms and representing a possible sentinel of an underlying multi-organ condition. Renal biopsy still remains the gold standard for the identification, characterization and classification of these diseases, solving complex differential diagnosis thanks to the combined application of light microscopy (LM), immunofluorescence (IF) and electron microscopy (EM). Due to the progressively increasing complexity of renal vasculitis classification systems (e.g. pauci-immune vs immune complex related forms), a clinico-pathological approach is mandatory and adequate technical and interpretative expertise in nephropathology is required to ensure the best standard of care for our patients. In this complex background, the present review aims at summarising the current knowledge and challenges in the world of renal vasculitis, unveiling the potential role of the introduction of digital pathology in this setting, from the creation of hub-spoke networks to the future application of artificial intelligence (AI) tools to aid in the diagnostic and scoring/classification process.
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Affiliation(s)
- Vincenzo L’Imperio
- Department of Medicine and Surgery, Pathology, IRCCS Fondazione San Gerardo dei Tintori, University of Milano-Bicocca, Italy
| | - Stefano Ceola
- Department of Medicine and Surgery, Pathology, IRCCS Fondazione San Gerardo dei Tintori, University of Milano-Bicocca, Italy
| | - Bruna Cerbelli
- Department of Medical Surgical Sciences and Biotechnologies, Sapienza University of Rome, Rome, Italy
| | - Antonella Barreca
- Pathology Unit, Città della Salute e della Scienza di Torino University Hospital, Turin, Italy
| | - Fabio Pagni
- Department of Medicine and Surgery, Pathology, IRCCS Fondazione San Gerardo dei Tintori, University of Milano-Bicocca, Italy
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Sharma VJ, Singh A, Grant JL, Raman J. Point-of-care diagnosis of tissue fibrosis: a review of advances in vibrational spectroscopy with machine learning. Pathology 2024; 56:313-321. [PMID: 38341306 DOI: 10.1016/j.pathol.2023.11.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 09/24/2023] [Accepted: 11/01/2023] [Indexed: 02/12/2024]
Abstract
Histopathology is the gold standard for diagnosing fibrosis, but its routine use is constrained by the need for additional stains, time, personnel and resources. Vibrational spectroscopy is a novel technique that offers an alternative atraumatic approach, with short scan times, while providing metabolic and morphological data. This review evaluates vibrational spectroscopy for the assessment of fibrosis, with a focus on point-of-care capabilities. OVID Medline, Embase and Cochrane databases were systematically searched using PRISMA guidelines for search terms including vibrational spectroscopy, human tissue and fibrosis. Studies were stratified based on imaging modality and tissue type. Outcomes recorded included tissue type, machine learning technique, metrics for accuracy and author conclusions. Systematic review yielded 420 articles, of which 14 were relevant. Ten of these articles considered mid-infrared spectroscopy, three dealt with Raman spectroscopy and one with near-infrared spectroscopy. The metrics for detecting fibrosis were Pearson correlation coefficients ranging from 0.65-0.98; sensitivity from 76-100%; specificity from 90-99%; area under receiver operator curves from 0.83-0.98; and accuracy of 86-99%. Vibrational spectroscopy identified fibrosis in myeloproliferative neoplasms in bone, cirrhotic and hepatocellular carcinoma in liver, end-stage heart failure in cardiac tissue and following laser ablation for acne in skin. It also identified interstitial fibrosis as a predictor of early renal transplant rejection in renal tissue. Vibrational spectroscopic techniques can therefore accurately identify fibrosis in a range of human tissues. Emerging data show that it can be used to quantify, classify and provide data about the nature of fibrosis with a high degree of accuracy with potential scope for point-of-care use.
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Affiliation(s)
- Varun J Sharma
- Brian F. Buxton Department of Cardiac and Thoracic Aortic Surgery, Austin Health, Heidelberg, Melbourne, Vic, Australia; Department of Surgery (Austin Health), Melbourne Medical School, The University of Melbourne, Vic, Australia; Spectromix Laboratory, Melbourne, Vic, Australia
| | - Aashima Singh
- Department of Surgery (Austin Health), Melbourne Medical School, The University of Melbourne, Vic, Australia; Melbourne Medical School, The University of Melbourne, Vic, Australia
| | | | - Jaishankar Raman
- Brian F. Buxton Department of Cardiac and Thoracic Aortic Surgery, Austin Health, Heidelberg, Melbourne, Vic, Australia; Department of Surgery (Austin Health), Melbourne Medical School, The University of Melbourne, Vic, Australia; Spectromix Laboratory, Melbourne, Vic, Australia; Department of Cardiac Surgery, St Vincent's Hospital, Fitzroy, Melbourne, Vic, Australia.
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Monach PA. The Future of Vasculitis: A Manifesto. Rheum Dis Clin North Am 2023; 49:713-729. [PMID: 37331742 DOI: 10.1016/j.rdc.2023.03.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Predictions for a general path forward in vasculitis care and research are provided based on advances made in the past 20 years. Prospects for advances in translational research with potential to improve care are highlighted, including identification of hemato-inflammatory diseases, autoantigens, disease mechanisms in animal models, and biomarkers. A list of active randomized trials is provided, and areas of potential paradigm shifts in care are highlighted. The importance of patient involvement and international collaboration is noted, and a plea is made for innovative trial designs that would improve access of patients to trials and to clinical experts at referral centers.
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Affiliation(s)
- Paul A Monach
- Rheumatology Section, VA Boston Healthcare System, 150 South Huntington Avenue, Boston, MA 01230, USA.
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Delrue C, Speeckaert MM. The Potential Applications of Raman Spectroscopy in Kidney Diseases. J Pers Med 2022; 12:jpm12101644. [PMID: 36294783 PMCID: PMC9604710 DOI: 10.3390/jpm12101644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 09/09/2022] [Accepted: 09/29/2022] [Indexed: 12/23/2022] Open
Abstract
Raman spectroscopy (RS) is a spectroscopic technique based on the inelastic interaction of incident electromagnetic radiation (from a laser beam) with a polarizable molecule, which, when scattered, carries information from molecular vibrational energy (the Raman effect). RS detects biochemical changes in biological samples at the molecular level, making it an effective analytical technique for disease diagnosis and prognosis. It outperforms conventional sample preservation techniques by requiring no chemical reagents, reducing analysis time even at low concentrations, and working in the presence of interfering agents or solvents. Because routinely utilized biomarkers for kidney disease have limitations, there is considerable interest in the potential use of RS. RS may identify and quantify urinary and blood biochemical components, with results comparable to reference methods in nephrology.
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Affiliation(s)
- Charlotte Delrue
- Department of Nephrology, Ghent University Hospital, 9000 Ghent, Belgium
| | - Marijn M. Speeckaert
- Department of Nephrology, Ghent University Hospital, 9000 Ghent, Belgium
- Research Foundation-Flanders (FWO), 1000 Brussels, Belgium
- Correspondence: ; Tel.: +32-9-332-4509
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