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Lavalle S, Scapaticci R, Masiello E, Salerno VM, Cuocolo R, Cannella R, Botteghi M, Orro A, Saggini R, Donati Zeppa S, Bartolacci A, Stocchi V, Piccoli G, Pegreffi F. Beyond the Surface: Nutritional Interventions Integrated with Diagnostic Imaging Tools to Target and Preserve Cartilage Integrity: A Narrative Review. Biomedicines 2025; 13:570. [PMID: 40149547 PMCID: PMC11940242 DOI: 10.3390/biomedicines13030570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2025] [Revised: 02/12/2025] [Accepted: 02/16/2025] [Indexed: 03/29/2025] Open
Abstract
This narrative review provides an overview of the various diagnostic tools used to assess cartilage health, with a focus on early detection, nutrition intervention, and management of osteoarthritis. Early detection of cartilage damage is crucial for effective patient management. Traditional diagnostic tools like radiography and conventional magnetic resonance imaging (MRI) sequences are more suited to detecting late-stage structural changes. This paper highlights advanced imaging techniques, including sodium MRI, T2 mapping, T1ρ imaging, and delayed gadolinium-enhanced MRI of cartilage, which provide valuable biochemical information about cartilage composition, particularly the glycosaminoglycan content and its potential links to nutrition-related factors influencing cartilage health. Cartilage degradation is often linked with inflammation and measurable via markers like CRP and IL-6 which, although not specific to cartilage breakdown, offer insights into the inflammation affecting cartilage. In addition to imaging techniques, biochemical markers, such as collagen breakdown products and aggrecan fragments, which reflect metabolic changes in cartilage, are discussed. Emerging tools like optical coherence tomography and hybrid positron emission tomography-magnetic resonance imaging (PET-MRI) are also explored, offering high-resolution imaging and combined metabolic and structural insights, respectively. Finally, wearable technology and biosensors for real-time monitoring of osteoarthritis progression, as well as the role of artificial intelligence in enhancing diagnostic accuracy through pattern recognition in imaging data are addressed. While these advanced diagnostic tools hold great potential for early detection and monitoring of osteoarthritis, challenges remain in clinical translation, including validation in larger populations and integration into existing clinical workflows and personalized treatment strategies for cartilage-related diseases.
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Affiliation(s)
- Salvatore Lavalle
- Department of Medicine and Surgery, Kore University of Enna, 94100 Enna, Italy; (S.L.); (V.M.S.); (F.P.)
| | - Rosa Scapaticci
- Institute for the Electromagnetic Sensing of the Environment, National Research Council of Italy, 80124 Naples, Italy;
| | - Edoardo Masiello
- Department of Radiology, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
| | - Valerio Mario Salerno
- Department of Medicine and Surgery, Kore University of Enna, 94100 Enna, Italy; (S.L.); (V.M.S.); (F.P.)
| | - Renato Cuocolo
- Department of Medicine, Surgery, and Dentistry, University of Salerno, 84081 Baronissi, Italy;
| | - Roberto Cannella
- Department of Biomedicine, Neuroscience and Advanced Diagnostics, University of Palermo, 90127 Palermo, Italy
| | - Matteo Botteghi
- Experimental Pathology Research Group, Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, 60121 Ancona, Italy;
- Medical Physics Activities Coordination Centre, Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy
| | - Alessandro Orro
- Institute of Biomedical Technologies CNR, Via Fratelli Cervi, 93, 20054 Segrate, Italy;
| | - Raoul Saggini
- Faculty of Psychology, eCampus University, 22060 Novedrate, Italy;
| | - Sabrina Donati Zeppa
- Department of Biomolecular Sciences, University of Urbino Carlo Bo, 61029 Urbino, Italy; (A.B.); (G.P.)
- Department of Human Sciences for the Promotion of Quality of Life, University San Raffaele, 20132 Roma, Italy;
| | - Alessia Bartolacci
- Department of Biomolecular Sciences, University of Urbino Carlo Bo, 61029 Urbino, Italy; (A.B.); (G.P.)
| | - Vilberto Stocchi
- Department of Human Sciences for the Promotion of Quality of Life, University San Raffaele, 20132 Roma, Italy;
| | - Giovanni Piccoli
- Department of Biomolecular Sciences, University of Urbino Carlo Bo, 61029 Urbino, Italy; (A.B.); (G.P.)
| | - Francesco Pegreffi
- Department of Medicine and Surgery, Kore University of Enna, 94100 Enna, Italy; (S.L.); (V.M.S.); (F.P.)
- Recovery and Functional Rehabilitation Unit, Ospedale Umberto I, 94100 Enna, Italy
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Chaudhry MS, Czekanski A. Surface slicing and toolpath planning for in-situbioprinting of skin implants. Biofabrication 2024; 16:025030. [PMID: 38447215 DOI: 10.1088/1758-5090/ad30c4] [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: 06/29/2023] [Accepted: 03/06/2024] [Indexed: 03/08/2024]
Abstract
Bioprinting has emerged as a successful method for fabricating engineered tissue implants, offering great potential for wound healing applications. This study focuses on an advanced surface-based slicing approach aimed at designing a skin implant specifically forin-situbioprinting. The slicing step plays a crucial role in determining the layering arrangement of the tissue during printing. By utilizing surface slicing, a significant shift from planar fabrication methods is achieved. The developed methodology involves the utilization of a customized robotic printer to deliver biomaterials. A multilayer slicing and toolpath generation procedure is presented, enabling the fabrication of skin implants that incorporate the epidermal, dermal, and hypodermal layers. One notable advantage of using the approximate representation of the native wound site surface as the slicing surface is the avoidance of planar printing effects such as staircasing. This surface slicing method allows for the design of non-planar and ultra-thin skin implants, ensuring a higher degree of geometric match between the implant and the wound interface. Furthermore, the proposed methodology demonstrates superior surface quality of thein-situbio-printed implant on a hand model, validating its ability to create toolpaths on implants with complex surfaces.
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Affiliation(s)
| | - Aleksander Czekanski
- Lassonde School of Engineering, York University, 4700 Keele Street, Toronto M3J1P3, Canada
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