ArticleScientific reports2023
Brillouin-Raman micro-spectroscopy and machine learning techniques to classify osteoarthritic lesions in the human articular cartilage.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.
- Predictive Performance of Raman Spectroscopy in Osteoarthritis: A Systematic Review.Journal of medical systems · 2025Pooled it
- Full vibrational spectroscopy for simultaneous mechanical, structural and chemical analysis.Nature communications · 2026Article
- Exploring the biomechanical complexity of glioblastoma spheroids and organoids with co-localized Brillouin and Raman microspectroscopy.Biochemistry and biophysics reports · 2025Article
- Understanding and measuring mechanical signals in the tumor stroma.FEBS open bio · 2025Review
- Raman spectroscopic probe provides optical biomarkers of cartilage composition predictive of tissue function.Osteoarthritis and cartilage · 2025Article
- Highly Flexible, High-Performance, and Stretchable Piezoelectric Sensor Based on a Hierarchical Droplet-Shaped Ceramics with Enhanced Damage Tolerance.Advanced materials (Deerfield Beach, Fla.) · 2024Article
- An Artificial Neural Network to Eliminate the Detrimental Spectral Shift on Mid-Infrared Gas Spectroscopy.Sensors (Basel, Switzerland) · 2023Article
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Authors and funding
11 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this study, Brillouin and Raman micro-Spectroscopy (BRamS) and Machine Learning were used to set-up a new diagnostic tool for Osteoarthritis (OA), potentially extendible to other musculoskeletal diseases. OA is a degenerative pathology, causing the onset of chronic pain due to cartilage disruption. Despite this, it is often diagnosed late and the radiological assessment during the routine examination may fail to recognize the threshold beyond which pharmacological treatment is no longer sufficient and prosthetic replacement is required. Here, femoral head resections of OA-affected patients were analyzed by BRamS, looking for distinctive mechanical and chemical markers of the progressive degeneration degree, and the result was compared to standard assignment via histological staining. The procedure was optimized for diagnostic prediction by using a machine learning algorithm and reducing the time required for measurements, paving the way for possible future in vivo characterization of the articular surface through endoscopic probes during arthroscopy.
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Registered trials
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