Abstract
Musculoskeletal disorders are the most common reason of chronic pain and disability, representing an enormous socioeconomic burden worldwide. In this review, new biomedical application fields for Raman spectroscopy (RS) technique related to skeletal tissues are discussed, showing that it can provide a comprehensive profile of tissue composition in situ, in a rapid, label-free, and nondestructive manner. RS can be used as a tool to study tissue alterations associated to aging, pathologies, and disease treatments. The main advantage with respect to currently applied methods in clinics is its ability to provide specific information on molecular composition, which goes beyond other diagnostic tools. Being compatible with water, RS can be performed without pretreatment on unfixed, hydrated tissue samples, without any labeling and chemical fixation used in histochemical methods. This review first provides the description of the basic principles of RS as a biotechnology tool and is introduced into the field of currently available RS-based techniques, developed to enhance Raman signals. The main spectral processing, statistical tools, fingerprint identification, and available databases are mentioned. The recent literature has been analyzed for such applications of RS as tendon and ligaments, cartilage, bone, and tissue engineered constructs for regenerative medicine. Several cases of proof-of-concept preclinical studies have been described. Finally, advantages, limitations, future perspectives, and challenges for the translation of RS into clinical practice have been also discussed. Impact statement Raman spectroscopy (RS) is a powerful noninvasive tool giving access to molecular vibrations and characteristics of samples in a wavelength window of 600 to 3200 cm(-1), thus giving access to a molecular fingerprint of biological samples in a nondestructive way. RS could not only be used in clinical diagnostics, but also be used for quality control of tissues and tissue-engineered constructs, reducing number of samples, time, and the variety of analysis required in the quality control chain before implantation.