Prevention of Post mEniscectomy Osteoarthritis: From New Animal Model to Patient pRofiLing

Patient demographic, anamnestic, clinical, radiological and morphological data will be collected and reported in the database PEARL, assigning an individual ID to each patient. The most relevant and abundant miRNAs obtained through the transcriptomic analyses will be included too. Information about age, gender, body mass index, type of meniscal lesion, type of injury (if any), time of symptoms onset, general knee condition, previous surgical and/or pharmacological treatments, co-morbidities will be included too. Subjective knee evaluations of patients will be collected by using internationally accepted PROMs (Patient Reported Outcome Measures) among which IKDC (International Knee Documentation Committee) Objective Score, KOOS (Knee Injury and Osteoarthritis Outcome Score), VAS (Visual Analogue Score) Pain and EQ-5D-5L. All these data will be collected during the pre-surgical visit and on follow up. Two MRIs are planned for the study, during screening visit and at 6 months follow-up visit; at least one of the two MRIs will be performed with a 3D protocol to assess the bone component. Therefore,radiological and morphological data will include standard x-ray and MRI protocol implemented by metadata of 3D MRI protocol (near-isotropic 0.83mm T2 SPACE and near-isotropic 0.63mm proton density SPACE) when needed. Accurate 3D models of femur bone and cartilage, tibia bone and cartilage and menisci will be reconstructed from (near-)isotropic high-resolution 3D MRI scans. For morphology analysis, a 3D DESS MRI sequence will be complemented with modern clinical sequences for diagnostic purposes. Using the reconstructed 3D models, advanced landmark-based and statistical shape analyses will be performed. The extracted shape features from these analyses will then serve as input for conventional statistical algorithms or state-of-the-art machine learning techniques. Finally, the addition of standing full-leg radiographs gives more insights in the biomechanics of the complete lower-limb from hip to toe. Alignment of the femur with respect to the tibia will be evaluated in both coronal and sagittal plane. These alignment variables will then be used as input for conventional statistics and machine learning algorithms both separately and combined with the knee-specific shape features (cf. previous paragraph). Data related to the high-throughput transcriptomic analyses will include the most expressed blood miRNAs for each patients. Data will be generated on the Applied Biosystems' QuantStudio' 12K Flex RealTime PCR System using Expression Suite Software. Quantitation will be assessed by the 'relative threshold' method (Crt method) that sets a threshold for each amplification individually that is based on the shape of the amplification curve. Data normalization will be performed with RefFinder tool that evaluates and screens stable candidates from extensive experimental datasets. After publication, the raw data related to in vitro analyses as well as pre-clinical and clinical anonimazed data will be made available through an open access database. The timing of analysis data of the study will be as follows: 1. Enrollment and treatment of 100 patients with symptomatic degenerative meniscal lesions undergoing partial arthroscopic meniscectomy: 0-12 months. 2. Transcriptomic analysis will be conducted on blood samples collected at the time of surgery from the patients enrolled in the observational clinical study. The final data will be available within six months after the last enrollment. 3. Follow up evaluation: all the patients will be evaluated at 6 and 12 months. The PEARL registry will permit to eventually clinically and radiologically evaluate the patients also beyond the project duration to monitor the possible onset of post-meniscectomy OA also beyond the one year time limit. Their evaluation after the end of the project will strengthen the findings of the study with longer-term evaluation