T he scientific, academic, medical and data science communities have come together in the face of the COVID-19 pandemic crisis to rapidly assess novel paradigms in artificial intelligence (AI) that are rapid and secure, and potentially incentivize data sharing and model training and testing without the usual privacy and data ownership hurdles of conventional collaborations 1,2 . Healthcare providers, researchers and industry have pivoted their focus to address unmet and critical clinical needs created by the crisis, with remarkable results [3][4][5][6][7][8][9] . Clinical trial recruitment has been expedited and facilitated by national regulatory bodies and an international cooperative spirit 10-12 . The data analytics and AI disciplines have always fostered open

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W e performed MRI on 16 patients who had had reconstruction of the anterior cruciate ligament (ACL) with a mid-third bone-patellar-tendon-bone autograft. Our aim was to assess the tendon and the site of its insertion at an average of seven years after the original operation. In four of these patients biopsies were taken from the donor site when they had revision of their original operation.MRI showed reconstitution of the tendon into the patellar defect with no evidence of bone formation. Six patients had a persistent defect in the patellar tendon itself. Histological examination of the biopsies of the donor site showed an indirect pattern of insertion with absence of the normal fibrocartilage zone. These morphological changes may adversely affect the biomechanical properties of the healed donor site and we suggest that another graft taken from this site may not be suitable for use in a further operation for reconstruction of the ACL.

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