Hans‐Joachim Wilke

Background Intervertebral disc degeneration is frequent in dogs and can be associated with symptoms and functional impairments. The degree of disc degeneration can be assessed on T2‐weighted MRI scans using the Pfirrmann classification scheme, which was developed for the human spine. However, it could also be used to quantify the effectiveness of disc regeneration therapies. We developed and tested a deep learning tool able to automatically score the degree of disc degeneration in dog spines, starting from an existing model designed to process images of human patients. Methods MRI midsagittal scans of 5991 lumbar discs of dog patients were collected and manually evaluated with the Pfirrmann scheme and a modified scheme with transitional grades. A deep learning model was trained to classify the disc images based on the two schemes and tested by comparing its performance with the model processing human images. Results The determination of the Pfirrmann grade showed sensitivities higher than 83% for all degeneration grades, except for grade 5, which is rare in dog spines, and high specificities. In comparison, the correspondent human model had slightly higher sensitivities, on average 90% versus 85% for the canine model. The modified scheme with the fractional grades did not show significant advantages with respect to the original Pfirrmann grades. Conclusions The novel tool was able to accurately and reliably score the severity of disc degeneration in dogs, although with a performance inferior than that of the human model. The tool has potential in the clinical management of disc degeneration in canine patients as well as in longitudinal studies evaluating regenerative therapies in dogs used as animal models of human disorders.

Background Surgical treatment of adolescent idiopathic scoliosis (AIS) is very complex and modern instrumentation techniques offer multiple possibilities. Despite numerous publications, there is no clear consensus on the optimal strategy for the correction of scoliotic deformities. The goal of this study was to summarize the current surgical strategies for specific AIS cases within various countries. Method Thirty‐two experienced scoliosis surgeons from 15 countries were asked to plan surgeries on 12 representative AIS cases. All AIS cases had an indication for surgery. A questionnaire was provided to document surgical planning. The surgeons were provided with the patients' age and sex, together with radiographs in the lateral and sagittal planes during upright standing and in lateral bending to the left and right, as well as with clinical images. The angles of the main spinal curvatures were specified in the questionnaire. The surgeons were asked to specify their preferred classification system, their surgical approach, the planned fusion length, the type of implants, the rod type, and the resection steps. The data were analyzed with respect to the inter‐rater variability, which was quantified using the Fleiss‐Kappa Method. Results There was a good agreement ( k = 0.61) between the surgeons in choosing the Lenke curve type, and a moderate agreement for the lumbar (0.41) and sagittal (0.56) modifiers. The most frequently planned resection procedure was complete facetectomy (67%). The posterior approach was the most commonly (91%) selected strategy to treat AIS. Anterior approaches were chosen most for Lenke 5 type with a rate of 20%. The upper instrumented vertebra (UIV) varied most for Lenke 1, 5, and 6 cases, with a vertebral level discrepancy of up to 10 levels at Lenke 6. The lowest instrumented vertebra varied most for Lenke 1 and 4 by up to five levels. Polyaxial screws were chosen most (56%), followed by monoaxial (20%) and uniplanar (19%) screws and hooks (5%). Conclusions The results highlight the commonalities and discrepancy in the surgical treatment of AIS in between surgeons. The selected LIV and UIV can vary depending on the curve type and surgeon. Hook constructs appear to be generally replaced by transpedicular screws. The survey indicates open questions in the AIS treatment and in the understanding of scoliosis biomechanics.