Comparison of In Vivo Stiffness of Tendons Commonly Used for Anterior Cruciate Ligament Reconstruction - A Shear Wave Elastography Study.

RATIONALE AND OBJECTIVES: There are currently no studies investigating the in vivo stiffness of the most commonly used autografts for anterior cruciate ligament reconstruction (ACLR) using Shear wave elastography (SWE). We hypothesize that there are differences regarding the elastic properties between the three tendons commonly used for ACLR and that they are influenced by patient-related factors. MATERIALS AND METHODS: 80 healthy subjects (25 females, 55 males, age: 25.33 ± 4.76 years, BMI: 23.76 ± 3.14 kg/m2, 40 semiprofessional athletes, athlete group [AG], age: 25.51 [19-29]; 40 healthy controls, control group [CG], age: 25.50 [20-29]) were recruited as participants. In addition to patient reported outcome scores, every participant underwent a standardized multimodal ultrasound protocol consisting of B-mode-ultrasound (B-US), Color Doppler-ultrasound (CD-US) and a SWE examination of the bilateral quadriceps tendon (QT), patellar tendon (PT) and semitendinosus tendon (ST). RESULTS: The highest shear wave velocity (SWV) were observed in ST (4.88 (4.35-5.52) m/s, ST vs QT, p = 0.005; ST vs PT, p < 0.001) followed by QT (4.61 (4.13-5.26) m/s, QT vs PT, p < 0.001) and PT (3.73 (3.30-4.68) m/s). Median QT, PT and ST stiffness was significantly higher in AG compared to CG. Male subjects tend to have stiffer QT and PT than female subjects. Positive correlation with SWV was obtained for age and activity level. CONCLUSION: There are significant differences regarding in vivo tendon stiffness between the most frequently used autograft tendon options for ACLR. The quantitative information obtained by SWE could be of particular interest for graft choice for ACLR.

Allografts for Medial Patellofemoral Ligament (MPFL) Reconstruction in Adolescent Patients with Recurrent Patellofemoral Instability: A Systematic Review.

This systematic review updates the currently available evidence on medial patella-femoral ligament (MPFL) reconstruction using allografts. The outcomes were measured with patient-reported outcome measures (PROMs), redislocation and complication rates. This study was performed according to the 2020 PRISMA guidelines using the PubMed, Scopus, Web of Science databases, accessed in February 2023. Studies examining the clinical outcomes of MPFL reconstruction with allografts in adolescents and children with recurrent patellofemoral instability (PFI) were included. Data from three trials, including 113 surgical procedures in 121 children, were retrieved. 40% (48/121) of the included patients were girls. The mean age of the patients was 14.7 ± 0.8 years, and the mean follow-up length was 38.1 ± 16.5 months. With MPFL allograft reconstruction, the Kujala score improved by 14.7% (p < 0.0001) and the IKDC by 38.8% (p < 0.0001). The rate of dislocations was 5% (6 of 121), reoperation for instability was 11% (13 of 121), and subluxation was 2% (1 of 47). Conclusion: These results encourage the use of allografts for MPFL reconstruction in adolescent patients with recurrent patellofemoral instability. Though patellofemoral instability is common in clinical practice, the current literature lacks clinical evidence on allograft MPFL reconstruction. Additional high-quality investigations are required to properly establish the long-term advantages of allograft MPFL and its complication rate.

Same same but different: A Web-based deep learning application revealed classifying features for the histopathologic distinction of cortical malformations.

OBJECTIVE: The microscopic review of hematoxylin-eosin-stained images of focal cortical dysplasia type IIb and cortical tuber of tuberous sclerosis complex remains challenging. Both entities are distinct subtypes of human malformations of cortical development that share histopathological features consisting of neuronal dyslamination with dysmorphic neurons and balloon cells. We trained a convolutional neural network (CNN) to classify both entities and visualize the results. Additionally, we propose a new Web-based deep learning application as proof of concept of how deep learning could enter the pathologic routine. METHODS: A digital processing pipeline was developed for a series of 56 cases of focal cortical dysplasia type IIb and cortical tuber of tuberous sclerosis complex to obtain 4000 regions of interest and 200 000 subsamples with different zoom and rotation angles to train a neural network. Guided gradient-weighted class activation maps (Guided Grad-CAMs) were generated to visualize morphological features used by the CNN to distinguish both entities. RESULTS: Our best-performing network achieved 91% accuracy and 0.88 area under the receiver operating characteristic curve at the tile level for an unseen test set. Novel histopathologic patterns were found through the visualized Guided Grad-CAMs. These patterns were assembled into a classification score to augment decision-making in routine histopathology workup. This score was successfully validated by 11 expert neuropathologists and 12 nonexperts, boosting nonexperts to expert level performance. SIGNIFICANCE: Our newly developed Web application combines the visualization of whole slide images with the possibility of deep learning-aided classification between focal cortical dysplasia IIb and tuberous sclerosis complex. This approach will help to introduce deep learning applications and visualization for the histopathologic diagnosis of rare and difficult-to-classify brain lesions.