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The aim of this study was to assess the prevalence of regional and distant metastases from cutaneous squamous cell carcinomas (SCCs) in dogs (n = 11) and cats (n = 9) in a retrospective case series over 36 years (1985-2020), as well as to characterize its macroscopic aspects (location and size), degree of differentiation (well, moderately and poorly differentiated [WD, MD and PD, respectively]) and the rate of cell proliferation, by counting the AgNORs. Immunohistochemistry (IHC) was used to identify patterns of tumour migration and invasion (islands, ribbons, cords, small aggregates, individual cells [fusiform and amoeboid]) and to evaluate the intensity of desmoplasia and the amount of myofibroblasts. The prevalence of metastatic SCCs was 4.39% (21/478), being 3.8% in dog (12/309) and 5.3% in cat (9/169). Metastases affected lymph nodes in all dogs and 66% (6/9) of cats, and less frequently distant organs. Primary tumours predominantly affected the abdominal skin in dogs and the nasal planum in cats. Among the 20 cases, 52% were MDs, 34% were WDs, and 14% were PDs. Histological lesions suggestive of exposure to chronic solar radiation were present in 57% (8/14). The main patterns of tumour migration and invasion were islands for WD SCCs and individual cells for PD SCCs. MD SCCs had a mix of patterns. In cats, individual spindle cells were restricted to PDs. A marked desmoplastic reaction was more associated with PD SCCs and often with MDs. This study highlights that the prevalence of SCC metastases in dogs and cats is predominantly regional. The IHC was essential in the identification of individual fusiform keratinocytes, whose presence in surgical margins may represent a greater risk of recurrence. Although the presence of myofibroblasts was observed in all infiltrative and metastatic tumours, further studies evaluating these cells may be important to better understand their role in the tumour microenvironment of cutaneous SCCs with metastasis in dogs and cats., (© 2023 John Wiley & Sons Ltd.)

Introduction: The correct positioning of the implant in revision total hip arthroplasty (rTHA) is critical to obtaining substantial functional outcomes, and to avoiding complications. Current literature supports three-dimensional (3D)-printed models as potentially useful tools for preplanning, as well as the "do it yourself (DIY)" methodology to reduce both the time and costs of this procedure. However, no study has determined the efficacy of both methods combined in a cohort of patients with severe acetabular defects. In the lack of bibliography, we performed rTHA after preoperative planning by DIY-3D-printed models to evaluate its influence in: 1) the surgical time, 2) the functional scores, 3) the intra and postoperative complications, and 4) the reconstruction of the center of rotation (COR) of the hip., Hypothesis: Preoperative planning through 3D-DIY printed models will both improve the accuracy of the implant positioning, and the surgical time, leading the latter to improved functional scores and reduced complications., Materials & Methods: A comparative study of 21 patients with Paprosky IIB to IIIB acetabular defects who underwent rTHA after 3D-printed model preoperative planning by the DIY method between 2016 and 2019 was conducted. A historical cohort of 24 patients served as the comparator. Surgical time, reconstruction of the COR, functional scores, and complications were analyzed., Results: The mean follow-up was 32.4 (range, 12 to 60) months. All the patients showed significant improvement of the Harris hip score (HHS) after the operation (3D group: 26.58±10.73; control group 22.47±15.43 (p=0.00)). In the 3D-printed model preoperative planning group the mean operation time and the intraoperative complications were significantly lower (156.15±43.03min vs 187.5±54.38min (p=0.045); and 19% vs 62.5% (p=0.003), respectively), and the HHS and patient satisfaction score (PSS) were significantly greater (83.74±8.49 vs 75.59±11.46 (p=0.019); and 8.17±0.88 vs 7.36±1.17 (p=0.023), respectively). No differences were found in the postoperative complications, nor in the restoration of the COR as determined from the acetabular index, verticalization or horizontalization, although the acetabular index was closer to the intended one in the 3D-printed model planning group (46.67°±7.63 vs 49.22±8.1 (p=0.284))., Conclusion: Preoperative planning of severe acetabular defects through 3D-printed models shortens the surgical time, leading to a decrease in complications and thus to better functional outcomes and greater patient satisfaction. Moreover, the DIY philosophy could decrease both the time and costs of traditional 3D planning., Level of Evidence: III, retrospective case matched study., (Copyright © 2022 Elsevier Masson SAS. All rights reserved.)

Aims: Noncompaction cardiomyopathy (NCC) is considered a genetic cardiomyopathy with unknown pathophysiological mechanisms. We propose to evaluate echocardiographic predictors for rigid body rotation (RBR) in NCC using a machine learning (ML) based model., Methods and Results: Forty-nine outpatients with NCC diagnosis by echocardiography and magnetic resonance imaging (21 men, 42.8±14.8 years) were included. A comprehensive echocardiogram was performed. The layer-specific strain was analyzed from the apical two-, three, four-chamber views, short axis, and focused right ventricle views using 2D echocardiography (2DE) software. RBR was present in 44.9% of patients, and this group presented increased LV mass indexed (118±43.4 vs. 94.1±27.1g/m2, P = 0.034), LV end-diastolic and end-systolic volumes (P< 0.001), E/e' (12.2±8.68 vs. 7.69±3.13, P = 0.034), and decreased LV ejection fraction (40.7±8.71 vs. 58.9±8.76%, P < 0.001) when compared to patients without RBR. Also, patients with RBR presented a significant decrease of global longitudinal, radial, and circumferential strain. When ML model based on a random forest algorithm and a neural network model was applied, it found that twist, NC/C, torsion, LV ejection fraction, and diastolic dysfunction are the strongest predictors to RBR with accuracy, sensitivity, specificity, area under the curve of 0.93, 0.99, 0.80, and 0.88, respectively., Conclusion: In this study, a random forest algorithm was capable of selecting the best echocardiographic predictors to RBR pattern in NCC patients, which was consistent with worse systolic, diastolic, and myocardium deformation indices. Prospective studies are warranted to evaluate the role of this tool for NCC risk stratification., Competing Interests: The authors received no specific funding for this work and the authors have declared that no competing interests exist.