Objective. The aim of this study was to analyse the outcomes of single-and multi-level anterior cervical discectomy and fusion (ACDF) with standalone polyetheretherketone (PEEK) cages, with particular emphasis on the risk of secondary adjacent segment disease.Materials and methods. This retrospective study included 30 patients with single-or multi-level cervical disc herniation. Before the ACDF, and one year thereafter, the patients underwent clinical and radiological evaluation including determination of cervical pain severity with a numerical rating scale (NRS), and a survey with a Polish adaptation of the neck disability index questionnaire (NDI-PL). Biomechanical parameters of the cervical spine were determined using the Cobb method.Results. One year after ACDF, all patients had achieved complete fusions, and 97% showed a significant reduction of pain severity. Also, a significant decrease in all NDI-PL indices was observed. A significant decrease in overall cervical spine mobility coexisted with a significant increase in the mobility of the segment above the one operated upon and a non-significant decrease in the mobility of the segment below. No statistically significant change was found in the intervertebral disc space height (IVH) above and below the operated segment, and no evidence of degeneration within the segments adjacent to the operated one was documented. Conclusion.One-and two-level ACDF with standalone PEEK cages provided high fusion rates. Surgical spondylosis contributed to a reduction of spinal mobility despite the hypermobility in adjacent spinal segments. No degeneration in adjacent spinal segments was documented within a year of ACDF, and the treatment seemed to improve patients' quality of life.

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The outbreak of the SARS-CoV-2 pandemic has put healthcare systems worldwide to their limits, resulting in increased waiting time for diagnosis and required medical assistance. With chest radiographs (CXR) being one of the most common COVID-19 diagnosis methods, many artificial intelligence tools for image-based COVID-19 detection have been developed, often trained on a small number of images from COVID-19-positive patients. Thus, the need for high-quality and well-annotated CXR image databases increased. This paper introduces POLCOVID dataset, containing chest X-ray (CXR) images of patients with COVID-19 or other-type pneumonia, and healthy individuals gathered from 15 Polish hospitals. The original radiographs are accompanied by the preprocessed images limited to the lung area and the corresponding lung masks obtained with the segmentation model. Moreover, the manually created lung masks are provided for a part of POLCOVID dataset and the other four publicly available CXR image collections. POLCOVID dataset can help in pneumonia or COVID-19 diagnosis, while the set of matched images and lung masks may serve for the development of lung segmentation solutions.

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