No abstract

Our data revealed a high prevalence of ankylosing spondylitis, axial spondyloarthritis, and inflammatory back pain 20 years after the IBD diagnosis. HLA-B27 but not NOD-2 was a predisposing factor for the inflammatory back disorders in IBD patients. Axial spondyloarthritis was associated with a more chronic active IBD disease course.

There have been very few reports of severe complications accompanied by wire localization of breast lesions, such as transsection of the wire and wire migration to the extramammary sites. This is a report of wire migration into the pulmonary hilus demanding surgical removal.

This randomized clinical trial compares the effectiveness of 3 minimally invasive posterior decompression techniques for lumbar spinal stenosis at 16 public hospitals in Norway.

Purpose The aim was to describe magnetic resonance imaging findings in patients planned for lumbar spinal stenosis surgery. Further, to describe possible associations between MRI findings and patient characteristics with patient reported disability or pain. Methods The NORDSTEN spinal stenosis trial included 437 patients planned for surgical decompression of LSS. The following MRI findings were evaluated before surgery: morphological (Schizas) and quantitative (cross-sectional area) grade of stenosis, disk degeneration (Pfirrmann), facet joint tropism and fatty infiltration of the multifidus muscle. Patients were dichotomized into a moderate or severe category for each radiological parameter classification. A multivariable linear regression analysis was performed to investigate the association between MRI findings and preoperative scores for Oswestry Disability Index, Zurich Claudication Questionnaire and Numeric rating scale for back and leg pain. The following patient characteristics were included in the analysis: gender, age, smoking and weight. Results The percentage of patients with severe scores was as follows: Schizas (C + D) 71.3%, cross-sectional area (< 75 mm2) 86.8%, Pfirrmann (4 + 5) 58.1%, tropism (≥ 15°) 11.9%, degeneration of multifidus muscle (2–4) 83.7%. Regression coefficients indicated minimal changes in severity of symptoms when comparing the groups with moderate and severe MRI findings. Only gender had a significant and clinically relevant association with ODI score. Conclusion In this cross-sectional study, the majority of the patients had MRI findings classified as severe LSS changes, but the findings had no clinically relevant association with patient reported disability and pain at baseline. Patient characteristics have a larger impact on disability and pain than radiological findings. Trial registration www.ClinicalTrials.gov identifier: NCT02007083, registered December 2013.

Primary malignancies in adult brains are globally fatal. Computer vision, especially recent developments in artificial intelligence (AI), have created opportunities to automatically characterize and diagnose tumor lesions in the brain. AI approaches have provided scores of unprecedented accuracy in different image analysis tasks, including differentiating tumor-containing brains from healthy brains. AI models, however, perform as a black box, concealing the rational interpretations that are an essential step towards translating AI imaging tools into clinical routine. An explainable AI approach aims to visualize the high-level features of trained models or integrate into the training process. This study aims to evaluate the performance of selected deep-learning algorithms on localizing tumor lesions and distinguishing the lesion from healthy regions in magnetic resonance imaging contrasts. Despite a significant correlation between classification and lesion localization accuracy (R = 0.46, p = 0.005), the known AI algorithms, examined in this study, classify some tumor brains based on other non-relevant features. The results suggest that explainable AI approaches can develop an intuition for model interpretability and may play an important role in the performance evaluation of deep learning models. Developing explainable AI approaches will be an essential tool to improve human–machine interactions and assist in the selection of optimal training methods.

Purpose To investigate changes in dural sac area after three different posterior decompression techniques in patients undergoing surgery for lumbar spinal stenosis. Summary of background data Decompression of the nerve roots is the main surgical treatment for lumbar spinal stenosis. The aim of this study was to radiologically investigate three commonly used posterior decompression techniques. Methods The present study reports data from one of two multicenter randomized trials included in the NORDSTEN study. In the present trial, involving 437 patients undergoing surgery, we report radiological results after three different midline retaining posterior decompression techniques: unilateral laminotomy with crossover (UL) (n = 146), bilateral laminotomy (BL) (n = 142) and spinous process osteotomy (SPO) (n = 149). MRI was performed before and three months after surgery. The increase in dural sac area and Schizas grade at the most stenotic level was evaluated. Three different predefined surgical indicators of substantial decompression were used: (1) postoperative dural sac area of > 100 mm2, (2) increase in the dural sac area of at least 50% and (3) postoperative Schizas grade A or B. Results No differences between the three surgical groups were found in the mean increase in dural sac area. Mean values were 66.0 (SD 41.5) mm2 in the UL-group, 71.9 (SD 37.1) mm2 in the BL-group and 68.1 (SD 41.0) mm2 in the SPO-group (p = 0.49). No differences in the three predefined surgical outcomes between the three groups were found. Conclusion For patients with lumbar spinal stenosis, the three different surgical techniques provided the same increase in dural sac area. Clinical trial registration The study is registered at ClinicalTrials.gov reference on November 22th 2013 under the identifier NCT02007083.

Background Magnetic Resonance Imaging (MRI) is an important tool in preoperative evaluation of patients with lumbar spinal stenosis (LSS). Reported reliability of various MRI findings in LSS varies from fair to excellent. There are inconsistencies in the evaluated parameters and the methodology of the studies. The purpose of this study was to evaluate the reliability of the preoperative MRI findings in patients with LSS between musculoskeletal radiologists and orthopaedic spine surgeons, using established evaluation methods and imaging data from a prospective trial. Methods Consecutive lumbar MRI examinations of candidates for surgical treatment of LSS from the Norwegian Spinal Stenosis and Degenerative Spondylolisthesis (NORDSTEN) study were independently evaluated by two musculoskeletal radiologists and two orthopaedic spine surgeons. The observers had a range of experience between six and 13 years and rated five categorical parameters (foraminal and central canal stenosis, facet joint osteoarthritis, redundant nerve roots and intraspinal synovial cysts) and one continuous parameter (dural sac cross-sectional area). All parameters were re-rated after 6 weeks by all the observers. Inter- and intraobserver agreement was assessed by Gwet’s agreement coefficient (AC1) for categorical parameters and Intraclass Correlation Coefficient (ICC) for the dural sac cross-sectional area. Results MRI examinations of 102 patients (mean age 66 ± 8 years, 53 men) were evaluated. The overall interobserver agreement was substantial or almost perfect for all categorical parameters (AC1 range 0.67 to 0.98), except for facet joint osteoarthritis, where the agreement was moderate (AC1 0.39). For the dural sac cross-sectional area, the overall interobserver agreement was good or excellent (ICC range 0.86 to 0.96). The intraobserver agreement was substantial or almost perfect/ excellent for all parameters (AC1 range 0.63 to 1.0 and ICC range 0.93 to 1.0). Conclusions There is high inter- and intraobserver agreement between radiologists and spine surgeons for preoperative MRI findings of LSS. However, the interobserver agreement is not optimal for evaluation of facet joint osteoarthritis. Trial registration www.ClinicalTrials.gov identifier: NCT02007083, registered December 2013.