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Study Design: Systemic review and meta-analysis.Objectives: Several studies have reported the impact of accidental dural tears (DT) on the outcome of spinal surgery, some with conflicting results. Therefore, the aim of this study was to carry out a systemic review and meta-analysis of the literature to establish the overall clinical outcome of spinal surgery following accidental DT.Method: A systemic literature search was carried out. Postoperative improvement in Oswestry Disability Index (ODI), Short-Form 36 survey (SF36), leg pain visual analogue scale (VAS), and back pain VAS were compared between patients with and without DT at different time intervals.Results: Eleven studies were included in this meta-analysis. There was a slightly better improvement in ODI and leg VAS score (standardized mean difference of −0.06, 95% confidence interval [CI] −0.12 to −0.01, and −0.06, 95% CI −0.09 to −0.02, respectively) in patients without DT at 12 months postsurgery, but this effect was not demonstrated at any other time intervals up to 4 years. There were no differences in the overall SF36 (function) score at any time interval or back pain VAS at 12 months.Conclusion: Based on this study, accidental DT did not have an overall significant adverse impact on the short-term clinical outcome of spinal surgery. More studies are needed to address the long-term impact and other outcome measures including other immediate complications of DT.

Table of Contents Abstract Introduction Patients and Methods Results Discussion Conclusion References Abstract Introduction: The literature supporting routine preoperative MRI scanning in patients with late onset idiopathic scoliosis is less [...]

Scoliosis has a detrimental effect on lung function. Since spine radiographs are commonly used for monitoring the progress of the disorder, semi-automated lung field segmentation from scoliosis radiographs is a primary step in further automation and processing. Existing lung field segmentation algorithms have been developed specifically for chest radiographs, which differ from spine radiographs in imaging aspects and appearance. The present work uses intensity profile processing followed by the optimization of a flexible polynomial template developed without prior training data. Right and left lungs are processed separately due to the presence of the cardiac shadow and differences in lung shape. Intensity profile processing is based on identification of the maxima and minima in segments of the horizontal profiles or their derivatives. The polynomial template represents an implicit shape model defined separately for each lung using three initial points chosen by the user. Thus, a unique template is generated for each case. The algorithm was tested on six sets of patient radiographs varying in severity of scoliosis and image quality. The proposed method successfully detects overlapping regions of the lung and the spine and has high accuracy even for severely deformed lungs.