Purpose of Review Heterotopic ossification (HO) in hip arthroscopy is a common post-operative complication. This review was undertaken to provide an update (2014 present) on the current literature regarding HO in hip arthroscopy. Recent Findings Risk factors for HO post-hip arthroscopy include male gender, mixed impingement, picture, and the size of CAM resection. HO prophylaxis with NSAIDs has been proven to decrease the rate of HO post-hip arthroscopy; however, there is inherent risk to long-standing NSAIDs therapy. HO post-hip arthroscopy is not uncommon as a radiological finding, but symptomatic HO post-hip arthroscopy requiring revision surgery is a rare event, at < 1%. The outcomes for revision surgery for HO excision have fair outcomes. Summary The hip arthroscopist should stratify their patients based on known risk factors, and determine whether NSAIDs prophylaxis is warranted.

BackgroundA dominating focus of the theory of medicine has been the interplay of facts, values and emotions. The quantitative evaluation of this ªmØnage à troisº seems to be especially important in the ethics and economy of diagnostic and interventional radiology. Traditionally, making a diagnosis and postulating alternative diagnoses has been understood as an intellectual challenge and epistemological performance which is restricted to facts and precludes subjective moments. Contemporary costefficiency analyses challenge this presumption. A diagnostic test cannot be judged purely on the amount of information it provides and its ability to classify disease states. Questions of knowledge and experience in diagnosis are closely linked with subsequent diagnostic and/ or therapeutic measures. Consequently, rigid testing efficacy and contributions of imaging procedures to the case management process, clinical appropriateness' evaluation and clinical effectiveness' appraisal have become mandatory for responsible diagnostic radiology [1,2].Interest in cost-effectiveness analyses of interventional radiology is continuously growing. But the answers are sparse. The appropriate models, such as the five-or six-stage evaluative hierarchy according to Maisey and Hutton [3] and Fryback and Thornbury [4], respectively, are well-known and widely accepted,and the tools for statistical evaluation, such as decision trees or Markov analyses, easily accessible. The use of decision trees is well established in the analysis of clinical management problems. Decision models integrate the available evidence and can analyse the effects of varying assumptions. They may be preferentially used to determine the medium-term effects and expenditures to explore the effect of improved treatment results, and to evaluate the myriad of sequences and logical combinations. But decision trees can quickly become very complex, even when considering narrow areas such as the comparison of different diagnostic or therapeutic strategies for a given disease. Now as before, most trials stop at determining technical and diagnostic performance and fail to proceed in measuring diagnostic and therapeutic impact, thereby ignoring that assessment of the effects of an interventional procedure, be it diagnostic or therapeutic or both, depends on the evaluation of a chain of events between its application and any potential influence on the disease ± and the diseased. The post-interventional fate of the patient will be settled outside the department of radiology, mostly without the chance of exerting additional influence for the radiologist and dominated by the therapeutic decision of the clinicians. Thus, the traces left by the intervention will disappear sooner or later, mostly sooner than might be expected. But we ought to follow the tracks, if we wish to be accepted as clinical radiologists. Surgeons, internists and the other cooperating colleagues will not take care of the outcome analysis for us, and if sociologists and epidemiologists get started on this task, they...