To make Quantitative Radiology (QR) a reality in radiological practice, computerized body-wide automatic anatomy recognition (AAR) becomes essential. With the goal of building a general AAR system that is not tied to any specific organ system, body region, or image modality, this paper presents an AAR methodology for localizing and delineating all major organs in different body regions based on fuzzy modeling ideas and a tight integration of fuzzy models with an Iterative Relative Fuzzy Connectedness (IRFC) delineation algorithm. The methodology consists of five main steps: (a) gathering image data for both building models and testing the AAR algorithms from patient image sets existing in our health system; (b) formulating precise definitions of each body region and organ and delineating them following these definitions; (c) building hierarchical fuzzy anatomy models of organs for each body region; (d) recognizing and locating organs in given images by employing the hierarchical models; and (e) delineating the organs following the hierarchy. In Step (c), we explicitly encode object size and positional relationships into the hierarchy and subsequently exploit this information in object recognition in Step (d) and delineation in Step (e). Modality-independent and dependent aspects are carefully separated in model encoding. At the model building stage, a learning process is carried out for rehearsing an optimal threshold-based object recognition method. The recognition process in Step (d) starts from large, well-defined objects and proceeds down the hierarchy in a global to local manner. A fuzzy model-based version of the IRFC algorithm is created by naturally integrating the fuzzy model constraints into the delineation algorithm. The AAR system is tested on three body regions – thorax (on CT), abdomen (on CT and MRI), and neck (on MRI and CT) – involving a total of over 35 organs and 130 data sets (the total used for model building and testing). The training and testing data sets are divided into equal size in all cases except for the neck. Overall the AAR method achieves a mean accuracy of about 2 voxels in localizing non-sparse blob-like objects and most sparse tubular objects. The delineation accuracy in terms of mean false positive and negative volume fractions is 2% and 8%, respectively, for non-sparse objects, and 5% and 15%, respectively, for sparse objects. The two object groups achieve mean boundary distance relative to ground truth of 0.9 and 1.5 voxels, respectively. Some sparse objects – venous system (in the thorax on CT), inferior vena cava (in the abdomen on CT), and mandible and naso-pharynx (in neck on MRI, but not on CT) – pose challenges at all levels, leading to poor recognition and/or delineation results. The AAR method fares quite favorably when compared with methods from the recent literature for liver, kidneys, and spleen on CT images. We conclude that separation of modality-independent from dependent aspects, organization of objects in a hierarchy, encoding of object relationship informati...

Umbilical cord blood transplants are now used to treat numerous types of immune- and blood-related disorders and genetic diseases. Cord blood (CB) banks play an important role in these transplants by processing and storing CB units. In addition to their therapeutic potential, these banks raise ethical and regulatory questions, especially in emerging markets in the Arab world. In this article, the authors review CB banking in five countries in the region, Jordan, Saudi Arabia, Egypt, Qatar, and the United Arab Emirates, selected for their different CB banking policies and initiatives. In assessing these case studies, the authors present regional trends and issues, including religious perspectives, policies, and demographic risk factors. This research suggests strong incentives for increasing the number of CB units that are collected from and available to Arab populations. In addition, the deficit in knowledge concerning public opinion and awareness in the region should be addressed to ensure educated decision-making.

Background and Purpose— In randomized stroke trials, central adjudication of a trial’s primary outcome is regularly implemented. However, recent evidence questions the importance of central adjudication in randomized trials. The aim of this review was to compare outcomes assessed by central adjudicators with outcomes assessed by site investigators. Methods— We included randomized stroke trials where the primary outcome had undergone an assessment by site investigators and central adjudicators. We searched MEDLINE, EMBASE, CENTRAL (Cochrane Central Register of Controlled Trials), Web of Science, PsycINFO, and Google Scholar for eligible studies. We extracted information about the adjudication process as well as the treatment effect for the primary outcome, assessed both by central adjudicators and by site investigators. We calculated the ratio of these treatment effects so that a ratio of these treatment effects >1 indicated that central adjudication resulted in a more beneficial treatment effect than assessment by the site investigator. A random-effects meta-analysis model was fitted to estimate a pooled effect. Results— Fifteen trials, comprising 69 560 participants, were included. The primary outcomes included were stroke (8/15, 53%), a composite event including stroke (6/15, 40%) and functional outcome after stroke measured on the modified Rankin Scale (1/15, 7%). The majority of site investigators were blind to treatment allocation (9/15, 60%). On average, there was no difference in treatment effect estimates based on data from central adjudicators and site investigators (pooled ratio of these treatment effects=1.02; 95% CI, [0.95–1.09]). Conclusions— We found no evidence that central adjudication of the primary outcome in stroke trials had any impact on trial conclusions. This suggests that potential advantages of central adjudication may not outweigh cost and time disadvantages in stroke studies if the primary purpose of adjudication is to ensure validity of trial findings.

Background Ischemic optic neuropathy is the most common form of perioperative visual loss, with highest incidence in cardiac and spinal fusion surgery. To date, potential risk factors have been identified in cardiac surgery by only small, single-institution studies. To determine the preoperative risk factors for ischemic optic neuropathy, the authors used the National Inpatient Sample, a database of inpatient discharges for nonfederal hospitals in the United States. Methods Adults aged 18 yr or older admitted for coronary artery bypass grafting, heart valve repair or replacement surgery, or left ventricular assist device insertion in National Inpatient Sample from 1998 to 2013 were included. Risk of ischemic optic neuropathy was evaluated by multivariable logistic regression. Results A total of 5,559,395 discharges met inclusion criteria with 794 (0.014%) cases of ischemic optic neuropathy. The average yearly incidence was 1.43 of 10,000 cardiac procedures, with no change during the study period (P = 0.57). Conditions increasing risk were carotid artery stenosis (odds ratio, 2.70), stroke (odds ratio, 3.43), diabetic retinopathy (odds ratio, 3.83), hypertensive retinopathy (odds ratio, 30.09), macular degeneration (odds ratio, 4.50), glaucoma (odds ratio, 2.68), and cataract (odds ratio, 5.62). Female sex (odds ratio, 0.59) and uncomplicated diabetes mellitus type 2 (odds ratio, 0.51) decreased risk. Conclusions The incidence of ischemic optic neuropathy in cardiac surgery did not change during the study period. Development of ischemic optic neuropathy after cardiac surgery is associated with carotid artery stenosis, stroke, and degenerative eye conditions.