Sarcoidosis may be affected by sex, race, and age. A Case Control Etiologic Study of Sarcoidosis (ACCESS) enrolled 736 patients with sarcoidosis within 6 mo of diagnosis from 10 clinical centers in the United States. Using the ACCESS sarcoidosis assessment system, we determined organ involvement for the whole group and for subgroups differentiated by sex, race, and age (less than 40 yr or 40 yr and older). The study population was heterogeneous in terms of race (53% white, 44% black), sex (64% female, 36% male), and age (46% < 40 yr old, 54% > or = 40 yr old). Women were more likely to have eye and neurologic involvement (chi(2) = 4.74, p < 0.05 and chi(2) = 4.60, p < 0.05 respectively), have erythema nodosum (chi(2) = 7.28, p < 0.01), and to be age 40 yr or over (chi(2) = 6.07, p < 0.02) whereas men were more likely to be hypercalcemic (chi(2) = 7.38, p < 0.01). Black subjects were more likely to have skin involvement other than erythema nodosum (chi(2) = 5.47, p < 0.05), and eye (chi(2) = 13.8, p < 0.0001), liver (chi(2) = 23.3, p < 0.0001), bone marrow (chi(2) = 18.8, p < 0.001), and extrathoracic lymph node involvement (chi(2) = 7.21, p < 0.01). We conclude that the initial presentation of sarcoidosis is related to sex, race, and age.

Purpose:The development of computer-aided diagnostic ͑CAD͒ methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography ͑CT͒ scans. The Lung Image Database Consortium ͑LIDC͒ and Image Database Resource Initiative ͑IDRI͒ completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute ͑NCI͒, further advanced by the Foundation for the National Institutes of Health ͑FNIH͒, and accompanied by the Food and Drug Administration ͑FDA͒ through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process. Methods: Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories ͑"noduleՆ 3 mm," "noduleϽ 3 mm," and "non-noduleՆ 3 mm"͒. In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus. Results:The Database contains 7371 lesions marked "nodule" by at least one radiologist. 2669 of these lesions were marked "noduleՆ 3 mm" by at least one radiologist, of which 928 ͑34.7%͒ received such marks from all four radiologists. These 2669 lesions include nodule outlines and subjective nodule characteristic ratings. Conclusions:The LIDC/IDRI Database is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice.

Endobronchial-valve treatment for advanced heterogeneous emphysema induced modest improvements in lung function, exercise tolerance, and symptoms at the cost of more frequent exacerbations of COPD, pneumonia, and hemoptysis after implantation. (Funded by Pulmonx; ClinicalTrials.gov number, NCT00129584.)

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The interpretation of experimental results from functional medical imaging is complicated by intersubject and interspecies differences in airway geometry. The application of computational models in understanding the significance of these differences requires methods for generation of subject-specific geometric models of the bronchial airway tree. In the current study, curvilinear airway centerline and diameter models have been fitted to human and ovine bronchial trees using detailed data segmented from multidetector row X-ray-computed tomography scans. The trees have been extended to model the entire conducting airway system by using a volume-filling algorithm to generate airway centerline locations within detailed volume descriptions of the lungs or lobes. Analysis of the geometry of the scan-based and model-based airways has verified their consistency with measures from previous anatomic studies and has provided new anatomic data for the ovine bronchial tree. With the use of an identical parameter set, the volume-filling algorithm has produced airway trees with branching asymmetry appropriate for the human and ovine lung, demonstrating the dependence of the method on the shape of the lung or lobe volume. The modeling approach that has been developed can be applied to any level of detail of the airway tree and into any volume shape for the lung; hence it can be used directly for different individuals or animals and for any number of scan-based airways. The resulting models are subject-specific computational meshes with anatomically consistent geometry, suitable for application in simulation studies.