Deep learning method for aortic root detection

Background: Computed tomography angiography (CTA) is a preferred imaging technique for a wide range of vascular diseases. However, extensive manual analysis is required to detect and identify several anatomical landmarks for clinical application. This study demonstrates the feasibility of a fully automatic method for detecting the aortic root, which is a key anatomical landmark in this type of procedure. The approach is based on the use of deep learning techniques that attempt to mimic expert behavior. Methods: A total of 69 CTA scans (39 for training and 30 for validation) with different pathology types were selected to train the network. Furthermore, a total of 71 CTA scans were selected independently and applied as the test set to assess their performance. Results: The accuracy was evaluated by comparing the locations marked by the method with benchmark locations (which were manually marked by two experts). The interobserver error was 4.6 ± 2.3 mm. On an average, the differences between the locations marked by the two experts and those detected by the computer were 6.6 ± 3.0 mm and 6.8 ± 3.3 mm, respectively, when calculated using the test set. Conclusions: From an analysis of these results, we can conclude that the proposed method based on pre-trained CNN models can accurately detect the aortic root in CTA images without prior segmentationThis work was partially financed by Consellería de Cultura, Educación e Universidade (reference 2019–2021, ED431C 2018/19)S

Automatic detection of pulmonary nodules: Evaluation of performance using two different MDCT scanners

The purpose of this study was to evaluate the diagnostic performance of a computer-aided diagnosis (CAD) system, on the detection of pulmonary nodules in multidetector row computed tomography (MDCT) images, by using two different MDCT scanners. The computerized scheme was based on the iris filter. We have collected CT cases of patients with pulmonary nodules. We have included in the study one hundred and thirty-two calcified and noncalcified nodules, measuring 4-30 mm in diameter. CT examinations were performed by using two different equipments: a CT scanner (SOMATOM Emotion 6), and a dual-source computed tomography system (SOMATOM Definition) (Siemens Medical System, Forchheim, Germany), with the following parameters: collimation, 6x1.0mm (Emotion 6); and 64×0.6mm (Definition); 100-130 kV; 70-110 mAs. Data were reconstructed with a slice thickness of 1.25mm (Emotion 6) and 1mm (Definition). True positive cases were determined by an independent interpretation of the study by three experienced chest radiologists, the panel decision being used as the reference standard. Free-response Receiver Operating Characteristic curves, sensitivity and number of false-positive per scan, were calculated. Our CAD scheme, for the test set of the study, yielded a sensitivity of 80%, with an average of 5.2 FPs per examination. At an average false positive rate of 9 per scan, our CAD scheme achieved sensitivities of 94% for all nodules, 94.5% for solid, 80% for non-solid, 84% for spiculated, and 97% for non-spiculated nodules. These encouraging results suggest that our CAD system, advocated as a second reader, may help radiologists in the detection of lung nodules in MDCTThis work has been partially supported by the Xunta de Galicia (expte. nº PGIDIT06BTF20802PR), and by the FIS (expte. nº PI060058) and (expte. nº PI080072)S

Trend di ospedalizzazione nell’asma dell’adulto: effetto di età e genere

Background: Hospital admissions due to asthma are a reliable source of information on the morbidity of the disease which, after the increase observed in the last quarter of the last century, shows a declining trend in the last few years. The aim of this study was to look at hospital admission trends due to asthma in our community and analyze some of its associated factors. Methods: Retrospective analysis of all hospital admissions involving adults aged 15 years and older with asthma as the primary or secondary diagnosis (if the first diagnosis was respiratory failure or respiratory infection) in Public Health Service hospitals in the Galician region of Spain between the years 1995-2009 (total 24,766 admissions). Results: The majority of patients admitted were female (71%), over 60 years of age (64%), and admission occurred predominantly in the winter months. The hospitalization rate due to asthma tripled over the period studied, this being mainly accounted for by women aged over 60 years. Mean hospital stay was 9.2 days, longer in older patients or those admitted over the weekend. Conclusions: A significant increase in hospital admissions due to asthma over the last few years has been observed in our community, mainly involving older women. The mean stay seems long, increasing with patients' age and admission over the weekend.Razionale: I ricoveri ospedalieri dovuti ad asma sono una fonte d’informazione attendibile sulla morbilità della patologia che, dopo un incremento osservato nell’ultimo quarto del secolo scorso, è in fase di declino negli ultimi anni. Scopo di questo studio era descrivere i trend di ospedalizzazione per asma nella nostra comunità ed analizzare alcuni dei fattori associati. Metodi: Analisi retrospettiva di tutte le ospedalizzazioni di adulti dai 15 anni in su per asma come diagnosi primaria, o come diagnosi secondaria in caso la prima diagnosi fosse insufficienza respiratoria o un’infezione respiratoria, in ospedali pubblici della regione Galizia della Spagna tra gli anni 1995 e 2009 (totale dei ricoveri: 24.766). Risultati: La maggioranza dei pazienti ricoverati erano femmine (71%), di età superiore a 60 anni (64%) e la maggior parte degli accessi avveniva nella stagione invernale. Il tasso di ospedalizzazione per asma è triplicato nel periodo studiato, soprattutto per le donne di età superiore a 60 anni. La durata media del ricovero era di 9,2 giorni, più prolungata nei pazienti più anziani ed in coloro che erano ricoverati nel fine settimana. Conclusioni: Un significativo incremento delle ospedalizzazioni per asma negli ultimi anni è stato osservato nella nostra comunità, soprattutto a carico delle donne più anziane. La durata media del ricovero appare lunga ed aumenta con l’età del paziente e nei ricoveri del fine settimana.S