Order of importance of anatomical risk factors in Kienböck's disease: An artificial neural network study.

Anatomical variations in bony structures around the wrist have been considered as risk factors for Kienböck's disease: ulnar variance, Nattrass index, ulnar variance/capitate height ratio and presence of a lunohamate joint. This study aimed to assess the order of importance of these variations as risk factors for Kienböck's disease. Two groups were formed: patients (n = 58) and controls (n = 235). On posteroanterior radiographs in the two groups, these risk factors were examined by four raters. After inter-rater correlation analysis, an artificial neural network was used to estimate their relative importance. All parameters showed statistically significant inter-rater correlation (p < 0.05). The artificial neural network study showed that the three most important risk factors, in descending order, were: Nattrass index, ulnar variance/capitate height ratio and negative ulnar variance. The study determined the order of importance of the anatomical risk factors for Kienböck's disease measurable on posteroanterior wrist radiographs. Although these findings seem to be useful in the diagnostic algorithm of Kienböck's disease, multivariate analysis of all measurable risk factors is still needed. The artificial neural network approach could contribute to such a comprehensive study.

Effect of internal carotid artery aberrations on the distance between styloid process and carotid artery / Efecto de las variaciones de la arteria carótida interna en la distancia entre el proceso estiloides y la arteria carótida

SUMMARY: The objective of this study was to evaluate the role of the variations of carotid artery course on the relationship between styloid process (SP) and internal carotid artery (ICA). Carotid CT angiography scans of 170 patients were retrospectively evaluated. The variability of the course of ICA were classified. The length and medial angulation of the SP were measured on coronal 3D images. On axial images, the shortest distance between the bone edge of the SP and ICA were measured. The distance between SP and ICA among the course patterns of carotid artery were compared statistically. In the comparison of distances between SP and ICA with respect to the course of ICA, the difference between straight and curving (p <0.001) was statistically significant. Curving caused the separation of ICA and SP. The highest and the shortest distance was at the curving and coiling group, respectively. We found that SP-ICA distance has a positive and negative correlation with SP angle (p<0.001) and SP length (p<0.001), respectively. The course of ICA is one of the major determinants affecting the relationship of ICA and SP. The curving pattern of ICA has a tendency to increase the distance between SP and ICA.

RESUMEN: El objetivo de este estudio fue evaluar el rol de las variaciones que tiene el curso de la arteria carótida en la relación entre el proceso estiloides (PE) y la arteria carótida interna (ACI). Se evaluaron retrospectivamente angiografías por tomografía computarizada carotídea de 170 pacientes. Se clasificó la variabilidad del curso de ACI. Se midieron en imágenes coronales y en 3D la longitud y la angulación medial del PE. En las imágenes axiales, se midió la distancia más corta entre el margen del PE y la ACI. Se comparó estadísticamente la distancia entre PE y la ACI entre los patrones de trayecto de la arteria carótida. La comparación de las distancias entre PE y la ACI respecto al curso de ACI, fue estadísticamente significativa, siendo la diferencia entre arterias recta y curva (p <0,001). La arteria curva provocó la separación de la ACI y del PE. Las mayores y menores distancias estaban en el grupo de arterias curvas y enrolladas, respectivamente. La distancia PE-ACI tiene una correlación positiva y negativa con el ángulo PE (p <0,001) y la longitud del PE (p <0,001), respectivamente. El curso de la arteria carótida interna es uno de los principales determinantes que afectan la relación con el proceso estiloides. El patrón de curva de la ACI tiende a aumentar la distancia entre PE y la propia arteria arteria.

[Computer Aided Diagnosis system of breast ultrasound based on support vector machine: a clinical analysis].

Objective: To investigate the value of based on support vector machine (SVM) breast ultrasonography technology of Computer-Assisted diagnosis (CAD) for differential diagnosis of benign and malignant breast masses. Methods: Total of 143 patients who had 151 breast masses were collected in Fujian Maternity and Children Health Hospital or The Fist Affiliated Hospital of Fujian Medical University from June 2014 to December 2015. Based on pathological results as the gold standard, the diagnostic efficiency of CAD and ultrasonography were compared. Results: The sensitivity, specificity, accuracy, positive predictive value and negative predictive value of ultrasonography were 80.1%, 71.0%, 76.8%, 80.0% and 72.1%, respectively. And the sensitivity, specificity, accuracy, positive predictive value and negative predictive value of CAD were 96.6%, 90.3%, 94.0%, 93.5% and 94.9%, respectively. The specificity, accuracy, positive predictive value and negative predictive of CAD technology were significantly higher than those of ultrasonography (P<0.05). The area under the receiver operator characteristic curve of ultrasonography and CAD were 0.759 and 0.935 respectively, with significant difference (P<0.05). Conclusions: CAD has a higher specificity and accuracy rate than ultrasonography in the diagnosis of breast masses. It could help to differentiate benign from malignant breast masses.