Long-term secular trend of skeletal maturation of Taiwanese children between agricultural (1960s) and contemporary (after 2000s) generations using the Tanner-Whitehouse 3 (TW3) method.

BACKGROUND: The Tanner-Whitehouse (TW) method is one of the well-known techniques in determining the bone age. OBJECTIVE: According to the objectivity of TW3, the secular trend was investigated to discover whether the skeletal maturation of Taiwanese children between two generations was different. SUBJECTS AND METHODS: The large-scale database of Taiwan was collected. The first group, called mid-1960s, included 265 boys and 295 girls in the agricultural generation (between 1966 and 1967). The second group, called mid-2000s, includes 114 boys and 616 girls in the contemporary generation (after 2000s). The bone age was determined by three radiologists using the carpals-only system of the TW3 method and by two physicians using the Greulich and Pyle method. A comparison of the means (independent-samples t-test) was applied by examining the difference of the children's skeletal maturation between the two generations in the same chronological age. The significant difference was considered while the p-value was 0.05 or less (95% confidence interval). RESULTS: A significant difference of the mean bone age (by, on average, three radiologists using the TW3 method) between the mid-1960s and mid-2000s in the same gender and chronological age was presented by the independent-samples t-test (p<0.001 with 95% confidence interval), and the bone age, determined by the TW3 method, of the mid-2000s group was higher than that of the mid-1960s group. This scenario corresponded with the children's bone age determined by pediatricians. Besides, it deserved to notice that the bone age of boys in the mid-2000s was larger than that of the girls in the mid-1960s. Furthermore, by comparing the environmental condition, we suspect that the difference of bone age of children between the two generations was attributed to the discrepancy in nutrition and socioeconomic variation during the four decades in Taiwan. CONCLUSION: The study presents that the secular trend of skeletal maturation of children in the mid-2000s is faster than that in the mid-1960s.

Interrelationship of carpal angle and bone age in children of different generations: a retrospective study.

BACKGROUND: Carpal angle measurement is one of the anthropometrical methods to evaluate the maturation of children. OBJECTIVE: To discuss the relationship between bone age and carpal angle in the maturation of children of two different generations. SUBJECTS AND METHODS: The first group (mid-1960s group) includes 521 Taiwanese children, 196 boys and 325 girls, growing during the agricultural period (between 1966 and 1967). The second group (mid-2000s group) includes 326 children, 74 boys and 252 girls, growing during the mid-2000s. The bone age of both groups was assessed by two leading physicians, and the carpal angle was measured by two senior radiologists. The Mann-Whitney U-test was used to compare the relationship of carpal angle and bone age among eras, sexes, and chronological ages. RESULTS: According to the same chronological age and sexes, the carpal angle of those in the mid-2000s group was larger than that of the mid-1960s group. In addition, in the same chronological age, the results also show that the mean carpal angle of girls in both generations was larger than that of boys. However, it is notable that the carpal angle of boys in the mid-2000s group is larger than that of girls in the mid-1960s group. Furthermore, by comparing the environmental condition, we suspect that the differences between carpal angles of both generation children are caused by the great changes in socioeconomic and nutrition status in Taiwan. CONCLUSION: The study presents a quantitative comparison of carpal angle between two generations of Taiwanese. The preliminary result indicates that the carpal angle for the mid-2000s group is larger than that for the mid-1960s groups.

Simplified radius, ulna, and short bone-age assessment procedure using grouped-Tanner-Whitehouse method.

BACKGROUND: The Tanner-Whitehouse III (TW3) method is popular for assessing children's bone age, but it is time-consuming in clinical settings; to simplify this, a grouped-TW algorithm (GTA) was developed. METHODS: A total of 534 left-hand roentgenograms of subjects aged 2-15 years, including 270 training and 264 testing datasets, were evaluated by a senior pediatrician. Next, GTA was used to choose the appropriate candidate of radius, ulna, and short bones and to classify the bones into three groups by data mining. Group 1 was composed of the maturity pattern of the radius and the middle phalange of the third and fifth digits and three weights were obtained by data mining, yielding a result similar to that of TW3. Subsequently, new bone-age assessment tables were constructed for boys and girls by linear regression and fuzzy logic. In addition, the Bland-Altman plot was utilized to compare accuracy between the GTA, the Greulich-Pyle (GP), and the TW3 method. RESULTS: The relative accuracy between the GTA and the TW3 was 96.2% in boys and 95% in girls, with an error of 1 year, while that between the assessment results of the GP and TW3 was about 87%, with an error of 1 year. However, even if the three weights were not optimally processed, GTA yielded a marginal result with an accuracy of 78.2% in boys and 79.6% in girls. CONCLUSIONS: GTA can efficiently simplify the complexity of the TW3 method, while maintaining almost the same accuracy. The relative accuracy between the assessment results of GTA and GP can also be marginal.

Evaluation of placental maturity by the sonographic textures.

PURPOSE: Routine ultrasound screening to predict gestational age is important for risk assessment of pregnancy complications among pregnant women. We explored a quantitative method for sonographic analysis of placental texture, with the objective of reproducible measurement. METHODS: We studied 151 pregnant women; the gestational ages of their fetuses ranged from 10 to 38 weeks. Three experienced sonographers delineated the placental contour to define the region of interest (ROI). From these sonograms, 72 texture features were derived from the spatial gray-level dependence matrices and gray-level difference matrices. We used these as input variables in a multiple linear regression analysis. RESULTS: A significant positive correlation (P < 0.01) was found between the multiple linear regression results and the corresponding gestation ages by the three assessors (r (A) = 0.755, r (B) = 0.851, and r (C) = 0.832). We also found good agreement between multiple linear regression results for the three observers. Their κ statistic values were 0.685 between assessors A and B, 0.679 between A and C, and 0.804 between B and C. CONCLUSION: Quantitative sonography using texture analysis of the placenta was useful in practice to determine gestational age.

Using Convolutional Neural Networks to Measure the Physiological Age of Caenorhabditis elegans.

Caenorhabditis elegans (C. elegans) is a popular and excellent model for studies of aging due to its short lifespan. Methods for precisely measuring the physiological age of C. elegans are critically needed, especially for antiaging drug screening and genetic screening studies. The effects of various antiaging interventions on the rate of aging in the early stage of the aging process can be determined based on the quantification of physiological age. However, in general, the age of C. elegans is evaluated via human visual inspection of morphological changes based on personal experience and subjective judgment. For example, the rate of motor activity decay has been used to predict lifespan in early- to mid-stage aging. Using image processing, the physiological age of C. elegans can be measured and then classified into periods or classes from childhood to elderhood (e.g., 3 periods comprising days 0-2, 4-6 and 10-12) by using texture entropy (Shamir, L. et al., 2009). Our dataset consists of 913 microscopic images of C. elegans, with approximately 60 images per day from day 1 to day 14 of adulthood. We present quantitative methods to measure the physiological age of C. elegans with convolution neural networks (CNNs), which can measure age with a granularity of days rather than periods. The methods achieved a mean absolute error (MAE) of less than 1 day for the measured age of C. elegans. In our experiments, we found that after training and testing our dataset, 5 popular CNN models, 50-layer residual network (ResNet50), InceptionV3, InceptionResNetV2, 16-layer Visual Geometry Group network (VGG16) and MobileNet, measured the physiological age of C. elegans with an average testing MAE of 1.58 days. Furthermore, based on the results, we propose two models, one model for linear regression analysis and the other model for logistic regression, that combine a CNN model and a new attribute: curved_or_straight. The linear regression analysis model achieved a test MAE of 0.94 days; the logistic regression model achieved an accuracy of 84.78 percent with an error tolerance of 1 day.

Turner syndrome phalangeal screening based on a two-stage linear regression concept.

BACKGROUND: Turner syndrome (TS) is a congenital chromosomal abnormality, resulting in short stature, short fourth metacarpal, and retarded skeletal maturation in children. The existing methods of diagnosis, which include carpal angle, metacarpal sign, and body mass index (BMI), cannot accurately diagnose TS. The authors propose a novel procedure for examining the hand skeleton to distinguish between normal individuals and patients with TS. METHODS: This investigation was divided into two parts. In the first part, existing methods (evaluation of the metacarpal sign, measurement of the carpal angle, and determination of BMI) were used. Examination in the second part was based on the two-stage screening method (TSSM). In the first stage in TSSM, the ratio of the lengths of the distal-middle phalanges of the fifth digit was determined in normal subjects with average range of satisfactory body height and TS patients. A suitable cut-off was found on linear regression and used to divide the plot into TS patients and normal subjects. In the second stage, the normal section was transferred to another group based on bone and chronological ages. A greater number of patients were diagnosed with TS using this method. Finally, four cut-off parameters were determined on linear regression analysis. Results with optimal sensitivity and specificity were automatically obtained. RESULTS: The combination of TSSM with optimal programming (sensitivity = 0.81 and specificity = 0.91) was satisfactory for diagnosing TS patients. CONCLUSION: TSSM can suitably evaluate growth of the hand skeleton to distinguish between normal individuals and patients with TS.

Bone age estimation based on phalanx information with fuzzy constrain of carpals.

The proposed automatic bone age estimation system was based on the phalanx geometric characteristics and carpals fuzzy information. The system could do automatic calibration by analyzing the geometric properties of hand images. Physiological and morphological features are extracted from medius image in segmentation stage. Back-propagation, radial basis function, and support vector machine neural networks were applied to classify the phalanx bone age. In addition, the proposed fuzzy bone age (BA) assessment was based on normalized bone area ratio of carpals. The result reveals that the carpal features can effectively reduce classification errors when age is less than 9 years old. Meanwhile, carpal features will become less influential to assess BA when children grow up to 10 years old. On the other hand, phalanx features become the significant parameters to depict the bone maturity from 10 years old to adult stage. Owing to these properties, the proposed novel BA assessment system combined the phalanxes and carpals assessment. Furthermore, the system adopted not only neural network classifiers but fuzzy bone age confinement and got a result nearly to be practical clinically.

Analysis of closed eyes motion using a wireless eye-mask.

The closed eyes motion strongly depends on the sleep depth of humans. Typically, the electroencephalogram and motion of ciliary muscle's measurement are common methods of evaluating the sleep status and eyeball motion respectively. The proposed survey is to make a wireless eye-mask for monitoring the closed eye motion non-invasively. The mask with CCD unit, wireless module, and an antenna can send the image of closed eye motion into the image-processing module in PC host. The spatial and frequency features from the eye-mask are analyzed to quantitatively describe relative position, velocity, and moving direction of eyelids and eyeballs. Besides, the motion history can feed into the support vector machine neural network and statistics units to evaluate the appropriate time to trigger the alarm if emergency occurs. The survey not only constructs a system with wireless monitoring the closed eye motion non-invasively but develops an algorithm judging whether the closed eye moving or not.

Computerized geometric features of carpal bone for bone age estimation.

BACKGROUND: Bone age development is one of the significant indicators depicting the growth status of children. However, bone age assessment is an heuristic and tedious work for pediatricians. We developed a computerized bone age estimation system based on the analysis of geometric features of carpal bones. METHODS: The geometric features of carpals were extracted and analyzed to judge the bone age of children by computerized shape and area description. Four classifiers, linear, nearest neighbor, back-propagation neural network, and radial basis function neural network, were adopted to categorize bone age. Principal component and discriminate analyses were employed to improve assorting accuracy. RESULTS: The hand X-ray films of 465 boys and 444 girls served as our database. The features were extracted from carpal bone images, including shape, area, and sequence. The proposed normalization area ratio method was effective in bone age classification by simulation. Besides, features statistics showed similar results between the standard of the Greulich and Pyle atlas and our database. CONCLUSIONS: The bone area has a higher discriminating power to judge bone age. The ossification sequence of trapezium and trapezoid bones between Taiwanese and the atlas of the GP method is quite different. These results also indicate that carpal bone assessment with classification of neural networks can be correct and practical.

Integrating Flexible Sensor and Virtual Self-Organizing DC Grid Model With Cloud Computing for Blood Leakage Detection During Hemodialysis.

Blood leakage and blood loss are serious complications during hemodialysis. From the hemodialysis survey reports, these life-threatening events occur to attract nephrology nurses and patients themselves. When the venous needle and blood line are disconnected, it takes only a few minutes for an adult patient to lose over 40% of his / her blood, which is a sufficient amount of blood loss to cause the patient to die. Therefore, we propose integrating a flexible sensor and self-organizing algorithm to design a cloud computing-based warning device for blood leakage detection. The flexible sensor is fabricated via a screen-printing technique using metallic materials on a soft substrate in an array configuration. The self-organizing algorithm constructs a virtual direct current grid-based alarm unit in an embedded system. This warning device is employed to identify blood leakage levels via a wireless network and cloud computing. It has been validated experimentally, and the experimental results suggest specifications for its commercial designs. The proposed model can also be implemented in an embedded system.