Pediatric Bone Age Assessment Using Deep Convolutional Neural Networks

Skeletal bone age assessment is a common clinical practice to diagnose endocrine and metabolic disorders in child development. In this paper, we describe a fully automated deep learning approach to the problem of bone age assessment using data from Pediatric Bone Age Challenge organized by RSNA 2017. The dataset for this competition is consisted of 12.6k radiological images of left hand labeled by the bone age and sex of patients. Our approach utilizes several deep learning architectures: U-Net, ResNet-50, and custom VGG-style neural networks trained end-to-end. We use images of whole hands as well as specific parts of a hand for both training and inference. This approach allows us to measure importance of specific hand bones for the automated bone age analysis. We further evaluate performance of the method in the context of skeletal development stages. Our approach outperforms other common methods for bone age assessment.Comment: 14 pages, 9 figure

Chemical Modification of Polaronic States in Anatase TiO2(101)

Two polymorphs of TiO2, anatase and rutile, are employed in photocatalytic applications. It is broadly accepted that anatase is the more catalytically active and subsequently finds wider commercial use. In this work, we focus on the Ti3+ polaronic states of anatase TiO2(101), which lie at ∼1.0 eV binding energy and are known to increase catalytic performance. Using UV-photoemission and two-photon photoemission spectroscopies, we demonstrate the capability to tune the excited state resonance of polarons by controlling the chemical environment. Anatase TiO2(101) contains subsurface polarons which undergo sub-band-gap photoexcitation to states ∼2.0 eV above the Fermi level. Formic acid adsorption dramatically influences the polaronic states, increasing the binding energy by ∼0.3 eV. Moreover, the photoexcitation oscillator strength changes significantly, resonating with states ∼3.0 eV above the Fermi level. We show that this behavior is likely due to the surface migration of subsurface oxygen vacancies

Photoexcitation of bulk polarons in rutile TiO₂

The excitation of surface-localized polaronic states has recently been discussed as an additional photocatalytic channel to band gap excitation for rutile Ti O 2 . A contribution from photoexcitation of bulk polarons could, in principle, provide a greater contribution because of their higher number and their protection from oxidation. However, determining such a contribution to the photoyield is challenging and has not been achieved thus far. Here we use two photon photoemission spectroscopy measurements to separate bulk and surface polaron photoexcitation. We find that bulk polarons are less bound by 0.2 eV compared with polarons at the surface, consistent with our results of hybrid density functional theory calculations. Because the excited state is also shifted to higher energy, bulk polarons have the same photoexcitation resonance energy as at the surface (3.6 eV) with a threshold at 3.1 eV. This is degenerate with the band gap, suggesting that bulk polarons could also provide an additional contribution to the photoyield

Influence of supramolecular forces on the linear viscoelasticity of gluten

Stress relaxation behavior of hydrated gluten networks was investigated by means of rheometry combined with μ-computed tomography (μ-CT) imaging. Stress relaxation behavior was followed over a wide temperature range (0–70 °C). Modulation of intermolecular bonds was achieved with urea or ascorbic acid in an effort to elucidate the presiding intermolecular interactions over gluten network relaxation. Master curves of viscoelasticity were constructed, and relaxation spectra were computed revealing three relaxation regimes for all samples. Relaxation commences with a well-defined short-time regime where Rouse-like modes dominate, followed by a power law region displaying continuous relaxation concluding in a terminal zone. In the latter zone, poroelastic relaxation due to water migration in the nanoporous structure of the network also contributes to the stress relief in the material. Hydrogen bonding between adjacent protein chains was identified as the determinant force that influences the relaxation of the networks. Changes in intermolecular interactions also resulted in changes in microstructure of the material that was also linked to the relaxation behavior of the networks

Mechanical behaviour of biodegradable AZ31 magnesium alloy after long term in vitro degradation

Biodegradable magnesium alloys including AZ31 are exciting candidates for temporary implants as they eliminate the requirement for surgical removal, yet have higher mechanical properties than degradable polymers. However, the very long term mechanical properties and degradation of these alloys have not been fully characterized. The tensile, bending and corrosion behaviour of biodegradable AZ31 Mg alloy specimens have been investigated for up to 9 months in vitro in phosphate buffered saline (PBS). Small AZ31 Mg specimens showed a significant drop in bend yield strength and modulus after 3 months in vitro degradation and an average mass loss of 6.1%. Larger dumbbell specimens showed significant drops in tensile strength from 251.96 ± 3.53 MPa to 73.5 ± 20.2 MPa and to 6.43 ± 0.9 MPa and in modulus from 47.8 ± 5.6GPa to 25.01 ± 3.4GPa and 2.36 ± 0.89GPa after 3 and 9 months respectively. These reductions were accompanied by an average mass loss of 18.3% in 9 months. Degradation rate for the small and large specimens followed similar profiles with immersion time, with peak degradation rates of 0.1747 g m− 2 h−1 and 0.0881 g m− 2 h−1, and average rates of 0.1038 g m− 2 h−1 and 0.0397 g m− 2 h−1 respectively. SEM fractography and polished specimen cross-sections revealed corrosion pits, cracks and corrosion induced defects. These data indicate the potential of AZ31 Mg for use in implants that require medium term degradation with load bearing mechanical properties

Revisiting protein aggregation as pathogenic in sporadic Parkinson and Alzheimer diseases.

The gold standard for a definitive diagnosis of Parkinson disease (PD) is the pathologic finding of aggregated α-synuclein into Lewy bodies and for Alzheimer disease (AD) aggregated amyloid into plaques and hyperphosphorylated tau into tangles. Implicit in this clinicopathologic-based nosology is the assumption that pathologic protein aggregation at autopsy reflects pathogenesis at disease onset. While these aggregates may in exceptional cases be on a causal pathway in humans (e.g., aggregated α-synuclein in SNCA gene multiplication or aggregated β-amyloid in APP mutations), their near universality at postmortem in sporadic PD and AD suggests they may alternatively represent common outcomes from upstream mechanisms or compensatory responses to cellular stress in order to delay cell death. These 3 conceptual frameworks of protein aggregation (pathogenic, epiphenomenon, protective) are difficult to resolve because of the inability to probe brain tissue in real time. Whereas animal models, in which neither PD nor AD occur in natural states, consistently support a pathogenic role of protein aggregation, indirect evidence from human studies does not. We hypothesize that (1) current biomarkers of protein aggregates may be relevant to common pathology but not to subgroup pathogenesis and (2) disease-modifying treatments targeting oligomers or fibrils might be futile or deleterious because these proteins are epiphenomena or protective in the human brain under molecular stress. Future precision medicine efforts for molecular targeting of neurodegenerative diseases may require analyses not anchored on current clinicopathologic criteria but instead on biological signals generated from large deeply phenotyped aging populations or from smaller but well-defined genetic-molecular cohorts

A paediatric bone index derived by automated radiogrammetry

Hand radiographs are obtained routinely to determine bone age of children. This paper presents a method that determines a Paediatric Bone Index automatically from such radiographs. The Paediatric Bone Index is designed to have minimal relative standard deviation (7.5%), and the precision is determined to be 1.42%. Introduction We present a computerised method to determine bone mass of children based on hand radiographs, including a reference database for normal Caucasian children. Methods Normal Danish subjects (1,867), of ages 7-17, and 531 normal Dutch subjects of ages 5-19 were included. Historically, three different indices of bone mass have been used in radiogrammetry all based on A = pi TW(1 - T/W), where T is the cortical thickness and W the bone width. The indices are the metacarpal index A/W-2, DXR-BMD=A/W, and Exton-Smith's index A/(WL), where L is the length of the bone. These indices are compared with new indices of the form A/((WLb)-L-a), and it is argued that the preferred index has minimal SD relative to the mean value at each bone age and sex. Finally, longitudinal series of X-rays of 20 Japanese children are used to derive the precision of the measurements. Results The preferred index is A/((WL0.33)-L-1.33), which is named the Paediatric Bone Index, PBI. It has mean relative SD 7.5% and precision 1.42%. Conclusions As part of the BoneXpert method for automated bone age determination, our method facilitates retrospective research studies involving validation of the proposed index against fracture incidence and adult bone mineral densit

Rural to Urban Migration and Changes in Cardiovascular risk Factors in Tanzania: A Prospective Cohort Study.

High levels of rural to urban migration are a feature of most African countries. Our aim was to investigate changes, and their determinants, in cardiovascular risk factors on rural to urban migration in Tanzania. Men and women (15 to 59 years) intending to migrate from Morogoro rural region to Dar es Salaam for at least 6 months were identified. Measurements were made at least one week but no more than one month prior to migration, and 1 to 3 monthly after migration. Outcome measures included body mass index, blood pressure, fasting lipids, and self reported physical activity and diet. One hundred and three men, 106 women, mean age 29 years, were recruited and 132 (63.2%) followed to 12 months. All the figures presented here refer to the difference between baseline and 12 months in these 132 individuals. Vigorous physical activity declined (79.4% to 26.5% in men, 37.8% to 15.6% in women, p < 0.001), and weight increased (2.30 kg men, 2.35 kg women, p < 0.001). Intake of red meat increased, but so did the intake of fresh fruit and vegetables. HDL cholesterol increased in men and women (0.24, 0.25 mmoll-1 respectively, p < 0.001); and in men, not women, total cholesterol increased (0.42 mmoll-1, p = 0.01), and triglycerides fell (0.31 mmoll-1, p = 0.034). Blood pressure appeared to fall in both men and women. For example, in men systolic blood pressure fell by 5.4 mmHg, p = 0.007, and in women by 8.6 mmHg, p = 0.001. The lower level of physical activity and increasing weight will increase the risk of diabetes and cardiovascular disease. However, changes in diet were mixed, and may have contributed to mixed changes in lipid profiles and a lack of rise in blood pressure. A better understanding of the changes occurring on rural to urban migration is needed to guide preventive measures

Estimation of progression of multi-state chronic disease using the Markov model and prevalence pool concept

<p>Abstract</p> <p>Background</p> <p>We propose a simple new method for estimating progression of a chronic disease with multi-state properties by unifying the prevalence pool concept with the Markov process model.</p> <p>Methods</p> <p>Estimation of progression rates in the multi-state model is performed using the E-M algorithm. This approach is applied to data on Type 2 diabetes screening.</p> <p>Results</p> <p>Good convergence of estimations is demonstrated. In contrast to previous Markov models, the major advantage of our proposed method is that integrating the prevalence pool equation (that the numbers entering the prevalence pool is equal to the number leaving it) into the likelihood function not only simplifies the likelihood function but makes estimation of parameters stable.</p> <p>Conclusion</p> <p>This approach may be useful in quantifying the progression of a variety of chronic diseases.</p