Comparison of Comprehensive Morphological and Radiomics Features of Subsolid Pulmonary Nodules to Distinguish Minimally Invasive Adenocarcinomas and Invasive Adenocarcinomas in CT Scan

ObjectiveTo investigative the diagnostic performance of the morphological model, radiomics model, and combined model in differentiating invasive adenocarcinomas (IACs) from minimally invasive adenocarcinomas (MIAs).MethodsThis study retrospectively involved 307 patients who underwent chest computed tomography (CT) examination and presented as subsolid pulmonary nodules whose pathological findings were MIAs or IACs from January 2010 to May 2018. These patients were randomly assigned to training and validation groups in a ratio of 4:1 for 10 times. Eighteen categories of morphological features of pulmonary nodules including internal and surrounding structure were labeled. The following radiomics features are extracted: first-order features, shape-based features, gray-level co-occurrence matrix (GLCM) features, gray-level size zone matrix (GLSZM) features, gray-level run length matrix (GLRLM) features, and gray-level dependence matrix (GLDM) features. The chi-square test and F1 test selected morphology features, and LASSO selected radiomics features. Logistic regression was used to establish models. Receiver operating characteristic (ROC) curves evaluated the effectiveness, and Delong analysis compared ROC statistic difference among three models.ResultsIn validation cohorts, areas under the curve (AUC) of the morphological model, radiomics model, and combined model of distinguishing MIAs from IACs were 0.88, 0.87, and 0.89; the sensitivity (SE) was 0.68, 0.81, and 0.83; and the specificity (SP) was 0.93, 0.79, and 0.87. There was no statistically significant difference in AUC between three models (p > 0.05).ConclusionThe morphological model, radiomics model, and combined model all have a high efficiency in the differentiation between MIAs and IACs and have potential to provide non-invasive assistant information for clinical decision-making.

Classifying Ruptured Middle Cerebral Artery Aneurysms With a Machine Learning Based, Radiomics-Morphological Model: A Multicentral Study

ObjectiveRadiomics and morphological features were associated with aneurysms rupture. However, the multicentral study of their predictive power for specific-located aneurysms rupture is rare. We aimed to determine robust radiomics features related to middle cerebral artery (MCA) aneurysms rupture and evaluate the additional value of combining morphological and radiomics features in the classification of ruptured MCA aneurysms.MethodsA total of 632 patients with 668 MCA aneurysms (423 ruptured aneurysms) from five hospitals were included. Radiomics and morphological features of aneurysms were extracted on computed tomography angiography images. The model was developed using a training dataset (407 patients) and validated with the internal (152 patients) and external validation (73 patients) datasets. The support vector machine method was applied for model construction. Optimal radiomics, morphological, and clinical features were used to develop the radiomics model (R-model), morphological model (M-model), radiomics-morphological model (RM-model), clinical-morphological model (CM-model), and clinical-radiomics-morphological model (CRM-model), respectively. A comprehensive nomogram integrating clinical, morphological, and radiomics predictors was generated.ResultsWe found seven radiomics features and four morphological predictors of MCA aneurysms rupture. The R-model obtained an area under the receiver operating curve (AUC) of 0.822 (95% CI, 0.776, 0.867), 0.817 (95% CI, 0.744, 0.890), and 0.691 (95% CI, 0.567, 0.816) in the training, temporal validation, and external validation datasets, respectively. The RM-model showed an AUC of 0.848 (95% CI, 0.810, 0.885), 0.865 (95% CI, 0.807, 0.924), and 0.721 (95% CI, 0.601, 0.841) in the three datasets. The CRM-model obtained an AUC of 0.856 (95% CI, 0.820, 0.892), 0.882 (95% CI, 0.828, 0.936), and 0.738 (95% CI, 0.618, 0.857) in the three datasets. The CRM-model and RM-model outperformed the CM-model and M-model in the internal datasets (p < 0.05), respectively. But these differences were not statistically significant in the external dataset. Decision curve analysis indicated that the CRM-model obtained the highest net benefit for most of the threshold probabilities.ConclusionRobust radiomics features were determined related to MCA aneurysm rupture. The RM-model exhibited good ability in classifying ruptured MCA aneurysms. Integrating radiomics features into conventional models might provide additional value in ruptured MCA aneurysms classification.

SIMULATION OF LARGE AGGREGATE PARTICLES SYSTEM WITH A NEW MORPHOLOGICAL MODEL

For the development of a new porous material such as catalytic carrier, the control of the textural properties is of fundamental importance. In order to move towards rational synthesis, it is necessary to better understand the physical phenomena that generate a defined solid structure. A contribute to this purpose can be achieved by studying the aggregation process inside colloidal suspensions, leading to porosity generation: this phenomenon can be described with a Brownian dynamics model that, for any set of chemical parameters, gives access to the mass distribution and the fractal dimension of colloidal aggregates. However, this model cannot be used for the simulation of large colloidal systems, due to its high computational time, limiting comparison with analytical methods, which probe the whole multi-scale system. This problem is solved by developing a new aggregation morphological model, wherein the fractal dimension is tuned with two compactness parameters. An efficient simulation algorithm is proposed in case of spheres, for which the fractal dimension of the generated aggregates varies between 1.2 and 3. Brownian dynamics results are used to parametrize this purely geometric model, in order to constrain the size and the morphology of the aggregates created. The large numerical solid will be representative of the textural properties of a real solid and will give more information on the porous network. It could be used, for example, to simulate diffusive transport coupled with chemical reaction and to study the impact of the geometry of the porous system on the catalytic performance.

Тhe operability analysis of spindle-motor hybrid electromechanical systems

Motor-spindles are belong to a special class of complex dynamic systems of natural and natural-anthropogenic origin, which can be realized both translational and rotational motion, and represent a variety of developing species. Such systems are used in metalworking complexes, lathes, milling, drilling, grinding, multi-purpose and other machines. In modern designs of spindle units rolling bearings, hydrostatic, hydrodynamic, gas-static (aerostatic), gas-dynamic (aerodynamic), magnetic bearings and their combinations (hybrids) are used, for example, gas-magnetic (gas-static bearings with a magnetic suspension that allows to provide rotational frequencies) up to 10-20 thousand rpm, and in drilling and milling and grinding up to 100-200 thousand rpm and above. With the further development of technology in the machine-building industry, motor-spindles began to appear, which are able to realize the movement of the feed by means of gears and couplings, using pneumatic systems. They are also able to realize the movement of in using hydraulic systems, using screw gears. The design concepts of hybrid and combined the motor spindles, received by results of structural anticipation on the basis of use of innovative synthesis methods of hybrid electromechanical systems are considered. Results of mechanical calculations of rigidity and electromagnetic calculations are presented in the article. On the ground of the calculation data the operability analysis of the electromechanical systems of motor spindles is made. To develop a morphological model, functional features were selected, which are systematized and divided into three groups in accordance with the modular principle.

Going round the twist—an empirical analysis of shell coiling in helicospiral gastropods

The logarithmic helicospiral has been the most widely accepted model of regularly coiled molluscan form since it was proposed by Moseley and popularized by Thompson and Raup. It is based on an explicit assumption that shells are isometric and grow exponentially, and an implicit assumption that the external form of the shell follows the internal shape, which implies that the parameters of the spiral could be reconstructed from the external whorl profile. In this contribution, we show that these assumptions fail on all 25 gastropod species we examine. Using a dataset of 176 fossil and modern gastropod shells, we construct an empirical morphospace of coiling using the parameters of whorl expansion rate, translation rate, and rate of increasing distance from coiling axis, plus rate of aperture shape change, from their best-fit models. We present a case study of change in shell form through geologic time in the austral family Struthiolariidae to demonstrate the utility of our approach for evolutionary paleobiology. We fit various functions to the shell-coiling parameters to demonstrate that the best morphological model is not the same for each parameter. We present a set of R routines that will calculate helicospiral parameters from sagittal sections through coiled shells and allow workers to compare models and choose appropriate sets of parameters for their own datasets. Shell-form parameters in the Struthiolariidae highlight a hitherto neglected hypothesis of relationship between Antarctic Perissodonta and the enigmatic Australian genus Tylospira that fits the biogeographic and stratigraphic distribution of both genera.

Differential Patterns of Gyral and Sulcal Morphological Changes During Normal Aging Process

The cerebral cortex is a highly convoluted structure with distinct morphologic features, namely the gyri and sulci, which are associated with the functional segregation or integration in the human brain. During the lifespan, the brain atrophy that is accompanied by cognitive decline is a well-accepted aging phenotype. However, the detailed patterns of cortical folding change during aging, especially the changing age-dependencies of gyri and sulci, which is essential to brain functioning, remain unclear. In this study, we investigated the morphology of the gyral and sulcal regions from pial and white matter surfaces using MR imaging data of 417 healthy participants across adulthood to old age (21–92 years). To elucidate the age-related changes in the cortical pattern, we fitted cortical thickness and intrinsic curvature of gyri and sulci using the quadratic model to evaluate their age-dependencies during normal aging. Our findings show that comparing to gyri, the sulcal thinning is the most prominent pattern during the aging process, and the gyrification of pial and white matter surfaces were also affected differently, which implies the vulnerability of functional segregation during aging. Taken together, we propose a morphological model of aging that may provide a framework for understanding the mechanisms underlying gray matter degeneration.

ALGORITHM DEVELOPMENT AND IMPLEMENTATION STEMMATIZATION AND GENERATION OF WORD FORMS OF UZBEK LANGUAGE FOR AUTOMATIC PROCESSING SYSTEMS TEXTS

In the thesis, the problem of the morphological model of theUzbek language is solved to create algorithms for the generation andstemmatization of word forms. In the process of work, a morphological model ofthe Uzbek language was built, a dictionary of affixes and their combinationsdescribing inflectional classes was created, and for the development of a webapplication for stemmatization and generation of word forms in the Uzbeklanguage, it was created in order to be included in automatic text processingsystems.

Differential patterns of gyral and sulcal morphological changes during normal aging process

ABSTRACTThe cerebral cortex is a highly convoluted structure with distinct morphologic features, namely the gyri and sulci, which are associated with the functional segregation or integration in the human brain. During the lifespan, the brain atrophy that is accompanied by cognitive decline is a well-accepted aging phenotype. However, the detailed patterns of cortical folding change during aging, especially the changing trajectories of gyri and sulci, which is essential to brain functioning, remain unclear. In this study, we investigated the morphology of the gyral and sulcal regions from pial and white matter surfaces using MR imaging data of 417 healthy participants across the lifespan (21-92y). To elucidate the age-related changes in the cortical pattern, we fitted cortical thickness and intrinsic curvature of gyri and sulci using the quadratic model to evaluate their trajectories during normal aging. Our findings show that comparing to gyri, the sulcal thinning is the most prominent pattern during the aging process, and the gyrification of pial and white matter surfaces were also affected differently, which implies the vulnerability of functional segregation during aging. Taken together, we propose a morphological model of aging that may provide a framework for understanding the mechanisms underlying the gray matter degeneration.