Data Workflow in Large Scale Simulations of Blood Flow in Aneurysms

Aneurysms are responsibile for significant morbidity and mortality, and there is a need for an increased understanding of all the aspects of the natural history of these lesions. We are currently working to extend our analyses with the goal of creating models of aneurysmal progression that are able to predict rupture risk through the description of the evolving geometry, structure, properties, and loads. Realization of patient specific models of the blood circulation necessitates a complex computationally and data intensive procedure that starts from the collection of medical images in a clinical setting and encompasses several stages of data processing on (and transfer to and from) specialized hardware, which include high-performance and visualization clusters as well as consumer workstations and local drives for final storage

Observability of Rembrandt scarp with Mercury radio science experiment

Il lavoro presentato ha come scopo la determinazione dell sensibilità di stima della anomali gravitazionali nell'emisfero sud di Mercurio per mezzo dell'esperimento di radio scienza della futura missione europea BepiColombo a Mercurio.The radio science experiment of the ESA mission BepiColombo (MORE, Mercury Orbiter Radio science Exper- iment) is devoted to the estimation of Mercury’s gravity field with unprecedented accuracy, by means of highly stable, multi-frequency radio links in X and Ka band, provided by the Ka band transponder (KaT) on-board the Mercury Planetary Orbiter (MPO). The estimation of gravity field coefficients and planetary tidal deformation with radio science experiment will provide fundamental constraints for modelling planet interior, but additional analysis can be carried out in order to verify whether radio science can give a significant contribution in the study of other physical phenomena, like for example crustal thickening due to tectonic phenomena. This work reports the accuracy obtainable by the MORE experiment

Model order reduction for left ventricular mechanics via congruency training

Computational models of the cardiovascular system and specifically heart function are currently being investigated as analytic tools to assist medical practice and clinical trials. To achieve clinical utility, models should be able to assimilate the diagnostic multi-modality data available for each patient and generate consistent representations of the underlying cardiovascular physiology. While finite element models of the heart can naturally account for patient-specific anatomies reconstructed from medical images, optimizing the many other parameters driving simulated cardiac functions is challenging due to computational complexity. With the goal of streamlining parameter adaptation, in this paper we present a novel, multifidelity strategy for model order reduction of 3-D finite element models of ventricular mechanics. Our approach is centered around well established findings on the similarity between contraction of an isolated muscle and the whole ventricle. Specifically, we demonstrate that simple linear transformations between sarcomere strain (tension) and ventricular volume (pressure) are sufficient to reproduce global pressure-volume outputs of 3-D finite element models even by a reduced model with just a single myocyte unit. We further develop a procedure for congruency training of a surrogate low-order model from multiscale finite elements, and we construct an example of parameter optimization based on medical images. We discuss how the presented approach might be employed to process large datasets of medical images as well as databases of echocardiographic reports, paving the way towards application of heart mechanics models in the clinical practice. © 2020 Di Achille et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.19-14- 00134Russell Sage Foundation, RSFSK and OS were funded by RSF (http:// www.rscf.ru/en/) as described below. Part of this work was carried out within the framework of the IIF UrB RAS government assignment and was partially supported by the UrFU Competitiveness Enhancement Program (agreement 02. A03.21.0006) as well as the RSF grant (No. 19-14- 00134). The Uran supercomputer at IMM UrB RAS was used for part of the model calculations. IBM provided support in the form of salaries for authors PA, JP, JK and VG but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the "author contributions" section

Biochemomechanics of intraluminal thrombus in abdominal aortic aneurysms

Most computational models of abdominal aortic aneurysms address either the hemodynamics within the lesion or the mechanics of the wall. More recently, however, some models have appropriately begun to account for the evolving mechanics of the wall in response to the changing hemodynamic loads. Collectively, this large body of work has provided tremendous insight into this life-threatening condition and has provided important guidance for current research. Nevertheless, there has yet to be a comprehensive model that addresses the mechanobiology, biochemistry, and biomechanics of thrombus-laden abdominal aortic aneurysms. That is, there is a pressing need to include effects of the hemodynamics on both the development of the nearly ubiquitous intraluminal thrombus and the evolving mechanics of the wall, which depends in part on biochemical effects of the adjacent thrombus. Indeed, there is increasing evidence that intraluminal thrombus in abdominal aortic aneurysms is biologically active and should not be treated as homogeneous inert material. In this review paper, we bring together diverse findings from the literature to encourage next generation models that account for the biochemomechanics of growth and remodeling in patient-specific, thrombus-laden abdominal aortic aneurysms

Chromosome 5 allelic losses are early events in tumours of the papilla of Vater and occur at sites similar to those of gastric cancer.

During our studies of DNA fingerprinting of tumours of the pancreas and papilla (ampulla) of Vater, using arbitrarily primed polymerase chain reaction (AP-PCR), we noticed two bands showing a decreased intensity in six of ten ampullary tumours with respect to matched normal tissues. Those bands were both assigned to chromosome 5. Such a finding was somewhat in contrast with the reportedly low frequency of APC gene mutations in ampullary cancers, located at chromosome 5q21, and suggested that loci different from that of APC might be the target of chromosome 5 allelic losses (LOH) in these tumours. Therefore, we analysed chromosome 5 LOH in a panel of 27 ampullary tumours, including eight adenomas, four early- and 15 advanced-stage cancers, using 16 PCR-amplified CA microsatellite polymorphic markers spanning the entire chromosome. Nineteen cases (70%) showed LOH, and the interstitial deletions found in these tumours described two smallest common deleted regions, in which putative suppressor genes might reside. They were at 5q13.3-q14 and at 5q23-q31 respectively, which correspond to those found in gastric tumours. In addition, the presence of 5q LOH in six of eight adenomas and in three of four early-stage cancers suggests that such phenomena occur at early stages of neoplastic progression of the ampullary epithelium

Sensory-Glove-Based Open Surgery Skill Evaluation

Manual dexterity is one of the most important surgical skills, and yet there are limited instruments to evaluate this ability objectively. In this paper, we propose a system designed to track surgeons’ hand movements during simulated open surgery tasks and to evaluate their manual expertise. Eighteen participants, grouped according to their surgical experience, performed repetitions of two basic surgical tasks, namely single interrupted suture and simple running suture. Subjects’ hand movements were measured with a sensory glove equipped with flex and inertial sensors, tracking flexion/extension of hand joints, and wrist movement. The participants’ level of experience was evaluated discriminating manual performances using linear discriminant analysis, support vector machines, and artificial neural network classifiers. Artificial neural networks showed the best performance, with a median error rate of 0.61% on the classification of single interrupted sutures and of 0.57% on simple running sutures. Strategies to reduce sensory glove complexity and increase its comfort did not affect system performances substantially