Towards Omni-Tomography—Grand Fusion of Multiple Modalities for Simultaneous Interior Tomography

We recently elevated interior tomography from its origin in computed tomography (CT) to a general tomographic principle, and proved its validity for other tomographic modalities including SPECT, MRI, and others. Here we propose “omni-tomography”, a novel concept for the grand fusion of multiple tomographic modalities for simultaneous data acquisition in a region of interest (ROI). Omni-tomography can be instrumental when physiological processes under investigation are multi-dimensional, multi-scale, multi-temporal and multi-parametric. Both preclinical and clinical studies now depend on in vivo tomography, often requiring separate evaluations by different imaging modalities. Over the past decade, two approaches have been used for multimodality fusion: Software based image registration and hybrid scanners such as PET-CT, PET-MRI, and SPECT-CT among others. While there are intrinsic limitations with both approaches, the main obstacle to the seamless fusion of multiple imaging modalities has been the bulkiness of each individual imager and the conflict of their physical (especially spatial) requirements. To address this challenge, omni-tomography is now unveiled as an emerging direction for biomedical imaging and systems biomedicine

The Virtual Physiological Human: Ten Years After

Biomedical research and clinical practice are struggling to cope with the growing complexity that the progress of health care involves. The most challenging diseases, those with the largest socioeconomic impact (cardiovascular conditions; musculoskeletal conditions; cancer; metabolic, immunity, and neurodegenerative conditions), are all characterized by a complex genotype–phenotype interaction and by a “systemic” nature that poses a challenge to the traditional reductionist approach. In 2005 a small group of researchers discussed how the vision of computational physiology promoted by the Physiome Project could be translated into clinical practice and formally proposed the term Virtual Physiological Human. Our knowledge about these diseases is fragmentary, as it is associated with molecular and cellular processes on the one hand and with tissue and organ phenotype changes (related to clinical symptoms of disease conditions) on the other. The problem could be solved if we could capture all these fragments of knowledge into predictive models and then compose them into hypermodels that help us tame the complexity that such systemic behavior involves. In 2005 this was simply not possible—the necessary methods and technologies were not available. Now, 10 years later, it seems the right time to reflect on the original vision, the results achieved so far, and what remains to be done

Biomechanics-based in silico medicine: The manifesto of a new science

In this perspective article we discuss the role of contemporary biomechanics in the light of recent applications such as the development of the so-called Virtual Physiological Human technologies for physiology-based in silico medicine. In order to build Virtual Physiological Human (VPH) models, computer models that capture and integrate the complex systemic dynamics of living organisms across radically different space–time scales, we need to re-formulate a vast body of existing biology and physiology knowledge so that it is formulated as a quantitative hypothesis, which can be expressed in mathematical terms. Once the predictive accuracy of these models is confirmed against controlled experiments and against clinical observations, we will have VPH model that can reliably predict certain quantitative changes in health status of a given patient, but also, more important, we will have a theory, in the true meaning this word has in the scientific method. In this scenario, biomechanics plays a very important role, biomechanics is one of the few areas of life sciences where we attempt to build full mechanistic explanations based on quantitative observations, in other words, we investigate living organisms like physical systems. This is in our opinion a Copernican revolution, around which the scope of biomechanics should be re-defined. Thus, we propose a new definition for our research domain “Biomechanics is the study of living organisms as mechanistic systems”

HD Physiology Project-Japanese efforts to promote multilevel integrative systems biology and physiome research.

The HD Physiology Project is a Japanese research consortium that aimed to develop methods and a computational platform in which physiological and pathological information can be described in high-level definitions across multiple scales of time and size. During the 5 years of this project, an appropriate software platform for multilevel functional simulation was developed and a whole-heart model including pharmacokinetics for the assessment of the proarrhythmic risk of drugs was developed. In this article, we outline the description and scientific strategy of this project and present the achievements and influence on multilevel integrative systems biology and physiome research

SAPHIR - a multi-scale, multi-resolution modeling environment targeting blood pressure regulation and fluid homeostasis.

International audienceWe present progress on a comprehensive, modular, interactive modeling environment centered on overall regulation of blood pressure and body fluid homeostasis. We call the project SAPHIR, for "a Systems Approach for PHysiological Integration of Renal, cardiac, and respiratory functions". The project uses state-of-the-art multi-scale simulation methods. The basic core model will give succinct input-output (reduced-dimension) descriptions of all relevant organ systems and regulatory processes, and it will be modular, multi-resolution, and extensible, in the sense that detailed submodules of any process(es) can be "plugged-in" to the basic model in order to explore, eg. system-level implications of local perturbations. The goal is to keep the basic core model compact enough to insure fast execution time (in view of eventual use in the clinic) and yet to allow elaborate detailed modules of target tissues or organs in order to focus on the problem area while maintaining the system-level regulatory compensations

Концепция виртуального организма в биоинформатике

Проанализированы современное состояние и некоторые тенденции разработок и исследований в области биоинформатики. Обсуждены проблемы и перспективы создания информационной технологии, интегрирующей в себе разнородные данные об анатомии и морфологии, биомеханике, биохимии и физиологии человека для комплексного анализа разномасштабных по размерам и динамике процессов. Изложены основы теории адаптивного реагирования организма на экзогенные случайные возмущения и оригинальный подход к моделированию функционирования организма. Конечной целью моделирования является повышение надежности диагностики состояния человека и создание оптимальных технологий управления его работоспособностью и здоровьем

Virtual Patients and Sensitivity Analysis of the Guyton Model of Blood Pressure Regulation: Towards Individualized Models of Whole-Body Physiology

Mathematical models that integrate multi-scale physiological data can offer insight into physiological and pathophysiological function, and may eventually assist in individualized predictive medicine. We present a methodology for performing systematic analyses of multi-parameter interactions in such complex, multi-scale models. Human physiology models are often based on or inspired by Arthur Guyton's whole-body circulatory regulation model. Despite the significance of this model, it has not been the subject of a systematic and comprehensive sensitivity study. Therefore, we use this model as a case study for our methodology. Our analysis of the Guyton model reveals how the multitude of model parameters combine to affect the model dynamics, and how interesting combinations of parameters may be identified. It also includes a “virtual population” from which “virtual individuals” can be chosen, on the basis of exhibiting conditions similar to those of a real-world patient. This lays the groundwork for using the Guyton model for in silico exploration of pathophysiological states and treatment strategies. The results presented here illustrate several potential uses for the entire dataset of sensitivity results and the “virtual individuals” that we have generated, which are included in the supplementary material. More generally, the presented methodology is applicable to modern, more complex multi-scale physiological models

Models of the human metabolic network: aiming to reconcile metabolomics and genomics

The metabolic syndrome, inborn errors of metabolism, and drug-induced changes to metabolic states all bring about a seemingly bewildering array of alterations in metabolite concentrations; these often occur in tissues and cells that are distant from those containing the primary biochemical lesion. How is it possible to collect sufficient biochemical information from a patient to enable us to work backwards and pinpoint the primary lesion, and possibly treat it in this whole human metabolic network? Potential analyses have benefited from modern methods such as ultra-high-pressure liquid chromatography, mass spectrometry, nuclear magnetic resonance spectroscopy, and more. A yet greater challenge is the prediction of outcomes of possible modern therapies using drugs and genetic engineering. This exposes the notion of viewing metabolism from a completely different perspective, with focus on the enzymes, regulators, and structural elements that are encoded by genes that specify the amino acid sequences, and hence encode the various interactions, be they regulatory or catalytic. The mainstream view of metabolism is being challenged, so we discuss here the reconciling of traditionally quantitative chemocentric metabolism with the seemingly 'parameter-free' genomic description, and vice versa

A novel paradigm for cell and molecule interaction ontology: from the CMM model to IMGT-ONTOLOGY

International audienc