from other sources, such as autoradiography. Similarly, quantitative maps could

also be statistically analyzed. Thus, this tool could carry out quantitative

parametric mapping for more than 25 models.

PCARDP tool: PCARDP tool offers a comprehensive environment for static,

dynamic, and gated analysis of cardiac PET images. One can easily understand

different processing stages in a streamlined workflow. The involved crucial steps

are provisioned with automatic procedures which include short-axis reorientation

of the images and myocardial segmentation However, there is freedom for the

user to interactively modify the outcomes. Dynamic data could be easily modeled

in PKIN and leveraging the PET quantification solution for the cardiac environ-

ment. One obtains results in the form of comprehensive reports which could be

exported numerically or in standard report formats. Numerous powerful analysis

tools are available for investigating cardiac research environments.

PCARDM tool: It is a combination of PMOD’s modeling expertise with ETH’s

leading-edge MR methodology for qualitative and quantitative CMR image

analysis by employing the state-of-the art perfusion quantification approaches

to the available data. This tool in conjunction with accelerated MR acquisition

sequences can possibly image the full extent of the heart in a single breath hold.

PGEM tool: This tool is helpful in carrying out analyses with different types of

geometry. Fiber tracking and track visualization (PMOD) can be done by

using DWI MR images. By measuring the velocity vector of fluids in vessels as a

function of time, one can possibly analyze and have a streamline visualization of

4D flow MR images. It can also create geometric models to carry out different

simulations. It also facilitates comprehensive support for computational fluid

dynamics (CFD) research in the form of vessel models and interface with the

OpenFOAM simulation system. It can also assist in quantitative image

processing.

Other software packages include Carimas, Corridor4DM, HOQUTO, MunichHeart,

QPET, syngo MBF, UW-QPP, etc.

The subsequent section deals with a microscopic theoretical modeling which

explains the flow of fluid in different nano-geometries.

16.6

Theoretical Model: Flow of Fluids in Nano-Geometries

Motion of a nanoconfined fluid gets strongly affected in layers near the wall which

modifies its diffusive and viscous properties. The structural and dynamical

properties of liquids have been found to experience changes when liquids are

confined even by smooth walls. Moreover, at the nanolevel, the Reynolds number

reduces considerably resulting only in laminar flow. The continuum behavior of the

liquid is unsuccessful in explaining fluid transport. Thus, theoretical modeling and

its analysis become a challenging task as one has to incorporate the complexity of the

fluid in the model. In this section we shall discuss an attempt to include all these

aspects in a microscopic model developed by Tankeshwar and his research group.

16

Role of Microfluidics and Nanofluidics in Managing CAD

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