Biomedical subjects

Hanif M Ladak

Publications and source records attributed to Hanif M Ladak.

4 recordsLinked to original sources

PubMed2003

A new method for assessing arteriolar diameter and hemodynamic resistance using image analysis of vessel lumen.

To characterize the nonuniform diameter response in a blood vessel after a given stimulus (e.g., arteriolar conducted response), frequent serial diameter measurements along the vessel length are required. We used an advanced image analysis algorithm (the "discrete dynamic contour") to develop a quick, reliable method for serial luminal diameter measurements along the arteriole visualized by intravital video microscopy. With the use of digitized images of the arteriole and computer graphics, the method required an operator to mark the image of the two inner edges of the arteriole at several places along the arteriolar length. The algorithm then "filled in" these marks to generate two continuous contours that "hugged" these edges. A computer routine used these contours to determine luminal diameters every 20 microm. Based on these diameters and on Poiseuille's law, the routine also estimated the hemodynamic resistance of the blood vessel. To demonstrate the usefulness of the method, we examined the character of spatial decay of KCl-induced conducted constriction along approximately 500-microm-long arteriolar segments and the KCl-induced increase in hemodynamic resistance computed for these segments. The decay was only modestly fitted by a simple exponential, and the computed increase in resistance (i.e., 5- to 70-fold) was only modestly predicted by resistance increase based on our mathematical model involving measurements at two arteriolar sites (Tyml K, Wang X, Lidington D, and Oullette Y. Am J Physiol Heart Circ Physiol 281: H1397-H1406, 2001). We conclude that our method provides quick, reliable serial diameter measurements. Because the change in hemodynamic resistance could serve as a sensitive index of conducted response, use of this index in studies of conducted response may lead to new mechanistic insights on the response.

Animals↗

PubMed2003

Testing and optimization of a semiautomatic prostate boundary segmentation algorithm using virtual operators.

Image analysis tasks such as size measurement and landmark-based registration require the user to select control points in an image. The output of such algorithms depends on the choice of control points. Since the choice of points varies from one user to the next, the requirement for user input introduces variability into the output of the algorithm. In order to test and/or optimize such algorithms, it is necessary to assess the multiplicity of outputs generated by the algorithm in response to a large set of inputs; however, the input of data requires substantial time and effort from multiple users. In this paper we describe a method to automate the testing and optimization of algorithms using "virtual operators," which consist of a set of spatial distributions describing how actual users select control points in an image. In order to construct the virtual operator, multiple users must repeatedly select control points in the image on which testing is to be performed. Once virtual operators are generated, control points for initializing the algorithm can be generated from them using a random number generator. Although an initial investment of time is required from the users in order to construct the virtual operator, testing and optimization of the algorithm can be done without further user interaction. We illustrate the construction and use of virtual operators by testing and optimizing our prostate boundary segmentation algorithm. The algorithm requires the user to select four control points on the prostate as input.

Algorithms↗

PubMed2003

Prostate boundary segmentation from 3D ultrasound images.

Segmenting, or outlining the prostate boundary is an important task in the management of patients with prostate cancer. In this paper, an algorithm is described for semiautomatic segmentation of the prostate from 3D ultrasound images. The algorithm uses model-based initialization and mesh refinement using an efficient deformable model. Initialization requires the user to select only six points from which the outline of the prostate is estimated using shape information. The estimated outline is then automatically deformed to better fit the prostate boundary. An editing tool allows the user to edit the boundary in problematic regions and then deform the model again to improve the final results. The algorithm requires less than 1 min on a Pentium III 400 MHz PC. The accuracy of the algorithm was assessed by comparing the algorithm results, obtained from both local and global analysis, to the manual segmentations on six prostates. The local difference was mapped on the surface of the algorithm boundary to produce a visual representation. Global error analysis showed that the average difference between manual and algorithm boundaries was -0.20 +/- 0.28 mm, the average absolute difference was 1.19 +/- 0.14 mm, the average maximum difference was 7.01 +/- 1.04 mm, and the average volume difference was 7.16% +/- 3.45%. Variability in manual and algorithm segmentation was also assessed: Visual representations of local variability were generated by mapping variability on the segmentation mesh. The mean variability in manual segmentation was 0.98 mm and in algorithm segmentation was 0.63 mm and the differences of about 51.5% of the points comprising the average algorithm boundary are insignificant (P < or = 0.01) to the manual average boundary.

Algorithms↗

PubMed2002

Reconstruction of carotid bifurcation hemodynamics and wall thickness using computational fluid dynamics and MRI.

A thorough understanding of the relationship between local hemodynamics and plaque progression has been hindered by an inability to prospectively monitor these factors in vivo in humans. In this study a novel approach for noninvasively reconstructing artery wall thickness and local hemodynamics at the human carotid bifurcation is presented. Three-dimensional (3D) models of the lumen and wall boundaries, from which wall thickness can be measured, were reconstructed from black-blood magnetic resonance imaging (MRI). Along with time-varying inlet/outlet flow rates measured via phase contrast (PC) MRI, the lumen boundary was used as input for computational fluid dynamic (CFD) simulation of the subject-specific flow patterns and wall shear stresses (WSSs). Results from a 59-year-old subject with early, asymptomatic carotid artery disease show good agreement between simulated and measured velocities, and demonstrate a correspondence between wall thickening and low and oscillating shear at the carotid bulb. High shear at the distal internal carotid artery (ICA) was also colocalized with higher WSS; however, a quantitative general relationship between WSS and wall thickness was not found. Similar results were obtained from a 23-year-old normal subject. These findings represent the first direct comparison of hemodynamic variables and wall thickness at the carotid bifurcation of human subjects. The noninvasive nature of this image-based modeling approach makes it ideal for carrying out future prospective studies of hemodynamics and plaque development or progression in otherwise healthy subjects.

Adult↗