Ananda S. Chowdhury

Multi-organ segmentation from multi-phase abdominal CT via 4D graphs using enhancement, shape and location optimization

The interpretation of medical images benefits from anatomical and physiological priors to optimize computer-aided diagnosis (CAD) applications. Diagnosis also relies on the comprehensive analysis of multiple organs and quantitative measures of soft tissue. An automated method optimized for medical image data is presented for the simultaneous segmentation of four abdominal organs from 4D CT data using graph cuts. Contrast-enhanced CT scans were obtained at two phases: non-contrast and portal venous. Intra-patient data were spatially normalized by non-linear registration. Then 4D erosion using population historic information of contrast-enhanced liver, spleen, and kidneys was applied to multi-phase data to initialize the 4D graph and adapt to patient specific data. CT enhancement information and constraints on shape, from Parzen windows, and location, from a probabilistic atlas, were input into a new formulation of a 4D graph. Comparative results demonstrate the effects of appearance and enhancement, and shape and location on organ segmentation.

Reversible Projection Technique for Colon Unfolding

Colon unfolding provides an efficient way to navigate the colon in computed tomographic colonography (CTC). Most existing unfolding techniques only compute forward projections. When radiologists find abnormalities or conduct measurements on the unfolded view (which is often quicker and easier), it is difficult to locate the corresponding region on the 3-D view for further examination (which is more accurate and reliable). To address this, we propose a reversible projection technique for colon unfolding. The method makes use of advanced algorithms including rotation-minimizing frames, recursive ring sets, mesh skinning, and cylindrical projection. Both forward and reverse mapping can be computed for points on the colon surface. Therefore, it allows for detecting and measuring polyps on the unfolded view and mapping them back to the 3-D surface. We generated realistic colon simulation data incorporating most colon characteristics, such as curved centerline, variable distention, haustral folds, teniae coli, and colonic polyps. Our method was tested on both simulated data and data from 110 clinical CTC studies. The results showed submillimeter accuracy in simulated data and -0.23 ± 1.67 mm in the polyp measurement using clinical CTC data. The major contributions of our technique are: 1) the use of a recursive ring set method to solve the centerline and surface correspondence problem; 2) reverse transformation from the unfolded view to the 3-D view; and 3) quantitative validation using a realistic colon simulation and clinical CTC polyp measurement.

Colonic fold detection from computed tomographic colonography images using diffusion-FCM and level sets

Colon cancer is the second major cause of cancer related deaths in industrial nations. Computed tomographic colonography (CTC) has emerged in the last decade as a new less invasive colon diagnostic alternative to the usually practiced optical colonoscopy. The overall goal is to increase the effectiveness of virtual endoscopic navigation of the existing computer-aided detection (CAD) system. The colonic/haustral folds serve as important landmarks for various associated tasks in the virtual endoscopic navigation like prone-supine registration, colonic polyp detection and tenia coli extraction. In this paper, we present two different techniques, first in isolation and then in synergism, for the detection of haustral folds. Our input is volumetric computed tomographic colonography (CTC) images. The first method, which uses a combination of heat diffusion and fuzzy c-means algorithm (FCM), has a tendency of over-segmentation. The second method, which employs level sets, suffers from under-segmentation. A synergistic combination, where the output of the first is used as an input for the second, is shown to improve the segmentation quality. Experimental results are presented on digital colon phantoms as well as real patient scans. The combined method has a total erroneous (over-segmentation plus under-segmentation) detection of (6.5+/-2)% of the total number of folds per colon as compared to (12.5+/-5)% for the diffusion-FCM-based method and (11.5+/-3)% for the level set-based method. The p-values obtained from the associated ANOVA tests indicate that the performance improvements are statistically significant.

Detection of anatomical landmarks in human colon from computed tomographic colonography images

Colon cancer is the second leading cause of cancer-related deaths per year in industrial nations. Virtual colonoscopy is a new, less invasive alternative to the usually practiced optical colonoscopy for colorectal polyp and cancer screening. In this paper, we present some physics-based modeling and pattern recognition techniques to identify anatomical landmarks in the human colon like the haustral folds and the tenia coli to further exploit the benefits of virtual colonoscopy. A combination of heat diffusion field algorithm and fuzzy c-means clustering algorithm is used to detect the haustral folds in human colon from volumetric computed tomography (CT) images. Each voxel on the corresponding colon surface is parameterized using the colon centerline information and associated local Frenet frames. The parameterized fold information is utilized to establish the tentative location of one tenia coli. Preliminary results on automated detection of tenia coli are shown on the colon surface.

Two Methods of Haustral Fold Detection from Computed Tomographic Virtual Colonoscopy Images

Virtual colonoscopy (VC) has gained popularity as a new colon diagnostic method over the last decade. VC is a new, less invasive alternative to the usually practiced optical colonoscopy for colorectal polyp and cancer screening, the second major cause of cancer related deaths in industrial nations. Haustral (colonic) folds serve as important landmarks for virtual endoscopic navigation in the existing computer-aided-diagnosis (CAD) system. In this paper, we propose and compare two different methods of haustral fold detection from volumetric computed tomographic virtual colonoscopy images. The colon lumen is segmented from the input using modified region growing and fuzzy connectedness. The first method for fold detection uses a level set that evolves on a mesh representation of the colon surface. The colon surface is obtained from the segmented colon lumen using the Marching Cubes algorithm. The second method for fold detection, based on a combination of heat diffusion and fuzzy c-means algorithm, is employed on the segmented colon volume. Folds obtained on the colon volume using this method are then transferred to the corresponding colon surface. After experimentation with different datasets, results are found to be promising. The results also demonstrate that the first method has a tendency of slight under-segmentation while the second method tends to slightly over-segment the folds.

Macromolecule-Network Electrostatics Controlling Delivery of the Biotherapeutic Cell Modulator TIMP-2

Tissue inhibitor of metalloproteinase 2 (TIMP-2) is an endogenous 22 kDa proteinase inhibitor, demonstrating antitumorigenic, antimetastatic and antiangiogenic activities in vitro and in vivo. Recombinant TIMP-2 is currently undergoing preclinical testing in multiple, murine tumor models. Here we report the development of an inert, injectable peptide hydrogel matrix enabling encapsulation and sustained release of TIMP-2. We studied the TIMP-2 release profile from four β-hairpin peptide gels of varying net electrostatic charge. A negatively charged peptide gel (designated AcVES3) enabling encapsulation of 4 mg/mL of TIMP-2, without effects on rheological properties, facilitated the slow sustained release (0.9%/d) of TIMP-2 over 28 d. Released TIMP-2 is structurally intact and maintains the ability to inhibit MMP activity, as well as suppress lung cancer cell proliferation in vitro. These findings suggest that the AcVES3 hydrogel will be useful as an injectable vehicle for systemic delivery of TIMP-2 in vivo for ongoing preclinical development.

Tissue Inhibitor of Metalloprotease-2 (TIMP-2): Bioprocess Development, Physicochemical, Biochemical, and Biological Characterization of Highly Expressed Recombinant Protein

Tissue inhibitor of metalloprotease-2 (TIMP-2) is a secreted 21 kDa multifunctional protein first described as an endogenous inhibitor of matrix metalloproteinases (MMPs) that prevents breakdown of the extracellular matrix often observed in chronic diseases. TIMP-2 diminishes the level of growth factor-mediated cell proliferation in vitro, as well as neoangiogenesis and tumor growth in vivo independent of its MMP inhibitory activity. These physiological properties make TIMP-2 an excellent candidate for further preclinical development as a biologic therapy of cancer. Here we present a straightforward bioprocessing methodology that yields >35 mg/L recombinant human TIMP-2 6XHis-tagged protein (rhTIMP-2) from suspension cultures of HEK-293-F cells. Enhanced rhTIMP-2-6XHis yields were achieved by optimization of both TIMP-2 cDNA codon sequence and cell culture conditions. Using a two-step chromatographic process, we achieved >95% purity with minimal processing losses. Purified rhTIMP-2-6XHis was free of mouse antigen contamination. Circular dichroism spectroscopy indicated a well-folded rhTIMP-2-6XHis that is highly stable and refractory to pH changes. Two-dimensional heteronuclear single-quantum coherence nuclear magnetic resonance of full length rhTIMP-2-6XHis also indicated a monodisperse, well-folded protein preparation. Purified rhTIMP-2-6XHis inhibited MMP-2 enzymatic activity in a dose-dependent fashion with an IC50 of ∼1.4 nM. Pretreatment of A549 lung cancer and JygMC(A) triple-negative breast cancer cells with rhTIMP-2-6XHis in low-nanomolar amounts inhibited EGF-induced proliferation to basal (unstimulated) levels. This study therefore not only offers a robust bioprocess methodology for rhTIMP-2 production but also characterizes critical physicochemical and biological attributes that are useful for monitoring quality control of the production process.

Abstract 676: Tissue inhibitor of metalloproteinase-2 (TIMP2) deficiency enhances tumor burden via increasing HIF-2á expression

The tissue inhibitor of metalloproteinase family of proteins (TIMPs 1-4) function as natural MMP inhibitors, and have been shown to play a role in maintenance and remodeling of the ECM as well as other cellular processes including proliferation, apoptosis and angiogenesis. A number of studies have shown that the down-regulation or silencing of TIMP2 accelerates tumor development, however, the mechanism is not well understood. High HIF-2a levels in non-small cell lung cancer (NSCLC) correlate with decreased overall survival, while inhibition of HIFs targeted genes VEGF or VEGFR2 are associated with improved clinical outcome. Similarly, TIMP2 mRNA levels were found to be low in NSCLC compared to the corresponding non-neoplastic surrounding lung (p Citation Format: Sarvesh Kumar, Sandra M. Jensen, Ananda Chowdhury, Beiyang Wei, William G. Stetler-Stevenson. Tissue inhibitor of metalloproteinase-2 (TIMP2) deficiency enhances tumor burden via increasing HIF-2a expression. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 676.

Realistic Colon Simulation in CT Colonography Using Mesh Skinning

Realistic colon simulations do not exist but would be valuable for CT colonography (CTC) CAD development and validation of new colon image processing algorithms. The human colon is a convoluted tubular structure and very hard to model physically and electronically. In this investigation, we propose a novel approach to generate realistic colon simulation using mesh skinning. The method proceeds as follows. First, a digital phantom of a cylindrical tube is modeled to simulate a straightened colon. Second, haustral folds and teniae coli are added to the cylindrical tube. Third, a centerline equipped with rotation-minimizing frames (RMF) and distention values is computed. Fourth, mesh skinning is applied to warp the tube around the centerline and generate realistic colon simulation. Lastly, colonic polyps in the shape of ellipsoids are also modeled. Results show that the simulated colon highly resembles the real colon. This is the first colon simulation that incorporates most colon characteristics in one model, including curved centerline, variable distention, haustral folds, teniae coli and colonic polyps.