Mathematical models of tumor growth using Voronoi tessellations in pathology slides of kidney cancer

Examining the efficacy of localised gemcitabine therapy for the treatment of pancreatic cancer using a hybrid agent-based model

The prognosis for pancreatic ductal adenocarcinoma (PDAC) patients has not significantly improved in the past 3 decades, highlighting the need for more effective treatment approaches. Poor patient outcomes and lack of response to therapy can be attributed, in part, to a lack of uptake of perfusion of systemically administered chemotherapeutic drugs into the tumour. Wet-spun alginate fibres loaded with the chemotherapeutic agent gemcitabine have been developed as a potential tool for overcoming the barriers in delivery of systemically administrated drugs to the PDAC tumour microenvironment by delivering high concentrations of drug to the tumour directly over an extended period. While exciting, the practicality, safety, and effectiveness of these devices in a clinical setting requires further investigation. Furthermore, an in-depth assessment of the drug-release rate from these devices needs to be undertaken to determine whether an optimal release profile exists. Using a hybrid computational model (agent-based model and partial differential equation system), we developed a simulation of pancreatic tumour growth and response to treatment with gemcitabine loaded alginate fibres. The model was calibrated using in vitro and in vivo data and simulated using a finite volume method discretisation. We then used the model to compare different intratumoural implantation protocols and gemcitabine-release rates. In our model, the primary driver of pancreatic tumour growth was the rate of tumour cell division. We were able to demonstrate that intratumoural placement of gemcitabine loaded fibres was more effective than peritumoural placement. Additionally, we quantified the efficacy of different release profiles from the implanted fibres that have not yet been tested experimentally. Altogether, the model developed here is a tool that can be used to investigate other drug delivery devices to improve the arsenal of treatments available for PDAC and other difficult-to-treat cancers in the future.

The Voronoi theory of the normal liver lobular architecture and its applicability in hepatic zonation

The precise characterization of the lobular architecture of the liver has been subject of investigation since the earliest historical publications, but an accurate model to describe the hepatic lobular microanatomy is yet to be proposed. Our aim was to evaluate whether Voronoi diagrams can be used to describe the classic liver lobular architecture. We examined the histology of normal porcine and human livers and analyzed the geometric relationships of various microanatomic structures utilizing digital tools. The Voronoi diagram model described the organization of the hepatic classic lobules with overall accuracy nearly 90% based on known histologic landmarks. We have also designed a Voronoi-based algorithm of hepatic zonation, which also showed an overall zonal accuracy of nearly 90%. Therefore, we have presented evidence that Voronoi diagrams represent the basis of the two-dimensional organization of the normal liver and that this concept may have wide applicability in liver pathology and research.

Gene Expressions, Hippocampal Volume Loss, and MMSE Scores in Computation of Progression and Pharmacologic Therapy Effects for Alzheimer's Disease

We build personalized relevance parameterization method (prep-ad) based on artificial intelligence (ai) techniques to compute Alzheimer's disease (ad) progression for patients at the mild cognitive impairment (mci) stage. Expressions of ad related genes, mini mental state examination (mmse) scores, and hippocampal volume measurements of mci patients are obtained from the Alzheimer's Disease Neuroimaging Initiative (adni) database. In evaluation of cognitive changes under pharmacological therapies, patients are grouped based on available clinical measurements and the type of therapy administered, namely donepezil monotherapy and polytherapy of donepezil with memantine. Average leave one out cross validation (loocv) error rates are calculated for prep-ad results as less than 8 percent when mmse scores are used to compute disease progression for a 60 month period, and 3 percent with hippocampal volume measurements for 12 months. Statistical significance is calculated as p = 0.003 for using ad related genes in disease progression and as for the results computed by prep-ad. These relatively small average loocv errors and p-values suggest that our prep-ad methods employing gene expressions, mmse scores and hippocampal volume loss measurements can be useful in supporting pharmacologic therapy decisions during early stages of ad.

Spatial Heterogeneity Analysis in Evaluation of Cell Viability and Apoptosis for Colorectal Cancer Cells

In evaluation of cell viability and apoptosis, spatial heterogeneity is quantified for cancerous cells cultured in 3-D in vitro cell-based assays under the impact of anti-cancer agents. In 48-h experiments using human colorectal cancer cell lines of HCT-116, SW-620, and SW-480, incubated cells are divided into control and drug administered groups, to be grown in matrigel and FOLFOX solution, respectively. Our 3-D cell tracking and data acquisition system guiding an inverted microscope with a digital camera is utilized to capture bright field and fluorescent images of colorectal cancer cells at multiple time points. Identifying the locations of live and dead cells in captured images, spatial point process and Voronoi tessellation methods are applied to extract morphological features of in vitro cell-based assays. For the former method, spatial heterogeneity is quantified with the second-order functions of Poisson point process, whereas the deviation in the area of Voronoi polygons is computed for the latter. With both techniques, the results indicate that the spatial heterogeneity of live cell locations increases as the viability of in in vitro cell cultures decreases. On the other hand, a decrease is observed for the heterogeneity of dead cell locations with the decrease in cell viability. This relationship between morphological features of in vitro cell-based assays and cell viability can be used for drug efficacy measurements and utilized as a biomarker for 3-D in vitro microenvironment assays.