Giardia duodenalis assemblage B dominates transmission in this community. A variety of G. duodenalis subtypes persist, and reinfection of children with different genetic variants is possible. The similar frequencies of assemblage A and B in this study to other Australian communities warrants further investigation to assess whether disease dynamics are similar between communities, despite differences in prevalence. In contrast, conditions specific to remote Indigenous communities may enhance mixed or heterogeneous infections. Knowledge of parasite prevalence, infectious subtypes, and community dynamics that enhance transmission are required to address the continuing burden that gastrointestinal diseases impose on children in remote Indigenous communities. Intratumor genetic or epigenetic heterogeneity has been found in many cancers as evidenced by deep sequencing selectively applied to different parts of the same tumor. Consequently, cancer cells display remarkable phenotypic variability, including ability to induce LY294002 154447-36-6 angiogenesis, seed metastases, and survive therapy. Advanced solid tumors often contain vascular compartments with distinct pharmacokinetics, comprising hypoxic regions and spatially intermingled irregular vasculature that is leaky and inefficient. The complexity of heterogeneity has clinical implications. A more heterogeneous tumor is more likely to fail therapy due to increased drug-resistant variants, and characteristics of the dominant cell type will not necessarily predict the behaviors of interest rooted in specific cells. Dynamic contrast-enhanced magnetic resonance imaging provides a noninvasive in vivo method to evaluate tumor vasculature architectures based on contrast accumulation and washout. While DCE-MRI can potentially depict the intratumor heterogeneity of vascular permeability, the quantitative application of DCE-MRI has been hindered by its inability to accurately resolve vascular compartments with distinct pharmacokinetics due to limited imaging resolution. We emphasize that identification of spatially mixed multiple vascular cytotypes is principally different from imaging an inhomogeneously distributed single vascular cytotype, and it is the former scenario that presents significant technological challenges to portraying tumor cytotypes. This indistinction among the contributions of different compartments to the mixed tracer signals can confound compartment modeling and deep phenotyping for association studies. The goal of the present work was to discern vascular heterogeneity and its changes in tumors using DCE-MRI and novel mathematical models, for personalized cancer diagnosis and treatment. We developed a computational method for deconvolving intratumor vascular heterogeneity and identifying pharmacokinetics changes in many biological contexts. MTCM works by applying a convex analysis of mixtures that enables geometrically-principled delineation of distinct vascular structures from DCE-MRI data.