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Pathania, Divya

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Pathania

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Divya

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Pathania, Divya
Author's Publications: search.filters.isAuthorOfPublication.10fc391a-fcda-4b14-8460-f452c6712d25

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    Holographic Assessment of Lymphoma Tissue (HALT) for Global Oncology Field Applications
    (Ivyspring International Publisher, 2016) Pathania, Divya; Im, Hyungsoon; Kilcoyne, Aoife; Sohani, Aliyah R.; Fexon, Lioubov; Pivovarov, Misha; Abramson, Jeremy; Randall, Thomas; Chabner, Bruce; Weissleder, Ralph; Lee, Hakho; Castro, Cesar
    Low-cost, rapid and accurate detection technologies are key requisites to cope with the growing global cancer challenges. The need is particularly pronounced in resource-limited settings where treatment opportunities are often missed due to the absence of timely diagnoses. We herein describe a Holographic Assessment of Lymphoma Tissue (HALT) system that adopts a smartphone as the basis for molecular cancer diagnostics. The system detects malignant lymphoma cells labeled with marker-specific microbeads that produce unique holographic signatures. Importantly, we optimized HALT to detect lymphomas in fine-needle aspirates from superficial lymph nodes, procedures that align with the minimally invasive biopsy needs of resource-constrained regions. We equipped the platform to directly address the practical needs of employing novel technologies for “real world” use. The HALT assay generated readouts in <1.5 h and demonstrated good agreement with standard cytology and surgical pathology.
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    Sparsity-Based Pixel Super Resolution for Lens-Free Digital In-line Holography
    (Nature Publishing Group, 2016) Song, Jun; Leon Swisher, Christine; Im, Hyungsoon; Jeong, Sangmoo; Pathania, Divya; Iwamoto, Yoshiko; Pivovarov, Misha; Weissleder, Ralph; Lee, Hakho
    Lens-free digital in-line holography (LDIH) is a promising technology for portable, wide field-of-view imaging. Its resolution, however, is limited by the inherent pixel size of an imaging device. Here we present a new computational approach to achieve sub-pixel resolution for LDIH. The developed method is a sparsity-based reconstruction with the capability to handle the non-linear nature of LDIH. We systematically characterized the algorithm through simulation and LDIH imaging studies. The method achieved the spatial resolution down to one-third of the pixel size, while requiring only single-frame imaging without any hardware modifications. This new approach can be used as a general framework to enhance the resolution in nonlinear holographic systems.
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    Computational imaging reveals mitochondrial morphology as a biomarker of cancer phenotype and drug response
    (Nature Publishing Group, 2016) Giedt, Randy; Fumene Feruglio, Paolo; Pathania, Divya; Yang, Katherine; Kilcoyne, Aoife; Vinegoni, Claudio; Mitchison, Timothy; Weissleder, Ralph
    Mitochondria, which are essential organelles in resting and replicating cells, can vary in number, mass and shape. Past research has primarily focused on short-term molecular mechanisms underlying fission/fusion. Less is known about longer-term mitochondrial behavior such as the overall makeup of cell populations’ morphological patterns and whether these patterns can be used as biomarkers of drug response in human cells. We developed an image-based analytical technique to phenotype mitochondrial morphology in different cancers, including cancer cell lines and patient-derived cancer cells. We demonstrate that (i) cancer cells of different origins, including patient-derived xenografts, express highly diverse mitochondrial phenotypes; (ii) a given phenotype is characteristic of a cell population and fairly constant over time; (iii) mitochondrial patterns correlate with cell metabolic measurements and (iv) therapeutic interventions can alter mitochondrial phenotypes in drug-sensitive cancers as measured in pre- versus post-treatment fine needle aspirates in mice. These observations shed light on the role of mitochondrial dynamics in the biology and drug response of cancer cells. On the basis of these findings, we propose that image-based mitochondrial phenotyping can provide biomarkers for assessing cancer phenotype and drug response.