Biometrics (Just Accepted)
Abstract: Identifying direct links between gene pathways and clinical endpoints for highly fatal diseases such as cancer is a formidable task. Integrative analyses play a crucial role in modeling these links by relying upon associations between a wealth of intermediary variables and genomic measurements. Motivated to harness phenotypic information about tumors towards a molecular characterization of low-grade gliomas, we develop a data driven Bayesian framework to define sharp models, and calibrate accurately and efficiently uncertainties associated with the promising biological findings.
Neuroscience Informatics (2022).
Abstract: Background and Purpose MRI features of tumor progression and pseudoprogression may be indistinguishable especially without enhancing portion of the diffuse gliomas. Our aim is to discriminate these two conditions using radiomics and machine learning algorithm and to compare them with human observations.
Materials and Methods Three consecutive MRI studies before a definitive biopsy in 43 diffuse glioma patients (7 pseudoprogression and 36 true progression cases) who underwent treatment were evaluated.
Scientific Reports (2021).
Abstract: Immune checkpoint inhibitors (ICI) with anti-PD-1/PD-L1 agents have improved the survival of patients with metastatic non-small cell lung cancer (mNSCLC). Tumor PD-L1 expression is an imperfect biomarker as it does not capture the complex interactions between constituents of the tumor microenvironment (TME). Using multiplex fluorescent immunohistochemistry (mfIHC), we modeled the TME to study the influence of cellular distribution and engagement on response to ICI in mNSCLC. We performed mfIHC on pretreatment tissue from patients with mNSCLC who received ICI.
American Journal of Neuroradiology (2021).
Nominated for 2021 Lucien Levy Best Research Article. AJNR Blog Annoucement
Abstract: Background and Purpose. T2-FLAIR mismatch sign is a validated imaging sign of IDH-mutant 1p/19q non-codeleted gliomas. It is identified by radiologists through visual inspection of pre-operative MRI scans, and has been shown to identify IDH-mutant 1p/19q non-codeleted gliomas with high positive predictive value. We have developed an approach to quantify the T2-FLAIR mismatch signature, and use it to predict molecular status of lower-grade gliomas (LGG).
Annals of Applied Statistics (2021).
Abstract: Recent technological advancements have enabled detailed investigation of associations between the molecular architecture and tumor heterogeneity, through multi-source integration of radiological imaging and genomic (radiogenomic) data. In this paper, we integrate and harness radiogenomic data in patients with lower grade gliomas (LGG), a type of brain cancer, in order to develop a regression framework called RADIOHEAD (RADIOgenomic analysis incorporating tumor HEterogeneity in imAging through Densities) to identify radiogenomic associations.