Shrey Sukhadia

Radiological images such as CT, MRI and PET allude a plethora of tumor-phenotypic features such as shape, size, texture and intensity of a tumor region of interest (ROI) carved by radiologists and further biopsied and examined using immunohistochemistry technique in pathology. Such a specimen then undergoes a variety of genomic and proteomic tests to identify genetic aberrations in patients responsible for the underlying state of their disease and alluding treatment options thereof. Further, a patient’s response to such treatments is also recorded. Such imaging and omic profiles along with the corresponding treatment outcomes data could be correlated statistically and modeled together using several AI techniques to understand which of the features would actually allow the most non-invasive and fastest way to predict a patients disease state and/or their response to a particular therapy. ImaGene, a web-based software platform was designed keeping in mind the robustness, flexibility and transparency required for such a wide data-analysis yielding a systematic report explaining how certain parameter settings affect the results, thereby allowing researchers to steer their efforts in appropriate direction yielding significant outcomes. ImaGene is free to use and has been proven to yield significant imaging-omic associations in breast, head-and-neck and lung cancer cases and is currently being tested on several other cancer types as well. The models build therein (and the reports thereof) are shareable across laboratories and hospitals boosting collaborations achieving consensus in such imaging-omic associations (or predictions) for several cancer types thereby aiding clinical research in cancer.

Shrey Sukhadia has been leading clinical bioinformatics efforts at top tier hospitals in United States, such as Dartmouth-Hitchcock Medical Center, Phoenix Children’s Hospital and Hospital of the University of Pennsylvania. His expertise includes Genomic data analysis, Precision Medicine, Statistics, Artificial intelligence, Imaging-genomics, Transcriptomics, Copy number alterations, Protein structure predictions and protein-protein docking, and Software Engineering.

Through his PhD-research in Radiogenomics at Queensland University of Technology, Australia, Shrey has developed a robust AI-based software named “IMAGENE” for effective integration and analysis of imaging and omics data for cancer patients. IMAGENE has already been tested on Breast, Head-and-Neck, Lung and Brain Cancer datasets and is currently being tested for other cancer types as well. It accommodates both radiology and histopathology (aka tissue slide) imaging data along with omic data such as genomic, proteomic or several patient treatment outcomes and builds robust AI models thereof accompanied by a transparent report. A web app for IMAGENE is freely available at “https://www.imagene.pgxguide.org/index.php” to foster testing of cancer datasets worldwide. It hosts a novel knowledge-base of imaging-genomics’ AI models, thereby aiding the advancement of precision medicine for better (and faster) diagnosis and treatment of cancer patients globally.

Come join us in our efforts to democratize the imaging-genomics analysis for all patients worldwide and provide them with a better future thereof.

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