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Joseph Liao is a professor of urology and a surgeon-scientist at Stanford University. He is a magna cum laude graduate of Harvard College and received his medical degree from Stanford School of Medicine. After completing his urology residency and fellowship at UCLA, he returned to Stanford in 2006 as a faculty with a joint appointment as the Chief of Urology at VA Palo Alto Health Care System. Dr. Liao is certified by the American Board of Urology and maintains an active clinical practice focusing on patients with urological cancer and kidney stone disease.At Stanford, Dr. Liao is a member of the Bio-X, Stanford Cancer Institute, Center for Artificial Intelligence in Medicine & Imaging, and Institute for Immunity, Transplantation, and Infection. He leads a multidisciplinary laboratory that focuses on development of optical imaging technologies for cancer surgery and molecular diagnostics for urological cancer and infections. He has served as the principal investigator on several R01 grants from the National Institutes of Health and Merit Review Awards from the Department of Veterans Affairs, as well as a standing member of the NIH Instrument Systems Development study section. He has authored over 150 manuscripts and served as the editor of the textbook Advances in Image-Guided Urologic Surgery. He has been an invited speaker to numerous international meetings including the Gordon Research Conferences, IEEE-NANOMED, IEEE-NEMS, SPIE, Society of Urologic Oncology, Endourology Society, American Urological Association, and European Association of Urology.
1. Multimodal optical imaging of bladder cancer<br/><br/>A major focus of my lab is to develop enhanced endoscopic imaging technologies (e.g. fluorescence, endomicroscopy, molecular imaging, computer vision, and artificial intelligence) to improve bladder tumor detection and resection. We have investigated CD47, an innate immune checkpoint, as a bladder cancer imaging and therapeutic target. We identified and validated CD47 as a promising cancer imaging target and proposed a strategy for intravesical administration of imaging agents based on therapeutic antibodies (Pan 2014). In animal models, we investigated the biodistribution and systemic toxicity of nanoparticle-labeled anti-CD47 (Pan 2017) and demonstrated that CD47-mediated near-infrared photoimmunotherapy, a novel form of targeted phototherapy, led to enhanced tumor destruction and prolonged survival (Kiss 2019). In the clinical arena, we pioneered the urological applications of confocal endomicroscopy for bladder cancer (Sonn 2009), upper tract urothelial carcinoma (Bui 2015) and prostate cancer (Lopez 2015). This optical biopsy technology enables real-time intraoperative imaging with spatial resolution comparable to histology. Finally, we are developing computer vision and artificial intelligence tools to enhance cystoscopic navigation and tumor identification. We have an ongoing effort to curate a high quality annotated cystoscopy imaging dataset of diverse bladder cancer variants and recently reported the first AI-assisted cystoscopy using convolutional neural networks for automated tumor annotation (Shkolyar 2019).<br/><br/><br/>2. Precision diagnostics for bladder cancer <br/><br/>Another major focus is identification and validation of urine-based biomarkers to inform bladder cancer diagnosis, prognosis, and treatment response. Given its abundance and non-invasive nature of sample collection, urine serves as an ideal source of liquid biopsy. To overcome the diagnostic shortcomings of standard urine cytology, we have utilized high throughput sequencing technology as a discovery and diagnostic tool. We applied bulk RNA sequencing to urinary pellets for biomarker discovery and developed a diagnostic 3-marker urinary RNA panel (Sin 2017), and led a multi-center effort to validate another urinary RNA panel using an integrated microfluidic cartridge (Wallace 2019). Collaboratively with other colleagues at Stanford, we are developing an ultrasensitive targeted sequencing approach called uCAPP-Seq (urine tumor DNA Cancer Personalized Profiling by deep sequencing) for bladder cancer (Dudley 2019) and have started prospective longitudinal validation studies of these precision diagnostic platforms.<br/><br/><br/>3. Precision diagnostics of urinary tract infections <br/><br/>A longstanding focus of my lab has been the development of molecular diagnostics for bacterial infections to direct evidence-based utilization of antibiotics and curtail the proliferation of multidrug resistant pathogens. We focus on urinary tract infections, the most common urological disease and healthcare-associated infection. We have made broad advances in molecular probe development for amplification-free bacterial detection, microfluidic-based antimicrobial susceptibility testing (AST), sample preparation strategies compatible with matrix effects from clinical samples, system integration, and single cell analysis. Representative works include rapid, sensitive pathogen identification through 16S rRNA targeting (Ouyang 2013, Mach 2019), validation of integrated AST in clinical samples (Altobelli 2016), and single cell analysis (Hsieh 2018, Li 2019). Most recently, we report a 30-minute sample-to-answer assay based on single-cell measurements of bacterial 16S rRNA in picoliter droplets to achieve simultaneous molecular pathogen identification and phenotypic antimicrobial susceptibility assessment (Kaushik 2021).
Fiber-Optic Confocal Microscopy of the Urinary Tract Histopathology
The goal of the study is to develop a novel approach to obtain real time optical biopsy of
urinary tract pathology (e.g., bladder tumors) during urinary tract endoscopy using a novel
fibered confocal microscope.
Stanford is currently not accepting patients for this trial.
For more information, please contact Jospeh C Liao, M.D., 650-852-3284.
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