Bio

Kristen is a PhD student in Electrical Engineering at Stanford University and is advised by Dr. Audrey Ellerbee. Kristen was awarded a Stanford Graduate Fellowship, an NSF Graduation Research Fellowship, and a National Defense Science and Engineering Graduate (NDSEG) Fellowships to pursue her doctoral studies. She received her A.B. and B.E. degrees from Dartmouth College in Engineering Sciences and a MS in Electrical Engineering also from Stanford University. Her research interests lie at the intersection of optics and computer vision for medical applications. Her dissertation is primarily focused on developing endoscopes and 3D computer vision algorithms for applications in urology.

New optical imaging tools and visualization techniques for bladder cancer

New optical imaging tools and visualization techniques for bladder cancer

Bladder cancer is the most costly cancer to treat as the high rate of recurrence necessitates lifelong surveillance in order to detect cancer as early as possible. White light cystoscopy (WLC) is the standard tool used for these surveillance procedures, but this imaging technique has several limitations. First, WLC cannot accurately detect all tumors, causing some – particularly early stage tumors – to go untreated. Second, WLC cannot gauge the penetration depth of lesions, the criterion for cancer staging, which requires an excisional biopsy. This follow-up procedure is costly and risky and may ultimately be unnecessary if the tumor is incorrectly classified. Third, it is difficult to review the image data, making it easy to overlook signs of cancer due to work flow challenges or insufficient annotations.

To overcome these limitations, I developed targeted techniques to improve the cystoscopy examination. Specifically, I augmented WLC with optical coherence tomography (OCT), a complementary imaging technique whose ability to visualize the subsurface appearance of the bladder wall reveals early stage tumors better than WLC alone and makes it possible to stage cancers. To this end, I developed a miniaturized, rapid-scanning OCT endoscope that facilitates tumor detection and classification during the initial cystoscopy. Finally, to improve the review of the cystoscopy data, I developed techniques that can enable a more comprehensive review among and between WLC and OCT imaging data. These techniques include (1) a volumetric mosaicing algorithm to extend the field of view of OCT, (2) 3D reconstruction technique to generate models with the shape and appearance of the bladder, and (3) a registration approach that registers OCT data to the 3D bladder model. Taken together, the new OCT endoscope and image reconstruction algorithms I describe can have a tremendous impact on the future of cystoscopy for improved management of bladder cancer patients.