Prostate Cancer Grade Mapping with Transrectal Electrical Impedance Tomography
Abstract
No clinical test or imaging modality is able to accurately discriminate between aggressive and indolent prostate cancer. As a result, a significant number of men are unnecessarily treated with radical, life-altering therapies including external beam radiation, brachytherapy, and radical prostatectomy. The New England Journal of Medicine reports that 15 men need to undergo radical prostatectomy in order to save a single man from dying of prostate cancer. This means that 14 of 15 men are "overtreated" due to inaccurately identifying how aggressive their disease is. The primary reason for this is that the definitive method for diagnosing prostate cancer and determining treatment strategies depends primarily on microscopic assessment of tissue cores obtained during a transrectal ultrasound (TRUS)-guided biopsy; a typical biopsy procedure samples less than 0.5% of a typical prostate gland. Because of the small volume of tissue sampled, it is difficult to determine with certainty how aggressive or indolent the disease is. An imaging modality able to accurately map cancer morphology, based on a Gleason-like scoring system, throughout the entire prostatic volume would have obvious clinical benefits for determining appropriate treatment strategies and reducing the number of men undergoing unnecessary radical therapies. We propose to develop an imaging device capable of mapping the cancer grade distribution in a man undergoing a routine image-guided prostate biopsy procedure to improve patient care. Specifically, we plan to integrate electrical property imaging with a standard clinically accepted ultrasound probe. We have previously shown that the electrical impedance (a property that describes how easily electrical current passes through a tissue) of tissue is sensitive to a tissue s cellular arrangement and can be used to distinguish cancer from benign prostate. We have also shown significant differences in the electrical properties between cancers of different Gleason grades. The ability to distinguish high- and low-grade prostate cancer is similar to that reported for magnetic resonance (MR) imaging-based alternatives, currently the most promising technologies for grading disease. Our team has been developing a multimodal imaging platform able to perform ultrasound imaging in tandem with electrical impedance tomography (EIT). To date, we have coupled this EIT system to both side-fired and end-fired TRUS probes for synchronous ultrasound and EIT data acquisition, but have been limited in (1) the frequency range over which we can acquire impedance data and (2) the speed at which we acquire data. We have shown that high-frequency impedance data provide much more accurate discrimination between high- and low-grade disease, and in order to integrate this technology into a routine biopsy procedure, it is critical that data acquisition rates are extremely fast (<1 second per image). Here we propose to develop a custom EIT system-on-a-chip that will enable us to achieve high-frequency, real-time data acquisition. In addition, we aim to couple an electrical impedance sensing biopsy needle that was developed as part of a Prostate Cancer Research Program-sponsored New Investigator Award into this image-guided biopsy framework to improve image resolution and accuracy. By coupling this needle-based device with our transrectal EIT system, we expect to produce highly accurate images of Gleason grade within the prostate. In an effort to rapidly translate this technology to the clinic, the multi-modal image-guidance system will be used to image a series of 25 ex vivo human prostates; we propose to evaluate how well the pathology of the entire gland correlates to the electrical property images obtained and to assess the clinical potential imaging the electrical properties of prostate provides. We have established a unique pair of Principal Investigators, Odame (expert in system-on-a-chip design) and Halter (expert in prostate EIT
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Apr 04, 2016
- Source ID
- W81XWH1510572
Entities
People
- Kofi Odame
Organizations
- Dartmouth College
- United States Army