Anatomically accurate hard priors for transrectal electrical impedance tomography (TREIT) of the prostate.

Current prostate biopsy procedures entail sampling tissues at template-based locations that are not patient specific. Ultrasound (US)-coupled transrectal electrical impedance tomography (TREIT), featuring an endorectal US probe retrofitted with electrodes, has been developed for prostate imaging. This multi-modal imaging system aims to identify suspicious tumor regions based on their electrical properties and ultimately provide additional patient-specific locations where to take biopsy samples. Unfortunately, the open-domain geometry associated with TREIT results in a severely ill-posed problem due to the small number of measurements and unbounded imaging domain. Furthermore, reconstructing contrasts within the prostate volume is challenging because the conductivity differences between the prostate and surrounding tissues are much larger than the conductivity differences between benign and malignant tissues within the prostate. To help overcome these problems, anatomically accurate hard priors can be employed to limit estimation of the electrical property distribution to within the prostate volume; however, this requires the availability of structural information. Here, a method that extracts the prostate surface from US images and incorporates this surface into the image reconstruction algorithm has been developed to enable estimation of electrical parameters within the prostate volume. In this paper, the performance of this algorithm is evaluated against a more traditional EIT algorithm that does not use anatomically accurate structural information, in the context of numerical simulations and phantom experiments. The developed anatomically accurate hard-prior algorithm demonstrably identifies contrasts within the prostate volume while an algorithm that does not rely on anatomically accurate structural information is unable to localize these contrasts. While inclusions are identified in the correct locations, they are found to be smaller in size than the actual object due to the rapid decay in sensitivity at increasing distances from the probe surface. Despite this, identifying the size of the inclusion accurately may not be essential for biopsy guidance in a clinical setting; instead, knowledge of the general vicinity of a cancerous lesion may be sufficient for suggesting and guiding clinicians to extract additional biopsy cores.