Silicon-based 3D beta ray radiopharmaceutical trackers: a Monte Carlo computational study

<i>Objective.</i>Radiopharmaceutical development and dose planning requires detailed knowledge of isotope distribution on small distance scales. To quantify the radiotracer uptake and distribution in biological samples in cellular scale, digital autoradiography (DAR) techniques have been developed. However, conventional DARs are limited to imaging of thin tissue samples in a 2D planar detection modality. Radiopharmaceutical therapy (RPT) small-scale dosimetry would be greatly enhanced by a detector capable of imaging thick tissues intact, saving acquisition time and preserving volumetric information.<i>Approach.</i>We propose a new imaging modality, three-dimensional DAR (3D DAR), capable of imaging thick tissue samples in a single exposure, enabling preservation of intact tissues and imaging short-lived isotopes. The proposed system uses multiple layers of ultra-thin silicon detectors to track charged particles. By stacking two detectors in parallel, the particle trajectory is estimated from connecting the line of responses from detectors for each event. In this study, we use Monte-Carlo simulation to quantify the spatial resolution and sensitivity for sources at different depths within the thick tissue samples.<i>Main results.</i>Through the mathematical modeling of detector configuration and simulation on broad energy levels with depths, we demonstrated tens of micron spatial resolution and approximately 30% coincidence sensitivity. Spatial resolution was improved by approximately a factor of 3 compared to 2D, achieving about 27 <i>µ</i>m at 30 <i>µ</i>m depth. This confirms that proposed 3D DAR provides volumetric information of sources within tissue.<i>Significance.</i>The proposed detector design exhibited the potential to provide sub-tissue scale activity maps across substantially thicker tissue samples than those possible with conventional DAR approaches. The 3D activity map from the detector will enable a more detailed understanding of the radiopharmaceutical distribution in the tumor microenvironment and greatly facilitate<i>ex-vivo</i>tissue analysis for preclinical RPT development.