Abstract

Cherenkov-excited luminescence scanned imaging (CELSI) is achieved with External Beam Radiotherapy, to map out molecular luminescence intensity or lifetime in tissue. In order to realize a deeper imaging depth with a reasonable spatial resolution, we optimized the original scanning gesture to do in a similar way to computed tomography (CT) and the image reconstruction was instead used a customized Maximum-likelihood expectation maximization (ML-EM) for CELSI. In tomographic CELSI (TCELSI), tomographic images are generated by irradiating the subject using a sequence of programmed X-ray beams at a fixed projection angle, while sensitive measurement is to take a sum for all image pixels from an intensified charge-coupled device. By restricting the X-ray excitation to a single, narrow beam of radiation, the origin of the optical photons can be inferred regardless of where these photons were detected, and how many times they scattered in tissue. Measurement geometry was designed for clinical expectation: CT scanning was achieved by a clinical linear accelerator (LINAC), where X-ray beam sequence and multiple projections were realized with multi leaf collimator (MLC) and gantry movement, respectively. Furthermore, in most modern External Beam Radiotherapy, MLC movement is synchronized with gantry angle to release a uniform radiation, and some of treatment plans, e.g., Intensity Modulated Radiation Therapy (IMRT), have a potential to match the scanning way mentioned. By including Cherenkov imaging results, medium surface profile can be additionally acquired, which can be used as boundary reference to do depth correction and co-register with molecular images. Resolution phantom studies showed that a 0.3 mm diameter capillary tube containing 0.01 nM luminescent nanospheres could be recognized at a depth of 21 mm into tissue-like media. Small animal imaging with a 1 mm diameter cylindrical target demonstrated that fast 3D data acquisition was achieved by a multi-pinhole collimator to image local luminescence 20mm deep.

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