Purpose Spectral CT using a photon counting x-ray detector (PCXD) shows great potential for measuring material composition based on energy dependent x-ray attenuation. Spectral CT is especially suited for imaging with K-edge contrast agents to address the otherwise limited contrast in soft tissues. We have developed a micro-CT system based on a PCXD. This system enables both 4 energy bins acquisition, as well as full-spectrum mode in which the energy thresholds of the PCXD are swept to sample the full energy spectrum for each detector element and projection angle. Measurements provided by the PCXD, however, are distorted due to undesirable physical effects in the detector and can be very noisy due to photon starvation in narrow energy bins. To address spectral distortions, we propose and demonstrate a novel artificial neural network (ANN)-based spectral distortion correction mechanism, which learns to undo the distortion in spectral CT, resulting in improved material decomposition accuracy. To address noise, post-reconstruction denoising based on bilateral filtration, which jointly enforces intensity gradient sparsity between spectral samples, is used to further improve the robustness of ANN training and material decomposition accuracy. Methods Our ANN-based distortion correction method is calibrated using 3D-printed phantoms and a model of our spectral CT system. To enable realistic simulations and validation of our method, we first modeled the spectral distortions using experimental data acquired from 109Cd and 133Ba radioactive sources measured with our PCXD. Next, we trained an ANN to learn the relationship between the distorted spectral CT projections and the ideal, distortion-free projections in a calibration step. This required knowledge of the ground truth, distortion-free spectral CT projections, which were obtained by simulating a spectral CT scan of the digital version of a 3D-printed phantom. Once the training was completed, the trained ANN was used to perform distortion correction on any subsequent scans of the same system with the same parameters. We used joint bilateral filtration (BF) to perform noise reduction by jointly enforcing intensity gradient sparsity between the reconstructed images for each energy bin. Following reconstruction and denoising, the CT data was spectrally decomposed using the photoelectric effect, Compton scattering, and a K-edge material (i.e. iodine). The ANN-based distortion correction approach was tested using both simulations and experimental data acquired in phantoms and a mouse with our PCXD-based micro-CT system for 4 bins and full-spectrum acquisition modes. The iodine detectability and decomposition accuracy were assessed using the contrast-to-noise ratio and relative error in iodine concentration estimation metrics in images with and without distortion correction. Results In simulation, the material decomposition accuracy in the reconstructed data was vastly improved following distortion correction and denoising, with 50% and 20% reductions in material conce...

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Purpose:To demonstrate an embedded tissue equivalent presage dosimeter for measuring 3D doses in moving tumors and to study the interplay effect between the tumor motion and intensity modulation in hypofractioned Volumetric Modulated Arc Therapy(VMAT) lung treatment.Methods:Motion experiments were performed using cylindrical Presage dosimeters (5cm diameter by 7cm length) mounted inside the lung insert of a CIRS thorax phantom. Two different VMAT treatment plans were created and delivered in three different scenarios with the same prescribed dose of 18 Gy. Plan1, containing a 2 centimeter spherical CTV with an additional 2mm setup margin, was delivered on a stationary phantom. Plan2 used the same CTV except expanded by 1 cm in the Sup‐Inf direction to generate ITV and PTV respectively. The dosimeters were irradiated in static and variable motion scenarios on a Truebeam system. After irradiation, high resolution 3D dosimetry was performed using the Duke Large Field‐of‐view Optical‐CT Scanner, and compared to the calculated dose from Eclipse.Results:In the control case (no motion), good agreement was observed between the planned and delivered dose distributions as indicated by 100% 3D Gamma (3% of maximum planned dose and 3mm DTA) passing rates in the CTV. In motion cases gamma passing rates was 99% in CTV. DVH comparisons also showed good agreement between the planned and delivered dose in CTV for both control and motion cases. However, differences of 15% and 5% in dose to PTV were observed in the motion and control cases respectively.Conclusion:With very high dose nature of a hypofraction treatment, significant effect was observed only motion is introduced to the target. This can be resulted from the motion of the moving target and the modulation of the MLC. 3D optical dosimetry can be of great advantage in hypofraction treatment dose validation studies.

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