Improving dose calculation accuracy in preclinical radiation experiments using multi-energy element resolved cone beam CT

Multi-stage image registration based on list-mode proton radiographies for small animal proton irradiation: A simulation study

We present a multi-stage and multi-resolution deformable image registration framework for image-guidance at a small animal proton irradiation platform. The framework is based on list-mode proton radiographies acquired at different angles, which are used to deform a 3D treatment planning CT relying on normalized mutual information (NMI) or root mean square error (RMSE) in the projection domain. We utilized a mouse X-ray micro-CT expressed in relative stopping power (RSP), and obtained Monte Carlo simulations of proton images in list-mode for three different treatment sites (brain, head and neck, lung). Rigid transformations and controlled artificial deformation were applied to mimic position misalignments, weight loss and breathing changes. Results were evaluated based on the residual RMSE of RSP in the image domain including the comparison of extracted local features, i.e. between the reference micro-CT and the one transformed taking into account the calculated deformation. The residual RMSE of the RSP showed that the accuracy of the registration framework is promising for compensating rigid (>97% accuracy) and non-rigid (∼95% accuracy) transformations with respect to a conventional 3D-3D registration. Results showed that the registration accuracy is degraded when considering the realistic detector performance and NMI as a metric, whereas the RMSE in projection domain is rather insensitive. This work demonstrates the pre-clinical feasibility of the registration framework on different treatment sites and its use for small animal imaging with a realistic detector. Further computational optimization of the framework is required to enable the use of this tool for online estimation of the deformation.

Small animal photon counting cone-beam CT on a preclinical radiation research platform to improve radiation dose calculation accuracy

Objective.Cone beam CT (CBCT) in preclinical small animal irradiation platforms provides essential information for image guidance and radiation dose calculation for experiment planning. This project developed a photon-counting detector (PCD)-based multi(3)-energy (ME-)CBCT on a small animal irradiator to improve the accuracy of material differentiation and hence dose calculation, and compared to conventional flat panel detector (FPD)-based CBCT.Approach.We constructed a mechanical structure to mount a PCD to an existing preclinical irradiator platform and built a data acquisition pipeline to acquire x-ray projection data with a 100 kVp x-ray beam using three different energy thresholds in a single gantry rotation. We implemented an energy threshold optimization scheme to determine optimal thresholds to balance signal-to-noise ratios (SNRs) among energy channels. Pixel-based detector response calibration was performed to remove ring artifacts in reconstructed CBCT images. Feldkamp-Davis-Kress method was employed to reconstruct CBCT images and a total-variance regularization-based optimization model was used to decompose CBCT images into bone and water material images. We compared dose calculation results using PCD-based ME-CBCT with that of FPD-based CBCT.Main results.The optimal nominal energy thresholds were determined as 26, 56, and 90 keV, under which SNRs in a selected region-of-interest in the water region were 6.11, 5.91 and 5.93 in the three energy channels, respectively. Compared with dose calculation results using FPD-based CBCT, using PCD-based ME-CBCT reduced the mean relative error from 49.5% to 16.4% in bone regions and from 7.5% to 6.9% in soft tissue regions.Significance.PCD-based ME-CBCT is beneficial in improving radiation dose calculation accuracy in experiment planning of preclinical small animal irradiation researches.

Improving small animal cone beam CT resolution by mitigating x-ray focal spot induced blurring via deconvolution

Objective. Modern preclinical small animal radiation platforms utilize cone beam computerized tomography (CBCT) for image guidance and experiment planning purposes. The resolution of CBCT images is of particular importance for visualizing fine animal anatomical structures. One major cause of spatial resolution reduction is the finite size of the x-ray focal spot. In this work, we proposed a simple method to measure x-ray focal spot intensity map and a CBCT image domain deblurring model to mitigate the effect of focal spot-induced image blurring. Approach. We measured a projection image of a tungsten ball bearing using the flat panel detector of the CBCT platform. We built a forward blurring model of the projection image and derived the spot intensity map by deconvolving the measured projection image. Based on the measured spot intensity map, we derived a CBCT image domain blurring model for images reconstructed by the filtered backprojection algorithm. Based on this model, we computed image domain blurring kernel and improved the CBCT image resolution by deconvolving the CBCT image. Main results. We successfully measured the x-ray focal spot intensity map. The spot size characterized by full width at half maximum was ∼0.75 × 0.55 mm2 at 40 kVp. We computed image domain convolution kernels caused by the x-ray focal spot. A simulation study on noiseless projections was performed to evaluate the spatial resolution improvement exclusively by the focal spot kernel, and the modulation transfer function (MTF) at 50% was increased from 1.40 to 1.65 mm−1 for in-plane images and 1.05–1.32 mm−1 for cross-plane images. Experimental studies on a CT insert phantom and a plastinated mouse phantom demonstrated improved spatial resolution after image domain deconvolution, as indicated by visually improved resolution of fine structures. MTF at 50% was improved from 1.00 to 1.12 mm−1 for in-plane direction and from 0.72 to 0.84 mm−1 for cross-plane direction. Significance. The proposed method to mitigate blurring caused by finite x-ray spot size and improve CBCT image resolution is simple and effective.