Cone-beam CT (CBCT) has become the standard image guidance tool for patient setup in image-guided radiation therapy. However, due to its large illumination field, scattered photons severely degrade its image quality. While kernel-based scatter correction methods have been used routinely in the clinic, it is still desirable to develop Monte Carlo (MC) simulation-based methods due to their accuracy. However, the high computational burden of the MC method has prevented routine clinical application. This paper reports our recent development of a practical method of MC-based scatter estimation and removal for CBCT. In contrast with conventional MC approaches that estimate scatter signals using a scatter-contaminated CBCT image, our method used a planning CT image for MC simulation, which has the advantages of accurate image intensity and absence of image truncation. In our method, the planning CT was first rigidly registered with the CBCT. Scatter signals were then estimated via MC simulation. After scatter signals were removed from the raw CBCT projections, a corrected CBCT image was reconstructed. The entire workflow was implemented on a GPU platform for high computational efficiency. Strategies such as projection denoising, CT image downsampling, and interpolation along the angular direction were employed to further enhance the calculation speed. We studied the impact of key parameters in the workflow on the resulting accuracy and efficiency, based on which the optimal parameter values were determined. Our method was evaluated in numerical simulation, phantom, and real patient cases. In the simulation cases, our method reduced mean HU errors from 44 HU to 3 HU and from 78 HU to 9 HU in the full-fan and the half-fan cases, respectively. In both the phantom and the patient cases, image artifacts caused by scatter, such as ring artifacts around the bowtie area, were reduced. With all the techniques employed, we achieved computation time of less than 30 sec including the time for both the scatter estimation and CBCT reconstruction steps. The efficacy of our method and its high computational efficiency make our method attractive for clinical use.

High sensitivity dedicated cardiac systems cameras provide an opportunity to lower injected doses for SPECT myocardial perfusion imaging (MPI), but the exact limits for lowering doses have not been determined. List mode data acquisition allows for reconstruction of various fractions of acquired counts, allowing a simulation of gradually lower administered dose. We aimed to determine the feasibility of very low dose MPI by exploring the minimal count level in the myocardium for accurate MPI. Methods Seventy nine patients were studied (mean body mass index 30.0 ± 6.6, range 20.2–54.0 kg/m2) who underwent 1-day standard dose 99mTc-sestamibi exercise or adenosine rest/stress MPI for clinical indications employing a Cadmium Zinc Telluride dedicated cardiac camera. Imaging time was 14-min with 803 ± 200 MBq (21.7 ± 5.4mCi) of 99mTc injected at stress. To simulate clinical scans with lower dose at that imaging time, we reframed the list-mode raw data to have count fractions of the original scan. Accordingly, 6 stress equivalent datasets were reconstructed corresponding to each fraction of the original scan. Automated QPS/QGS software was used to quantify total perfusion deficit (TPD) and ejection fraction (EF) for all 553 datasets. Minimal acceptable count was determined based on previous report with repeatability of same-day same-injection Anger camera studies. Pearson correlation coefficients and SD of differences with TPD for all scans were calculated. Results The correlations of quantitative perfusion and function analysis were excellent for both global and regional analysis on all simulated low-counts scans (all r ≥0.95, p<0.0001). Minimal acceptable count was determined to be 1.0 million counts for the left ventricular region. At this count level, SD of differences was 1.7% for TPD and 4.2% for EF. This count level would correspond to a 92.5 MBq (2.5 mCi) injected dose for the 14 min acquisition. Conclusion 1.0 million myocardial count images appear to be sufficient to maintain excellent agreement quantitative perfusion and function parameters as compared to those determined from 8.0 million count images. With a dedicated cardiac camera, these images could be obtained over 10 minutes with an effective radiation dose of less than 1 mSv without significant sacrifice in accuracy.

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