The American Association of Physicists in Medicine Task Group 119 instructed institutions to use a low‐dose threshold of 10% or a region of interest determined by the jaw setting when they collected gamma analysis quality assurance (QA) data for the planar dose distribution. However, there are no clinical data to quantitatively demonstrate the impact of the low‐dose threshold on the gamma index. Therefore, we performed a gamma analysis with various low‐dose thresholds in the range of 0% to 15% according to both global and local normalization and different acceptance criteria (3%/3 mm, 2%/2 mm, and 1%/1 mm). A total of 30 treatment plans — 10 head and neck, 10 brain, and 10 prostate cancer cases — were randomly selected from the Varian Eclipse treatment planning system (TPS). For the gamma analysis, a calculated portal image was acquired through a portal dose calculation algorithm in the Eclipse TPS, and a measured portal image was obtained using an electronic portal‐imaging device. Then, the gamma analysis was performed using the Portal Dosimetry software (Varian Medical Systems, Palo Alto, CA). The gamma passing rate (%GP) for the global normalization decreased as the low‐dose threshold increased, and all low‐dose thresholds led to %GP values above 95% for both the 3%/3 mm and 2%/2 mm criteria. However, for the local normalization, %GP for a low‐dose threshold of 10% was 7.47%, 10.23%, and 6.71% greater than the low‐dose threshold of 0% for head and neck, brain, and prostate for the 3%/3 mm criteria, respectively. The results indicate that applying the low‐dose threshold to global normalization does not have a critical impact on patient‐specific QA results. However, in the local normalization, the low‐dose threshold level should be carefully selected because the excluded low‐dose points could cause the average %GP to increase rapidly.PACS number: 87.55.Qr

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Purpose: Conventional iterative low-dose CBCT reconstruction techniques are slow and tend to over-smooth edges through uniform weighting of the image penalty gradient. In this study, we present a non-iterative analytical low-dose CBCT reconstruction technique by restoring the noisy low-dose CBCT projection with the non-local total variation (NLTV) method.Methods: We modeled the low-dose CBCT reconstruction as recovering high quality, high-dose CBCT x-ray projections (100 kVp, 1.6 mAs) from low-dose, noisy CBCT x-ray projections (100 kVp, 0.1 mAs). The restoration of CBCT projections was performed using the NLTV regularization method. In NLTV, the x-ray image is optimized by minimizing an energy function that penalizes gray-level difference between pair of pixels between noisy x-ray projection and denoising x-ray projection. After the noisy projection is restored by NLTV regularization, the standard FDK method was applied to generate the final reconstruction output.Results: Significant noise reduction was achieved comparing to original, noisy inputs while maintaining the image quality comparable to the high-dose CBCT projections. The experimental validations show the proposed NLTV algorithm can robustly restore the noise level of x-ray projection images while significantly improving the overall image quality. The improvement in normalized mean square error (NMSE) and peak signal-to-noise ratio (PSNR) measured from the non-local total variation-gradient projection (NLTV-GPSR) algorithm is noticeable compared to that of uncorrected low-dose CBCT images. Moreover, the difference of CNRs from the gains from the proposed algorithm is noticeable and comparable to high-dose CBCT. Conclusion:The proposed method successfully restores noise degraded, low-dose CBCT projections to high-dose projection quality. Such an outcome is a considerable improvement to the reconstruction result compared to the FDK-based method. In addition, a significant reduction in reconstruction time makes the proposed algorithm more attractive. This demonstrates the potential use of the proposed algorithm for clinical practice in radiotherapy.

The purpose of the present study was to develop a hybrid magnetic resonance/computed tomography (MR/CT)-compatible phantom and tissue-equivalent materials for each MR and CT image. Therefore, the essential requirements necessary for the development of a hybrid MR/CT-compatible phantom were determined and the development process is described. A total of 12 different tissue-equivalent materials for each MR and CT image were developed from chemical components. The uniformity of each sample was calculated. The developed phantom was designed to use 14 plugs that contained various tissue-equivalent materials. Measurement using the developed phantom was performed using a 3.0-T scanner with 32 channels and a Somatom Sensation 64. The maximum percentage difference of the signal intensity (SI) value on MR images after adding K2CO3 was 3.31%. Additionally, the uniformity of each tissue was evaluated by calculating the percent image uniformity (%PIU) of the MR image, which was 82.18 ±1.87% with 83% acceptance, and the average circular-shaped regions of interest (ROIs) on CT images for all samples were within ±5 Hounsfield units (HU). Also, dosimetric evaluation was performed. The percentage differences of each tissue-equivalent sample for average dose ranged from −0.76 to 0.21%. A hybrid MR/CT-compatible phantom for MR and CT was investigated as the first trial in this field of radiation oncology and medical physics.

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