Radiological Physics and Technology最新文献

This study aimed to evaluate discrepancies between planned, delivered and adapted doses to target and organs at risk (OARs) during bladder cancer radiotherapy, using deformable image registration from CT to CBCT in view of better treatment personalization. Twenty patients with a total of 165 CBCT images were analysed. Intensity modulated techniques (IMRT and VMAT) were simulated in the Monaco planning system. The initial plans were adapted to each CBCT using the Adapt to shape (ATS) function. A reduction in PTV66 and CTV66 coverage was observed upon calculation of treatment dose on CBCTcalc in comparison with plans on CT. The PTV66 coverage was 86.7% IMRT and 86.4% VMAT, respectively. Meanwhile, the optimized plans on CBCTopt provided PTV66 coverage of 97.1% IMRT and 96.4% VMAT, which was similar to the initial planning on CT (97.4% IMRT and 96.6% VMAT). Furthermore, CTV66 showed a coverage of 94.2% IMRT and 94.0% VMAT on CBCTcalc, in comparison to the values on CT (99.8% IMRT and 99.9% VMAT) and the values on CBCTopt (99.8% IMRT and 99.8% VMAT). For OARs, the rectum, bowel bag, and sigmoid exhibited higher values on CBCTcalc than on CT planning and CBCTopt. This study demonstrates that CBCT- guided adaptive radiotherapy enhances treatment precision and personalization in bladder cancer, improving target coverage and reducing radiation exposure to healthy tissues. Next to highlighting the importance of personalizing bladder cancer radiotherapy, the study substantiates that daily reoptimization with ATS constitutes an efficacious strategy in centers with limited resources.

Dosimetry using SPECT/CT images enables personalized medicine by estimating absorbed doses and optimizing therapy. Differences in organ contouring and calculation algorithms contribute to inter-institutional variability, emphasizing the need for standardization. The present study aimed to investigate factors contributing to inter-institutional variability in kidney dosimetry in Japan. We analyzed four time points in SPECT/CT images of one male and one female patient each from the ¹⁷⁷Lu SNMMI Dosimetry Challenge. Kidney volumes and absorbed doses were calculated at 10 Japanese institutes using their preferred organ-based (OLINDA 2.2, IDAC DOSE 2.1) and voxel-based (Voxel Dosimetry, RT-PHITS, MIM SurePlan MRT, OpenDose3D) software. Reference volumes of interest (VOI) files were distributed to assess the effect of contouring differences on kidney volumes and absorbed doses. Manual VOI contouring revealed substantial inter-institutional variability in kidney volumes, with coefficients of variation (%CVs) up to 16.9%. The reference VOIs reduced volume variability to ≤ 7.4%. Compared to manual VOIs, reference VOIs showed slightly increased doses in both patients with slightly reduced inter-institutional variability. The absorbed doses were generally higher in voxel- than organ-based dosimetry. The %CVs of the right and left kidneys in female patient decreased from 31.36% to 6.26% and 41.28%-3.97%, respectively. Variability in Kidney volume and absorbed doses significantly varied among Japanese institutes. Reference VOIs reduced volume variability but could not fully control dose differences. Voxel-based dosimetry can mitigate inter-institutional variability independent of contouring. Our findings emphasize the importance of algorithm standardization for reliable ¹⁷⁷Lu-DOTATATE kidney dosimetry in Japan.

Previous studies have shown that high kilovoltage (kV) angiographic imaging techniques can reduce radiation doses to patients more effectively than using low kV techniques. While radiologists often accept the resulting image quality, a detailed quantitative comparison between these techniques remains limited. This study aimed to evaluate and compare the quality of cerebral angiographic images acquired using high kV (79-90 kV) and low kV (68-82 kV) techniques on a biplane digital subtraction angiography (DSA) system. Images were analyzed from patients with cerebral aneurysms as well as a quality assurance phantom (TO DSA), focusing on 2-dimensional angiography (2D-DSA). The contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) were measured at various vascular locations in posteroanterior (PA) axial and lateral views. While demographic data did not differ between groups, CNR for PA axial view and PA phantom images produced with high kV was significantly lower than that with low kV. In contrast, the high kV technique demonstrated higher SNR values in both PA and lateral views compared to the low kV technique. Radiation dose per frame confirmed a reduction in dose for the high kV protocol. Conversely, TO DSA images acquired using high kV had a lower SNR than those from low kV. The low kV technique achieved better vessel contrast, as evidenced by its higher CNR compared to the high kV technique. However, it also resulted in a lower SNR in patient images and a higher radiation dose. Protocol selection should, therefore, aim to optimize the trade-off between image quality and radiation exposure.

This study aimed to propose a definition of linearity in image reconstruction and demonstrate, by reductio ad absurdum, that the row-action maximum likelihood algorithm (RAMLA) and ordered subset expectation maximization (OSEM) are nonlinear when the number of iterations is low and linear approximation when the number of iterations increases. Block sequential regularized expectation maximization (BSREM) and one-step late maximum a posteriori expectation maximization (OSLEM), which serve as regularized versions of RAMLA and OSEM, respectively, remain nonlinear regardless of the number of iterations. Simulations using ideal two-dimensional (2D) parallel beam projections validated the results of the reductio ad absurdum proof. The three numerical phantoms were point source ${\overline{x}}_1$ , represented by 2D Gaussian with a full width at half maximum of 3 pixels positioned at the center of disk background; point source ${\overline{x}}_2$ , separated by 24 pixels along the x-axis; and point source ${\overline{x}}_3$ , is the sum of ${\overline{x}}_1$ and ${\overline{x}}_2$ . In numerical experiment, when the difference of the area under the curve (AUC) or recovery for reconstructed image of ${\overline{x}}_3$ and the summed reconstructed images of ${\overline{x}}_1$ and ${\overline{x}}_2$ is within reference values, or when AUC profiles are visually consistent, we defined image reconstruction as linear approximation. RAMLA and OSEM were deemed nonlinear when less than 20 iterations were performed with 64 subsets and linear approximation when $\ge 20$ iterations were used. By contrast, BSREM and OSLEM remained nonlinear. Algebraic reconstruction technique is linear and its regularized variant has a tendency of linear approximation, indicating that the same regularization function works differently in linear and nonlinear image reconstructions.

Medical radiation plays a crucial role in diagnostic imaging; however, any exposure carries potential risks. The thyroid gland, due to its proximity to the imaging field, is particularly vulnerable to radiation during CT brain scans. This study aims to evaluate the effectiveness of lead thyroid shields in reducing the estimated absorbed dose to the thyroid gland during CT brain imaging. This cross-sectional study was conducted at a tertiary care hospital in Sri Lanka over a 3-month period. Adult patients referred for contrast-enhanced CT (CECT) brain scans, who underwent both non-contrast and contrast-enhanced imaging, were included. The estimated absorbed dose to the thyroid gland was calculated using a Dose i-R Electronic Personal Dosimeter. Radiation dose measurements were taken with and without a 0.5 mm lead thyroid shield by placing the dosimeter both above and behind the shield. The sample consisted of 32 patients. The mean (SD) effective radiation dose during the procedures was calculated as 2.325 (0.118) mGy using a standard conversion factor of 0.0021. Without the thyroid shield, the mean (SD) estimated absorbed dose was 0.748 (0.178) mGy, which decreased to 0.352 (0.113) mGy with the lead thyroid shield. There was a statistically significant reduction in estimated absorbed dose with the thyroid shielding. There was a significant reduction in the estimated absorbed dose to the thyroid region with the use of the lead thyroid shield in patients undergoing CT brain studies. These findings highlight the effectiveness of lead thyroid shielding in minimizing radiation exposure to the thyroid region.

The aim of this study is to evaluate the impact of dynamic jaw width adjustment in tomotherapy on hippocampal sparing, target dose conformity, and treatment efficiency in hippocampal-avoidance whole-brain radiotherapy (HA-WBRT), in accordance with RTOG 0933 guidelines. A retrospective study of 60 patients treated with HA-WBRT was conducted. CT-MRI fusion facilitated accurate hippocampal delineation. Treatment plans were created using Accuray Precision TPS and delivered on the Radixact Tomotherapy system with three jaw widths (1 cm, 2.5 cm, and 5 cm), fixed pitch (0.215), and modulation factor (3.0). The prescription dose was 30 Gy in 10 fractions. Evaluation metrics included PTV coverage (D98%, V95%, D2%, Dmax), homogeneity index (HI), conformity index (CI), hippocampal and lens doses, and beam-on time (BOT). Plan verification was performed with ArcCHECK using 3%/3 mm and 3%/2 mm gamma criteria. The 1 cm jaw achieved the best PTV coverage (D98% = 29.22 Gy, V95% = 98.71%), with HI = 0.09, CI = 0.99, and superior hippocampal sparing (Dmax = 14.91 Gy, Dmin = 7.57 Gy), but had the longest BOT (1165 s). Wider jaws (2.5 cm, 5 cm) reduced BOT (480 s, 280 s) but slightly compromised conformity and increased OAR doses, all within limits. Jaw width selection in Helical Tomotherapy influences dose distribution characteristics and treatment delivery efficiency in hippocampus-sparing WBRT. A 1 cm jaw width provides superior dosimetric conformity and enhanced hippocampal sparing, albeit at the cost of increased BOT. In contrast, wider jaw widths (2.5 cm and 5 cm) improve delivery efficiency but result in modest reductions in dose precision and organ-at-risk sparing. Therefore, jaw width selection should be carefully individualized based on clinical objectives, balancing the trade-off between organ preservation and treatment efficiency.

This study compares the dosimetric performance of Base Dose Optimization (BDO) and Gradient-Based Optimization (GBO) for extended target volumes in Total Body Irradiation (TBI). The focus is on overlapping regions using the Rando Phantom. The study evaluates dose distribution, conformity, homogeneity, and sensitivity to positional deviations. The Rando Phantom was used for treatment planning with both BDO and GBO plans. Positional shifts of ± 5 mm and ± 10 mm were introduced to assess uncertainties. Dosimetric metrics included mean dose, minimum dose, maximum dose, homogeneity index (HI), and conformity index (CI). Positional deviations and their impact on dose variations were analyzed. Quality assurance was performed using OSLDs and an array detector. The BDO plan delivered higher mean doses (103.6%-108.7%) and hotspot values, with a maximum of 133.7%. In contrast, the GBO plan produced a more uniform dose distribution (99.6%-100.3%) with lower hotspots, peaking at 112%. The BDO plan achieved better uniformity (HI 0.025-0.103) and higher conformity (CI 0.938-0.981). The GBO plan showed greater variability (HI 0.143-0.253) and slightly lower conformity (CI 0.941-0.964). Positional shifts revealed that the BDO plan was highly sensitive, with overdoses of + 46.60% and underdoses of - 47.29%. The GBO plan showed smaller deviations (+ 11.62% overdose, - 11.73% underdose). Gamma analysis demonstrated higher pass rates for the GBO plan. The BDO plan excels in target coverage and conformity but is sensitive to positional shifts. The GBO plan offers better uniformity and robustness, supporting its use in complex clinical scenarios. Further refinement of both approaches could improve clinical applicability and patient outcomes.

We evaluated the effectiveness of aluminum interspace grids with varying grid ratios, conventional 10:1 (r10) and 14:1 (r14) and experimental 17:1 (r17), in terms of image quality of digital radiography for phantom thicknesses of 20 to 30 cm. The signal-to-noise improvement factor (SIF) and signal-difference-to-noise ratio (SDNR) were measured at tube voltages of 80-110 kV. An acrylic object and a bone equivalent object were used for the SDNR measurements. While the grid ratio had a positive impact on SIF, its effect on SDNR was not remarkable: SDNR was not higher with r17 than with r14 for the acrylic object. For the bone-like object, it exhibited some meager, or even negative, improvements with r14 and r17 compared with r10. These results can be attributed to reduced contrast caused by beam hardening due to higher grid ratios. Consequently, the grid ratio should be chosen considering the reduction in contrast.

Accurate signal-to-noise ratio (SNR) measurement is essential for evaluating image quality in magnetic resonance imaging (MRI). While the subtraction-map method provides precise SNR measurements, it requires two consecutive acquisitions, limiting its clinical applicability. This study aims to develop and validate a method for practical SNR measurement using clinical MRI images. The proposed method generates an SNR map by computing a noise-only image from a single MRI image using pixel shifting and edge component removal. The accuracy of our method was compared with the subtraction-map method in three evaluations: (1) optimization of a key parameter for edge component removal, (2) analysis of spatial resolution and SNR level effects, and (3) validation using brain MRI images. The study included brain MRI from 188 patients, and SNR measurements were performed on the resulting images. Correlation coefficients and Bland-Altman analysis were used for comparisons. Parameter optimization identified an optimal threshold for separating noise and edge components. Higher spatial resolution improved accuracy, whereas lower resolution and low SNR conditions led to overestimation. In clinical MRI, the proposed method showed a strong correlation with the subtraction-map method (Spearman r = 0.96), and the highest average error rate was 8.1% in T1-weighted images. Bland-Altman analysis demonstrated good agreement across sequences and regions. This method enables practical SNR estimation from a single image, eliminating the need for repeated acquisitions. While limitations remain in low-SNR or structurally complex regions, the method shows promise as a practical tool for retrospective and routine clinical image quality assessments.