Journal of Medical Physics最新文献

Purpose: The distribution of neutron ambient dose equivalent within the TrueBeam 10 MV photon chamber was investigated.

Materials and methods: The research used particle and heavy ion transport code system (PHITS) code and JENDL-5.0 to simulate the neutron ambient dose equivalent on and around TrueBeam's head. The simulated results were compared with the measured results using CR-39 detectors when TrueBeam radiated 5000 monitor units of 10 MV photons with field sizes 20 cm × 20 cm and 0.5 cm × 0.5 cm.

Results: Out of field size, the neutron ambient dose equivalents of the 0.5 cm × 0.5 cm field size are higher than those values of the 20 cm × 20 cm field size from 4% to 30%. The differences between the simulated value and the measured value of the neutron ambient dose equivalents at all points out of field size are smaller than 20%.

Conclusion: The neutron ambient dose equivalents, simulated with PHITS and JENDL-5.0, are satisfied with the measured neutron ambient dose equivalent.

Three-dimensional (3D) printing technology has revolutionized surgical practices, offering precise solutions for planning, education, and patient care. Surgeons now wield tangible, patient-specific 3D models derived from imaging data, allowing for meticulous presurgical planning. These models enhance surgical precision, reduce operative times, and minimize complications, ultimately improving patient outcomes. The technology also serves as a powerful educational tool, providing hands-on learning experiences for medical professionals and clearer communication with patients and their families. Despite its advantages, challenges such as model accuracy and material selection exist. Ongoing advancements, including bioactive materials and artificial intelligence integration, promise to further enhance 3D printing's impact. The future of 3D printing in surgery holds potential for regenerative medicine, increased global accessibility, and collaboration through telemedicine. Interdisciplinary collaboration between medical and engineering fields is crucial for responsible and innovative use of this technology.

Purpose: This study aims to investigate the radiation enhancement effects of ultrasound-stimulated microbubbles (USMB) with X-rays and nanoparticles on pancreatic cancer cells in vitro.

Methods: Sonazoid™ microbubbles were used for USMB treatment with a commercially available ultrasound unit. The characterization of the microbubbles before and after ultrasound exposure with different mechanical parameters was evaluated microscopically. Two pancreatic cancer cell lines, MIAPaCa-2 and PANC-1, were treated with different concentrations of microbubbles in combination with 150 kVp X-rays and hydrogen peroxide-modified titanium dioxide nanoparticles. Cell viability was evaluated using a water-soluble tetrazolium dye and a colony formation assay. In addition, intracellular reactive oxygen species (ROS) induced by the combined treatment were assessed.

Results: The number of burst microbubbles increased with ultrasound's higher mechanical index and the exposure time. A significant radiation enhancement effect with a significant increase in ROS levels was observed in MIAPaCa-2 cells treated with USMB and 6 Gy X-rays, whereas it was not significant in PANC-1 cells treated with the same. When a higher concentration of USMB was applied with X-rays, no radiation enhancement effects were observed in either cell line. Moreover, there was no radiation enhancement effect by USMB between cells treated with and without nanoparticles.

Conclusions: The results indicate that USMB treatment can additively enhance the therapeutic efficacy of radiation therapy on pancreatic cancer cells, while the synergistic enhancement effects are likely to be cell type and microbubble concentration dependent. In addition, USMB did not improve the efficacy of nanoparticle-induced radiosensitization in the current setting.

Background and purpose: Size-specific dose estimates (SSDE) have been introduced into computed tomography (CT) dosimetry to tailor patients' unique sizes to facilitate accurate CT radiation dose quantification and optimization. The purpose of this study was to develop and validate an automated algorithm for the determination of patient size (effective diameter) and SSDE.

Materials and methods: A MATLAB platform was used to develop software of algorithms based on image segmentation techniques to automate the calculation of patient size and SSDE. The algorithm was used to automatically estimate the individual size and SSDE of four CT dose index phantoms and 80 CT images of pediatric patients comprising head, thorax, and abdomen scans. For validation, the American Association of Physicists in Medicine (AAPM) manual methods were used to determine the patient's size and SSDE for the same subjects. The accuracy of the proposed algorithm in size and SSDE calculation was evaluated for agreement with the AAPM's estimations (manual) using Bland-Altman's agreement and Pearson's correlation coefficient. The normalized error, system bias, and limits of agreement (LOA) between methods were derived.

Results: The results demonstrated good agreement and accuracy between the automated and AAPM's patient size estimations with an error rate of 1.9% and 0.27% on the patient and phantoms study, respectively. A 1% percentage difference was found between the automated and manual (AAPM) SSDE estimates. A strong degree of correlation was seen with a narrow LOA between methods for clinical study (r > 0.9771) and phantom study (r > 0.9999).

Conclusion: The proposed automated algorithm provides an accurate estimation of patient size and SSDE with negligible error after validation.

Aims: Magnetic resonance imaging (MRI)-only radiotherapy has emerged as a solution to address registration errors that can lead to missed dose delivery. However, the presence of systemic geometric distortion (SGD) stemming from gradient nonlinearity (GNL) and inhomogeneity of the main magnetic field (B₀) necessitates consideration. This study aimed to quantitatively assess residual SGD in 1.5T MRI simulation using a three-dimensional (3D) geometric distortion phantom and evaluate its impact on dosimetric accuracy for retrospective prostate cancer patients.

Materials and methods: Ten retrospective cases of prostate cancer patients treated with volumetric modulated arc radiotherapy (VMAT) were randomly selected. A geometric distortion phantom was scanned on a 1.5T MRI simulation using a 3D T1 volumetric interpolated breath-hold examination sequence, varying bandwidth (BW), and two-phase-encoding directions. Distortion maps were generated and applied to the original computed tomography (oriCT) plan to create a distorted computed tomography plan (dCT), and a dice similarity coefficient (DSC) was observed. Dosimetric accuracy was evaluated by recalculating radiation dose for dCT plans using identical beam parameters as oriCT.

Results: The SGD increased with distance from the isocenter in all series. DSC exceeded 0.95 for all plans except the rectum. Regarding GNL's impact on dosimetric accuracy, most mean percentage errors for clinical target volume, planning target volume, and both femurs were under 2% in all plans, except for the bladder and rectum.

Conclusion: SGD pre-evaluation is crucial and should be incorporated into a quality assurance program to ensure effective MRI-simulation performance before MRI-only treatment planning for prostate cancer.

Purpose: When exact information regarding the treatment head and initial electron beam is available, the Monte Carlo (MC) approach can properly simulate any linear accelerator. However, manufacturers seldom offer information such as the incident electron beam's energy, radial intensity (spot size), or angular spread. This research aims to forecast these features and verify an MC-simulated linear accelerator model using measurements.

Materials and methods: The BEAMnrc code simulated a 6 MV photon beam from a Radixact™ Tomotherapy Linac. Percentage depth dose and beam profile calculations were conducted using DOSYXZnrc by various electron energies and spot sizes and compared to measurements using a Gamma index with two distinct criterion sets. Furthermore, the fine-tuned electron energy and spot size profiles were created to minimize any disparities using distinct angle spreads. Finally, the output factors (OFs) for various field sizes were compared.

Results: The MC model's fine-tuned electron energy was determined to be 5.8 MeV, with 88.6% of the calculation points passing the 1%/1 mm γ test. A circular radial intensity of 1.4 mm best represented the 6 MV photon beam regarding spot size. Furthermore, a mean angular spread of 0.05 reduced the disparity in cross-field profile between computation and measurement. The most considerable disparities between the MC model OFs and observations were 1.5%.

Conclusion: Using the BEAMnrc code, a reliable MC model of the Radixact™ Tomotherapy Linac can be created, as shown in this paper. This model can be used to compute dose distributions with confidence.

Purpose: This study aims to evaluate the performance of dual-energy window (DEW) and triple-energy window (TEW) scatter correction methods in cardiac SPECT imaging with technetium-99m (Tc-99m) and thallium-201 (Tl-201) radioisotopes.

Materials and methods: The SIMIND Monte Carlo program was used to simulate the imaging system and produce the required projections. Two phantoms, including the simple cardiac phantom and the NCAT phantom, were used to evaluate the scatter correction methods. The simulations were repeated 5 times for each phantom and finally, the mean values obtained from these 5 tests were used in the analysis of the results.

Results: The obtained results from this study show that in the case of both investigated phantoms, the use of correction methods leads to improve the contrast of the images obtained from Tc-99m and Tl-201 radioisotopes. In the case of the simple cardiac phantom, the use of DEW and TEW correction methods leads to a relative increase in image contrast of about 23.88% and 12.23% for ^99mTc radioisotope and about 29.19% and 20.98% for ²⁰¹Tl radioisotope, respectively. This relative increase in the case of the NCAT phantom is about 22.48% and 19.43% for ^99mTc radioisotope and about 27.74% and 24.74% for ²⁰¹Tl radioisotope, respectively.

Conclusion: According to the obtained results, despite the higher contrast of the noncorrected images of ^99mTc radioisotope, the relative increase in contrast of the corrected images of ²⁰¹Tl radioisotope is more than that of ^99mTc radioisotope. Furthermore, for both radioisotopes, the relative increase related to the DEW method is higher than the TEW method.

Objective: The aim of the study is to compare the accuracy of dose calculation for different dose calculation algorithms with different prescription points (air, tissue, air-tissue interface in carcinoma lung patients and bone, tissue, and bone-tissue interface in carcinoma buccal Mucosa tumors).

Materials and methods: Forty-one patients with carcinoma lung and buccal mucosa were retrospectively selected for this study. A three-dimensional conformal radiotherapy reference plan was created using the prescription point in the tissue with Monte Carlo (MC) algorithms for both the groups of patients. The reference plan was modified by changing the prescription point and algorithms in the tissue, air, air-tissue interface for lung patients and tissue, bone, and bone-tissue interface for buccal mucosa patients. The dose received by the target volume and other organs at risk (OAR) structures was compared. To find out the statistical difference between different prescription points and algorithms, the statistical tests were performed with repeated measures ANOVA.

Results: The target volume receiving 95% dose coverage in lung patients decreased to -3.08%, -5.75%, and -1.87% in the dose prescription point at the air-tissue interface with the dose calculation algorithms like MC, collapsed cone (CC), and pencil beam (PB), respectively, compared to that of the MC tissue. Spinal cord dose was increased in the CC and PB algorithms in all prescription points in patients with lung and buccal mucosa. OAR dose calculated by PB in all prescription points showed a significant deviation compared to MC tissue prescription point.

Conclusion: This study will help demonstrate the accuracy of dose calculation for the different dose prescription points with the different treatment algorithms in radiotherapy treatment planning.

Aims: This study aimed to evaluate the geometrical accuracy of atlas-based auto-segmentation (ABAS), deformable image registration (DIR), and deep learning auto-segmentation (DLAS) in adaptive radiotherapy (ART) for head-and-neck cancer (HNC).

Subjects and methods: Seventeen patients who underwent replanning for ART were retrospectively studied, and delineated contours on their replanning computed tomography (CT2) images were delineated. For DIR, the planning CT image (CT1) of the evaluated patients was utilized. In contrast, ABAS was performed using an atlas dataset comprising 30 patients who were not part of the evaluated group. DLAS was trained with 143 patients from different patients from the evaluated patients. The ABAS model was improved, and a modified ABAS (mABAS) was created by adding the evaluated patients' own CT1 to the atlas datasets of ABAS (number of patients of the atlas dataset, 31). The geometrical accuracy of DIR, DLAS, ABAS, and mABAS was evaluated.

Results: The Dice similarity coefficient in DIR was the highest, at >0.8 at all organs at risk. The mABAS was delineated slightly more accurately than the standard ABAS. There was no significant difference between ABAS and DLAS in delineation accuracy. DIR had the lowest Hausdorff distance (HD) value (within 10 mm). The HD values in ABAS, mABAS, and DLAS were within 16 mm.

Conclusions: DIR delineation is the most geometrically accurate ART for HNC.

Aim: The purpose of this study is to improve the precision of radiation treatment and sparing of organ-at-risk (OAR) in patients with thoracic esophageal cancer (EC) affecting the heart, lung, and spinal cord. To improve and personalize cancer treatment plans, it assesses the dosimetric benefits of coplanar RapidArc (RA_c), hybrid arc (RA_Hyb), and noncoplanar RapidArc (RA_nc).

Materials and methods: Fourteen patients with EC were chosen for our investigation from our hospital's database. RapidArc (RA) plan patients had already received treatment. Retrospectively, additional RA_nc and RA_Hyb plans were made with a prescription dose of 50.4 Gy in 28 fractions for the planning target volume (PTV). A prescription dose of 95% of PTV was used, so that three different treatment planning procedures could be compared. The cumulative dose-volume histogram was used to analyze the plan quality indices homogeneity index (HI), conformity index (CI), conformation number (CN) as well as the OARs doses to the lung, heart, and spinal cord.

Results: In comparison to RA_c and RA_nc techniques, the study indicated that RA_Hyb plans significantly increased D95%, CI and HI; Dmax and CN did not differ substantially. In addition, compared to RA_c (lung: 16.15 ± 0.03 Gy and heart: 23.91 ± 4.67 Gy) and RA_nc (lung: 15.24 ± 0.03 Gy and heart 23.82 ± 5.10 Gy) plans, RA_Hyb resulted in significantly lower mean lung doses (15.10 ± 0.03 Gy) and heart doses (21.33 ± 6.99 Gy). Moreover, the RA_Hyb strategy showed a statistically significant (P < 0.05) lower average MU (452.7) than both the RA_c (517.5) and RA_nc (566.2) plans.

Conclusion: The D95%, conformity, and homogeneity indices were better for hybrid arc plans compared to RA_c and RA_nc plans. They also successfully managed to reduce the lung and heart doses as well as the mean MU per fraction.