Objective To compare the performance of two different deep learning models,VTcGAN and Pix2pix,in generating synthetic computed tomography(sCT)from magnetic resonance imaging(MRI)of nasopharyngeal carcinoma(NPC),and to evaluate their accuracies in treatment planning dose calculations.Methods MRI and CT images as well as treatment planning data of 115 NPC patients were retrospectively selected,and paired dataset was obtained through rigid image registration,with 105 cases as the training set,and the remaining 10 cases as the test set.Two kinds of models,namely Pix2pix model based on conventional convolutional neural network and the improved VTcGAN model based on Transformer network,were constructed with the consistent structure except for the bottleneck network in the generator.The generated sCT images(sCTPix2pix and sCTVTcGAN)were assessed in terms of image quality,intensity value and dosimetric differences.Results For the cases in test set,the mean error,mean absolute error,peak signal-to-noise ratio,and structural similarity index between the ground truth CT images and the sCTPix2pix were(-0.86±12.42)HU,(40.77±3.06)HU,(33.45±0.62)dB,and 0.928±0.013,respectively;and those between the ground truth CT images and the sCTVTcGAN were(-1.10±8.56)HU,(37.40±2.08)HU,(34.33±0.45)dB,and 0.936±0.009,respectively.For the criterion of 1 mm/1%,the averaged gamma passing rates of sCTPix2pix and sCTVTcGAN were(96.62±1.08)%and(96.88±0.99)%at a dose threshold of 10%,(94.31±1.03)%and(94.72±0.91)%at a dose threshold of 50%,(84.62±1.74)%and(86.06±1.41)%at a dose threshold of 80%,respectively.Conclusion The proposed VTcGAN model is superior to the traditional Pix2pix model in terms of accuracy in generating sCT from MRI of NPC,and it can fulfill the requirements for dose calculation in the MRI-Only workflow.

Objective To compare the performance of two different deep learning models,VTcGAN and Pix2pix,in generating synthetic computed tomography(sCT)from magnetic resonance imaging(MRI)of nasopharyngeal carcinoma(NPC),and to evaluate their accuracies in treatment planning dose calculations.Methods MRI and CT images as well as treatment planning data of 115 NPC patients were retrospectively selected,and paired dataset was obtained through rigid image registration,with 105 cases as the training set,and the remaining 10 cases as the test set.Two kinds of models,namely Pix2pix model based on conventional convolutional neural network and the improved VTcGAN model based on Transformer network,were constructed with the consistent structure except for the bottleneck network in the generator.The generated sCT images(sCTPix2pix and sCTVTcGAN)were assessed in terms of image quality,intensity value and dosimetric differences.Results For the cases in test set,the mean error,mean absolute error,peak signal-to-noise ratio,and structural similarity index between the ground truth CT images and the sCTPix2pix were(-0.86±12.42)HU,(40.77±3.06)HU,(33.45±0.62)dB,and 0.928±0.013,respectively;and those between the ground truth CT images and the sCTVTcGAN were(-1.10±8.56)HU,(37.40±2.08)HU,(34.33±0.45)dB,and 0.936±0.009,respectively.For the criterion of 1 mm/1%,the averaged gamma passing rates of sCTPix2pix and sCTVTcGAN were(96.62±1.08)%and(96.88±0.99)%at a dose threshold of 10%,(94.31±1.03)%and(94.72±0.91)%at a dose threshold of 50%,(84.62±1.74)%and(86.06±1.41)%at a dose threshold of 80%,respectively.Conclusion The proposed VTcGAN model is superior to the traditional Pix2pix model in terms of accuracy in generating sCT from MRI of NPC,and it can fulfill the requirements for dose calculation in the MRI-Only workflow.

Objective:To explore the effect of case study combined with scenario simulation in teaching clinical internship of radiation oncology.Methods:This study selected 144 undergraduate students majoring in clinical medicine who interned at the Department of Radiotherapy at Sun Yat-sen University Cancer Center from November 2022 to May 2023 as the research subjects. They were randomly divided into a control group and an observation group. The control group received traditional teaching, while the observation group received case study combined with scenario simulation teaching, with 72 students in each group. The two groups of trainees were evaluated for theoretical and skill assessment scores, core competencies, and teaching satisfaction. The t-test and chi-square test were performed using SPSS 22.0. Results:The theoretical and skill scores of the trainees in the observation group [(88.27±3.40) and (92.69±3.65)] were higher than those in the control group [(83.01±10.38) and (87.20±3.74)], and the differences were statistically significant. Compared with the control group, the observation group showed higher core competency scores in eight dimensions, including learning initiative and enthusiasm, knowledge comprehension ability, critical thinking ability, clinical specialty practice ability, analytical and problem-solving ability, doctor-patient communication, professional ethics, and teamwork ability, and the differences were statistically significant ( P<0.05). The satisfaction scores of the observation group trainees of teaching plan, teaching content, teaching methods, teaching results, and teaching ability were higher than those of the control group, and the differences were statistically significant ( P<0.05). Conclusions:The application of case study combined with scenario simulation teaching clinical internship of radiation oncology can help improve the theoretical and skill scores of medical students, as well as their core competencies and teaching satisfaction. This is a teaching method worthy of application and promotion.

Objective:To explore the effect of case study combined with scenario simulation in teaching clinical internship of radiation oncology.Methods:This study selected 144 undergraduate students majoring in clinical medicine who interned at the Department of Radiotherapy at Sun Yat-sen University Cancer Center from November 2022 to May 2023 as the research subjects. They were randomly divided into a control group and an observation group. The control group received traditional teaching, while the observation group received case study combined with scenario simulation teaching, with 72 students in each group. The two groups of trainees were evaluated for theoretical and skill assessment scores, core competencies, and teaching satisfaction. The t-test and chi-square test were performed using SPSS 22.0. Results:The theoretical and skill scores of the trainees in the observation group [(88.27±3.40) and (92.69±3.65)] were higher than those in the control group [(83.01±10.38) and (87.20±3.74)], and the differences were statistically significant. Compared with the control group, the observation group showed higher core competency scores in eight dimensions, including learning initiative and enthusiasm, knowledge comprehension ability, critical thinking ability, clinical specialty practice ability, analytical and problem-solving ability, doctor-patient communication, professional ethics, and teamwork ability, and the differences were statistically significant ( P<0.05). The satisfaction scores of the observation group trainees of teaching plan, teaching content, teaching methods, teaching results, and teaching ability were higher than those of the control group, and the differences were statistically significant ( P<0.05). Conclusions:The application of case study combined with scenario simulation teaching clinical internship of radiation oncology can help improve the theoretical and skill scores of medical students, as well as their core competencies and teaching satisfaction. This is a teaching method worthy of application and promotion.

Objective:To compare the difference between breast bracket combined with polyurethane foam and single polyurethane foam in the accuracy of immobilization, providing a better immobilization for breast cancer radiotherapy.Methods:Fifty breast cancer patients who received radiotherapy in Sun Yat-sen University Cancer Center from March 2021 to July 2021 were selected. Among them, 25 patients were immobilized with polyurethane foam (foam group), and the other 25 patients were immobilized with polyurethane foam combined with breast bracket (combination group). All patients were scanned by CBCT once a week to obtain setup errors in the SI, LR and AP directions for t-test. The formula M PTV=2.5 Σ+0.7 σ was used to calculate the margin of the planning target volume(M PTV). Results:The setup errors in the foam group were SI (2.0±3.26) mm, LR (0.88±2.76) mm, AP (1.22±3.55) mm, Rtn -0.24°±0.85°, Pitch 0.16°±1.11°, Roll -0.32°±1.05°, and the M PTV were 6.75 mm, 8.46 mm and 8.73 mm, respectively. The setup errors in the combination group were SI (1.0±3.01) mm, LR (0.62±2.74) mm, AP (1.82±3.21) mm, Rtn 0.64°±0.59°, Pitch 0.71°±1.22°, Roll 0.29°±0.73°, and the M PTV were 6.35 mm, 7.47 mm, and 7.61 mm, respectively. After comparing the setup errors in the three-dimensional directions between two groups, the t value of LR, SI, AP and Rtn, Pitch, Roll was -4.304, -2.681, 1.384, and -9.457, -3.683, -5.323, respectively. And the differences in the LR, SI, Rtn, Pitch and Roll directions were statistically significant (all P<0.05). Conclusions:The immobilization effect of polyurethane foam combined with breast bracket is better and the M PTV is also smaller than those of polyurethane foam alone. Therefore, it is recommended to use polyurethane foam combined with breast bracket for immobilization in breast cancer radiotherapy.

Objective:To investigate the feasibilityof the adaptive radiotherapy using high-field MR-Linac systems for head neck cancers and perform the evaluation of target coverage and dose criteria.Methods:This study investigated 128 treatment plans of six patients who were treated on 1.5T MR-Linacsystems in Sun Yat-sen University Cancer Center in 2019, compared the differences in target coverage and dose criteria between the dose accumulation in the adaptive radiotherapy using MR-Linac systems and the reference plans, and evaluated the target coverage and dose criteria of each fraction of adaptive plan based on daily MRI anatomy.Results:There was no significant change in the target coverage and dose criteria for each treatment fraction(<1%). However, the change of lens dose was significant (maximum 98%). In addition, the result showed that there was no significant difference in target coverage and dose criteria between the dose accumulation in adaptive radiotherapy using MR-Linac systems and reference plans.In contrast, the average dose to lens was increased by 31.7%.Conclusions:It is feasible to perform adaptive radiotherapy using 1.5T MR-Linacsystems for head neck cancers according tothe evaluation of target coverage and dose criteria. Additionally, since the actual dose tolens was quite different from the reference plan, the lens exposure should be considered in clinical practice.

Objective:To investigate the clinical feasibility of the Unity radiotherapy system guided by magnetic resonance imaging.Methods:Twenty-four patients were enrolled and received a total of 384 fractions of treatment at Unity system. According to the treatment site, all patients were divided into head-neck, abdomen-thorax, pelvic, spine and limb groups. The patients were set-up without external laser. And then, the time required at different stages in online treatment process and the registration error of each fraction were separately calculated. The geometric deformations of MR images were weekly measured by using MR geometric deformation phantom. At last, the Arccheck was used to perform the dose verification of reference plan, online plan and offline plan.Results:The mean duration of radiotherapy in the five groups were 29.1, 27.6, 26.6, 25.6 and 32.0 min, respectively. The set-up errors in the left-right, superior-inferior and anterior-posterior direction in the five groups were: head-neck group (0.08±0.06 cm, 0.16±0.13 cm, 0.08±0.05 cm), abdomen-thorax group (0.23±0.18 cm, 0.50±0.47 cm, 0.12±0.1 cm), pelvic group (0.25±0.19 cm, 0.32±0.25 cm, 0.11±0.09 cm), spine group (0.46±0.38 cm, 0.26±0.26 cm, 0.13±0.07 cm) and limb group (0.33±0.30 cm, 0.34±0.23 cm, 0.08±0.06 cm), respectively. In the central region, the geometric deformation of MR was less than 0.3 mm, and that of the sphere with a diameter of 500 mm was less than 2.1 mm. The meanγ pass rate of the reference plan, online plan and offline plan were 97.92%, 97.84% and 94.58%, respectively.Conclusions:MR-guided radiotherapy has great potential for clinical application, whereas the process of Unity system is relatively complex. The synergy of different departments has a great impact on the treatment, which needs further optimization.

Objective:To characterize the imaging distortion of the 1.5T magnetic resonance imaging-guided linear accelerator (MR-Linac) and to analyze the influence of MR-Linac and peripheral devices on the geometric distortion.Methods:Specialized MRI imaging distortion phantom and analysis software were applied. The baseline of imaging distortion within diameter spherical volume (DSV) around the center of the magnet was established. The influence of the beam generation system, mechanical system and peripheral devices on the imaging distortion was analyzed. The long-term stability of imaging distortion was tested on the MR-Linac.Results:Imaging distortion of the MR-Linac was increased with the increasing distance to the center of the magnet. Within DSV 400 mm, few test points surpassed 1 mm imaging distortion in 3D directions. However, imaging distortion surpassed 2 mm in part of region within DSV 400-500 mm, with the largest distortion over 7 mm. Imaging distortion of the MR-Linac remained unchanged within 7 months after installation. And the influence of the MR-Linac and peripheral devices on the imaging distortion was only observed in the overall largest distortion within DSV 400-500 mm.Conclusions:Cautions should be taken during the application of high-field MR-Linac in patients whose tumor location is over 20 cm from the ISO center. Imaging distortion of the MR-Linac remains stable within 7 months after installation. The influence of the MR-Linac and peripheral devices on the imaging distortion is trivial, which can be neglected in clinical practice.

Objective An improved water-fat separation method based on region-growing was proposed for use in regions with low signal-noise ratio (SNR).Methods Region-growing method was applied to 4 sub-images acquired by a downsampling operation on the acquired phasor maps.The spatial smoothing constraint was exploited to calculate 4 error phasor maps to construct the final smooth error phasor map,which was used in two-point Dixon technique for water-fat separation.Results The simulation experiment showed that the proposed method produced smaller errors,and for dinical images of the knees,abdomen and lower limbs,the proposed method achieved accurate water-fat separations.Conclusion The proposed method is more robust and reliable than the original global region-growing algorithm,and serves as a promising water-fat separation method for clinical applications.

Objective An improved water-fat separation method based on region-growing was proposed for use in regions with low signal-noise ratio (SNR).Methods Region-growing method was applied to 4 sub-images acquired by a downsampling operation on the acquired phasor maps.The spatial smoothing constraint was exploited to calculate 4 error phasor maps to construct the final smooth error phasor map,which was used in two-point Dixon technique for water-fat separation.Results The simulation experiment showed that the proposed method produced smaller errors,and for dinical images of the knees,abdomen and lower limbs,the proposed method achieved accurate water-fat separations.Conclusion The proposed method is more robust and reliable than the original global region-growing algorithm,and serves as a promising water-fat separation method for clinical applications.