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Objective:To develop a multi-scale fusion and attention mechanism based image automatic segmentation method of organs at risk (OAR) from head and neck carcinoma radiotherapy.Methods:We proposed a new OAR segmentation method for medical images of heads and necks based on the U-Net convolution neural network. Spatial and channel squeeze excitation (csSE) attention block were combined with the U-Net, aiming to enhance the feature expression ability. We also proposed a multi-scale block in the U-Net encoding stage to supplement characteristic information. Dice similarity coefficient (DSC) and 95% Hausdorff distance (HD) were used as evaluation criteria for deep learning performance.Results:The segmentation of 22 OAR in the head and neck was performed according to the medical image computing computer assisted intervention (MICCAI) StructSeg2019 dataset. The proposed method improved the average segmentation accuracy by 3%-6% compared with existing methods. The average DSC in the segmentation of 22 OAR in the head and neck was 78.90% and the average 95%HD was 6.23 mm.Conclusion:Automatic segmentation of OAR from the head and neck CT using multi-scale fusion and attention mechanism achieves high segmentation accuracy, which is promising for enhancing the accuracy and efficiency of radiotherapy in clinical practice.
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Ischemic stroke is a common disease of the nervous system, which is characterized by high incidence, recurrence, disability and mortality rate. The pathological mechanism of ischemic brain injury is complex. Synaptic plasticity injury is considered to be the earliest pathological change after cerebral ischemia, and regulating synaptic plasticity is one of the important mechanisms to promote the recovery of neurological function after stroke. This article reviews the advances in synaptic plasticity after ischemic brain injury, which provides theoretical basis for the development of neuroprotective drugs in the future.
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Objective:To investigate the correlation between residual cholesterol (RC) and carotid intima-media thickness (cIMT) in non-diabetic population.Methods:Non-diabetes population received health examination in Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School from January 1, 2018 to December 31, 2021 were retrospectively included. According to the carotid ultrasound results, they were divided into cIMT thickening group (≥1 mm) and non-thickening group (<1 mm). The RC level was calculated according to total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C). Multivariate logistic regression analysis was used to determine the correlation between RC and cIMT. Results:A total of 1 803 non-diabetes subjects, aged 58.3±15.6 years, including 1 100 males (61.0%), were enrolled. There were 916 patients (50.8%) in the cIMT thickening group and 887 (49.2%) in the non-cIMT thickening group. Compared with the non-cIMT thickening group, cIMT thickening group had significantly higher proportion of male, hypertension, hyperlipidemia, atrial fibrillation, past stroke history, smoking and alcohol consumption, as well as significantly higher age, blood glucose, triglyceride, RC, TC and LDL-C, and significantly lower HDL-C (all P<0.01). Multivariate logistic regression analysis showed that RC was independently associated with cIMT thickening ( Ptrend<0.001). Conclusion:RC is associated with cIMT thickening in non-diabetes population.
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Objective:To investigate the predictors of intracranial hemorrhage in patients with cerebral venous sinus thrombosis (CVST).Methods:Patients with CVST treated in Drum Tower Hospital Affiliated to Medical School of Nanjing University from January 2008 to March 2021 were retrospectively enrolled. The risk factors, clinical manifestations, imaging examination and 90 d follow-up data were collected. The complicated intracranial hemorrhage group and non-intracranial hemorrhage group were compared. Multivariate logistic regression analysis was used to determine the independent predictors of intracranial hemorrhage in patients with CVST. Results:A total of 104 patients with CVST were enrolled, including 42 males and 62 females. Their age was 35.24 ± 10.92 years old (range 22-68 years). Thirty-eight patients (36.84%) were complicated with intracranial hemorrhage, including 34 hemorrhagic cerebral infarction and 4 complicated subarachnoid hemorrhage. Univariate analysis showed that compared with the non-intracerebral hemorrhage group, the intracranial hemorrhage group was more common in puerperal/pregnant patients (60.52% vs. 48.48%; P=0.012), with more acute onset (57.89% vs. 48.48%; P=0.004), focal neurological signs (47.37% vs. 19.70%; P=0.003) and seizure (39.47% vs. 18.18%; P=0.017), and the site of thrombosis was more common in the superior sagittal sinus (57.89% vs. 36.36%; P=0.033). Multivariate logistic regression analysis showed that puerperium/pregnancy (odds ratio 2.857, 95% confidence interval 1.095-7.453; P=0.031) and superior sagittal sinus thrombosis (odds ratio 2.847, 95% confidence interval 1.110-7.302; P=0.027) were the independent predictors of intracranial hemorrhage in patients with CVST. The analysis at 90 d after onset showed that there was no significant difference in the good outcome rate between the intracranial hemorrhage group and the non-intracranial hemorrhage group (86.84% vs. 89.39%; P=0.695). Conclusions:Puerperium/pregnancy and superior sagittalsinus thrombosis are the independent risk factors for intracranial hemorrhage in patients with CVST. However, complicated with intracranial hemorrhage is not associated with 90-day clinical outcomes.
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Objective:To design a knowledge-based cervical cancer planning model and apply it to cases of endometrial cancer and rectal cancer in order to explore the generalization of the model.Methods:A total of 179 cases of pelvic regions with different prescribed doses of dual-arc volumetric modulated arc therapy clinical plans were collected, of which 99 cases of cervical cancer clinical plans with a prescribed dose of 50.4 Gy were used as the training set to establish the RapidPlan model, and the remaining clinical plans were divided into 4 validation groups with 20 cases in each group. The clinical plans for cervical cancer and endometrial cancer with a prescription dose of 50.4 Gy were named groups A and B, while the clinical plan for endometrial cancer and rectal cancer with a prescription dose of 45 Gy were named groups C and D. The model was used to redesign the clinical plans in the 4 groups and the automatic plans were obtained. The planning target volume (PTV) and organ at risk (OAR) dosimetry parameters were compared between automatic plans and clinical plans.Results:The conformity index (CI) of the automatic plans in the A, B, C, and D groups were equivalent to that of the clinical plans ( P>0.05). The homogeneity index (HI) and D2% of the automatic plans in groups A, B, and C were all lower than those in clinical plans(HI, Z=-3.248, -3.360, -2.329, P<0.05; D2%, Z=-2.987, -3.397, -2.442, P<0.05). The HI and D2% of the automatic plans in group D were similar those in the clinical plans ( P>0.05). While ensuring the PTV coverage, the average value of OAR dosimetry parameters in all automatic plans groups were lower than that of the clinical plans. Conclusions:The RapidPlan model established by the cervical cancer clinical plans can complete the automatic plan design for endometrial cancer and rectal cancer under different prescription doses, which preliminarily proves the possibility of the generalization of the RapidPlan model.
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The design of a conventional radiotherapy plan is a time-consuming and labor-intensive process, and relevant parameters need to be continuously adjusted in the plan optimization to identify the optimal plan. In addition, experience differences between planners, time invested in plan design, and institutional standards all affect the quality of the plan, which in turn influences clinical outcomes and patient prognosis. In recent years, automatic planning has developed rapidly, which can improve the efficiency of planning design while ensuring the quality of the plan. At present, there are several methods dedicated to the automation of radiotherapy planning design, such as the Rapid Plan and Auto-Planning functions in Eclipse and Pinnacle commercial treatment planning systems, and there are also studies applying artificial intelligence technology in dose prediction to achieve automatic planning. In this article, the research progress on automatic radiotherapy planning was reviewed, and the realization principles, clinical efficacy and existing problems of various automatic planning methods were illustrated.
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Objective:To investigate the effect of Halo-Vest on the dose distribution of different radiotherapy techniques for primary cervical spine malignant tumors.Methods:Ten patients with primary cervical spine malignancies who underwent radiotherapy after Halo-Vest surgery were retrospectively studied. The IMRT and VMAT plans were designed on the contoured CT images including Halo-Vest delineations using Monaco planning system. The IMRT and VMAT plans with the same field parameters were duplicated to the CT images without the Halo-Vest delineations, and the dose distribution was recalculated. The dose distribution of the target, organs at risk and normal tissues was analyzed and compared for the plans with and without the Halo-Vest delineation.Results:For most dosimetric parameters of VMAT plans, the mean deviations induced by the Halo-Vest were less than 1%, except for PGTV 107%. Without Halo-Vest delineation, the mean maximum dose of spinal cord and spinal cord-PRV increased by 0.38 Gy and 0.42 Gy ( Z=-2.803, -2.803, P<0.05), respectively. The mean Dmean of spinal cord and spinal cord PRV increased by 0.35 Gy and 0.37 Gy, respectively ( Z=-2.703, -2.701, P<0.05). The maximum deviation observed in the mean V5, V30, and Dmean of mucosa, thyroid, parotid gland, mandible, mandibular joint, and normal tissues was 0.74%. For IMRT plans, larger dosimetric deviations than VMAT plans were observed in PTV and PGTV, most of which were more than 1.0% and the maximum deviation was 4.55%. The absence of Halo-Vest delineation increased the mean maximum dose of spinal cord and spinal cord-PRV by 0.48 Gy and 0.59 Gy ( P>0.05), respectively. The mean Dmean of spinal cord and spinal cord PRV increased by 0.57 Gy and 0.59 Gy, respectively ( Z=-2.293, -2.293, P<0.05). The maximum deviation of other organs at risk was 1.98%. Conclusions:There are no clinically significant dose differences for VMAT planning with or without Halo-Vest delineation on the CT images. But the dosimetric impact of absent or partial Halo-Vest delineation on IMRT planning is relatively large and should be considered.
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Objective:To develope a deep-learning-based auto-segmentation model to segment organs at risk (OARs) in head and neck (H&N) region and compare with atlas-based auto-segmentation software (Smart segmentation).Methods:The auto-segmentation model consisted of classification model and segmentation model based on deep learning neural network. The classification model was utilized to classify CT slices into six categories in the cranio-caudal direction, and then the CT slices corresponding to the categories for different OARs were pushed to the segmentation model respectively. The CT image data of 150 patients were used for auto-segmentation model training and building atlas library in Smart segmentation software. Another 20 patients were used as testing dataset for both auto-segmentation model and Smart segmentation software. Dice similarity coefficient (DSC) and Hausdorff distance (HD) were used to evaluate the accuracy of two method, and auto-segmentation time cost was recorded. Paired Student′s t-test or non-parametric Wilcoxon signed-rank test was performed depending on result of normality test. Results:The DSC and HD of auto-segmentation model for brainstem, left eye, right eye, left optic nerve, right optic nerve, left temporal lobe, right temporal lobe, mandible, left parotid and right parotid were 0.88 and 4.41 mm, 0.89 and 2.00 mm, 0.89 and 2.12 mm, 0.70 and 3.00 mm, 0.80 and 2.24 mm, 0.81 and 7.98 mm, 0.84 and 8.82 mm, 0.89 and 5.57 mm, 0.70 and 11.92 mm, 0.77 and 11.27 mm respectively. The results of auto-segmentation model were better than those of Smart segmentation ( t=3.115-7.915, Z=-1.352 to -3.921, P<0.05) except left and right parotids. In addition, the speed of auto-segmentation model was 51.28% faster than that of Smart segmentation. Conclusions:In this study, the deep-learning-based auto-segmentation model demonstrated superior performance in accuracy and efficiency on segmenting OARs in H&N CT images, which was better than Smart segmentation software.
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Objective@#To analyze the patient-specific dosimetric verification result of stereotactic body radiotherapy (SBRT) plans, and to investigate the sensitivity of the result to three factors: interpolation of measured data, size of dose calculation grid and assessment threshold.@*Methods@#The dosimetric verification results of SBRT plans of 50 patients were retrospectively analyzed to evaluate the impact of the following factors. The linear interpolation (1.00 mm) and non-interpolation (7.62 mm) were applied to measured data respectively. Three dose calculation grid sizes of Eclipse planning system, i. e., 1.0 mm, 2.5 mm and 4.0 mm were compared respectively. The threshold of dose assessment was selected as 10%, 20% and 30%, respectively. Three criteria of γ analysis were selected: 2%/2 mm, 3%/2 mm and 3%/3 mm.@*Results@#Under criteria of 2%/2 mm, 3%/2 mm and 3%/3 mm, the average γ passing rates were (86.3±7.3)% and (93.7±5.6)%, (94.1±4.4)% and(97.7±3.9)%, (97.7 ±2.2)% and (99.1±1.7)%, respectively, with and without linear interpolation. Relative to the 1.0 mm reference grid, the grids of 2.5 mm and 4.0 mm significantly decreased γ passing rates by 3.8%, 1.9%, 0.8% (t=8.41, 9.06, 5.30, P<0.05) and by 6.5%, 6.0%, 3.5% (t=-13.76, -13.15, -9.80, P<0.05) under criteria of 2%/2 mm, 3%/2 mm and 3%/3 mm, respectively. Relative to the 10% reference threshold, the shresholds of 20% and 30% significantly decreased γ passing rates by 2.4%, 1.0%, 0.6%(t=-8.60, -5.86, -4.68, P<0.05) and by 4.0%, 1.7%, 0.9% (t=-9.45, -6.66, -5.06, P<0.05) under criteria of 2%/2 mm, 3%/2 mm and 3%/3 mm, respectively.@*Conclusions@#Interpolation, dose calculation grid size and dose assessment threshold are influential factors of dose verification result, and need to be considered during dosimetric verification of stereotactic radiotherapy patients.
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Objective To analyze the patient-specific dosimetric verification result of stereotactic body radiotherapy ( SBRT ) plans, and to investigate the sensitivity of the result to three factors:interpolation of measured data, size of dose calculation grid and assessment threshold. Methods The dosimetric verification results of SBRT plans of 50 patients were retrospectively analyzed to evaluate the impact of the following factors. The linear interpolation ( 1. 00 mm) and non-interpolation ( 7. 62 mm) were applied to measured data respectively. Three dose calculation grid sizes of Eclipse planning system, i.e., 1. 0 mm, 2. 5 mm and 4. 0 mm were compared respectively. The threshold of dose assessment was selected as 10％, 20％ and 30％, respectively. Three criteria of γ analysis were selected: 2％/2 mm, 3％/2 mm and 3％/3 mm. Results Under criteria of 2％/2 mm, 3％/2 mm and 3％/3 mm, the average γ passing rates were (86. 3±7. 3)％ and (93. 7±5. 6)％, (94. 1±4. 4)％ and(97. 7±3. 9)％, (97. 7 ±2. 2)％ and (99. 1±1. 7)％, respectively, with and without linear interpolation. Relative to the 1. 0 mm reference grid, the grids of 2. 5 mm and 4. 0 mm significantly decreased γ passing rates by 3. 8％, 1. 9％, 0. 8％ ( t=8. 41, 9. 06, 5. 30, P<0. 05) and by 6. 5％, 6. 0％, 3. 5％ ( t=-13. 76, -13. 15, -9. 80, P<0. 05) under criteria of 2％/2 mm, 3％/2 mm and 3％/3 mm, respectively. Relative to the 10％ reference threshold, the shresholds of 20％ and 30％ significantly decreasedγpassing rates by 2. 4％, 1. 0％, 0. 6％(t=-8. 60, -5. 86, -4. 68, P<0. 05) and by 4. 0％, 1. 7％, 0. 9％ (t=-9. 45, -6. 66, -5. 06, P<0. 05) under criteria of 2％/2 mm, 3％/2 mm and 3％/3 mm, respectively. Conclusions Interpolation, dose calculation grid size and dose assessment threshold are influential factors of dose verification result, and need to be considered during dosimetric verification of stereotactic radiotherapy patients.
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In recent years,the application of machine learning in the field of radiotherapy has been gradually increased along with the development of big data and artificial intelligence technology.Through the training of previous plans,machine learning can predict the results of plan quality and dose verification.It can also predict the multi-leaf collimator (MLC) positioning error and linear accelerator performance.In addition,machine learning can be applied in the quality assurance of intensity-modulated radiotherapy to improve the quality and efficiency of treatment plan and implementation,increase the benefits to the patients and reduce the risk.However,there are many problems,such as difficulty in the selection,extraction and calculation of characteristic value,requirement for large training sample size and insufficient prediction accuracy,which impede its clinical translation and application.In this article,research progress on the application of machine learning in the quality assurance of IMRT was reviewed.
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Objective To evaluate the accuracy and reliability of the CyberKnife VSI system for stereotactic radiotherapy.Methods First,the mechanical accuracy of the robotic manipulator system,the repeatability of the Iris variable aperture collimator system,the couch position accuracy of the patient positioning system,the tacking precision of the target locating system and the dosimetric beam characteristics of the linac system for each subsystem of CyberKnife VSI system were tested.Finally,the total beam delivery precision of the CyberKnife VSI system was evaluated.Results The mean positioning deviations of the mechanical arm movement of the robotic manipulator system were less than 0.1 mm,and the maximum positioning deviation of single note was ≤ 0.29 mm.The repeatability of the aperture sizes for the Iris variable aperture collimator system was ≤ 0.28 mm.The couch position accuracy of the patient positioning system was＜0.2 mm and the tracking precision of the target locating system was less than 0.5°.The linac beam-laser beam axes coincidence between the Iris and fixed collimators was better than 0.4 mm.The 6-MV beam parameters,such as beam quality and profile,were found within the acceptance limits.The deviations of output reproducibility,linearity and constancy versus linac orientation were less than 1.0％.The transmission factors of two types of collimators were lower than 0.4％.End-to-end test demonstrated that the maximum deviation of the total delivery precision of CyberKnife VSI system was 0.87 mm.Conclusion The CyberKnife VSI system is accurate and reliable for stereotactic radiotherapy.
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Machine learning has developed rapidly in recent years.Using machine learning to predict the radiotherapy outcomes and complications can more accurately evaluate the patients' conditions and take appropriate treatment measures as soon as possible.The non-dose and dose related factors generated during radiotherapy are filtered and input into the algorithm model,then corresponding prediction result can be obtained.There are many algorithm models to predict survival rate,tumor control rate and radiotherapy complications,and the predicted result are more accurate now.However,the algorithm model also has various problems,and it needs constant exploration and improvement.
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Objective To compare five different detectors in output factor(OF)measurement for the CyberKnife(CK)system,and to select a suitable detector. Methods OFs for 12 different sizes of CK collimators were measured by EBT3films and 5 different commercially available detectors,consisting of diode detectors PTW 60017 and PTW 60018,ionizing chamber detectors PTW 31010 and PTW 30013,and diamond detector PTW 600019.OF was compared between different detectors and different measurement orientations. Results When the size of collimator was larger than 30 mm,the OF deviation among five detectors was less than 1%.When the size of collimator was smaller than 30 mm,however,the OF deviation among five detectors became large and obviously increased with the decrease in the size of collimator. With a OF deviation less than 2%,PTW 60019 achieved the best agreement with films. Compared with films,diode detectors gave slightly higher OFs,while ionizing chamber detectors gave much smaller OFs. The OF measurement was also affected by measurement orientation. PTW 60019 gave a smaller OF in the direction parallel to the central axis than in the direction perpendicular to the central axis of the radiation field,while PTW 31010 had an opposite result. Conclusions When the size of collimator is larger than 30 mm,PTW 31010,PTW 60017,PTW 60018,and PTW 60019 can be directly used for the OF measurement. When the size of collimator is smaller than 30 mm,correction is needed for the OF measurement using the above detectors. PTW 30013 is not suitable for the OF measurement in the small radiation field.
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In recent years,a large number of pre-clinical and clinical investigations have indicated that stereotactic body radiation therapy(SBRT)can not only kill cancer cells directly,but also induce the immunogenic death of cancer cells through releasing numerous tumor-associated antigens and damage-associated molecular patterns to form in situ tumor vaccine. CD8(+)T cells in lymph nodes are cross-sensitized by activated antigen-presenting cells. SBRT initiates local and systemic anti-tumor immune response. Moreover, SBRT can induce the abscopal effect if combined with immunotherapy. In addition, SBRT improves the microenvironment for tumor immunosuppression and enhances the sensitivity of tumors to immunotherapy. This article reviews the research advances in the synergistic mechanisms for combination therapy with SBRT and immunotherapy.
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Objective To evaluate four detectors for the off-axis ratio profile measurements of a CyberKnife system, and provide reference and suggestions for selecting and using the correct detectors. Methods Profiles were acquired by using four detectors, PTW-60017, PTW-60018, PTW-60019 and IBA-SFD, at different depths for different collimator sizes, with the detector stem being oriented both perpendicular and parallel to the central beam axis. The differences of profiles and the influence of detector orientation on measurement result were analyzed. Results All full width at half maximum ( FWHM) of field measured by four detectors in parallel orientation was larger than that in actual field size. The deviation was increased with the size of collimator and measurement depth, with the maximum deviation of 1. 9 mm. The maximum deviation of FWHM among four detectors was 0. 2 mm. The penumbra was the smallest for IBA-SFD, and the largest for PTW-60019. The maximum deviation of penumbra was 0. 3 mm. The IBA-SFD tended to over-respond in the out-of-field region when the collimator size was larger than 30 mm. Both FWHM and penumbra in perpendicular orientation were smaller than those in parallel orientation for PTW-60017, PTW-60018 and PTW-60019, especially at 5 mm collimator. However, the trend was opposite for IBA-SFD. With the increase of collimator aperture, the difference between the right and left penumbra acquired by four detectors was increased, with more obvious stem effects. Conclusions Similar profiles were acquired by four detectors, but the detector characteristics and effects of detector orientations should be considered.
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Objective To evaluate four detectors for the off-axis ratio profile measurements of a CyberKnife system, and provide reference and suggestions for selecting and using the correct detectors. Methods Profiles were acquired by using four detectors, PTW-60017, PTW-60018, PTW-60019 and IBA-SFD, at different depths for different collimator sizes, with the detector stem being oriented both perpendicular and parallel to the central beam axis. The differences of profiles and the influence of detector orientation on measurement result were analyzed. Results All full width at half maximum ( FWHM) of field measured by four detectors in parallel orientation was larger than that in actual field size. The deviation was increased with the size of collimator and measurement depth, with the maximum deviation of 1. 9 mm. The maximum deviation of FWHM among four detectors was 0. 2 mm. The penumbra was the smallest for IBA-SFD, and the largest for PTW-60019. The maximum deviation of penumbra was 0. 3 mm. The IBA-SFD tended to over-respond in the out-of-field region when the collimator size was larger than 30 mm. Both FWHM and penumbra in perpendicular orientation were smaller than those in parallel orientation for PTW-60017, PTW-60018 and PTW-60019, especially at 5 mm collimator. However, the trend was opposite for IBA-SFD. With the increase of collimator aperture, the difference between the right and left penumbra acquired by four detectors was increased, with more obvious stem effects. Conclusions Similar profiles were acquired by four detectors, but the detector characteristics and effects of detector orientations should be considered.
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Objective To investigate an X-ray total body irradiation (TBI) technique using anterior-posterior opposed fields with patients at the side-lying position,and to analyze the real-time in vivo dosimetry results.Methods The accelerator with 10 MV X-rays of Varian Trilogy was used for the TBI with the extended source to skin distance of 390 cm.The percent depth dose,off axis factors and absolute dose output were measured.The dose accuracy and homogeneity was monitored real-time using multichannel diode dosimeter for 10 patients.The monitored sites included forehead,mandible,suprasternal fossae,xiphoid,umbilicus,pelvis,middle of thigh,knee,middle of leg and ankle.The patients were irradiated at the side-lying position,with the prescription dose of 1 200 cGy/6 f during 3 days,the middle line dose rate of 5.0 cGy/min.Solid water was used for the compensation of the dose homogeneity.Results The off axis dose homogeneity was less than ± 5.0％ for the TBI geometry.The absolute dose output was 0.072 1 cGy/MU at the maximum dose point.The total body irradiation was finished smoothly for the 10 patients lying on side.The deviation of monitored total dose from the total prescription dose was within -4.9％ to 6.7％ for the 10 monitored sites.The monitored dose homogeneity was less than 5.0％.Conclusions The fractionated anterior-posterior opposed parallel TBI can be finished smoothly with patients side-lying.Accurate and homogenous dose distribution can be obtained using real-time dose monitoring and compensation with solid water.
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Objective To test the accuracy and reliability of Axesse accelerator for volumetric modulated arc therapy (VMAT).Methods The accuracy and reliability of Axesse accelerator for VMAT were tested in a stepwise manner, from the simple to the complex and from the part to the whole.For the parts of the system, the stability of dosimetric output and the position accuracy of multi-leaf collimator (MLC) were tested.For the process of the system, the variable VMAT dose rates and gantry speed modulation, the MLC speed and dose rate modulation, and dosimetric verification in patients were tested.Results Compared with fixed gantry irradiation, the variation in dosimetric output was below 1.0% for rotary irradiation including the slide rotary irradiation of the dynamic MLC.The MLC position error of 0.5 mm was visible using the electronic portal imaging system of Axesse, iViewGT 3.40.The MLC position accuracy was within 1 mm for fixed gantry irradiation and rotary irradiation.In the range of the dose rate applied in clinical practice, the testing results of variable VMAT dose rates and gantry speeds as well as variable dose rates and MLC speeds showed that the variation between different strip-field beam intensities was below 2.0%.Using a gamma criterion of 3 mm/3%, the pass rates in dosimetric verification of patients with cervical cancer, prostate cancer, and breast cancer were 96.52%, 95.72%, and 98.83%, respectively.Conclusions The Axesse system can precisely control MLC motion, variable dose rates, and gantry speeds in VMAT.The Axesse system is accurate and reliable for VMAT.
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Based on a review of currently published 40 papers ( 20 published in recent 5 years, 20 published in recent 10 years) on gold nanoparticles for cancer radiotherapy, the general characteristics, theoretical studies, in vitro experiment, in vivo experiment,and the clinical prospects of targeted radiotherapy with gold nanoparticles were reviewed. Three key aspects guarantee further investigation for the full understanding of the radiosensitization effect of gold nanoparticles:the cellular localization and tissue distribution of nanoparticles and influential factors;the micro dose enhancement effect of gold nanoparticles, and the molecular biological mechanism. More cross disciplinary collaboration, research, development and translation are needed before gold nanoparticles are put into clinical trials.