Objective: To evaluate the diagnostic performance of magnetic resonance spectroscopy (MRS) in discriminating fumarate hydratase-deficient (FH-d) uterine leiomyomas (ULs) from FH-preserved ULs. Materials and Methods: This study consisted of three stages, with independent cohorts recruited for each stage: 1) sample-size estimation was retrospectively performed on UL specimens (diameter ≥3 cm; age, 20–40 years) from our database with immunohistochemistry (IHC) for 2-succinocysteine (2-SC) as the reference, without genetic testing, 2) MRS sequence optimization in confirmed FH germline mutation participants with ultrasound-detected ULs (diameter ≥3 cm), without IHC analysis, and 3) prospective diagnostic test accuracy was evaluated in consecutive participants with ultrasound-detected ULs (diameter ≥3 cm;age, 20–40 years), using IHC for 2-SC for determining the FH status and subsequent genetic testing in those with positive 2-SC results to identify whether FH mutations were germline or somatic in origin. The choline and fumarate peaks in MRS were classified as positive, negative, or technical failure (TF). TFs were analyzed separately and excluded from the primary diagnostic accuracy calculations. T1-, T2-, and diffusion-weighted images were interpreted as hyperintense or hypointense. The enhancement rate and apparent diffusion coefficient were also acquired. Diagnostic performance was compared between MRS and various magnetic resonance imaging (MRI) features. Results: The optimal MRS parameters for the fumarate peak were echo time (TE) = 140 ms and an average of 256. Among the 360 prospective participants, 37 were confirmed to have FH-dULs. MRS showed positive fumarate peaks in 35 of 37 FH-dULs.After excluding six TFs, the positive fumarate peak on MRS showed 94.6% (35/37) sensitivity, 99.7% (316/317) specificity, and 99.2% (351/354) accuracy, all of which were significantly superior to those of other MRI features (P ≤ 0.002). Conclusion A positive fumarate peak on MRS may be a useful imaging biomarker for diagnosing FH-dULs.

Objective: To assess the status of sexual behaviors, HIV/AIDS knowledge awareness, and novel synthetic drug use among school attending young students in Guangdong Province, so as to provide evidence base for formulating targeted intervention strategies. Methods: From September to December 2024, a convenience sampling method was employed to conduct an anonymous online survey among 41 119 students from 20 higher education institutions and vocational colleges in Guangdong Province. Chi square test was utilized for rate comparisons and univariate analysis, and a multivariate Logistic regression model was applied to analyze factors associated with novel synthetic drug use. Results: The self reported rate of sexual behavior was 5.2%. Among sexually active students, the rates of unprotected sexual intercourse, having temporary sexual partners, and having commercial sexual partners were 32.4%, 34.5%, and 26.3%, respectively. The awareness rate of HIV related knowledge was 75.7%. The overall use rate of novel psychoactive substances(NPS) was 1.0%, and among sexually active students it was 6.5%. Multivariate Logistic regression analysis showed that students with sexual experience ( OR =4.15) and those with HIV testing history ( OR =9.38) had higher risks of NPS use; among sexually active students, those with unprotected sexual intercourse ( OR =6.83) and those with commercial sexual partners ( OR = 4.68 ) had higher risks of NPS use (all P <0.05). Conclusions The HIV/AIDS knowledge level among surveyed students needs further improvement, and high risk sexual behaviors are cross linked with novel synthetic drug use. It is recommended to carry out integrated health education for all students and implement comprehensive targeted interventions for sexually active students.

Objective:To investigate the current application of blood purification in the treatment of acute poisoning within Jiangsu Province and to evaluate the impact of extracorporeal blood purification on the clinical outcomes of critically poisoned patients.Methods:This multicenter, cross-sectional real-world observational study followed patients presenting with poisoning to the emergency departments of nine hospitals in Jiangsu Province between June 2015 and May 2019. Data were collected on demographic characteristics, vital signs within the first hour of emergency presentation, treatment modalities, length of hospital stay, and survival outcomes. Clinical data from patients who underwent extracorporeal blood purification were compared with those who did not, using the Wilcoxon rank-sum test and Chi-square test.Results:A total of 4 178 poisoning cases were included between June 2015 and May 2019. Among them, 21.7% (908/4 178) received blood purification therapy, while 78.3% (3 270/4 178) did not. Hemoperfusion (90.4%) was the most frequently employed method, followed by continuous renal replacement therapy (CRRT) (4.4%). In combined blood purification modalities, 4.8% underwent hemoperfusion combined with CRRT, 0.1% received hemoperfusion with plasma exchange, and another 0.1% underwent hemoperfusion combined with both CRRT and plasma exchange. Among patients who underwent blood purification, pesticide poisoning was the most prevalent (76.3%), with the most common toxic agents being paraquat (23.7%), dichlorvos (8.7%), methamidophos (5.2%), omethoate (4.0%), and glyphosate (3.7%). Compared to the non-blood purification group, patients in the blood purification group were more likely to present within the first hour with a low Glasgow Coma Scale (GCS) score (3-8) (22.6% vs. 9.7%, P <0.05), low mean arterial pressure (8.0% vs. 3.2%, P <0.05), longer hospital stays [5(3,9) days vs. 2(1,4) days, P <0.05] and a higher in-hospital mortality rate (21.1% vs. 5.3%, P <0.05). Follow-up via telephone 28 days after discharge revealed a survival rate of 78.9%, with a mortality rate of 21.1% in the blood purification group. Conclusions:Hemoperfusion is the most commonly utilized blood purification technique for treating poisoning in Jiangsu Province, with pesticides being the primary toxic agents treated. Although the mortality rate is higher in the blood purification group, the intervention may still contribute to improved patient outcomes.

Artificial intelligence (AI) technologies are being widely applied in radiotherapy. However, the integration of AI into clinical workflows of radiotherapy faces a series of challenges, such as poor model interpretability, domain shifts between clinical application and training data, and the inherent model uncertainties. Therefore, case-specific quality assurance (QA) is essential before deploying AI models in clinical practice. This paper reviews and summarizes QA methodologies for the application of AI models in radiotherapy across four key areas: image registration, image generation, region of interest segmentation, and treatment planning.

Objective:To evaluate the feasibility of using the domestic ArcherQA system for fast and simplified independent verification of CyberKnife (CK) stereotactic radiotherapy (SRT) plans.Methods:SRT plans of 57 patients treated with CK at Tianjin Medical University Cancer Institute and Hospital from August 2021 to August 2022 were retrospectively analyzed, including 15 intracranial, 30 pulmonary, and 12 abdominal tumors cases. Point-dose and planar-dose verifications were performed using an ionization chamber and radiochromic films embedded in a homogeneous phantom, and the results were compared with those calculated by the treatment planning system (TPS). The localization CT images and corresponding SRT plans were imported into the ArcherQA system for independent dose verification and analysis. The correlation between ArcherQA results and phantom measurements was analyzed, with comparisons of target mean dose differences and γ pass rates.Results:Phantom measurement results showed, the measured point-dose differences for intracranial, lung, and abdominal plans were -0.94% ± 3.22%, 1.92% ± 2.05%, and 2.12% ± 0.77%, respectively. The mean dose differences in target dose calculation between ArcherQA and TPS: intracranial in the gross tumor volume (GTV) regions were 0.34% ± 2.21%, lung tumor GTV were -2.47% ± 2.46%, and abdominal tumor GTV were 0.80% ± 2.61%, respectively. Among them, the abdominal GTV region showed the highest correlation between ArcherQA and measured results ( r=0.78). The average two-dimensional γ pass rates (2 mm/2%, threshold=10%) measured using phantom films were 95.92% ± 2.35% for intracranial, 95.70% ± 2.74% for lung, and 96.74% ± 3.41% for abdominal tumors plans, respectively. The three-dimensional ArcherQA results showed comparable γ pass rates (1 mm/2%, threshold=10%) for lung and abdominal GTV and PTV regions, with similar medians and data dispersion to film measurements. Conclusions:The ArcherQA system enables rapid and efficient independent dose verification of CK SRT plans without the need for additional hardware. The verification results show good correlation with phantom measurements, supporting its potential as an auxiliary quality assurance tool in clinical CK SRT implementation.

Artificial intelligence (AI) technologies are being widely applied in radiotherapy. However, the integration of AI into clinical workflows of radiotherapy faces a series of challenges, such as poor model interpretability, domain shifts between clinical application and training data, and the inherent model uncertainties. Therefore, case-specific quality assurance (QA) is essential before deploying AI models in clinical practice. This paper reviews and summarizes QA methodologies for the application of AI models in radiotherapy across four key areas: image registration, image generation, region of interest segmentation, and treatment planning.

Objective:To evaluate the feasibility of using the domestic ArcherQA system for fast and simplified independent verification of CyberKnife (CK) stereotactic radiotherapy (SRT) plans.Methods:SRT plans of 57 patients treated with CK at Tianjin Medical University Cancer Institute and Hospital from August 2021 to August 2022 were retrospectively analyzed, including 15 intracranial, 30 pulmonary, and 12 abdominal tumors cases. Point-dose and planar-dose verifications were performed using an ionization chamber and radiochromic films embedded in a homogeneous phantom, and the results were compared with those calculated by the treatment planning system (TPS). The localization CT images and corresponding SRT plans were imported into the ArcherQA system for independent dose verification and analysis. The correlation between ArcherQA results and phantom measurements was analyzed, with comparisons of target mean dose differences and γ pass rates.Results:Phantom measurement results showed, the measured point-dose differences for intracranial, lung, and abdominal plans were -0.94% ± 3.22%, 1.92% ± 2.05%, and 2.12% ± 0.77%, respectively. The mean dose differences in target dose calculation between ArcherQA and TPS: intracranial in the gross tumor volume (GTV) regions were 0.34% ± 2.21%, lung tumor GTV were -2.47% ± 2.46%, and abdominal tumor GTV were 0.80% ± 2.61%, respectively. Among them, the abdominal GTV region showed the highest correlation between ArcherQA and measured results ( r=0.78). The average two-dimensional γ pass rates (2 mm/2%, threshold=10%) measured using phantom films were 95.92% ± 2.35% for intracranial, 95.70% ± 2.74% for lung, and 96.74% ± 3.41% for abdominal tumors plans, respectively. The three-dimensional ArcherQA results showed comparable γ pass rates (1 mm/2%, threshold=10%) for lung and abdominal GTV and PTV regions, with similar medians and data dispersion to film measurements. Conclusions:The ArcherQA system enables rapid and efficient independent dose verification of CK SRT plans without the need for additional hardware. The verification results show good correlation with phantom measurements, supporting its potential as an auxiliary quality assurance tool in clinical CK SRT implementation.

Objective To improve the performance of auto-segmentation of prostate target area and organs-at-risk in online magnetic resonance image and enhance the efficiency of magnetic resonance imaging-guided adaptive radiotherapy(MRIgART)for prostate cancer.Methods A retrospective study was conducted on 40 patients who underwent MRIgART for prostate cancer,including 25 in the training set,5 in the validation set,and 10 in the test set.The planning CT images and corresponding contours,along with online MR images,were registered and input into a deep learning network for online MR image auto-segmentation.The proposed method was compared with deformable image registration(DIR)method and single-MR-input deep learning(SIDL)method.Results The overall accuracy of the proposed method for auto-segmentation was superior to those of DIR and SIDL methods,with average Dice similarity coefficients of 0.896 for clinical target volume,0.941 for bladder,0.840 for rectum,0.943 for left femoral head and 0.940 for right femoral head,respectively.Conclusion The proposed method can effectively improve the accuracy and efficiency of auto-segmentation in MRIgART for prostate cancer.

Objective To evaluate the effects of the multiple factors especially image geometric accuracy of the imaging system on the segmentations of target areas and organs-at-risk.Methods The study used phantoms to test the imaging performance of the 1.5T magnetic resonance(MR)linear accelerator system,including the assessments of MR image geometric distortion and the segmentation errors caused by factors such as image geometric distortion.Model 604-GS large field MR image distortion phantom was used to explore the geometric distortion of the MR images for MR-guided radiotherapy;and CIRS Model 008z upper abdominal phantom was used to analyze the segmentation errors of target areas and organs-at-risk.Results The average geometric distortion and maximum distortion of 3D T1WI-FFE images vs 3D T2WI-TSE images were 0.54 mm vs 0.53 mm and 1.96 mm vs 1.68 mm,respectively;and the control points of the large distortions were distributed at the edges of the phantom,which was consistent with the MR imaging characteristics previously reported.Compared with CT-based segmentation contour,the MDA was 1.17 mm and DSC was 0.91 for 3D T1WI-FFE,while MDA was 0.86 mm and DSC was 0.94 for 3D T2WI-TSE.Conclusion The study quantitatively assesses the geometric accuracy of the imaging system for MR-guided radiotherapy.The phantom-based contour analysis reveals that with CT image as gold standard,the segmentation error in MRI images meets the clinical requirements,and that 3D T2WI-TSE image is advantageous over 3D T1WI-FFE image in segmentation accuracy.

Objective Magnetic resonance simulator(MR Sim)is a novel type of simulation equipment utilized in radiotherapy.Acceptance testing is an essential quality assurance procedure prior to the clinical use of the MR Sim.The report provides the detailed procedures and result analysis of acceptance testing for an MR Sim.Methods The acceptance testing scheme was developed following the recently published AAPM TG284 report and the NCC/T-RT 002-2023 guidelines.Quality control equipments such as ACR(American College of Radiology)large phantom and geometric distortion measurement phantom were used for evaluating various aspects of the MR Sim,including the effectiveness of shielding,the functionality of imaging system,the image quality,the performance of radio frequency coils,the geometric accuracy of large field imaging,the precision of external laser markings,the couch movement accuracy,and the image transmission accuracy.Results The shielding effectiveness at a frequency of 150 MHz exhibited an average value of 105 dB.All of 8 image quality indices,namely geometric accuracy,slice position accuracy,slice thickness accuracy,image uniformity,artifact ratio,signal-to-noise ratio,high-contrast spatial resolution,and low-contrast resolution,fell within recommended tolerances.The maximum geometric distortion observed across a 25 cm field of view was less than 2 mm.The errors in external laser markings and couch movement accuracy were both less than 1 mm.The couch levelness was less than 1°.Both radio frequency coils and image transmission passed the required tests.Conclusion MR Sim is high-precision and complex.To ensure its precise application in radiotherapy,the acceptance testing for an MR Sim should be meticulously designed and executed following the established guidelines and accounting for its unique performance characteristics.