Methods:This study was a cross-sectional study. A prospective cohort study enrolled 42 patients with clinically suspected acute cerebrovascular disease and those undergoing follow-up examinations after intracranial vascular stenting at the First Affiliated Hospital of Zhengzhou University from June 2024 to May 2025. All patients underwent UHR PCD-CT examinations of the head and neck. Reconstructions were performed based on raw data, yielding conventional standard resolution (SR group) reconstructions and UHR images reconstructed using four distinct convolution kernels (Hv40, Hv48, Hv56, Hv64) in separate groups (Hv40 UHR group, Hv48 UHR group, Hv56 UHR group, Hv64 UHR group). Regions of interest were selected in the anterior cerebral artery, middle cerebral artery, posterior cerebral artery, posterior communicating artery, and anterior communicating artery. CT values and standard deviation (SD) values were measured for each artery, and signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. Additionally, the sharpness of the vessel edges and the full-width-half-maximum (FWHM) of each artery were measured. One-way analysis of variance or the nonparametric Kruskal-Wallis test was used to compare the subjective and objective image quality metrics across the five groups. Pairwise comparisons were performed using the LSD test or Dunn method.Results:Statistically significant differences were observed in the overall comparison of vascular imaging SD, SNR, CNR, vascular edge sharpness, and FWHM among the SR group, Hv40 UHR group, Hv48 UHR group, Hv56 UHR group, and Hv64 UHR group ( P<0.05). No statistically significant differences in CT values were found ( P>0.05). Pairwise comparisons revealed statistically significant differences between all groups ( P<0.05), except that no significant differences were observed in image SD, SNR, CNR, vascular edge sharpness, or FWHM between the Hv56 UHR and Hv64 UHR groups ( P>0.05). Conclusions:UHR PCD-CT provides better image quality for neurovascular imaging. For the display of small intracranial vessels, the Hv64 provides sharper vessel walls and better subjective image quality compared to the less sharp convolutional cores.Objective:To explore the value of ultra-high resolution (UHR) photon-counting detector CT (PCD-CT) to improve the quality of neurovascular images.

Objective:To explore the feasibility of high-level deep learning image reconstruction (DLIR-H) algorithm in dynamic myocardial perfusion (CTP) and coronary CT angiography (CCTA) extraction.Methods:From October 2021 to October 2022, 41 patients with confirmed or suspected coronary heart disease who underwent traditional CCTA and dynamic CTP examinations on GE Apex CT were prospectively collected. Traditional CCTA used 100 kVp tube voltage scan and DLIR-H to reconstruct the original image, while dynamic CTP used 80 kVp tube voltage scan to reconstruct the original image with ASiR-V 100% and DLIR-H, respectively. Comparing subjective and objective scores and myocardial blood flow (MBF) values?of rest and stress CTP between ASiR-V100% and DLIR-H. Subjective and objective scores, as well as stenosis degree and coronary CT blood flow reserve fraction (CT-FFR) value were analyzed on a vessel basis, and the image quality and diagnostic performance of traditional CCTA and single-phase CCTA (SP-CCTA) extracted under DLIR-H CTP were compared. Statistical analysis were performed using paired t test, Wilcoxon signed-rank test and χ2 test. Results:In the subjective image quality analysis of resting and stress CTP, DLIR-H was improved compared with ASiR-V100%, and the difference was statistically significant (all P<0.05). There was no significant difference in MBF values obtained by the two reconstruction methods in the assessment of quantitative myocardial perfusion ( P>0.05). Compared with traditional CCTA, the vascular CT value of SP-CCTA increased by 15.12%, the noise value increased by 32.27%, and the subjective score was also slightly lower (4.23±0.05). However, there were no statistically significant differences in total plaque volume, maximum stenosis degree, and number of CT-FFR positive vessels between SP-CCTA and traditional CCTA (all P>0.05). Conclusion:The deep learning reconstruction algorithm can not only improve the quality of the original image to a certain extent on dynamic CTP, but also extract high-quality single-phase CCTA to meet clinical diagnosis and realize a “one-stop” dynamic myocardial perfusion examination, which will help simplify the examination process, reduce contrast agent and radiation doses in the future.

Methods:This study was a cross-sectional study. A prospective cohort study enrolled 42 patients with clinically suspected acute cerebrovascular disease and those undergoing follow-up examinations after intracranial vascular stenting at the First Affiliated Hospital of Zhengzhou University from June 2024 to May 2025. All patients underwent UHR PCD-CT examinations of the head and neck. Reconstructions were performed based on raw data, yielding conventional standard resolution (SR group) reconstructions and UHR images reconstructed using four distinct convolution kernels (Hv40, Hv48, Hv56, Hv64) in separate groups (Hv40 UHR group, Hv48 UHR group, Hv56 UHR group, Hv64 UHR group). Regions of interest were selected in the anterior cerebral artery, middle cerebral artery, posterior cerebral artery, posterior communicating artery, and anterior communicating artery. CT values and standard deviation (SD) values were measured for each artery, and signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. Additionally, the sharpness of the vessel edges and the full-width-half-maximum (FWHM) of each artery were measured. One-way analysis of variance or the nonparametric Kruskal-Wallis test was used to compare the subjective and objective image quality metrics across the five groups. Pairwise comparisons were performed using the LSD test or Dunn method.Results:Statistically significant differences were observed in the overall comparison of vascular imaging SD, SNR, CNR, vascular edge sharpness, and FWHM among the SR group, Hv40 UHR group, Hv48 UHR group, Hv56 UHR group, and Hv64 UHR group ( P<0.05). No statistically significant differences in CT values were found ( P>0.05). Pairwise comparisons revealed statistically significant differences between all groups ( P<0.05), except that no significant differences were observed in image SD, SNR, CNR, vascular edge sharpness, or FWHM between the Hv56 UHR and Hv64 UHR groups ( P>0.05). Conclusions:UHR PCD-CT provides better image quality for neurovascular imaging. For the display of small intracranial vessels, the Hv64 provides sharper vessel walls and better subjective image quality compared to the less sharp convolutional cores.Objective:To explore the value of ultra-high resolution (UHR) photon-counting detector CT (PCD-CT) to improve the quality of neurovascular images.

Objective:To explore the feasibility of high-level deep learning image reconstruction (DLIR-H) algorithm in dynamic myocardial perfusion (CTP) and coronary CT angiography (CCTA) extraction.Methods:From October 2021 to October 2022, 41 patients with confirmed or suspected coronary heart disease who underwent traditional CCTA and dynamic CTP examinations on GE Apex CT were prospectively collected. Traditional CCTA used 100 kVp tube voltage scan and DLIR-H to reconstruct the original image, while dynamic CTP used 80 kVp tube voltage scan to reconstruct the original image with ASiR-V 100% and DLIR-H, respectively. Comparing subjective and objective scores and myocardial blood flow (MBF) values?of rest and stress CTP between ASiR-V100% and DLIR-H. Subjective and objective scores, as well as stenosis degree and coronary CT blood flow reserve fraction (CT-FFR) value were analyzed on a vessel basis, and the image quality and diagnostic performance of traditional CCTA and single-phase CCTA (SP-CCTA) extracted under DLIR-H CTP were compared. Statistical analysis were performed using paired t test, Wilcoxon signed-rank test and χ2 test. Results:In the subjective image quality analysis of resting and stress CTP, DLIR-H was improved compared with ASiR-V100%, and the difference was statistically significant (all P<0.05). There was no significant difference in MBF values obtained by the two reconstruction methods in the assessment of quantitative myocardial perfusion ( P>0.05). Compared with traditional CCTA, the vascular CT value of SP-CCTA increased by 15.12%, the noise value increased by 32.27%, and the subjective score was also slightly lower (4.23±0.05). However, there were no statistically significant differences in total plaque volume, maximum stenosis degree, and number of CT-FFR positive vessels between SP-CCTA and traditional CCTA (all P>0.05). Conclusion:The deep learning reconstruction algorithm can not only improve the quality of the original image to a certain extent on dynamic CTP, but also extract high-quality single-phase CCTA to meet clinical diagnosis and realize a “one-stop” dynamic myocardial perfusion examination, which will help simplify the examination process, reduce contrast agent and radiation doses in the future.

In 2009,the World Health Organization included snakebite on the list of neglected tropical diseases,acknowledging it as a common occupational hazard for farmers,plantation workers,and others,causing tens of thousands of deaths and chronic physical disabilities every year.This guideline aims to provide practical information to help clinical professionals evaluate and treat snakebite victims.These recommendations are based on clinical experience and clinical research evidence.This guideline focuses on the following topics:snake venom,clinical manifestations,auxiliary examination,diagnosis,treatments,and prevention.

BACKGROUND: Pneumonia-like primary pulmonary lymphoma (PPL) was commonly misdiagnosed as infectious pneumonia, leading to delayed treatment. The purpose of this study was to establish a computed tomography (CT)-based radiomics model to differentiate pneumonia-like PPL from infectious pneumonia. METHODS: In this retrospective study, 79 patients with pneumonia-like PPL and 176 patients with infectious pneumonia from 12 medical centers were enrolled. Patients from center 1 to center 7 were assigned to the training or validation cohort, and the remaining patients from other centers were used as the external test cohort. Radiomics features were extracted from CT images. A three-step procedure was applied for radiomics feature selection and radiomics signature building, including the inter- and intra-class correlation coefficients (ICCs), a one-way analysis of variance (ANOVA), and least absolute shrinkage and selection operator (LASSO). Univariate and multivariate analyses were used to identify the significant clinicoradiological variables and construct a clinical factor model. Two radiologists reviewed the CT images for the external test set. Performance of the radiomics model, clinical factor model, and each radiologist were assessed by receiver operating characteristic, and area under the curve (AUC) was compared. RESULTS: A total of 144 patients (44 with pneumonia-like PPL and 100 infectious pneumonia) were in the training cohort, 38 patients (12 with pneumonia-like PPL and 26 infectious pneumonia) were in the validation cohort, and 73 patients (23 with pneumonia-like PPL and 50 infectious pneumonia) were in the external test cohort. Twenty-three radiomics features were selected to build the radiomics model, which yielded AUCs of 0.95 (95% confidence interval [CI]: 0.94-0.99), 0.93 (95% CI: 0.85-0.98), and 0.94 (95% CI: 0.87-0.99) in the training, validation, and external test cohort, respectively. The AUCs for the two readers and clinical factor model were 0.74 (95% CI: 0.63-0.83), 0.72 (95% CI: 0.62-0.82), and 0.73 (95% CI: 0.62-0.84) in the external test cohort, respectively. The radiomics model outperformed both the readers' interpretation and clinical factor model ( P <0.05). CONCLUSIONS The CT-based radiomics model may provide an effective and non-invasive tool to differentiate pneumonia-like PPL from infectious pneumonia, which might provide assistance for clinicians in tailoring precise therapy.
Humans ; Retrospective Studies ; Pneumonia/diagnostic imaging* ; Analysis of Variance ; Tomography, X-Ray Computed ; Lymphoma/diagnostic imaging*

Objective: To identify the most appropriate meteorological variable for forecasting the health risk of high temperatures. Methods: The surveillance on causes of death, meteorological data and surveillance on air quality among registered residents in Ningbo City, Zhejiang Province during the period between May and October from 2013 to 2019 were collected. The association models of daily minimum temperature, average daily temperature, daily maximum temperature, daily minimum heat index, average daily heat index, daily maximum heat index, average daily apparent temperature and torridity index with deaths and years of life lost (YLL) were created using time series analysis and distributed lag non-linear models, and the model fitting effect was evaluated using the minimum Akaike information criterion (AIC) procedure. The most appropriate meteorological variable for forecasting gender-, age- and mortality-specific health risks of high temperatures was identified. Results: A total of 120 628 deaths were reported during the study period, with daily deaths of 94 cases, and daily YLL rate of 19.74 person-years/105. Except for daily minimum heat index and torridity index, the exposure-response relationships between other six meteorological variables and deaths and overall YLL rate all appeared a “J” shape. The lowest AIC values and the optimal model fitting effects were measured for the association models between average daily temperature and whole populations, females, subjects at ages of 65 years and older, and deaths and YLL rates due to circulatory diseases and respiratory diseases. Conclusion High model fitting effects are observed between average daily temperature and deaths and YLL rates, which are more suitable for forecasting the health risk of high temperature.

Objective : To evaluate the excess mortality risk related to heat wave in Ningbo, Zhejiang from 2013 to 2018, so as to provide a basis for formulating coping strategies for heat wave. Methods : The data of daily mortality, meteorological and air quality from May to October in Ningbo from 2013 to 2018 were obtained from Ningbo Center for Disease Control and Prevention, Ningbo Meteorological Bureau and Environmental Monitoring Center of Ningbo, respectively. The generalized linear model ( GLM ) and distributed lag non-linear model ( DLNM ) were used to estimate the associations between heat wave and cause-specific mortality. Results : Among 1 104 days of the study period, 18 heat waves occured and lasted for 132 days, accounting for 11.96%. A total of 102 954 deaths were reported in the same period. The risks of mortality in circulatory system diseases ( RR=1.09, 95%CI: 1.03-1.16 ), respiratory system diseases ( RR=1.14, 95%CI: 1.04-1.25 ), digestive system diseases ( RR=1.38, 95%CI: 1.15-1.65 ), nervous system diseases ( RR=1.32, 95%CI: 1.08-1.61 ), mental disorders ( RR=1.51, 95%CI: 1.12-2.03 ) and accidental injury ( RR=1.18, 95%CI: 1.06-1.32 ) and all causes ( RR=1.10, 95%CI: 1.06-1.14 ) increased at lag 0-1 day of heat wave. The total excess death related to heat wave was 1 218 ( 95%CI: 731-1 705 ) . The excess deaths of circulatory system diseases, respiratory system diseases, accidental injury, digestive system diseases, nervous system diseases, mental disorders, urinary system diseases and endocrine system diseases were 313 ( 95%CI: 104-556 ), 206 ( 95%CI: 59-368 ), 164 ( 95%CI: 55-292 ), 122 ( 95%CI: 48-208 ), 69 ( 95%CI: 17-131 ), 56 ( 95%CI: 13-113 ), 18 ( 95%CI: -15-64 ) and 3 ( 95%CI: -51-72 ). The excess deaths of urinary system and endocrine system diseases was not statistically significant ( P>0.05 ). Conclusion Heat wave can increase the mortality risk on the day and after a day in Ningbo from 2013 to 2018. Circulatory system diseases, respiratory system diseases and accidental injury rank top three in excess deaths.

Objective:Tumor-treating fields (TTFields) is a kind of non-invasive anti-mitotic tumor therapy, which has been approved for patients with newly diagnosed and recurrent glioblastoma. This study aims to explore the efficacy and safety of TTFields in high-grade gliomas in clinical practice settings.Methods:The clinical data of 15 patients with recurrent glioma and 9 patients with newly diagnosed high-grade glioma admitted to our center from April 2019 to January 2021 were retrospectively analyzed. All patients accepted TTFields≥1 month. Follow-up was performed for 5.3 months (ranged from 2.3 to 10.7 months); Response Assessment in Neuro-Oncology Working Group (RANO) criteria was used to evaluate the glioma responses. The progression-free survival (PFS) and overall survival (OS) were calculated according to Kaplan-Meier method. Common Terminology Criteria for Adverse Events v5.0 (CTCAE v5.0) and TTFields related skin adverse reaction (dAE) criteria were used to evaluate the adverse events. Quality of life questionnaire-core 30 (QLQ-C30) and QLQ-brain cancer module (QLQ-BN20) questionnaires were used to evaluate the health-related quality of life (HRQoL). Treatment compliance was evaluated by data on the use of NovoTTF-200A devices, and calculated as a percentage of daily TTFields usage.Results:The median duration of TTFields was 4.2 months (ranged from 1.0 to 10.7 months), with a median compliance rate of 91.5% (67.0%-97.0%). TTFields was used alone in 2 patients and used with combination of chemotherapy in 22 patients. From follow-up to April 2021, 14 patients had stable symptoms and 10 had disease progression (8 died). The median PFS and OS of recurrent patients were 5.9 months ( 95%CI: 3.3-8.6 months) and 8.5 months ( 95%CI: 3.2-13.8 months), respectively; and the median PFS and OS of newly diagnosed patients were both 10.7 months (without 95%CI). The common adverse events included grading 1 dAE (58.3%) and grading 2 dAE (12.5%), without grading 3 or 4 dAE, manifested as contact or allergic dermatitis, erosion, folliculitis and ulcers. And 87.5% patients had stable HRQoL. Conclusions:The preliminary results showed that the survival of recurrent high-grade glioma patients treated by TTFields is similar to that reported in foreign literature; and the newly diagnosed patients need further survival follow-up. The patients' treatment compliance and safety are good. The dAE incidence (grading 1-2) is higher than that reported in the literature, and the toxicity was acceptable.

Objective To analyze the correlations of clinical characteristics,CT and pathology features of peripheral primitive neuroectrodermal tumors (pPNET)in abdomen-pelvis region,and to improve the understanding of the disease.Methods The clinical information,CT and pathological features of 23 confirmed pPNET patients in abdomen-pelvis region were analyzed retrospectively.Results (1)All patients had preoperative clinical and imaging data integrallty.(2)23 cases showed soft tissue masses with fuzzy boundary and the average diameter were 10.72 cm.Among all,9 cases showed with varying degrees of sac necrosis,while 2 cases showed with platelet hemorrhage and 4 cases with speckled calcifications.Most showed slight-to-moderate heterogeneous enhancement and the necrosis and cystic are-as showed more obvious.12 cases showed with different degree of recurrence,invasion or distant metastasis.5 cases combined with tumor emboli and 4 cases with tumor feeding vessels.(3)Immunohistochemical examination showed CD99 expressed in 1 9 patients, CD56 in 11,vimentin(Vim)in 12,synaptophysin(Syn)in 11,neuron specific enolase(NSE)in 4,FLI-1 in 4 and epithelial membrane antigen (EMA)in 4 patients.Conclusion pPNET is common among young patients with a high degree of malignancy.CT features include large mass with invasive growth,commonly combined heterogenous density,necrosis and cystic changes.Persistent enhancement is observed during nephrographic phase.