Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

Objective To evaluate the accuracy of multiparametric imaging on the dual-source CT through acceptance and commissioning testing, and to provide a reference for standardized clinical application. Methods Both the adult and pediatric dual-source CT scanning modes were used to scan the electron density phantom, and identical multiparametric image reconstruction tasks were performed, including the conventional CT images, the mixed CT images, the virtual monoenergetic images, the iodine images, the electron density images, and the effective atomic number images. Results In the adult scanning mode, the virtual monoenergetic CT numbers showed the greatest difference for the cortical bone (1722 HU at 40 keV vs. 30 HU at 80 keV), with smaller differences observed for other materials as their atomic numbers decreased. The pediatric scanning mode exhibited a similar trend, with the largest difference occurring at 40 keV (1393 HU). In the adult scanning mode, the deviations between the theoretical and measured iodine concentration values were all within 5%, whereas in the pediatric scanning mode, the largest deviation was 15% for an iodine concentration of 2.0 mg/mL. For the electron density, the largest deviation between the theoretical and measured values occurred in the LN450 lung (9.18% in the adult scanning mode and 8.96% in the pediatric scanning mode); the deviations for the LN300 lung were all below 7.2%, for aluminum below 6.3%, and for other tissues within 3%. For the effective atomic number, the deviations between the theoretical and measured values were all within 5% in both scanning modes. Conclusion To ensure the accuracy and reproducibility of the dual-source CT applications, a comprehensive acceptance testing protocol should be established to guarantee the safety and precision of the CT localization process.

Two novel diketopiperazines (1 and 5), along with ten known compounds (2-4, 6-12) demonstrating significant skin inflammation inhibition, were isolated from a marine-derived fungus identified as Aspergillus sp. FAZW0001. The structural elucidation and configurational reassessments of compounds 1-5 were established through comprehensive spectral analyses, with their absolute configurations determined via single crystal X-ray diffraction using Cu Kα radiation, Marfey's method, and comparison between experimental and calculated electronic circular dichroism (ECD) spectra. Compounds 1, 2, and 8 exhibited significant anti-inflammatory activities in Propionibacterium acnes (P. acnes)-induced human monocyte cell lines. Compound 8 demonstrated the ability to down-regulate interleukin-1β (IL-1β) expression by inhibiting Toll-like receptor 2 (TLR2) expression and modulating the activation of myeloid differentiation factor 88 (MyD88), mitogen-activated protein kinase (MAPK), and nuclear factor κB (NF-κB) signaling pathways, thus reducing the cellular inflammatory response induced by P. acnes. Additionally, compound 8 showed the capacity to suppress mitochondrial reactive oxygen species (ROS) production and nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3) inflammasome activation, thereby reducing IL-1β maturation and secretion. A three-dimensional quantitative structure-activity relationships (3D-QSAR) model was applied to compounds 5-12 to analyze their anti-inflammatory structure-activity relationships.
Humans ; Aspergillus/chemistry* ; Diketopiperazines/isolation & purification* ; Anti-Inflammatory Agents/isolation & purification* ; Interleukin-1beta/genetics* ; Toll-Like Receptor 2/immunology* ; Propionibacterium acnes/drug effects* ; NF-kappa B/genetics* ; Molecular Structure ; Myeloid Differentiation Factor 88/immunology* ; Monocytes/immunology* ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics* ; Cell Line

Objective:To investigate the influence of ultrasonic monitoring of bladder filling levels on setup errors before fractionated radiotherapy for cervical cancer patients through a comparative analysis, and its effectiveness in improving clinical target volume (CTV) margins.Methods:A retrospective study was conducted on 1 284 error data of setup via cone beam CT (CBCT) and 6D setup error correction system from 172 cervical cancer patients treated in the Radiotherapy Department of Peking University Cancer Hospital from January 2019 to October 2023. These patients were classified into two groups: 87 (659 times of setup) with ultrasonic monitoring of bladder filling levels and 85 (625 times of setup) without ultrasonic monitoring. The setup errors, error distributions, and numbers of abnormal setups between the two groups were compared in the lateral (Lat), longitudinal (Lng), vertical (Vrt), pitch (Pitch), roll (Roll), and rotational (Rtn) dimensions. Moreover, the CTV to planning target volume(PTV) margin values in the three-dimensional direction were calculated for both groups to assess the clinical value of ultrasonic monitoring of bladder filling levels before fractionated radiotherapy.Results:Compared to the group without ultrasonic monitoring, the group with ultrasonic monitoring exhibited lower median values of setup errors in all six-dimensional directions and smaller upper and lower interquartile ranges ( Z = -10.86 to -6.34, P<0.05). The group with ultrasonic monitoring manifested more concentrated setup errors in various directions and statistically significantly reduced numbers of abnormal setups ( χ2=15.33, P<0.05). Moreover, CTV-PTV margins of the group with ultrasonic monitoring displayed reduced CTV-PTV margin values by 0.55, 1.52, and 1.26 mm in the Vrt, Lng, and Lat directions, respectively. Conclusions:Pre-radiotherapy ultrasonic monitoring of bladder filling levels in cervical cancer patients can significantly improve the repeatability of setup, thus notably reducing the incidence of abnormal setups. Theoretically, it can narrow the range from the CTV to the PTV, thereby minimizing radiation exposure to healthy tissues and ultimately enhancing radiotherapy precision for cervical cancer and reducing radiation damage.

Objective:To investigate the influence of ultrasonic monitoring of bladder filling levels on setup errors before fractionated radiotherapy for cervical cancer patients through a comparative analysis, and its effectiveness in improving clinical target volume (CTV) margins.Methods:A retrospective study was conducted on 1 284 error data of setup via cone beam CT (CBCT) and 6D setup error correction system from 172 cervical cancer patients treated in the Radiotherapy Department of Peking University Cancer Hospital from January 2019 to October 2023. These patients were classified into two groups: 87 (659 times of setup) with ultrasonic monitoring of bladder filling levels and 85 (625 times of setup) without ultrasonic monitoring. The setup errors, error distributions, and numbers of abnormal setups between the two groups were compared in the lateral (Lat), longitudinal (Lng), vertical (Vrt), pitch (Pitch), roll (Roll), and rotational (Rtn) dimensions. Moreover, the CTV to planning target volume(PTV) margin values in the three-dimensional direction were calculated for both groups to assess the clinical value of ultrasonic monitoring of bladder filling levels before fractionated radiotherapy.Results:Compared to the group without ultrasonic monitoring, the group with ultrasonic monitoring exhibited lower median values of setup errors in all six-dimensional directions and smaller upper and lower interquartile ranges ( Z = -10.86 to -6.34, P<0.05). The group with ultrasonic monitoring manifested more concentrated setup errors in various directions and statistically significantly reduced numbers of abnormal setups ( χ2=15.33, P<0.05). Moreover, CTV-PTV margins of the group with ultrasonic monitoring displayed reduced CTV-PTV margin values by 0.55, 1.52, and 1.26 mm in the Vrt, Lng, and Lat directions, respectively. Conclusions:Pre-radiotherapy ultrasonic monitoring of bladder filling levels in cervical cancer patients can significantly improve the repeatability of setup, thus notably reducing the incidence of abnormal setups. Theoretically, it can narrow the range from the CTV to the PTV, thereby minimizing radiation exposure to healthy tissues and ultimately enhancing radiotherapy precision for cervical cancer and reducing radiation damage.

Objective To investigate the identification of octreotide(OCT)modified chitosan(CS)miR-155 molecular beacon nanoparticles(CS-miR-155-MB-OCT)and imaging of lung cancer cells for the early screening of lung cancer.Methods A nude mouse model of lung transplantation tumor was established by injecting A549 lung cancer cells into tail veins to establish lung xenograft models.Cre adenovirus was injected through nasal cavity,and mice were killed at 4,6,8 and 12 weeks after adenovirus injection to establish lung cancer models of atypical hyperplasia,adenoma,carcinoma in situ and adenocarcinoma of lung in LSL K-ras G12D transgenic mice at different pathological stages.Lung tissue samples were taken and observed by HE staining.Immunohistochemistry were used to detect the expression of somatostatin receptor 2(SSTR2).Real-time fluorescence quantitative PCR was used to detect miR-155 expression levels in lung xenograft models and transgenic mice at different stages of lung cancer.Then CS-miR-155-MB and CS-miR-155-MB-OCT were injected via tail vein in lung xenograft models.CS-miR-155-MB-OCT was injected via tail vein in transgenic mice models.The fluorescence signals of lung in nude mice and transgenic mice at different disease stages were imaged by living imaging system.Frozen slices of lung tissue were made.The source of fluorescence signal was detected by laser confocal scanning microscope(CLSM).Results HE staining showed that lung transplantation tumor models and lung cancer models of atypical hyperplasia,adenoma,carcinoma in situ and lung adenocarcinoma at different pathological stages were successfully constructed.Immunohistochemical analysis showed somatostatin receptor 2(SSTR2)was expressed in transplanted lung tumor and tissue at different pathological stages.In transgenic mouse models,the expression of miR-155 was gradually increased as the disease progressed(P＜0.05).In lung xenograft models,the fluorescence signals were significantly higher in the CS-miR-155-MB-OCT group than those of the CS-miR-155-MB group(P＜0.05).In transgenic mouse models,the fluorescence signals gradually increased with the gradual progression of lesions(P＜0.05).After re-imaging the lung tissue,it was found that the fluorescence signal came from lung,and CLSM showed that the fluorescence signal came from cancer cells and some normal alveolar epithelial cells.Conclusion CS-miR-155-MB-OCT can dynamically reflect the occurrence and development of lung cancer according to changes of different fluorescence intensity,thus providing a new technology for the early diagnosis of lung cancer.

Objective To investigate the clinical characteristics and dosimetric parameters associated with acute hematologic toxicity (AHT) resulting from radiation-induced damage to hematopoietic organs in patients undergoing chemoradiotherapy for cervical cancer and to provide a reference for establishing dose constraints in relevant regions of interest (ROIs) and predicting adverse tissue reactions during the development of clinical treatment plans. Methods A retrospective analysis was conducted on 556 patients with cervical cancer who underwent chemoradiotherapy at our hospital. Univariate (χ² and t-test) and multivariate (binary logistic regression analyses) methods were employed to investigate the association of clinical factors and pelvic dose-volume parameters with grade ≥ 3 AHT in patients with cervical cancer. Clinical factors comprised patients’ age, clinical stage, pathologic stage, whether the patient had received chemotherapy in the radiotherapy cycle of interest, and dose-volume dosimetric parameters V_x and D_mean for pelvic bone marrow (BM) and femoral head (FH) structures. Results The incidence of AHT among the included cases was 30.4% (169/556). Chi-square analysis of the clinical factors revealed that whether the patient had received chemotherapy, patient’s age, and pathologic stage had a significant impact on AHT. Univariate analysis showed that the factors associated with AHT were mean dose, V₅, V₁₀, V₁₅, V₂₀, and V₂₅ of BM and FH; dosimetric parameters such as V₃₅ of FH had a significant impact on the development of AHT. Multivariate logistic regression analysis identified V₁₅ of pelvic BM as an independent risk factor for AHT (P=0.041), with a threshold value of 84.29% as determined by a receiver operating characteristic (ROC) curve. Conclusion Whether a patient had received chemotherapy in the radiotherapy cycle of interest, and patient’s age and pathologic stage can serve as predictors of AHT. V₁₅ of BM is an independent risk factor for AHT development. Therefore, when formulating a treatment plan, it is crucial to ensure that pelvic V₁₅ remains below 84.29% to effectively reduce the incidence of grade ≥ 3 acute bone marrow depression.

Purpose/Significance To construct a specialized database for inflammatory demyelinating disease of the central nervous system(CNS),so as to contribute to clinical research and improve the diagnostic and treatment capabilities of primary healthcare institu-tions.Method/Process Using the internet to collect medical data,after processing and analysis,the CNS inflammatory demyelinating disease database is constructed.Using statistical analysis,natural language processing(NLP),artificial intelligence(AI)image recog-nition and data visualization and other technologies,the database information is integrated and analyzed.Result/Conclusion A standard-ized big database for CNS inflammatory demyelinating diseases is constructed,which enables visualization of clinical research data,pro-vides patient education and specialist training,and facilitates multi-center teleconsultations.The establishment of a specialized database for the CNS inflammatory demyelinating disease can promote the transformation of medical research achievements,provide references for future real-world clinical research,optimize the process of diagnosis and treatment,and improve the clinical capability of primary healthcare institutions.