Objective To study the effect of local mild hypothermia on serum brain natriuretic peptide (BNP) in patients with acute intracerebral hemorrhage.Methods Sixty patients with acute intracerebral hemorrhage were divided into local mild hypothermia group (30 cases) and routine therapy group (30 cases) by random digits table method.Routine therapy group was given conventional therapy,and local mild hypothermia group was given local mild hypothermia treatment besides conventional therapy.The neurologic impairment was evaluated according to American National Institute of Health Stroke Scale (NIHSS) scores on admission,and on the 3rd,7th and 14th day after treatment.Serum BNP levels in patients were determined dynamically on admission,and on the 3rd and 14th day after treatment.The effect was evaluated on the 14th day after treatment.Results There was no significant difference in serum BNP on admission between two groups (P ＞ 0.05).Serum BNP on the 3rd,14th day after treatment in local mild hypothermia group was lower than that in routine therapy group[(153.47 ± 32.01) ng/L vs.(187.45 ± 40.21)ng/L and (111.02 ± 38.27) ng/L vs.(139.71 ± 29.53) ng/L],and there was significant difference(P ＜ 0.01 or ＜ 0.05).There was no significant difference in NIHSS scores on admission and on the 3rd day after treatment between two groups (P ＞0.05).NIHSS scores on the 7th and 14th day after treatment in local mild hypothermia group was lower than that in routine therapy group [(13.84 ± 6.00) scores vs.(16.59 ± 4.62)scores and (9.23 ± 4.48) scores vs.(13.02 ± 6.76) scores],and there was significant difference (P ＜ 0.01).The total effective power in local mild hypothermia group was higher than that in routine therapy group[90.0％(27/30) vs.66.7％ (20/30)],and there was significant difference (P ＜ 0.05).Conclusions The local mild hypothermia therapy can not only significantly improve the defect of nerve function in patients with acute intracerebral hemorrhage but also reduce the serum BNP.It can improve the curative effect in patients with acute intracerebral hemorrhage.

Objective:Proton pencil beam (PB) dose calculation can achieve rapid dose calculation, whereas it is inaccurate due to the approximation in dealing with inhomogeneities. Monte Carlo (MC) dose calculation is recognized as the most accurate method, but it is extremely time consuming. The aim of this study was to apply deep-learning methods to improve the accuracy of PB dose calculation by learning the difference between the MC and PB dose distribution.Methods:A model which could convert the PB dose into the MC dose in lung cancer patients treated with intensity-modulated proton therapy (IMPT) was established based on the Hierarchically Densely Connected U-Net (HD U-Net) network. PB dose and CT images were used as model input to predict the MC dose for IMPT. The beam dose and CT images of 27 non-small cell lung cancer patients were preprocessed to the same angle and normalized, and then used as model input. The accuracy of the model was evaluated by comparing the mean square error and γ passing rate (1 mm/1%) results between the predicted dose and MC dose.Results:The predicted dose showed good agreement with MC dose. Using the 1 mm/1% criteria, the average γ passing rate (voxels receiving more than 10% of maximum MC dose) between the predicted and MC doses reached (92.8±3.4)% for the test patients. The average dose prediction time for test patients was (6.72±2.26) s.Conclusion:A deep-learning model that can accurately predict the MC dose based on the PB dose and CT images is successfully developed, which can be used as an efficient and practical tool to improve the accuracy of PB dose calculation for IMPT in lung cancer patients.

Objective:In Shanghai Advanced Proton Therapy Facility (SAPT) of Ruijin Hospital Proton Therapy Center, the calculation accuracy of the commercial proton treatment planning system RayStation (V10), especially the accuracy of the proton range calculation, was measured and verified, aiming to provide reference for the clinical application of the treatment planning system.Methods:A head phantom was used to verify the calculation accuracy of RayStation. The phantom CT was imported into treatment planning system (TPS). The phantom was followed closely by a water tank with a one-liter cubic target. A single field verification plan with the prescribed dose of 200 cGy (relative biological effectiveness) was designed and implemented. Then, the measured distribution results were compared with the calculation results.Results:When the verification plan of the phantom was designed with the default settings of RayStation, the measured longitudinal dose distribution was approximately 4 mm deeper than that of TPS, indicating that RayStation overestimated the water equivalent thickness (WET) of the tissue substitute materials in the phantom. To study the range error, the actual beam was used to measure the WET of the soft tissue substitute material. The default setting of RayStation was fine-tuned according to the measured results. It was found that the error between the measured SOBP and TPS calculations was reduced to only 2 mm.Conclusions:Using the default setting of RayStation to calculate the stopping power of the phantom may cause a large range error. A method that combines tissue segmentation with the measured WET of the tissue substitute material is proposed to improve the range calculation accuracy of the TPS. The results show that the proposed method can improve the dose and range accuracy of the commercial TPS including RayStation for tissue substitute materials.

Objective:To propose a new robust optimization method, known as modified worst case method, was proposed, which can enable users to control the trade-off between nominal plan quality and plan robustness.Methods:In each iteration of the plan optimization process, the dose value of each voxel in nine scenarios, which corresponded to a nominal scenario and eight perturbed scenarios with range or set-up uncertainties, were calculated and the maximum of deviations of each scenario voxel dose from that of the nominal scenario was included as an additive robust optimization term in the objective function. A weighting factor p robust was used to this robust optimization term to balance the nominal plan quality and plan robustness. Results:The robust optimization methods were implemented and compared in an in-house developed robust optimization module. When p robust=0.8, compared with conventional optimization, the ΔD 95% of CTV was reduced from 9.8 Gy to 7.6 Gy. When p robust was reduced from 1 to 0, ΔD 95% was increased from 7.0 Gy to 9.8 Gy, whereas the D 95% and D max of CTV, and the D 5% and D max of organs at risk (OAR) in the nominal scenario were reduced. Conclusions:The proposed modified worst case method can effectively improve the robustness of the plan to the range and set-up uncertainties. Besides, the weighting factor p robust in this method can be adopted to control the trade-off between nominal plan quality and plan robustness.

OBJECTIVES: To observe the effect of type 2 diabetes mellitus (T2DM) on mandibular bone regeneration and the expression of factors related to T helper cell 17 (Th17 cell) and regulatory T cell (Treg cell) in mice. METHODS: Thirty-six 6-week-old C57BL/6J male mice were randomly divided into normal control (NC) and T2DM groups. Fasting blood glucose levels were detected 0 d, 7 d, 14 d, and 28 d after surgery for mandibular defects. Hematoxylin-eosin (HE) staining was used in observing the bone after 7 d, 14 d, and 28 d of the healing process. Immunohistochemical staining was used in observing the expression of alkaline phosphatase (ALP), Runt-related transcription factor 2 (RUNX2), forkhead box protein P3 (Foxp3), retinoic acid related orphan receptor gamma T (RORγt), and protein tyrosine phosphatase non-receptor type 2 (PTPN2) after 7 d, 14 d, and 28 d of healing. RESULTS: HE staining showed that the area with new bones in the T2DM group was significantly smaller than that in the NC group. Immunohistochemical staining showed that the expression of osteogenesis related proteins ALP and RUNX2 were significantly reduced in the T2DM group. In addition, the number of RORγt positive cells increased, whereas the number of Foxp3 positive cells and the expression PTPN2 decreased significantly in the mandibular bone defect in mice with T2DM. CONCLUSIONS T2DM significantly inhibit mandibular bone regeneration in mice. Decline in PTPN2 expression and the transition of Treg and Th17 may be the underlying molecular mechanisms.
Animals ; Bone Regeneration ; Diabetes Mellitus, Type 2 ; Forkhead Transcription Factors ; Male ; Mice ; Mice, Inbred C57BL ; TCF Transcription Factors ; Th17 Cells