正常肺组织大分割照射全肺平均耐受剂量与生物学效应研究

目的 建立正常组织分次照射基于肺纤维化影像学改变的全肺平均剂量-效应模型,定量分析分割照射相比单次照射的生物学效应及耐受剂量关系。方法 采用8~10周龄C57BL6雌性小鼠按随机数表法分组进行X射线全肺野照射,分别给予梯度剂量0、2.0 Gy×5次、4.0 Gy×5次、6.0 Gy×5次、7.0 Gy×5次、8.5 Gy×5次。照射后24周行CT扫描成像,CT图像三维重建后经三维分割算法获得肺部平均密度与肺部体积值,并分别据此进行Boltzmann模型放射生物学建模。结果 照射后24周CT图像三维重建冠状位图像提示剂量依赖的肺部影像学改变。同一时间点肺组织全基因组芯片与组织病理学研究均提示与影像学改变高度吻合。经放射生物学建模,分次照射诱导肺密度改变的全肺平均剂量（D_mean）中位剂量为（30.80±0.80）Gy（校正R²=0.97）;引起肺体积减小的中位剂量为（31.31±7.07）Gy（校正R²=0.92）。基于影像学参数的剂量-效应曲线提示,肺组织对分次照射的耐受性相比单次照射显著提高。结论 纤维化进展过程中,肺密度与肺体积改变对X射线的依赖性不仅取决于总剂量大小,也与分割次数、分次剂量存在一定关联。     

无创吸入式麻醉精准肺野照射装置在小鼠肺损伤研究中的应用

目的 探索小鼠放射性肺损伤模型中大批量、快速、低成本实现全肺野精准照射的有效方法,普及这一重要放射生物学模型在多领域的应用。方法 采用8~10周龄C57BL6雌性小鼠,使用micro-CT三维重建图像进行肺部解剖学参数测量并确定放射野范围（n=12）。结合标准化胸腔暴露及固定、无创通气麻醉等手段建立"一体化"麻醉、固定、定位装置,借助常规医用直线加速器完成批量小鼠精准肺野照射。结果 小鼠CT图像三维重建后在冠状位与矢狀位图像上确定肺结构的解剖位置与尺寸平均值。并进一步根据小鼠呼吸频率及幅度确定受呼吸频率影响的肺野上界、中线和下界,并将测量值标记于专门设计的肺野照射装置用来指导实际操作。本装置大致可分为小鼠固定架和麻醉通气系统两部分构成。固定架用以安置每排10只小鼠用弹力栓妥善固定暴露胸腔。照射中通过麻醉面罩全程给予异氟烷混合气体,确保实验过程中小鼠处于深度麻醉以及均匀呼吸动度。结论 本研究设计的集麻醉、固定、定位为一体的"弹匣式"小鼠肺野照射装置,可显著增加胸部放射实验的准确性、简易性、安全性、稳定性和高效性。大幅减低实验成本和对高端辐照设备的依赖,具有一定的实际应用及推广价值。     

Optimal needle design for minimal insertion force and bevel length

This research presents a methodology for optimal design of the needle geometry to minimize the insertion force and bevel length based on mathematical models of cutting edge inclination and rake angles and the insertion force. In brachytherapy, the needle with lower insertion force typically is easier for guidance and has less deflection. In this study, the needle with lancet point (denoted as lancet needle) is applied to demonstrate the model-based optimization for needle design. Mathematical models to calculate the bevel length and inclination and rake angles for lancet needle are presented. A needle insertion force model is developed to predict the insertion force for lancet needle. The genetic algorithm is utilized to optimize the needle geometry for two cases. One is to minimize the needle insertion force. Using the geometry of a commercial lancet needle as the baseline, the optimized needle has 11% lower insertion force with the same bevel length. The other case is to minimize the bevel length under the same needle insertion force. The optimized design can reduce the bevel length by 46%. Both optimized needle designs were validated experimentally in ex vivo porcine liver needle insertion tests and demonstrated the methodology of the model-based optimal needle design.     

A model to predict deflection of bevel-tipped active needle advancing in soft tissue

Active needles are recently being developed to improve steerability and placement accuracy for various medical applications. These active needles can bend during insertion by actuators attached to their bodies. The bending of active needles enables them to be steered away from the critical organs on the way to target and accurately reach target locations previously unachievable with conventional rigid needles. These active needles combined with an asymmetric bevel-tip can further improve their steerability. To optimize the design and to develop accurate path planning and control algorithms, there is a need to develop a tissue–needle interaction model. This work presents an energy-based model that predicts needle deflection of active bevel-tipped needles when inserted into the tissue. This current model was based on an existing energy-based model for bevel-tipped needles, to which work of actuation was included in calculating the system energy. The developed model was validated with needle insertion experiments with a phantom material. The model predicts needle deflection reasonably for higher diameter needles (11.6% error), whereas largest error was observed for the smallest needle diameter (24.7% error).     

Semi-supervised medical image segmentation via a tripled-uncertainty guided mean teacher model with contrastive learning

Due to the difficulty in accessing a large amount of labeled data, semi-supervised learning is becoming an attractive solution in medical image segmentation. To make use of unlabeled data, current popular semi-supervised methods (e.g., temporal ensembling, mean teacher) mainly impose data-level and model-level consistency on unlabeled data. In this paper, we argue that in addition to these strategies, we could further utilize auxiliary tasks and consider task-level consistency to better excavate effective representations from unlabeled data for segmentation. Specifically, we introduce two auxiliary tasks, i.e., a foreground and background reconstruction task for capturing semantic information and a signed distance field (SDF) prediction task for imposing shape constraint, and explore the mutual promotion effect between the two auxiliary and the segmentation tasks based on mean teacher architecture. Moreover, to handle the potential bias of the teacher model caused by annotation scarcity, we develop a tripled-uncertainty guided framework to encourage the three tasks in the student model to learn more reliable knowledge from the teacher. When calculating uncertainty, we propose an uncertainty weighted integration (UWI) strategy for yielding the segmentation predictions of the teacher. In addition, following the advance of unsupervised learning in leveraging the unlabeled data, we also incorporate a contrastive learning based constraint to help the encoders extract more distinct representations to promote the medical image segmentation performance. Extensive experiments on the public 2017 ACDC dataset and the PROMISE12 dataset have demonstrated the effectiveness of our method.     

The Hepatorenal Toxicity and Tumor Response of Chemotherapy With or Without Aidi Injection in Advanced Lung Cancer: A Meta-Analysis of 80 Randomized Controlled Trials

PurposeChemotherapy-induced hepatorenal toxicity often decreases tolerance for further therapies and results in poor quality of life and prognosis for patients with lung cancer. In this meta-analysis, all related studies were systematically re-evaluated to determine whether Aidi injection relieves hepatorenal toxicity and improves tumor response, and to determine its threshold and the optimal treatment regimen for obtaining the desired responses.MethodsAll studies regarding Aidi injection with chemotherapy were gathered from Chinese and English databases (from inception until January 2019). Their bias risk was evaluated and the data were synthesized using meta-analysis; the quality of evidence of all outcomes was rated by using the Grades of Recommendation Assessment, Development, and Evaluation approach.FindingsEighty randomized controlled trials containing 6279 patients were included in the study. Most of the trials showed unclear risk of bias. Aidi injection with chemotherapy increased the objective response rate (risk ratio [RR], 1.32; 95% CI, 1.25–1.40) and the disease control rate (RR, 1.15; 95% CI, 1.12–1.17) and resulted in a lower incidence of hepatotoxicity (RR, 0.61; 95% CI, 0.55–0.69) and nephrotoxicity (RR, 0.62; 95% CI, 0.53–0.72) than that of chemotherapy alone. Subgroup analyses showed that treatment with 50 mL per time, 10 to 14 days per cycle, and 2 to 3 cycles of Aidi injection with chemotherapy resulted in a low incidence of hepatorenal toxicity. All of the results were robust, and their quality was moderate.ImplicationsThe moderate evidence indicates that Aidi injection with chemotherapy may improve tumor response and result in a low incidence of hepatorenal toxicity in patients with lung cancer. Aidi injection may relieve hepatorenal toxicity and exhibit an important protective effect against chemotherapy-induced hepatorenal toxicity. Based on the subgroup analysis results, Aidi injection seems to lower the threshold for chemotherapy. Treatment with 50 mL per time, 10 to 14 days per cycle, and 2 to 3 cycles may be the optimal usage for attaining a decrease in hepatorenal toxicity.     

Longitudinal Trends of AMS and IIEF-5 Scores in Randomly-Selected Community Men 40 to 80 Years Old: Preliminary Results

IntroductionMost of conclusions on the relationship between age and reproductive health in aging men relied on cross-sectional data.AimTo better characterize the natural degradation trajectory of reproductive health of aging men based on longitudinal data.MethodsA community cohort study was performed in randomly selected men 40 to 80 years old, initiated in 2012 and followed up in 2014 and 2016. Participants were investigated by face-to-face structured interview, including demographic information and International Index of Erectile Function (IIEF-5) and Aging Males’ Symptoms (AMS) scales.Main Outcome MeasuresThe differences among the 3 assessments of IIEF-5 and AMS were analyzed, and progression trajectories were traced.ResultsThe high degree of variability on AMS and IIEF-5 was evident across individual subjects, as was the variability within individuals. The average IIEF-5 score of 248 subjects decreased from 16.9 to 14.1 during the 4 years, and the total AMS score increased from 22.6–27.0 (P < .001). Longitudinal data, both of individuals and of groups, showed the more rapid increase or decrease on AMS or IIEF-5 scores over 4 years in the 61–70 age group than in other age groups.Clinical ImplicationThe evidence of the greatest changes on AMS and IIEF-5 scores in the 61–70 age group prompts the importance of early intervention to postpone the degradation of reproductive health.Strength & LimitationsCompared with cross-sectional data, longitudinal data can provide a more natural progression trajectory of reproductive health of aging male individuals. The low follow-up rate might affect the parameter estimation to some extent.ConclusionCohort data over 4 years’ follow-up showed more abrupt changes on AMS and IIEF-5 scores in the 61–70 age group than in other age groups.Zheng J-B, Liang Q-F, Li J-H, et al. Longitudinal Trends of AMS and IIEF-5 Scores in Randomly-Selected Community Men 40 to 80 Years Old: Preliminary Results. J Sex Med 2019;16:1567–1573.     

Climate change transformation: A definition and typology to guide decision making in urban environments

Climate change presents a threat to the sustainability of cities and their societies, and must be adequately addressed. Urban environments (cities) are responsible for the creation of a significant amount of greenhouse gas emissions which are the source of climate change. Cities have been increasingly the focus of action to address climate change, yet emissions are not significantly reducing. Additionally, there a lack of integration between adaptation and mitigation. This prevents responses adequate to limit global warming to 1.5^OC, and to be well adapted to anticipated changes. This paper critically analyses existing definitions and typologies of climate change actions. A definition of ‘climate change transformation’ is proposed which includes the integration of adaptation and mitigation goals to enable a new regime in which global warming is limited to 1.5^OC. A new three-part typology: ‘coping, malaction and transformation,’ is presented for categorising climate change actions by the extent to which they integrate adaptation and mitigation, and define a new regime. The typology is accompanied by illustrations to demonstrate the relationship between adaptation and mitigation. The definition, typology and illustration serve to guide effective climate change decision making, and provides principles to guide application in urban environments.     

Prognostic value of receptor tyrosine kinase-like orphan receptor (ROR) family in cancer: A meta-analysis

IntroductionIdentification of membrane proteins expressed exclusively on tumor cells is a goal for cancer drug development. The receptor tyrosine kinase-like orphan receptor type 1 and 2 (ROR1/2), are type-I transmembrane proteins expressed in cancer but not in adult normal tissue. Here, we explore the prognostic role ROR1/2 expression on patient outcome.MethodsA systematic search of electronic databases identified publications exploring the effect of ROR1/2 on overall survival (OS). Hazard ratios (HR) from collected data were pooled in a meta-analysis using generic inverse-variance and random effects modeling. Subgroup analyses were conducted based on disease site or tumor type.ResultsTwenty five studies met the inclusion criteria. ROR1 was associated with worse overall survival (HR 2.13, 95% confidence interval (CI) 1.62–2.80; P < 0.001) with subgroup analysis showing the strongest association between ROR1 and OS was in lung cancer. There was no significant difference between solid tumors and hematological malignancies (HR 2.15, 95% CI 1.52–3.06 vs. HR 2.02, 95% CI 1.46–2.84; subgroup difference P = 0.80). ROR2 was also associated with worse OS (HR 1.84, 95% CI 1.43–2.38; P < 0.001). There was no significant difference between disease sites although the highest association seen was in head and neck cancers (HR 3.19, 95% CI 1.13–8.97) and the lowest in gynecological cancers (HR 1.19, 95% CI 0.71–2.00; subgroup difference P = 0.10).ConclusionsROR1 and ROR2 expression is associated with adverse outcome in several tumors. ROR1/2 warrants study as a target for developmental therapeutics.