The Prognostic Role of Peritumoral Edema in Patients with Newly Diagnosed Glioblastoma: A Retrospective Analysis

ObjectivePrevious studies on glioblastomas (GBMs) have not reached a consensus on peritumoral edema (PTE)’s influence on survival. This study evaluated the PTE index’s prognostic role in newly diagnosed GBMs using a well-designed method.MethodsSelected patients were reviewed after a rigorous screening process. Their general information was obtained from electronic medical records. The imaging metrics (MTD, TTM, TTE) representing tumor diameter, laterality, and PTE extent were obtained by manual measurement in Syngo FastView software. The PTE index was a ratio of TTE to MTD. Multiple variables were evaluated using analysis of variance and Cox regression model.ResultsOf 143 patients, 62 were included in this study. MGMT promoter methylation and tumor laterality were both independent prognostic factors (p = 0.020, 0.042; HR = 0.272, 2.630). The lateral tumors’ index was higher than that of the medial tumors (57.7% vs. 42.6%, p = 0.027). Low-index tumors were located in relatively medial positions compared with high-index tumors (TTM, 4.9 vs. 12.8, p = 0.032). This finding indicated that the PTE index tended to increase with tumor laterality. Moreover, the patients with low-index tumors had a significant survival disadvantage in the univariate analysis but not in the multivariate analysis (p = 0.023, 0.220). However, further analysis found that the combination of tumor laterality and PTE statistically stratified the survival outcome. The patients with lateral high-index tumors survived significantly longer (p = 0.022, HR = 1.927).ConclusionsIn contrast with the previous studies, this study recommends combining PTE and tumor laterality for survival stratification in newly diagnosed GBMs.     

腹腔镜微创治疗高龄完全性直肠脱垂

目的探讨腹腔镜微创治疗高龄完全性直肠脱垂的手术方法,总结手术操作体会及临床治疗经验。方法总结2012年6月~2017年6月收治的22例完全性直肠脱垂患者的临床资料,患者年龄67~79岁,均在腹腔镜下行悬吊固定。结肠造影和术中均可见明显增厚且冗长的乙状结肠,直肠周围组织宽松,膀胱直肠窝或子宫直肠窝之间脂肪结缔组织明显增厚,尤其是直肠前壁。术中切除直肠周围增厚的脂肪结缔组织,切除冗长的乙状结肠和直肠上端,行结肠直肠吻合。结果所有患者手术顺利,无中转开腹。手术时间平均(86.59±14.84)min,出血量平均(63.41±23.67)ml,术后住院时间平均(10.01±1.57)d。无吻合口出血、感染、肠瘘等并发症发生,无术中死亡或术后2周内死亡病例。22患者均获得临床治愈,随访2~4年,平均(2.81±0.91)年,患者排便次数1~2次/d,肛门功能正常,无复发。结论腹腔镜下微创切除直肠周围增厚的结缔组织、切除冗长的乙状结肠和直肠上端,是一种较好的微创治疗高龄直肠脱垂的方法。     

Smo、Gli2及FoxM1对神经胶质瘤诊断和预后的评估价值

目的探讨Smo、胶质瘤相关癌基因同源蛋白2(Gli2)及叉头框转录因子M1(FoxM1)对神经胶质瘤诊断和预后的评估价值。 方法取80例神经胶质瘤标本为神经胶质瘤组,60例正常脑组织标本为正常组。免疫组化法检测两组Smo、Gli2、FoxM1表达水平,分析其与神经胶质瘤患者临床病理特征的关系;Kaplan-Meier生存曲线分析不同Smo、Gli2、FoxM1表达水平神经胶质瘤患者预后的差异,分析影响神经胶质瘤预后的相关因素。 结果神经胶质瘤组织Smo、Gli2、FoxM1高表达率均高于正常脑组织,且随神经胶质瘤患者组织学分级升高而表达率增高(P＜0.05)。不同组织学分级、不同Smo、Gli2、FoxM1表达水平的神经胶质瘤患者5年生存率存在显著差异(P＜0.05)。组织学Ⅲ~Ⅳ级、Smo高表达、Gli2高表达、FoxM1高表达是神经胶质瘤预后的危险因素(P＜0.05)。 结论Smo、Gli2、FoxM1高表达是神经胶质瘤预后的危险因素,三者有望作为神经胶质瘤诊断和预后的判断指标。     

甲状腺机能亢进症危险因素病例对照研究

目的 探讨各危险因素与甲亢的关系。方法 对三亚地区110例甲亢采用1：2配比的病例对照研究,资料处理采用条件Logistic回归分析.结果 甲亢发病与下列5因素关系密切：家庭年收入(OR=2．055)、食用碘盐(OR=2．133)、喜食海产品(OR=2．183)、感染(OR=2．382)、家庭生活事件(OR=3．017) 结论 家庭生活事件、感染、喜食海产品、食用碘盐、家庭年收入增高等是甲亢的危险因素。     

血液净化法抢救重症中毒临床疗效

血液灌注是血液净化方法之一，也是目前抢救重症毒物药物中毒病人的一种安全有效的方法，海南省农垦三亚医院血液净化中心采用以血液灌注为主的血液净化法抢救重症毒物药物中毒病人已取得一定疗效，现对2001—2006年收治病人62例，进行分析，现总结如下。     

深刺局部穴治疗三叉神经痛疗效观察

目的:寻找提高三叉神经痛疗效的有效方法.方法:将90例原发性三叉神经痛患者随机分为深刺组(45例)、常规针刺组(45例).常规针刺组以局部近取浅刺和循经远取手足阳明经穴位为主,深刺组在此基础上对局部穴位采用深刺达神经干的方法.治疗3个疗程后统计疗效.结果:两组均收到明显疗效,深刺组临床治愈12例,显效24例,好转7例,无效2例,有效率为95.6%;而常规针刺组分别为7例、15例、12例、11例、75.6%.深刺组疗效优于常规针刺组(P＜0.05).结论:针刺治疗三叉神经痛,局部穴位深刺加循经远取手足阳明经穴位,能明显提高疗效.     

Dravet综合征患儿致病基因定位及GEFS+基因突变检测

目的分析海南地区Dravet综合征患儿的遗传特征。方法收集2015—2017年期间海南省18例Dravet综合征患儿及家系成员的外周血,采用PCR扩增及Sanger测序法进行SCN1A基因检测,运用连锁分析应用软件GenomeStudio进行致病基因定位分型与连锁分析;对Sanger测序法未发现SCN1A基因突变的患儿,采用多重连接依赖的探针扩增(MLPA)方法分析SCN1A基因片段缺失或重复,并筛查父母SCN1A基因,分析其突变来源。结果 18例Dravet综合征患儿及父母基因定位扫描结果完全符合亲子间的孟德尔遗传关系。SCN1A基因突变患儿可定位到5号、9号、22号染色体3个候选突变区域。其中5号染色体区域位于SNPRs 4957954至Rs 728937,在Rs 1459085处可获取到最大LOD值2. 13;9号染色体区域位于SNPRs 720974至Rs 1220087,在Rs 71332677处可获取到最大LOD值1. 92;22号染色体区域位于SNPRs 756658至Rs 713751,在Rs 374225处可获取到最大LOD值1. 91。18例患儿中,12例SCN1A基因突变,其中6例CDS区域的第5383位碱基呈现杂合变异(G→A),4例13号外显子和CDS区域的第2292位碱基纯合变异(T→C),2例SCN1A基因非编码区域碱基纯合变异(A→T)。结论海南Dravet综合征患儿的基因定位完全符合孟德尔遗传关系,推测Rs4957954至Rs728937、Rs720974至Rs1220087、及Rs756658至Rs713751区域是Dravet综合征的可能致病性区域。     

Releasing of The White Paper on Medical Imaging Artificial Intelligence in China

In the afternoon of March 26,2019, The White Paper on Medical Imaging Artificial Intelligence in China was officially released in Beijing by the Chinese Innovative Alliance of Industry, Education, Research and Application of Artificial Intelligence for Medical Imaging (CAIERA). The white paper was co-operatively written by the medical imaging experts from the tertiary Chinese hospitals, the scientific experts from AI research institutions and the leading AI medical enterprises in China. The contents of the white paper not only cover the up-to-date application of AI in medical field, the latest advances of AI algorithms in medical image processing, the data requirement for medical AI development, and the current situation of structured data, but also expatiate the goal and challenge of clinical application for medical imaging AI development in 16 medical subject areas, which helps to identify the demands and opportunities for the AI industry. Forty representative enterprises of AI medical imaging in China were introduced in the white paper. The white paper points out the three key problems in development of AI products: the robustness, ease of usage and data security, which provides guidance of direction and strategy for the enterprises. Particularly, in view of the national policy on developing AI, the white paper gives a profound analysis on the challenges and the opportunities that medical imaging AI is facing. These contents agglomerate the cutting-edge efforts of experts in the industry-academia-research-application chain of medical AI, represent the mainstream voice of the society in China. The White Paper will play a guiding role in understanding the market demands and establishing standardized systems in the path of landing AI products in the field medical imaging. Full text of the White paper is publicly accessible from the CAIERA website, or by scanning the 2D code in the article.