基于自动勾画和快速蒙特卡罗计算的放射治疗全身器官剂量数据库平台的可行性研究

目的:探讨建立一种放射治疗全身器官剂量数据库平台的可行性。方法:使用基于深度学习的自动勾画软件DeepViewer?1例食管癌患者的全身CT上勾画全身器官，然后利用基于GPU加速的蒙特卡罗软件ARCHER计算相应的器官剂量分布，最后利用Lyman-Kutcher-Burman（LKB）模型评估放疗患者正常组织并发症概率（NTCP）。结果:针对该病例，成功建立基于DeepViewer?ARCHER和LKB模型的全身器官剂量数据库，发现距离靶区越近的器官剂量越大，其中心脏与靶区间距离最小，剂量为14.11 Gy，但因其模型参数特殊，通过LKB模型计算的NTCP为0.00%；左、右肺的剂量分别为3.19和1.16 Gy，但是NTCP值却很大，分别为2.13%和1.60%。对于距离靶区较远的头颈部器官（视交叉、视神经和眼）和腹部器官（直肠、膀胱和股骨头）剂量分别约为9和2 mGy，并且NTCP均近似为0.00%。结论:研究结果证明通过自动勾画软件DeepViewer?蒙特卡罗软件ARCHER和LKB模型建立全身器官剂量数据库的可行性。     

一种有效去除脂血对血清多种生化指标测定干扰的方法

目的 :探讨一种去除脂血对血清生化项目测定干扰的方法。方法 :沉淀、离心沉淀去除血清中过量的乳糜微粒。结果 :该法简便去脂效果彻底 ,不影响测定结果。结论 :获得了一种满意的去脂方法     

Detection of Atrial Fibrillation by Implanted Devices with Wireless Data Transmission Capability

Remote telemetry may facilitate the management of implantable devices. We tested the reliability of a new automatic, wireless home monitoring (HM) system that archives data every 24 hours. We retrospectively analyzed archival data from 276 consecutive pacing system implants to define temporal atrial fibrillation (AF) patterns and associated ventricular rate. An "AF day" was defined by a >20%/24 hour mode switch (MS) duration, irrespective of the MS number. Management decisions resulting from transmissions were noted. A pilot study confirmed that 89% of 22,356 transmissions were successful, of which >90% were received in <5 minutes. Data integrity was 100% preserved. Overall, AF developed in 29 patients (10.5%), representing a total of 645 AF days (mean = 22.2 ± 29.6 AF, median = 9 days), over 12 ± 2 months of monitoring. AF was infrequent (50% of 24 hours. Ventricular rates during 645 AF days in 29 patients averaged 95.1 ± 9.9 beats/min (median = 94 beats/min). Ventricular rates were >80 beats/min in 25 ± 30 AF days (median = 11 days). HM enabled rapid anticoagulation decisions. In recipients of implantable devices, automatic wireless telemetry with HM was efficient and reliable. Its application may overcome some current challenges in AF management by early notification and precise measurement of both AF burden and ventricular rate during AF.     

胃粘膜癌前病变的形态定量研究——胃粘膜核腺比值的定量分析

应用自动化图象分析仪对131个胃粘膜肠型病灶(单纯性肠化27个;异型增生:轻度30,中度35个,重度20个;肠型胃癌19个)进行定量分析。以单个腺管内细胞核总面积与细胞面积之比(ING)作为反映细胞核大小、数量及覆层排列程度的客观定量指标。结果发现:单纯性肠化(对照组)0.165±0.025,轻度异型增生0.21±0.023,中度异型增生0.259±0.026,重度异型增生0.32±0.028,分化型胃癌0.371±0.052,各组ING值呈正态,各组间的均值有非常显著的差异(P<0001)。因而,ING可作为胃粘膜癌前病变诊断的指标。     

Le traitement du signal en électromyographie: mise au point

Automatic analysis of electromyography (EMG) signals, first operated in 1950 with analogic machines, steeply expanded from 1980 when fast computers and worthwhile programs became available. On-line measurement of response area and latency, averaging of low amplitude waves, fast sorting of motor unit potential shape parameters, computation of the “jitter” between two muscle fibers, turns/amplitude and spectral analysis of interferential pattern records, are some examples of programs currently offered in modern EMG machines. Other techniques are still reserved for research purposes: scanning EMG, decomposition of nerve and muscle compound potentials, measurement of the threshold and firing rate of motor units, trace analysis using tracking models. Finally, the credit for artificial intelligence systems (knowledge based systems, fuzzy logic, neuronal networks) is still not clearly stated.     

1例安置埋藏式自动复律除颤器病人的随访

埋藏式自动复律除颤器(AICD)能降低恶性快速室性心律失常患者的猝死发生率,已经得到基本肯定,但其猝死率的降低,在相当程度上取决于能否对置入AICD患者进行认真随访,不断完善其治疗。本文报告1例随访16个月经验,并就随访结果,结合文献,略予讨论。     

Automatic Implantable Cardioverter Defibrillator/Permanent Pacemaker Interaction: Loss of Pacemaker Capture Following AICD Discharge

A 78-year-old man treated with amiodarone for recurrent ventricular tachycardia, had sequential placement of a bipolar VVI pacemaker and an automatic implantable cardioverter defibrillator (AICD). During defibrillation threshold testing, there was failure to capture of the pacer in the post-shock period. The time of failure to capture appeared energy-related: the greater the energy delivered, the longer the failure to capture. Careful attention will be necessary in constructing combined AICD/pacemaker units.     

Understanding capture detection.

Automatic capture detection systems are currently available in several cardiac pacing devices. All current systems use low-polarization electrodes and no beat to beat detection system is available for all types of electrodes. In addition the success ratio for currently available systems is not always 100%. Failure to detect capture reliably is often related to the behaviour of the electrode-tissue interface under different circumstances. Pacemaker electrodes can be considered electrochemical cells with complicated characteristics depending on time, temperature and electrical charge. This electrochemical cell is disturbed when a charge is transferred across the electrode-tissue interface during pacing. Several measures can be taken in order to minimise this disturbance or pace polarization artefact (PPA) including the use of high active surface area electrodes and application of tri-phasic pacing pulses. Another factor influencing detection of evoked potentials is the input circuit of the pacemaker affecting the PPA and the evoked response. Positive PPAs can be falsely interpreted as evoked potentials due to the undershoot of the second order filters applied in modern cardiac pacemakers. This paper explains the behaviour of the interface between the electrode and the cardiac tissue in combination with the pacemaker output circuits and input amplifiers under different circumstances.     

Automatic assessment of levodopa-induced dyskinesias in daily life by neural networks.

We developed an objective and automatic procedure to assess the severity of levodopa-induced dyskinesia (LID) in patients with Parkinson's disease during daily life activities. Thirteen patients were continuously monitored in a home-like situation for a period of approximately 2.5 hours. During this time period, the patients performed approximately 35 functional daily life activities. Behavior of the patients was measured using triaxial accelerometers, which were placed at six different positions on the body. A neural network was trained to assess the severity of LID using various variables of the accelerometer signals. Neural network scores were compared with the assessment by physicians, who evaluated the continuously videotaped behavior of the patients off-line. The neural network correctly classified dyskinesia or the absence of dyskinesia in 15-minute intervals in 93.7, 99.7, and 97.0% for the arm, trunk, and leg, respectively. In the few cases of misclassification, the rating by the neural network was in the class next to that indicated by the physicians using the AIMS score (scale 0-4). Analysis of the neural networks revealed several new variables, which are relevant for assessing the severity of LID. The results indicate that the neural network can accurately assess the severity of LID and could distinguish LID from voluntary movements in daily life situations.     

全自动可定量洗胃机的研制

本文介绍一种全自动可定量洗胃机的基本结构、工作原理及软件程序。该机具有设定洗胃液的进胃量，检测进出胃的液量，进出胃液量不平衡时报警，出胃过程堵塞时报警，洗胃液用尽时报警等功能。具有智能化程度高、安全可靠性好、使用方便等特性。