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1.
目的 使用磁共振扩散张量成像技术(DTI)研究视网膜色素变性(RP)患者的视神经改变及其与视野检查的相关性。方法 46例RP患者(RP组)和46例健康对照志愿者(对照组)进行了前瞻性研究。所有受试者进行3.0T MRI-DTI扫描检测,使用简化的小视野扩散张量成像(rFOV-DTI)序列推导出单个视神经的各向异性(FA)、平均弥散系数 (MD)、平行扩散系数(λ//)、垂直扩散系数(λ⊥),获得平均分数FA、平均扩散率和特征值图,用于定量分析。进一步分析视野平均偏差(MDVF)与患者的分数FA、平均扩散率、λ//及λ⊥的相关性。结果 RP组与对照组受试者间年龄和体质量等差异均无统计学意义(均为P>0.05),而两组之间最佳矫正视力和MDVF差异均具有统计学意义(均为P=0.000)。与对照组相比,RP组患者视神经FA降低,MD、λ//、λ⊥升高,两组之间差异有统计学意义(P<0.001)。RP组患者两侧视神经的FA、MD、λ//和λ⊥与MDVF行相关性分析,视神经FA及λ⊥与MDVF有显著相关性(右侧:r=-0.864、0.719,均为P<0.001;左侧:r=-0 .997、r=0.830,均为P<0.001);MD与MDVF不相关(右侧:r=-0.026,P=0.866;左侧:r=-0.115,P=0.445)。结论 rFOV-DTI测量值可用于RP患者视神经轴突和髓鞘病变的早期诊断。  相似文献   
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[摘要] 目的 探讨表观扩散系数(apparent diffusion coefficient, ADC)值与肝细胞癌(hepatocellular carcinoma, HCC)组织学分级的相关性以及不同直径肿瘤的ADC值与HCC的相关性。方法?回顾性分析2017年—2020年180例病理证实为HCC的病例资料,按肿瘤直径大小分为<2 cm、≥2 cm且<3 cm、≥3 cm且<5 cm、≥5 cm 4组,标为I、II、III、IV组。分析ADC值与HCC组织学分级的相关性,并分析在不同直径肿瘤ADC值与HCC的相关性。结果?高、中和低分化HCC的ADC值分别为(1.159±0.302)×10-3、(0.951±0.213)×10-3和(0.811±0.239)×10-3 mm2/s,逐级降低(P<0.05)。ADC值与总体HCC的组织学分级呈负相关(r=-0.474),与I~III组HCC的组织学分级均呈负相关(r值分别为-0.663、-0.527、-0.364),而与IV组HCC的组织学分级无相关性。结论?ADC值可以作为非侵入性预测HCC组织学分级的指标,预测结果受肿瘤大小影响,更适用于小肝细胞癌。  相似文献   
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《Clinical microbiology and infection》2022,28(9):1286.e1-1286.e8
ObjectiveAntibiotic susceptibility testing (AST) is necessary in order to adjust empirical antibiotic treatment, but the interpretation of results requires experience and knowledge. We have developed a machine learning software that is capable of reading AST images without any human intervention and that automatically interprets the AST, based on a database of antibiograms that have been clinically validated with European Committee on Antimicrobial Susceptibility Testing rules.MethodsWe built a database of antibiograms that were labelled by senior microbiologists for three species: Escherichia coli, Klebsiella pneumoniae, and Staphylococcus aureus. We then developed Antilogic, a Python software based on an original image segmentation module and supervised learning models that we trained against the database. Finally, we blind tested Antilogic against a validation set of 5100 photos of antibiograms.ResultsWe trained Antilogic against a database of 18072 pictures of antibiograms. Overall agreement against the validation set reached 97% (16 855/17 281) regarding phenotypes. The severity rate of errors was also evaluated: 1.66% (287/17 281) were major errors and 0.80% (136/17 281) were very major errors. After implementation of uncertainty quantifications, the rate of errors decreased to 0.80% (114/13 451) and 0.42% (51/13 451) for major and very major errors respectively.DiscussionAntilogic is the first machine learning software that has been developed for AST interpretation. It is based on a novel approach that differs from the typical diameter measurement and expert system approach. Antilogic is a proof of concept that artificial intelligence can contribute to faster and easier diagnostic methods in the field of clinical microbiology.  相似文献   
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Catheter ablation is currently the only curative treatment for scar-related ventricular tachycardias (VTs). However, not only are ablation procedures long, with relatively high risk, but success rates are punitively low, with frequent VT recurrence. Personalized in-silico approaches have the opportunity to address these limitations. However, state-of-the-art reaction diffusion (R-D) simulations of VT induction and subsequent circuits used for in-silico ablation target identification require long execution times, along with vast computational resources, which are incompatible with the clinical workflow. Here, we present the Virtual Induction and Treatment of Arrhythmias (VITA), a novel, rapid and fully automated computational approach that uses reaction-Eikonal methodology to induce VT and identify subsequent ablation targets. The rationale for VITA is based on finding isosurfaces associated with an activation wavefront that splits in the ventricles due to the presence of an isolated isthmus of conduction within the scar; once identified, each isthmus may be assessed for their vulnerability to sustain a reentrant circuit, and the corresponding exit site automatically identified for potential ablation targeting. VITA was tested on a virtual cohort of 7 post-infarcted porcine hearts and the results compared to R-D simulations. Using only a standard desktop machine, VITA could detect all scar-related VTs, simulating activation time maps and ECGs (for clinical comparison) as well as computing ablation targets in 48 minutes. The comparable VTs probed by the R-D simulations took 68.5 hours on 256 cores of high-performance computing infrastructure. The set of lesions computed by VITA was shown to render the ventricular model VT-free. VITA could be used in near real-time as a complementary modality aiding in clinical decision-making in the treatment of post-infarction VTs.  相似文献   
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视觉通路包括视神经、视交叉、视束、视放射及视皮质。常规磁共振检查技术难以发现视路损伤后白质纤维微结构改变,眼科学检查也存在一定的局限性及主观性,且不能探测后视路的变化。弥散张量成像(diffusion tensor imaging,DTI)作为一种新兴的磁共振成像技术,通过各种后处理分析方法结合不同的参数进行分析,可提供组织的微结构信息,并能够直观显示活体白质纤维束,在无创地探索疾病的神经病理机制、评估预后方面起着重要的作用。近年来随着DTI后处理方法的不断创新,其在视路损伤中的研究越来越多。本文在介绍DTI的主要参数及常见脑白质微结构分析方法的同时,阐述了其在视路损伤研究中的应用,并进一步对各种分析方法的优缺点进行总结。  相似文献   
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BackgroundPatients with single-ventricle physiology have a significant risk of cardiorespiratory deterioration between their first and second stage palliation surgeries.ObjectivesThe objective of this study is to develop and validate a real-time computer algorithm that can automatically recognize physiological precursors of cardiorespiratory deterioration in children with single-ventricle physiology during their interstage hospitalization.MethodsA retrospective study was conducted from prospectively collected physiological data of subjects with single-ventricle physiology. Deterioration events were defined as a cardiac arrest requiring cardiopulmonary resuscitation or an unplanned intubation. Physiological metrics were derived from the electrocardiogram (heart rate, heart rate variability, ST-segment elevation, and ST-segment variability) and the photoplethysmogram (peripheral oxygen saturation and pleth variability index). A logistic regression model was trained to separate the physiological dynamics of the pre-deterioration phase from all other data generated by study subjects. Data were split 50/50 into model training and validation sets to enable independent model validation.ResultsOur cohort consisted of 238 subjects admitted to the cardiac intensive care unit and stepdown units of Texas Children’s Hospital over a period of 6 years. Approximately 300,000 h of high-resolution physiological waveform and vital sign data were collected using the Sickbay software platform (Medical Informatics Corp., Houston, Texas). A total of 112 cardiorespiratory deterioration events were observed. Seventy-two of the subjects experienced at least 1 deterioration event. The risk index metric generated by our optimized algorithm was found to be both sensitive and specific for detecting impending events 1 to 2 h in advance of overt extremis (receiver-operating characteristic curve area: 0.958; 95% confidence interval: 0.950 to 0.965).ConclusionsOur algorithm can provide 1 to 2 h of advanced warning for 62% of all cardiorespiratory deterioration events in children with single-ventricle physiology during their interstage period, with only 1 alarm being generated at the bedside per patient per day.  相似文献   
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This paper presents results on tribological characteristics for polymer blends made of polybutylene terephthalate (PBT) and polytetrafluoroethylene (PTFE). This blend is relatively new in research as PBT has restricted processability because of its processing temperature near the degradation one. Tests were done block-on-ring tribotester, in dry regime, the variables being the PTFE concentration (0%, 5%, 10% and 15% wt) and the sliding regime parameters (load: 1, 2.5 and 5 N, the sliding speed: 0.25, 0.5 and 0.75 m/s, and the sliding distance: 2500, 5000 and 7500 m). Results are encouraging as PBT as neat polymer has very good tribological characteristics in terms of friction coefficient and wear rate. SEM investigation reveals a quite uniform dispersion of PTFE drops in the PBT matrix. Either considered a composite or a blend, the mixture PBT + 15% PTFE exhibits a very good tribological behavior, the resulting material gathering both stable and low friction coefficient and a linear wear rate lower than each component when tested under the same conditions.  相似文献   
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