基于时域后向投影的光声谱成像系统研究

光声谱成像是一种新的生物组织成像方法,它结合光学成像和超声成像的特点,可提供高分辨率和对比度的图像。采用波长532nm、重复频率10Hz的脉冲激光作为激励源,宽带PVDF非聚焦超声探测器频率响应范围为200kHz～15MHz,探测器以圆周扫描的方式采集样品的时域光声信号,并采用时域后向投影算法重建样品内部的二维光学吸收分布图像。实验表明,系统成像的空间分辨率小于1mm,重建的图像与原始样品完全吻合。     

基于焦区积分的高分辨率光声变焦显微成像

光声显微成像兼具高光学组织对比度,以及超声的高穿透深度和高空间分辨率的优点。但一方面在光声显微成像中,组织深层目标易被浅表目标屏蔽,另一方面其横向分辨率与焦深的矛盾一直限制了光声显微的成像质量。针对这两个问题,本实验搭建了一套基于超声分辨的光声显微成像系统。其采用一种非共轴的照明-探测方式来减少浅层组织对深层信息的影响,并且采用一种新的焦区积分算法来进行数据的处理,结合多次纵向变焦扫描来实现深层组织的高分辨探测。仿体实验表明,该方法可以在不同纵向深度上保持约0.6 mm的横向分辨率,与理论值相接近。裸鼠肿瘤成像结果表明,本文所提出的方法可以比普通的背向探测声聚焦光声显微成像方法在深度方向上获取更多的信息。随着超快脉冲激光和高速扫描方式的发展,本文所提出的方法有望在脑部血管成像、宫颈癌内窥成像、浅表肿瘤成像等方面得到较好的应用。     

基于滤波反投影算法的血管内光声图像重建

将目前在光声断层（PAT）成像中得到广泛应用的滤波反投影（FBP）重建算法应用到血管内光声（IVPA）成像中,提出一种简单快速的二维图像重建方法。首先,对组织产生的光声信号进行滤波、逆卷积和时域一阶求导的预处理;然后,针对IVPA在血管腔内封闭成像的特殊性,采用权重法将预处理后的光声信号数据对导管以外的成像区域沿弧线进行反投影,得到成像平面内每个网格点处的初始光声压。最后,得到反映血管壁组织结构形态的横截面灰阶图像。对仿真血管模型的实验表明,采用所提出的方法重建IVPA图像的结构,相似性指标（SSIM）可达到 0.571 7。合理选择滤波函数、滤波截止频率以及测量位置数,可以提高IVPA重建图像的质量;对光声信号进行时域一阶求导处理,能有效地突出重建图像中的组织结构信息。该方法为后续图像重建算法的优化奠定基础。     

血管内光声成像的研究进展

血管内光声（IVPA）成像是近年来发展起来的一种微创血管内成像技术,结合了光声信号激发阶段光吸收较高的对比度和光声信号发射阶段超声检测较高的分辨率,根据斑块成分对光的吸收差异检测和区分动脉粥样硬化斑块,可对斑块的形态和成分做更为全面的了解。介绍IVPA成像系统的研究现状、血管内超声(IVUS)/IVPA组合成像导管的设计与改进,以及在光谱成像、热成像、分子成像和对冠状动脉支架成像方面的应用现状,指出目前存在的问题,并对未来的研究进行展望。     

基于时域光声信号的谱分析技术及其在生物医学领域的应用

基于时域光声信号的谱分析技术是一种能够提供生物组织结构和功能信息的非侵入式检测技术,其结合了光学模态的高对比度和超声模态在深层组织中的高分辨率两重特性,可对不同波长光激发下的目标生物组织的光声信号数据集进行处理分析。相较于传统光谱检测,该技术不易受被测对象形状、形态的限制和光散射的影响,使其对较深层组织的检测仍具有较高灵敏度。相较于光声成像,该技术无需引入图像重建算法且专注于实现定量分析。综述时域光声信号的谱分析技术在生物组织、生物体液、生物呼出气体检测中的应用,介绍相关研究所采用的改进实验系统或不同信号处理方法,阐述该技术的研究进展与发展方向。     

光声技术在癌症检测和非侵犯性诊断中的应用（英文）

目的：探讨光声技术的原理、优势及癌症临床应用前景。方法：根据肿瘤发展过程,相继介绍光声技术在肿瘤检测过程中的应用。结果：光声技术对光散射生物组织-肿瘤,能够进行无损深层探测及成像,具有其他成像技术所无法比拟的优势。结论：光声技术是一种新的发展中的成像模式,应用于生物医药并获得解剖和功能信息。它对于了解肿瘤生长、转移,癌症诊断和评测治疗功效都有着潜在的重大用途。     

时域光声谱法在生物医学领域中的应用及进展

基于光声效应的时域光声光谱法将光学与声学有效结合起来，部分克服了组织的强散射性对测量结果的影响，具有灵敏度高、分辨力高等优点，广泛应用于生物医学领域。文中综合论述了时域光声谱法测量原理、关键技术，应用及将来时域光声谱法研究的发展方向，以进一步推动理论及应用研究的工作。     

正常及挫伤脊髓血管的三维直视化:同步辐射相衬成像

背景:同步辐射相位衬度成像凭借硬X射线光源的高准直、高相干等特性,其能大幅度提高对软骨细胞及微血管的空间分辨能力。目的:利用高空间分辨率同步辐射相衬成像技术观察大鼠正常及急性损伤脊髓的微血管的形态变化。方法:雄性SD大鼠分为2组:实验组以改良ALLEN’s打击法制作大鼠急性脊髓挫伤模型;伪手术组大鼠只行椎板减压术,不打击脊髓作为正常对照。术后第1天取正常及伤段脊髓标本经甲醛-水杨酸甲酯序贯处理48 h,标本于上海光源BL13W1硬X射线站进行扫描和成像。采集数据以利用VG Studio Max 2.1软件包进行3D图形重建及血管量化分析。结果与结论:相位衬度成像以特有的血管边缘增强效应直观呈现脊髓微血管形态,其结合CT技术(相衬断层成像)从三维视角对脊髓微血管进行直观成像,急性脊髓挫伤后神经组织的破坏伴随着严重的血管结构的损毁,组织损伤及血供的缺失在髓内由中央区向头、尾两侧呈梭性蔓延。三维血管量化数据显示脊髓挫伤后微血管数目及血管灌注容积急剧减少(P0.01)。结果表明无需血管造影的条件下,相衬断层成像可作为一种新的有潜力的超高分辨率可视化技术用于脊髓微血管3D结构成像及量化分析。     

生物磁光声联合成像的研究现状

超声(US)成像、光学相干断层(OCT)成像和磁共振成像(MRI)是临床常用的医学成像手段。此外,光声层析(PAT)和磁声(MA)成像是近年来新兴的多物理场耦合功能成像手段。将两种或者两种以上的成像手段结合起来形成多模态联合成像,可以使各成像模态的优点得到充分展现,对目标进行高精度和高分辨率的成像,精确识别病变组织,并对其功能成分进行定性和定量的分析。对US-PAT、US-OCT、PAT-OCT、US-PAT-OCT、磁光以及磁光声(MPA)联合成像,特别是对血管内联合成像的研究进展和临床应用前景进行综述,总结目前存在的问题,并展望未来可能的发展方向。     

生物感应式磁声成像的研究现状

生物感应式磁声(MAT-MI)成像是一种新型功能成像技术,融合电磁技术、超声技术和多物理场探测与成像技术,具有电阻抗成像的高对比度以及超声扫描成像的高空间分辨率的特点,能够反映生物组织的电导率变化信息,达到对病变组织进行早期诊断的目的。将MAT-MI与内窥检测技术相结合,则可直接检测生物腔体组织(如鼻腔、消化道以及血管等)病变的情况,为腔体组织疾病的诊断和治疗提供更及时可靠的依据。在分析MAT-MI的成像原理的基础上,对其正/逆问题的研究现状进行综述,并探讨内窥感应式磁声成像的可行性以及所面临的技术难点。     

Fast photoacoustic imaging system based on 320-element linear transducer array

A fast photoacoustic (PA) imaging system, based on a 320-transducer linear array, was developed and tested on a tissue phantom. To reconstruct a test tomographic image, 64 time-domain PA signals were acquired from a tissue phantom with embedded light-absorption targets. A signal acquisition was accomplished by utilizing 11 phase-controlled sub-arrays, each consisting of four transducers. The results show that the system can rapidly map the optical absorption of a tissue phantom and effectively detect the embedded light-absorbing target. By utilizing the multi-element linear transducer array and phase-controlled imaging algorithm, we thus can acquire PA tomography more efficiently, compared to other existing technology and algorithms. The methodology and equipment thus provide a rapid and reliable approach to PA imaging that may have potential applications in noninvasive imaging and clinic diagnosis.     

Computer-aided diagnosis in chest radiography for detection of childhood pneumonia

OBJECTIVES: This article presents a novel approach based on computer-aided diagnostic (CAD) scheme and wavelet transforms to aid pneumonia diagnosis in children, using chest radiograph images. The prototype system, named Pneumo-CAD, was designed to classify images into presence (PP) or absence of pneumonia (PA). MATERIALS AND METHODS: The knowledge database for the Pneumo-CAD comprised chest images confirmed as PP or PA by two radiologists trained to interpret chest radiographs according to the WHO guidelines for the diagnosis of pneumonia in children. The performance of the Pneumo-CAD was evaluated by a subset of images randomly selected from the knowledge database. The retrieval of similar images was made by feature extraction using wavelets transform coefficients of the image. The energy of the wavelet coefficients was used to compose the feature vector in order to support the computational classification of images as PP or PA. Methodology I worked with a rank-weighted 15-nearest-neighbour scheme, while methodology II employed a distance-dependent weighting for image classification. The performance of the prototype system was assessed by the ROC curve. RESULTS: Overall, the Pneumo-CAD using the Haar wavelet presented the best accuracy in discriminating PP from PA for both, methodology I (AUC=0.97) and methodology II (AUC=0.94), reaching sensitivity of 100% and specificity of 80% and 90%, respectively. CONCLUSION: Pneumo-CAD could represent a complementary tool to screen children with clinical suspicion of pneumonia, and so to contribute to gather information on the burden of-pneumonia estimates in order to help guide health policies toward preventive interventions.     

Preliminary Evaluation of Biplane Correlation (BCI) Stereographic Imaging for Lung Nodule Detection

A biplane correlation (BCI) imaging system obtains images that can be viewed in stereo, thereby minimizing overlapping structures. This study investigated whether using stereoscopic visualization provides superior lung nodule detection compared to standard postero-anterior (PA) image display. Images were acquired at two oblique views of ±3° as well as at a standard PA position from 60 patients. Images were processed using optimal parameters and displayed on a stereoscopic display. The PA image was viewed in the standard format, while the oblique views were paired to provide a stereoscopic view of the subject. A preliminary observer study was performed with four radiologists who viewed and scored the PA image then viewed and scored the BCI stereoscopic image. The BCI stereoscopic viewing of lung nodules resulted in 71 % sensitivity and 0.31 positive predictive value (PPV) index compared to PA results of 86 % sensitivity and 0.26 PPV index. The sensitivity for lung nodule detection with the BCI stereoscopic system was reduced by 15 %; however, the total number of false positives reported was reduced by 35 % resulting in an improved PPV index of 20 %. The preliminary results indicate observer dependency in terms of relative advantage of either system in the detection of lung nodules, but overall equivalency of the two methods with promising potential for BCI as an adjunct diagnostic technique.     

上消化道出血患者检测血清前白蛋白的临床意义

目的:探讨血清前白蛋白在上消化道出血中的意义。方法:对32例肝硬化并发上消化道出血患者及30例胃十二指肠疾病并发上消化道出血患者进行血清前白蛋白(PA)测定,并与34例正常对照相比较。结果:肝硬化并发上消化道出血患者血清PA低于胃十二指肠疾病并发上消化道出血者及正常对照组,且肝硬化组PA分布与后两者无重迭;Child分级间PA有显著差异。结论:上消化道出血患者检测血清PA有助于肝硬化并发出血的诊断,并可帮助判断病情及估计预后。     

Severity modeling of propionic acidemia using clinical and laboratory biomarkers

PurposeTo conduct a proof-of-principle study to identify subtypes of propionic acidemia (PA) and associated biomarkers.MethodsData from a clinically diverse PA patient population (https://clinicaltrials.gov/ct2/show/NCT02890342) were used to train and test machine learning models, identify PA-relevant biomarkers, and perform validation analysis using data from liver-transplanted participants. k-Means clustering was used to test for the existence of PA subtypes. Expert knowledge was used to define PA subtypes (mild and severe). Given expert classification, supervised machine learning (support vector machine with a polynomial kernel, svmPoly) performed dimensional reduction to define relevant features of each PA subtype.ResultsForty participants enrolled in the study; five underwent liver transplant. Analysis with k-means clustering indicated that several PA subtypes may exist on the biochemical continuum. The conventional PA biomarkers, plasma total 2-methylctirate and propionylcarnitine, were not statistically significantly different between nontransplanted and transplanted participants motivating us to search for other biomarkers. Unbiased dimensional reduction using svmPoly revealed that plasma transthyretin, alanine:serine ratio, GDF15, FGF21, and in vivo 1-¹³C-propionate oxidation, play roles in defining PA subtypes.ConclusionSupport vector machine prioritized biomarkers that helped classify propionic acidemia patients according to severity subtypes, with important ramifications for future clinical trials and management of PA.Graphical Abstract

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Near-infrared fluorescent dyes for enhanced contrast in optical mammography: phantom experiments

Optical mammography with near-infrared (NIR) light using time-domain, frequency-domain, or continuous-wave techniques is a novel imaging modality to locate human breast tumors. By investigating excised specimens of normal and diseased mamma tissue we were able to demonstrate that differences in their scattering properties are a poor predictive parameter for normal and diseased mamma tissue. This paper describes the application of a NIR dye to improve the differentiation between breast tumors and normal tissue in a rat model. The NIR dye furnished a high tumor-to-tissue contrast ratio (6:1) in fluorescence images. Furthermore, this dye was used to develop liquid scattering phantoms with absorbing and fluorescent inhomogeneities. Using frequency-domain and time-domain instrumentation these inhomogeneities were localized at sufficient contrast by their increased absorption and fluorescence. Contrast between inhomogeneities and surrounding medium could be improved by combining fluorescence and transmittance images.     

Reactive Compatibilization of Melt Mixed PA6/SWNT Composites: Mechanical Properties and Morphology

Summary: Styrene maleic anhydride copolymer (SMA) encapsulated single wall carbon nanotubes (SWNT) were melt mixed with polyamide 6 (PA6) utilizing an interfacial reaction in order to disperse SWNT homogeneously and to enhance interfacial adhesion. The intended reactive coupling between PA6 and SMA was evident from IR spectroscopy. Raman spectroscopy was used to characterize the SWNT and the nanocomposites. Studies on crystallization behavior showed the nucleating behavior of SWNT in the composites, as found using DSC and WAXD. The encapsulation of SWNT by SMA copolymer leads to increased elongation at break in the composites, which can be attributed to the enhanced interfacial adhesion between PA6 and SMA modified SWNT as observed from the SEM investigation of tensile fractured surfaces of PA6/SWNT+SMA composites. The glass transition temperature of PA6 increased significantly in the composites.

Tensile fractured surface of SMA encapsulated PA6/SWNT composites.     

A computerized method for automated identification of erect posteroanterior and supine anteroposterior chest radiographs

A computerized scheme was developed for automated identification of erect posteroanterior (PA) and supine anteroposterior (AP) chest radiographs. The method was based on three features, the tilt angle of the scapula superior border, the tilt angle of the clavicle and the extent of radiolucence in lung fields, to identify the view of a chest radiograph. The three indices A(scapula), A(clavicle) and C(lung) were determined from a chest image for the three features. Linear discriminant analysis was used to classify PA and AP chest images based on the three indices. The performance of the method was evaluated by receiver operating characteristic analysis. The proposed method was evaluated using a database of 600 PA and 600 AP chest radiographs. The discriminant performances Az of A(scapula), A(clavicle) and C(lung) were 0.878 ± 0.010, 0.683 ± 0.015 and 0.962 ± 0.006, respectively. The combination of the three indices obtained an Az value of 0.979 ± 0.004. The results indicate that the combination of the three indices could yield high discriminant performance. The proposed method could provide radiologists with information about the view of chest radiographs for interpretation or could be used as a preprocessing step for analyzing chest images.