2015 ACVIM Small Animal Consensus Statement on Seizure Management in Dogs

This report represents a scientific and working clinical consensus statement on seizure management in dogs based on current literature and clinical expertise. The goal was to establish guidelines for a predetermined, concise, and logical sequential approach to chronic seizure management starting with seizure identification and diagnosis (not included in this report), reviewing decision‐making, treatment strategies, focusing on issues related to chronic antiepileptic drug treatment response and monitoring, and guidelines to enhance patient response and quality of life. Ultimately, we hope to provide a foundation for ongoing and future clinical epilepsy research in veterinary medicine.     

Thyroid imaging in the dog: current status and future directions

This review describes the advantages and disadvantages of radiography, ultrasonography, and nuclear medicine in the 2 most frequent thyroid pathologies of the dog: acquired primary hypothyroidism and thyroid neoplasia. Ultrasonography and scintigraphy remain the 2 most indicated imaging modalities for these thyroid abnormalities. However, as in human medicine, computed tomography and magnetic resonance imaging also have potential indications. This is especially the case in the evaluation of the extent, local invasiveness, and local or distant metastases of thyroid neoplasia. Based on experience with different imaging modalities in people, we suggest future directions in the imaging of the canine thyroid gland.     

Pilot study of the ultrasonographic examination of the intact and transected medial glenohumeral ligament in dogs

Medial glenohumeral ligament injury is commonly reported during medial shoulder joint instability in dogs. Arthroscopy is considered the gold standard procedure, but it is invasive and requires distension of the joint. Ultrasonographic examination of the medial glenohumeral ligament has been studied as a possible, less invasive alternative to arthroscopy however it has not been considered a useful method of assessment due to the interference of the probe with the pectoral muscles. The aims of this prospective analytical randomized pilot study were to develop a standardized ultrasound protocol for visualizing the canine medial glenohumeral ligament and to compare goniometry and ultrasound findings in cadaver dogs with versus without transection of the medial glenohumeral ligament. Nine adult Beagle cadavers (18 shoulders) were used. The first six shoulders were used in a preliminary study to describe an ultrasound technique to identify the medial glenohumeral ligament. Arthroscopy was performed on the remaining 12 shoulders, with six randomly selected medial glenohumeral ligaments from these shoulders, transected during the procedure. Ultrasound examination was performed after each arthroscopic procedure by an ultrasonographer blinded to the patient group. Four medial glenohumeral ligaments (67%) were correctly identified during the preliminary study. Ultrasonographic examination failed to diagnose the transection of all six medial glenohumeral ligaments in the second part of the study. No difference was observed in the ligament thickness between the dogs with and without a transected medial glenohumeral ligament. Dogs with a transected medial glenohumeral ligament had a wider articular space compared to dogs without a transected ligament (P < 0.001), and an articular space wider than 8.2 mm was discriminatory of a transected medial glenohumeral ligament in all the shoulders. In conclusion, the medial glenohumeral ligament could be identified with a medial ultrasonographic approach of the shoulder and a wider articular space can be a sign of a medial shoulder joint instability. Further studies are needed to confirm these preliminary findings in living dogs, with and without shoulder instability.     

Gross anatomy,computed tomography,magnetic resonance imaging and bone mineral densitometry of the ovine metacarpo/metatarsophalangeal joint

This study was aimed to provide anatomical atlas of the ovine metacarpo/metatarsophalangeal joints using computed tomography (CT) scan and magnetic resonance imaging (MRI), as well as to investigate bone mineral density (BMD) and morphometric features of this joint. The limbs of twenty adult Sanjabi sheep were examined. Imaging was performed using a 16-slice multi-detector CT scanner and a 1.5 Tesla MRI scanner. The obtained images were correlated with corresponding anatomical sections. BMD was measured by Dual Energy X-ray Absorptiometry (DEXA) method. Also morphometric features included distance between metacarpal and metatarsal heads, width of metacarpal and metatarsal head, length, width and the height of the proximal sesamoid bones were measured. In MRI images, compact bones, ligaments and tendons showed less signal intensity (hypointense). The fatty tissue and bone marrow had more signal intensity (hyperintense), but articular cartilage and synovial fluid showed moderate signal intensity. BMD in the left hind limb was significantly higher than other three limbs (p ≤ 0.05). The length of proximal sesamoid bones in left forelimb was higher than right forelimb (p ≤ 0.05). The thickness of proximal sesamoid bones in left limbs was higher than those in their counterparts (p ≤ 0.05). The width of the medial head in the forelimbs was significantly greater than the hind limbs (p ≤ 0.05). The present results might be useful in managing the clinical techniques on this joint. Larger volume of the proximal sesamoid bones and wider medial head in the forelimbs compared to the hindlimbs impel this speculation that the centre of gravity is closer to the forelimbs.     

基于多源数据融合的盐分遥感反演与季节差异性研究

为提高多光谱盐分遥感反演的精度,利用实测高光谱与多光谱进行数据融合,并分析了不同季节盐分遥感的差异性。以河套灌区永济灌域为研究区域,以实测光谱仪测定的土壤高光谱数据和Landsat-8 OLI多光谱数据为基础,通过光谱变换和多元逐步回归方法筛选特征波段和特征光谱指数,构建了春、秋两季土壤盐分多光谱、高光谱反演模型,并利用特征光谱指数的线性回归构建了高-多光谱数据融合反演模型。结果表明:高光谱的反射率总体比多光谱高36. 83%,春季反射率比秋季平均高23. 78%。利用模型中最优变量-特征光谱指数对多光谱模型与高光谱模型进行融合,高-多光谱融合反演模型训练集和验证集R2平均值分别为0. 651和0. 635,RMSE平均值分别为2. 44 g/kg和2. 49 g/kg,精度明显高于对应的多光谱反演模型,其中训练集、验证集的R2平均值分别提高了36. 19%和35. 64%,RMSE平均值分别降低了34. 28%和41. 72%。春季多光谱、高光谱和融合反演模型的精度均高于秋季,其中训练集R2平均值比秋季模型分别提高了6. 03%、6. 05%和4. 40%,验证集R2平均值分别提高了19. 07%、12. 21%和1. 75%。构建的高-多光谱融合模型反演灌域春秋两季平均盐分含量分别为6. 05、5. 97 g/kg,平均相对误差分别为9. 65%和10. 68%,总体上该区域春季土壤主要为重盐化土,秋季土壤主要为中盐化土。     

连续投影算法融合信息熵选择霉变玉米高光谱特征波长

运用高光谱技术鉴别玉米霉变等级时,因光谱波段数多、数据量大、信息冗余度高,使鉴别工作难度加大。为了减少数据量,获得最有利于鉴别的高光谱信息特征波长,本研究提出了一种连续投影算法(SPA)融合信息熵的特征波长选择方法。首先,对霉变玉米样本高光谱数据运用多元散射校正(MSC)进行光谱预处理以消除噪声,然后利用SPA对处理过的光谱进行波长初选,得到8个初选特征波长,再通过信息熵原理处理初选特征波长下的图像信息,获得最佳特征波长。结果表明,运用SPA融合信息熵法得到有利于霉变玉米鉴别的最佳波长为819 nm,提取该波长下霉变玉米图像的纹理特征后,采用Fisher判别分析(FDA)进行鉴别,6个等级霉变玉米的鉴别正确率高达98.6%,充分证明所给出的特征波长选择方法是有效的。本研究特征波长选择方法可为更好地运用高光谱技术鉴别玉米霉变等级提供指导。     

基于灰度关联-岭回归的荒漠土壤有机质含量高光谱估算

为改善高光谱技术对荒漠土壤有机质的估测效果,该文采集了以色列Seder Boker地区的荒漠土壤,经预处理、理化分析后将土样分为砂质土和黏壤土2类,再通过光谱采集、处理得到6种光谱指标:反射率(reflectivity,REF)、倒数之对数变换(inverse-log reflectance,LR)、去包络线处理(continuum removal,CR)、标准正态变量变换(standard normal variable reflectance,SNV)、一阶微分变换(first order differential reflectance,FDR)和二阶微分变换(second order differential reflectance,SDR)。通过灰度关联(gray correlation,GC)法确定SNV、FDR、SDR为敏感光谱指标,采用偏最小二乘回归(partial least squares regression,PLSR)法和岭回归(ridge regression,RR)法,构建基于敏感光谱指标的土壤有机质高光谱反演模型,并对模型精度进行比较。结果表明:砂质土有机质含量的反演效果要优于黏壤土;基于SNV指标建立的模型决定系数R~2和相对分析误差RPD均为最高、均方根误差RMSE最低,所以SNV是土壤有机质的最佳光谱反演指标;对SNV-PLSR模型和SNV-RR模型综合比较得出,SNV-RR模型仅用全谱4%左右的波段建模,实现了更为理想的反演效果:其中,对砂质土有机质的预测能力极强(R_p~2为0.866,RMSE为0.610 g/kg、RPD为2.72),对黏壤土有机质的预测能力很好(Rp2为0.863,RMSE为0.898 g/kg、RPD为2.37)。荒漠土壤有机质GC-SNV-RR反演模型的建立为高光谱模型的优化、土壤有机质的快速测定提供了一种新的途径。     

基于高光谱数据的水体叶绿素a指数反演模型的建立

水体叶绿素a含量是反映水体质量的重要指标之一,利用遥感技术监测其含量具有众多优势。该研究利用2012年7月在广西壮族自治区桂林市漓江流域实地采集的水体高光谱数据和实验室化验分析数据,借鉴陆表植被叶绿素a的遥感反演模型,发展了一种新的水体叶绿素a提取指数(water chlorophyll-a index,WCI)。通过与反射率敏感波段法、波段比值法和半分析方法对比分析发现,新提出的WCI指数使用650、685、696 nm波段,波段稳定,决定系数R2可达0.58,均方根误差最小为0.24,受水体悬浮物影响小,在天津海河区域的验证效果也表明了该模型可以有效地提取水体叶绿素a含量。该方法扩展了水体叶绿素a监测的建模思路,对水体叶绿素a监测建模有一定的指导作用。     

应用可见/近红外高光谱成像测定鲑鱼片脂肪含量分布(英文)

脂肪作为一种重要的品质参数,在大西洋鲑鱼片中的分布很不均匀。为寻找一种能替代脂肪化学检测的快速无损的方法,该研究应用可见/近红外高光谱成像测定大西洋鲑鱼片的脂肪含量分布。分别采用可见/短波近红外(400-1100 nm)和近红外(900-1700 nm)系统获取大西洋鲑鱼片样本的高光谱图像。提取样本图像的平均光谱并与其相应的脂肪含量化学值采用偏最小二乘回归(partial least squares regression,PLSR)和最小二乘支持向量机(least-squares support vector machines,LS-SVM)建立相关性模型。为降低高光谱图像的共线性和冗余度,基于竞争性自适应重加权算法(competitive adaptive reweighted sampling,CARS)分别在可见/短波近红外和近红外光谱区间提取16个(468,479,728,734,785,822,863,890,895,899,920,978,1005,1033,1040,1051 nm)和15个(975,995,1023,1047,1095,1124,1167,1210,1273,1316,1354,1368,1575,1632,1661 nm)特征波长,并分别建立PLSR和LS-SVM模型。特征波长模型的性能优于全波段模型,且近红外区间的特征波长PLSR模型为最优,预测决定系数(R2p)为0.92,预测均方根误差(root mean square error of prediction,RMSEP)为0.92%,剩余预测偏差(residual predictive deviation,RPD)为3.50。最后,将最优模型用于预测高光谱图像上所有像素点的脂肪含量以展示样本上脂肪的分布。此外,还基于该技术对大西洋鲑整鱼片实现了脂肪分布可视化。结果表明高光谱成像技术结合化学计量学方法在大西洋鲑鱼片脂肪的定量和分布可视化上有一定的研究和应用前景。