鼻咽癌图像引导放射治疗IGRT中两种匹配模式对摆位误差的影响研究

目的:观察在鼻咽癌图像引导放射治疗中采用骨和灰度两种图像匹配模式对摆位误差的影响。方法:在保证客观和尽可能操作规范和标准的条件下,对同一鼻咽癌患者12次治疗重复摆位后用CBCT采集的图像信息,分别采用骨和灰度两种模式与参考图像匹配,观察两种方法对摆位误差的影响。结果:对两种匹配方式的摆位误差分别进行比较,t检验结果显示P值均大于0.05,无统计学意义。结论:鼻咽癌图像引导放射治疗IGRT中采用骨匹配模式进行图像匹配是一种更优选择。     

DSA图像中运动伪影的消除方法

由于病人存在着各种运动(如呼吸、肌肉运动、心脏运动、设备噪声),在成像过程中常会造成图像上出现伪影,干扰医生的正常诊断,为消除这种伪影,本文提出一种基于图像配准思想的全自动消除伪影的方法,该方法能够自动消除DSA图像中的大部分运动伪影,使DSA图像得到较好的增强,并为后面的血管分割和三维重建提供便利,是一种快速有效的方法。     

基于TM卫星影像数据的北京市植被变化及其原因分析

植被覆盖变化是全球变化研究的重要内容之一,由于NDVI与植被的分布密度呈线性相关,是指示大尺度植被覆盖的良好指标,因此在宏观植被盖度的估算中常被应用.利用1987年9月26日和2009年9月22日的Landsat TM卫星影像,以NDVI为桥梁,分别计算了北京市域的植被盖度和大于0.1的NDVI差值指数,北京市域与不同生态区域两个尺度对其植被变化情况进行了量化分析,结果表明,2009年与1987年相比,北京市极低覆盖度、中覆盖度和高覆盖度植被的面积均有所减少,其所占全市土地面积的比例从1987年到2009年分别降低了5.15％和0.54％和0.03％;而低覆盖度和极高覆盖度植被的面积比例则分别增加了5.71％和0.01％.大于0.1的植被差值指数统计结果显示,全市域植被质量以改善为主,全市植被发生改善变化的土地面积共919302.3 hm2,其中发生轻微改善的比例为28.31％,中度改善的为41.33％,极度改善的面积为30.36％;全市植被发生退化变化的面积326931.12 hm2,其中发生中度退化、轻微退化和极度退化的面积分别占到了退化变化土地面积的41.98％、43.20％和14.82％.从不同区域的植被差值指数看,植被发生退化变化最明显的区域为燕山山区北部、五环以内和五至六环间区域,这几个区域退化变化的植被面积占相应区域的面积比例分别达到了30.25％、58.17％和47.38％,而且均以严重退化与中度退化为主,两者合计的面积比例分别为15.79％、44.72％和34.19％.而发生退化变化面积比例最小的区域为太行山区和延庆盆地,其退化面积占该区域植被面积的比例分别为13.35％和17.02％,且退化程度均以轻微退化和中度退化为主,其面积比例介于5％-8％之间.从植被变化的驱动力看,目前还看不出北京这种植被变化结果与气候变化之间的直接关联.北京市植被变化的驱动力主要还是人为因素.这包括了区域性的大环境绿化生态工程建设(包括山区与平原区),城市绿化市政工程建设、平原区农业结构调整、新农村生态环境建设,以及由于降水而导致的山区河岸带变化等.其中河流水面变化对河岸带植被变化的影响范围在多年平均水面线外0-150 m范围内,0-100 m范围为受影响较大的区域.     

基于混合像元分解的 MODIS 绿潮覆盖面积精细化提取方法研究

在绿潮遥感业务化监测中,250 m 分辨率的 MODIS 卫星数据是主要数据源,归一化差值植被指数（ND-VI）是绿潮卫星遥感信息提取的主要方法。研究发现,由于 MODIS 空间分辨率较低,存在大量的混合像元,导致提取的绿潮覆盖面积明显偏大。针对该问题,本文在 MODIS 绿潮 NDVI 计算的基础上,首先对大于 NDVI 阈值的像元进行混合像元分解,得到 MODIS NDVI 混合像元分解后的绿潮面积,然后以准同步的30 m 分辨率 HJ-1 CCD 影像提取的绿潮覆盖面积为真值,建立了 MODIS NDVI 混合像元分解得到的绿潮面积与 HJ-1提取的绿潮面积之间的关系模型,以实现绿潮面积的精细化提取。与传统的 NDVI 阈值法和混合像元分解法相比,该方法提取的绿潮覆盖面积更接近于“真值”,面积约为“真值”的96％,而传统的 NDVI 阈值法和混合像元分解方法提取的面积分别为“真值”的2．96倍和45％。另外,与传统的 NDVI 阈值法相比,新方法对 NDVI 阈值变化不敏感,在相同的 NDVI 阈值变化区间内,前者提取的绿潮覆盖面积变化了41％,而新方法的变化仅为11％。本文的工作在很大程度上解决了 MODIS 空间分辨率低导致的绿潮监测结果不准确的问题,为精细化的绿潮卫星遥感业务监测提供了参考。     

全脊柱MR成像9例失败原因分析

目的:探讨全脊柱MR成像中因体位设计、参数设置、病人配合等因素造成全眷柱MR成像失败的原因及其解决方法.方法:采用GE SIGNA双梯度HDx 1.5-T磁共振成像系统,专用8通道全脊柱相控阵线圈,GE AW4.3图像后处理工作站,拼接处理软件pasting 1.1.利用自动移床技术一次定位分两段扫描,即颈胸段和胸腰骶段;将矢状位、冠状位扫描图像传至后处理工作站,通过pasting 1.1软件将上下两段同一序列图像分别进行自动的无缝隙拼接生成全脊柱图像.结果:79例中全脊柱MR成像失败9例;其中4例因体位设计不当或在两序列扫描间歇期由于患者左右移动,使得脊髓正中面不能拼接在一幅图像中;有3例因上下两段的层数、扫描起始位置不一致或扫描定位时定位线偏转了一定角度,使得全脊柱图像序列中有几幅只有上段或只有下段原始扫描图像;有1例因下段扫描野过小使得全脊柱图像序列中胸12椎体层面信息缺失;还有1例因扫描下段T2W1像时患者向上移动了一段距离,使得全脊柱图像T2WI序列中颈1-腰5只有22个椎体显示.其余70例均获得准确、直观的全椎管内脊髓及椎体结构的影像.结论:要获得高质量的全脊柱MR成像,必须选择正确的扫描参数,体位设计时要求操作者有足够的细心和耐心一次性摆好体位,还要和患者有良好的沟通以便取得患者最好的配合.     

食管癌三维适形放疗长期疗效的多因素分析

[目的]分析影响食管癌三维适形放疗(3D-CRT)长期生存的预后因素,为个体化治疗方案的选择和临床分期的修订提供依据.[方法]收集2005～2006年在汕头大学医学院附属肿瘤医院行根治性3D-CRT的食管癌患者236例,对患者的一般临床参数和影像资料进行单因素分析,将筛选出来的有意义的因素纳入Cox模型进行多因素分析.[结果]全组患者中位随访时间为50个月,5年总生存率为26.2％.单因素分析显示病灶部位、X线下病灶长度、病灶横截面最长径、最大横径、最大前后径、壁厚、病灶CT长度、GTV-E、是否外侵、有无淋巴结转移、淋巴结转移模式、淋巴结个数、GTV-LN、GTV-T均是影响预后的因素;多因素分析显示GTV-T、病灶横截面最大径是影响预后的独立因素.[结论]食管癌CT影像上GTV-T和病灶横截面最长径影响食管癌3D CRT的疗效,可以作为制定个体化治疗方案和临床分期的重要指标.     

40多年来塔南策勒绿洲动态变化研究

 利用策勒绿洲1956、1990和1998年3个不同时期的遥感数据（航片、TM和SPOT）进行配准、解译与分类处理,比较分析绿洲40多年来的动态变化,并从自然和人为因素两个方面探讨绿洲变化的原因。结果表明,从1956年到1998年策勒绿洲西北部的景观格局发生了显著变化,绿洲面积增加了近20％;林地的分布明显改变;河道发生显著位移,据实地调查大约向北移动400 m。对1990年TM与1998年SPOT分类数据,用FRAGSTATS软件计算景观格局指数并比较分析,发现研究区的绿洲、绿洲 荒漠交错带、荒漠和沙丘4种景观类型发生了明显的变化。绿洲面积增加而斑块数减少了近一半;交错带面积减少而斑块数增加了35％;荒漠面积减少而斑块数增加了60％;沙丘面积基本没有变化但斑块数减少了20％。绿洲变化的总体趋势是人工绿洲的面积增大而绿洲 荒漠交错带的面积明显减少,同时整个绿洲的破碎度增加而连通性降低,绿洲的稳定性和自我调节的功能下降。     

普遍野生稻和亚洲栽培稻遗传多样性的研究

用 ４４个 ＲＦＬＰ标记对来自中国、印度、泰国等亚洲 １０个国家的普通野生稻（简称普野,下同）和来自多个国家的７５个栽培稻品种,从多态位点的比率、等位基因数、基因型数、平均杂合度及平均基因多样性等多个方面,比较了不同国家和不同地区的普通野生稻、栽培稻籼粳亚种及栽培稻与普野之间遗传多样性的差异。结果表明：中国普野的遗传多样性最大;其次是印度普野;南亚普野的平均基因多样性大于东南亚普野,而多态位点的比率、等位基因数及基因型数等却低于东南亚普野;栽培稻的遗传多样性明显小于普通野生稻。在所检测的４４个位点中,栽培稻的多态位点数仅为野生稻的３／４,等位基因数约为野生稻的６０％,基因型种类约为野生稻的１／２。栽培稻中籼稻的遗传多样性高于粳稻。在平均每个位点的实际杂合度上,以中国普野杂合度最高,普通野生稻是栽培稻的２倍。说明从野生稻演化成栽培稻的过程中,经过自然选择和人工选择,杂合度降低,等位基因减少,基因多样性下降。     

MatriX Generator （MG）：一个基于DNA片段的0／1矩阵生成程序

分子群体遗传学研究的特点是取样量人——存在于群体样本中的遗传变异必须要充分代表该群体和该物种的遗传变异量及分析的位点数多——位点样本必须恰当代表基因组。大样本的群体取样和位点取样产生大量的原始数据,使原始数据人工处理非常困难甚至不可能,从而迫切需要原始数据处理的自动化。目前一些大公司提供的凝胶图像收集仪器和配套的软件已经使原始数据的获取基本上自动化或半自动化。获得DNA片段分子量数据后,必须把这些分子量数据转变成可反映操作单位(样本)之间关系的数据矩阵,原来用于计算分子量的那些软件已不实用或派不上用场。目前,除了用于fAFLP的Binthere弥补了部分不足外,还没有此类软件。Binthere存在固定栏宽(Bin)的缺陷,也就是将分子量最大值与最小值之间等分的方法来归纳不同操作单位(OUT)之间的异同,使得分子量绝对值差很小的数据可能被归入不同的栏,导致结果不正确。为了解决这类问题,我们设计编写了一个新的软件,取名为Matrix Generator (MG)。与同类软件相比,MG具有两个主要优点：(1)采用动态栏宽和智能归并算法,克服了固定栏宽可能造成的错误：(2)可用于非荧光标记的分子标记技术。MG的基本思路是：分子量差异越小的片段,越可能是同缘片段,越应该处于相同的栏内。为此,我们采用绝对对应的动态过程。也就是说,从最小分子量到最大分子量之间的栏目数不是事先确定,而是由所分析的所有样品的特点和所使用的凝胶的分辨率(用户根据凝胶的特点给出数值)决定的。当两片段的差异小于凝胶所能达到的分辨率时,两片段被认为是同缘片段而归入相同的栏内。归并的过程从差异最小值开始,直至任意两片段的差异都大于凝胶的分辨率为止。这样就排除了同缘片段被隔离或者非同缘片段被合并的错误,从而使最可能同缘的片段归结在同一位点。MG第一版(v1．0,DOS版)集中体现了实用和易用的优点而没有包含同类软件所具有的一些功能,所以MG必须与其他软件结合使用。对于非荧光标记的分子标记技术,如RAPD、RFLP、AFLP等,可用Quantity One等软件得到分子量,用Excel生成样品与(分子量数据代表的)DNA片段矩阵,然后用MG处理。对于荧光标记的分子标记技术,如fAFIP、fSSR等,除可以用Excel牛成矩阵外,可直接用Binthere和Genotyper等生成分子量矩阵,然后用MG处理。MG输出的矩阵经过适当编辑后,就可用后续的软件如Paup、Ntsys、Philip等运算。为了检验MG的有效性,我们用六道木属(Abelia)的AFIJP分析数据进行检验,14个样品的DNA片段分别用Binthere和MG进行处理。前者得到295个含信息的位点,后者得到210个含信息的位点。用Nei and Li (1979)的算法分别计算距离矩阵并对两距离矩阵作Mantel检验。结果,两矩阵之间存在一定的差别,但相似性系数高达0．941 63,说明两种方法总体上会得到相似的结果,但局部会有所不同。用Paup对两矩阵作进一步分析,生成两个Neighbor-joining (NJ)树。结果表明,MG生成的数据更符合实际情况,而且分辨率高。     

Matrix Generator(MG):一个基于DNA片段的0/1矩阵生成程序

分子群体遗传学研究的特点是取样量大--存在于群体样本中的遗传变异必须要充分代表该群体和该物种的遗传变异量及分析的位点数多--位点样本必须恰当代表基因组.大样本的群体取样和位点取样产生大量的原始数据,使原始数据人工处理非常困难甚至不可能,从而迫切需要原始数据处理的自动化.目前一些大公司提供的凝胶图像收集仪器和配套的软件已经使原始数据的获取基本上自动化或半自动化.获得DNA片段分子量数据后,必须把这些分子量数据转变成可反映操作单位(样本)之间关系的数据矩阵,原来用于计算分子量的那些软件已不实用或派不上用场.目前,除了用于fAFLP的Binthere弥补了部分不足外,还没有此类软件.Binthere存在固定栏宽(Bin)的缺陷,也就是将分子量最大值与最小值之间等分的方法来归纳不同操作单位(OUT)之间的异同,使得分子量绝对值差很小的数据可能被归入不同的栏,导致结果不正确.为了解决这类问题,我们设计编写了一个新的软件,取名为Matrix Generator(MG).与同类软件相比,MG具有两个主要优点:(1)采用动态栏宽和智能归并算法,克服了固定栏宽可能造成的错误;(2)可用于非荧光标记的分子标记技术.MG的基本思路是:分子量差异越小的片段,越可能是同缘片段,越应该处于相同的栏内.为此,我们采用绝对对应的动态过程.也就是说,从最小分子量到最大分子量之间的栏目数不是事先确定,而是由所分析的所有样品的特点和所使用的凝胶的分辨率(用户根据凝胶的特点给出数值)决定的.当两片段的差异小于凝胶所能达到的分辨率时,两片段被认为是同缘片段而归入相同的栏内.归并的过程从差异最小值开始,直至任意两片段的差异都大于凝胶的分辨率为止.这样就排除了同缘片段被隔离或者非同缘片段被合并的错误,从而使最可能同缘的片段归结在同一位点.MG第一版(V1.0,DOS版)集中体现了实用和易用的优点而没有包含同类软件所具有的一些功能,所以MG必须与其他软件结合使用.对于非荧光标记的分子标记技术,如RAPD、RFLP、AFLP等,可用Quantity One等软件得到分子量,用Excel生成样品与(分子量数据代表的)DNA片段矩阵,然后用MG处理.对于荧光标记的分子标记技术,如fAFLP、fSSR等,除可以用Excel生成矩阵外,可直接用Binthere和Genotyper等生成分子量矩阵,然后用MG处理.MG输出的矩阵经过适当编辑后,就可用后续的软件如Paup、Ntsys、Philip等运算.为了检验MG的有效性,我们用六道木属(Abelia)的AFLP分析数据进行检验,14个样品的DNA片段分别用Binthere和MG进行处理.前者得到295个含信息的位点,后者得到210个含信息的位点.用Nei and Li(1979)的算法分别计算距离矩阵并对两距离矩阵作Mantel检验.结果,两矩阵之间存在一定的差别,但相似性系数高达0.941 63,说明两种方法总体上会得到相似的结果,但局部会有所不同.用Paup对两矩阵作进一步分析,生成两个Neighbor-joining(NJ)树.结果表明,MG生成的数据更符合实际情况,而且分辨率高.     

A review of automatic lung tumour segmentation in the era of 4DCT

AimTo review the literature on auto-contouring methods of lung tumour volumes on four-dimensional computed tomography (4DCT).BackgroundManual delineation of lung tumour on 4DCT has been the gold standard in clinical practice. However, it is resource intensive due to the high volume of data which results in longer contouring duration and uncertainties in defining target. Auto-contouring may present as an attractive alternative by decreasing manual inputs required, thus improving the contouring process. This review aims to assess the accuracy, variability and contouring duration of automatic contouring compared with manual contouring in lung cancer on 4DCT datasets.Materials and methodsA search and review of literature were conducted to identify studies regarding lung tumour contouring on 4DCT. Manual and auto-contours were assessed and compared based on accuracy, variability and contouring duration.ResultsThirteen studies were included in this review and their results were compared. Accuracy of auto-contours was found to be comparable to manual contours. Auto-contouring resulted in lesser inter-observer variation when compared to manual contouring, however there was no significant reduction in intra-observer variability. Additionally, contouring duration was reduced with auto-contouring although long computation time could present as a bottleneck.ConclusionAuto-contouring is reliable and efficient, producing accurate contours with better consistency compared to manual contours. However, manual inputs would still be required both before and after auto-propagation.     

Growth Pattern Analysis of Murine Lung Neoplasms by Advanced Semi-Automated Quantification of Micro-CT Images

Computed tomography (CT) is a non-invasive imaging modality used to monitor human lung cancers. Typically, tumor volumes are calculated using manual or semi-automated methods that require substantial user input, and an exponential growth model is used to predict tumor growth. However, these measurement methodologies are time-consuming and can lack consistency. In addition, the availability of datasets with sequential images of the same tumor that are needed to characterize in vivo growth patterns for human lung cancers is limited due to treatment interventions and radiation exposure associated with multiple scans. In this paper, we performed micro-CT imaging of mouse lung cancers induced by overexpression of ribonucleotide reductase, a key enzyme in nucleotide biosynthesis, and developed an advanced semi-automated algorithm for efficient and accurate tumor volume measurement. Tumor volumes determined by the algorithm were first validated by comparison with results from manual methods for volume determination as well as direct physical measurements. A longitudinal study was then performed to investigate in vivo murine lung tumor growth patterns. Individual mice were imaged at least three times, with at least three weeks between scans. The tumors analyzed exhibited an exponential growth pattern, with an average doubling time of 57.08 days. The accuracy of the algorithm in the longitudinal study was also confirmed by comparing its output with manual measurements. These results suggest an exponential growth model for lung neoplasms and establish a new advanced semi-automated algorithm to measure lung tumor volume in mice that can aid efforts to improve lung cancer diagnosis and the evaluation of therapeutic responses.     

Occupational disparities in survival from common cancers in Japan: Analysis of Kanagawa cancer registry

BackgroundLittle is known about occupational disparities in survival for common cancer sites in Japan.MethodsUsing data from a population-based cancer registry, we identified 32,870 cancer patients diagnosed during 1992–2011. We followed the patients for 5 years (median follow-up time 5.0 years). For each individual, we classified their longest-held occupation into 5 classes (upper non-manual, lower non-manual, manual, farmer, and others) following the Erikson-Goldthorpe-Portocarero scheme. Poisson regression models were used to estimate overall and site-specific mortality rate ratios (MRRs) and 95% confidence intervals (CI) for each occupational class, adjusted for sex, age, and diagnosis year. Upper non-manual workers served as the reference group. Additionally, using a binary categorization of occupations (manual workers versus non-manual workers), a causal mediation analysis with 4-way decomposition was performed to investigate the potential mediation of the association between occupation and overall mortality by cancer stage.ResultsOverall prognosis was good in this population (5-year overall survival was 81.7%). Compared with upper non-manual workers, both overall and cancer-specific mortality was higher in lower non-manual workers (MRR=1.14, 95% CI 1.05–1.24) and manual workers (MRR=1.40, 95% CI 1.29–1.53). After adjusting for the mediating influence of prognostic factors (stage and treatment), the observed occupational differences were attenuated but remained significant in manual workers: MRR = 1.23 (95% CI 1.08–1.39). Observed occupational disparities tended to be attributable to common cancers, i.e., stomach and lung among men and female breast cancer. Additionally, manual workers had 1.25 times higher odds for advanced stage. In the mediation analysis, the overall proportion explained by mediating effect of cancer stage was 29% (4% due to mediated interaction and 25% due to pure indirect effect).ConclusionWe documented occupational disparities in survival from commonly-occurring cancers in Japan. Occupational differences in cancer stage may explain one-third of the survival disparities.     

Role and accuracy of rapid on‐site evaluation of CT‐guided fine needle aspiration cytology of lung nodules

A. Fassina, M. Corradin, D. Zardo, R. Cappellesso, F. Corbetti and M. Fassan
Role and accuracy of rapid on‐site evaluation of CT‐guided fine needle aspiration cytology of lung nodules Objective: To prospectively investigate the role of trans‐thoracic fine needle aspiration cytology (FNA) and the value of rapid on‐site evaluation (ROSE) in the clinical management of patients with pulmonary nodules/masses. Computed tomography (CT)‐guided FNA is commonly employed for the diagnosis of lung lesions although its position in the diagnostic work‐up is still a matter of debate. Methods: We reviewed 311 patients (211 males and 100 females, mean age 69.5 years) admitted to the University of Padova from 2004 to 2008, correlating the results of cytology with the available histological findings obtained from biopsies, surgery or autopsy. Results: Smears were adequate in 305 cases (98%) and inadequate in six (2%); a diagnosis of malignancy was achieved in 263 cases (86.2%); 39 cases (12.8%) were classified as non‐malignant; and three cases (1%) were classified as suspect for malignancy. When correlated with histology, FNA with ROSE discriminated malignant versus non‐malignant lesions (Cohen’s kappa 0.78), with three false negatives (sensitivity 96.3%, specificity 100%). Moreover, a satisfactory overall agreement of 71.4% was achieved in differentiating the cancer histological types. Pneumothorax occurred in 13 cases, haemoptysis in four, and chest pain in three. A single aspiration was sufficient in 79.6% of patients; two aspirations were needed in 17.4% and three in 3%. The low complication rate was related to the limited number of aspirations needed due to ROSE. Conclusions: FNA with ROSE is a safe and useful tool in the diagnostic work‐up of lung cancer patients, with no contraindications to its use as the first diagnostic procedure for all patients with peripheral lung lesions. FNA with ROSE should be reconsidered in the guidelines for diagnosing and managing lung cancer.     

EBUS-TBNA Provides Highest RNA Yield for Multiple Biomarker Testing from Routinely Obtained Small Biopsies in Non-Small Cell Lung Cancer Patients - A Comparative Study of Three Different Minimal Invasive Sampling Methods

Background

Multiple biomarker testing is necessary to facilitate individualized treatment of lung cancer patients. More than 80% of lung cancers are diagnosed based on very small tumor samples. Often there is not enough tissue for molecular analysis. We compared three minimal invasive sampling methods with respect to RNA quantity for molecular testing.

Methods

106 small biopsies were prospectively collected by three different methods forceps biopsy, endobronchial ultrasound (EBUS) guided transbronchial needle aspiration (TBNA), and CT-guided core biopsy. Samples were split into two halves. One part was formalin fixed and paraffin embedded for standard pathological evaluation. The other part was put in RNAlater for immediate RNA/DNA extraction. If the pathologist confirmed the diagnosis of non-small cell lung cancer(NSCLC), the following molecular markers were tested: EGFR mutation, ERCC1, RRM1 and BRCA1.

Results

Overall, RNA-extraction was possible in 101 out of 106 patients (95.3%). We found 49% adenocarcinomas, 38% squamouscarcinomas, and 14% non-otherwise-specified(NOS). The highest RNA yield came from endobronchial ultrasound guided needle aspiration, which was significantly higher than bronchoscopy (37.74±41.09 vs. 13.74±15.53 ng respectively, P = 0.005) and numerically higher than CT-core biopsy (37.74±41.09 vs. 28.72±44.27 ng respectively, P = 0.244). EGFR mutation testing was feasible in 100% of evaluable patients and its incidence was 40.8%, 7.9% and 14.3% in adenocarcinomas, squamouscarcinomas and NSCLC NOS subgroup respectively. There was no difference in the feasibility of molecular testing between the three sampling methods with feasibility rates for ERCC1, RRM1 and BRCA1 of 91%, 87% and 81% respectively.

Conclusion

All three methods can provide sufficient tumor material for multiple biomarkers testing from routinely obtained small biopsies in lung cancer patients. In our study EBUS guided needle aspiration provided the highest amount of tumor RNA compared to bronchoscopy or CT guided core biopsy. Thus EBUS should be considered as an acceptable option for tissue acquisition for molecular testing.     

Quantitative monitoring of mouse lung tumors by magnetic resonance imaging

Primary lung cancer remains the leading cause of cancer-related death in the Western world, and the lung is a common site for recurrence of extrathoracic malignancies. Small-animal (rodent) models of cancer can have a very valuable role in the development of improved therapeutic strategies. However, detection of mouse pulmonary tumors and their subsequent response to therapy in situ is challenging. We have recently described MRI as a reliable, reproducible and nondestructive modality for the detection and serial monitoring of pulmonary tumors. By combining respiratory-gated data acquisition methods with manual and automated segmentation algorithms described by our laboratory, pulmonary tumor burden can be quantitatively measured in approximately 1 h (data acquisition plus analysis) per mouse. Quantitative, analytical methods are described for measuring tumor burden in both primary (discrete tumors) and metastatic (diffuse tumors) disease. Thus, small-animal MRI represents a novel and unique research tool for preclinical investigation of therapeutic strategies for treatment of pulmonary malignancies, and it may be valuable in evaluating new compounds targeting lung cancer in vivo.     

Quantification of Tumor Burden in a Genetically Engineered Mouse Model of Lung Cancer by Micro-CT and Automated Analysis

Genetically engineered mouse models (GEMMs) of lung cancer closely recapitulate the human disease but suffer from the difficulty of evaluating tumor growth by conventional methods. Herein, a novel automated image analysis method for estimating the lung tumor burden from in vivo micro-computed tomography (micro-CT) data is described. The proposed tumor burden metric is the segmented soft tissue volume contained within a chest space region of interest, excluding an estimate of the heart volume. The method was validated by comparison with previously published manual analysis methods and applied in two therapeutic studies in a mutant K-ras GEMM of non–small cell lung carcinoma. Mice were imaged by micro-CT pre-treatment and stratified into four treatment groups: an antibody inhibiting vascular endothelial growth factor (anti-VEGF), chemotherapy, combination of anti-VEGF and chemotherapy, or control antibody. In the first study, post-treatment imaging was performed 4 weeks later. In the second study, mice were scanned serially on a high-throughput scanner every 2 weeks for 8 weeks during treatment. In both studies, the automated tumor burden estimates were well correlated with manual metrics (r value range: 0.83-0.93, P < .0001) and showed a similar, significant reduction in tumor growth in mice treated with anti-VEGF alone or in combination with chemotherapy. Given the fully automated nature of this technique, the proposed analysis method can provide a valuable tool in preclinical drug research for screening and randomizing animals into treatment groups and evaluating treatment efficacy in mouse models of lung cancer in a highly robust and efficient manner.     

Fabrication of skeletal muscle constructs by topographic activation of cell alignment

Skeletal muscle fiber construction for tissue-engineered grafts requires assembly of unidirectionally aligned juxtaposed myotubes. To construct such a tissue, a polymer microchip with linearly aligned microgrooves was fabricated that could direct myoblast adaptation under stringent conditions. The closely spaced microgrooves fabricated by a modified replica molding process guided linear cellular alignment. Examination of the myoblasts by immunofluorescence microscopy demonstrated that the microgrooves with subcellular widths and appropriate height-to-width ratios were required for practically complete linear alignment of myoblasts. The topology-dependent cell alignment encouraged differentiation of myoblasts into multinucleate, myosin heavy chain positive myotubes. The monolayer of myotubes formed on the microstructured chips allowed attachment, growth and differentiation of subsequent layers of linearly arranged myoblasts, parallel to the primary monolayer of myotubes. The consequent deposition of additional myoblasts on the previous layer of myotubes resulted in three-dimensional multi-layered structures of myotubes, typical of differentiated skeletal muscle tissue. The findings demonstrate that the on-chip device holds promise for providing an efficient means for guided muscle tissue construction.     

Molecular phylogenetics of the lizard genus Microlophus (squamata:tropiduridae): aligning and retrieving indel signal from nuclear introns

We use a multigene data set (the mitochondrial locus and nine nuclear gene regions) to test phylogenetic relationships in the South American "lava lizards" (genus Microlophus) and describe a strategy for aligning noncoding sequences that accounts for differences in tempo and class of mutational events. We focus on seven nuclear introns that vary in size and frequency of multibase length mutations (i.e., indels) and present a manual alignment strategy that incorporates insertions and deletions (indels) for each intron. Our method is based on mechanistic explanations of intron evolution that does not require a guide tree. We also use a progressive alignment algorithm (Probabilistic Alignment Kit; PRANK) and distinguishes insertions from deletions and avoids the "gapcost" conundrum. We describe an approach to selecting a guide tree purged of ambiguously aligned regions and use this to refine PRANK performance. We show that although manual alignment is successful in finding repeat motifs and the most obvious indels, some regions can only be subjectively aligned, and there are limits to the size and complexity of a data matrix for which this approach can be taken. PRANK alignments identified more parsimony-informative indels while simultaneously increasing nucleotide identity in conserved sequence blocks flanking the indel regions. When comparing manual and PRANK with two widely used methods (CLUSTAL, MUSCLE) for the alignment of the most length-variable intron, only PRANK recovered a tree congruent at deeper nodes with the combined data tree inferred from all nuclear gene regions. We take this concordance as an objective function of alignment quality and present a strongly supported phylogenetic hypothesis for Microlophus relationships. From this hypothesis we show that (1) a coded indel data partition derived from the PRANK alignment contributed significantly to nodal support and (2) the indel data set permitted detection of significant conflict between mitochondrial and nuclear data partitions, which we hypothesize arose from secondary contact of distantly related taxa, followed by hybridization and mtDNA introgression.     

MALIDUP: a database of manually constructed structure alignments for duplicated domain pairs

We describe MALIDUP (manual alignments of duplicated domains), a database of 241 pairwise structure alignments for homologous domains originated by internal duplication within the same polypeptide chain. Since duplicated domains within a protein frequently diverge in function and thus in sequence, this would be the first database of structurally similar homologs that is not strongly biased by sequence or functional similarity. Our manual alignments in most cases agree with the automatic structural alignments generated by several commonly used programs. This carefully constructed database could be used in studies on protein evolution and as a reference for testing structure alignment programs. The database is available at http://prodata.swmed.edu/malidup.