用18F-FDG PET/CT勾画肺肿瘤靶区最佳阈值的模型研究

目的 通过模型实验初步建立使18F-脱氧葡萄糖(FDG)PET图像上显示的肿瘤体积肿瘤实际体积一致的最佳阈值条件.方法 采用美国DATA SPECTUM公司NEMA IEC-BodyPhantom setTM>体模,以不同大小的球体(体积分别为0.52,1.15,2.60,5.50,11.40,26.50 ml)模拟临床常见肺肿瘤的大小和靶/本底(T/B)比值.选择合适的窗位和窗宽,使CT图像上显示的球体体积与球体实测体积一致,并以此作为球体的实际体积,调节PET图像的阈值,使PET图像上勾画的球体轮廓与CT图像上所勾画的最接近.设绝对阈值(Ithreshold)=本底平均像素值(Iback)+相对阈值[x%Imax-back(slice)>,即每个层面的最大像素值与本底平均像素值的差值的百分比].比较应用筛选出的最佳绝对阈值与应用最广泛的靶体内最大像素值[42%Imax(total)>]为阈值勾画的球体体积大小及对实际体积覆盖率的差异.采用SPSS 13.0软件进行统计学处理,行Wilcoxon法检验.结果 对体积≥5.50 ml的不同T/B比值的球体,中央1/2层面的最佳相对阈值与最大层面的最佳相对阈值相差(1.6±2.0)%,而两端1/2层面的最佳相对阈值与最大层面的最佳相对阈值相差(19.3±10.1)%,二者差异有统计学意义(Z=-7.26,P<0.01).最大层面的最佳相对阈值在20%～25%之间的改变引起勾画体积与实际体积的差异≤5%.以Ithreshold=Iback+20%Imax-back作为各层面的最佳绝对阈值,所勾画的球体体积较实际体积扩大(12.6±6.6)%,而42%Imax(total)勾画的体积较实际体积缩小(-17.2±15.2)%(Z=2.67,P<0.01),前者对实际体积的覆盖率优于后者(97.1%与79.4%,Z=-2.67,P<0.01).结论 Iback+20%Imax-back(slice)可能是不依赖于CT提供的肿瘤体积信息层面化的最佳阈值条件,其准确性优于42%Imax(total)阈值法.     

PET图像勾画肿瘤靶区边界的水模研究

目的 通过水模研究,探讨影响18F-脱氧葡萄糖（FDG）PET图像靶区勾画阈值（TH%）的因素,建立计算阈值的公式,为不同生物学特征的肿瘤选取不同阈值.方法 对特制的拥有5个不同大小靶区、7种不同靶区本底放射性比值的水模进行PET/CT图像采集,由图像得到每个靶区的最大标准摄取值（SUVmax）、靶区边界处的SUV（SUVborder）、本底中1 cm×1 cm大小感兴趣区的平均SUV（SUVbg）以及靶区内径（D）等,使用SPSS 13.0的曲线估计和线性回归分析方法,得到计算阈值的公式,并以此对29个经病理检查确诊的肺癌原发灶或转移淋巴结进行肿瘤靶区勾画,求出体积,比较PET和CT图像勾画的体积间的差别.结果 通过分析水模数据,得出阈值与靶区的大小呈负相关,与靶区的SUVmax呈负相关,与SUVbg呈正相关,阈值的计算公式为TH%=33.1%＋46.8%×SUVbg/SUVmax＋13.9%/D,r=0.994.通过对29个病灶进行比较,发现PET和CT勾画的平均大体肿瘤体积（GTV）分别是（7.36±1.62）ml和（8.31±2.05）ml,两者间差异无统计学意义（t=-1.26,P＞0.05）.结论 靶区的大小、SUVmax及SUVbg均会影响靶区勾画阈值;通过公式TH%=33.1%＋46.8%×SUVbg/SUVmax＋13.9%/D可对不同肿瘤计算合适的阈值.按此公式PET和CT勾画的靶区无明显差异.     

呼吸门控PET/CT对于肺癌放疗靶区勾画的指导

目的 目的通过对肺部肿瘤进行呼吸门控PET/CT研究,给予肺部肿瘤放疗靶区勾画指导,最终使患者接受合理的照射靶区。 方法 对20个恶性结节进行呼吸门控PET/CT与常规PET/CT采集,比较肺部不同位置结节的平均四维PET体积与三维PET体积的差别,以及平均四维CT体积与三维CT体积的差别。以平均四维体积与三维体积的相对差值作为体积间的差异, 分别从结节位置、运动幅度研究其对四维体积与三维体积的影响。 结果 用两种方法测得的平均四维PET体积比三维PET体积大17.2%。体积相对差值与结节呼吸运动幅度及结节位置有关。下肺和肺门病灶平均四维PET体积与三维PET体积的平均差值为26.5%,远远大于上肺和胸膜病灶的平均差值（2.7%）。当结节呼吸运动幅度大于3 mm时,四维与三维PET体积差值的平均值为24.3%;小于3 mm时,平均值为1.8%。平均四维CT体积比三维CT体积大3.9%,体积差值范围为0.2~5.9 cm3,体积比值为1.10依0.32。只有在下肺,平均四维CT体积明显大于三维CT体积,平均差值为11.3%。 结论 对于靠近肝脾的下肺结节,用平均四维PET勾画肿瘤靶区更精确些;对于肺门周围的结节,考虑平均四维PET体积作为肿瘤靶区;对于上肺和胸膜的结节,建议采用低剂量呼吸门控扫描且已经考虑了呼吸运动的平均四维CT体积勾画靶区。     

核素显像法估测不同条件下甲状腺模型体积计算方法的探讨

目的 探讨在核素平面显像条件下,Allen法和椭球体法对估测不同体积、不同放射性活度甲状腺模型体积的影响.方法 向甲状腺气球模型内注入不同体积和不同放射性活度的99Tcm O4- 溶液,并置入有机玻璃制成的颈部模型中,内充稻米模拟甲状腺颈部软组织吸收,进行核素平面显像.用Allen法和椭球体法在不同本底扣除水平下计算甲状腺模型体积,并将其与实际体积相比较,计算误差.结果 在99TcmO4-溶液为7.4和18.5MBq条件下,当甲状腺模型体积为20～30 ml时,用Allen 法,本底扣除20％,测量值误差最小,其相对误差均值为10.04％,误差范围为-19.23％～11.25％;当模型体积为40～80 ml时,用椭球体法,本底扣除20％,测量值误差最小,其相对误差均值为13.06％,误差范围为-21.41％ ～39.45％;当模型体积为90～110 ml时,用Allen法,本底扣除20％,测量值误差最小,其相对误差均值为8.12％,误差范围为- 11.05％～ 6.66％.在37.0和74.0 MBq条件下,当甲状腺模型体积为20～30 ml时,用Allen法,本底扣除20％,测量值误差最小,其相对误差均值为5.30％,误差范围为-1.25％～-11.73％;当模型体积为40～80 ml时,用椭球体法,本底扣除20％,测量值误差最小,其相对误差均值为11.74％,误差范围为- 30.36％～9.23％;当体积为90～ 110 ml 时,用Allen法,本底扣除15％,测量值误差最小,其相对误差均值为7.21％,误差范围为- 13.76％～1.46％.结论 用核素平面显像估测甲状腺模型体积时,体积大于90 ml或小于40 ml时用Allen 法,本底扣除20％时(体积大于90 ml、活度为37.0和74.0 MBq时本底扣除15％),测得的体积误差较小;体积在40～ 80 ml时,利用椭球体法,本底扣除20％,测得的体积误差较小.     

胸部模型~(18)F-FDG双探头符合显像实验研究

目的　评价18F 脱氧葡萄糖 (FDG)双探头符合线路显像对肺部结节的探测效果。方法用胸部模型作双探头符合显像。结果　符合计数率足够时 ,衰减校正 (AC)和非衰减校正 (NOAC)均能见到≥ 11mm的球体 ,AC的靶 /本底 (T/B)比值小于NOAC ,大结节的T/B值比小结节高。增大T/B值则结节的分辨率提高。随着符合计数率的减低 ,NOAC仅能发现≥ 15mm的球体 ,而AC能发现所有的球体。结论　符合计数率适当时产生的图像最佳 ,AC比NOAC能发现更小的结节。     

18F-FDG PET/CT代谢体积与病理体积对比确定宫颈癌最大标准摄取值的最佳百分阈值

目的 通过18F-氟代脱氧葡萄糖正电子发射型计算机断层扫描仪(18F-FDG PET/CT)代谢体积与病理体积的比较,确定宫颈癌最大标准摄取值(SUMmax)的最佳百分阈值.方法 12例宫颈癌患者术前行PET/CT,经PET图像选取肿瘤SUVmax的10％、15％、20％、25％、30％、35％、40％、45％、50％等不同阈值勾画肿瘤边界,生成相应的PET大体肿瘤体积(PET GTV).术后进行病理切片,确定每层切片肿瘤边缘及面积,由面积乘以切片厚度计算每张切片的肿瘤体积,累积所有切片的肿瘤体积作为全部肿瘤的病理大体体积(病理GTV).将与肿瘤病理GTV最接近的PET GTV确定为最佳PET GTV值,将其对应的SUVmax阈值称为最佳百分阈值.结果 12例患者的最佳SUVmax阈值为40.83％±6.34％(30％～50％).以SUVmax的41％阈值勾画肿瘤边界所得PET GTV与病理GTV比较,差异无统计学意义(P=0.352),并且两者有较好的相关性(r=0.99,P=0.000).结论 通过病理体积确定的PET最佳SUVmax阈值能准确指导宫颈癌靶区的勾画,对提高三维适形调强放疗疗效具有重要意义.     

根据本底半自动化确定肿瘤内靶区:模型实验

目的根据本底标准化摄取值(SUV)计算肺肿瘤内靶区(ITV)SUV阈值,并评价其可行性。材料与方法 3个空心插件固定在圆桶底部,空心插件与圆桶分别充满55.06 k Bq/ml和5.37 k Bq/ml 18F-FDG溶液以模拟肿瘤与肺组织。以三维运动滑台驱动该模型模拟呼吸运动,最大位移10.9 mm、21.8 mm、43.7 mm。采集模型二维PET/CT图像。记肺本底SUV为±SD,以+3SD作为确定ITV的阈值,以真实ITV和测量ITV的Dice相似系数(DSC)和容积恢复系数(VRC)为评价指标,并与SUV2.5、35%SUVmax、41%SUVmax、a×m SUV70+b×、0.42×(SUVmax+)及Riegel等根据肿瘤体积、靶本底比及肿瘤运动幅度确定SUV阈值的方法进行比较,分析各方法的ITV、DSC和VRC。结果 3个肿瘤模型共9个ITV真实值分别为134.3 ml、166.1 ml、223.5 ml、86.6 ml、108.5 ml、150.7 ml、32.3 ml、43.8 ml、63.6 ml。采用Riegel等的方法测得ITV与真实值差异无统计学意义(t=-0.48,P>0.05)。其他6种SUV阈值法测量ITV与真实值差异有统计学意义(t=-5.11~2.76,P<0.05)。+3SD和Riegel等的方法制订的ITV的DSC和VRC分别为0.75~0.92、0.69~0.93和0.82~0.97、0.74~0.96,差异无统计学意义(t=-0.73,P>0.05),但大于其他5种方法所得值。结论根据本底确定的SUV阈值(+3SD)具有描绘肺癌ITV的潜力,可以为放射治疗提供ITV的参考范围。     

基于深度学习的计算机辅助诊断系统对脑出血血肿体积的测量研究

目的:探讨基于深度学习的计算机辅助诊断系统(DL-CAD)对脑出血规则和不规则形态血肿体积测量的准确性与实用性。方法:收集符合纳入标准的脑出血患者120例,根据CT图像上血肿最大层面的形态分为规则组和不规则组各60例;分别采用itk-snap软件手工勾画、2/3Sh法、Coniglobus公式法及DL-CAD测量血肿体积;以itk-snap软件手工勾画作为血肿体积测量的金标准,采用两两配对t检验比较各种方法测量的血肿体积。结果:4种方法对规则及不规则血肿的测量结果比较,差异均有统计学意义(均P<0.05)。对于规则血肿,与itk-snap软件手工勾画测得的血肿平均体积相比,2/3Sh法平均误差为7.58%,Coniglobus公式法为13.15%,DL-CAD为4.11%;对于不规则血肿,与itk-snap软件手工勾画测得的血肿平均体积相比,2/3Sh法平均误差为8.37%,Coniglobus公式法为30.99%,DL-CAD为6.05%。结论:DL-CAD对规则和不规则脑出血血肿体积测量的结果较2/3Sh法、Coniglobus公式法更准确,能减少测量误差,对于不规则血肿测量的临床意义更明显。     

18F-FDG符合线路SPECT/CT显像对乳腺癌腋窝淋巴结转移的诊断价值

目的探讨18F-FDG符合线路SPECT/CT显像半定量分析法预测乳腺癌腋窝淋巴结转移的最佳阈值。资料与方法以58例行腋窝淋巴结清扫术的乳腺癌患者为研究对象,18F-FDG符合线路SPECT/CT测量腋窝淋巴结(L)与对侧相应部位腋窝本底(B)最大放射性计数比值(L/B值)。以病理为"金标准",通过ROC曲线建立预测乳腺癌腋窝淋巴结转移的最佳阈值,将最佳阈值下的判定结果与病理结果行一致性检验。结果 58例患者共检测到119枚与手术区匹配的淋巴结(直径≥8mm)。L/B值的ROC曲线下面积为0.938,最佳阈值为2.22。采用L/B值≥2.22预测腋窝淋巴结转移的灵敏度、特异度、阳性预测值、阴性预测值分别为88.9%、97.9%、98.5%、85.2%,与病理诊断的一致性较好(Kappa=0.862,P<0.05)。结论采用L/B值≥2.22作为预测直径≥8mm的腋窝淋巴结转移的标准具有较高的准确性,可用于腋窝淋巴结转移的评估。     

MRI与CT成像差异对鼻咽癌T分期以及原发肿瘤靶区体积影响的研究

目的 探讨鼻咽癌MRI和CT成像差异对鼻咽癌T分期的影响及对原发肿瘤靶区体积的影响.资料与方法 比较101例经病理诊断为鼻咽低分化鳞癌的患者的MRI和CT表现,应用其差异比较鼻咽癌靶区的体积对放射治疗效果的影响.结果 咽后淋巴结、头长肌、蝶骨、枕骨斜坡、鼻窦等处的病灶在MRI的发现率高于CT(P<0.05).对鼻咽癌的T分期,MRI和CT之间有差异(P<0.05).根据MRI表现勾画的鼻咽癌靶区体积大于根据CT表现勾画的鼻咽癌靶区体积(P<0.05).结论 MRI对发现鼻咽癌、鼻咽癌分期及勾画鼻咽癌原发肿瘤靶区体积优于CT.     

Validation of ultrafast computed tomographic left ventricular volume measurement

Left ventricular volume has been measured with ultrafast computed tomography. However, the accuracy with which this can be done is unknown. We therefore imaged with ultrafast computed tomography 11 rectangular phantoms, 20 to 225 ml, and 17 left ventricular casts, 15 to 112 ml. Two observers planimetered serial tomographic images and computed volume from sequential tomograms. There was no significant inter- or intraobserver difference in measurement of phantoms. Deviation of ultrafast computed tomographic volume from true phantom volume was -0.1 +/- 3.5% SD, range 9.0 to -7.6%. Correlation of true phantom volume with ultrafast computed tomographic volume was 0.99, SEE = 1.9 ml. No significant difference was observed between merged and single ultrafast computed tomographic scanning sequences. Left ventricular cast volume determined by ultrafast computed tomography deviated from true volume by 6% +/- 20%, range 54% to -45%. Correlation of true volume with ultrafast computed tomographic volume was 0.99, SEE = 5.1 ml. There was no interobserver significant difference in measurement of left ventricular cast volume. Correlation between ultrafast computed tomographic volume and cineradiographic volume of the same left ventricular casts was 0.99, SEE = 4.4 ml. Thus, phantom volumes can be measured accurately without significant intra- or interobserver variation. Merged scanning sequences did not influence volume determination. Left ventricular cast volume determination was comparable to that obtained with cineradiography.     

Segmentation of PET volumes by iterative image thresholding.

The segmentation of metastatic volumes in PET is usually performed by thresholding methods. In a clinical application, the optimum threshold obtained from the adaptive thresholding method requires a priori estimation of the lesion volume from anatomic images such as CT. We describe an iterative thresholding method (ITM) used to estimate the PET volumes without anatomic a priori knowledge and its application to clinical images. METHODS: The ITM is based on threshold-volume curves at varying source-to-background (S/B) ratio acquired from a body phantom. The spheres and background were filled either with (18)F-FDG or Na(124)I ((124)I). These calibrated S/B-threshold-volume curves were used in estimating the volume by applying an iterative procedure. The ITM was validated with a PET phantom containing spheres and with 39 PET tumors that were discernable on CT by using whole-body (18)F-FDG (15 patients) and (124)I PET/CT (9 patients): The measured S/B ratios of the lesions were estimated from PET images, and their volumes were iteratively calculated using the calibrated S/B-threshold-volume curves. The resulting PET volumes were then compared with the known sphere inner volume and CT volumes of tumors that served as gold standards. RESULTS: Phantom data analysis showed that the S/B-threshold-volume curves of (18)F-FDG and (124)I were similar. The average absolute deviation (expressed as a percentage of the expected volume) obtained in the PET validation phantom was 10% for volumes larger than 1.0 mL; sphere volumes of 0.5 mL showed a significantly larger deviation. For patients, the average absolute deviation for volumes between 0.8 and 7.5 mL was about 9% (31 lesions), whereas volumes larger than 7.5 mL showed an average volume mismatch of 15% (8 lesions). CONCLUSION: The ITM sufficiently estimated the clinical volumes in the range of 0.8-7.5 mL; volumes larger than 7.5 mL showed greater deviations that were still acceptable. These findings are associated with the limitation of the ITM. The ITM is especially useful for lesions that are only visible on PET. As a consequence, the lesion dosimetry is feasible with sufficient accuracy using PET images only.     

Flat panel detector-based volumetric computed tomography (fpVCT): performance evaluation of volumetric methods by using different phantoms in comparison to 64-multislice computed tomography

OBJECTIVES: Evaluation of a silicon-based flat panel volumetric computed tomography (fpVCT) and multislice CT in terms of volumetry of phantoms with different algorithms. Furthermore, to compare the different volumetric analysis methods themselves. MATERIALS AND METHODS: Four phantoms of different materials have been scanned with fpVCT (GE prototype with circular gantry with 2 aSi/CsI flat panel detector) and a 64-slice spiral CT (MSCT: LightSpeed VCT). Three spherical phantoms of different materials and 1 phantom with an irregular shape were evaluated. True volumes were calculated in dependence from the diameter or by water displacement method. Imaging parameters (80 kVp, 100 mA) and the position of the phantoms were identical in both techniques. After reconstruction of the images different algorithms have been used 4 times for each phantom. These analysis methods have been performed: Region growing, threshold method, planimetry, 3-dimensional volumetry measurement by using the equation of an ellipsoid (ellipse) and an advanced lung analysis modus [single advanced lung analysis (ALA)]. The mean values and the standard deviations have been evaluated and compared with the true volumes. RESULTS: In all phantoms fpVCT showed better results with lower deviations from the true values than in MSCT, especially for small volumes of the phantoms. However, the results of the ALA single method demonstrated no significant difference between the fpVCT and MSCT. The comparison of the different analysis methods revealed that 3-dimensional measurement with the ellipse method was the worst method for volume estimation, especially for the irregularly formed phantom. CONCLUSION: fpVCT was superior to MSCT in the volumetry of small objects. The ellipse method has been shown to be the worst for volumetry with the highest relative deviations from the true volume value. The single ALA method shows the lowest standard deviation thereby revealing a reproducible volumetric method for small nodules. However, further future developments of volumetric analysis methods are necessary to use them accurately in daily routine. Due to the truly isotropic volume data set with high spatial resolution fpVCT is a powerful tool for the volumetry of small nodules.     

饮水排尿再充盈延迟显像在膀胱病灶PET／CT检查中的价值

目的探讨提高SUVmax显示阈值结合大量饮水排尿后充盈膀胱延迟显像在^18F—FDGPET／CT诊断膀胱病灶中的价值。方法回顾性分析2007年7月至2012年10月因可疑膀胱占位和膀胱肿瘤治疗后（保留膀胱）行^18F—FDGPET／CT显像的患者63例[男55例,女8例,平均年龄69．1岁],常规显像后患者饮水1500～2000ml,觉憋尿时排尿,重复3次后再次充盈膀胱行盆腔延迟显像。对常规显像图进行2次阅片分析,第2次是对提高SUVmax显示阈值（从6—8至8～20）后的显像图再分析。所有患者经病理活组织检查或随访（〉6个月）确诊。观察常规显像与延迟显像尿液SUVmax及膀胱病灶^18F—FDG代谢的变化。采用配对样本t检验分析数据。结果常规显像和延迟显像尿液的SUVmax分别为15．11±11．11和4．73±2．00,差异有统计学意义（t=4．15,P〈0．01）。经病理及临床随访,63例患者中,发现膀胱病变18例（恶性15例,良性3例）,均为PET／CT检出,3例PET／CT假阳性中,2例无^18F—FDG代谢增高（良性）,1例为炎性反应。余45例PET／CT显像膀胱未见明显异常的患者经临床影像学随访6个月以上均未发现病变。16个病灶（16例患者）表现为^18F—FDG代谢增高,其中15例为膀胱癌原发或复发病灶,1例为炎性反应。16例PET显像高代谢病灶中,常规显像SUVmax显示阈值范围下分析,有18．8％（3／16）为阳性;提高SUVmax显示阈值范围后43．8％（7／16）为阳性。结论提高SUVmax显示阈值结合大量饮水排尿后再次充盈膀胱行延迟显像用于可疑膀胱肿瘤及膀胱肿瘤治疗后的^18F—FDGPET／CT显像,可有效提高膀胱病灶的检出率和诊断准确性。     

A gradient-based method for segmenting FDG-PET images: methodology and validation

Purpose A new gradient-based method for segmenting FDG-PET images is described and validated. Methods The proposed method relies on the watershed transform and hierarchical cluster analysis. To allow a better estimation of the gradient intensity, iteratively reconstructed images were first denoised and deblurred with an edge-preserving filter and a constrained iterative deconvolution algorithm. Validation was first performed on computer-generated 3D phantoms containing spheres, then on a real cylindrical Lucite phantom containing spheres of different volumes ranging from 2.1 to 92.9 ml. Moreover, laryngeal tumours from seven patients were segmented on PET images acquired before laryngectomy by the gradient-based method and the thresholding method based on the source-to-background ratio developed by Daisne (Radiother Oncol 2003;69:247–50). For the spheres, the calculated volumes and radii were compared with the known values; for laryngeal tumours, the volumes were compared with the macroscopic specimens. Volume mismatches were also analysed. Results On computer-generated phantoms, the deconvolution algorithm decreased the mis-estimate of volumes and radii. For the Lucite phantom, the gradient-based method led to a slight underestimation of sphere volumes (by 10–20%), corresponding to negligible radius differences (0.5–1.1 mm); for laryngeal tumours, the segmented volumes by the gradient-based method agreed with those delineated on the macroscopic specimens, whereas the threshold-based method overestimated the true volume by 68% (p = 0.014). Lastly, macroscopic laryngeal specimens were totally encompassed by neither the threshold-based nor the gradient-based volumes. Conclusion The gradient-based segmentation method applied on denoised and deblurred images proved to be more accurate than the source-to-background ratio method. The first two authors (Xavier Geets and John A. Lee) have equally contributed to this paper.     

CT评价胸腔积液量准确性的实验研究

目的评价CT测算胸腔积液量的准确性。方法采用GE—sytec 4000i全身CT扫描系统，对注水肺脏模型进行扫描。选取右侧肺脏共作15次测量。由一名熟练的CT操作人员在积液最明显的一层上用轨迹手工圈划出积液的完整轮廓，预设感兴趣区的CT值上下限范围0-20 HU，采用计算机体积测算功能，计算出各层满足上述要求的感兴趣区图像总体积。结果肺脏模型体积CT测值与实际注水量的散点图呈直线趋势，R^2=1.000。回归系数t检验的t值=681、077，P=0．0001（P〈0.001），可认为肺脏模型体积CT测值与实际注水量之间有直线关系；直线回归方程为：Y=-0．238＋0．999X。肺脏模型体积的标准差为893．27504，实际注水量的标准差为894．42719。肺脏模型体积CT测值与实际注水量的相关分析表明，肺脏模型体积CT测值与实际注水量高度相关（P〈0．001）。结论CT能够准确测量胸腔积液量，它有可能替代传统X线的粗略估算。     

三维DSA距离测量准确性的模体定量评价研究

目的：运用模体定量评估三维DSA距离测量的准确性,以指导临床工作。方法：应用模拟动脉瘤模体和动脉狭窄模体,改变不同的扫描野、重建矩阵、模体方向来研究三维空间距离测量的准确性。通过对模体中球体和圆柱体三维容积重建图像尺寸测量与模体实际尺寸进行对比评估。结果：在三维图像重建中不同的扫描野、重建矩阵、模体方向均能清晰显示圆柱体、球体影像及模拟狭窄的程度。随着扫描野的缩小,对球体直径和狭窄直径的测量精度提高,对于圆柱体长度测量元变化。重建矩阵加大,球体直径测量误差减少（1283最大为0．36mm,2563最大为0．12mm）。圆柱体狭窄百分率测量误差大约为3％。结论：当选用合适的图像成像参数和后处理方法时,利用重建后的三维图像测量动脉瘤的大小和动脉狭窄的程度是相当可靠的。     

256层螺旋CT双时相重建评估左心室收缩功能的可行性研究

目的：通过与超声心动图检查对比,评估256层螺旋C T冠状动脉成像双时相重建评估左心室收缩功能可行性。方法回顾性分析临床怀疑冠心病62例患者的冠脉C T影像学及超声心动图检查资料。采用多时相重建（间隔5％R-R间期）及双时相重建（同步记录心电图波形选择时相进行重建分析,即Q波峰开始时相定义为舒张末期,T波升支中点开始扫描时相定义为收缩末期）分析分别获得左心室舒张末期容积（LVEDV）、左心室收缩末期容积（LVESV）、左心室每搏输出量（LVSV）、左心室射血分数（LVEF）,并与超声心动图检查结果分别进行对比。所有数据运用 MedCalc V11.4.2统计软件处理,P ＜0．05具有统计学差异。结果62例患者均顺利完成检查。双时相及多时相分析所得左心室功能各参数与超声心动图检查结果均具有良好一致性。两种方法均与超声心动图检查具有良好相关性（0．838＜ r ＜0.997）,但运用Bland-Altman分析发现与CT多时相分析相比,双时相重建分析LVEDV、LVESV、LVSV、LVEF值与超声心动图结果之间差异更小（CT双时相-超声差值分别为（6．9±8．9）ml/m2、（0．9±2．6）ml/m2、（6．0±9．0）ml/m2、（1．1±3．6）％;CT多时相-超声LVEDV、LVESV、LVSV、LVEF差值分别为（-7．2±16．5）ml/m2、（5．4±13．1）ml/m2、（-12．6±17．2）ml/m2、（-8．5±10．9）％。结论冠脉CT双时相左心室收缩功能重建分析结果与超声心动图结果具有良好相关性,能够满足临床对左心室收缩功能分析的需要,值得进一步研究与应用。