能谱CT在甲状腺病变诊断及鉴别诊断中的应用研究

发布时间：2018-01-19 19:30

  本文关键词： 甲状腺病变 体层摄影术 X线计算机 能谱CT 甲状腺癌 体层摄影术 X线计算机 能谱CT 甲状腺微小癌 体层摄影术 X线计算机 能谱CT　出处：《北京协和医学院》2017年博士论文　论文类型：学位论文

【摘要】：第一部分能谱CT在甲状腺良恶性病变诊断及鉴别诊断中的价值目的对甲状腺良恶性病变的形态学征象及能谱参数进行分析,探讨能谱CT在甲状腺病变诊断及鉴别诊断中的价值。材料与方法收集2014年3月至2016年12月以甲状腺病变行颈部CT扫描的患者。采用GE Discovery 750 HD CT扫描机能谱成像模式进行扫描,获得常规混合能量图像和一组单能量图像,分别在PACS终端和AW4.6工作站进行病灶形态学基本征象的评价和能谱分析。在碘基物质图像测量病灶、正常甲状腺及颈总动脉的碘含量(Iodine Concentration,IC),在水基物质图像上测量病灶、正常甲状腺及颈总动脉的水含量(Water Concentration,WC),计算动脉标准化碘含量(NICA)、正常甲状腺标准化碘含量(NICT)和能谱曲线斜率(Slope of SpectralHU curve,λHU)。采用SPSS19.0统计软件进行统计学分析。通过受试者工作特征(ROC)曲线下面积来确定病变的诊断能力。P0.05为差异有统计学意义。采用Logistic回归分析,评价能谱参数和形态学征象联合诊断效能。结果225名患者共计230个病灶入组(良性57个病灶,恶性173个病灶),良恶性病变在边界是否清楚、是否有微小钙化和颈部可疑转移淋巴结方面差异有统计学意义(P值均0.05),根据边界不清楚、出现微小钙化、颈部可疑淋巴结转移诊断为甲状腺癌的敏感度分别为76.3%、25.4%、68.8%,特异度分别为63.2%、96.5%、94.7%,准确度分别为73.0%、43.0%、75.2%。三者联合诊断为恶性肿瘤的敏感度、特异度和准确度分别为73.4%、93.0%、82.6%。三组良性病变(甲状腺腺瘤、结节性甲状腺肿和甲状腺炎)间除IC差异有统计学意义(P0.05)外,其余各项参数差异均无统计学意义。结节性甲状腺肿与腺瘤、结节性甲状腺肿与甲状腺炎间IC差异均无统计学意义,而腺瘤IC明显高于炎症IC,差异有统计学意义(P=0.006,P0.05)。结节性甲状腺肿与恶性肿瘤、甲状腺腺瘤与恶性肿瘤在病灶IC,NICT和λHU方面差异有统计学意义(P0.05),而甲状腺炎与恶性肿瘤在所分析诸参数差异均无统计学意义(P0.05)。将IC3.2mg/ml,NICT0.55和λHU3.73作为诊断甲状腺恶性肿瘤的能谱参数指标,敏感度分别为71.1%、46.2%、68.2%,特异度分别为 68.4%、84.2%、75.4%,准确度分别为 70.4%、55.7%、70.0%。能谱参数 IC、NICT、λHU联合形态学边界不清、出现微小钙化灶及颈部可疑转移淋巴结,对恶性肿瘤的诊断效能较高,敏感度、特异度和准确度分别为86.1%、86.0%和83.9%。结论能谱CT能够定量评估甲状腺病变碘含量情况,对良恶性鉴别有一定的价值。联合能谱参数与形态学特征,对良恶性病变鉴别诊断的效能较高。第二部分不同病理类型甲状腺恶性肿瘤的能谱参数初步研究目的探讨不同病理类型的甲状腺恶性肿瘤的影像表现及能谱参数,以提高对各病理类型甲状腺恶性肿瘤的认识和诊断水平。材料与方法回顾性分析67例甲状腺恶性肿瘤(乳头状癌44例,滤泡癌2例,髓样癌9例,未分化癌7例,原发甲状腺淋巴瘤5例)的形态学表现及能谱参数。采用GE Discovery 750HD CT扫描机能谱模式进行扫描,在最佳单能量图像上对病灶进行形态学分析。采用能谱分析与测量软件对不同病理类型的病灶碘含量(IC)、水含量(WC)、能谱曲线斜率(λHU)等参数进行计算和分析,采用SPSS19.0软件进行统计学处理。结果甲状腺恶性肿瘤形态学表现为单发57例(85.1%),形态不规则46例(68.7%),边界不清楚45例(67.2%),密度不均匀48例(71.6%),出现钙化灶21例(31.3%)。不同病理类型的甲状腺恶性肿瘤的病灶IC及λHU值差异有统计学意义(P0.05),WC差异无统计学意义(P0.05)。乳头状癌、滤泡癌、髓样癌的IC及λHU值均高于未分化癌和淋巴瘤,差异均有统计学意义(P0.05),病灶IC从多到少分别为滤泡癌、髓样癌、乳头状癌、淋巴瘤及未分化癌,斜率的高低也与之一致。乳头状癌、滤泡癌、髓样癌参数两两之间在IC、λHU方面差异均无统计学意义(P0.05),淋巴瘤与未分化癌参数比较差异无统计学意义(P0.05),而乳头状癌、滤泡癌、髓样癌三组分别与淋巴瘤、未分化癌参数比较,差异有统计学意义(P0.05)。结论不同病理类型甲状腺恶性肿瘤形态学表现及能谱参数有一定差异,了解其差异有助于该类病变的诊断及鉴别诊断。第三部分能谱CT对甲状腺微小癌诊断价值的初步研究目的分析甲状腺微小乳头状癌的能谱CT影像,旨在探讨能谱CT在微小癌检出和诊断中的价值。材料与方法回顾性分析我院2015年1月至2016年1月行颈部能谱CT扫描并经手术病理证实甲状腺微小癌33例(35枚病灶),采用GE Discovery 750HD CT扫描机,通过能谱扫描和GSIViewer图像分析软件获得:140kVp混合能量图像(A组);最佳单能量图像(B组);最佳单能量图像与物质分离(碘基)图像融合获得的图像(C组)。对A、B组影像质量进行客观评价,并对3组影像检出性能进行主观评分。对所有病灶的影像表现及能谱参数进行分析和测量。使用SPSS19.0统计软件对数据进行统计学分析。结果本组病灶的最佳CNR能量水平为62～75keV,平均(65.96±4.01)keV。能谱CT最佳单能量图像的CNR高于混合能量图像(t=-5.626,P=0.000),噪声低于混合能量图像(t=12.00,P=0.000),差异均有统计学意义(P0.05)。3组影像对微小病灶的检出率分别为 A 组 91.4%(32/35)、B 组 97.1%(34/35)、C 组 100%(35/35)。三组图像主观评分分别为2.54±1.15、3.31±0.93、3.46±0.74,单能量与碘基融合影像(C组)在病灶的检出方面优于混合能量CT(A组),并与单能量影像相仿(B组)。微小癌表现为形态不规则19枚(54.3%),边缘不清楚24枚(68.6%),密度不均匀24枚(68.6%)、可见微小钙化灶(16枚,45.7%)。20例出现颈部淋巴结转移(20/33,60.6%)。病灶碘含量范围0.9～4.3mg/ml,平均2.5±1.0mg/ml,能谱曲线斜率范围-0.83～5.38,平均 2.99±1.59。结论能谱CT单能量图像较混合能量图像具有更好的图像质量,能谱CT单能量图像与碘基物质图像融合影像可为甲状腺微小癌诊断提供更多信息,有助于病灶的检出与诊断。
[Abstract]:The purpose of the first part the value of spectral CT in the diagnosis and differential diagnosis of thyroid benign and malignant lesions in the morphological features of benign and malignant thyroid lesions and spectral parameters were analyzed, to investigate the spectrum of CT in the diagnosis and differential diagnosis of thyroid lesions. Materials and methods from March 2014 to December 2016 with thyroid disease patients underwent CT scan using GE Discovery 750. HD CT scanning imaging mode scanning spectrum function, obtain conventional mixed energy images and a set of monochromatic images, respectively in the PACS terminal and AW4.6 workstation for evaluation of the basic signs of lesion morphology and energy spectrum analysis. The iodine based material image measurement of lesions, the iodine content of normal thyroid and carotid artery (Iodine Concentration, IC), was measured in the water-based material image, water content of normal thyroid and common carotid artery (Water, Concentration, WC), the calculation of dynamic The content of iodine pulse Standardization (NICA), standard normal thyroid iodine content (NICT) and energy spectrum curve slope (Slope of SpectralHU curve, 2 HU). Using the statistical analysis software SPSS19.0. The receiver operating characteristic (ROC) area under the curve to determine the diagnosis ability of.P0.05 for statistical difference meaning. Using Logistic regression analysis, evaluation of spectral parameters and morphological features of combined diagnostic efficiency. Results a total of 225 patients with 230 lesions group (57 benign lesions and 173 malignant lesions), benign and malignant lesions in the boundary is clear, whether small calcification and cervical lymph node metastasis suspected there was a significant difference (the P value was 0.05), according to the boundary is not clear, micro calcification, neck lymph node metastasis diagnosis for suspected thyroid cancer sensitivity of 76.3% and 25.4% respectively, 68.8%, specificity respectively 63.2%, 96.5%, 94.7%, accuracy Were 73%, 43%, 75.2%. three combined diagnosis of malignant tumor sensitivity, specificity and accuracy were 73.4%, 93%, 82.6%. three were benign lesions (thyroid adenoma, nodular goiter and Hashimoto thyroiditis) except IC had significant difference (P0.05), the other parameters had no statistical difference meaning. Nodular goiter with adenoma, nodular goiter and the difference of IC between thyroiditis were not statistically significant, while IC was significantly higher than that in adenoma inflammation of IC, the difference was statistically significant (P=0.006, P0.05). Nodular goiter and thyroid adenoma with malignant tumor, malignant tumor lesions in IC, NICT and the difference was statistically significant a HU (P0.05), and in the analysis of thyroiditis and malignant tumor parameters showed no significant difference (P0.05). IC3.2mg/ml, NICT0.55 and HU3.73 as a diagnosis of malignant thyroid tumor spectrum parameters The index, the sensitivity was 71.1%, respectively, 46.2%, 68.2%, the specificity was 68.4%, 75.4%, 84.2% respectively, the accuracy was 70.4%, 55.7% respectively, the 70.0%. spectrum parameters IC, NICT, HU combined with lambda morphological boundary is not clear, micro calcification and cervical lymph node metastasis is higher, suspicious, diagnostic efficacy of malignant tumor the sensitivity, specificity and accuracy were 86.1%, 86% and 83.9%. conclusion spectral CT to quantitatively assess the iodine content in thyroid disease, have a certain value for differentiating benign and malignant. Combined with spectral parameters and morphological characteristics, the high efficiency of the differential diagnosis of benign and malignant lesions. Imaging findings of different pathological types objective to investigate the spectrum of thyroid malignant tumor parameters second different pathological types of thyroid malignant tumor and spectral parameters, to improve the understanding and diagnostic level of various pathological types of thyroid malignant tumors. Materials and Methods a retrospective analysis of 67 cases of thyroid malignant tumor (44 cases, 2 cases of papillary carcinoma, 9 cases of follicular carcinoma, medullary carcinoma and 7 cases of undifferentiated carcinoma, 5 cases of primary thyroid lymphoma) the morphological and spectral parameters. Using GE Discovery 750HD CT scanning function spectral model for scanning, in the best single energy images of lesions by morphological analysis. Using spectrum analysis and measurement software focus on the iodine content of different pathological types (IC), water content (WC), energy spectrum curve slope (lambda HU) to calculate and analyze the parameters of statistical processing by using SPSS19.0 software. The results showed the morphology of thyroid malignant tumor one in 57 cases (85.1%), irregular shape in 46 cases (68.7%), the boundary is not clear in 45 cases (67.2%), uneven density in 48 cases (71.6%), appearance of calcification in 21 cases (31.3%). The different pathological types of thyroid malignant tumor lesions in IC and a HU value difference was statistically significant (P0.0 5), there was no significant difference of WC (P0.05). Papillary carcinoma, follicular carcinoma, medullary carcinoma and IC lambda HU value is higher than that of undifferentiated carcinoma and lymphoma, the differences were statistically significant (P0.05), IC lesions from more to less were follicular carcinoma, medullary carcinoma, papillary carcinoma, lymphoma and undifferentiated carcinoma, slope height also consistent with papillary carcinoma, follicular carcinoma, medullary carcinoma between 22 parameters in IC, the differences were not statistically significant in terms of lambda HU (P0.05), lymphoma and anaplastic carcinoma parameters showed no significant difference (P0.05), papillary carcinoma, follicular carcinoma the three groups were medullary carcinoma, undifferentiated carcinoma and lymphoma, parameter comparison, the difference was statistically significant (P0.05). The morphology of different pathological types of thyroid malignant tumor showed and energy spectrum parameters have certain difference, helpful to the diagnosis and differential diagnosis of such lesions the difference. The third part spectrum CT on thyroid microcarcinoma Objective to investigate the diagnostic value of cancer spectrum analysis of CT imaging of papillary thyroid microcarcinoma, aims to explore the spectrum of CT in the detection and diagnosis of small cancer. Materials and methods of analysis of our hospital from January 2015 to January 2016 for the neck spectrum CT scan and pathologically confirmed thyroid microcarcinoma 33 cases (35 foci) by GE Discovery, 750HD CT scanner, through spectrum scanning and GSIViewer image analysis software: 140kVp mixed energy images (A group); the best single energy image (group B); optimal monochromaticenergy image and separation of substances (iodine based) image fusion obtained (group C). The A. The objective evaluation of image quality of B group, and 3 groups of image detection performance. The subjective scores of all lesions imaging and spectral parameters were analyzed and measured. The data were statistically analyzed using SPSS19.0 statistical software. The results of this group of diseases 鐏剁殑鏈，

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