ISSN 1004-4140
CN 11-3017/P

CT增强定量参数预测肾透明细胞癌WHO/ISUP分级

张晓金, 翟建, 张虎, 谢闵, 吴树剑, 过永

张晓金, 翟建, 张虎, 等. CT增强定量参数预测肾透明细胞癌WHO/ISUP分级[J]. CT理论与应用研究, 2023, 32(6): 746-752. DOI: 10.15953/j.ctta.2022.253.
引用本文: 张晓金, 翟建, 张虎, 等. CT增强定量参数预测肾透明细胞癌WHO/ISUP分级[J]. CT理论与应用研究, 2023, 32(6): 746-752. DOI: 10.15953/j.ctta.2022.253.
ZHANG X J, ZHAI J, ZHANG H, et al. Prediction of WHO/ISUP Grading of Renal Clear Cell Carcinoma by Quantitative Parameters of CT Enhancement Scanning[J]. CT Theory and Applications, 2023, 32(6): 746-752. DOI: 10.15953/j.ctta.2022.253. (in Chinese).
Citation: ZHANG X J, ZHAI J, ZHANG H, et al. Prediction of WHO/ISUP Grading of Renal Clear Cell Carcinoma by Quantitative Parameters of CT Enhancement Scanning[J]. CT Theory and Applications, 2023, 32(6): 746-752. DOI: 10.15953/j.ctta.2022.253. (in Chinese).

CT增强定量参数预测肾透明细胞癌WHO/ISUP分级

详细信息
    作者简介:

    张晓金: 女,芜湖市第二人民医院副主任医师,主要从事腹部影像学研究,E-mail:252394498@qq.com

    通讯作者:

    张虎: 男,芜湖市第二人民医院主治医师,主要从事CT、MRI临床应用研究,E-mail:m18055373782@163.com

  • 中图分类号: R  814;TP  391

Prediction of WHO/ISUP Grading of Renal Clear Cell Carcinoma by Quantitative Parameters of CT Enhancement Scanning

  • 摘要:

    目的:探讨CT增强定量参数术前预测肾透明细胞癌(ccRCC)世界卫生组织/国际泌尿病理学会(WHO/ISUP)分级的价值。方法:连续搜集行手术治疗的98例ccRCC患者临床和CT增强资料,根据WHO/ISUP分级分为低级别组(76例)和高级别组(22例)。比较CT增强定量参数两组间差异及各参数预测ccRCC WHO/ISUP分级的诊断效能,并进行外部验证,找寻泛化能力最佳的CT增强定量参数。结果:两组间皮质期CT值、皮质期净增值、皮质期强化率、实质期CT值、实质期净增值、实质期强化率差异均有统计学意义,AUC值分别依次为0.834、0.871、0.900、0.707、0.678和0.762;截断值分别依次为123.5 HU、71 HU、0.73、87.5 HU、54 HU、0.67;皮质期强化率诊断效能最高,AUC=0.900,敏感度为0.842,特异度为0.864;外部验证结果显示皮质期强化率诊断效能(AUC=0.867)优于皮质期CT值(AUC=0.735)、皮质期净增值(AUC=0.709),Z值分别为 2.134和2.417。结论:CT增强定量参数可用于预测ccRCC WHO/ISUP分级,皮质期强化率是诊断效能最高、泛化能力最佳的CT增强定量参数。

    Abstract:

    Objective: To investigate the potential of CT-enhanced quantitative parameters for preoperative prediction of WHO/ISUP grading for renal clear cell carcinoma (ccRCC). Methods: The study involved collecting clinical and CT-enhanced data of 98 patients with ccRCC, who were then classified into low level group (76 cases) and high level group (22 cases) based on the WHO/ISUP classification. Differences in CT-enhanced quantitative parameters between the two groups were compared, and the diagnostic efficacy of each parameter for predicting ccRCC WHO/ISUP grading was evaluated. External verification was conducted to identify CT-enhanced quantitative parameters with the best generalization ability. Results: There were significant differences in the CT value, net increment, and enhancement rate in both cortical and substantive phases between the two groups. The AUC values were 0.834, 0.871, 0.900, 0.707, 0.678, and 0.762, respectively. The cut-off values were 123.5 HU, 71 HU, 0.73, 87.5 HU, 54 HU, 0.67, respectively. The diagnostic efficacy of cortical enhancement rate was the highest with an AUC of 0.900, a sensitivity of 0.842, and a specificity of 0.864. The external validation results revealed that the diagnostic efficacy of cortical phase enhancement rate (AUC=0.867) was better than that of cortical phase CT (AUC=0.735) and cortical phase net increment (AUC=0.709). The Z values were 2.134 and 2.417, respectively. Conclusion: The quantitative parameters of CT enhancement can be used to predict ccRCC WHO/ISUP grading. Cortical phase enhancement rate is the parameter with the highest diagnostic efficiency and the best generalization ability.

  • 随着年龄的增长,腰椎退行性变及椎间盘病变日趋增多,CT检查能及时发现诊断腰椎病变并能随访治疗效果,但CT检查辐射问题一直为人们所关注,随着患者受辐射剂量的增加,癌症的发生概率会增大,腰椎CT扫描范围包括性腺,而人体性腺对辐射最敏感,所以开展低剂量腰椎CT检查非常必要。

    以往研究均是通过降低管电压或者降低管电流来降低辐射剂量,因腰椎体层较厚,降低管电压或管电流会导致图像噪声增加。本文为解决腰椎CT高辐射剂量及图像噪声偏高的问题,采用最新的能谱纯化技术结合高级模拟迭代重建(ADMIRE)技术,探讨如何更好的优化腰椎CT检查的图像质量和降低辐射剂量。

    选取2021年8月至2022年5月因腰痛来我院行腰椎CT检查的患者,在检查前计算患者的体质量指数(bodymassindex,BMI),BMI=体重(kg)/身高(m)2。纳入年龄在25~65岁,BMI在18.5~25 kg/m2的患者,排除有腰椎手术史和腰椎畸形及有椎体金属植入物的患者,共收集88例。对照组(A组)、试验组(B组)每组44例。

    A组与B组平均年龄分别为(45.9±12.1)岁和(47.2±13.8)岁。两组间年龄差异无统计学意义,A组与B组平均BMI分别为(20.1±2.89)kg/m和(21.40±3.50)kg/m

    采用德国SOMATOM Force第3代双源CT,扫描范围从胸12椎体至骶1椎体。扫描参数:对照组(A组)管电压120 kV,参考管电流350 mAs;试验组(B组)管电压Sn 150 kV,参考管电流350 mAs,其他扫描参数均一致。

    重建采用高级模拟迭代重建算法(ADMIRE),重建等级3级,重建薄层图像,层厚1 mm,层间距0.60 mm,软组织窗采用软组织算法,卷积核Br40,骨窗采用骨算法,卷积核Br64,重建图像窗宽,窗位分别为350 HU和50 HU(软组织窗)、2500 HU和800 HU(骨窗)。所有图像重建完成后自动发至西门子Syngovia VB20A后处理工作站。

    由1名主管技师从工作站中取L3椎体正中层面,在软组织窗上测量腰大肌与竖脊肌的CT值和噪声,腰大肌的噪声为SD1,竖脊肌的噪声为SD2,噪声值用对应所测的标准差表示,并计算信噪比(SNR):

    $$ {\rm{SNR}}=腰大肌\;{\rm{CT}}\;值/{\rm{SD}}1。$$ (1)

    由3名副主任及以上诊断医师双盲法进行评分。评价L3/4层面椎间盘、椎间孔、黄韧带、硬膜囊及小关节图像质量。评价标准[1]:2分(软组织结构清晰,其边缘清楚,无伪影,且诊断明确);1分(软组织结构清晰,边缘欠清,有轻度伪影,但尚可诊断);0分(软组织结构不清,边缘模糊,伪影较重,不能进行诊断)。

    统计设备记录的容积CT剂量指数(CT dose index volumes,CTDIvol)及剂量长度乘积(dose length product,DLP),并计算有效辐射剂量(effective dose,ED)[2],计算公式:

    $$ {\rm{ED}}={\rm{DLP}}\times k(k=0.011\;{\rm{mSv}}\cdot{\rm{mGy}}\cdot{\rm{cm}})。$$ (2)

    采用SPSS 26.0软件对数据进行统计学分析。连续性数据非正态分布数据两组间比较采用Mann-Whitney U检验,用中位数及四分位数(M(Q25,Q75))表示。双侧检验,以P<0.05为差异有统计学意义。

    采用组内相关系数(intraclass correlation coefficient,ICC)对3位诊断医师的评分结果一致性进行分析。ICC介于0和1之间,ICC大于0.75表示一致性较好。

    两组图像腰大肌的CT值、竖脊肌的CT值和噪声(SD2)、SNR均存在统计学差异,而腰大肌的噪声(SD1)不具有统计学差异(表1);图1为120 kV轴位上噪声和CT值测量及矢状位重组图,图2为Sn 150 kV下的轴位上噪声和CT值测量测量及矢状位重组图。

    表  1  A组和B组图像质量客观评价表
    Table  1.  Objective evaluation of image quality in groups A and B
    项目 组别统计检验
    A组B组ZP
       腰大肌/HU53.00(48.70~56.00)47.90(43.70~51.00)2.7410.016
       SD15.73(4.83~6.83)5.09(4.69~5.24)1.9040.057
       竖脊肌/HU52.00(46.2~55.00)43.50(38.20~51)3.511<0.001
       SD25.41(5.27~5.98)4.56(3.62~5.63)3.964<0.001
       SNR9.12(7.88~10.51)9.86(7.95~10.02)-0.693 0.488
    下载: 导出CSV 
    | 显示表格
    图  1  管电压120 kV下CT值和噪声测量及矢状位重组图(重组层厚1 mm、间隔0.6 mm)
    Figure  1.  CT value, noise measurement, and sagittal position recombination at 120 kV tube voltage (recombination layer thickness 1 mm, interval 0.6 mm)
    图  2  管电压Sn 150 kV下CT值和噪声测量及矢状位重组图(重组层厚1 mm、间隔0.6 mm)
    Figure  2.  CT value, noise measurement, and sagittal position recombination at tube voltage Sn 150 kV (recombination layer thickness 1 mm, interval 0.6 mm)

    3位医师对椎间盘、椎间孔、黄韧带、硬膜囊及小关节及整体图像质量评价均无统计学差异(表2),说明两组图像质量医师主观评价无差异,且均能符合医师诊断要求。

    表  2  3位诊断医师的主观评分统计分析表
    Table  2.  Statistical analysis of the subjective scores from the three doctors interpreting the computed tomography images
    指标组别P
    A组B组
    椎间盘   2.00±0.002.00±0.00>0.999
    椎间孔   1.98±0.151.98±0.15 0.156
    黄韧带   1.95±0.212.00±0.00 0.562
    硬膜囊   1.98±0.151.95±0.21>0.999
    小关节图像 2.00±0.002.00±0.00 0.320
    整体图像质量2.00±0.002.00±0.00>0.999
    下载: 导出CSV 
    | 显示表格

    两组辐射剂量DLP、ED有统计学差异,两组辐射剂量差异明显,B组DLP值比A组降低了32.27%,B组ED值比A组降低了30.31%(表3)。

    表  3  A组和B组辐射剂量统计表
    Table  3.  Radiation dose in groups A and B
    项目组别统计检验
    A组B组ZP
       mAs333.00(300.00~362.00)237.50(222.00~261.00)7.885<0.001
       CTDIvol14.75(13.65~16.00)6.57(5.20~7.23)8.015<0.001
       DLP413.60(351.00~425.50)280.13(230.89~327.20)6.946<0.001
       ED4.55(3.86~4.68)3.08(2.54~3.60)6.946<0.001
    下载: 导出CSV 
    | 显示表格

    腰椎因体层相对较厚,需要高管电压来增加X线的穿透力,高管电流来降低图像的噪声,造成腰椎CT辐射剂量往往较高,以往研究都是通过降低管电流来降低辐射剂量。随着设备和技术的进步,众多新的降低辐射剂量的技术出现,如:低管电压[3-4]、自动管电流[5-6]、高级迭代重建算法[7]、能谱纯化[8]等,这些技术为我们开展低剂量CT提供了条件。

    本研究B组管电压是用能谱纯化Sn 150 kV,而A组管电压是用120 kV,统计结果显示B组的辐射剂量低于A组30.31%。因为A组120 kV的X线球管是用铜和铝滤过,Sn 150 kV的X线球管是用能谱纯化技术的锡滤过,锡的原子序数比铜和铝高,锡滤过板能过滤掉X线球管的低能级射线,提高射线能量,而对人体产生辐射的主要是低能级软射线,低能级软射线以光电效应为主,大部分被人体吸收产生辐射。能谱纯化技术只保留了对人体成像有用的高能级射线,高能级射线会穿过人体相对辐射较少,所以B组辐射剂量低于A组,多学者也证实了这一说法[9-13]

    客观评价中A组肌肉的噪声要高于B组,腰大肌的噪声两组之间无统计学差异,而竖脊肌的噪声两组之间有统计学差异,此结果说明射线能量和图像噪声成正相关,也证实了Sn 150 kV的穿透力较120 kV的好。因竖脊肌处于腰大肌的下层,射线先穿过腰大肌再到竖脊肌,射线能量会因组织的阻挡发生衰减,A组射线的能量到达竖脊肌时比B组衰减更多,因衰减后的能量差异造成了噪声值的差异,故造成了两组不同肌肉之间统计学结果的差异。

    沈梓璇等[14]论述了120 kVp管电压所获得的腰椎图像质量评分以及信噪比皆较高,但辐射剂量也较大的观点。本文为了解决这一问题,首次采用Sn 150 kV用于腰椎CT检查,主观评价结果显示,3位观察者的ICC为0.829,表示为两组图像主观评价一致性较好,说明两组图像质量均满足诊断要求,主客观评价结果均证实了Sn 150 kV用于腰椎CT检查是可行的。王帅等[15]也证实Sn 150 kV能用于全腹部CT检查,且辐射剂量较低,与本文研究结果一致。

    高级模拟迭代重建,是将原始图像中的原始数据噪声投射到图像中,得到的图像是多次迭代重建后的组合,再将原始数据进行准确的图像校正,对原始数据域进行去噪及去除伪影,最后进行图像域的校正,反复迭代来降低噪声,图像空间分辨率不受影响。客观评价表中A组和B组图像的噪声均值都处于10以下,证实了高级模拟迭代重建的降噪能力。顾海峰等[16]和Schlunk等[17]也证明了迭代重建能降低噪声保证图像质量满足诊断需求。

    综上所述,采用能谱纯化Sn 150 kV结合ADMIRE,不但能有效减低辐射剂量,还可保证优质的图像质量,值得在成人腰椎CT中推广使用。

  • 图  1   男性,53岁,肾透明细胞癌

    Figure  1.   Male, 53 years old, clear cell renal cell carcinoma

    图  2   实验组CT增强定量参数预测ccRCC二分类WHO/ISUP分级的ROC曲线

    Figure  2.   ROC curve of ccRCC secondary classification based on WHO/ISUP grading scheme predicted by CT-enhanced quantitative parameters in the experimental group

    图  3   外部验证组预测ccRCC二分类WHO/ISUP分级的ROC曲线

    Figure  3.   ROC curve of the external validation group for predicting the WHO/ISUP classification of ccRCC

    表  1   低级别组和高级别组肾透明细胞癌一般资料比较

    Table  1   Comparison of general ccRCC characteristics between low- and high-grade groups

    项目  组别统计检验
    低级别组(n=76)高级别组(n=22)统计量P
      年龄/岁62.54±11.7162.91±9.17-0.136 0.892
      性别(n(%))   男性44(57.89)17(77.27)2.7260.099
       女性32(42.11) 5(22.73)
      位置(n(%))   左肾46(60.53)14(63.64)0.0700.792
       右肾30(39.47) 8(36.36)
    下载: 导出CSV

    表  2   低级别组和高级别组肾透明细胞癌CT增强定量参数比较

    Table  2   Comparison of CT-enhanced quantitative parameters of ccRCC between the low- and high-level groups

    CT增强定量参数组别统计检验
    低级别组(n=76)高级别组(n=22)tP
    皮质期CT值 143.71±32.39 103.27±23.70 6.447<0.001
    皮质期净增值98.24±27.3261.86±19.646.954<0.001
    皮质期强化率1.01±0.240.63±0.139.823<0.001
    实质期CT值 103.91±25.25 87.36±19.782.829 0.006
    实质期净增值68.26±22.4354.64±15.792.661 0.009
    实质期强化率0.82±0.220.63±0.144.736 <0.001
    下载: 导出CSV

    表  3   肾透明细胞癌CT增强定量参数诊断效能

    Table  3   Diagnostic efficacy of CT-enhanced quantitative parameters for ccRCC

    CT增强定量参数AUC95%CIP敏感度/%特异度/%
    皮质期CT值 0.8340.741~0.927<0.0010.6580.909
    皮质期净增值0.8710.782~0.960<0.0010.8160.818
    皮质期强化率0.9000.840~0.959<0.0010.8420.864
    实质期CT值 0.7070.582~0.832 0.0030.7630.727
    实质期净增值0.6780.558~0.799 0.0110.7760.545
    实质期强化率0.7620.655~0.868<0.0010.7370.773
    下载: 导出CSV
  • [1]

    SHEELA DEVI C S, SUCHITHA S, VEERENDRASAGAR R S. Evaluation of nuclear morphometry and ki-67 index in clear cell renal cell carcinomas: A five-year study[J]. Iranian Journal of Pathology, 2017, 12(2): 150−157. doi: 10.30699/ijp.2017.24873

    [2]

    MOCH H, CUBILLA A L, HUMPHREY P A, et al. The 2016 WHO classification of tumours of the urinary system and male genital organs-part a: Renal, penile, and testicular tumours[J]. European Urology, 2016, 70(1): 93−105. doi: 10.1016/j.eururo.2016.02.029

    [3]

    DELAHUNT B, EBLE J N, EGEVAD L, et al. Grading of renal cell carcinoma[J]. Histopathology, 2019, 74(1): 4−17. doi: 10.1111/his.13735

    [4] 张涛, 汪建文, 陈立芳. 肾透明细胞癌多排螺旋CT影像表现与Fuhrman分级的相关性分析[J]. 安徽医药, 2020,24(6): 1192−1194.

    ZHANG T, WANG J W, CHEN L F. Correlation analysis of the relationship between MDCT feature and Fuhrman grading in 40 patients with clear cell renal cell carcinoma[J]. Anhui Medical and Pharmaceutical Journal, 2020, 24(6): 1192−1194. (in Chinese).

    [5]

    ZHU Y H, WANG X, ZHANG J, et al. Low enhancement on multiphase contrast-enhanced CT images: An independent predictor of the presence of high tumor grade of clear cell renal cell carcinoma[J]. American Journal of Roentgenology, 2014, 203(3): 295−300. doi: 10.2214/AJR.13.12297

    [6] 高杨, 陈炜越, 陈春妙, 等. 肾透明细胞癌的CT特征与其侵袭性的相关性研究[J]. 中国中西医结合影像学杂志, 2022,20(3): 250−254, 258.

    GAO Y, CHEN W Y, CHEN C M, et al. CT features of clear cell renal cell carcinoma and its correlation with the invasiveness[J]. Chinese Imaging Journal of Integrated Traditional and Western Medicine, 2022, 20(3): 250−254, 258. (in Chinese).

    [7]

    DAGHER J, DELAHUNT B, RIOUX-LECLERCQ N, et al. Clear cell renal cell carcinoma: Validation of World Health Organization/International Society of Urological Pathology Grading[J]. Histopathology, 2017, 71(6): 918−925.

    [8] 张庆林, 庄梅香, 罗雪萍. 增强CT参数在鉴别肾脏良恶性肿瘤中的初步研究[J]. 影像科学与光化学, 2021,39(6): 845−848. doi: 10.7517/issn.1674-0475.210505

    ZHANG Q L, ZHUANG M X, LUO X P. Preliminary study of enhanced CT parameters in differential diagnosis of benign and malignant renal tumors[J]. Imaging Science and Photochemistry, 2021, 39(6): 845−848. (in Chinese). doi: 10.7517/issn.1674-0475.210505

    [9] 陈天昱, 樊树峰. Fisher判别模型在肾透明细胞癌多层螺旋CT征像及病理学WHO/ISUP分级中的价值[J]. 浙江医学, 2021,43(7): 753−756, 774. doi: 10.12056/j.issn.1006-2785.2021.43.7.2020-2256

    CHEN T Y, FAN S F. Establishment of a Fisher discriminant model for preoperative grading of renal clear cell carcinoma based on MSCT features and WHO/ISUP classification[J]. Zhejiang Medicine, 2021, 43(7): 753−756, 774. (in Chinese). doi: 10.12056/j.issn.1006-2785.2021.43.7.2020-2256

    [10] 刘阳, 朱丽, 李建春, 等. 肾透明细胞癌WHO/ISUP分级的超声预测因素分析[J]. 中华医学超声杂志(电子版), 2021,18(6): 605−610.

    LIU Y, ZHU L, LI J C, et al. Ultrasonic predictors of WHO/ISUP classification of clear cell renal cell carcinoma[J]. Chinese Journal of Medical Ultrasound (Electronic Edition), 2021, 18(6): 605−610. (in Chinese).

    [11]

    GAO J, XU Q, FU Y, et al. Comprehensive evaluation of 68 Ga-PSMA-11 PET/CT parameters for discriminating pathological characteristics in primary clear-cell renal cell carcinoma[J]. European Journal of Nuclear Medicine and Molecular Imaging, 2021, 48(2): 561−569. doi: 10.1007/s00259-020-04916-6

    [12]

    WANG X, SONG G, JIANG H, et al. Can texture analysis based on single unenhanced CT accurately predict the WHO/ISUP grading of localized clear cell renal cell carcinoma?[J]. Abdominal Radiology, 2021, 46(9): 4289−4300. doi: 10.1007/s00261-021-03090-z

    [13] 顾长青, 李陆, 孙冬雪, 等. 影像组学诺模图在术前预测肾透明细胞癌WHO/ISUP分级的应用研究[J]. 临床放射学杂志, 2022,41(10): 1915−1920.

    GU C Q, LI L, SUN D X, et al. Application of radiomic nomogram in preoperative prediction of WHO/ISUP grade of renal clear cell carcinoma[J]. Journal of Clinical Radiology, 2022, 41(10): 1915−1920. (in Chinese).

    [14]

    MA Y, GUAN Z, LIANG H, et al. Predicting the WHO/ISUP grade of clear cell renal cell carcinoma through CT-based tumoral and peritumoral radiomics[J]. Front Oncol, 2022, 12: 831112.

    [15]

    MAYER P, FRITZ F, KOELL M, et al. Assessment of tissue perfusion of pancreatic cancer as potential imaging biomarker by means of Intravoxel incoherent motion MRI and CT perfusion: Correlation with histological microvessel density as ground truth[J]. Cancer Imaging, 2021, 21(1): 13.

    [16]

    SENGUPTA S, LOHSE C M, LEIBOVICH B C, et al. Histologic coagulative tumor necrosis as a prog-nostic indicator of renal cell carcinoma aggressiveness[J]. Cancer, 2005, 104(3): 511−520. doi: 10.1002/cncr.21206

    [17]

    IANNESSI A, BEAUMONT H, HEBERT C, et al. Computer tomography-based body surface area evaluation for drug dosage: Quantitative radiology versus anthropomorphic evaluation[J]. The Public Library of Science, 2018, 13(2): e0192124.

    [18] 赵文敬, 郭君武. 低浓度低剂量对比剂结合高注射流率在肠系膜上动脉CTA中的应用[J]. 中国中西医结合影像学杂志, 2020,18(1): 87−90.

    ZHAO W J, GUO J W. Application of a low dose of contrast media combined with high injection rate to superior mesenteric artery CTA[J]. Chinese Imaging Journal of Integrated Traditional and Western Medicine, 2020, 18(1): 87−90. (in Chinese).

  • 期刊类型引用(2)

    1. 涂立冬,李雅萍. 岩土勘查技术在盐矿绿色矿山建设中的应用初探. 盐科学与化工. 2025(04): 9-12 . 百度学术
    2. 杨兆林,潘懿,白旭晨,刘禄平. 露天铁矿采空区隐蔽致灾普查与防治措施应用研究. 矿业研究与开发. 2024(09): 74-81 . 百度学术

    其他类型引用(2)

图(3)  /  表(3)
计量
  • 文章访问数:  298
  • HTML全文浏览量:  222
  • PDF下载量:  27
  • 被引次数: 4
出版历程
  • 收稿日期:  2022-12-19
  • 录用日期:  2023-03-29
  • 网络出版日期:  2023-04-03
  • 刊出日期:  2023-10-31

目录

/

返回文章
返回
x 关闭 永久关闭