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临床研究
DCE-MRI结合DWI对前列腺癌Ki-67表达和Gleason评分的预测价值
周定燕 何文琪 王伟 陈梅泞 罗敏

Cite this article as: ZHOU D Y, HE W Q, WANG W, et al. The predictive value of DCE-MRI and DWI for Ki-67 expression and Gleason score in prostate cancer[J]. Chin J Magn Reson Imaging, 2024, 15(9): 94-100, 119.本文引用格式:周定燕, 何文琪, 王伟, 等. DCE-MRI结合DWI对前列腺癌Ki-67表达和Gleason评分的预测价值[J]. 磁共振成像, 2024, 15(9): 94-100, 119. DOI:10.12015/issn.1674-8034.2024.09.016.


[摘要] 目的 旨在评估动态对比增强磁共振成像(dynamic contrast-enhancement magnetic resonance imaging, DCE-MRI)结合扩散加权成像(diffusion weighted imaging, DWI)在预测前列腺癌(prostate cancer, PCa)Ki-67表达和Gleason评分中的诊断效能。材料与方法 回顾性分析了2019年1月至2023年10月自贡市第四人民医院收治的66例PCa患者的临床及影像资料。结合T2WI、DWI序列和由DWI自动计算出的表观扩散系数(apparent diffusion coeffieient, ADC),在DCE-MRI图像上手动勾画肿瘤感兴趣区(region of interest, ROI),计算ROI药代动力学参数,包括容积转运常数(volume transfer contrast, Ktrans)、速率常数(rate contrast, Kep)、血管外细胞外容积分数(extravascular extracellular volume fraction, Ve),并测量ADC值。根据靶向穿刺病理诊断Gleason评分和Ki-67表达水平,分为Ki-67高表达组(Ki-67>10%)和低表达组(Ki-67≤10%),Gleason评分低级别(GG 1~2)和高级别(GG 3~5)组。组间差异比较使用两独立样本t检验或非参数检验,采用Spearman相关分析评价DCE-MRI参数和ADC值与Ki-67、Gleason评分的相关性,并建立logistic回归模型,通过受试者工作特征(receiver operating characteristic, ROC)曲线评估诊断效能。结果 ADC值与Ki-67表达、Gleason评分均呈负相关(P<0.001),Ktrans、Kep、Ve与Ki-67表达均呈正相关(P<0.001),Ktrans、Kep与Gleason评分均呈正相关(P<0.001)。Ki-67高、低表达组Ktrans、Kep、Ve、ADC值比较差异均具有统计学意义(P<0.01)Gleason评分高、低级别组Ktrans、Kep、ADC值比较差异均具有统计学意义(P<0.01);Ki-67表达的ROC曲线分析显示,联合模型Ktrans+Kep+Ve+ADC诊断效能最好,曲线下面积(area under the curve, AUC)为0.940;Gleason评分分级的ROC曲线分析显示,联合模型Ktrans+Kep+ADC诊断效能最好,AUC为0.861。结论 DCE-MRI的药代动力学参数和ADC值相结合,在预测PCa的Ki-67表达和Gleason评分中显示出高诊断效能。联合使用DCE-MRI定量参数与ADC值可提高PCa病理分级和生物侵袭性的预测准确性。
[Abstract] Objective To evaluate the diagnostic efficacy of dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) combined with diffusion weighted imaging (DWI) in predicting Ki-67 expression and Gleason score in prostate cancer (PCa) Ki-67 expression and Gleason score.Materials and Methods A retrospective analysis of MRI data from 66 PCa patients treated at the Zigong Fourth People's Hospital from January 2019 to October 2023 was conducted. Combining T2WI, DWI sequences and the apparent diffusion coefficient (ADC) automatically calculated by DWI, the regions of interest (ROI) of the tumor was manually outlined on the DCE-MRI images, calculate ROI pharmacokinetic parameters, including volumetric transport constants (Ktrans), rate constant (Kep), extravascular extracellular volume fraction (Ve), and measure apparent diffusion coefficient values (ADC). According to the targeted puncture pathology diagnosis Gleason score and Ki-67 expression level were categorized into Ki-67 high expression group (Ki-67>10%) and low expression group (Ki-67≤10%), and Gleason score low grade (GG 1-2) and high grade (GG 3-5) groups. Differences between groups were compared using two independent samples t-test or non-parametric test, Spearman correlation analysis was used to evaluate the correlation of DCE-MRI parameters and ADC values with Ki-67 and Gleason scores, and logistic regression model was established to evaluate the diagnostic efficacy by receiver operating characteristic (ROC) curve to evaluate the diagnostic efficacy.Results ADC values in PCa were negatively correlated with Ki-67 expression and Gleason score (P<0.001), while Ktrans, Kep and Ve were positively correlated with Ki-67 expression (P<0.001). Ktrans and Kep were also positively correlated with Gleason score (P<0.001). Statistically significant differences were found in Ktrans, Kep, Ve and ADC values between high and low Ki-67 expression groups (P<0.01), as well as between high and low Gleason score groups (P<0.01). ROC curve analysis for Ki-67 expression showed that the combined model of Ktrans+Kep+Ve+ADC had the best diagnostic performance, with an area under the curve (AUC) of 0.940. ROC curve analysis for Gleason score grading showed that the combined model of Ktrans+Kep+ADC had the best diagnostic performance, with an AUC of 0.861.Conclusions The quantitative parameters of DCE-MRI combined with ADC values show high diagnostic efficacy in predicting Ki-67 expression and Gleason score in PCa. These findings suggest that the combined use of quantitative DCE-MRI parameters with ADC values improves the accuracy of predicting pathological grading and biological aggressiveness of PCa.
[关键词] 前列腺癌;Ki-67;Gleason评分;磁共振成像;动态对比增强;扩散加权成像
[Keywords] prostate cancer;Ki-67;Gleason score;magnetic resonance imaging;dynamic contrast-enhanced;diffusion weighted imaging

周定燕 1   何文琪 2   王伟 2   陈梅泞 3   罗敏 2*  

1 西南医科大学附属医院放射科,泸州 646000

2 自贡市第四人民医院放射科,自贡 643000

3 西门子医疗系统有限公司磁共振科研部,上海 200124

通信作者:罗敏,E-mail: zghd1234@163.com

作者贡献声明::罗敏设计本研究的方案,对稿件重要的学术内容进行了修改;周定燕起草和撰写稿件,获取、分析和解释本研究的数据;何文琪、王伟、陈梅泞分析本研究的数据,对稿件的重要内容进行了修改;罗敏获得了四川省医学会(恒瑞)科研基金资助;全体作者都同意发表最后的修改稿,同意对本研究的所有方面负责,确保本研究的准确性和诚信。


基金项目: 四川省医学会(恒瑞)科研基金专项科研课题项目 2021HR55
收稿日期:2024-04-30
接受日期:2024-09-10
中图分类号:R445.2  R737.25 
文献标识码:A
DOI: 10.12015/issn.1674-8034.2024.09.016
本文引用格式:周定燕, 何文琪, 王伟, 等. DCE-MRI结合DWI对前列腺癌Ki-67表达和Gleason评分的预测价值[J]. 磁共振成像, 2024, 15(9): 94-100, 119. DOI:10.12015/issn.1674-8034.2024.09.016.

0 引言

       前列腺癌(prostate cancer, PCa)是男性第二常见的恶性肿瘤,仅次于肺癌[1, 2]。临床根据其侵袭性不同而选择不同的治疗方案,惰性PCa患者仅需主动监测并终身密切随访,侵袭性PCa患者需要手术、放疗等治疗[3]。目前根治性前列腺切除术是侵袭性PCa最有效的治疗方法之一,但由于恶性肿瘤的生物学特性、细胞残留及远处微转移灶等原因,仍有近23%~57%患者出现术后生化复发,其死亡率显著高于未生化复发的PCa患者[4, 5],因此发现和验证能够帮助判断疾病侵袭性及预后的标志物,从而为临床医生提供更准确、全面的信息是至关重要的。根据TOLLEFSON等[6]的研究,结合Gleason评分、神经周围浸润和Ki-67表达可能能为PCa患者术前提供更全面的信息、更准确的预测PCa长期预后。Gleason评分作为公认的PCa侵袭性指标,能反映PCa细胞分化程度和异质性[7, 8],但Gleason评分是由肿瘤中得分最高的肿瘤来确定的,这可能会高估总体Gleason分级[9]。增殖细胞核抗原Ki-67是细胞增殖的非特异性标志物,与PCa细胞分级显著相关,PCa分化程度越低,其表达强度越高,Ki-67可能在PCa侵袭性及预后评估中作为Gleason评分的良好补充[10, 11, 12]。目前,PCa的Ki-67表达和Gleason评分只能通过术前活检或根治性前列腺切除术来获得,活检是一种侵入性操作,可能导致不适和并发症,如感染和出血,并且得到的是穿刺点的组织,获取样本有限,可能无法直观反映整个前列腺的病变情况[13, 14]。根治性前列腺切除术虽然能提供完整组织评估,但风险大、成本高,并对生活质量有较大影响,如尿失禁和性功能障碍[15]。之前有研究通过影像组学方法对提取T2WI、扩散加权成像(diffusion weighted imaging, DWI)及表观扩散系数(apparent diffusion coeffieient, ADC)的特征进行PCa的Ki-67表达和Gleason评分进行分析[16],或通过T2WI、DWI对Ki-67表达或Gleason评分进行单独预测,依靠单一参数进行诊断难以保证诊断准确性和结果重复性[17, 18, 19, 20]。T2WI、DWI和动态对比增强磁共振成像(dynamic contrast-enhancement magnetic resonance imaging, DCE-MRI)是检测PCa分期和风险分层的重要影像学手段,DWI及DCE-MRI通过计算水分子扩散运动信息及病灶灌注定量参数值,反映肿瘤侵袭性、新生血管密度和血流灌注变化[21]。有研究发现PCa的DCE-MRI中容积转运常数(volume transfer contrast, Ktrans)、速率常数(rate contrast, Kep)与Ki-67表达呈正相关;ADC值与Gleason评分呈正相关,也有部分研究提出ADC均值与Gleason评分及分组间无相关性[22, 23, 24],结果不尽相同,且这些研究通常是独立进行的,是否能将Ki-67、Gleason评分结合起来分析,从而更全面了解PCa的增殖活性和细胞分化程度尚不完全清楚。因此,本研究将DCE-MRI和DWI结合起来,对PCa进行更全面的评估,通过对Ktrans、Kep、血管外细胞外容积分数(extravascular extracellular volume fraction, Ve)与ADC对Ki-67表达、Gleason分级的相关性分析及Ki-67表达与Gleason分级相关性的分析,期望为治疗前预测PCa的生物侵袭性和临床识别提供影像学证据。

1 材料与方法

       本研究遵守《赫尔辛基宣言》,经自贡市第四人民医院伦理委员会批准,免除受试者知情同意,批准文号:2022-087。

1.1 研究对象

       回顾性分析自贡市第四人民医院2019年1月至2023年10月收治的66例PCa患者临床、病理及MRI资料。纳入标准:(1)有完整MRI平扫、DWI及DCE-MRI序列检查影像资料;(2)穿刺或手术活检确诊为PCa且有完整的病理资料(包括Ki-67表达水平、Gleason评分);(3)检查前未行穿刺、手术治疗或内分泌等治疗。排除标准:(1)合并有其他恶性肿瘤;(2)肿瘤长径<5 mm或病灶无法准确测量。

1.2 方法

1.2.1 MRI设备及扫描参数

       采用3.0 T扫描仪(Magnet Verio Dot, Magnetom Verio, Siemens, Germany),6通道相控阵线圈,患者取仰卧位,检查前4小时禁食、排便和排尿,扫描中心位于耻骨联合上方2 cm处,进行T1WI、T2WI、T2WI脂肪抑制(fat saturation, FS)、DWI(b值:0、800、1200、1600 s/mm2)、DCE-MRI扫描。DCE-MRI先扫描1期作为蒙片后,用双筒高压注射器(MEDTRON,上海高朗医疗设备有限公司,上海)经肘静脉以0.1 mmol/kg团注钆贝葡胺注射液(上海博莱科信谊有限责任公司,上海),注射速度为2 mL/s,完成后注射以相同注射速度注射生理盐水12 mL,注射对比剂后连续进行13期动态扫描,每期扫描时间约17 s,动态增强时间共3.41 min。序列扫描参数详见表1

表1  序列扫描参数表
Tab. 1  Sequence scanning parameter table

1.2.2 图像处理

       将T2WI、DCE-MRI序列导入西门子TISSUE 4D软件(syngo MR XA20),由2名有5年以上阅片经验的主治医师在未知患者一般临床资料及病理结果的情况下,参考T2WI、DWI和ADC图像寻找病变显示最大的层面,分别在DCE-MRI图像上对肿瘤进行感兴趣区(region of interest, ROI)勾画,尽量避开出血或钙化灶,对病灶最大层面连续勾画3层,每层在软件中根据Tofts药代动力学模型自动计算ROI的Ktrans、Kep、Ve值,再计算三层的平均值,最终结果为两位医师测量结果的平均值,当对病灶有争议时,由彼此商议得出最终值,ROI示意图如图1、2。将DWI和ADC图像导入西门子后处理工作站,选取DWI(b=1600 s/mm2)图像,结合T2WI、DCE-MRI并参考DCE-MRI ROI的测量位置,按照其测量原则,测量ADC图ROI的数值。

图2  男,74岁,前列腺癌,WHO/ISUP分组为3组,Gleason评分为高级别组(4+3=7分),Ki-67低表达(5%);2A:T2WI图示病灶主要位于外周带,呈斑片状低信号(红箭);2B:ADC图,ADC=528.1×10-3 mm2/s,白色圆圈为某一层面ROI;2C:后处理软件自动生成的时间-信号强度曲线;2D~2F:DCE-MRI定量伪彩图示Ktrans=0.299 min-1,Kep=0.656 min-1,Ve=0.450。WHO/ISUP:世界卫生组织/国际泌尿病理学会;ADC:表观扩散系数;ROI为感兴趣区域;DCE-MRI为磁共振动态对比增强;Ktrans为容积转运常数;Kep为速率常数;Ve为血管外细胞外容积分数。
Fig. 2  Male, 74-year-old, diagnosed with prostate cancer, WHO/ISUP grade group 3, high Gleason score of 4+3=7, Ki-67 low expression at 5%; 2A: The T2WI lesion is mainly located in the peripheral band and has patchy low signal, as shown by red arrows; 2B: ADC value of 528.1×10−3 mm2/sec, white circles are ROIs at one level; 2C:Time-signal intensity curves automatically generated by post-processing software;Fig. 2D-2F: DCE-MRI quantitative pseudo-colors illustrating that Ktrans is 0.299min-1, Kep is 0.656 min-1, Ve is 0.450. WHO/ISUP: World Health Organization/International Society of Urological Pathology; ADC: apparent diffusion coefficient; ROI: region of interest; DCE-MRI: dynamic contrast-enhancement; Ktrans: volume transfer contras; Kep: rate contrast; Ve: extravascular extracellular volume fraction.

1.2.3 病理资料

       对患者行常规系统穿刺(12针),在此基础上,再对可疑区域行靶向穿刺,即12+X针。由1名5年经验的病理科住院医师和10年以上经验的副主任医师对送检组织进行诊断,给出Gleason评分,再通过免疫组化得到Ki-67的值。根据之前的研究[25, 26, 27]结果,Ki-67高表达的最佳值是有10%以上的阳性细胞。因此,我们将研究病例分为两组:Ki-67高表达组(Ki-67>10%)和Ki-67低表达组(Ki-67≤10%)。Gleason评分根据国际泌尿病理学会(International Society of Urological Pathology, ISUP)预后分级分组系统(grade group, GG)标准严格评定[28],将患者分为Gleason低级别(GG 1~2)和Gleason高级别(GG 3~5)组。

1.2.4 统计学方法

       采用SPSS 27.0统计学软件进行数据分析。等级资料用卡方检验,计数资料进行正态性和方差齐性检验,采用Kolmogorov-Smirnov检验评估连续变量是否为正态分布,单因素ANOVA分析检验数据是否满足方差齐性,比较组间Ktrans、Kep、Ve、ADC参数差异,符合正态分布的用两独立样本t检验,不符合正态分布的用非参数检验。采用Spearman相关分析评价DCE-MRI药代动力学模型参数和ADC值与Ki-67、Gleason评分之间的相关性,以及Ki-67与Gleason评分之间的相关性,并进行二元logistic回归分析,建立DCE-MRI和ADC值联合模型,再使用ROC曲线评估Ktrans、Kep、Ve、ADC单独及联合对Ki-67表达和Gleason评分的预测效能。P<0.01为差异具有统计学意义。

2 结果

2.1 Ki-67、Gleason评分不同分组间临床资料对比

       本研究共纳入66例符合标准的PCa患者,Ki-67低表达组为45例,高表达组为21例;Gleason分级高级别组为49例,低级别组为17例。两组患者年龄、病变部位差异无统计学意义。如表2所示。

表2  前列腺癌Ki-67表达、Gleason评分不同分组间临床资料对比
Tab. 2  Comparison of clinical data between prostate cancer Ki-67 expression and Gleason score among different groups

2.2 Ki-67、Gleason评分不同分组间DCE-MRI药代动力学模型参数及ADC值的均值比较

       Ki-67、Gleason评分不同分组Ktrans、Kep、Ve及ADC值均值比较结果显示(表3),Ki-67高表达组与低表达组Ktrans、Kep、Ve和ADC均值比较差异均具有统计学意义(P<0.01)。同样,Gleason高级别组与低表达组Ktrans、Kep、ADC均值比较差异均具有统计学意义(P<0.01),但Ve值差异无统计学意义(P=0.200)。

表3  前列腺癌Ki-67、Gleason评分各组DCE-MRI药代动力学模型参数及ADC值均值比较
Tab. 3  Comparison of quantitative parameters and mean ADC values of DCE-MRI in prostate cancer Ki-67 and Gleason score

2.3 Ki-67表达、Gleason评分与Ktrans、Kep、Ve及ADC值的相关性及Ki-67与Gleason评分之间的相关性

       Ki-67表达、Gleason评分与Ktrans、Kep、Ve及ADC值的相关性结果显示(表4),Ktrans、Kep、Ve与Ki-67表达均呈正相关(P<0.001),Ktrans、Kep与Gleason评分均呈正相关(P<0.001),Ve与Gleason评分无线性关系(P=0.250),ADC与Ki-67表达、Gleason评分均呈负相关。Ki-67与Gleason评分之间呈正相关性,但相关性较弱r=0.34(P=0.005)。典型病例见图12

图1  男,83 岁,前列腺癌,WHO/ISUP 分组为4 组,Gleason 评分为高级别组(4+4=8 分),Ki-67 高表达(20%)。1A:T2WI 图示病灶主要位于外周带,呈环形低信号(红箭);1B:ADC图,ADC值=555.4×10-3 mm²/s,白色圆圈为某一层面ROI;1C:后处理软件自动生成的时间-信号强度曲线;图1D~1F:DCE-MRI定量伪彩图示Ktrans=0.167 min−1,Kep=0.553 min−1,Ve=0.518。WHO/ISUP:世界卫生组织/国际泌尿病理学会;ADC:表观扩散系数;ROI 为感兴趣区域;DCE-MRI 为磁共振动态对比增强;Ktrans为容积转运常数;Kep为速率常数;Ve为血管外细胞外容积分数。
Fig. 1  Male, 83 years old, diagnosed with prostate cancer, ISUP/WHO grade group 4, high Gleason score of 4+4=8, Ki-67 high expression at 20%. 1A: The T2WI lesion is mainly located in the peripheral band and have a ring-shaped low signal, as shown by the red arrow; 1B: ADC value of 555.4×10−3 mm2/s, white generated by the post-processing software; 1D-1F: DCE-MRI quantitative pseudo-colors illustrating that Ktrans is 0.167 min-1, Kep is 0.553 min-1, Ve is 0.518. WHO/ISUP: World Health Organization/International Society of Urological Pathology; ADC: apparent diffusion coefficient; ROI: region of interest; DCE-MRI: dynamic contrast-enhancement; Ktrans: volume transfer contras; Kep: rate contrast; Ve: extravascular extracellular volume fraction.
表4  前列腺癌Ki-67、Gleason评分各组DCE-MRI药代动力学模型参数及ADC值相关性
Tab. 4  Correlation of DCE-MRI parameters and ADC values between prostate cancer Ki-67 and Gleason scores among different

2.4 各定量参数对PCa Ki-67表达、Gleason评分预测结果

       我们分析了Ki-67表达和Gleason评分下多种MRI参数对PCa诊断的贡献(表5)。对于Ki-67表达,单独参数中Ktrans、Kep、Ve和ADC值的AUC值分别为0.883、0.861、0.769和0.848,显示了它们在区分高低Ki-67值上的有效性。特别是Ktrans表现出较高的诊断效能。而在联合药代动力学模型参数及ADC值建立的logistic回归模型中,联合模型Ktrans+Kep+Ve+ADC显示了最高的AUC值(0.940),明显提高了诊断精度。此外,这一组合在敏感度和特异度上也表现出色,约登指数高达0.813。

       对于Gleason评分,分析结果表明,单独参数中Ktrans、Kep、Ve和ADC的AUC值分别为0.840、0.788、0.595和0.795,其中Ktrans同样显示出最好的诊断效能。在联合药代动力学模型参数及ADC值建立的logistic回归模型中,联合模型Ktrans+Kep+ADC提供了最高的AUC值(0.861)。Ktrans+ADC的组合在特异度(87.8%)和敏感度(76.5%)方面同样表现良好,约登指数为0.642。Ki-67表达、Gleason评分的ROC曲线如图34

图3  Ktrans、Kep、Ve、ADC及联合模型对前列腺癌Ki-67表达的受试者工作特征曲线。单独分析时Ktrans的AUC值最高,为0.883,联合分析时Ktrans+Kep+Ve+ADC的AUC值最高,为0.940。
图4  Ktrans、Kep、Ve、ADC及联合模型对前列腺癌Gleason评分的受试者工作特征曲线。单独分析时Ktrans的AUC值最高,为0.840,联合分析时Ktrans+Kep+ADC的AUC值最高,为0.861。Ktrans:容积转运常数;Kep:速率常数;Ve:血管外细胞外容积分数,ADC:表观扩散系数;AUC:曲线下面积。
Fig. 3  Receiver operating characteristic curve of subjects with Ki-67 expression in prostate cancer by Ktrans, Kep, Ve, ADC and combined models. Ktrans have the highest AUC value of 0.883 when analyzed alone, the highest AUC value of 0.940 is obtained for Ktrans+Kep+Ve+ADC in the joint analysis.
Fig. 4  Receiver operating characteristic curve of subjects with Gleason score expression in prostate cancer by Ktrans, Kep, Ve, ADC and combined models. Ktrans have the highest AUC value of 0.840 when analyzed alone, the highest AUC value of 0.861 is obtained for Ktrans+Kep+ADC in the combined analysis. Ktrans: volume transfer contras; Kep: rate contrast; Ve: fractional volume of the extravascular-extracellular; ADC: apparent diffusion coefficient; AUC: area under the curve.
表5  Ki-67、Gleason评分中各参数及联合参数在前列腺癌中的诊断效能
Tab. 5  The diagnostic performance of each parameter and combined parameters in Ki-67 and Gleason scores in prostate cancer

3 讨论

       本研究通过DCE-MRI和DWI对PCa患者的Ki-67表达和Gleason评分进行评估,目前尚未无类似的研究。本研究发现,Ki-67高表达组的Ktrans、Kep和Ve值均显著高于低表达组,而ADC值显著低于低表达组。同样,Gleason高级别组的Ktrans和Kep值显著高于低级别组,且高级别组的ADC值显著低于低级别组。相关性分析表明,Ktrans、Kep、Ve与Ki-67表达均呈正相关,Ktrans、Kep与Gleason评分均呈正相关,而ADC值与Ki-67表达和Gleason评分均呈负相关。但Ki-67与Gleason评分之间呈弱正关性。本研究将DCE-MRI和DWI结合起来,能够更准确地预测Ki-67表达和Gleason评分,提供更为精确的肿瘤分级和预后信息。

3.1 ADC值对Ki-67表达、Gleason评分的预测价值

       本研究发现,ADC值与PCa的Ki-67表达和Gleason评分均呈显著负相关,这与ZHANG等[29]、BORRETZEN等[30]的研究结果一致,且ADC值在区分高低Ki-67表达、高低Gleason评分中敏感度,特异度均较高,表明ADC值越低的组织,肿瘤细胞增殖越活跃、细胞密度越高,恶性程度也越高。但有研究提出ADC均值在Gleason评分和Gleason分级组之间无显著差异,如当Gleason值为3+4和4+3时[31]。这与本文研究结果不一致,这可能是因为b值的选择和数量及其分布对测得的ADC值有显著影响,目前尚无合理的模型或相关假设能解释当ADC与Gleason分级组具有相关性时使用哪两个b值组合计算ADC值最为合适[24, 32, 33]。单独使用ADC值对Ki-67或Gleason分级进行预测价值的结果是不够准确、全面的,因此我们的研究采用了多参数MRI方法对其进行了预测。

3.2 药代动力学模型参数对Ki-67表达、Gleason评分的预测价值

       本研究发现,Ktrans、Kep、Ve与Ki-67表达呈正相关,Ki-67是细胞增殖的非特异性标志物,对于细胞增殖,以往的研究主要集中在微血管密度和Gleason评分上[30, 34],只有少量研究评估了DCE-MRI与Ki-67表达的关系,如ZHANG等[22]等通过直方图分析发现Ktrans、Kep、Ve与Ki-67表达均呈正相关,结果与本文大致相同。分析原因可能是恶性肿瘤生长时,细胞会经历一个叫作“血管生成”的过程,新形成血管的典型特征是对大分子具有高渗透性、形成动静脉分流和血管高度弯曲等弱点,DCE-MRI有助于可视化血管生成的所有这些特征[35],DCE-MRI中Ktrans代表单位时间内血管内对比剂进入血管外细胞外间隙扩散的速度,Kep代表单位时间内对比剂血管外细胞外间隙回流至血管的速度[36],由此可以得出Ktrans、Kep值越高的区域肿瘤微血管生长越不均匀,肿瘤血流量更高、恶性程度更高,侵袭性和转移性扩散潜力增加。同样Ktrans、Kep与Gleason分级均呈正相关,与高Gleason评分的病理特征一致。本文虽得出Ve与Ki-67表达水平正相关,但相关性较Ktrans、Kep弱(r=0.43,P<0.001);Ve与Gleason评分无线性相关,与之前的研究相似[22, 30, 37],由于Ve主要反映对比剂暂时滞留在血管外细胞间隙中的量,导致Ve与Ki-67相关性弱、与Gleason评分无线性相关的原因可能与血流、血管外细胞间隙和组织静水压以及缺血时空分布失衡等因素有关[38, 39]。在药代动力学模型参数对PCa的Ki-67表达、Gleason评分诊断效能预测中,Ktrans在三个药代动力学模型参数Ktrans、Kep、Ve中区分高低Ki-67表达、高低Gleason级别组中均表现出较好的诊断效能,较高的敏感度和特异度。这些结果表明,DCE-MRI作为非侵入性影像学指标,能够有效预测PCa的Ki-67表达和Gleason评分,对PCa的侵袭性进行良好的预测,但其预测能力较联合分析时低。

3.3 联合分析对Ki-67表达、Gleason评分的预测价值

       本研究将Ktrans、Kep、Ve与ADC联合对Ki-67高低表达、Gleason高低级别组进行预测,DCE-MRI和ADC联合模型在区分Ki-67高低表达、Gleason高低级别组的诊断效能提高,均高于单独使用ADC或DCE-MRI对PCa Ki-67表达、Gleason评分的预测作用。有研究发现DCE-MRI联合DWI对PCa的诊断效果优于T2WI+DWI、T2WI+DCE、DWI+MRS、DCE+MRS等其他两种MRI组合方式的诊断效果[40],如ZHOU等[16]用影像组学的方法从T2WI、DWI和ADC图像中提取特征对Ki-67高低表达、Gleason高低评分进行预测,得出训练集和验证集在区分Ki-67高低表达的AUC分别为0.884和0.793,训练集和验证集在区分Gleason高低评分的AUC分别为0.827和0.813,AUC值较本研究低,这可能是由于T2WI虽能显示病变位置、大小、形状和范围,但其对外周带的病变显示敏感,在移行带与前列腺增生结节鉴别困难,而本研究中的DCE-MRI通过药代动力学参数定量地对肿瘤血流灌注进行测定,再结合ADC值联合诊断,得到较为准确、可靠的肿瘤组织的血流灌注、水分子扩散运动信息,有利于提高术前预测PCa病理分级诊断的准确性,更好地预测肿瘤的侵袭性及预后情况,为术前提供更为全面的信息。

       另外,本研究试图将Ki-67表达、Gleason分级进行综合分析,期望得到预测PCa侵袭性与预后更为全面的结果,但Ki-67与Gleason分级呈弱相关性,相关系数仅为0.34,表明Ki-67在一定程度上可以对Gleason分级进行补充,但补充价值有限。推测其原因如下,首先,Ki-67和Gleason分级是PCa侵袭性的优秀预测指标,但Ki-67、Gleason评分对PCa的预测本质并不相同,Ki-67代表肿瘤细胞增殖能力,而Gleason评分代表细胞异型性和分化能力[27];其次,有研究表明Ki-67在瘤间和瘤内具有高度变异性,虽然大部分Gleason高级别组Ki-67是高表达的,但GG 4~5组肿瘤显示出矛盾的Ki-67低增殖率,可能是这部分细胞凋亡的失调而不是增殖增加所致[41]。要实现对两个或更多变量的预测,需要进行更多的探究,如对Gleason分级与Ki-67增殖差异潜在机制、细胞增殖和肿瘤生长途径的转录调控等进行的探索。

3.4 局限性

       本文的局限性在于:(1)本研究为回顾性研究,可能存在选择偏倚;(2)研究样本量较少,在患者Ki-67不同分组间临床资料对比中,患者分布不均匀,未来应加大样本量不仅对疾病的诊断进行预测;(3)最后所有的数据均是由手动标定ROI进行测量,可能导致误差,只能捕获部分信息,因此可以考虑用基于种子点的半自动分割方法或者机器学习中的全自动分割来更准确地获得DCE-MRI定量特征,结合这些特征和其他临床信息,能构建更为精准的预测模型,得出更为准确的结果。

4 结论

       DCE-MRI药代动力学模型参数Ktrans、Kep、Ve对PCa的Ki-67表达,Gleason评分病理分级有较好的预测作用,高于ADC值单独预测作用,DCE-MRI与ADC联合诊断效能高于DCE-MRI或ADC单独诊断的效率,联合使用这些定量参数可提高PCa病理分级和生物侵袭性的预测准确性。

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