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临床研究
动脉自旋标记联合扩散张量成像对腮腺肿瘤的鉴别诊断价值
周金亮 崔运福 张迪鸣 任瑞 狄宁宁 沈善昌 姜兴岳 王山山

Cite this article as: ZHOU J L, CUI Y F, ZHANG D M, et al. Differential diagnostic value of arterial spin labeling combined with diffusion tensor imaging in parotid gland tumors[J]. Chin J Magn Reson Imaging, 2024, 15(3): 50-55.本文引用格式周金亮, 崔运福, 张迪鸣, 等. 动脉自旋标记联合扩散张量成像对腮腺肿瘤的鉴别诊断价值[J]. 磁共振成像, 2024, 15(3): 50-55. DOI:10.12015/issn.1674-8034.2024.03.009.


[摘要] 目的 探讨应用动脉自旋标记(arterial spin labeling, ASL)和扩散张量成像(diffusion tensor imaging, DTI)评价多参数MRI在鉴别腮腺肿瘤中的临床价值。材料与方法 回顾性分析滨州医学院附属医院2019年6月至2023年11月66名经手术病理证实的腮腺肿瘤患者,术前均行3D ASL和DTI,并测量肿瘤最大血流量(maximum tumor blood flow, TBFmax)和最小表观扩散系数(minimum apparent diffusion coefficient, ADCmin)、各向异性分数(fraction anisotropy, FA)。使用Mann-Whitney U检验或Kruskal-Wallis检验比较良性肿瘤(benign tumors, BT)和恶性肿瘤(malignant tumors, MT)的各参数值。使用受试者工作特征(receiver operating characteristic, ROC)曲线分析评估各参数和联合有差异的参数对腮腺肿瘤的诊断效能。结果 66例腮腺肿瘤患者中,BT 55例[其中Warthin瘤(Warthin tumors, WT)15例,多形性腺瘤(pleomorphic adenomas, PA)23例,其他17例],MT 11例。BT的FA值低于MT(0.13±0.06 vs. 0.18±0.04,P=0.003)。PA的TBFmax值[(43.72±37.64)mL/(100 g·min-1)]低于MT [(92.56±58.26)mL/(100 g·min-1)](P<0.001)和WT [(145.26±64.54)mL/(100 g·min-1)](P=0.016)。PA的ADCmin值[(1.55±0.51)×10-3 mm2/s]高于MT [(1.11±0.28)×10-3 mm2/s](P=0.016)和WT [(1.03±0.53)×10-3 mm2/s](P<0.001)。MT的FA值(0.18±0.05)高于PA(0.11±0.04)(P<0.001)和WT(0.12±0.02)(P=0.015)。FA鉴别腮腺BT与MT的曲线下面积(area under the curve, AUC)为0.78,敏感度、特异度分别为81.82%、70.18%。FA区分WT、PA与MT的AUC分别为0.85、0.87,敏感度分别为72.73%、100.00%,特异度分别为94.12%、65.22%。TBFmax、ADCmin鉴别WT与PA的AUC分别为0.90、0.85,敏感度分别为94.12%、95.65%,特异度分别为91.30%、82.35%。三者联合鉴别PA与MT的AUC可提高至0.98,敏感度为100.00%,特异度为86.96%。结论 ASL联合DTI有助于鉴别诊断腮腺良恶性肿瘤,综合运用多参数各优势有助于区分WT、PA和MT。联合有差异的参数可显著提高区分PA与MT的诊断效能。
[Abstract] Objective To evaluate the clinical value of multi-parameter MRI in distinguishing parotid tumors by arterial spin labeling (ASL) and diffusion tensor imaging (DTI).Materials and Methods A total of 66 patients with surgically and pathologically proven parotid gland tumors from Binzhou Medical University Hospital from June 2019 to November 2023 were retrospectively analyzed. 3D ASL imaging and DTI were perfomed before surgery, and the maximum tumor blood flow (TBFmax), minimum apparent diffusion coefficient (ADCmin) and fraction anisotropy (FA) were measured. The Mann-Whitney U test or Kruskal-Wallis test were used to compare the parameters of benign tumors (BT) and malignant tumors (MT). Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic efficacy of each parameter and the combination of different parameters for parotid tumors.Results There were 66 patients with parotid gland tumors, including 55 BT [15 Warthin tumors (WT), 23 pleomorphic adenomas (PA), 17 others] and 11 MT. The FA value of BT was lower than that of MT (0.13±0.06 vs. 0.18±0.04, P=0.003). The TBFmax value of PA [(43.72±37.64) mL/(100 g·min-1)] was lower than that of MT [(92.56±58.26) mL/(100 g·min-1)] (P<0.001) and WT [(145.26±64.54) mL/(100 g·min-1)] (P=0.016). The ADCmin value of PA [(1.55±0.51)×10-3 mm2/s] was higher than that of MT [(1.11±0.28)×10-3 mm2/s] (P=0.016) and WT [(1.03±0.53)×10-3 mm2/s] (P<0.001). The FA value of MT (0.18±0.05) was higher than that of PA (0.11±0.04) (P<0.001) and WT (0.12±0.02) (P=0.015). The area under the curve (AUC) for distinguishing BT from MT by FA was 0.78, and the sensitivity and specificity were 81.82% and 70.18%, respectively. The AUC for distinguishing WT, PA from MT by FA were 0.85 and 0.87, the sensitivity were 72.73% and 100.00%, and the specificity were 94.12% and 65.22%, respectively. The AUC for distinguishing WT from PA by TBFmax and ADCmin were 0.90 and 0.85, the sensitivity were 94.12% and 95.65%, and the specificity were 91.30% and 82.35%, respectively. The AUC for distinguishing PA from MT by combining them could be increased to 0.98, the sensitivity was 100.00%, and the specificity was 86.96%.Conclusions The combination of ASL and DTI is helpful for the differential diagnosis of benign and malignant parotid tumors, and the comprehensive application of multiple parameters is helpful for the differentiation of WT, PA and MT. Combining the different parameters can significantly improve the diagnostic efficiency of distinguishing PA from MT.
[关键词] 腮腺肿瘤;Warthin瘤;多形性腺瘤;恶性肿瘤;动脉自旋标记成像;扩散张量成像;磁共振成像
[Keywords] parotid gland tumors;Warthin tumor;pleomorphic adenoma;malignant tumors;arterial spin labeling;diffusion tensor imaging;magnetic resonance imaging

周金亮 1   崔运福 1   张迪鸣 1   任瑞 2   狄宁宁 1   沈善昌 1   姜兴岳 1   王山山 1*  

1 滨州医学院附属医院放射科,滨州 256600

2 滨州医学院附属医院门诊部,滨州 256600

通信作者:王山山,E-mail:wss3256590@126.com

作者贡献声明:王山山设计本研究的方案,对稿件重要内容进行了修改;周金亮起草和撰写稿件,获取、分析及解释本研究的数据,对稿件的重要内容进行了修改;崔运福、张迪鸣、任瑞、狄宁宁、沈善昌、姜兴岳获取及分析本研究的数据,对稿件重要内容进行了修改;周金亮获得了滨州医学院科研计划与科研启动基金项目资助;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: 滨州医学院科研计划与科研启动基金项目 BY2021KJ34
收稿日期:2023-10-12
接受日期:2024-02-26
中图分类号:R445.2  R739.87 
文献标识码:A
DOI: 10.12015/issn.1674-8034.2024.03.009
本文引用格式周金亮, 崔运福, 张迪鸣, 等. 动脉自旋标记联合扩散张量成像对腮腺肿瘤的鉴别诊断价值[J]. 磁共振成像, 2024, 15(3): 50-55. DOI:10.12015/issn.1674-8034.2024.03.009.

0 引言

       唾液腺肿瘤约占头颈部肿瘤的3%~6%[1, 2],80%位于腮腺[3],以良性肿瘤(benign tumors, BT)中多形性腺瘤(pleomorphic adenomas, PA)和Warthin瘤(Warthin tumors, WT)最常见[4],恶性肿瘤(malignant tumors, MT)大约占1/4[5, 6, 7]。BT中,由于PA局部复发的可能性较高,建议采用腮腺浅表切除术[8],WT由于恶变的概率较低,可选择随访。然而,恶性肿瘤通常采用更积极的方法,包括全切除腮腺伴或不伴面部神经切除[9]。因此术前正确区分腮腺肿瘤的亚型对于治疗策略的规划至关重要[10, 11]

       腮腺BT与MT之间的常规影像学表现存在重叠[12, 13, 14, 15]。近年来,一些功能MRI技术如扩散加权成像(diffusion weighted imaging, DWI)、扩散张量成像(diffusion tensor imaging, DTI)、动态对比增强(dynamic contrast-enhanced, DCE)MRI、动脉自旋标记(arterial spin labeling, ASL)等已被报道可以提高腮腺肿瘤的诊断准确性[16, 17, 18, 19]。DWI提供了与水分子在组织中随机微观运动相关的额外定量信息,表观扩散系数(apparent diffusion coefficient, ADC)测量已被报道可用于区分各种器官的良恶性病变,然而,ADC值在区分腮腺BT和MT方面的效果受到不同亚型肿瘤之间相当大的重叠的限制[20, 21, 22, 23]。DTI作为一种先进的MRI技术,提供了有关三维空间中水分子扩散的大小和方向的定量信息,可以提供ADC和各向异性分数(fraction anisotropy, FA),但关于DTI鉴别腮腺肿瘤的报道较少[24]。DCE MRI需要对比剂注射,不适用于有肾功能障碍或不良反应史的患者[25, 26]。而ASL技术无需对比剂即可进行组织灌注的无创定量评估,即血液中的质子被磁性标记,用作内在示踪剂以测量组织血流量,关于ASL成像评估腮腺肿瘤的报道较少[5, 27, 28]。然而,因肿瘤异质性,这些研究者多采用测量整个或几乎整个肿瘤的平均肿瘤血流量(tumor blood flow, TBF)和平均ADC值,难以代表肿瘤细胞生长最活跃或肿瘤细胞密度最高的区域,另外,学者间研究结果也存在差异。因此本研究探讨联合应用ASL与DTI生成的多参数最大肿瘤血流量(maximum tumor blood flow, TBFmax)和最小表观扩散系数(minimum apparent diffusion coefficient, ADCmin)、FA在区分腮腺肿瘤的联合诊断价值,旨在帮助临床医师选择最优的治疗策略。

1 材料与方法

1.1 一般资料

       回顾性分析滨州医学院附属医院2019年6月至2023年11月经手术病理证实的66例腮腺肿瘤患者临床资料,男41例,女25例,年龄14~75岁。纳入标准:(1)所有患者均有病理组织学检查结果;(2)术前均行3D ASL、DTI及MRI常规扫描。排除标准:(1)患有心、脑、肾等严重器质性病变者;(2)有严重的精神疾患;(3)腮腺囊性病变,无明确实性成分;(4)图像质量较差影响分析测量。本研究遵守《赫尔辛基宣言》,经滨州医学院附属医院伦理委员会批准,免除受试者知情同意,批准文号:KT-14。

1.2 MRI检查方法

       本研究所用设备为3.0 T MRI(美国GE Discovery MR 750)和8通道头部线圈(美国GE Medical System),所有患者行3D ASL、DTI及常规MRI序列扫描。ASL-MRI:延时标记时间 1 525 ms,TR 4 490 ms,TE 10.7 ms,矩阵256×256,FOV 240 mm×240 mm,层厚4 mm,层间距0 mm,扫描时间4 min 21 s;DTI:TR 8 000 ms,TE minimum,FOV 240 mm×240 mm,矩阵256×256,层厚4 mm,层间距0 mm,扫描时间4 min 24 s;T1WI:TR 462 ms,TE min full,矩阵256×256,FOV 240 mm×240 mm,层厚4 mm,层间距0 mm,扫描时间2 min 25 s;T2WI-IDEAL:TR 4 129 ms,TE 85 ms,矩阵256×256,FOV 240 mm×240 mm,层厚4 mm,层间距0 mm,扫描时间2 min 41 s。

1.3 图像处理及分析

       使用GE AW4.6后处理工作站对扫描获得的3D ASL和DTI的原始图像进行处理分别获得TBF图和ADC、FA图,参考T1和T2加权图像,将大小为30~50 mm2感兴趣区置于TBF图最大信号区、ADC图最低信号区,得到肿瘤的TBFmax和ADCmin、FA值,两名放射科医师(分别有10年和7年工作经验的主治医师)采用双盲法对病灶进行测量,取其平均值。一个月后由医师(10年工作经验)再次对病灶进行测量,分析可重复性。

1.4 统计学分析

       使用统计软件SPSS 26.0和MedCalc进行分析。连续变量数据以平均值±标准差表示。计算组内相关系数(intra-class correlation coefficient, ICC)以评估各参数值的观察组间及观察组内一致性。ICC值取0~1之间,若ICC小于0.4,认为可重复性较差;若ICC值大于0.75,认为可重复性较好。使用Mann-Whitney U检验(不符合正态分布)或t检验(符合正态分布)比较所有BT和MT的TBFmax、ADCmin和FA值。P<0.05认为差异具有统计学意义。使用Kruskal-Wallis检验对WT、PA与MT三组肿瘤亚型之间的TBFmax、ADCmin和FA值进行比较。P<0.05或P<0.017(Bonferroni校正)认为差异有统计学意义。使用MedCalc进行受试者工作特征(receiver operating characteristic, ROC)曲线分析各参数和联合有差异的参数区分腮腺肿瘤各亚型的能力,使用阈值标准来选择最佳临界值,该阈值标准最大化用于预测腮腺病变的约登指数,得到敏感度、特异度。使用DeLong检验比较AUC,检验水准α=0.05。

2 结果

2.1 一致性检验

       所有腮腺肿瘤患者的TBFmax、ADCmin和FA值在观察组间及观察组内一致性较高(P<0.05)(表1)。

表1  腮腺肿瘤患者TBFmax、ADCmin和FA值的一致性检验
Tab. 1  The consistency test of TBFmax, ADCmin and FA values in parotid gland tumor patients

2.2 腮腺良恶性肿瘤的各参数比较

       66例腮腺肿瘤患者中,BT 55例(WT 15例,PA 23例,其他17例),MT 11例(腺泡细胞癌2例、腺样囊性癌3例、黏液表皮样癌5例,淋巴结转移性黑色素瘤1例)(图1, 2, 3)。BT的FA值低于MT,差异具有统计学意义(P<0.05),而BT和MT之间的TBFmax、ADCmin差异均无统计学意义(P>0.05)(表2)。

图1  男,55岁,左侧腮腺Warthin瘤。1A:TBF图;1B:ADC图;1C:FA图。TBFmax值为224.03 mL/(100 g·min-1),ADCmin值为0.97×10-3 mm2/s,FA值为0.11。TBF:肿瘤血流量;ADC:表观扩散扩散系数;FA:各向异性分数;TBFmax:最大肿瘤血流量;ADCmin:最小表观扩散系数。
Fig. 1  Male, 55 years old, with Warthin tumor of the left parotid gland. 1A: TBF image; 1B: ADC image; 1C: FA image. The TBFmax value is 224.03 mL/(100 g·min-1); The ADCmin value is 0.97×10-3 mm2/s; The FA value is 0.11. TBF: tumor blood flow; ADC: apparent diffusion coefficient; FA: fraction anisotropy; TBFmax: maximum tumor blood flow; ADCmin: minimum apparent diffusion coefficient.
图2  男,25岁,右侧腮腺多形性腺瘤。2A:TBF图;2B:ADC图;2C:FA图。TBFmax值为46.87 mL/(100 g·min-1),ADCmin值为1.13×10-3 mm2/s,FA值为0.07。TBF:肿瘤血流量;ADC:表观扩散扩散系数;FA:各向异性分数;TBFmax:最大肿瘤血流量;ADCmin:最小表观扩散系数。
Fig. 2  Male, 25 years old, with pleomorphic adenoma of the right parotid gland. 2A: TBF image; 2B: ADC image; 2C: FA image. The TBFmax value is 46.87 mL/(100 g·min-1); The ADCmin value is 1.13×10-3 mm2/s; The FA value is 0.07. TBF: tumor blood flow; ADC: apparent diffusion coefficient; FA: fraction anisotropy; TBFmax: maximum tumor blood flow; ADCmin: minimum apparent diffusion coefficient.
图3  男,58岁,右侧腮腺高级别黏液表皮样癌。3A:TBF图;3B:ADC图;3C:FA图。TBFmax值为98.35 mL/(100 g·min-1),ADCmin值为1.32×10-3 mm2/s,FA值为0.10。TBF:肿瘤血流量;ADC:表观扩散扩散系数;FA:各向异性分数;TBFmax:最大肿瘤血流量;ADCmin:最小表观扩散系数。
Fig. 3  Male, 58 years old, with high-grade mucoepidermoid carcinoma of the right parotid gland. 3A: TBF image; 3B: ADC image; 3C: FA image. The TBFmax value is 98.35 mL/(100 g·min-1); The ADCmin value is 1.32×10-3 mm2/s; The FA value is 0.10. TBF: tumor blood flow; ADC: apparent diffusion coefficient; FA: fraction anisotropy; TBFmax: maximum tumor blood flow; ADCmin: minimum apparent diffusion coefficient.
表2  BT、MT患者TBFmax、ADCmin和FA值的比较
Tab. 2  Comparison of TBFmax, ADCmin and FA values between BT and MT patients

2.3 腮腺肿瘤各亚型之间各参数比较

       WT的TBFmax高于MT,但差异无统计学意义(H=9.241,P=0.108),PA的TBFmax低于MT,WT的TBFmax明显高于PA,差异均有统计学意义(H=-13.079,P=0.016;H=22.320,P<0.001);WT与MT的ADCmin之间差异无统计学意义(H=-5.706,P=0.321),WT、MT的ADCmin均明显低于PA,差异均有统计学意义(H=-18.793,P<0.001;H=13.087,P=0.016);WT、PA的FA均低于MT,差异均有统计学意义(H=-21.449,P<0.001;H=-13.936,P=0.015),WT与PA的FA之间差异无统计学意义(H=7.513,P=0.114)(表3)。

表3  腮腺肿瘤各亚型TBFmax、ADCmin和FA值的比较
Tab. 3  Comparison of TBFmax, ADCmin and FA values of each parotid tumor subtype

2.4 腮腺肿瘤不同亚型之间各参数的ROC曲线分析

       以FA=0.14为临界值区分BT与MT的AUC为0.78,敏感度为81.82%,特异度为70.18%。以72.36 mL/(100 g·min-1)的TBFmax和1.03×10-3 mm2/s的ADCmin为临界值区分WT和PA的AUC分别为0.90、0.85,敏感度分别为94.12%、95.65%,特异度分别为91.30%、82.35%,联合TBFmax+ADCmin没有提高AUC。以64.62 mL/(100 g·min-1)的TBFmax、1.43×10-3 mm2/s的ADCmin和0.12的FA为临界值区分PA与MT的AUC分别为0.81、0.78、0.87,敏感度分别为72.73%、100.00%、100.00%,特异度分别为86.96%、60.87%、65.22%,联合TBFmax+ADCmin+FA提高AUC至0.98,敏感度为100.00%,特异度为86.96%(表4图4)。

图4  各参数单独及联合有差异的参数鉴别WT、MT及PA的受试者工作特征曲线。4A:WT与MT之间TBFmax、ADCmin和FA的AUC比较;4B:PA与MT之间TBFmax、ADCmin和FA的AUC比较;4C:WT与PA之间TBFmax、ADCmin和FA的AUC比较。WT:Warthin瘤;PA:多形性腺瘤;MT:恶性肿瘤;TBFmax:最大肿瘤血流量;ADCmin:最小表观扩散系数;FA:各向异性分数;AUC:曲线下面积。
Fig. 4  Receiver operating characteristic curve of each parameter alone and in combination of different parameters to differentiate WT, MT and PA. 4A: Comparison of AUC of TBFmax, ADCmin and FA between WT and MT; 4B: Comparison of AUC of TBFmax, ADCmin and FA between PA and MT; 4C: Comparison of AUC of TBFmax, ADCmin and FA between WT and MT. TBFmax: the maximum tumor blood flow; ADCmin: the minimum apparent diffusion coefficient; FA: fraction anisotropy; WT: Warthin tumor; PA: pleomorphic adenomas; AUC: area under the curve.
表4  腮腺肿瘤的TBFmax、ADCmin和FA的ROC曲线结果
Tab. 4  Results of ROC curves of TBFmax, ADCmin and FA in parotid gland tumors

3 讨论

       本研究发现FA有助于区分腮腺BT和MT,BT的FA值低于MT。然而,使用TBFmax和ADCmin还不能区分腮腺所有BT和MT,分析原因可能与腮腺BT亚型种类较多,不同亚型之间其值可能存在较大差异有关。TBFmax和ADCmin可以区分PA与WT、MT,PA的TBFmax值低于WT和MT,ADCmin值高于WT和MT,但二者均不能区分WT与MT。而FA可以区分WT与MT,WT的FA值低于MT。联合TBFmax+ADCmin+FA相对于单参数可以提高鉴别PA与MT的诊断效能。

3.1 ASL对腮腺肿瘤的诊断价值

       ASL是一种非侵入性方法,旨在通过测量动脉血液中的被磁性标记的氢质子来测量TBF,且在不使用对比剂的情况下通过TBF的定量测量提供了有关肿瘤血管性的信息[8]。本研究中,腮腺所有BT和MT之间的TBFmax差异无统计学意义,与研究[20, 29]报道一致,而研究[30]报道腮腺MT的平均TBF高于BT不一致,分析原因可能与腮腺BT和MT中的亚型种类较多,其TBF值之间可能存在较大的差异如WT与PA的TBF值有关。本研究中PA的TBFmax值均低于WT和MT,差异具有统计学意义,WT的TBFmax值虽高于MT,但差异无统计学意义,与部分文献报道[28]相似。然而与部分研究者报道MT与PA之间TBF差异无统计学意义的结果[29, 31, 32]不一致,分析原因可能与本研究采用代表肿瘤细胞生长最活跃的TBFmax有关,另外腮腺肿瘤发病率低,样本量普遍相对较少,而且良恶性肿瘤亚型分类较多,因此样本纳入也可能存在差异。理论上因WT微血管密度较高,MT肿瘤血管形成、动静脉分流、毛细血管通透性等,而PA乏血管性[20, 27],因此,WT的TBFmax最高,其次为MT,PA的TBFmax最低。未来仍需要扩充样本量及多中心研究进一步比较各亚型之间的差异。

3.2 DTI对腮腺肿瘤的诊断价值

       DTI可以确定水分子的微观运动,从而识别由具有不同基质和细胞组成的不同组织,其参数平均扩散率即在x、y和z三个平面方向的扩散平均值,等同于ADC值。FA表示水分子在微观结构扩散的方向性水平,取决于结构组织取向,并与肿瘤细胞性质和恶性程度呈线性相关[24, 29]。本研究中腮腺所有BT和MT的ADCmin比较差异无统计学意义,与研究[24, 29, 33]报道相一致,然而部分研究[30, 34, 35, 36, 37]报道腮腺MT的平均ADC低于BT,分析原因可能是WT有相对较低的ADC,其归因于上皮细胞增殖和淋巴细胞浸润引起的高细胞成分,PA有较高的ADC值归因于黏液样和软骨样基质相对丰富[24],研究结果存在差异可能与腮腺肿瘤亚型种类所占比例不同有关。然而,BT和MT的FA值之间差异具有统计学意义,与研究[24, 38]报道MT的FA值显著高于BT相一致。本研究中采用代表肿瘤细胞密度最高的ADCmin可以区分PA和WT以及PA和MT,但仍不能区分WT和MT,与研究[8]报道结果相一致,分析原因与WT上皮细胞增殖和淋巴细胞浸润引起的高细胞成分,PA黏液样和软骨样基质相对丰富,MT肿瘤细胞数量较多有关。FA值可以区分WT和MT以及PA和MT,但不能区分WT与PA,与研究[24]报道一致,表明MT的FA值高于WT和PA,反映MT细胞向各个方向生长速度的不一致性,肿瘤组织中的扩散各向异性受到包括细胞外与细胞内空间比、细胞外基质和血管等因素的影响[24]

3.3 联合ASL和DTI对腮腺肿瘤的诊断价值

       多参数MRI分析有助于充分利用各参数优势增加正确诊断疾病的信心。本研究联合应用有差异的参数鉴别诊断腮腺肿瘤,结果显示,与单参数比较,联合TBFmax和ADCmin、FA区分PA与MT的诊断效能显著提高,AUC提高至0.98;然而,联合TBFmax和ADCmin区分WT与MT的诊断效能并未进一步提高,这可能与部分WT表现出低至中等TBF[29]有关,另外也可能与本文MT亚型种类较多,各亚型之间TBFmax存在一定差异有关。因此,未来仍需继续纳入更多样本量来积累MT的病例数,进一步分析比较。最后,临床工作中可以使用FA区分腮腺BT包括WT、PA与MT;因部分PA细胞密度高呈低至中等ADC,与WT、MT存在重叠[29],这时可以使用TBFmax和ADCmin共同区分PA与WT以及PA与MT。

3.4 本研究的局限性

       本研究的局限性是样本量较少,尤其是MT,而且BT和MT亚型种类较多,不同亚型之间各参数值可能存在一定的差异,当综合比较BT和MT时因各参数值的均化,可能造成差异的不显著性。未来继续扩充样本量,进一步比较各亚型之间的差异。

4 结论

       总之,使用DTI和ASL生成的多参数FA有助于鉴别诊断腮腺BT和MT,TBFmax、ADCmin有助于鉴别WT和PA。三者联合可显著提高区分PA与MT的诊断性能。

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