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临床研究
磁化传递成像预测胰腺导管腺癌病理学分级的可行性研究
李雯漪 强静 李澄 周丹 贾鹏

本文引用格式:李雯漪, 强静, 李澄, 等. 磁化传递成像预测胰腺导管腺癌病理学分级的可行性研究[J]. 磁共振成像, 2026, 17(2): 101-106. DOI:10.12015/issn.1674-8034.2026.02.015.


[摘要] 目的 探究胰腺导管腺癌(pancreatic ductal adenocarcinoma, PDAC)肿瘤组织的磁化传递率(magnetic transfer rate, MTR)与病理分级之间的相关性。材料与方法 回顾性分析2024年8月至2025年11月期间于南京医科大学附属明基医院接受胰十二指肠切除术,且术后病理确诊为PDAC的75例患者的临床及影像资料。所有患者术前均行磁化传递成像检查,测量肿瘤区域的MTR值,并收集其他临床及影像学参数,根据病理分化程度及肿瘤生物学行为,将患者分为低级别组与高级别组,分析各参数与PDAC病理分级之间的相关性。分类变量的比较采用卡方检验;符合正态分布的连续变量采用两独立样本t检验,非正态分布变量则采用Mann-Whitney U秩和检验。将单因素分析中具有统计学意义的变量纳入二元logistic回归模型,使用前向似然比法进行变量筛选,并建立联合预测模型。采用受试者工作特征曲线评估各参数及联合模型对PDAC病理分级的诊断效能。结果 高级别组的MTR值显著高于低级别组(0.269±0.059 vs. 0.196±0.056),组间差异具有统计学意义(P<0.001)。年龄和MTR值均为诊断PDAC病理分级的独立预测因子(P均<0.05)。基于二者构建的联合模型诊断效能最高,其AUC值为0.844(95% CI:0.742~0.918),敏感度为76.0%,特异度为86.0%。该联合模型显著优于单一年龄模型(AUC=0.683,敏感度56.0%,特异度78.0%,P=0.007);与单一MTR模型(AUC=0.830,敏感度84.0%,特异度74.0%)相比,虽诊断效能差异无统计学意义(P=0.563),但特异度提高了12.0%。结论 MTR与PDAC的病理分级显著相关,MTR值越高,肿瘤分化越差。基于MTR与年龄构建的联合模型可作为术前无创评估PDAC分化程度的一种潜在影像学生物标志物。
[Abstract] Objective To investigate the correlation between the magnetization transfer ratio (MTR) of tumor tissue and the pathological grade in pancreatic ductal adenocarcinoma (PDAC).Materials and Methods A total of 75 patients who underwent pancreaticoduodenectomy and were pathologically diagnosed with PDAC at the Affiliated BenQ Hospital of Nanjing Medical University from August 2024 to November 2025 were retrospectively enrolled. All patients underwent preoperative magnetization transfer imaging (MTI) to measure the MTR values within the tumor region. Other clinical and imaging parameters were also collected. Based on the degree of pathological differentiation and tumor biological behavior, patients were classified into low-grade and high-grade groups. The correlation between various parameters and PDAC pathological grade was analyzed. Categorical variables were compared using the Chi-square test; normally distributed continuous variables were analyzed with the independent samples t-test, while non-normally distributed variables were assessed using the Mann-Whitney U test. Variables with statistical significance in univariate analysis were incorporated into a binary logistic regression model. Variable selection was performed using the forward likelihood ratio method to establish a combined predictive model. The diagnostic performance of each parameter and the combined model for predicting PDAC pathological grade was evaluated using receiver operating characteristic curves.Results The MTR value was significantly higher in the high-grade group than in the low-grade group (0.269 ± 0.059 vs. 0.196 ± 0.056), with a statistically significant inter-group difference (P < 0.001). Both age and MTR value were identified as independent predictors of PDAC pathological grade (all P < 0.05). The combined model incorporating both factors demonstrated the highest diagnostic performance, with an AUC of 0.844 (95% CI: 0.742 to 0.918), sensitivity of 76.0%, and specificity of 86.0%. This combined model was significantly superior to the age-alone model (AUC = 0.683, sensitivity = 56.0%, specificity = 78.0%, P = 0.007). Although there was no statistically significant difference in diagnostic performance compared to the MTR-alone model (AUC = 0.830, sensitivity = 84.0%, specificity = 74.0%, P = 0.563), the combined model improved specificity by 12.0%.Conclusions MTR is significantly correlated with the pathological grade of PDAC, with higher MTR values indicating poorer tumor differentiation. The combined model suggesting its potential as a non-invasive imaging biomarker for preoperatively assessing the differentiation degree of PDAC.
[关键词] 胰腺导管腺癌;胰腺纤维化;磁共振成像;磁化传递成像;磁化传递率;定量分析
[Keywords] pancreatic ductal adenocarcinoma;pancreatic fibrosis;magnetic resonance imaging;magnetization transfer imaging;magnetization transfer ratio;quantitative analysis

李雯漪    强静    李澄    周丹    贾鹏 *  

南京医科大学附属明基医院放射科,南京 210019

通信作者:贾鹏,E-mail:iambone66@163.com

作者贡献声明::贾鹏设计本研究的方案,负责审核数据、分析结果,并对稿件重要内容进行了修改;李雯漪、强静负责起草和撰写稿件,获取、分析和解释本研究的数据;李澄、周丹参与研究方案设计,对稿件重要内容进行了修改,获得了2024年度南京市卫生科技发展专项资金的资助;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: 2024年度南京市卫生科技发展专项资金项目 ZKX24064
收稿日期:2025-09-29
接受日期:2026-01-14
中图分类号:R445.2  R736.7 
文献标识码:A
DOI: 10.12015/issn.1674-8034.2026.02.015
本文引用格式:李雯漪, 强静, 李澄, 等. 磁化传递成像预测胰腺导管腺癌病理学分级的可行性研究[J]. 磁共振成像, 2026, 17(2): 101-106. DOI:10.12015/issn.1674-8034.2026.02.015.

0 引言

       胰腺导管腺癌(pancreatic ductal adenocarcinoma, PDAC)是恶性程度最高的肿瘤之一,5年生存率仅5%~12%[1]。且由于胰腺位于腹膜后,早期临床症状不明显,确诊时往往已是晚期[2]。胰腺根治性切除术是唯一可能治愈的方法,但仅不到10%的患者有手术机会[3]。由大量细胞外间质沉积引起的广泛纤维化是PDAC最显著的组织病理学特征[4]。既往多项研究已证实纤维化可促进PDAC病程进展[5, 6, 7]。高纤维化程度往往提示更高的组织学分级和更高的恶性程度[8, 9]。组织病理学分级是影响PDAC预后重要的独立危险因素,可分为高级别和低级别[10]。高级别的PDAC具有更高的侵袭性,更易发生转移,预后更差[11]

       明确PDAC的组织病理学分级对指导治疗至关重要,但传统分级方法依赖术后标本,无手术机会的患者难以获得这一关键信息。对于不能行手术治疗的患者,可在超声或CT引导下行细针穿刺活检术定位肿瘤组织并微量抽吸标本用于分级[12]。然而,穿刺检查有创,存在术后胰腺炎风险。并且肿瘤具有异质性,仅抽取少量组织得到的结果不能准确代表完整肿瘤。如果能在术前无创预测PDAC的组织病理学分级,有助于治疗方案制订。已有多项研究着眼于通过术前影像学检查预测肿瘤的组织学分级。CHEN等[13]基于双能CT定量参数和影像学特征构建模型,有效预测了PDAC的病理组织学分级和生存期。CEN等[14]结合临床及影像学特征建立列线图预测PDAC病理组织学分级,发现模型具有较高的预测效能(AUC=0.77,95% CI:0.66~0.87)。宋奇科等[15]则发现PDAC的弹性值越高,病理级别越高。

       磁化传递成像(magnetization transfer imaging, MTI)是一种非增强MR成像技术,通过选择性饱和与大分子结合的质子,利用其与自由水质子之间的磁化交换效应,降低自由水信号以调控组织对比[13, 15]。磁化传递率(magnetic transfer rate, MTR)是MTI技术中的定量参数,磁化传递效应越强,MTR值就越高[16]。在腹部影像学中,MTR值已被应用于肝脏、小肠、肾脏等的纤维化评估[17, 18, 19]。然而,国内外关于MTI技术在胰腺纤维化评估的研究相对较少。LI等[20]首次利用小鼠模型证实MTR可以定量检测PDAC的纤维化。SCHAWKAT等[21]利用MTI实现术前精准评估PDAC纤维化程度,且与术后病理结果相适应。沈志秋等[7]证实PDAC纤维化程度越高,MTR值越高。本研究进一步利用MTI技术,探讨术前MTR值评价PDAC组织病理学分级的价值。

1 材料与方法

1.1 研究对象

       本研究为回顾性队列研究,分析了2024年8月至2025年11月于南京医科大学附属明基医院就诊并行胰腺癌根治术的患者的影像学资料。每位患者术前均行上腹部MRI检查并采集相关临床检验信息。纳入标准:(1)术后病理证实为PDAC;(2)术前上腹部MRI检查时间、临床检验信息采集时间与手术日期间隔不超过1周;(3)病灶最大径>5 mm。排除标准:(1)术前行新辅助化疗或放疗;(2)胆道引流或胆道支架置入术后;(3)术后病理证实为鳞癌,不适用于临床分期者;(4)术前出现肝转移者;(5)图像质量差,伪影较重影响诊断及后续分析;(6)有其他恶性肿瘤病史或胰腺炎病史。本研究遵照《赫尔辛基宣言》,并经南京医科大学附属明基医院伦理委员会批准,免除受试者知情同意,批准文号:2024-KL029。

1.2 检查方法

       本研究采用1.5 T MRI扫描仪(Siemens Altea,德国),患者取仰卧位,扫描前禁食禁水4小时以上。分别行横断位基于MTI技术的T1WI及常规T2WI序列扫描。基于MTI技术的T1WI序列采用扰相梯度回波序列,具体参数如下:重复时间(repetition time, TR)6.5 ms,回波时间(echo time, TE)2.39 ms,视野(field of view, FOV)380 mm×308 mm,矩阵256×179,层厚3.0 mm。T1WI增强序列具体参数:TR 4.3 ms,TE 1.95 ms,FOV 400 mm×330 mm,矩阵352×246,层厚3.0 mm。T2WI序列具体参数:TR 1300 ms,TE 108 ms,FOV 400 mm×337 mm,矩阵320×224,层厚6.0 mm。

1.3 图像分析方法

       由两位胰腺病变研究方向的放射科医生(分别有3年及2年PDAC诊断经验)在上腹部MRI图像上进行感兴趣区(region of interest, ROI)勾画及MTR值的测量,评估时医生对患者临床信息及术后病理组织学分级均不知情。将MRI数据传输至Siemens后处理工作站,选择病灶显示最大层面,在未施加MT脉冲的noMTC图像上绘制ROI,应包括尽可能大的肿瘤体积,避开胰周大血管、主胰管及胰周脂肪组织,同时避开伪影、坏死、钙化成分,测量值记为M0;然后将ROI复制到施加MT脉冲的MTC图像的相应位置上,测量值记为M1;最后,计算肿瘤的MTR值,MTR=(M0-M1)/M0×100%[19]。每位医生独立勾画和测量,当结果不一致时,取两位医生测量值的平均值。全部ROI勾画与MTR测量结果均由一位具有20年腹部影像诊断经验的放射科医师进行复核,若存在分歧则以该医师判定为准。

1.4 临床及病理学评估

       记录患者的临床基本资料,包括性别、年龄、肿瘤标志物检验结果[糖类抗原19-9(carbohydrate antigen 19-9, CA19-9)水平、癌胚抗原(carcinoembryonic antigen, CEA)]。术后病理学评估由病理科医生(具有3年PDAC术后病理诊断经验)采用常规病理组织学分级方法,对肿瘤组织行苏木精-伊红染色,根据PDAC分化程度可分为高分化、中分化、低分化及无分化[22]。根据病理结果中对肿瘤分化程度的描述,将低分化、无分化者纳入高级别组,高分化、中分化者纳入低级别组[10]。然后再对术后病理切片行Masson染色评估肿瘤纤维化,记录胶原纤维所占百分比用于评估纤维化程度[23]

1.5 统计学方法

       采用SPSS 26.0与MedCalc 20.0软件进行统计分析。定性资料根据适用条件采用卡方检验或Fisher确切概率法进行比较。符合正态分布的定量参数以均值±标准差(±s)表示,组间比较采用两独立样本t检验;非正态分布定量参数则以中位数及四分位数间距[MQ1,Q3)]表示,组间比较采用Mann-Whitney U秩和检验。通过组内相关系数(intra-class correlation coefficients, ICC)评价不同观察者对病灶最大径和MTR值测量结果的一致性。采用Spearman相关分析评估MTR值与PDAC纤维化程度相关性。将单因素分析中具有统计学差异的变量纳入二元logistic回归模型,使用前向最大似然估计逐步法筛选变量并构建联合模型。绘制受试者工作特征(receiver operating characteristic, ROC)曲线,计算曲线下面积(area under the curve, AUC),评估各模型的诊断效能,采用DeLong检验比较AUC差异。以P<0.05为差异具有统计学意义。

2 结果

2.1 基线资料

       本研究收集93名患者,排除18名患者,其中3名患者术前行新辅助化疗,2名患者术前已放置胆道支架,3名患者为鳞癌、临床分期不适用,6名患者术前已出现肝转移,4名患者伪影较重、图像质量不良。最终共纳入75例PDAC患者病例,根据病理分化程度及肿瘤生物学行为分为高级别组(25例)和低级别组(50例)。低级别组患者年龄[(66.4±6.7)岁]高于高级别组[(60.8±9.2)岁],两组间年龄差异具有统计学意义(t=-3.025,P=0.003)。

2.2 一致性检验

       两名观察者对病灶最大径及MTR的测量结果具有高度一致性,ICC分别为0.946(95% CI:0.915~0.965,P<0.001)和0.887(95% CI:0.827~0.927,P<0.001)。

2.3 MTR值与PDAC纤维化的相关性分析

       纤维化程度与MTR值呈正相关(r=0.733,P<0.001),随着纤维化程度增加,MTR值相应增加,详见图1

图1  MTR值与PDAC纤维化的相关性分析散点图。MTR:磁化传递率;PDAC:胰腺导管腺癌。
Fig. 1  Scatter plot showing the correlation between MTR values and PDAC fibrosis. MTR: magnetic transfer rate; PDAC: pancreatic ductal adenocarcinoma.

2.4 临床和图像特征

       高级别组的MTR值(0.269±0.059)高于低级别组(0.196±0.056),差异具有统计学意义(t=5.239,P<0.001)。两组在性别、CA19-9水平、CEA水平、病灶位置及最大径方面的差异均无统计学意义(P均>0.05),详见表1

表1  低级别组和高级别组PDAC患者的临床及图像参数比较
Tab. 1  Comparison of clinical and imaging parameters between low-grade and high-grade groups in PDAC patients

2.5 PDAC患者病理分级的独立危险因素

       将单因素分析中具有显著差异的参数(年龄与MTR)进一步纳入二元logistic回归分析。为便于解释回归系数,以MTR值×10³后纳入模型,结果显示:年龄、MTR×10³均为PDAC患者病理分级的独立危险因素。详见表2图2, 图3

图2  男,69岁,胰腺体部PDAC。2A:T2WI图像示胰体部见稍高信号结节影(箭),经测量得出最大径为17 mm;2B:T1WI图像示结节影呈稍低信号(箭);2C:T1WI增强门脉期图像示病灶呈不均匀强化(箭),强化程度低于正常胰腺实质;2D~2E:分别为未施加MT脉冲(2D)及施加MT脉冲(2E)的图像感兴趣区勾画,测得的M0=236.73,M1=187.07,则肿瘤的MTR值为0.209;2F:经病理(HE ×100)证实为低级别PDAC。
图3  男,59岁,胰腺尾部PDAC。3A:T2WI图像示胰体部见混杂高信号团片影(箭),经测量得出最大径为64 mm;3B:T1WI图像示团片影呈低信号(箭);3C:T1WI增强动脉期图像示病灶边缘可见强化,内部无明显强化(箭);3D~3E:分别为未施加MT脉冲(3D)及施加MT脉冲(3E)的图像感兴趣区勾画,测得的M0=275.82,M1=202.12,则肿瘤的MTR值为0.267;3F:经病理(HE ×40)证实为高级别PDAC。PDAC:胰腺导管腺癌;MT:磁化传递;MTR:磁化传递率。
Fig. 2  Male, 69 years old, PDAC in the pancreatic body. 2A: T2WI shows a slightly hyperintense nodule (arrow) in the pancreatic body, with a maximum diameter of 17 mm as measured; 2B: T1WI shows the nodule exhibiting slight hypotintensity (arrow); 2C: Contrast-enhanced T1WI portal phase image shows the lesion with heterogeneous enhancement (arrow), with a degree of enhancement lower than that of the normal pancreatic parenchyma; 2D-2E: Region of interest delineation on the images without an MT pulse applied (2D) and with an MT pulse applied (2E) respectively, with a measured M0 = 236.73, M1 = 187.07, respectively, the MTR value of the tumor is calculated as 0.209; 2F: Pathologically (HE ×100) confirmed as low-grade PDAC.
Fig. 3  Male, 59 years old, PDAC in the pancreatic tail. 3A: T2WI shows a heterogeneous hyperintense mass (arrow) in the pancreatic tail, with a maximum diameter of 64 mm as measured; 3B: T1-weighted image shows the mass exhibiting hypotintensity (arrow); 3C: Contrast-enhanced T1WI arterial phase image shows enhancement along the periphery of the lesion without significant internal enhancement (arrow); 3D-3E: Region of interest delineation on the images without an MT pulse applied (3D) and with an MT pulse applied (3E) respectively, with a measured M0 = 275.82, M1 = 202.12, respectively, the MTR value of the tumor is calculated as 0.267; 3F: Pathologically (HE ×40) confirmed as high-grade PDAC. PDAC: pancreatic ductal adenocarcinoma; MT: magnetic transfer; MTR: magnetic transfer rate.
表2  二元logistic回归筛选鉴别PDAC患者病理分级参数
Tab. 2  Identification of parameters for differentiating pathological grade in PDAC patients by binary logistic regression

2.6 年龄、MTR值及两者联合的诊断效能

       为进一步评估各因素对PDAC患者病理分级的鉴别能力,建立了年龄、MTR及两者联合的诊断模型。其中,联合诊断模型的回归方程为:logit(P)=-0.198-0.083×年龄+0.021×MTR×103。ROC分析显示,联合模型的诊断效能最高,AUC=0.844(95% CI:0.742~0.918),敏感度为76.0%,特异度为86.0%,显著优于单一年龄模型(AUC=0.683,P=0.007),但与单一MTR模型(AUC=0.830)的差异无统计学意义(P=0.563)。详见表3图4

图4  年龄、MTR值及两者联合对鉴别PDAC患者病理分级的ROC曲线。MTR:磁化转移率;PDAC:胰腺导管腺癌;ROC:受试者工作特征。
Fig. 4  ROC curves of age, MTR value, and their combination for discriminating pathological grade in PDAC patients. MTR: magnetization transfer ratio; PDAC: pancreatic ductal adenocarcinoma; ROC: receiver operating characteristic.
表3  年龄、MTR值及两者联合对PDAC患者病理分级的诊断效能
Tab. 3  Diagnostic performance of age, MTR value, and their combination for pathological grading in PDAC patients

3 讨论

       本研究利用MTI技术测量MTR值,以探讨其与PDAC组织病理学分级的关系。研究发现MTR值越高,PDAC组织病理学分级越高。进一步回归分析表明,MTR值与年龄是PDAC组织病理学分级的独立危险因素,基于二者构建的联合模型可实现术前无创评估PDAC分化程度,并展现出较高的预测效能。本研究系国内首次将MTI技术应用于PDAC组织病理学分级的术前评估,为临床提供了新的无创预测方法。

3.1 MTR值与PDAC纤维化的相关性

       胰腺纤维化是炎症、损伤等刺激下纤维结缔组织异常增生的病理过程,会导致胰腺功能不可逆丧失[24]。纤维化促进了PDAC的发生发展,驱动肿瘤的早期播散与转移,并会缩短手术患者的术后生存期[25, 26, 27]。纤维化也会损害化疗疗效,这可能是因为过度增生的纤维结缔组织在肿瘤周围形成致密的物理屏障,阻碍化疗药物抵达[28, 29]。同样,化疗药物也会通过上调胎盘生长因子水平,激活癌相关成纤维细胞,最终加剧纤维化[16]。因此,纤维化是PDAC预后不良的重要指标。MTI技术可间接反映组织内大分子(如胶原蛋白)的含量和微观结构变化,组织内大分子的含量越高,磁化传递效应越强,MTR值也就越高,因此可实现对纤维化的敏感检测[30]。利用MTR值反映纤维化程度的可行性已在肝脏、小肠、肾脏等多部位得到证实,且具有一定的敏感度[17, 18, 19]。本研究将MTI技术应用于胰腺,证实了MTR值评估PDAC纤维化的可行性,为MTR值成为术前评估PDAC病灶纤维化的影像学标志物提供新的证据。

3.2 MTR值与PDAC病理组织学分级的相关性

       根据肿瘤的分化程度及生物学行为,PDAC可分为高级别和低级别。高级别组分化更差,恶性程度更高,侵袭性更强,早期即可发生局部或远处转移,预后更差[11]。高级别PDAC患者即使行手术治疗预后可能也没有明显改善,部分患者甚至会因手术并发症降低生活质量[31]。如能通过术前影像学检查识别出高级别PDAC可影响治疗方案的制订、提高临床获益。本研究表明高级别组MTR值更高,这可能是因为高级别组肿瘤细胞分化程度更低,周围具有更致密的细胞外基质,更厚的胶原纤维,纤维化程度更高[8, 15, 32]。本研究中基于MTR构建的预测模型展现出了较高的诊断效能(AUC=0.830),并且MTI技术本身具有无辐射、无需对比剂、无需特殊专用线圈的优势,具有重要的临床应用价值与推广前景。

3.3 一般特征对预测PDAC病理组织学分级的附加价值

       本研究还分析了高、低级别组PDAC患者的年龄、性别、肿瘤部位、肿瘤最大径和肿瘤标志物水平(包括CEA和CA19-9),结果发现高级别组患者年龄更小,而其他一般特征的组间比较均未发现差异有统计学意义。既往研究结果均未提及年龄对PDAC病理组织学分级的预测价值[13, 14, 15]。基因组学研究未发现不同年龄组PDAC核心驱动基因突变频率之间存在差异[33]。关于年龄影响的结果差异可能是因为样本量较小,且75名患者平均年龄为64.2岁,最大为84岁,仅有2名患者年龄小于50岁,存在一定的选择偏倚。也可能是因为本研究需要术后病理结果提供PDAC病理组织学分级证据,所以仅可纳入手术患者,而高龄患者更易因一般状况较差失去手术机会,一定程度上削弱了高龄患者的代表性。年龄是否为PDAC病理组织学分级的独立危险因素还需要更多中心、更大样本的研究确定。但是,MTR值与年龄的联合预测模型相较于单一MTR模型,虽然诊断效能没有显著提高,但特异度提高了12.0%,也具有一定的临床价值。

3.4 本研究的局限性

       (1)单中心研究且样本量较少,存在一定的选择偏倚;(2)只关注了MTR值,未纳入其他MR功能参数进行综合评估;(3)为横断面研究,尚未进行随访。本研究仅初步证实了MTR值与PDAC病理组织学分级的相关性,后续应继续扩大样本量并进行随访,进一步探索MTR值对患者实际预后的预测价值。

4 结论

       综上所述,术前MTR值是术后PDAC病理组织学分级的独立危险因素。MTR值有望成为预测PDAC病理组织学分级的简便、无创、精准的术前影像学标志物,帮助制订个性化治疗方案,提高诊疗效果,最终改善患者预后。

[1]
SIEGEL R L, GIAQUINTO A N, JEMAL A. Cancer statistics, 2024[J]. CA Cancer J Clin, 2024, 74(1): 12-49. DOI: 10.3322/caac.21820.
[2]
GHEORGHE G, BUNGAU S, ILIE M, et al. Early diagnosis of pancreatic cancer: The key for survival[J/OL]. Diagnostics (Basel), 2020, 10(11): 869 [2025-09-28]. https://pubmed.ncbi.nlm.nih.gov/33114412/. DOI: 10.3390/diagnostics10110869.
[3]
NAPPO G, DONISI G, CAPRETTI G, et al. Early recurrence after upfront surgery for pancreatic ductal adenocarcinoma[J]. Curr Oncol, 2023, 30(4): 3708-3720. DOI: 10.3390/curroncol30040282.
[4]
ORTH M, METZGER P, GERUM S, et al. Pancreatic ductal adenocarcinoma: biological hallmarks, current status, and future perspectives of combined modality treatment approaches[J/OL]. Radiat Oncol, 2019, 14(1): 141 [2025-09-28]. https://pubmed.ncbi.nlm.nih.gov/31395068/. DOI: 10.1186/s13014-019-1345-6.
[5]
SHI S, LIANG C, XU J, et al. The strain ratio as obtained by endoscopic ultrasonography elastography correlates with the stroma proportion and the prognosis of local pancreatic cancer[J]. Ann Surg, 2020, 271(3): 559-565. DOI: 10.1097/SLA.0000000000002998.
[6]
YANG J B, ZENG L T, CHEN R W, et al. Leveraging tumor microenvironment infiltration in pancreatic cancer to identify gene signatures related to prognosis and immunotherapy response[J/OL]. Cancers, 2023, 15(5): 1442 [2025-09-28]. https://pubmed.ncbi.nlm.nih.gov/36900234/. DOI: 10.3390/cancers15051442.
[7]
沈志秋, 杨明明, 吕俊馨, 等. 磁化传递成像评价胰腺导管腺癌纤维化的可行性研究[J]. 磁共振成像, 2025, 16(5): 44-48. DOI: 10.12015/issn.1674-8034.2025.05.007.
SHEN Z Q, YANG M M, LÜ J X, et al. A feasibility study of magnetization transfer imaging on the evaluation of fibrosis in pancreatic duct adenocarcinoma[J]. Chin J Magn Reson Imaging, 2025, 16(5): 44-48. DOI: 10.12015/issn.1674-8034.2025.05.007.
[8]
LAKLAI H, MIROSHNIKOVA Y A, PICKUP M W, et al. Genotype tunes pancreatic ductal adenocarcinoma tissue tension to induce matricellular fibrosis and tumor progression[J]. Nat Med, 2016, 22(5): 497-505. DOI: 10.1038/nm.4082.
[9]
TIRKES T, SAEED O A, OSUJI V C, et al. Histopathologic correlation of pancreatic fibrosis with pancreatic magnetic resonance imaging quantitative metrics and Cambridge classification[J]. Abdom Radiol (NY), 2022, 47(7): 2371-2380. DOI: 10.1007/s00261-022-03532-2.
[10]
DUNET V, HALKIC N, SEMPOUX C, et al. Prediction of tumour grade and survival outcome using pre-treatment PET- and MRI-derived imaging features in patients with resectable pancreatic ductal adenocarcinoma[J]. Eur Radiol, 2021, 31(2): 992-1001. DOI: 10.1007/s00330-020-07191-z.
[11]
MACÍAS N, SAYAGUÉS J M, ESTEBAN C, et al. Histologic tumor grade and preoperative bilary drainage are the unique independent prognostic factors of survival in pancreatic ductal adenocarcinoma patients after pancreaticoduodenectomy[J/OL]. J Clin Gastroenterol, 2018, 52(2): e11-e17 [2025-09-28]. https://pubmed.ncbi.nlm.nih.gov/28059940/. DOI: 10.1097/mcg.0000000000000793.
[12]
FUKUI H, ONISHI H, OTA T, et al. Pancreatic fibrosis assessment and association with pancreatic cancer: comparison with the extracellular volume fraction[J/OL]. Clin Radiol, 2024, 79(11): e1356-e1365 [2025-09-28]. https://pubmed.ncbi.nlm.nih.gov/39266374/. DOI: 10.1016/j.crad.2024.08.007.
[13]
CHEN W Y, LIN G H, LI X, et al. Dual-energy computed tomography for predicting histological grading and survival in patients with pancreatic ductal adenocarcinoma[J]. Eur Radiol, 2025, 35(5): 2818-2832. DOI: 10.1007/s00330-024-11109-4.
[14]
CEN C Y, WANG C Y, WANG S Q, et al. Clinical-radiomics nomogram using contrast-enhanced CT to predict histological grade and survival in pancreatic ductal adenocarcinoma[J/OL]. Front Oncol, 2023, 13: 1218128 [2025-09-28]. https://pubmed.ncbi.nlm.nih.gov/37731637/. DOI: 10.3389/fonc.2023.1218128.
[15]
宋奇科, 钟时玲, 刘媛媛, 等. 磁共振弹性成像评价胰腺导管腺癌病理分级及生存期[J]. 磁共振成像, 2022, 13(3): 26-30. DOI: 10.12015/issn.1674-8034.2022.03.006.
SONG Q K, ZHONG S L, LIU Y Y, et al. MR elastography for evaluation of pathological grade of pancreatic ductal adenocarcinoma[J]. Chin J Magn Reson Imaging, 2022, 13(3): 26-30. DOI: 10.12015/issn.1674-8034.2022.03.006.
[16]
KIM D K, JEONG J, LEE D S, et al. PD-L1-directed PlGF/VEGF blockade synergizes with chemotherapy by targeting CD141+ cancer-associated fibroblasts in pancreatic cancer[J/OL]. Nat Commun, 2022, 13(1): 6292 [2025-09-28]. https://pubmed.ncbi.nlm.nih.gov/36272973/. DOI: 10.1038/s41467-022-33991-6.
[17]
SEO N, JEONG H K, CHOI J Y, et al. Liver MRI with amide proton transfer imaging: feasibility and accuracy for the characterization of focal liver lesions[J]. Eur Radiol, 2021, 31(1): 222-231. DOI: 10.1007/s00330-020-07122-y.
[18]
FANG Z N, LI X H, LIN J J, et al. Magnetisation transfer imaging adds information to conventional MRIs to differentiate inflammatory from fibrotic components of small intestinal strictures in Crohn's disease[J]. Eur Radiol, 2020, 30(4): 1938-1947. DOI: 10.1007/s00330-019-06594-x.
[19]
JIANG B C, LIU F, FU H D, et al. Advances in imaging techniques to assess kidney fibrosis[J/OL]. Ren Fail, 2023, 45(1): 2171887 [2025-09-28]. https://pubmed.ncbi.nlm.nih.gov/36723057/. DOI: 10.1080/0886022X.2023.2171887.
[20]
LI W G, ZHANG Z L, NICOLAI J, et al. Magnetization transfer MRI in pancreatic cancer xenograft models[J]. Magn Reson Med, 2012, 68(4): 1291-1297. DOI: 10.1002/mrm.24127.
[21]
SCHAWKAT K, ESHMUMINOV D, LENGGENHAGER D, et al. Preoperative evaluation of pancreatic fibrosis and lipomatosis: correlation of magnetic resonance findings with histology using magnetization transfer imaging and multigradient echo magnetic resonance imaging[J]. Invest Radiol, 2018, 53(12): 720-727. DOI: 10.1097/rli.0000000000000496.
[22]
NAGTEGAAL I D, ODZE R D, KLIMSTRA D, et al. The 2019 WHO classification of tumours of the digestive system[J]. Histopathology, 2020, 76(2): 182-188. DOI: 10.1111/his.13975.
[23]
DUAN K L, ZHOU H H, XU W N, et al. Evaluation of tumor fibrosis in pancreatic ductal adenocarcinoma by 2-D shear wave elastography: a pilot study[J]. Ultrasound Med Biol, 2023, 49(9): 2119-2125. DOI: 10.1016/j.ultrasmedbio.2023.06.003.
[24]
HUANG H Z, LU W Y, ZHANG X L, et al. Fibroblast subtypes in pancreatic cancer and pancreatitis: from mechanisms to therapeutic strategies[J]. Cell Oncol (Dordr), 2024, 47(2): 383-396. DOI: 10.1007/s13402-023-00874-x.
[25]
BAER J M, ZUO C, KANG L I, et al. Fibrosis induced by resident macrophages has divergent roles in pancreas inflammatory injury and PDAC[J]. Nat Immunol, 2023, 24(9): 1443-1457. DOI: 10.1038/s41590-023-01579-x.
[26]
SHI S Y, LUO Y J, WANG M, et al. Tumor fibrosis correlates with the survival of patients with pancreatic adenocarcinoma and is predictable using clinicoradiological features[J]. Eur Radiol, 2022, 32(9): 6314-6326. DOI: 10.1007/s00330-022-08745-z.
[27]
AL-HILAL T A, CHRYSOVERGI M A, GRASBERGER P E, et al. Durotaxis is a driver and potential therapeutic target in lung fibrosis and metastatic pancreatic cancer[J]. Nat Cell Biol, 2025, 27(9): 1543-1554. DOI: 10.1038/s41556-025-01697-8.
[28]
ADAMSKA A, DOMENICHINI A, FALASCA M. Pancreatic ductal adenocarcinoma: current and evolving therapies[J/OL]. Int J Mol Sci, 2017, 18(7): 1338 [2025-09-28]. https://pubmed.ncbi.nlm.nih.gov/28640192/. DOI: 10.3390/ijms18071338.
[29]
KUNG H C, YU J. Targeted therapy for pancreatic ductal adenocarcinoma: Mechanisms and clinical study[J/OL]. MedComm, 2023, 4(2): e216 [2025-09-28]. https://pubmed.ncbi.nlm.nih.gov/36814688/. DOI: 10.1002/mco2.216.
[30]
WOLFF S D, BALABAN R S. Magnetization transfer imaging: practical aspects and clinical applications[J]. Radiology, 1994, 192(3): 593-599. DOI: 10.1148/radiology.192.3.8058919.
[31]
CHANG N, CUI L L, LUO Y H, et al. Development and multicenter validation of a CT-based radiomics signature for discriminating histological grades of pancreatic ductal adenocarcinoma[J]. Quant Imaging Med Surg, 2020, 10(3): 692-702. DOI: 10.21037/qims.2020.02.21.
[32]
LI Q, YANG C, LI J Q, et al. The type I collagen paradox in PDAC progression: microenvironmental protector turned tumor accomplice[J/OL]. J Transl Med, 2025, 23(1): 744 [2025-09-28]. https://pubmed.ncbi.nlm.nih.gov/40616159/. DOI: 10.1186/s12967-025-06778-8.
[33]
BEN-AHARON I, ELKABETS M, PELOSSOF R, et al. Genomic landscape of pancreatic adenocarcinoma in younger versus older patients: does age matter [J]. Clin Cancer Res, 2019, 25(7): 2185-2193. DOI: 10.1158/1078-0432.CCR-18-3042.

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