分享:
分享到微信朋友圈
X
临床研究
基于磁共振扩散峰度成像的直肠癌微卫星不稳定状态研究
王莉莉 雷建凯 李生虎 崔雅琼 魏照坤 宋旭辉 马军 李大铭 马小梅 贾应梅 黄刚

WANG L L, LEI J K, LI S H, et al. Microsatellite instability of rectal cancer based on magnetic resonance diffusion kurtosis imaging[J]. Chin J Magn Reson Imaging, 2023, 14(8): 73-78.引用本文:王莉莉, 雷建凯, 李生虎, 等. 基于磁共振扩散峰度成像的直肠癌微卫星不稳定状态研究[J]. 磁共振成像, 2023, 14(8): 73-78. DOI:10.12015/issn.1674-8034.2023.08.012.


[摘要] 目的 探讨直肠癌微卫星不稳定(microsatellite instability, MSI)状态与磁共振扩散峰度成像(diffusion kurtosis image, DKI)各参数的相关性,为直肠癌治疗前后评估MSI状态提供影像学检测指标。材料与方法 回顾性纳入病理明确诊断为直肠癌的88例患者病例资料,所有患者行直肠癌根治术前一周内进行MRI检查,检查序列包含DKI,所得数据导入专用软件,获取DKI参数平均峰度(mean kurtosis, MK)、轴向峰度(axial kurtosis, Ka)、径向峰度(radial kurtosis, Kr)、平均扩散率(mean diffusion, MD)、轴向扩散率(axial diffusion, Da)、径向扩散率(radial diffusion, Dr)和各向异性分数(fractional anisotropy, FA)及术后病理生物学特征资料进行统计分析。采用组内相关系数评估两位观测者间的测量一致性。采用Kolmogorov-Smirnov检验分析DKI各参数分布正态性。采用Spearman相关系数比较DKI各定量参数与MSI和微卫星稳定(microsatellite stability, MSS)相关性。采用ROC曲线分析与MSI存在相关性的DKI各参数,观察其预测MSI的价值。采用DeLong检验比较各参数AUC值的统计学差异。P<0.05为差异具有统计学意义。结果 MSI和Da、Dr、Ka、MK之间的相关系数值分别为0.258(95% CI:0.122~0.386)、0.346(95% CI:0.191~0.476)、-0.276(95% CI:-0.421~-0.118)、-0.260(95% CI:-0.383~-0.139)。MSI和Da、Dr之间呈弱正相关关系,和Ka、MK呈弱负相关关系。MSI和MD、FA、Kr之间无显著相关性(P>0.05)。Da、Dr、Ka、MK诊断直肠癌微卫星不稳定的AUC值分别为0.759(95% CI:0.654~0.865)、0.847(95% CI:0.749~0.945)、0.777(95% CI:0.651~0.902)、0.758(95% CI:0.665~0.856),临界值分别为0.65、0.68、0.55、0.70。结论 直肠癌MSI状态与DKI参数存在相关性,且具有一定的预测价值,有望成为预测MSI状态的可选方法。
[Abstract] Objective To investigate the correlation between the microsatellite instability (MSI) status and each parameter of diffusion kurtosis image (DKI) in rectal cancer, and to provide imaging detection indicators for evaluating the MSI status before and after rectal cancer treatment.Materials and Methods Eighty eight patients with a pathologically definite diagnosis of rectal cancer were included for analysis. All patients underwent MRI examination within one week before radical resection of rectal cancer surgery. The examination sequence contained DKI imaging. The obtained data were imported into the dedicated software to acquire DKI parameters such as mean kurtosis (MK), axial kurtosis (Ka), radial kurtosis (Kr), mean diffusion (MD), axial diffusion (Da), radial diffusion (Dr), fractional anisotropy (FA), and postoperative pathobiological characteristics. These parameters were used for statistical analysis. Intra-class correlation coefficient was used to evaluate the measurement consistency between two observers. The Kolmogorov-Smirnov test was to assess the normal distribution of DKI parameters. Spearman correlation coefficient was employed to examine the correlation between each quantitative parameter of DKI and MSI and microsatellite stability (MSS). Spearman correlation coefficient was used to compare the correlation between each quantitative parameter of DKI and MSI and MSS. The ROC curve analysis was performed to analyze each parameter of DKI associated with the presence of MSI to observe its value in predicting MSI. The DeLong test was utilized to compare the statistical differences in the AUC of each parameter. P values less than 0.05 were considered statistically significant.Results The correlation coefficient values between MSI and the DKI parameters were as follows: 0.258 (95% CI: 0.122-0.386) for Da, 0.346 (95% CI: 0.191-0.476) for Dr, -0.276 (95% CI: -0.421--0.118) for Ka, and -0.260 (95% CI: -0.383--0.139) for MK. There was indeed a weak positive correlation observed between MSI and Da as well as Dr, while a weak negative correlation was found between Ka and MK. However, no significant correlation was observed between MSI and MD, FA, or Kr (P>0.05). The AUC values for Da, Dr, Ka, and MK in diagnosing MSI in rectal cancer were 0.759 (95% CI: 0.654-0.865), 0.847 (95% CI: 0.749-0.945), 0.777 (95% CI: 0.651-0.902), and 0.758 (95% CI: 0.665-0.856), respectively. The corresponding cut-off values were 0.65, 0.68, 0.55, and 0.70.Conclusions There is a correlation between MSI status and DKI parameters in rectal cancer, and they have some predictive value for it. This correlation is expected to make DKI parameters an optional method for predicting MSI status.
[关键词] 直肠癌;微卫星不稳定;磁共振成像;扩散峰度成像
[Keywords] rectal cancer;microsatellite instability;magnetic resonance imaging;diffusion kurtosis imaging

王莉莉 1   雷建凯 2   李生虎 3   崔雅琼 1   魏照坤 1   宋旭辉 1   马军 1   李大铭 1   马小梅 1   贾应梅 1   黄刚 1*  

1 甘肃省人民医院放射科,兰州 730000

2 高台县中医医院放射科,张掖 734300

3 无锡市中医医院放射科,无锡 214000

通信作者:黄刚,E-mail:keen0999@163.com

作者贡献声明:黄刚设计本研究的方案,对稿件重要内容进行了修改;王莉莉起草和撰写稿件,获取、分析或解释本研究的数据,获得了甘肃省科技计划项目基金资助;雷建凯、李生虎、崔雅琼、魏照坤、宋旭辉、马军、李大铭、马小梅、贾应梅获取、分析或解释本研究的数据,对稿件重要内容进行了修改;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: 甘肃省青年基金计划项目 20JR5RA143 甘肃省人民医院院内基金 20GSSY4-45
收稿日期:2023-02-24
接受日期:2023-07-21
中图分类号:R445.2  R735.37 
文献标识码:A
DOI: 10.12015/issn.1674-8034.2023.08.012
引用本文:王莉莉, 雷建凯, 李生虎, 等. 基于磁共振扩散峰度成像的直肠癌微卫星不稳定状态研究[J]. 磁共振成像, 2023, 14(8): 73-78. DOI:10.12015/issn.1674-8034.2023.08.012.

0 前言

       直肠癌是我国消化道常见的恶性肿瘤,其发生率与结肠癌接近,严重威胁着人类健康[1, 2]。近年来,直肠癌的治疗方法不断更新和发展,免疫治疗越来越受到关注。微卫星不稳定(microsatellite instability, MSI)是结直肠癌最佳的疗效预测指标之一[3, 4],主要由DNA错配修复(mismatch repair, MMR)基因突变或启动子甲基化引起,其状态对应着较为特殊的临床病理特征,与结直肠癌患者的预后、治疗相关[5, 6, 7, 8, 9]。MSI状态检测需要进行免疫组化或者基因分析,具有检测试剂依赖性、活检取材创伤性及并发症等风险,加之肿瘤组织在时间和空间的异质性导致检测结果偏倚,不利于肿瘤状态实时监测[10, 11, 12, 13]

       MRI因具有良好的软组织分辨率和多参数成像的特点,能够完整显示肿瘤整体状态及周围结构变化,在直肠癌诊断、临床分期、病理分级及预后评估等方面应用广泛。随着高场强MR设备的逐步应用,扩散峰度成像(diffusion kurtosis image, DKI)在肿瘤研究当中成为可能。这种技术利用生物组织内水分子扩散运动呈非高斯分布的原理进行成像,主要通过平均峰度(mean kurtosis, MK)、轴向峰度(axial kurtosis, Ka)、径向峰度(radial kurtosis, Kr)、平均扩散率(mean diffusion, MD)、轴向扩散率(axial diffusion, Da)、径向扩散率(radial diffusion, Dr)和各向异性分数(fractional anisotropy, FA)参数反映生物组织内微环境的复杂程度。已有较多关于DKI与直肠癌生物学特征等方面的相关研究[14, 15, 16, 17],不同的肿瘤组织学类型对DKI参数有不同程度影响,直肠黏液腺癌、KRAS突变病例中MD值显著增高,而MK值显著减低,且MK与预后因素相关。但到目前为止,对于DKI参数与MSI状态相互关系的研究极少。鉴于此,我们假设DKI参数与MSI存在一定的相关性。本研究旨在探寻能够体现MSI状态的DKI参数,为直肠癌的诊断、预后、治疗方案选择等方面提供可靠的影像学指标,从而扩大肿瘤患者在MRI检查中的应用范围,让更多患者从中受益。

1 材料与方法

1.1 病例资料

       本研究回顾性分析于2021年1月至2023年1月因直肠癌就诊于甘肃省人民医院的患者病例88例,其中男56例,女32例,年龄范围35~70岁,中位年龄51岁。纳入标准:(1)MRI检查时间段为术前1周,完成DKI序列扫描,且DKI参数FA、Dr、MD、Da、MK、Kr、Ka数据完整;(2)检查前未进行放疗或化疗等辅助治疗;(3)术后病理检查结果为直肠腺癌;(4)采用免疫组织化学方法检测肿瘤组织中MMR蛋白MLH1、MSH2、MSH6及PMS2的表达,数据完整。排除标准:(1)MRI图像不完善者(例如:因各种伪影导致无法进行后续诊断及后处理);(2)肿瘤体积小(小于5 mm),导致DKI专用软件处理失败者;(3)乙状结肠与直肠交界区肿瘤。本研究遵守《赫尔辛基宣言》,经甘肃省人民医院伦理委员会批准,免除受试者知情同意,批准文号:2022-370。

1.2 图像扫描及分析

       所有患者均采用3.0 T MRI扫描仪(Skyra, Siemens, Germany)及18通道相控矩阵表面线圈完成扫描。成像序列包括T1WI、T2WI、扩散加权成像(diffusion weighted imaging, DWI)及DKI。DKI扫描采用自旋回波-平面回波成像(spin echo-plane echo imaging, SE-EPI)技术。扫描参数:TR/TE 4900 ms/93 ms,扩散敏感梯度场30个,b值0、1000、2000 s/mm2,视野200 mm×200 mm,扫描时间10 min 13 s。

       扫描完成后,将DKI数据以DICOM格式导入Body Diffusion Toolbox(德国SIEMENS公司Healthcare GmbH,Erlangen)专用软件,由两位有10年腹部MRI影像诊断工作经历的副主任医师,在对临床病理等未知的情况下,参考常规序列图像和DKI伪彩图(图1),确定肿瘤实性区域,手动绘制ROI。为避免测量结果失真,尽量保持ROI范围一致,在选择ROI时,尽可能地包括肿瘤实性部分,最大程度避免周围脂肪和血管等结构。两位观测者测量结果的平均值为测得的FA、Dr、MD、Da、MK、Kr、Ka最终数据。

图1  男,57岁,直肠癌患者。1A:T2WI图像显示肿瘤(箭)在T2WI上显示等高信号影;1B:DWI图(b=1000 s/mm2)显示直肠信号升高(箭);3C:ADC图显示直肠癌低信号(箭);1D:DKI的MK图显示高亮黄绿色部分为直肠癌,其中红色类圆形区为感兴趣区。DWI:扩散加权成像;ADC:表观扩散系数;DKI:扩散峰度成像;MK:平均峰度。
Fig. 1  A 57-year-old male patient with rectal cancer shows an isointense signal (arrow) on T2WI (1A), an increased signal (arrow) on DWI (1B, b=1000 s/mm2), a low signal (arrow) on ADC map (1C), and a high-light yellow-green area on DKI's MK map (1D), which is the rectal cancer. The red circular area represents the region of interest. DWI: diffusion weighted imaging; ADC: apparent diffusion coefficient; DKI: diffusion kurtosis image; MK: mean kurtosis.

1.3 病理及免疫组化方法

       对入组患者的术后切除标本进行病理和免疫组化检测分析。免疫组化采用BenCHMARK-XT machine and Mul-timer系统(Roche公司,瑞士),Ultra View-DA染色,各制剂使用依据操作说明书严格执行。数据最终获取通过电子病例系统查询并详细纪录。包括患者性别、年龄、病理类型、T分期、MMR蛋白等。依据MMR蛋白表达情况将纳入患者分别定义,如显示完整MMR蛋白,即MLH1、MSH2、MSH6及PMS2均表达,记录为微卫星稳定(microsatellite stability, MSS),而那些丢失一种或多种MMR蛋白时,记录为MSI(图2)。

图2  病理图片,Ultra View-DA染色,放大倍数40×10。2A:PMS2蛋白表达阳性(方框);2B:MLH1蛋白表达阳性(方框);2C:MSH2蛋白表达缺失,而作为内对照的间质内淋巴细胞核着色(方框);2D:MSH6蛋白表达缺失,作为内对照的间质内淋巴细胞着色(方框)。
Fig. 2  The magnification of the above pathological images is 40×10, Ultra View-DA staining. 2A: Positive expression of PMS2 protein (box); 2B: Positive expression of MLHI protein (box); 2C: Demonstrates the absence of MSH2 protein expression, with interstitial lymphoid nucleus staining serving as an internal control (box); 2D: Displays the absence of MSH6 protein expression, with interstitial lymphocyte staining as an internal control (box).

1.4 统计学方法

       所有的统计学分析采用SPSS 26.0(IBM公司,美国)软件完成。两位观测者间的测量一致性评估采用组内相关系数,值大于0.75则说明一致性高,0.40~0.75之间为一致性较好,小于0.4说明一致性差。采用Kolmogorov-Smirnov检验DKI各参数分布正态性,符合正态分布的定量单数采用均数±标准差(x¯±s)表示,不满足正态分布的定量参数采用中位数(四分位数间距)表示。组间比较采用Mann-Whitney U检验。采用Spearman相关系数比较DKI各定量参数与MSI和MSS相关性。ROC曲线分析与MSI存在相关性的DKI参数,观察其预测MSI的价值,采用DeLong检验比较各参数AUC的差异。P<0.05为差异具有统计学意义。

2 结果

2.1 患者基本临床信息

       本研究当中共纳入病理明确诊断为直肠癌的患者病例88例,详细资料见表1。MSS组包括隆起型34例、溃疡型39例、浸润型7例;MSI组8例均为溃疡型,其中MLH1(-)1例,MSH6(-)1例,MSH2(-)4例,PMS2(-)1例,MSH6及MSH2均(-)1例。

表1  直肠癌患者基本信息和临床相关资料
Tab. 1  Basic information and clinically relevant data of rectal cancer patients

2.2 直肠癌MSI与DKI各参数相互关系

       两位观测者对DKI参数FA、Dr、MD、Da、MK、Kr、Ka的测量一致性组内相关系数值分别为0.898(95% CI:0.849~0.932)、0.946(95% CI:0.919~0.964)、0.938(95% CI:0.907~0.959)、0.956(95% CI:0.933~0.971)、0.868(95% CI:0.805~0.911)、0.926(95% CI:0.889~0.951)、0.820(95% CI:0.738~0.878),均大于0.75,一致性高,数据可进行后续研究。在进行二者相关性分析之前,对于DKI各参数进行正态性分布检验,因样本量大于50,故使用Kolmogorov-Smirnov检验,统计结果提示DKI各参数不具有正态分布特质。故进一步采用Spearman相关系数行相关性分析。结果提示MSI和Da、Dr、Ka、MK之间的相关系数值分布为0.258(95% CI:0.122~0.386)、0.346(95% CI:0.191~0.476)、-0.276(95% CI:-0.421~-0.118)、-0.260(95% CI:-0.383~-0.139),详见表2。即MSI和Da、Dr之间呈弱正相关关系,和Ka、MK呈弱负相关关系。而MSI和MD、FA、Kr之间无显著相关性(P>0.05)。

表2  直肠癌微卫星不稳定与DKI各参数相互关系
Tab. 2  Correlation between microsatellite instability and DKI parameters in rectal cancer

2.3 DKI参数预测直肠癌MSI能力评估

       为了进一步了解DKI参数对于直肠癌MSI的预测能力,对存在相关关系的参数Da、Dr、Ka、MK进一步行ROC曲线分析,如图3。Da、Dr、Ka、MK对应的AUC值为0.759(95% CI:0.654~0.865)、0.847(95% CI:0.749~0.945)、0.777(95% CI:0.651~0.902)、0.758(95% CI:0.665~0.856),临界值分别为0.65、0.68、0.55、0.70。

图3  参数Da、Dr检测MSI的ROC(3A)曲线和参数Ka、MK检测MSI的ROC曲线(3B)。Da:轴向扩散率;Dr:径向扩散率;MSI:微卫星不稳定;Ka:轴向峰度;MK:平均峰度。
Fig. 3  Displays the ROC curves for MSI detection using Da and Dr (3A) as well as Ka and MK (3B). Da: axial diffusion; Dr: radial diffusion; MSI: microsatellite instability; Ka: axial kurtosis; MK: mean kurtosis.

3 讨论

       本研究首次对DKI多个参数MK、Ka、Kr、MD、Da、Dr、FA与直肠癌患者MSI状态的相关性进行了研究。结果表明,MSI和Da、Dr之间呈弱正相关关系,和Ka、MK呈弱负相关关系,但此次研究尚未发现MSI与DKI参数MD、FA、Kr存在相关性。ROC曲线进一步分析提示DKI参数Da、Dr、Ka、MK对MSI状态具有较高的诊断价值。具体来说,DKI参数对直肠癌MSI具有一定的预测价值,为临床治疗决策提供一种可选择的无创检测技术,对于直肠癌的诊断和治疗具有重要的临床应用价值。

3.1 DKI评估直肠癌MSI状态的重要性

       在所有的消化道肿瘤当中,直肠癌发病率有增加趋势,位居第二[18]。治疗方法多为新辅助治疗后手术切除[19, 20],但是因肿瘤异质性等可能的相关原因,导致了放化疗反应的巨大个体差异,从完全反应到无反应程度各异。众所周知,直肠癌患者中MSI显示出比MSS更好的预后,且MSI患者对5-氟尿嘧啶(5-FU)的辅助化疗无效,寻求免疫治疗成为重要的有效治疗手段[21, 22],因此MSI也成为了免疫治疗的重要生物标志[23, 24]。有文献报道直肠癌MSI检出率为10.39%[25],本次研究中,检出率更低一些,约为9.09%。出现这些差异的原因考虑可能和直肠癌的位置、检测方法及样本量大小等有一定的关系。这也在一定程度上提示有创MSI检测方法并不完善,可能仍然存在诸多弊端。例如检测需要依赖检测试剂,采样具有一定的创伤性,以及肿瘤在时空上异质性,导致采样结果差异化。

3.2 DKI评估直肠癌MSI状态的可行性

       有学者基于CT影像组学模型来鉴别结直肠癌的MSI状态,也展现出较好的预测价值[26, 27, 28]。但CT检测存在电离辐射,软组织分辨率不及MRI。故此次研究中,选用MRI对直肠癌患者进行检查,可以避免上述弊端。目前为止,已有基于MRI的T1WI、T2WI、DWI和对比增强T1WI等多参数模式评估直肠癌MSI状态的相关研究[29, 30, 31],均提示其预测直肠癌患者的MSI状态性能良好。而此次研究当中采用DKI技术,分析对直肠癌患者MSI状态预测能力。研究结果初步发现,在众多参数当中,Da、Dr、Ka、MK与MSI存在相关性,并且MK、Ka与直肠癌患者MSI状态呈负相关,Da、Dr与其呈正相关。因MK、Ka、Da和Dr是DKI参数中的重要指标,代表了水分子扩散非高斯分布特点的显著性,即MK、Ka、Da和Dr大小与肿瘤微环境结构复杂程度,与肿瘤的异质性密切相关,且MK值越大,微环境结构越复杂,反之亦然。此研究结果也进一步提示了DKI技术具有评估肿瘤组织复杂微结构的能力,并且对于MSI状态具有一定的预测价值,预测性能之间差异并无统计学意义。但DKI参数MD、FA、Kr在本次研究中,未发现与MSI状态存在相关性。之所以出现这样的结果,考虑可能和样本量大小有一定关系,需要后续扩大样本量,选用人工智能等方法分割肿瘤组织,提高检测结果的精确性。

3.3 本研究的局限性

       本研究存在的不足之处:第一,本次研究为单中心研究,纳入88例直肠癌患者,样本量相对不足。本研究在持续研究当中,后续会增加样本量、开展多中心研究以不断完善研究结果。第二,DKI扫描对设备性能要求较高,并且扫描参数目前还没有统一标准,可能会影响检测结果的可重复性。因此在临床实际使用过程中仍然受到限制。第三,手动选择ROI,影响研究数据准确性。后期研究过程中,尽可能将人工智能等自动分割技术应用到DKI参数后处理当中。

4 结论

       总之,MRI DKI作为一种非侵入性的无创检查方法,与直肠癌患者的MSI状态存在相关性,对其具有一定的预测价值;作为预测MSI状态的可选方法,有助于直肠癌患者新辅助放化疗和免疫治疗等方案的正确选择,让患者从中受益。

[1]
中国抗癌协会, 中国抗癌协会大肠癌专业委员会. 中国恶性肿瘤整合诊治指南-直肠癌部分[J/OL]. 中华结直肠疾病电子杂志, 2022, 11(2):89-103 [2023-01-10]. https://zhjzcjbdzzz.cma-cmc.com.cn/CN/10.3877/cma.j.issn.2095-3224.2022.01.001. DOI: 10.3877/cma.j.issn.2095-3224.2022.02.001.
China Anti-Cancer Association, China Anti-Cancer Association Colorectal Cancer Professional Committee. CACA guidelines for holistic integrative management of cancer-Rectal cancer[J/OL]. Chin J Colorectal Dis Electron Ed, 2022, 11(2):89-103 [2023-01-10]. https://zhjzcjbdzzz.cma-cmc.com.cn/CN/10.3877/cma.j.issn.2095-3224.2022.01.001. DOI: 10.3877/cma.j.issn.2095-3224.2022.02.001.
[2]
BENSON A B, VENOOK A P, AL-HAWARY M M, et al. Rectal cancer, version 2.2022, NCCN clinical practice guidelines in oncology[J]. J Natl Compr Canc Netw, 2022, 20(10): 1139-1167. DOI: 10.6004/jnccn.2022.0051.
[3]
陈功. 结直肠癌免疫治疗现状及进展[J]. 精准医学杂志, 2019, 34(1): 1-5. DOI: 10.13362/j.jpmed.201901001.
CHEN G. Current situation and progress of immunotherapy for colorectal cancer[J]. J Precis Med, 2019, 34(1): 1-5. DOI: 10.13362/j.jpmed.201901001.
[4]
ZHANG X, WU T, CAI X Y, et al. Neoadjuvant immunotherapy for MSI-H/dMMR locally advanced colorectal cancer: new strategies and unveiled opportunities[J/OL]. Front Immunol, 2022, 13: 795972 [2023-01-10]. https://pubmed.ncbi.nlm.nih.gov/35371084/. DOI: 10.3389/fimmu.2022.795972.
[5]
BANDO H, TSUKADA Y, INAMORI K, et al. Preoperative chemoradiotherapy plus nivolumab before surgery in patients with microsatellite stable and microsatellite instability-high locally advanced rectal cancer[J]. Clin Cancer Res, 2022, 28(6): 1136-1146. DOI: 10.1158/1078-0432.CCR-21-3213.
[6]
SWETS M, GRAHAM MARTINEZ C, VAN VLIET S, et al. Microsatellite instability in rectal cancer: what does it mean? A study of two randomized trials and a systematic review of the literature[J]. Histopathology, 2022, 81(3): 352-362. DOI: 10.1111/his.14710.
[7]
MATSUBAYASHI H, OISHI T, SASAKI K, et al. Discordance of microsatellite instability and mismatch repair immunochemistry occurs depending on the cancer type[J]. Hum Pathol, 2023, 135: 54-64. DOI: 10.1016/j.humpath.2022.12.016.
[8]
MAHMOUD N N. Colorectal cancer: preoperative evaluation and staging[J]. Surg Oncol Clin N Am, 2022, 31(2): 127-141. DOI: 10.1016/j.soc.2021.12.001.
[9]
ZHANG Y, ZHANG F, ZHAO L D, et al. Long-term survival of a patient with microsatellite-stable refractory colorectal cancer with regorafenib and PD-1 inhibitor sintilimab: a case report and review of literature[J/OL]. BMC Gastroenterol, 2021, 21(1): 399 [2022-12-09]. https://pubmed.ncbi.nlm.nih.gov/34688262/. DOI: 10.1186/s12876-021-01950-y.
[10]
OH C R, KIM J E, KANG J, et al. Prognostic value of the microsatellite instability status in patients with stage Ⅱ/Ⅲ rectal cancer following upfront surgery[J/OL]. Clin Colorectal Cancer, 2018, 17(4): e679-e685 [2022-12-10]. https://pubmed.ncbi.nlm.nih.gov/30077598/. DOI: 10.1016/j.clcc.2018.07.003.
[11]
RATOVOMANANA T, COHEN R, SVRCEK M, et al. Performance of next-generation sequencing for the detection of microsatellite instability in colorectal cancer with deficient DNA mismatch repair[J/OL]. Gastroenterology, 2021, 161(3): 814-826.e7 [2022-12-08]. https://pubmed.ncbi.nlm.nih.gov/33992635/. DOI: 10.1053/j.gastro.2021.05.007.
[12]
SAMAISON L, UGUEN A. Idylla MSI test combined with immunohistochemistry is a valuable and cost effective strategy to search for microsatellite instable tumors of noncolorectal origin[J]. Pathol Int, 2022, 72(4): 234-241. DOI: 10.1111/pin.13208.
[13]
SHIA J R. The diversity of tumours with microsatellite instability: molecular mechanisms and impact upon microsatellite instability testing and mismatch repair protein immunohistochemistry[J]. Histopathology, 2021, 78(4): 485-497. DOI: 10.1111/his.14271.
[14]
TANG C, LU G X, XU J M, et al. Diffusion kurtosis imaging and MRI-detected extramural venous invasion in rectal cancer: correlation with clinicopathological prognostic factors[J/OL]. Abdom Radiol, 2023, 48(3): 844-854 [2023-01-10]. https://pubmed.ncbi.nlm.nih.gov/36562818/. DOI: 10.1007/s00261-022-03782-0.
[15]
王莉莉, 李生虎, 黄刚, 等. 基于磁共振扩散峰度成像直肠癌生物学特征研究[J]. 磁共振成像, 2020, 11(1): 35-39. DOI: 10.12015/issn.1674-8034.2020.01.008.
WANG L L, LI S H, HUANG G, et al. Study on biological characteristics of rectal cancer based on magnetic resonance diffusion kurtosis imaging[J]. Chin J Magn Reson Imag, 2020, 11(1): 35-39. DOI: 10.12015/issn.1674-8034.2020.01.008.
[16]
HU S, PENG Y, WANG Q S, et al. T2*-weighted imaging and diffusion kurtosis imaging (DKI) of rectal cancer: correlation with clinical histopathologic prognostic factors[J]. Abdom Radiol, 2022, 47(2): 517-529. DOI: 10.1007/s00261-021-03369-1.
[17]
DING X, SUN D Q, GUO Q C, et al. The value of diffusion kurtosis imaging and intravoxel incoherent motion quantitative parameters in predicting synchronous distant metastasis of rectal cancer[J/OL]. BMC Cancer, 2022, 22(1): 920 [2023-02-05]. https://pubmed.ncbi.nlm.nih.gov/36008790/. DOI: 10.1186/s12885-022-10022-7.
[18]
SUNG H, FERLAY J, SIEGEL R L, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2021, 71(3): 209-249. DOI: 10.3322/caac.21660.
[19]
SCHLECHTER B L. Management of rectal cancer[J]. Hematol Oncol Clin North Am, 2022, 36(3): 521-537. DOI: 10.1016/j.hoc.2022.03.002.
[20]
ZHOU L, YANG X Q, ZHAO G Y, et al. Meta-analysis of neoadjuvant immunotherapy for non-metastatic colorectal cancer[J/OL]. Front Immunol, 2023, 14: 1044353 [2023-06-09]. https://pubmed.ncbi.nlm.nih.gov/36776899/. DOI: 10.3389/fimmu.2023.1044353.
[21]
SU A L, PEDRAZA R, KENNECKE H. Developments in checkpoint inhibitor therapy for the management of deficient mismatch repair (dMMR) rectal cancer[J]. Curr Oncol, 2023, 30(4): 3672-3683. DOI: 10.3390/curroncol30040279.
[22]
MIYAMOTO Y, OGAWA K, OHUCHI M, et al. Emerging evidence of immunotherapy for colorectal cancer[J]. Ann Gastroenterol Surg, 2023, 7(2): 216-224. DOI: 10.1002/ags3.12633.
[23]
SAHIN I H, ZHANG J, SARIDOGAN T, et al. Neoadjuvant immune checkpoint inhibitor therapy for patients with microsatellite instability-high colorectal cancer: shedding light on the future[J]. JCO Oncol Pract, 2023, 19(5): 251-259. DOI: 10.1200/OP.22.00762.
[24]
SAKATA S, LARSON D W. Targeted therapy for colorectal cancer[J]. Surg Oncol Clin N Am, 2022, 31(2): 255-264. DOI: 10.1016/j.soc.2021.11.006.
[25]
ZHANG W, YIN H K, HUANG Z X, et al. Development and validation of MRI-based deep learning models for prediction of microsatellite instability in rectal cancer[J]. Cancer Med, 2021, 10(12): 4164-4173. DOI: 10.1002/cam4.3957.
[26]
WU J J, ZHANG Q H, ZHAO Y, et al. Radiomics analysis of iodine-based material decomposition images with dual-energy computed tomography imaging for preoperatively predicting microsatellite instability status in colorectal cancer[J/OL]. Front Oncol, 2019, 9: 1250 [2022-12-05]. https://pubmed.ncbi.nlm.nih.gov/31824843/. DOI: 10.3389/fonc.2019.01250.
[27]
GOLIA PERNICKA J S, GAGNIERE J, CHAKRABORTY J, et al. Radiomics-based prediction of microsatellite instability in colorectal cancer at initial computed tomography evaluation[J]. Abdom Radiol, 2019, 44(11): 3755-3763. DOI: 10.1007/s00261-019-02117-w.
[28]
YUAN H, PENG Y, XU X R, et al. A tumoral and peritumoral CT-based radiomics and machine learning approach to predict the microsatellite instability of rectal carcinoma[J]. Cancer Manag Res, 2022, 14: 2409-2418. DOI: 10.2147/CMAR.S377138.
[29]
HUANG Z X, ZHANG W, HE D, et al. Development and validation of a radiomics model based on T2WI images for preoperative prediction of microsatellite instability status in rectal cancer: study Protocol Clinical Trial (SPIRIT Compliant)[J/OL]. Medicine, 2020, 99(10): e19428 [2022-12-08]. https://pubmed.ncbi.nlm.nih.gov/32150094/. DOI: 10.1097/MD.0000000000019428.
[30]
LI Z, ZHANG J, ZHONG Q, et al. Development and external validation of a multiparametric MRI-based radiomics model for preoperative prediction of microsatellite instability status in rectal cancer: a retrospective multicenter study[J]. Eur Radiol, 2023, 33(3): 1835-1843. DOI: 10.1007/s00330-022-09160-0.
[31]
ZHANG Y, LIU J, WU C Y, et al. Preoperative prediction of microsatellite instability in rectal cancer using five machine learning algorithms based on multiparametric MRI radiomics[J/OL]. Diagnostics, 2023, 13(2): 269 [2023-06-10]. https://pubmed.ncbi.nlm.nih.gov/36673079/. DOI: 10.3390/diagnostics13020269.

上一篇 肿块型肝内胆管细胞癌的MRI增强特征与相关病理及预后
下一篇 基于小视野扩散加权成像的影像组学模型对临床显著性前列腺癌的诊断价值
  
诚聘英才 | 广告合作 | 免责声明 | 版权声明
联系电话:010-67113815
京ICP备19028836号-2