MRI影像组学联合炎症因子对肝细胞肝癌微血管侵犯的预测价值

【摘要】目的：探讨基于MRI影像组学联合炎症因子术前预测肝细胞肝癌（HCC）微血管侵犯（MVI）的价值。方法：纳入经病理证实的HCC患者221例,其中MVI阳性117例,MVI阴性104例。比较MVI阴性与阳性患者的炎症因子、影像特征差异,运用多因素Logistic分析确定MVI的独立危险因素,建立影像特征及炎症因子预测模型。勾画Gd-DTPA 增强门静脉期瘤周20mm及瘤内所有层面,使用最小绝对收缩和选择算子（LASSO）算法筛选影像组学特征,建立瘤周、瘤内、瘤周及瘤内共三种影像组学模型。选择瘤周、瘤内影像组学及炎症因子建立联合预测模型,使用ROC曲线在验证组中评估模型的预测效能。结果：Logistic多因素分析结果显示肿瘤最大直径、包膜、动脉期瘤周强化、［碱性磷酸酶（ALP）+γ-谷氨酰转肽酶(GGT)］/淋巴细胞计数（AGLR）是MVI的独立危险因素,基于上述独立危险因素建立的影像特征及炎症因子预测模型预测HCC MVI的ROC曲线下面积（AUC）训练组为0.80,验证组为0.75。基于瘤周及瘤内影像组学建立的影像组学模型较仅包含瘤内影像组学的模型预测HCC MVI的AUC高（瘤周及瘤内模型在训练组和验证组的AUC分别为0.83、0.79,瘤内模型在训练组和验证组的AUC分别为0.75、0.73）。瘤周、瘤内影像组学及炎症因子构建的联合预测模型预测HCC MVI的AUC训练组为0.87,验证组为0.82。结论：基于Gd-DTPA门静脉期建立的瘤周及瘤内影像组学模型可对HCC MVI进行术前预测,联合炎症因子可进一步提高其预测效能。     

基于多序列MRI影像组学评分及临床参数预测肝细胞癌微血管浸润的nomogram模型研究

目的:基于肝细胞癌(HCC)患者的临床资料及多模态肝脏影像组学分析建立机器学习模型,探讨此模型术前预测HCC微血管浸润(MVI)的价值。方法:回顾性分析2020年3月-2021年9月在本院经病理证实为原发性HCC的130例患者的术前肝脏MRI及临床资料。基于病理检查结果,将患者分为MVI阳性组及MVI阴性组。记录患者的各项术前临床资料。所有患者术前行MRI检查,检查序列包括T₂WI、DWI和ADC以及Gd-EOB-DTPA对比增强动脉期、门脉期、延迟期和肝胆期T₁WI共7个序列。由放射科医师评估肿瘤的常规影像特征。自7个序列的图像上分别提取影像组学特征并进行降维,然后采用线性支持向量机(SVM)方法构建预测MVI的预测模型。再将所有序列图像提取的特征整合,经降维分析后最终筛选出6个最佳组学特征并采用线性SVM方法构建多序列联合组学模型,然后基于此多序列联合组学模型计算每例患者的放射组学评分(Radscore)作为后续建模特征。最后共采用了5种机器学习算法对上述三类资料(即临床资料、常规影像特征、组学特征)中筛选出的特征进行综合模型的构建,包括...     

钆塞酸二钠增强MRI特征对肝细胞癌微血管侵犯的预测价值

目的 探讨术前钆塞酸二钠增强MRI特征预测肝细胞癌（HCC）微血管侵犯（MVI）的价值。 方法 回顾性分析83例经手术病理确诊的HCC病人的术前影像及临床资料,其中男75例,女8例,平均（57.6±11.4）岁。所有病人均进行了MRI平扫和增强检查,分析其常规MRI征象和肝胆期征象。根据术后病理结果将病人分为MVI阳性组30例及MVI阴性组53例。采用t检验或χ²检验比较2组间临床和影像特征的差异,将差异有统计学意义的特征纳入多因素Logistic回归分析,获得独立危险因素后分别建立单独预测模型及联合预测模型,采用受试者操作特征曲线评估不同模型的预测效能,计算其曲线下面积（AUC）,并采用DeLong检验比较不同模型预测MVI的AUC。 结果 与MVI阴性组相比,MVI阳性组的肝胆期肿瘤最大径、瘤周晕征、肿瘤边缘分型中的单结节外突/多结节融合型占比均更高,肿瘤信号强度比值较低;常规MRI征象中包膜不完整性、瘤周强化的占比更高;AFP水平大于MVI阴性组（均P<0.05）。多因素Logistic回归分析显示肝胆期的肿瘤最大径、瘤周晕征和单结节外突/多结节融合型均为HCC MVI的独立危险因素（OR值分别为1.424、26.998、6.144,均P<0.05）,肿瘤最大径越大、瘤周晕征阳性及单结节外突/多结节融合型表现的病人发生MVI的风险越高。联合预测模型、肿瘤最大径模型、单结节外突/多结节融合型模型和瘤周晕征模型预测MVI的AUC分别为0.926、0.803、0.792、0.823。联合模型预测MVI的敏感度、特异度和AUC值均最高,且AUC值分别高于肿瘤最大径模型、单结节外突/多结节融合型模型和瘤周晕征模型（均P<0.05）。 结论 钆塞酸二钠增强MRI上肿瘤最大径、单结节外突/多结节融合型和肝胆期瘤周晕征是预测MVI的独立危险因素,且三者联合预测效能更高。     

医学影像人工智能在预测肝细胞癌微血管侵犯中的研究

【摘要】肝细胞癌（HCC）是常见的消化系统恶性肿瘤,死亡率较高。HCC患者发生微血管侵犯(MVI)是肝癌术后复发和远期生存率的独立预测因素,术前无创、高效地预测MVI有着重要的临床意义。目前许多研究使用人工智能技术利用影像特征构建模型,预测MVI和预后,表现出了不错的应用前景。本文查阅了近年来使用人工智能技术构建模型预测MVI的相关文献,总结及概括现阶段该领域研究进展,以期为进一步研究提出新思考。     

钆塞酸二钠增强多模态 MRI联合临床特征同时预测肝细胞癌CK19表达及微血管侵犯的价值

【摘要】目的：探讨钆塞酸二钠多模态MRI联合临床特征构建的列线图模型同时预测肝细胞癌（HCC）中CK19表达及微血管侵犯(MVI)的价值。方法：回顾性搜集经病理诊断为单发性HCC的106例患者的病例资料,术前均行钆塞酸二钠增强多模态MRI检查,且术后病理报告清晰描述CK19及MVI状态。将CK19/MVI双生物学标志物分为双阳组（CK19及MVI均为阳性,19例）与非双阳组（87例）,比较两组间临床及影像特征的差异,通过多因素Logistic回归筛选独立预测因子,并通过R软件构建CK19/MVI双阳性表达的列线图模型。结果：临床特征中年龄、AFP、NLR、PLR在双阳组与非双阳组间差异有统计学意义（P＜0.05）,影像特征中T1rt-pre、T1rt-20min、ADC值、肿瘤直径、肿瘤包膜、肿瘤边缘、坏死、瘤周强化、肝胆期瘤周低信号在两组间差异有统计学意义（P＜0.05）,其余参数在两组间差异无统计学意义（P＞0.05）。多因素Logistic回归分析结果显示PLR、T1rt-20min、肝胆期瘤周低信号是CK19/MVI双阳表达的独立预测因子,各预测因子的ROC曲线下面积（AUC）分别为0.729、0.706、0.708。建立的列线图预测模型AUC为0.854,校准预测曲线与标准曲线贴合尚可。结论：钆塞酸二钠增强多模态MRI联合临床特征术前能较好地同时预测CK19表达及微血管侵犯,并通过列线图模型为个体化预测提供参考。     

基于增强CT图像纹理特征术前预测肝细胞癌微血管侵犯状态及危险度等级

【摘要】目的：探讨基于增强CT图像纹理特征模型术前预测肝细胞癌（HCC）微血管侵犯（MVI）的价值。方法：回顾性搜集本院2018年1月至2022年12月经手术病理证实的HCC患者496例，按2:1的比例随机分为训练组（331例）和测试组（165例）。采用ITK SNAP图像纹理分析软件对HCC瘤灶及瘤周邻近区域勾画兴趣区（ROI）并进行图像纹理特征提取、筛选，采用最小绝对收缩与选择算子（LASSO）回归算法对576个纹理特征进行降维，使用多变量Logistic回归提取有意义的纹理特征建立模型以预测MVI状态及危险度等级。联合纹理特征和肿瘤临床分期建立列线图以预测MVI危险度等级。采用ROC曲线下面积（AUC）评价模型的诊断效能。结果：训练组与测试组患者的年龄、性别、肿瘤位置差异均无统计学意义。基于增强CT图像纹理特征模型可以较好地预测MVI状态及危险度等级，在训练组和验证组中预测有无MVI的AUC分别为0.783、0.773，敏感度分别为0.705、0.883，特异度分别为 0.750、0.722；在训练组和验证组中预测MVI危险度等级的AUC分别为0.743、0.718。联合纹理特征和肿瘤临床分期建立的列线图对MVI危险度等级的预测效能（AUC=0.856）优于单纯纹理特征模型。结论：基于增强CT图像纹理特征模型可用于术前预测肝细胞癌的MVI状态和危险度等级，是一种可靠的临床评估工具，对临床医师选择合适的治疗方案、准确评估预后具有重要参考价值。     

原发性肝细胞肝癌微血管浸润分级的危险因素预测

【摘要】目的：肝切除术前预测肝细胞肝癌（HCC）微血管浸润（MVI）的分级有助于患者治疗策略的选择和预后的评估,本文对原发性HCC的MVI分级预测进行研究。方法：对117例经术后病理证实的原发性HCC患者进行回顾性研究,分析患者的基线资料及各项临床指标（性别、年龄、AFP、肝炎和肝硬化有无）、影像特征（肿瘤直径、数量、包膜）、病理（Edmondson分级）,将所有病例分为M0（无MVI）、M1（MVI低危组）和M2（MVI高危组）三组。采用单因素秩和检验、logistic回归、ROC曲线进行统计学分析。结果：单因素秩和检验显示不同MVI分级患者的肿瘤直径、包膜的差异有统计学意义（P＜0.001）,不同MVI分级的病理Edmondson分级差异也有统计学意义（P= 0.037）,其余因素在不同MVI分级中差异均无统计学意义（P>0.05）;进一步有序多分类logistic回归分析显示肿瘤直径（OR=0.195,P＜0.001）、包膜（OR=6.772,P＜0.001）及Edmondson分级（OR=5.720,P=0.040）为肝癌MVI分级的独立预测因子。预测MVI分级的最佳肿瘤直径临界值为3.9cm,直径＞3.9cm是MVI 2级的预测因子,其敏感度为92%,特异度为48.9%,曲线下面积（AUC）为0.764（95%CI：0.656～0.872,P＜0.001）。结论：肿瘤直径和包膜可作为术前肝癌MVI分级的有效预测指标,其预测效果与术后Edmondson分级相同。预测原发性HCC的MVI级别的最佳肿瘤直径阈值为3.9cm。     

增强CT提取影像组学特征联合临床参数评估肝细胞癌微血管侵犯

目的 基于术前增强CT动脉期与静脉期图像分别提取影像组学参数联合临床参数构建影像临床联合模型评估肝细胞癌(HCC)患者是否微血管侵犯(MVI)。方法 回顾性搜集重庆医科大学附属第三医院以及重庆医科大学附属大学城医院2016年3月至2021年3月术后经病理证实有无MVI的HCC患者。以重庆医科大学附属第三医院的HCC患者为第一中心,以分层随机为原则将MVI阳性和MVI阴性的患者按照7∶3比例分为训练组和内部测试组,以重庆医科大学附属大学城医院患者为外部验证组,对所有患者进行原发病灶分割后,分别根据动脉期和静脉期进行影像组学特征提取。以训练组患者是否MVI阳性为研究标签,采用最小冗余最大相关(mRMR)以及套索算法(LASSO)进行影像组学特征降唯,并构建影像组学标签(Radscore);继而对临床参数进行特征降唯,以训练组患者是否MVI阳性为研究标签,采用多元逻辑回归构建临床模型Clinics。同时纳入联合临床模型中的临床参数与Radscore构建多元逻辑回归模型评估训练组患者是否MVI阳性,采用受试者工作特征曲线(ROC)评估Radscore, Clinics以及联合模型诊断MVI阳性...     

原发性肝细胞癌微血管侵犯的术前诊断研究进展

原发性肝细胞癌（HCC）是最常见的恶性肿瘤之一,术后复发率高,预后差。微血管侵犯（MVI）指在显微镜下于内皮细胞衬覆的脉管腔内见到癌细胞巢团,且没有肉眼可发现的肿瘤血管侵犯,是导致HCC术后复发、影响预后最重要的因素之一。MVI的术前诊断对综合治疗方案的制定及预后判断有重要价值,但术前准确诊断仍存在较大的挑战。主要从临床、分子生物学、影像表现等方面对MVI术前诊断的研究进展进行综述。      

体素内不相干运动成像在预测肝癌微血管侵犯中的价值

【摘要】目的：探讨体素内不相干运动成像（IVIM）在预测肝细胞肝癌（HCC）微血管侵犯（MVI）中的价值。方法：回顾性纳入经手术病理证实为HCC的104例患者,并分为MVI阳性组和MVI阴性组。所有患者术前均完成了单b值DWI、多b值IVIM及增强扫描。测量HCC患者DWI参数表观扩散系数（ADC）及IVIM参数扩散系数（D）、灌注相关扩散系数（D*）和灌注分数（f）。比较MVI阳性组和阴性组DWI和IVIM参数的差异。采用Logistic回顾分析预测MVI阳性的独立危险因素,同时采用受试者操作特征（ROC）曲线评估差异有统计学意义的参数对MVI的预测效能。结果：在104例HCC中,MVI阳性57例,MVI阴性47例;MVI阳性组的ADC值和D值均低于MVI阴性组（P<0.05）,而两组的D*和f值差异无统计学意义（P>0.05）。D值是预测MVI的独立危险因素,当其临界值为0.853×10-3mm2/s,预测MVI阳性的曲线下面积（AUC）、敏感度、特异度分别为0.826,80.9%和71.2%。结论：D值在预测HCC患者的MVI中优于ADC值,IVIM成像有助于HCC患者的精准治疗及术后管理。     

Preoperative prediction of microvascular invasion of hepatocellular carcinoma using <Superscript>18</Superscript>F-FDG PET/CT: a multicenter retrospective cohort study

Purpose

The aim of this study was to assess the potential of tumor ¹⁸F-fluorodeoxyglucose (FDG) avidity as a preoperative imaging biomarker for the prediction of microvascular invasion (MVI) of hepatocellular carcinoma (HCC).

Methods

One hundred and fifty-eight patients diagnosed with Barcelona Clinic Liver Cancer stages 0 or A HCC (median age, 57 years; interquartile range, 50–64 years) who underwent ¹⁸F-FDG positron emission tomography with computed tomography (PET/CT) before curative surgery at seven university hospitals were included. Tumor FDG avidity was measured by tumor-to-normal liver standardized uptake value ratio (TLR) of the primary tumor on FDG PET/CT imaging. Logistic regression analysis was performed to identify significant parameters associated with MVI. The predictive performance of TLR and other clinical variables was assessed using receiver operating characteristic (ROC) curve analysis.

Results

MVI was present in 76 of 158 patients with HCCs (48.1%). Multivariable logistic regression analysis revealed that TLR, serum alpha-fetoprotein (AFP) level, and tumor size were significantly associated with the presence of MVI (P?<?0.001). Multinodularity was not significantly associated with MVI (P?=?0.563). The area under the ROC curve (AUC) for predicting the presence of MVI was best with TLR (AUC?=?0.704), followed by tumor size (AUC?=?0.685) and AFP (AUC?=?0.670). We were able to build an improved prediction model combining TLR, tumor size, and AFP by using multivariable logistic regression modeling (AUC?=?0.756).

Conclusions

Tumor FDG avidity measured by TLR on FDG PET/CT is a preoperative imaging biomarker for the prediction of MVI in patients with HCC.

     

Development and validation of a novel predictive scoring model for microvascular invasion in patients with hepatocellular carcinoma

PurposeMicrovascular invasion (MVI) in patients with hepatocellular carcinoma (HCC) cannot be accurately predicted preoperatively. This study aimed to establish a predictive scoring model of MVI in solitary HCC patients without macroscopic vascular invasion.MethodsA total of 309 consecutive HCC patients who underwent curative hepatectomy were divided into the derivation (n = 206) and validation cohort (n = 103). A predictive scoring model of MVI was established according to the valuable predictors in the derivation cohort based on multivariate logistic regression analysis. The performance of the predictive model was evaluated in the derivation and validation cohorts.ResultsPreoperative imaging features on CECT, such as intratumoral arteries, non-nodular type of HCC and absence of radiological tumor capsule were independent predictors for MVI. The predictive scoring model was established according to the β coefficients of the 3 predictors. Area under receiver operating characteristic (AUROC) of the predictive scoring model was 0.872 (95% CI, 0.817-0.928) and 0.856 (95% CI, 0.771-0.940) in the derivation and validation cohorts. The positive and negative predictive values were 76.5% and 88.0% in the derivation cohort and 74.4% and 88.3% in the validation cohort. The performance of the model was similar between the patients with tumor size ≤5 cm and >5 cm in AUROC (P = 0.910).ConclusionsThe predictive scoring model based on intratumoral arteries, non-nodular type of HCC, and absence of the radiological tumor capsule on preoperative CECT is of great value in the prediction of MVI regardless of tumor size.     

术前影像检查在预测肝癌微血管侵犯中的研究进展

微血管侵犯(MVI)是肝癌术后复发及转移独立预测因子之一,目前只能经病理学确诊,但随着影像技术的发展,超声、CT、MRI、PET-CT/MRI等技术逐渐用于肝癌MVI的预测,即通过对一些能够反映肿瘤内部微环境、细胞功能与物质成分以及血流动力学等方面的定量参数的测量得到实现。就术前影像检查预测肝癌MVI的研究进展进行综述。     

The importance of a nonsmooth tumor margin and incomplete tumor capsule in predicting HCC microvascular invasion on preoperative imaging examination: a systematic review and meta-analysis

ObjectivesMicrovascular invasion (MVI) is a key factor affecting the prognosis of hepatocellular carcinoma (HCC). Preoperative imaging plays an important role in the diagnosis of HCC, treatment planning and treatment evaluation, but it is still difficult to detect MVI directly. Whether the appearance of the tumor margin and the capsule on radiological images can predict MVI is still controversial. The aim of this study is to explore the correlation of the presence of MVI with the smoothness of the tumor margin and the integrity of the capsule in HCC.Materials and methodsThe PubMed, Embase, Medline, SCI and Cochrane Library databases up to January 2020. Heterogeneity among studies was assessed by sensitivity analysis, subgroup analysis and meta-regression, and the influence of threshold effects was also analyzed.ResultsEleven studies with 1618 patients were included. The results of the meta-analysis indicated that there was a significant relationship between MVI and nonsmooth tumor margin (DOR = 4.62 [2.73, 7.81]) and between MVI and incomplete tumor capsule (DOR = 2.25 [1.22, 4.15]); the sensitivity and specificity of these two parameters were 0.757 [0.602, 0.865], 0.597 [0.450, 0.728] and 0.646 [0.455, 0.800], 0.552 [0.419, 0.678], respectively. We drew the receiver operating characteristic (ROC) curves, and the area under curve (AUC) of the nonsmooth tumor margin variable for predicting MVI was 0.72 [0.69, 0.77], and the AUC of the incomplete tumor capsule variable for predicting MVI was 0.62 [0.58, 0.66].ConclusionNonsmooth tumor margins and incomplete tumor capsules observed by imaging are important for the preoperative prediction of MVI in HCC.     

Diagnostic test accuracies of F-18 FDG PET/CT for prediction of microvascular invasion of hepatocellular carcinoma: A meta-analysis

PurposeThe aim of the current meta-analysis was to evaluate diagnostic accuracies of preoperative F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) or positron emission tomography/computed tomography (PET/CT) for prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients.MethodsThe scientific database such as PubMed, Cochrane, and Embase database were searched for studies evaluating diagnostic accuracies of preoperative F-18 FDG PET or PET/CT for prediction of MVI in HCC patients up to November 30, 2020.ResultsFourteen eligible studies (1276 patients) were enrolled. The pooled sensitivity for F-18 FDG PET or PET/CT was 0.67 (95% CI; 0.57–0.76) with heterogeneity and a pooled specificity of 0.80 (95% CI; 0.74–0.85) with heterogeneity. Likelihood ratio (LR) syntheses gave an overall positive likelihood ratio (LR+) of 3.3 (95% CI; 2.5–4.5) and negative likelihood ratio (LR−) of 0.41 (95% CI; 0.31–0.55). The pooled diagnostic odds ratio (DOR) was 8 (95% CI; 5–14). Summary receiver operating characteristic (ROC) curve indicates that the area under the curve was 0.81 (95% CI; 0.78–0.84).ConclusionThe current meta-analysis showed a low sensitivity and moderate specificity of F-18 FDG PET or PET/CT for the prediction of MVI in HCC patients. F-18 FDG PET or PET/CT might not be useful for the preoperative prediction of MVI in HCC patients and should not be used to exclude MVI. Therefore, cautious application and interpretation should be paid to the F-18 FDG PET or PET/CT for the prediction of MVI in HCC patients preoperatively.     

Blood oxygen level‐dependent liver MRI: Can It predict microvascular invasion in HCC?

Purpose:

To assess Blood Oxygen Level‐Dependent (BOLD) Magnetic Resonance Imaging (MRI) for noninvasive preoperative prediction of Microvascular Invasion (MVI) in Hepatocellular Carcinoma (HCC).

Materials and Methods:

In this prospective, institutional review board approved study, 26 patients (21 men and 5 women age range, 34–77 years with mean age of 61 years) with HCC were evaluated preoperatively with liver MRI including baseline and post oxygen (O2) breathing BOLD MRI. Post processing of MRI data was performed to obtain R2* values (1/s) and correlated with histopathological assessment of MVI. Statistical analysis was performed to assess correlation of baseline R2*, post O2 R2* and R2* ratios to presence of MVI in HCC by binary logistic regression analysis.

Results:

MVI was present in 15/26 (58%) of HCC on histopathology. The mean R2* values ± SD at baseline and post O2 with and without MVI were 35 ± 12, 36 ± 12, 38 ± 10, 42 ± 17. The R2* values between the groups with and without MVI were not significantly different statistically.

Conclusion:

BOLD MRI is unable to accurately predict MVI in HCC. The noninvasive preoperative MRI detection of MVI in HCC remains elusive. J. Magn. Reson. Imaging 2013;37:692—699. © 2012 Wiley Periodicals, Inc.     

比较ADC平均值与最小值术前定量预测HCC微血管侵犯的诊断价值:Meta分析

目的 探讨磁共振表观扩散系数（ADC）值术前预测肝细胞癌（HCC）微血管侵犯（MVI）的可行性,并比较ADC平均值（ADC_mean）和ADC最小值（ADC_min）术前定量预测HCC MVI的诊断效能。 方法 检索PubMed、Embase、Web of Science、Cochrane Library和中国知网、万方数据库中关于磁共振ADC对HCC MVI诊断的相关研究,检索时间从建库至2020年10月。根据纳入与排除标准筛选文献,提取研究的基本特征和诊断参数,采用诊断试验质量评价工具-2量表对研究质量进行评分。绘制总受试者工作特征（SROC）曲线,计算曲线下面积（AUC）,组间差异的比较采用Mann-Whitney U检验。采用Egger's漏斗图及独立样本t检验比较纳入文献的发表偏倚。 结果 最终纳入13篇文献,共1432例HCC患者,2303个HCC病灶。MVI阳性病灶的ADC_mean和ADC_min明显低于MVI阴性病灶,组间的均数差分别为?0.17×10?3 mm2/s [95%CI:（?0.23~?0.12）×10?3 mm2/s,Z=6.58,P<0.001]和?0.15×10?3 mm2/s [95%CI:（?0.18~?0.12）×10?3 mm2/s,Z=9.91,P<0.001]。以最大Youden指数确定ADC_mean和ADC_min术前诊断HCC MVI阳性的最佳阈值分别为1.11×10?3 mm2/s和0.959×10?3 mm2/s。ADC_mean和ADC_min术前定量预测HCC MVI阳性的合并灵敏度分别为0.74和0.65、特异度分别为0.69和0.68、SROC的AUC分别为0.7722和0.7326,差异均无统计学意义（Z=?0.917、?0.525、?0.131,均P>0.05）。亚组分析结果显示,发表年份、MVI阳性与阴性病灶数的比例及b值数可能为异质性来源。ADC_mean和ADC_min的Egger's漏斗图结果显示,差异均无统计学意义（无发表偏倚,t=?1.58、?0.71,均P>0.05）。 结论 ADC值可作为一种可靠、无创的术前定量预测HCC MVI的检查指标。与ADC_min相比,ADC_mean术前定量预测HCC MVI阳性的诊断效能更优。     

Imaging features of microvascular invasion in hepatocellular carcinoma developed after direct-acting antiviral therapy in HCV-related cirrhosis

Objectives

To evaluate imaging features of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) developed after direct-acting antiviral (DAA) therapy in HCV-related cirrhosis.

Methods

Retrospective cohort study on 344 consecutive patients with HCV-related cirrhosis treated with DAA and followed for 48–74 weeks. Using established imaging criteria for MVI, HCC features were analysed and compared with those in nodules not occurring after DAA.

Results

After DAA, HCC developed in 29 patients (single nodule, 18 and multinodular, 11). Median interval between therapy end and HCC diagnosis was 82 days (0–318). Forty-one HCC nodules were detected (14 de novo, 27 recurrent): maximum diameter was 10–20 mm in 27, 20–50 mm in 13, and > 50 mm in 1. Imaging features of MVI were present in 29/41 nodules (70.7%, CI: 54–84), even in 17/29 nodules with 10–20 mm diameter (58.6%, CI: 39–76). MVI was present in only 17/51 HCC nodules that occurred before DAA treatment (33.3%, CI: 22–47) (p= 0.0007). MVI did not correlate with history of previous HCC.

Conclusions

HCC occurs rapidly after DAA therapy, and aggressive features of MVI characterise most neoplastic nodules. Close imaging evaluations are needed after DAA in cirrhotic patients.

Key Points

? In HCV cirrhosis, hepatocellular carcinoma develops soon after direct-acting antiviral therapy. ? HCC presents imaging features of microvascular invasion, predictive of more aggressive progression. ? Cirrhotic patients need aggressive and close monitoring after direct-acting antiviral therapy.

     

Diagnostic value of magnetic resonance imaging features of microvascular invasion in hepatocellular carcinoma: a meta-analysis

PURPOSEThis systematic review and meta-analysis of conventional enhanced magnetic resonance imaging (MRI) were conducted to evaluate the diagnostic performance of imaging features of microvascular invasion (MVI) prediction in hepatocellular carcinoma (HCC).METHODSRelevant studies on diagnosing MVI in HCC by MRI were searched in the MEDLINE, PUBMED, EMBASE, Cochrane library, and Web of Science databases. The pooled mean sensitivity and specificity were calculated using a random effects model. The corresponding positive likelihood ratio (PLR), negative likelihood ratio (NLR), and pooled diagnostic odds ratio (DOR) were calculated. The summary receiver operating characteristic (SROC) curve was used to summarize the overall diagnostic accuracy. Diagnostic performance was evaluated by determining the area under the curve (AUC). Regression analysis by subgroup and sensitivity analysis were used to explore potential sources of heterogeneity.RESULTSA total of 19 studies comprising 1920 HCC patients with 2033 tumors were ultimately enrolled. For the signs of the presence of peritumoral enhancement in the arterial phase, peritumoral hypointensity in the hepatobiliary phase, irregular non-smooth margin, and rim-like enhancement in the arterial phase, the pooled sensitivity values, the pooled specificity values, the pooled PLR values, the pooled NLR values, the pooled DOR values, and the values of the AUC of SROC curves were determined.CONCLUSIONThe conventional MRI features for predicting MVI showed poor diagnostic performance in HCC. Only signs of the presence of peritumoral enhancement in the arterial phase showed a moderate diagnostic accuracy.

Main points

• We summarized four of the most common magnetic resonance imaging (MRI) signs for microvascular invasion (MVI) in hepatocellular carcinoma (HCC).
• A systematic evaluation of the diagnostic performance was performed to predict MVI in HCC using conventional enhanced MRI (non-functional or radiomics) of each sign.
• The diagnostic performance of conventional enhanced MRI was not good, and all the signs showed low-moderate diagnostic accuracy.

In hepatocellular carcinoma (HCC), microvascular invasion (MVI), which is considered microscopic evidence of cancer embolism in the portal vein or vascular space lined by endothelial cells, is a prognostic factor for poor overall survival and recurrence after hepatectomy or liver transplantation.^1,2 For patients with HCC who underwent curative surgical resection, detection of MVI plays an important role in clinical decision-making. Subsequent treatment approaches, such as postoperative adjuvant transcatheter arterial chemoembolization, are recently recommended for patients with MVI-positive HCC to prevent recurrence and improve the prognosis.^3,4 Unfortunately, with a high positive incidence rate of up to 57%, MVI can only be confirmed by postoperative pathological examination after extensive resection of the tumor,^5,6 which makes it difficult to predict MVI preoperatively.As a non-invasive examination, enhanced magnetic resonance imaging (MRI), especially hepatobiliary-specific contrast-enhanced MRI, is currently used for detecting MVI.⁷ Incomplete tumor capsules, irregular non-smooth margin, rim-like enhancement on the arterial phase, peritumoral enhancement on the arterial phase, and peritumoral hypointensity on the hepatobiliary phase (HBP) are considered as possible radiographic signs for MVI detection.⁸ Rim-like enhancement is defined as the irregular rim-like peripheral hyperintensity area of the tumor with hypointensity area in the center of the tumor on the arterial phase enhancement. Peritumoral enhancement is defined as the variable-shaped hyperintensity area outside the tumor in wide contact with the tumor margin on the arterial phase enhancement and iso-intensity area on the delayed phase. Peritumoral hypointensity is defined as a flame-like or “V-shaped” hypointense area outside the tumor margin on the HBP. Irregular non-smooth margin is defined as an indistinct or irregular tumor margin with a budding portion.⁹ However, the diagnostic performance, with respect to the accuracy, is still controversial. The systematic evaluation of the image prediction of MVI in HCC has been reported in recent studies^10-13 with variable pooled results of diagnostic values. There were obvious methodological differences such as different examination types [computed tomography (CT), ultrasound, MRI, or positron emission tomography/CT (PET/CT)] and confused methodology (conventional MRI or using radiomics) among these studies. In addition, the radiographic signs selection in the MRI subgroup was different, so it is uncertain for comparing the diagnostic performance of the specific image signs on MRI. Therefore, we conducted a systematic review and meta-analysis of conventional enhanced MRI to evaluate the diagnostic performance of imaging features for MVI prediction in HCC.