Hepatocellular carcinoma(HCC)is a leading cause of morbidity and mortality worldwide,with rising clinical and economic burden as incidence increases.There are a multitude of evolving treatment options,including locore...Hepatocellular carcinoma(HCC)is a leading cause of morbidity and mortality worldwide,with rising clinical and economic burden as incidence increases.There are a multitude of evolving treatment options,including locoregional therapies which can be used alone,in combination with each other,or in combination with systemic therapy.These treatment options have shown to be effective in achieving remission,controlling tumor progression,improving disease free and overall survival in patients who cannot undergo resection and providing a bridge to transplant by debulking tumor burden to downstage patients.Following locoregional therapy(LRT),it is crucial to provide treatment response assessment to guide management and liver transplant candidacy.Therefore,Liver Imaging Reporting and Data Systems(LI-RADS)Treatment Response Algorithm(TRA)was created to provide a standardized assessment of HCC following LRT.LIRADS TRA provides a step by step approach to evaluate each lesion independently for accurate tumor assessment.In this review,we provide an overview of different locoregional therapies for HCC,describe the expected post treatment imaging appearance following treatment,and review the LI-RADS TRA with guidance for its application in clinical practice.Unique to other publications,we will also review emerging literature supporting the use of LI-RADS for assessment of HCC treatment response after LRT.展开更多
AIM: To determine whether contrast-enhanced ultrasound(CEUS) can improve the precision of breast imaging reporting and data system(BI-RADS) categorization. METHODS: A total of 230 patients with 235 solid breast lesion...AIM: To determine whether contrast-enhanced ultrasound(CEUS) can improve the precision of breast imaging reporting and data system(BI-RADS) categorization. METHODS: A total of 230 patients with 235 solid breast lesions classified as BI-RADS 4 on conventional ultrasound were evaluated. CEUS was performed within one week before core needle biopsy or surgical resection and a revised BI-RADS classification was assigned based on 10 CEUS imaging characteristics. Receiver operating characteristic curve analysis was then conducted to evaluate the diagnostic performance of CEUS-based BI-RADS assignment with pathological examination as reference criteria. RESULTS: The CEUS-based BI-RADS evaluation classified 116/235(49.36%) lesions into category 3, 20(8.51%), 13(5.53%) and 12(5.11%) lesions into categories 4A, 4B and 4C, respectively, and 74(31.49%) into category 5. Selecting CEUS-based BI-RADS category 4A as an appropriate cut-off gave sensitivity and specificity values of 85.4% and 87.8%, respectively, for the diagnosisof malignant disease. The cancer-to-biopsy yield was 73.11% with CEUS-based BI-RADS 4A selected as the biopsy threshold compared with 40.85% otherwise, while the biopsy rate was only 42.13% compared with 100% otherwise. Overall, only 4.68% of invasive cancers were misdiagnosed.CONCLUSION: This pilot study suggests that evaluation of BI-RADS 4 breast lesions with CEUS results in reduced biopsy rates and increased cancer-to-biopsy yields.展开更多
AIM: To build and evaluate predictive models for contrast-enhanced ultrasound(CEUS) of the breast to distinguish between benign and malignant lesions. METHODS: A total of 235 breast imaging reporting and data system(B...AIM: To build and evaluate predictive models for contrast-enhanced ultrasound(CEUS) of the breast to distinguish between benign and malignant lesions. METHODS: A total of 235 breast imaging reporting and data system(BI-RADS) 4 solid breast lesions were imaged via CEUS before core needle biopsy or surgical resection. CEUS results were analyzed on 10 enhancing patterns to evaluate diagnostic performance of three benign and three malignant CEUS models, with pathological results used as the gold standard. A logistic regression model was developed basing on the CEUS results, and then evaluated with receiver operating curve(ROC). RESULTS: Except in cases of enhanced homogeneity, the rest of the 9 enhancement appearances were statistically significant(P < 0.05). These 9 enhancement patterns were selected in the final step of the logistic regression analysis, with diagnostic sensitivity and specificity of 84.4% and 82.7%, respectively, and the area under the ROC curve of 0.911. Diagnostic sensitivity, specificity, and accuracy of the malignant vs benign CEUS models were 84.38%, 87.77%, 86.38% and 86.46%, 81.29% and 83.40%, respectively. CONCLUSION: The breast CEUS models can predict risk of malignant breast lesions more accurately, decrease false-positive biopsy, and provide accurate BIRADS classification.展开更多
Hepatocellular carcinoma (HCC) usually develops in the setting of chronic liver disease. In the adequate clinical context, both multiphasic contrast-enhanced CT and magnetic resonance imaging are non-invasive modaliti...Hepatocellular carcinoma (HCC) usually develops in the setting of chronic liver disease. In the adequate clinical context, both multiphasic contrast-enhanced CT and magnetic resonance imaging are non-invasive modalities that allow accurate diagnosis and staging of HCC, although the latter demonstrates greater sensitivity and specificity. Imaging criteria for HCC diagnosis rely on hemodynamic features such as hyperenhancement in the arterial phase and washout in the portal or equilibrium phase. However, imaging performance drops considerably for small (< 20 mm) nodules because their tendency to exhibit atypical enhancement patterns. In order to improve accuracy in the diagnosis and staging of HCC, particularly in cases of atypical nodules, ancillary features, i.e., imaging characteristics that modify the likelihood of HCC, have been described and incorporated into clinical reports, especially in Liver Imaging Reporting and Data System. In this paper, ancillary imaging features will be reviewed and illustrated.展开更多
BACKGROUND The Liver Imaging Reporting and Data System(LI-RADS), supported by the American College of Radiology(ACR), has been developed for standardizing the acquisition, interpretation, reporting, and data collectio...BACKGROUND The Liver Imaging Reporting and Data System(LI-RADS), supported by the American College of Radiology(ACR), has been developed for standardizing the acquisition, interpretation, reporting, and data collection of liver imaging examinations in patients at risk for hepatocellular carcinoma(HCC). Diffusionweighted imaging(DWI), which is described as an ancillary imaging feature of LI-RADS, can improve the diagnostic efficiency of LI-RADS v2017 with gadoxetic acid-enhanced magnetic resonance imaging(MRI) for HCC.AIM To determine whether the use of DWI can improve the diagnostic efficiency of LIRADS v2017 with gadoxetic acid-enhanced magnetic resonance MRI for HCC.METHODS In this institutional review board-approved study, 245 observations of high risk of HCC were retrospectively acquired from 203 patients who underwent gadoxetic acid-enhanced MRI from October 2013 to April 2018. Two readers independently measured the maximum diameter and recorded the presence of each lesion and assigned scores according to LI-RADS v2017. The test was used to determine the agreement between the two readers with or without DWI. In addition, the sensitivity(SE), specificity(SP), accuracy(AC), positive predictive value(PPV), and negative predictive value(NPV) of LI-RADS were calculated.Youden index values were used to compare the diagnostic performance of LIRADS with or without DWI.RESULTS Almost perfect interobserver agreement was obtained for the categorization of observations with LI-RADS(kappa value: 0.813 without DWI and 0.882 with DWI). For LR-5, the diagnostic SE, SP, and AC values were 61.2%, 92.5%, and71.4%, respectively, with or without DWI; for LR-4/5, they were 73.9%, 80%, and75.9% without DWI and 87.9%, 80%, and 85.3% with DWI; for LR-4/5/M, they were 75.8%, 58.8%, and 70.2% without DWI and 87.9%, 58.8%, and 78.4% with DWI; for LR-4/5/TIV, they were 75.8%, 75%, and 75.5% without DWI and 89.7%,75%, and 84.9% with DWI. The Youden index values of the LI-RADS classification without or with DWI were as follows: LR-4/5: 0.539 vs 0.679; LR-4/5/M: 0.346 vs 0.467; and LR-4/5/TIV: 0.508 vs 0.647.CONCLUSION LI-RADS v2017 has been successfully applied with gadoxetate-enhanced MRI for patients at high risk for HCC. The addition of DWI significantly increases the diagnostic efficiency for HCC.展开更多
目的 评估甲状腺结节超声恶性危险分层中国指南(Chinese-thyroid imaging reporting and data system,C-TIRADS)联合超声造影(contrast-enhancedultrasound,CEUS)评估桥本甲状腺炎4类结节。方法 回顾性分析2022年6月至12月于益阳市中心...目的 评估甲状腺结节超声恶性危险分层中国指南(Chinese-thyroid imaging reporting and data system,C-TIRADS)联合超声造影(contrast-enhancedultrasound,CEUS)评估桥本甲状腺炎4类结节。方法 回顾性分析2022年6月至12月于益阳市中心医院就诊的79例桥本甲状腺炎患者的120个C-TIRADS4类甲状腺结节资料。CEUS检查时如结节表现可疑的1种或多种良/恶性特征,均采取降/升一级的处理,以最终手术病理结果为金标准。绘制受试者操作特征曲线(receiver operating characteristic curve,ROC曲线),比较诊断效能。结果 CEUS后再次分级的C-TIRADS诊断甲状腺结节良恶性的敏感度、特异性和准确性分别为93.0%、87.8%和90.8%(P<0.05)。ROC曲线下面积分别为0.811和0.904(P<0.05)。结论 C-TIRADS联合CEUS评估桥本甲状腺炎4类结节具有更好的诊断效能。展开更多
目的探讨多参数MRI联合影像组学在区分前列腺影像报告数据系统(PI-RADS)4~5分病灶良恶性中的应用价值,旨在构建能够有效区分两者的模型,提高诊断精确度。材料与方法回顾性分析2018年1月至2021年6月在我院行前列腺多参数MRI(multiparamet...目的探讨多参数MRI联合影像组学在区分前列腺影像报告数据系统(PI-RADS)4~5分病灶良恶性中的应用价值,旨在构建能够有效区分两者的模型,提高诊断精确度。材料与方法回顾性分析2018年1月至2021年6月在我院行前列腺多参数MRI(multiparametric MRI,mpMRI)检查后PI-RADS评分为4~5分的患者病例共135例,其中病理诊断良性64例,恶性71例。将入组病例随机分层采样按照7∶3的比例划分为训练集(95例,良性45例,恶性50例)和测试集(40例,良性19例,恶性21例),分析前列腺特异性抗原(prostate specific antigen,PSA)、MRI传统参数表观弥散系数(apparent diffusion coefficient,ADC)、多模态影像组学模型[T2WI、弥散加权成像(diffusion weighted imaging,DWI)、ADC三种模态]及联合模型(多模态影像组学联合传统参数ADC值)对PI-RADS 4~5分病灶良恶性的鉴别效力,构建诊断模型。结果良性病变组ADC值[(0.791±0.149)×10^(-3)mm^(2)/s]显著高于恶性组[(0.612±0.110)×10^(-3)mm^(2)/s],其在训练集、测试集中的曲线下面积(area under the curve,AUC)分别为0.870、0.772。而良性病变组总PSA(total PSA,tPSA)略低于恶性组,两组之间差异无统计学意义。ADC、DWI和T2WI多模态组合影像组学在训练集、测试集中的AUC分别为0.942、0.850。联合模型在训练集、测试集中的AUC分别为0.952、0.842。结论综合多模态MRI(T2WI、DWI、ADC)影像组学联合传统参数的模型能有效帮助鉴别PI-RADS 4~5分病灶的良恶性,帮助提高诊断准确度,进一步辅助个体化治疗方案的制订。展开更多
目的 探讨2018版肝脏影像报告和数据系统(Liver Imaging Reporting and Data System version 2018,LI-RADS v2018)对肝细胞癌(hepatocellular carcinoma,HCC)细胞角蛋白19(cytokeratin 19,CK19)表达的术前预测及预后评估的价值。材料与...目的 探讨2018版肝脏影像报告和数据系统(Liver Imaging Reporting and Data System version 2018,LI-RADS v2018)对肝细胞癌(hepatocellular carcinoma,HCC)细胞角蛋白19(cytokeratin 19,CK19)表达的术前预测及预后评估的价值。材料与方法 回顾性分析220例术前接受MRI检查并经病理证实为HCC患者的临床、病理及影像资料,包括CK19阳性组59例,CK19阴性组161例。将患者按7∶3比例分为训练集和验证集。通过单因素与多因素logistic回归分析确定CK19阳性表达HCC的独立预测因素并构建列线图评分模型。采用受试者工作特征(receiver operating characteristic,ROC)曲线分析模型诊断效能,绘制校准曲线、决策曲线评价模型的校准性能和临床适用性。计算患者的列线图得分并进行高低风险分组,采用Kaplan-Meier生存曲线分析比较不同亚组患者的总体、早期及晚期无复发生存率。结果 晕状强化(OR=3.432,P=0.045)、环形动脉期高强化(OR=32.073,P=0.017)、靶样扩散受限(OR=12.941,P=0.006)、不光滑肿瘤边缘(OR=4.590,P=0.014)及肝胆期肿瘤-肝实质相对增强比(the relative enhancement ratio,RER)(OR=0.014,P=0.023)是CK19阳性表达HCC的独立预测因素。预测模型在训练集和验证集的曲线下面积(area under the curve,AUC)分别为0.884(95%CI:0.823~0.930)、0.748(95%CI:0.625~0.846),校准曲线、决策曲线显示模型的校准性能和临床适用性较好。CK19阳性与阴性组的总体无复发生存率、高与低风险组的总体、早期及晚期无复发生存率之间均存在显著差异(P<0.05)。结论 晕状强化、环形动脉期高强化、靶样扩散受限结合不光滑肿瘤边缘、肝胆期增强定量参数可对HCC的CK19表达进行术前风险预测,并有助于评估HCC术后复发。展开更多
文摘Hepatocellular carcinoma(HCC)is a leading cause of morbidity and mortality worldwide,with rising clinical and economic burden as incidence increases.There are a multitude of evolving treatment options,including locoregional therapies which can be used alone,in combination with each other,or in combination with systemic therapy.These treatment options have shown to be effective in achieving remission,controlling tumor progression,improving disease free and overall survival in patients who cannot undergo resection and providing a bridge to transplant by debulking tumor burden to downstage patients.Following locoregional therapy(LRT),it is crucial to provide treatment response assessment to guide management and liver transplant candidacy.Therefore,Liver Imaging Reporting and Data Systems(LI-RADS)Treatment Response Algorithm(TRA)was created to provide a standardized assessment of HCC following LRT.LIRADS TRA provides a step by step approach to evaluate each lesion independently for accurate tumor assessment.In this review,we provide an overview of different locoregional therapies for HCC,describe the expected post treatment imaging appearance following treatment,and review the LI-RADS TRA with guidance for its application in clinical practice.Unique to other publications,we will also review emerging literature supporting the use of LI-RADS for assessment of HCC treatment response after LRT.
文摘AIM: To determine whether contrast-enhanced ultrasound(CEUS) can improve the precision of breast imaging reporting and data system(BI-RADS) categorization. METHODS: A total of 230 patients with 235 solid breast lesions classified as BI-RADS 4 on conventional ultrasound were evaluated. CEUS was performed within one week before core needle biopsy or surgical resection and a revised BI-RADS classification was assigned based on 10 CEUS imaging characteristics. Receiver operating characteristic curve analysis was then conducted to evaluate the diagnostic performance of CEUS-based BI-RADS assignment with pathological examination as reference criteria. RESULTS: The CEUS-based BI-RADS evaluation classified 116/235(49.36%) lesions into category 3, 20(8.51%), 13(5.53%) and 12(5.11%) lesions into categories 4A, 4B and 4C, respectively, and 74(31.49%) into category 5. Selecting CEUS-based BI-RADS category 4A as an appropriate cut-off gave sensitivity and specificity values of 85.4% and 87.8%, respectively, for the diagnosisof malignant disease. The cancer-to-biopsy yield was 73.11% with CEUS-based BI-RADS 4A selected as the biopsy threshold compared with 40.85% otherwise, while the biopsy rate was only 42.13% compared with 100% otherwise. Overall, only 4.68% of invasive cancers were misdiagnosed.CONCLUSION: This pilot study suggests that evaluation of BI-RADS 4 breast lesions with CEUS results in reduced biopsy rates and increased cancer-to-biopsy yields.
文摘AIM: To build and evaluate predictive models for contrast-enhanced ultrasound(CEUS) of the breast to distinguish between benign and malignant lesions. METHODS: A total of 235 breast imaging reporting and data system(BI-RADS) 4 solid breast lesions were imaged via CEUS before core needle biopsy or surgical resection. CEUS results were analyzed on 10 enhancing patterns to evaluate diagnostic performance of three benign and three malignant CEUS models, with pathological results used as the gold standard. A logistic regression model was developed basing on the CEUS results, and then evaluated with receiver operating curve(ROC). RESULTS: Except in cases of enhanced homogeneity, the rest of the 9 enhancement appearances were statistically significant(P < 0.05). These 9 enhancement patterns were selected in the final step of the logistic regression analysis, with diagnostic sensitivity and specificity of 84.4% and 82.7%, respectively, and the area under the ROC curve of 0.911. Diagnostic sensitivity, specificity, and accuracy of the malignant vs benign CEUS models were 84.38%, 87.77%, 86.38% and 86.46%, 81.29% and 83.40%, respectively. CONCLUSION: The breast CEUS models can predict risk of malignant breast lesions more accurately, decrease false-positive biopsy, and provide accurate BIRADS classification.
文摘Hepatocellular carcinoma (HCC) usually develops in the setting of chronic liver disease. In the adequate clinical context, both multiphasic contrast-enhanced CT and magnetic resonance imaging are non-invasive modalities that allow accurate diagnosis and staging of HCC, although the latter demonstrates greater sensitivity and specificity. Imaging criteria for HCC diagnosis rely on hemodynamic features such as hyperenhancement in the arterial phase and washout in the portal or equilibrium phase. However, imaging performance drops considerably for small (< 20 mm) nodules because their tendency to exhibit atypical enhancement patterns. In order to improve accuracy in the diagnosis and staging of HCC, particularly in cases of atypical nodules, ancillary features, i.e., imaging characteristics that modify the likelihood of HCC, have been described and incorporated into clinical reports, especially in Liver Imaging Reporting and Data System. In this paper, ancillary imaging features will be reviewed and illustrated.
基金National Natural Science Foundation of China,No.81471658Science and Technology Support Program of Sichuan Province,No.2017SZ0003
文摘BACKGROUND The Liver Imaging Reporting and Data System(LI-RADS), supported by the American College of Radiology(ACR), has been developed for standardizing the acquisition, interpretation, reporting, and data collection of liver imaging examinations in patients at risk for hepatocellular carcinoma(HCC). Diffusionweighted imaging(DWI), which is described as an ancillary imaging feature of LI-RADS, can improve the diagnostic efficiency of LI-RADS v2017 with gadoxetic acid-enhanced magnetic resonance imaging(MRI) for HCC.AIM To determine whether the use of DWI can improve the diagnostic efficiency of LIRADS v2017 with gadoxetic acid-enhanced magnetic resonance MRI for HCC.METHODS In this institutional review board-approved study, 245 observations of high risk of HCC were retrospectively acquired from 203 patients who underwent gadoxetic acid-enhanced MRI from October 2013 to April 2018. Two readers independently measured the maximum diameter and recorded the presence of each lesion and assigned scores according to LI-RADS v2017. The test was used to determine the agreement between the two readers with or without DWI. In addition, the sensitivity(SE), specificity(SP), accuracy(AC), positive predictive value(PPV), and negative predictive value(NPV) of LI-RADS were calculated.Youden index values were used to compare the diagnostic performance of LIRADS with or without DWI.RESULTS Almost perfect interobserver agreement was obtained for the categorization of observations with LI-RADS(kappa value: 0.813 without DWI and 0.882 with DWI). For LR-5, the diagnostic SE, SP, and AC values were 61.2%, 92.5%, and71.4%, respectively, with or without DWI; for LR-4/5, they were 73.9%, 80%, and75.9% without DWI and 87.9%, 80%, and 85.3% with DWI; for LR-4/5/M, they were 75.8%, 58.8%, and 70.2% without DWI and 87.9%, 58.8%, and 78.4% with DWI; for LR-4/5/TIV, they were 75.8%, 75%, and 75.5% without DWI and 89.7%,75%, and 84.9% with DWI. The Youden index values of the LI-RADS classification without or with DWI were as follows: LR-4/5: 0.539 vs 0.679; LR-4/5/M: 0.346 vs 0.467; and LR-4/5/TIV: 0.508 vs 0.647.CONCLUSION LI-RADS v2017 has been successfully applied with gadoxetate-enhanced MRI for patients at high risk for HCC. The addition of DWI significantly increases the diagnostic efficiency for HCC.
文摘目的探讨多参数MRI联合影像组学在区分前列腺影像报告数据系统(PI-RADS)4~5分病灶良恶性中的应用价值,旨在构建能够有效区分两者的模型,提高诊断精确度。材料与方法回顾性分析2018年1月至2021年6月在我院行前列腺多参数MRI(multiparametric MRI,mpMRI)检查后PI-RADS评分为4~5分的患者病例共135例,其中病理诊断良性64例,恶性71例。将入组病例随机分层采样按照7∶3的比例划分为训练集(95例,良性45例,恶性50例)和测试集(40例,良性19例,恶性21例),分析前列腺特异性抗原(prostate specific antigen,PSA)、MRI传统参数表观弥散系数(apparent diffusion coefficient,ADC)、多模态影像组学模型[T2WI、弥散加权成像(diffusion weighted imaging,DWI)、ADC三种模态]及联合模型(多模态影像组学联合传统参数ADC值)对PI-RADS 4~5分病灶良恶性的鉴别效力,构建诊断模型。结果良性病变组ADC值[(0.791±0.149)×10^(-3)mm^(2)/s]显著高于恶性组[(0.612±0.110)×10^(-3)mm^(2)/s],其在训练集、测试集中的曲线下面积(area under the curve,AUC)分别为0.870、0.772。而良性病变组总PSA(total PSA,tPSA)略低于恶性组,两组之间差异无统计学意义。ADC、DWI和T2WI多模态组合影像组学在训练集、测试集中的AUC分别为0.942、0.850。联合模型在训练集、测试集中的AUC分别为0.952、0.842。结论综合多模态MRI(T2WI、DWI、ADC)影像组学联合传统参数的模型能有效帮助鉴别PI-RADS 4~5分病灶的良恶性,帮助提高诊断准确度,进一步辅助个体化治疗方案的制订。
文摘目的 探讨2018版肝脏影像报告和数据系统(Liver Imaging Reporting and Data System version 2018,LI-RADS v2018)对肝细胞癌(hepatocellular carcinoma,HCC)细胞角蛋白19(cytokeratin 19,CK19)表达的术前预测及预后评估的价值。材料与方法 回顾性分析220例术前接受MRI检查并经病理证实为HCC患者的临床、病理及影像资料,包括CK19阳性组59例,CK19阴性组161例。将患者按7∶3比例分为训练集和验证集。通过单因素与多因素logistic回归分析确定CK19阳性表达HCC的独立预测因素并构建列线图评分模型。采用受试者工作特征(receiver operating characteristic,ROC)曲线分析模型诊断效能,绘制校准曲线、决策曲线评价模型的校准性能和临床适用性。计算患者的列线图得分并进行高低风险分组,采用Kaplan-Meier生存曲线分析比较不同亚组患者的总体、早期及晚期无复发生存率。结果 晕状强化(OR=3.432,P=0.045)、环形动脉期高强化(OR=32.073,P=0.017)、靶样扩散受限(OR=12.941,P=0.006)、不光滑肿瘤边缘(OR=4.590,P=0.014)及肝胆期肿瘤-肝实质相对增强比(the relative enhancement ratio,RER)(OR=0.014,P=0.023)是CK19阳性表达HCC的独立预测因素。预测模型在训练集和验证集的曲线下面积(area under the curve,AUC)分别为0.884(95%CI:0.823~0.930)、0.748(95%CI:0.625~0.846),校准曲线、决策曲线显示模型的校准性能和临床适用性较好。CK19阳性与阴性组的总体无复发生存率、高与低风险组的总体、早期及晚期无复发生存率之间均存在显著差异(P<0.05)。结论 晕状强化、环形动脉期高强化、靶样扩散受限结合不光滑肿瘤边缘、肝胆期增强定量参数可对HCC的CK19表达进行术前风险预测,并有助于评估HCC术后复发。
