We report a case of a 61-year-old man who presented with fatigue,abdominal pain and hepatomegaly.Computed tomography (CT) of the abdomen showed hepatomegaly and multiple hepatic lesions highly suggestive of metastatic...We report a case of a 61-year-old man who presented with fatigue,abdominal pain and hepatomegaly.Computed tomography (CT) of the abdomen showed hepatomegaly and multiple hepatic lesions highly suggestive of metastatic diseases.Due to the endoscopic finding of colon ulcer,colon cancer with liver metastases was suspected.Biochemically a slight increase of transaminases,alkaline phosphatase and gammaglutamyl transpeptidase were present;α- fetoprotein,carcinoembryogenic antigen and carbohydrate 19-9 antigen serum levels were normal.Laboratory and instrumental investigations,including colon and liver biopsies revealed no signs of malignancy.In the light of spontaneous improvement of symptoms and CT findings,his personal history was revaluated revealing direct contact with pigs and their tissues.Diagnosis of leptospirosis was considered and confirmed by detection of an elevated titer of antibodies to leptospira.After two mo,biochemical data,CT and colonoscopy were totally normal.展开更多
BACKGROUND Artificial intelligence,such as convolutional neural networks(CNNs),has been used in the interpretation of images and the diagnosis of hepatocellular cancer(HCC)and liver masses.CNN,a machine-learning algor...BACKGROUND Artificial intelligence,such as convolutional neural networks(CNNs),has been used in the interpretation of images and the diagnosis of hepatocellular cancer(HCC)and liver masses.CNN,a machine-learning algorithm similar to deep learning,has demonstrated its capability to recognise specific features that can detect pathological lesions.AIM To assess the use of CNNs in examining HCC and liver masses images in the diagnosis of cancer and evaluating the accuracy level of CNNs and their performance.METHODS The databases PubMed,EMBASE,and the Web of Science and research books were systematically searched using related keywords.Studies analysing pathological anatomy,cellular,and radiological images on HCC or liver masses using CNNs were identified according to the study protocol to detect cancer,differentiating cancer from other lesions,or staging the lesion.The data were extracted as per a predefined extraction.The accuracy level and performance of the CNNs in detecting cancer or early stages of cancer were analysed.The primary outcomes of the study were analysing the type of cancer or liver mass and identifying the type of images that showed optimum accuracy in cancer detection.RESULTS A total of 11 studies that met the selection criteria and were consistent with the aims of the study were identified.The studies demonstrated the ability to differentiate liver masses or differentiate HCC from other lesions(n=6),HCC from cirrhosis or development of new tumours(n=3),and HCC nuclei grading or segmentation(n=2).The CNNs showed satisfactory levels of accuracy.The studies aimed at detecting lesions(n=4),classification(n=5),and segmentation(n=2).Several methods were used to assess the accuracy of CNN models used.CONCLUSION The role of CNNs in analysing images and as tools in early detection of HCC or liver masses has been demonstrated in these studies.While a few limitations have been identified in these studies,overall there was an optimal level of accuracy of the CNNs used in segmentation and classification of liver cancers images.展开更多
目的:探讨增强电子计算机断层扫描(computer tomography,CT)在胆囊癌侵犯肝脏与肝癌累及胆囊病变中的鉴别诊断价值。方法:收集2012年2月到2022年2月重庆医科大学附属第一医院115例患者临床及影像学资料,其中胆囊癌侵犯肝脏病例69例,肝...目的:探讨增强电子计算机断层扫描(computer tomography,CT)在胆囊癌侵犯肝脏与肝癌累及胆囊病变中的鉴别诊断价值。方法:收集2012年2月到2022年2月重庆医科大学附属第一医院115例患者临床及影像学资料,其中胆囊癌侵犯肝脏病例69例,肝癌累及胆囊病例46例,记录性别、年龄、肿瘤大小、肿瘤边界、胆囊形态、肝硬化、胆管扩张、肿瘤内或胆管系统内高密度影、门静脉癌栓、强化方式、强化程度、淋巴结肿大及远处转移共13个观察指标,并进行统计学分析。结果:性别(P=0.007)、年龄(P=0.002)、肿瘤大小(P=0.003)、肝硬化(P<0.001)、肿瘤内或胆管系统内高密度影(P=0.013)、门静脉癌栓(P<0.001)、强化方式(P<0.001)及淋巴结肿大(P=0.034)有统计学差异。通过回归分析筛选出年龄(敏感度为0.812,特异度为0.457)、肿瘤大小(敏感度为0.630,特异度为0.696)、门静脉癌栓(敏感度为0.326,特异度为0.957)、淋巴结肿大(敏感度为0.681,特异度为0.522)为显著分类指标,联合4个观察指标的参数绘制受试者工作特征(receiver operating characteristic,ROC)曲线,曲线下面积(area under the curve,AUC)为0.770,敏感度为0.674,特异度为0.826。结论:增强CT在鉴别胆囊癌侵犯肝脏与肝癌累及胆囊病变时,性别、年龄、肿瘤大小、肝硬化、肿瘤内或胆管系统内高密度影、门静脉癌栓、强化方式及淋巴结肿大有鉴别价值,同时结合年龄、肿瘤大小、门静脉癌栓及淋巴结肿大有助于提高鉴别诊断能力。展开更多
文摘We report a case of a 61-year-old man who presented with fatigue,abdominal pain and hepatomegaly.Computed tomography (CT) of the abdomen showed hepatomegaly and multiple hepatic lesions highly suggestive of metastatic diseases.Due to the endoscopic finding of colon ulcer,colon cancer with liver metastases was suspected.Biochemically a slight increase of transaminases,alkaline phosphatase and gammaglutamyl transpeptidase were present;α- fetoprotein,carcinoembryogenic antigen and carbohydrate 19-9 antigen serum levels were normal.Laboratory and instrumental investigations,including colon and liver biopsies revealed no signs of malignancy.In the light of spontaneous improvement of symptoms and CT findings,his personal history was revaluated revealing direct contact with pigs and their tissues.Diagnosis of leptospirosis was considered and confirmed by detection of an elevated titer of antibodies to leptospira.After two mo,biochemical data,CT and colonoscopy were totally normal.
基金Supported by the College of Medicine Research Centre,Deanship of Scientific Research,King Saud University,Riyadh,Saudi Arabia
文摘BACKGROUND Artificial intelligence,such as convolutional neural networks(CNNs),has been used in the interpretation of images and the diagnosis of hepatocellular cancer(HCC)and liver masses.CNN,a machine-learning algorithm similar to deep learning,has demonstrated its capability to recognise specific features that can detect pathological lesions.AIM To assess the use of CNNs in examining HCC and liver masses images in the diagnosis of cancer and evaluating the accuracy level of CNNs and their performance.METHODS The databases PubMed,EMBASE,and the Web of Science and research books were systematically searched using related keywords.Studies analysing pathological anatomy,cellular,and radiological images on HCC or liver masses using CNNs were identified according to the study protocol to detect cancer,differentiating cancer from other lesions,or staging the lesion.The data were extracted as per a predefined extraction.The accuracy level and performance of the CNNs in detecting cancer or early stages of cancer were analysed.The primary outcomes of the study were analysing the type of cancer or liver mass and identifying the type of images that showed optimum accuracy in cancer detection.RESULTS A total of 11 studies that met the selection criteria and were consistent with the aims of the study were identified.The studies demonstrated the ability to differentiate liver masses or differentiate HCC from other lesions(n=6),HCC from cirrhosis or development of new tumours(n=3),and HCC nuclei grading or segmentation(n=2).The CNNs showed satisfactory levels of accuracy.The studies aimed at detecting lesions(n=4),classification(n=5),and segmentation(n=2).Several methods were used to assess the accuracy of CNN models used.CONCLUSION The role of CNNs in analysing images and as tools in early detection of HCC or liver masses has been demonstrated in these studies.While a few limitations have been identified in these studies,overall there was an optimal level of accuracy of the CNNs used in segmentation and classification of liver cancers images.
文摘目的:探讨增强电子计算机断层扫描(computer tomography,CT)在胆囊癌侵犯肝脏与肝癌累及胆囊病变中的鉴别诊断价值。方法:收集2012年2月到2022年2月重庆医科大学附属第一医院115例患者临床及影像学资料,其中胆囊癌侵犯肝脏病例69例,肝癌累及胆囊病例46例,记录性别、年龄、肿瘤大小、肿瘤边界、胆囊形态、肝硬化、胆管扩张、肿瘤内或胆管系统内高密度影、门静脉癌栓、强化方式、强化程度、淋巴结肿大及远处转移共13个观察指标,并进行统计学分析。结果:性别(P=0.007)、年龄(P=0.002)、肿瘤大小(P=0.003)、肝硬化(P<0.001)、肿瘤内或胆管系统内高密度影(P=0.013)、门静脉癌栓(P<0.001)、强化方式(P<0.001)及淋巴结肿大(P=0.034)有统计学差异。通过回归分析筛选出年龄(敏感度为0.812,特异度为0.457)、肿瘤大小(敏感度为0.630,特异度为0.696)、门静脉癌栓(敏感度为0.326,特异度为0.957)、淋巴结肿大(敏感度为0.681,特异度为0.522)为显著分类指标,联合4个观察指标的参数绘制受试者工作特征(receiver operating characteristic,ROC)曲线,曲线下面积(area under the curve,AUC)为0.770,敏感度为0.674,特异度为0.826。结论:增强CT在鉴别胆囊癌侵犯肝脏与肝癌累及胆囊病变时,性别、年龄、肿瘤大小、肝硬化、肿瘤内或胆管系统内高密度影、门静脉癌栓、强化方式及淋巴结肿大有鉴别价值,同时结合年龄、肿瘤大小、门静脉癌栓及淋巴结肿大有助于提高鉴别诊断能力。
