Artificial intelligence(AI)is making significant strides in revolutionizing the detection of Barrett's esophagus(BE),a precursor to esophageal adenocarcinoma.In the research article by Tsai et al,researchers utili...Artificial intelligence(AI)is making significant strides in revolutionizing the detection of Barrett's esophagus(BE),a precursor to esophageal adenocarcinoma.In the research article by Tsai et al,researchers utilized endoscopic images to train an AI model,challenging the traditional distinction between endoscopic and histological BE.This approach yielded remarkable results,with the AI system achieving an accuracy of 94.37%,sensitivity of 94.29%,and specificity of 94.44%.The study's extensive dataset enhances the AI model's practicality,offering valuable support to endoscopists by minimizing unnecessary biopsies.However,questions about the applicability to different endoscopic systems remain.The study underscores the potential of AI in BE detection while highlighting the need for further research to assess its adaptability to diverse clinical settings.展开更多
AIM:To evaluate the difference in diagnostic performance of hydro-stomach computed tomography(CT) to detect early gastric cancer(EGC) between blinded and unblinded analysis and to assess independent factors affecting ...AIM:To evaluate the difference in diagnostic performance of hydro-stomach computed tomography(CT) to detect early gastric cancer(EGC) between blinded and unblinded analysis and to assess independent factors affecting visibility of cancer foci.METHODS:Two radiologists initially blinded and then unblinded to gastroscopic and surgical-histological findings independently reviewed hydro-stomach CT images of 110 patients with single EGC.They graded the visibility of cancer foci for each of three gastric segments(upper,middle and lower thirds) using a 4-point scale(1:definitely absent,2:probably absent,3:probably present,and 4:definitely present).The sensitivity and specificity for detecting an EGC were calculated.Intraobserver and interobserver agreements were analyzed.The visibility of an EGC was evaluated with regard to tumor size,invasion depth,gastric segments,histological type and gross morphology using univariate and multivariate analysis.RESULTS:The respective sensitivities and specificities [reviewer 1:blinded,20%(22/110) and 98%(215/220);unblinded,27%(30/110) and 100%(219/220)/reviewer 2:blinded,19%(21/110) and 98%(216/220);unblinded,25%(27/110) and 98%(215/220)] were not significantly different.Although intraobserver agreements were good(weighted κ = 0.677 and 0.666),interobserver agreements were fair(blinded,0.371) or moderate(unblinded,0.558).For both univariate and multivariate analyses,the tumor size and invasion depth were statistically significant factors affecting visibility.CONCLUSION:The diagnostic performance of hydrostomach CT to detect an EGC was not significantly different between blinded and unblinded analysis.The tumor size and invasion depth were independent factors for visibility.展开更多
BACKGROUND Cancer detection is a global research focus,and novel,rapid,and label-free techniques are being developed for routine clinical practice.This has led to the development of new tools and techniques from the b...BACKGROUND Cancer detection is a global research focus,and novel,rapid,and label-free techniques are being developed for routine clinical practice.This has led to the development of new tools and techniques from the bench side to routine clinical practice.In this study,we present a method that uses Raman spectroscopy(RS)to detect cancer in unstained formalin-fixed,resected specimens of the esophagus and stomach.Our method can record a clear Raman-scattered light spectrum in these specimens,confirming that the Raman-scattered light spectrum changes because of the histological differences in the mucosal tissue.AIM To evaluate the use of Raman-scattered light spectrum for detecting endoscopically resected specimens of esophageal squamous cell carcinoma(SCC)and gastric adenocarcinoma(AC).METHODS We created a Raman device that is suitable for observing living tissues,and attempted to acquire Raman-scattered light spectra in endoscopically resected specimens of six esophageal tissues and 12 gastric tissues.We evaluated formalin-fixed tissues using this technique and captured shifts at multiple locations based on feasibility,ranging from six to 19 locations 200 microns apart in the vertical and horizontal directions.Furthermore,a correlation between the obtained Raman scattered light spectra and histopathological diagnosis was performed.RESULTS We successfully obtained Raman scattered light spectra from all six esophageal and 12 gastric specimens.After data capture,the tissue specimens were sent for histopathological analysis for further processing because RS is a label-free methodology that does not cause tissue destruction or alterations.Based on data analysis of molecular-level substrates,we established cut-off values for the diagnosis of esophageal SCC and gastric AC.By analyzing specific Raman shifts,we developed an algorithm to identify the range of esophageal SCC and gastric AC with an accuracy close to that of histopathological diagnoses.CONCLUSION Our technique provides qualitative information for real-time morphological diagnosis.However,further in vivo evaluations require an excitation light source with low human toxicity and large amounts of data for validation.展开更多
文摘Artificial intelligence(AI)is making significant strides in revolutionizing the detection of Barrett's esophagus(BE),a precursor to esophageal adenocarcinoma.In the research article by Tsai et al,researchers utilized endoscopic images to train an AI model,challenging the traditional distinction between endoscopic and histological BE.This approach yielded remarkable results,with the AI system achieving an accuracy of 94.37%,sensitivity of 94.29%,and specificity of 94.44%.The study's extensive dataset enhances the AI model's practicality,offering valuable support to endoscopists by minimizing unnecessary biopsies.However,questions about the applicability to different endoscopic systems remain.The study underscores the potential of AI in BE detection while highlighting the need for further research to assess its adaptability to diverse clinical settings.
文摘AIM:To evaluate the difference in diagnostic performance of hydro-stomach computed tomography(CT) to detect early gastric cancer(EGC) between blinded and unblinded analysis and to assess independent factors affecting visibility of cancer foci.METHODS:Two radiologists initially blinded and then unblinded to gastroscopic and surgical-histological findings independently reviewed hydro-stomach CT images of 110 patients with single EGC.They graded the visibility of cancer foci for each of three gastric segments(upper,middle and lower thirds) using a 4-point scale(1:definitely absent,2:probably absent,3:probably present,and 4:definitely present).The sensitivity and specificity for detecting an EGC were calculated.Intraobserver and interobserver agreements were analyzed.The visibility of an EGC was evaluated with regard to tumor size,invasion depth,gastric segments,histological type and gross morphology using univariate and multivariate analysis.RESULTS:The respective sensitivities and specificities [reviewer 1:blinded,20%(22/110) and 98%(215/220);unblinded,27%(30/110) and 100%(219/220)/reviewer 2:blinded,19%(21/110) and 98%(216/220);unblinded,25%(27/110) and 98%(215/220)] were not significantly different.Although intraobserver agreements were good(weighted κ = 0.677 and 0.666),interobserver agreements were fair(blinded,0.371) or moderate(unblinded,0.558).For both univariate and multivariate analyses,the tumor size and invasion depth were statistically significant factors affecting visibility.CONCLUSION:The diagnostic performance of hydrostomach CT to detect an EGC was not significantly different between blinded and unblinded analysis.The tumor size and invasion depth were independent factors for visibility.
基金Supported by Grants from the Conselleria de Sanidade of Xunta de Galicia,No.PS09/74Asociación Espa ola contra el Cáncer(Fundación Científica),Instituto de Salud Carlos III,No.PI08/90717+4 种基金Obra Social de Kutxa,Diputación Foral de Gi-puzkoa,No.DFG 07/5Departamento de Sanidad del Gobierno Vasco,EITB-Maratoia,No.BIO 07/CA/19Acción Transversal contra el Cáncer del CIBERehd(2008)CIBERehd funded by the Instituto de Salud Carlos IIIDirección Xeral de Innovación e Xestión da Saúde Pública,Conselleria de Sanidade,Xunta de Galicia
文摘AIM: To assess the fecal immunochemical test (FIT) accuracy for colorectal cancer (CRC) and advanced neoplasia (AN) detection in CRC screening.
基金Supported by MEXT KAKENHI,JP17K09022 and JP20K07643.
文摘BACKGROUND Cancer detection is a global research focus,and novel,rapid,and label-free techniques are being developed for routine clinical practice.This has led to the development of new tools and techniques from the bench side to routine clinical practice.In this study,we present a method that uses Raman spectroscopy(RS)to detect cancer in unstained formalin-fixed,resected specimens of the esophagus and stomach.Our method can record a clear Raman-scattered light spectrum in these specimens,confirming that the Raman-scattered light spectrum changes because of the histological differences in the mucosal tissue.AIM To evaluate the use of Raman-scattered light spectrum for detecting endoscopically resected specimens of esophageal squamous cell carcinoma(SCC)and gastric adenocarcinoma(AC).METHODS We created a Raman device that is suitable for observing living tissues,and attempted to acquire Raman-scattered light spectra in endoscopically resected specimens of six esophageal tissues and 12 gastric tissues.We evaluated formalin-fixed tissues using this technique and captured shifts at multiple locations based on feasibility,ranging from six to 19 locations 200 microns apart in the vertical and horizontal directions.Furthermore,a correlation between the obtained Raman scattered light spectra and histopathological diagnosis was performed.RESULTS We successfully obtained Raman scattered light spectra from all six esophageal and 12 gastric specimens.After data capture,the tissue specimens were sent for histopathological analysis for further processing because RS is a label-free methodology that does not cause tissue destruction or alterations.Based on data analysis of molecular-level substrates,we established cut-off values for the diagnosis of esophageal SCC and gastric AC.By analyzing specific Raman shifts,we developed an algorithm to identify the range of esophageal SCC and gastric AC with an accuracy close to that of histopathological diagnoses.CONCLUSION Our technique provides qualitative information for real-time morphological diagnosis.However,further in vivo evaluations require an excitation light source with low human toxicity and large amounts of data for validation.
文摘目的系统评价国内外现有胃癌筛查指南的方法学质量,为今后同类指南的制定和更新提供标准和参考依据。方法以“指南”“共识”“规范”“标准”“胃癌”“胃部肿瘤”“筛查”“筛检”“诊断”“Gastric Cancer”“Gastric Tumor”“guideline”“recommendation”“Early Detection of Cancer”“Screening”为检索关键词,系统检索中国知网、万方知识服务平台、中国生物医学文献数据库、中国临床指南文库、PubMed、The Cochrane Library、EMBASE、Web of Knowledge等数据库截止到2018年9月的中、英文文献,并同时检索美国预防服务工作组、美国癌症学会、国际癌症研究机构、澳大利亚癌症委员会、国际指南协作网的机构官网刊登的指南作为补充。纳入标准为胃癌筛查的独立指南文件,且符合美国医学研究所对指南的定义;排除标准包括指南的摘要、解读及评价类文献、重复发表、已更新的原始版指南以及胃癌临床治疗或实践指南。采用欧洲指南研究与评估工具(AGREEⅡ)和实践指南报告标准(RIGHT)对胃癌筛查指南的质量和报告规范程度进行比较和评价。结果共纳入5篇指南。AGREEⅡ质量评价结果显示,5篇指南整体质量参差不齐,其中推荐等级为“A”的有1篇,等级为“B”的有1篇,等级为“C”的有3篇;各指南在范围和目的、清晰性领域得分较高,在严谨性、独立性领域得分差异较大,在参与人员、应用性领域得分普遍较低。RIGHT评价结果显示,5篇指南报告质量有待提高,报告质量较差的6个条目分别为背景、证据、推荐意见、评审和质量保证、资金资助与利益冲突声明和管理以及其他方面。结论纳入的胃癌筛查指南的质量整体一般,规范性有待加强。
