肺癌早期检测必备工具
肺癌体检普查专用系统
肺癌已成为我国头号癌症杀手,其发病率和死亡率均呈不断上升趋势。肺癌早期症状并不明显,约80%以上的病人第一次确诊时已是中晚期,错失了最佳治疗时机。而晚期肺癌往往意味着更昂贵的治疗费用、更痛苦的治疗过程,以及难以令人满意的治疗效果。目前,我国肺癌患者五年生存率不到10%,这意味着90%以上的肺癌患者确诊之后活不过五年。因此,早预防、早发现、早诊治是提高肺癌治愈率、降低死亡率的唯一手段!
常规健康体检及普查是肺癌早期发现的有效手段,但由于种种原因,往往有漏诊、误诊的情况发生。如结节隐藏于心脏后、肺尖区、肺门旁、肋骨及膈肌附近等隐蔽区,读片不慎或因已有明确病变存在而遗漏其它病变。
IQQA®-Chest系统是应用获国际专利的独创技术,并结合世界著名医学影像专家及临床医生的知识和经验设计而成,是辅助医生进行肺癌早期发现、早期检测及减少漏诊、误诊的有效工具。本系统已成功通过中国SFDA、美国FDA、欧盟CE及台湾卫生署DOH等多方国际认证并成功上市。
经中国、美国、欧洲等国内外多家知名医院进行的独立临床实验表明(经由40多篇国际论文发表证实):
IQQA®-Chest系统
作为计算机电眼,显著提高人眼分辨率,是医生的“第二双眼睛”
辅助医生提高对5-15mm肺小结节的早期检出率
对肺小结节的敏感度明显与医生互补,降低漏诊率
有效减少不同医生及同一医生在不同时间的观测差异
同类产品中,平均假阳性最低,且易被排除(国际权威文献评估)
与医生现有工作流程无缝连接,不增加医生工作负担
肺癌早期检测必备,肺癌体检普查专用
本产品也是国际上唯一经过前瞻性临床实验证实的数字胸片CAD系统 (Journal of Academic Radiology 2008; 15:571-575) -- 美国爱荷华大学医院发表的该前瞻性实验结果表明 IQQA®-Chest 系统可辅助医生对肺小结节的检出率从63.8% 提高到92.7% ,而该检出率的显著提升只引起了很小数量的假阳性增加。
IQQA®胸片解读分析系统
K. H.Lee, J. M. Goo, C. M. Park, H. J. Lee, K. J. Jin, "Computer-Aided Detection of Malignant Lung Nodules on Chest Radiographs: Effect on Observers' Performance." Korean Journal of Radiology Sep/Oct 2012.
Yan Xu PhD, Daqing Ma MD and Wen He, "Assessing the Use of Digital Radiography and a Real-time Interactive Pulmonary Nodule Analysis System for Large Population Lung Cancer Screening." European Journal of Radiology, May 2011.
Yan Xu PhD, Daqing Ma MD and Wen He, "Assessing the Use of Digital Radiography and a Real-time Interactive Pulmonary Nodule Analysis System for Large Population Lung Cancer Screening." 96th Scientific Assembly and Annual Meeting, Radiological Society of North America. Chicago, Illinois, November 2010.
D.W. De Boo, M. Uffmann, S. Bipat, M.J. Schhrder, N.J.M. Freling and C.M. Schaefer-Prokop. "Impact of computer-aided detection on observer detection of solid pulmonary lesion in chest radiography." European Congress of Radiology. Vienna, Austria, March 2010.
W. Moore, J. Ripton-Snyder, G. Wu and C. Hendler. "Sensitivity and Specificity of a CAD Solution for Lung Nodule Detection on Chest Radiograph with CTA Correlation." Journal of Digital Imaging. March 2010.
Goo, JM; Park, CM; Lee, HJ; Lee, IS; Kang, MJ; Jin, KN, "Computer-Aided Diagnosis System in the Detection of Malignant Lung Nodules on Chest Radiograph: Effect on Observers’ Performance", 2nd World Congress of Thoracic Imaging and Diagnosis in Chest Disease, Valencia, Spain, June 2009.
De Boo, D.W.; Uffmann, M.; Bipat, S.; Scheerder, M.J.; Freling, N.J.M.; Schaefer-Prokop, C.M. "Detection of Small Solid Pulmonary Lesions on Digital Chest Radiographs: Could we Profit from Computer-Aided Detection?", 2nd World Congress of Thoracic Imaging and Diagnosis in Chest Disease, Valencia, Spain, June 2009.
Cakirdas, M; Lhoste Agnes; Daffaud Pierre; Roche Antoine; Brehant Julien; Michel Magalie; Camara Pierre Yves; Michel Jean Luc " Evaluation of a Computer Aided Detection Software for Pulmonary Nodules on Chest Radiograph", 2nd World Congress of Thoracic Imaging and Diagnosis in Chest Disease, Valencia, Spain, June 2009.
Diederick W. De Boo, M. Prokop, M.Uffmann, B. van Ginneken, C.M. Schaefer-Prokop, "Computed-aided detection (CAD) of lung nodules and small tumours on chest radiographs", European Journal of Radiology, May 2009.
T. Achenbach and C. Dueber. "Evaluating the Properties of Pulmonary Nodules Missed by Computer-Aided Detection (CAD) in Chest X-ray Imaging."European Congress of Radiology. Vienna, Austria. March 2009.
E. Kotter, MD, T. A. Bley, MD, "Comparison of Radiologist and CAD Performance in the Detection of CT-confirmed Subtle Pulmonary Nodules on Digital Chest Radiographs", Journal of Investigative Radiology, Vol.43, No.6, June, 2008.
Edwin J.R. van Beek MD, Brian Mullan MD, Brad Thompson MD, "Evaluation of a Real-time Interactive Pulmonary Nodule Analysis System on Chest Digital Radiographic Images: A Prospective Study", Journal of Academic Radiology, Vol.15, No.5, May, 2008.
Qian He, MD, Wen He, MD, PhD, KeYang Wang, MD, Da Qing Ma, MD, "Effect of Multiscale Processing in Digital Chest Radiography on Automated Detection of Lung Nodule with a Computer Assistance System", Journal of Medical Imaging 2008.
E. Kotter, T.A. Bley, T. Baumann, U. Saueressig, G. Pache, M. Treier, O. Schäfer, U. Neitzel and M. Langer. "Comparison of Performance of Radiologists and a Novel CAD System in the Detection of Pulmonary Nodules on Digital Chest Radiographs." European Congress of Radiology. Vienna, Austria. March 2008.
A.T. LARQIA, B. Thompson, B. Mullan, W. Stanford, E.J.R. van Beek. "Chest X-ray CAD System: Clinical Experience in Cancer Follow-up Patients." Society of Thoracic Radiology Thoracic Imaging Annual Meeting. Fort Myers, FL. March 2008.
M. Uffmann, M. Weber, M. Scheerder, E. Boorsma and C.M. Schaefer-Prokop. "Is the Computer-aided Detection of Lung Lesions also Effective in Chest Radiography?" European Congress of Radiology. Vienna, Austria. March 2008.
Guozhen Zhang, MD, PhD, "Advances of Imaging Diagnostics for Lung Cancer", Chinese Journal of Lung Cancer, Vol.11, No.1, February 2008.
Wei Guan, MD, Weimin Mao, MD, PhD, "Application of Computer Aided Diagnosis (CAD) with Digital Chest Radiograph to the Early Detection for Pulmonary Nodules", China Cancer, Vol.16, No.10, 2007.
W. Song, MD, PhD, Y. Xu, Y. Xie, L. Fan, PhD, J. Qian, PhD, Z. Jin, MD, "Inter-observer Variations of Digital Radiograph Pulmonary Nodule Marking by Using Computer Toolkit",Chinese Medical Sciences Journal, Vol.22, No.1, March, 2007.
Y. Xu, MD, D. Ma, MD, W. He, MD, Peking Friendship Hospital, "Assessing the Use of Digital Radiography and a Real-time Interactive Pulmonary Nodule Analysis System for Large Population Lung Cancer Screening", European Congress of Radiology, Vienna, Austria, March, 2007.
Edwin van Beek, MD, PhD, Brian Mullan, Brad Thompson, "Evaluation of a Real-time Interactive Pulmonary Nodule Analysis System on Chest Digital Radiographic Images: A Prospective Study", RSNA, Chicago, November, 2006.
W. Chai, MD, K. Chen, MD, X. Lin, MD, L. Tan, MD, Ruijin Hospital, Shanghai, P.R. China, L. Fan, PhD, G. Wei, PhD, X. Zeng, PhD, J. Qian, PhD, EDDA Technology, Inc., U.S.A. "Performance Analysis of Computer Aided Identification of Small Pulmonary Nodules from DR", the 15th International Conference on Screening for Lung Cancer, New York, October, 2006.
韩国首尔大学医院 Kyung Hee Lee, Jin Mo Goo, Chang Min Park, Hyun Ju Lee, Kwang Nam Jin – Korean Journal of Radiology杂志 2012年9月13卷 第5号
发表临床总结:
“The CAD system may help improve observer performance in detecting malignant lung nodules on chest radiographs and contribute to a decrease in missed lung cancer.”
“IQQA-Chest CAD系统不仅能够有效辅助临床医生提高对肺部恶性肿瘤的检出,还有助于降低漏诊率及误诊率的发生。”
北京友谊医院 马大庆教授、贺文教授等 -- European Journal of Radiology杂志 2011年5月
发表临床总结:
“The computer system could help radiologists identify more lesions, especially small ones that are more likely to be overlooked on chest DR/CR images, and could help reduce inter-observer diagnostic variations, while its FPs were easy to recognize and dismiss. It is suggested that DR/CR assisted by the real- time interactive pulmonary nodule analysis system maybe an effective means to screen large populations for lung cancer.”
“IQQA-Chest CAD可帮助医生在DR/CR胸片上识别更多的病灶,特别是一些很容易被忽略的小病灶,同时假阳性易判断并排除。建议采用DR/CR辅以该CAD可成为大规模肺癌筛查的有效手段。”
北京友谊医院 马大庆教授、贺文教授等 -- 2010年11月北美放射学会年会 (RSNA) 美国 芝加哥
发表临床总结:
“The combined sensitivity of four radiologists for detecting small(5-15mm diameter) pulmonary nodules rose from 65.6% when the digital images were read without CAD(IQQA-Chest) to 80.6% when they were re-read with CAD aiding the interpretation.”
“临床研究表明,使用IQQA-Chest CAD 可显著辅助临床医生提高肺小结节(尤其是5-15mm肺小结节)的检出率(注:敏感性从65.6%提高至80.6%)。
纽约州立大学石溪分校医院 William Moore MD -- Journal of Digital Imaging杂志 2010年3月
发表临床总结:
“When this chest radiograph CAD(IQQA-Chest) system is used as an interactive tool, a reasonably good specificity and accuracy can be obtained. The performance of this system is very good in this patient population, with a low number of false positives per case at 0.48. When used appropriately it also has a very good specificity (78.1%) for detecting nodules measuring between 5 and 15 mm.”
“IQQA-Chest CAD 作为交互式辅助阅片工具,可以大幅提高不同医生之间读片的一致性和诊断精度,尤其对于5-15mm肺小结节的检出率高达78.1%,而假阳性仅为平均每副0.48个。
荷兰阿姆斯特丹大学医院和奥地利维也纳大学医院 De Boo, D.W.; Uffmann, M.; Bipat, S.; Scheerder, M.J.; Freling, N.J.M.; Schaefer-Prokop, C.M. -- 2009年6月第二届国际胸部疾病影像学诊疗会议(WCTI) 西班牙
发表临床总结:
“CAD (IQQA-Chest) improves the sensitivity of inexperienced readers for the detection of small lung lesions without detrimental effect on false positive rate. CAD detects different lesions than radiologists. Reader performance with CAD may be further improved if the high rate of rejected true positive CAD marks can be reduced.”
“IQQA-Chest CAD系统能够在非影响假阳性的情况下有效提高年轻医生对于肺小结节的检出率。通常情况下,CAD更能够检测出医生往往忽略的病灶,为医生提供互补支持。”
法国克莱蒙-费朗大学医院 Cakirdas, M; Lhoste Agnes; Daffaud Pierre; Roche Antoine; Brehant Julien; Michel Magalie; Camara Pierre Yves; Michel Jean Luc -- 2009年6月第二届国际胸部疾病影像学诊疗会议(WCTI) 西班牙
发表临床总结:
“Radiologists can take advantage of the CAD (IQQA-Chest) software to improve the detection of lung nodules especially for small and subtlety nodules, without increasing the rate of false positives.”
“放射科医生可以使用IQQA-Chest CAD系统以提高肺小结节的检出率同时不增加假阳性,尤其是针对小结节和不明显结节”
韩国首尔大学医院Goo, JM; Park, CM; Lee, HJ; Lee, IS; Kang, MJ; Jin, KN – 2009年6月第二届国际胸部疾病影像学诊疗会议(WCTI) 西班牙
发表临床总结:
“The CAD (IQQA-Chest) system can improve the observers’ performance in detecting malignant lung nodules on chest radiograph.”
“IQQA-Chest CAD系统能够有效辅助临床医生提高对肺部恶性肿瘤的检出率。”
日本公立大学法人岩手县立大学医院 Yasuo Sasaki MD, PhD -- 2009年2月Health Imaging & IT.
发表临床总结:
“CAD(IQQA-Chest), which is integrated into the hospital’s Kodak Carestream PACS Client Suite has helped to streamline workflow.…As a doctor, it is always good to ask a second opinion, and we are able to get that with CAD.”
“IQQA-Chest CAD可与医院Carestream PACS系统无缝连接且工作流程极其方便,可有效辅助临床医生对肺小结节的检测。”
德国弗莱堡大学医院 Kotter MD, Bley MD等 -- Investigative Radiology杂志 2008年6月43卷 第6号
发表临床总结:
“The CAD (IQQA-Chest) system’s diagnostic sensitivity in detecting pulmonary nodules of 5 to 15mm of size was superior to the 1 of radiologists. The CAD system may be used for assisting the radiologist in the detection of lung nodules on digital chest radiographs.”
“IQQA-Chest CAD系统对于检测5-15mm肺小结节的敏感度明显与单个医生互补,此系统可很好地用来辅助医生对数字胸片上肺小结节的检测。”
美国爱荷华大学医学院 Edwin J.R. van Beek MD等 -- Academic Radiology杂志 2008 年5月15卷 第5号
发表临床总结:
“This study suggests that the interpretation of chest radiographs for lung nodules can be improved using an automated CAD nodule detection system. This improvement in reader performance comes with a minimal number of false positive interpretations.”
“该前瞻性实验研究表明,使用IQQA-Chest CAD 可提高胸片上的肺部结节检出(注:敏感性从63.8%提高至92.7%)。该检测率的显著提升只引起了很小数量的假阳性增加(注:假阳性在所有324病例中只是从3个病例增加到6个病例)”。 [注:美国爱荷华大学医学院是美国国家癌症研究中心指定的癌症研究教学医院,医院在日常诊断中全面使用IQQA-Chest企业版作为癌症病人的随访的一部分。]
上海华东医院 张国桢教授 -- 中国肺癌杂志 2008年2月第11卷第1期
发表临床总结:
“计算机辅助检测系统(Computer-aided Detection, CAD)可帮助放射科医生提高早期肺癌的检出率,减少漏诊率,被称为放射科医生的‘第二双眼睛’,现已成为系列随访的必备工具。新一代实时交互式计算机系统,如IQQA-Chest V1.0胸片解读分析系统(智能/交互式定性定量分析),可通过对比增强观察模式、结节增强观察模式及自动或手动的分割模式对数字化胸片影像中的肺部结节进行显示、辨认、标记、定量分析,自动汇总后再作出图文并茂的临床报告。”
北京友谊医院 马大庆教授、贺文教授等 -- 2008年1月Health Imaging & IT.
发表临床总结:
“Our results showed that both experienced and less experienced radiologists could benefit from lung CAD, although the less experienced had a greater benefit. For small nodules picked up at an early stage because of the use of IQQA-Chest, and later confirmed on CT and followed through to have a positive pathology report, patient prognosis changes.”
“临床结果表明,不同资质水平的医生都可从IQQA-Chest CAD中获益,应用此系统可对肺小结节进行早期检测,检测结果可通过CT和病理分析确诊,从而使医生对病人进行正确治疗。”
浙江医院 管卫教授、毛伟敏教授(现浙江省肿瘤医院院长)-- 中国肿瘤杂志 2007年第16卷第10期
发表临床总结:
“使用IQQA-Chest CAD系统可以在一定程度上提高诊断率,低年资放射诊断医生更能从中得到很大的帮助,使自己的诊断水平得到很大的提高。此外,在利用CAD系统输出结果时,高年资放射诊断医生对于肺部小结节检测的准确性高于低年资放射诊断医生。CAD系统的输出结果会出现一些假阳性,但大多数假阳性结节都较易识别,不会影响检测准确度,大约80%的假阳性是肋骨交叉或肋骨与血管的重叠,或肋骨与软组织,如乳房、心脏或横膈影等重叠而造成的。CAD系统能提示放射诊断医生将注意力集中到图像的可疑区域,检测出易于漏检的微、小结节,提高诊断的准确性。因此,CAD系统是有一定价值的,是放射诊断医生重要的辅助诊断工具。”
上海华东医院 张国桢教授 -- 2007年10月中华医学会第十四次全国放射学学术会议 中国 南京
发表临床总结:
“CR/DR胸片是基础检查方法,能发现病变,可作为筛选检查。但需要配置CAD软件(如IQQA-Chest),以增强对直径< 2cm肺小结节的识别、分析和确认,特别有助于对医生易遗漏的小结节和肺隐蔽部位的小结节的检测和诊断。CAD(计算机辅助检测诊断)将会成为系列随访的必需工具,既节约时间,又提高工作效率。”
北京协和医院 宋伟主任医师、金征宇教授等 -- 中国医学科学杂志 2007年3月22卷 第1号
发表临床总结:
“There is a critical need to develop computer-aided detection (CAD) of chest DR analysis, which can ensure accurate, consistent, and efficient diagnoses. IQQA-Chest will therefore provide assistance with the examination of chest DR images in large-scale screening for lung cancer.”
“发展数字胸片上使用的能够确保正确、一致和有效诊断CAD系统极为迫切。因此,IQQA-Chest系统在大规模肺癌筛查中,为数字胸片的解读提供了很好的帮助。”
北京友谊医院 马大庆教授、贺文教授等 -- 2007年3月欧洲放射年会ECR 奥地利 维也纳
发表临床总结:
“The computer system could help radiologists identify more lesions, especially small ones that are more likely to be overlooked, on chest DR/CR images, while its FPs were easy to recognize and dismiss. It is suggested that DR/CR assisted by the real-time interactive pulmonary nodule analysis system may be an effective means to screen large populations for lung cancer.”
“该计算机系统可以帮助放射医生在肺部DR数字放射影像/CR计算机放射影像上识别更多的病灶,特别是一些很容易被忽略的小病灶,同时系统的假阳性很容易判断并排除。建议采用DR/CR辅以该实时交互肺部结节分析系统可成为大规模肺癌筛查得有效手段。”
美国爱荷华大学医学院 Edwin J.R. van Beek MD等 -- 2006年11月北美放射学会年会 (RSNA) 美国 芝加哥
发表临床总结:
“The prospective study showed that a real-time interactive pulmonary nodule analysis and concurrent reading system could effectively help radiologists identify more lesions, especially small ones, and increase the confidence level of diagnosis in a routine clinical reading environment.”
“前瞻实验表明该实时交互式肺部结节解读分析及同步解读系统可以有效的帮助放射科医生识别更多的结节,尤其是小结节,同时可以提高医生日常读片的诊断信心。”
上海瑞金医院 陈克敏教授等 -- 2006年10月第15届肺癌普查国际会议 (International Conference of Screening on Lung Cancer) 美国 纽约
发表临床总结:
“Experimental results indicate that computer suggestions compliment individual reader, and the majority of false positives are considered as easy to dismiss.”
“实验结果表明,计算机系统的提示对医生的读片有辅助作用,而大部分系统提示的假阳性容易排除。
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