糖心原创

Contact

• workRoom B64 Clinical Sciences Building
  Nottingham City Hospital
  Hucknall Road
  Nottingham
  NG5 1PB
  UK
• work0115 8231895
• Yan.Chen@nottingham.ac.uk

Biography

Professor Chen was appointed to the Chair of Digital Screening and is the head of the Digital Cancer Screening Research Group at 糖心原创, having previously been the Director of the Applied Vision Research Centre at Loughborough University.

Professor Chen has led the development of the world-first national digital assessment and training scheme in radiology (PERFORMS) for breast screening readers which is fully embedded within the UK's National Breast Screening Programme for more than 34 years in order to help to ensure the quality of radiology reporting and improve readers' imaging interpretation skills (). This platform is endorsed by the Royal College of Radiologists, comprises a mandated activity for radiologists' annual appraisal and is also accredited by the European accreditation Council for Continuing Medical Education.

Due to its success, her research has been extended in the UK lung cancer screening programme (PERFECTS) which is the first assessment and training platform that aims to ensure appropriate interpretation of lung CT scans in order for radiologists to benefit patient outcome and streamline clinician workload (). It is the external quality assurance for lung screening programme and self-assessment and training to screening readers. The scheme addresses the need for continuous improvement in radiology reporting ability which is vital for any successful screening programme.

Expertise Summary

Professor Chen has received multiple large research grant awards as PI/Co-I, working closely with national and international organisations, including Horizon 2020, WHO, Innovate Research UK, National Institute for Health Research, and NHS England. Her research interests are in medical imaging, covering cancer screening, early cancer detection, and diagnostic accuracy in CT, breast mammography and tomosynthesis, contrast mammography, and digital pathology specialities. She's specifically interested in quality assurance of health professionals and Artificial Intelligence (AI) programmes that interpret medical images, as well as using eye tracking technology and developing AI applications to aid health professionals' training.

Yan's current research projects are:

• PERFORMS (Personal Performance in Mammographic Screening): UK National mandated Breast Cancer Screening External Quality Assurance scheme. UK Breast Screening Programme.
• IMPROVE: a specialist training scheme for radiographers who undergo breast screening training.
• PERFECTS (PERFormance Evaluation for CT Screening): the first national External Quality Assurance scheme for lung cancer imaging assessment. The scheme is used to ensure appropriate interpretation of lung scans which benefits patient outcome.
• DART (The Integration and Analysis of Data using Artificial Intelligence to Improve Patient Outcomes with Thoracic Diseases): an AI project aims to develop integrated diagnostics that will enable the earlier diagnosis of lung cancer for increased patient survival and large time and cost savings to the NHS.
• MyPeBS (My Personal Breast Screening): is a major ambitious European initiative. This unique international clinical study compares a personalised risk-based screening strategy (based on the individual women's risk of developing breast cancer) to standard screening among 85,000 women aged 40 to 70 in 6 countries: Belgium, France, Israel, Italy, United Kingdom and Spain.
• PROSPECTS (Prospective Randomised Trial of Digital Breast Tomosynthesis): A randomised contrail trial involving 100,000 female volunteers to compare the use of traditional 2D mammograms with the new 3D breast imaging technology. The trial will measure the efficacy and cost-effectiveness of the two technologies.

Professor Chen is also working on AI evaluation and benchmarking to ensure that AI can be safely implemented into the clinical setting to aid cancer detection, particularly in the screening setting. She advocates risk stratified approaches to screening programmes and is currently involved with the MyPEBS clinical trial, as well as screening technology improvement, such as the potential uptake of breast tomosynthesis in screening, part of the PROSPECTS trial.

She has held various positions, including Honorary Member of Royal College of Radiologists, RSNA Machine-Learning Committee Member, Chair of SPIE Medical Imaging, Associate Editor for British Journal of Radiology and Journal of Medical Imaging.

Research Summary

I have built an internationally recognised online teaching and training resource called 'PERFORMS' for breast clinicians, radiologists and radiographers which helps participants to improve their… read more

Recent Publications

• CHEN Y, JAMES J, MICHALOPOULOU E, DARKER I and JENKINS J, 2022. Radiology.
• YAN CHEN, JONATHAN JAMES, ELENI MICHALOPOULOU and IAIN DARKER, 2021. European Journal of Radiology. 142, 109881
• CHEN Y, JAMES JJ, CORNFORD EJ and JENKINS J, 2020. Radiology: Imaging Cancer.
• GALE A.G. and CHEN Y, 2020. A review of the PERFORMS scheme in breast screening The British Institite of Radiology. 93: 20190908,

• View all publications

Current Research

I have built an internationally recognised online teaching and training resource called 'PERFORMS' for breast clinicians, radiologists and radiographers which helps participants to improve their mammographic imaging interpretation skills and remain up to date in their specialities. I design the new PERFORMS test sets every year, selecting challenging breast screening cases that can provide participants with information about their individual strengths and weaknesses in reading performance, identify under-performing outliers and accommodate further tailored training to improve their performance. The cancer detection performance evidence from this has then been adopted as the model of service delivery (Appendix 4).

I am developing an online teaching and training module called 'PERFECTS', a new and ground-breaking platform that provides teaching and learning to all radiologists in the UK who interpret CT scans in order for them to benefit patient outcome and streamline clinician workload.

I have also contributed to the development of the 'IMPROVE' scheme, a special training case set designed for technologists and advanced practitioner radiographers who undergo breast screening training. As individuals undergo such training, they examine the same test set both early in their training and towards the end of their training. Differences in performance between the first and second occasion help to give insight into aspects of individual participants' improved skills as they have progressed through their mammographic education. This module, which is continually modified to keep it contemporary in terms of content and relevance, remains innovative in that it attracts and trains individuals from all UK screening programme national training centres.

Following my move to UoN I have worked very closely with UoN Technology Transfer Office (TTO) and Nottingham Technology Venture (NTV). I gained NTV business plan approval for an international medical imaging assessment MedTech spin-out company supported by UoN TTO. The approval has now converted to a private limited spin- out company, PERFORMS Assessment Ltd.

• CHEN Y, JAMES J, MICHALOPOULOU E, DARKER I and JENKINS J, 2022. Radiology.
• YAN CHEN, JONATHAN JAMES, ELENI MICHALOPOULOU and IAIN DARKER, 2021. European Journal of Radiology. 142, 109881
• CHEN Y, JAMES JJ, CORNFORD EJ and JENKINS J, 2020. Radiology: Imaging Cancer.
• GALE A.G. and CHEN Y, 2020. A review of the PERFORMS scheme in breast screening The British Institite of Radiology. 93: 20190908,
• MCMAHON M.A., HAIGH I., CHEN Y., MILLICAN-SLATER R.A. and SHARMA N., 2020. European Journal of Radiology.
• CHEN Y, JAMES J, CORNFORD EJ and JENKINS J, 2020. Radiology: Imaging Cancer.
• Prostate Imaging Self-assessment and Mentoring (PRISM): a prototype self-assessment scheme. 2019. At: Town and Country Resort & Convention Center San Diego, California, United States02/16/2019 00:00:00-02/21/2019 00:00:00.
• PRostate Imaging Self-assessment and Mentoring (PRISM): a prototype self-assessment scheme for radiologists. 2019. At: Austria Center Vienna02/27/2019 00:00:00-03/03/2019 00:00:00.
• N. SHARMA, M. MCMAHON, Y. CHEN and B. J. G. DALL, 2019. Radiology. 29(2), 310-317
• X.LIU, J.LOU, H.FANG, Y. CHEN, P. OUYANG, Y. WANG, B. ZOU and L. WANG, 2019. IEEEXplore. (In Press.)
• Q. TANG, Y. CHEN, G. SCHAEFER and A. GALE, 2019. In: Biomedical Optics and Imaging - Proceedings of SPIE. 10954. (In Press.)
• Prostate Imaging Self-assessment and Mentoring Scheme. 2018. At: Crowne Plaza Barcelona09/13/2018 00:00:00-09/16/2018 00:00:00.
• Y. CHEN, L. DONG, E. CORNFORD and J. JENKINS, 2018. The relationship between breast screening readers' real-life performance and their associated performance on the PERFORMS scheme. BREAST CANCER RESEARCH. 20,
• R. S. BHOGAL and A.G. GALE, 2018. International Journal of Information Technology and Computer Science(IJITCS).
• Y. ZENG, Y. ZHAO, S. LIAO, M. LIAO, Y. CHEN and X. LIU, 2018. Biomedical Signal Processing and Control. 45, 192-201
• Initial investigation of reading efficiency from experienced radiologists interpreting digital breast tomosynthesis (DBT) images. 2018. At: ACC Liverpool01/01/1900 00:00:00-01/01/1900 00:00:00.
• R.STANTON, D. JETHWA, K.JETHWA, Y. CHEN, L. WHISKER and S. TENNANT, 2018. The Value of Contrast Enhanced Spectral Mammography (CESM) in the Assessment of Lobular Breast Cancer. Tennant.
• Y. CHEN, Y. ZENG, S. LIAO, P. TANG, Y. ZHAO, M. LIAO and Y.X. LIANG, 2018. Computers in Biology and Medicine. 97, 63-73
• Discriminative and robust zero-watermarking scheme based on completed local binary pattern for authentication and copyright identification of medical images. 2018. At: Houston01/01/1900 00:00:00-01/01/1900 00:00:00.
• JAMES JJ and GIANNOTTI E, 2018. Clinical Radiology. 73, 886-892
• L. DONG, D. BERNADI, Q. TANG, A.G. GALE, X. LIU and Y. CHEN, 2017. Is there a difference in reading time when normal and abnormal DBT cases are examined by DBT experienced radiologists? BREAST CANCER RESEARCH. 19,
• DBT interpretation training: findings from analysis of expert visual search behaviour. 2017. At: Berlin, Germany01/01/1900 00:00:00-01/01/1900 00:00:00.
• H.NEVISI, Y. CHEN, L. DONG and A.G. GALE, 2017. How quickly do breast screeners learn their skills?. In: In SPIE Medical Imaging.
• L. DONG, Y. CHEN and A.G. GALE, 2017. Exploring the potential of analysing visual search behaviour data using FROC (free-response receiver operating characteristic) method: an initial study. In: SPIE Medical Imaging.
• Q. TANG, Y. CHEN and A.G. GALE, 2017. The implementation of an AR (augmented reality) approach to support mammographic interpretation training: an initial feasibility study.. In: SPIE Medical Imaging 2017 10136. 1013604-1-1013604-8
• Q. TANG, Y. CHEN and A.G. GALE, 2017. Communications in Computer and Information Science. 723, 377-385
• Y. CHEN, J.JAMES, A.G. GALE and L. DONG, 2016. Clinical Radiology.
• Y. CHEN, H.NEVISI and L. DONG, 2016. How new readers perform as compared to more experienced readers on the PERFORMS scheme. BREAST CANCER RESEARCH.
• The international use of PERFORMS mammographic test sets. 2016. At: Malm枚, Sweden01/01/1900 00:00:00-01/01/1900 00:00:00.
• S. TENNANT, J.JAMES, E. CORNFORD, H. BURRELL, L. HAMILTON and C. GIRO-FRAGOULAKIS, 2016. Contrast-Enhanced Spectral Mammography Improves Diagnostic Accuracy in the Symptomatic Setting. Clinical Radiology.
• Errors in Reporting Mammograms 2016. 01/01/1900 00:00:00-01/01/1900 00:00:00.
• L. DONG, Y. CHEN, A.G. GALE and P. PHILLIPS, 2016. Eye Tracking Method Compatible with Dual-screen Mammography Workstation.. In: Procedia Computer Science 90. Elsevier BV. 206-211
• A.G. GALE and Y. CHEN, 2016. Preface. In: 20th Conference on Medical Image Understanding and Analysis (MIUA) 90. Elsevier.
• E. CORNFORD, A.E. TURNBULL, J.JAMES, R. TSANG, T. AKRAM, H. BURRELL, V. JONES and Y. CHEN, 2015. BRITISH JOURNAL OF RADIOLOGY. 89(1058),
• Common mammography reading errors in real life and PERFORMS. 2015. At: East Midlands Conference Centre, Nottingham01/01/1900 00:00:00-01/01/1900 00:00:00.
• S. TENNANT, E. CORNFORD, J.JAMES, H. BURRELL, L. HAMILTON and Y. CHEN, 2015. BREAST CANCER RESEARCH. 17(Suppl 1), 14
• E. CORNFORD, A.E. TURNBULL, J.JAMES, R. TSANG, T. AKRAM, H. BURRELL and Y. CHEN, 2015. Breast Cancer Research. 17,
• A. SELVAN, Y. CHEN and A.G. GALE, 2015. A perceptual aid to delineating the extent of potential mammographic abnormalities. BREAST CANCER RESEARCH. 17(Suppl 1), 19
• Challenge to detection in screening mammography and feedback from mini-PERFORMS lab. 2015. At: Annual Meeting, London01/01/1900 00:00:00-01/01/1900 00:00:00.
• Performance Testing for Radiologists Interpreting Chest Radiographs. 2015. At: McCormick Place, Chicago, USA01/01/1900 00:00:00-01/01/1900 00:00:00.
• Y. CHEN, J.JAMES, A.E. TURNBULL and A.G. GALE, 2015. European Radiology. 25(10), 3003-3008
• L. DONG, Y. CHEN, A.G. GALE, B. REES and C. MAXWELL-ARMSTRONG, 2014. In: Proc. SPIE 9037, Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment. 903719.
• Y. CHEN, L. DONG, A.G. GALE, B. REES and C. MAXWELL-ARMSTRONG, 2014. Laparoscopic surgical skills training: an investigation of the potential of using surgeons' visual search behaviour as a performance indicator.. In: C. MELLO-THOMS and M. KUPINSKI, eds., Proc. SPIE 9037, Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment 903704.
• Y. CHEN, L. DONG and A.G. GALE, 2014. Breast Cancer Research. 16,
• J. YOUNGS, C. MAXWELL-ARMSTRONG, H. PARK, A.G. GALE and Y. CHEN, 2013. International Journal of Surgery. 11(8), 695
• L. DONG, Y. CHEN and A.G. GALE, 2013. Breast screening: understanding case difficulty and the nature of errors.. In: C. ABBEY, ed., Proc. SPIE 8673, Medical Imaging 2013: Image Perception, Observer Performance, and Technology Assessment
• Y. CHEN and A.G. GALE, 2013. Does routine breast screening practice over-ride display quality in reporting enriched test sets?. In: C. ABBEY and C. MELLO-THOMS, eds., Medical Imaging 2013: Image Perception, Observer Performance, and Technology Assessment.
• A.G. GALE and Y. CHEN, 2012. BMEI. 1104-1107
• Y. CHEN, A.G. GALE and M. EVANOFF, 2012. In: Medical Imaging 2012: Image Perception, Observer Performance, and Technology Assessment.
• L. DONG, Y. CHEN, A.G. GALE and D. CHAKRABORTY, 2012. In: In Medical Imaging 2012: Image Perception, Observer Performance, and Technology Assessment. SPIE.
• Y. CHEN, A.G. GALE, A.E. TURNBULL and J.JAMES, 2011. In: Progress in Biomedical Optics and Imaging - Proceedings of SPIE. 7966.
• Y. CHEN, A.G. GALE, A.E. TURNBULL and J.JAMES, 2011. In: Medical Imaging 2011: Image Perception, Observer Performance, and Technology Assessment. SPIE.
• I.T. DARKER, Y. CHEN and A.G. GALE, 2011. In: Progress in Biomedical Optics and Imaging - Proceedings of SPIE. 7966.
• L. DONG, Y. CHEN and A.G. GALE, 2011. Breast Cancer Research. 13,
• Y. CHEN, A.G. GALE, M. EVANOFF and U. ZAKIR, 2011. Breast Cancer Research.
• Y. CHEN, J.JAMES, A. EVANS, A.E. TURNBULL and A.G. GALE, 2010. Breast Cancer Research. 12(Suppl 3), 9
• I.T. DARKER, A.G. GALE and Y. CHEN, 2010. Breast Cancer Research. 12(Suppl 3), 42
• Y. CHEN and Y. CHEN, 2010. In: Proceedings of the 2010 workshop on Eye gaze in intelligent human machine interaction - EGIHMI '10..
• Y. CHEN and A.G. GALE, 2010. Intelligent Computing Applications Based on Eye Gaze: Their Role in Medical Image Interpretation. 320-325
• Y. CHEN, A.E. TURNBULL, J.JAMES, A.G. GALE and H. SCOTT, 2010. In: Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment. SPIE.
• Y. CHEN, A.G. GALE and A. EVANS, 2009. Breast Cancer Research. 11, 29
• Y. CHEN, A.G. GALE, H. SCOTT, A. EVANS and J.JAMES, 2009. Computer-Based Learning to Improve Breast Cancer Detection Skills.. In: J.A. JACKO, ed., Proceedings of the 13th International Conference on Human-Computer Interaction, Part IV: Interacting in Various Application Domains 5613. 49-57
• Y. CHEN, A.G. GALE and H. SCOTT, 2008. Breast Cancer Research. 10(S3),
• Y. CHEN, A.G. GALE and H. SCOTT, 2008. Anytime, Anywhere Mammographic Interpretation Training. Contemporary Ergonomics. 375-380
• Analysis of visual search behaviour from experienced radiologists interpreting digital breast tomosynthesis (DBT) images: a pilot study. At: Houston01/01/1900 00:00:00-01/01/1900 00:00:00.
• Q. TANG, Y. CHEN, G.SCHAEFER and A.G. GALE, The development of an augmented reality (AR) approach to mammographic training: overcoming some real world challenges.. In: Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling.: International Society for Optics and Photonics 10576.
• Y. CHEN, J.JAMES and A.G. GALE, Breast Cancer Research. 11(7),
• Y. CHEN, A.G. GALE and H. SCOTT, Mammographic interpretation training in the UK: current difficulties and future outlook.. In: B. SAHINER and D.J. MANNING, eds., Medical Imaging 2009: Image Perception, Oberver Performance and Technology Assessment 7263.
• Y. CHEN, A.G. GALE and H. SCOTT, Mammographic interpretation training: how useful is handhled technology? Progress in biomedical and optical imaging. 9,
• Y. CHEN, T. ROSS and V. MITCHELL, The need for technology to support creative information sharing whilst mobile: Identified activities and relationship groups. Lecture Notes in Computer Science. 4564, 50-59