Imaging Informatics Ann Scherzinger, PhD, CIIP C-TRIC Lecture Series, May 18, 2011

Transcription

1 Imaging Informatics Ann Scherzinger, PhD, CIIP C-TRIC Lecture Series, May 18, 2011

2 Science of Information and Information Processing! Breadth, depth of current activities in human medical imaging informatics! Research Imaging versus Clinical Imaging! National and Local Initiatives! C-TRIC web site as an AMC imaging information resource

3 ! Visual system! Subject Imaging Chain Issue which affect Image Information! Energy source and capture device! Image reconstruction and processing! Display! Storage and Transmission! Reporting

4 Visual Systems THE HUMAN THE COMPUTER Analysis of eye movements in performing diagnosis. Enhance speed Reduce fatigue Training Variations in sensitivity and specificity across users and/or algorithms. Variations in manually determined numerical results.

5 Vision Experiments Evaluating Eyegaze Targeting to Improve Mouse Pointing for Radiology Tasks Journal of Digital Imaging, Vol 24, No 1 (February), 2011: pp

6 Subject! Obvious is normal versus abnormal! Less obvious is: subject complexity! Anatomical variations! Contrast tolerance! Body habitus! Radiation exposure! When data is used for! Inter- and intra-subject comparisons! Inter-modality comparisons! Determine image content

7 Automated Correspondence Retinal Images Used in this Study Automatic Correspondence on Medical Images: A Comparative Study of Four Methods for Allocating Corresponding Points Economopoulos TL. etal. Journal of Digital Imaging, Vol 23, No 4 (August), 2010: pp

8 Image Fusion CT (UL), PET (UR), Fused (LL) Takes advantage of the high spatial resolution anatomy of CT and the functional information of PET

9 Energy Source and Capture Device! Obvious: appropriate for condition (MR/CT for MS)! Less obvious:! Radiation concerns! Imaging protocol variation! Resolution/noise variation! Scanner variation! Availability and accuracy of metadata

10 Acquisition variation Bone scan images acquired at varying time points. Bone scan images after a histogram matching technique. Comparison of Image Enhancement Methods for the Effective Diagnosis in Successive Whole-Body Bone Scans Jeong CB. Journal of Digital Imaging, Vol 24, No 3 (June), 2011: pp

11 Acquisition variation Variation in Protocol labels for Brain MRI study Study of protocol name variations for a sample of Brain MRI studies from 3 scanners

12 Slice Thickness Variation 3D models of the heart from 5mm and 1mm slice thickness, CT acquisitions

13 Image Reconstruction and Processing Variation in CT Number Obtained for Three Scanners! Filters Reconstruction Post-processing Electron Density CT Number Soft Tissue! Noise corrections! Compression! CAD

14 Display! Hanging protocols! Efficient reading! Multi-spectral comparison! Serial comparisons! Data visualization! Display characteristics! Atlases

15 Display - Atlas An Online Evidence-Based Decision Support System for Distinguishing Benign from Malignant Vertebral Compression Fractures by Magnetic Resonance Imaging Feature Analysis Wang KC. Journal of Digital Imaging, Vol 24, No 3 (June), 2011: pp

16 Storage and Transmission! File format variations DICOM (clinical) tiff, gif, jpg, zvi, lscm pdf, xml, doc, bmp Proprietary Compression! Recall needs! Metadata! Data organization! Sharing Mouse CT, 3GB study Human CT, 1.6G study! Architecture and size! Cloud vrs local! Research workflow! Sharing and security needs! Anonymization! Sufficient labeling to be of use! Testing of new algorithms

17 Data Sharing

18 Reporting! Clinical eports! Typically free text! ACR templates! DICOM-SR! BIRADS, OB reports! Limited standardization of terminology! Research! NLP! Integration of ontologies! Creation of domain specific ontology! Integration into reports: AIM

19 RadLex - RSNA The IR Radlex Project: An Interventional Radiology Lexicon A Collaborative Project of the Radiological Society of North America and the Society of Interventional Radiology. Kundu S. etal. J Vasc Interv Radiol 2009; 20:S275 S277

20 Annotated Image Markup NCI Automated Structured Reporting of Imaging Findings Using the AIM Standard and XML Zimmermann SL. etal. RadioGraphics 2011; 31:

21 Society for Imaging Informatics in! Medical imaging and informatics professionals! CIIP! ABII Certification Process! Educational materials! Journal, technical publications, on-line materials! Networking community Medicine (SIIM)

22 Research versus Clinical Clinical Trials as Research! Standard protocols! Organize by project! Quantitation more common! Requires standard terminology! Requires standard reporting! Non-standard image formats! Patient variable protocols! Organize by patient! Limited quantitation! Typically free text, not standardized language! Reporting templates becoming more common! DICOM images

23 C-TRIC Participation in Quantitative Imaging Initiatives! Clinical and Translational Science Awards Imaging Working Group (IWG)! The CTSA Imaging Working Group is dedicated to sharing ideas, visions, and expertise to enhance the utility of imaging in translational research.! Subgroups: Education, Informatics Resources, Protocol Standardization! NCI-Centers for Qualitative Imaging Excellence (CQIE)! NIBIB Quantitative Imaging Biomarkers Alliance (QIBA)! advance quantitative imaging and the use of imaging biomarkers in clinical trials and clinical practice..! Quantitative CT, MRI, PET and COPD-Asthma working groups! NCI-Quantitative Imaging Network (QIN)! improve the role of quantitative imaging for clinical decision making in oncology by the development and validation of data acquisition, analysis methods, and tools to tailor treatment to individual patients and to predict or monitor the response to drug or radiation therapy.! Informatics, Data Sharing, Clinical Trial Design, Data Collection, Image Analysis and Performance Metrics, Outreach

24 CTSA-IWG Issues facing translational imaging research! Fee Schedules: range of typical fees for research imaging expenses at CTSA sites human and animal.! Uniform Protocol for Imaging in Clinical Trials (UPICT) template. 18FDG PET/CT template.! Description of Imaging Cores at CTSA sites.! Overview of research informatics infrastructure needs. How can they work?! Whitepapers on research informatics needs

25 NCI Centers for Quantitative Imaging Excellence (CQIE) goals! Detect tumors early, monitor disease and guide therapy using the most advanced quantitative imaging techniques.! Establish a resource of trial ready sites within NCI Cancer Centers, with the ability to perform accurate and consistent quantitative imaging protocols! Pre-qualify sites to promote rapid start-up of clinical trials.! Promote collaboration among imaging and treatment teams. Zhao etal. Radiology: Volume 252: Number 1 July 2009

26 UCCC-UCD-UCH NCI-CQIE collaboration activities! Member of the first group of Cancer Centers chosen for pre-qualification.! Qualified in February 2011 to conduct clinical trials utilizing! CT/MRI volumetric studies! MRI dynamic contrast enhanced (DCE) imaging protocols! MRI diffusion weighted imaging! Static and Dynamic PET-PET/CT imaging protocols Marchiano A etal. Radiology: Volume 251: Number 3 June 2009! UCH Department of Radiology physics and technologist teams performing on-going testing to maintain yearly qualification.

27 /5#+&.9>?5A&B5?6C%599&D5E76?A&15%#5> /7C1A7%76?F&.%6< /7C$5E76?A&3,9#5$9 /C9#C%&D5E76?A&15%#5> />5?9# G5?A#+ D?%?=5$5%#F&.%6 />7=+?$&?%E&*C$5%H9&GC947#?A />79#CAID,5>9&3J"7KK /"6LA5>&/7C$5E76?A&MM1 113&!99C67?#59F&.%6< 1CA"$K7?&N%7O5>97#, B587%75%9 B"L5&N%7O5>97#, PB! QR&G5?A#+6?>5 QA5%875AE&GC947#?AF&NS G?>O?>E&D5E76?A&36+CCA G?"L5A?%E&N%7O&GC947#?A See speaker notes for full list of individual names G5%>,&PC>E&G5?A#+ 3,9#5$.$?=54?65.%#7CF&.%6<.C;?&1C$4>5+5%97O5&M"%=&.$?=7%=&15%#5> TC+%9&GC4L7%9&N%7O5>97#, S7#;?>5F&.%6< M57E5%&N%7O D5E1#> M"%=&1?%65>&!AA7?%65 D?AA7%6L>CE#&.%9#7#"#5&C8&U?E7CAC=, D?99?6+"95##9&Q5%5>?A&GC947#?A DB&!%E5>9C%&1?%65>&15%#5> D5E7?%&256+%CAC=759 D5>6L D5>=5&G5?A#+6?>5 D7AA5%%7"$&V+?>$?65"#76?A9 D.2!&WXRD!Y DC"%#&37%?7&GC947#?A D3S11 X?#7C%?A&T5;79+ G5?A#+ X1.&X.G&1?%65>&.$?=7%=&V>C=>?$ X.32 V5>654#7O5.%8C>$?#769F&.%6< V+7A749&G5?A#+6?>5 U?EV+?>$ UC9;5AA V?>L&1?%65>.%9#7#"#5 U"9+&N%7O5>97#,&D5E76?A&15%#5> 375$5%9 3#?%8C>E&N%7O5>97#,& 25>?U56C%F&.%6< 2+5&V+?%#C$&M?KC>?#C>,F&.%6< 2C9+7K? N%7O5>97#,&D5E76?A&.$?=7%= N%7O5>97#,&C8&!A?K?$?&?#&/7>$7%=+?$ N%7O5>97#,&C8&/>7#79+&1CA"$K7? N%7O5>97#,&C8 1?A78C>%7?F&B?O79 N%7O5>97#,&C8&1?A78C>%7?F&MC9&!%=5A59 N%7O5>97#,&C8&1+76?=C N%7O5>97#,&C8&1CAC>?ECF&B5%O5> N%7O5>97#,&C8&.AA7%C79&?#&1+76?=C&WN.1Y N%7O5>97#,&C8&.C;? N%7O5>97#,&C8&D?>,A?%E& N%7O5>97#,&C8&V5%%9,AO?%7? N%7O5>97#,&C8&V79? N%7O5>97#,&C8&N#?+ N%7O5>97#,&C8&:7>=7%7?&G5?A#+&3,9#5$ N%7O5>97#,&C8&*796C%97%ID?E79C% :.B!&B7?=%C9#769F&.%6< *57AA&1C>%5AA&D5E76?A&1CAA5=5 *+,&-./!0&12& '

28 !"#$%&'()*$+'!"#$%&%#%&'()*+)%,) -(#."/()0&.(#.()-,/()1/(2&.(34 AB";<7#;#7>5&7$;C5D&#?&AB";%#7#;#7>5& B";%#7#;#7>5&;44<76;#7?%9&#?&?4#7$7G5& HI;$4<590& <?%C7#"=7%;<&B";%#7#;#7?%?8& =795;95L!"#"$%&'()( *+,&-./!0&12& :

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

30 !"#$%#&'%()*)(+#*",#-"./0%1,)(#232.4&)&# 235#5%3&)1"0%1,4+#6%#2,%#,%7/%&1)389!""#"$%&#$'%()**+,)-+$#./%0-)123&)-4%+($#.#$#/"5 6+-$#(#7+$/%#2%/87/-#9/2$+*%"$13#/"%:)-%('+-+($/-#;#20%7/-:)-9+2(/< =/.#/&%-/>1/"$"%+23%7-).#3/%://3,+(4%)2%"$+23+-3#;#20%+(>1#"#$#)2% 6-/7+-/%:)-%:1$1-/%7-)31($%3/./*)79/2$%+23%9+-4/$#205 FK

31 Measurement Variability in the Assessment of Part-Solid Lung Nodules OBJECTIVE! Evaluate intra- and inter-observer variability of volumetric and longest diameter measures of part-solid lung nodules using a low-dose CT screening protocol. BACKGROUND AND SIGNIFICANCE! Part-Solid nodules (PSN) have much higher malignancy rate (62.5 %) than GGN (19%) or solid nodules (7%)! Solid portion correlates with the invasive component! Staging and treatment implications K. GARG, PI

32 a b c Invasive Adenocarcinoma. Axial CT image (a) shows a part solid nodule in the left upper lobe. Corresponding sagittal CT images (b) and (c) show automated estimation of the volume of solid component (1.188 ml) the entire lesion (8.312 ml). In this case, if tumor size were measured only by the invasive component, the size T factor would change from T2a to T1a Henschke C, et al. AJR Am J Roentgenol 2002;178(5): Travis W, Brambilla E, Noguchi M, et al. IASLC/ATS/ERS International multidisciplinary classification of lung adenocarcinoma. J Thoracic Oncol 2011;6:

33 ! 30 Subject Scans Image Acquisition! A combination of retro- (20) and prospective (10) part-solid lung nodule cases! Acquired on a Siemens 16 or Siemens 64 CT! Low Dose Imaging Protocol, B60 (sharp) reconstruction kernel! 1 nodule per patient! Phantom Scans! Scanning parameters identical to those for human subjects, performed on both Siemens 16 and Siemens 64 CT systems.! Imaging of Lungman phantom with synthetic part-solid nodules from Dr. Nicholas Petrick (1A Group). Performed on the Siemens 16 and Siemens 64 CT.! Evaluation of synthetic nodules using same metrics as for human subjects.! Imaging of ACR phantom to assess noise and spatial resolution, for comparison with data from Dr. Charles Fenimore (1C Group)

34 Measures! Analysts! 4 radiologists, repeating each measurement! Software! Vitrea 3D volumetry! Phantom calibration! Intra- and Inter-observer variability! Metrics Whole Lesion Solid Component Low Density Component Volume Volume Volume (Derived) Mean CT Density Mean CT Density Mean CT Density (Derived) RECIST RECIST RECIST (derived)

35 NCI-QIN Bioinformatics! Develop specifications for research archive! Central archive, access control! Support research and clinical file formats! User interface! Maintenance, documentation and support! Open source, user community support! Review existing systems:! NBIA - NCI! XNAT Washington University SOM! MIDAS Kitware open source

36 C-TRIC Web Site Scheduled to launch July 1, 2011 Purpose Access to information on imaging resources on campus Access to consultation and educational materials for those who would like to incorporate imaging into their research Mouse image courtesy N. Serkova