Imaging-based observational databases for clinical problem solving: The role of informatics

Journal of the American Medical Informatics Association

Volumn 20, Issue 6, 2013, Pages 1053-1058

  Bui, Alex A T ^a   Hsu, William ^a   Arnold, Corey ^a   El Saden, Suzie ^a   Aberle, Denise R ^a   Taira, Ricky K ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; CALIBRATION; DATA BASE; DIAGNOSTIC IMAGING; DISEASE MODEL; HUMAN; IMAGE ANALYSIS; KNOWLEDGE DISCOVERY; MEDICAL DECISION MAKING; MEDICAL INFORMATICS; PATIENT CARE; PROBLEM SOLVING;

BIOMARKERS; MEDICAL IMAGING; MEDICAL INFORMATICS;

BIOMEDICAL RESEARCH; DATABASES, FACTUAL; DECISION MAKING, COMPUTER-ASSISTED; DIAGNOSTIC IMAGING; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MEDICAL INFORMATICS;

EID: 84886296574     PISSN: 10675027     EISSN: 1527974X     Source Type: Journal    
DOI: 10.1136/amiajnl-2012-001340     Document Type: Article

References (69)

1. Hlatky MA, Lee KL, Harrell FE, et al. Tying clinical research to patient care by use of an observational database. Stat Med 1984;3:375-84.
2. Hlatky MA. Using databases to evaluate therapy. Stat Med 1991;10:647-52.
3. Lowe HJ, Ferris TA, Hernandez PM, et al. STRIDE-an integrated standards-based translational research informatics platform. Proceedings AMIA Fall Symposium 2009:391-5.
4. Gainer V, Hackett K, Mendis M, et al. Using the i2b2 hive for clinical discovery: an example. Proceedings AMIA Fall Symposium 2007:959.
5. Marcus DS, Olsen TR, Ramaratnam M, et al. The Extensible Neuroimaging Archive Toolkit: an informatics platform for managing, exploring, and sharing neuroimaging data. Neuroinformatics 2007;5:11-34.
6. Andriole KP, Wolfe JM, Khorasani R, et al. Optimizing analysis, visualization, and navigation of large image data sets: one 5000-section CT scan can ruin your whole day. Radiology 2011;259:346-62.
7. Tagare HD, Jaffe CC, Duncan J. Medical image databases: a content-based retrieval approach. J Am Med Inform Assoc 1997;4:184-98.
8. Donovan T, Manning DJ. The radiology task: Bayesian theory and perception. Br J Radiol 2007;80:389-91.
9. Clarke LP, Sriram RD, Schilling LB. Imaging as a biomarker: standards for change measurements in therapy workshop summary. Acad Radiol 2008;15:501-30.
10. Buckler AJ, Bresolin L, Dunnick NR, et al. A collaborative enterprise for multi-stakeholder participation in the advancement of quantitative imaging. Radiology 2011;258:906-14.
11. McNitt-Gray MF, Armato SG III, Meyer CR, et al. The Lung Image Database Consortium (LIDC) data collection process for nodule detection and annotation. Acad Radiol 2007;14:1464-74.
12. National Lung Screening Trial ResearchAberle T, Berg DR, Mueller SG, Weiner MW, Thal LJ, et al. The Alzheimer's disease neuroimaging initiative. Neuroimaging Clin N Am 2005;15:869-77, xi-xii.
13. Deserno T, Aach T, Amunts K, et al. Advances in medical image processing. Comput Sci Res Dev 2011;26:1-3.
14. Fei B, Yang X, Nye JA, et al. MRPET quantification tools: registration, segmentation, classification, and MR-based attenuation correction. Med Phys 2012;39:6443-54.
15. Channin DS, Mongkolwat P, Kleper V, et al. The caBIG™ annotation and image markup project. J Digit Imaging 2010;23:217-25.
16. Clunie DA. DICOM structured reporting and cancer clinical trials results. Cancer Inform 2007;4:33.
17. Nyce JM, Steele JS, Gunderman RB. Bridging the knowledge divide in radiology education. Radiology 2006;239:629-31.
18. Cootes TF, Edwards GJ, Taylor CJ. Active appearance models. IEEE Trans Pattern Anal Mach Intell 2001;23:681-5.
19. Pizer SM, Fletcher PT, Joshi S, et al. Deformable M-reps for 3D medical image segmentation. Int J Comput Vis 2003;55:85-106.
20. Toga AW, Thompson PM. What is where and why it is important. Neuroimage 2007;37:1045-9.
21. Boone JM. Radiological interpretation 2020: toward quantitative image assessment. Med Phys 2007;34:4173-9.
22. Bell DS, Greenes RA, Doubilet P. Form-based clinical input from a structured vocabulary: initial application in ultrasound reporting. Proceedings AMIA Fall Symposium 1992:789.
23. Liberman L, Menell JH. Breast imaging reporting and data system (BI-RADS). Radiol Clin North Am 2002;40:409-30.
24. Hussein R, Engelmann U, Schroeter A, et al. DICOM structured reporting: Part 1. Overview and characteristics. Radiographics 2004;24:891-6.
25. Reiner B. The challenges, opportunities, and imperative of structured reporting in medical imaging. J Digital Imaging 2009;22:562-8.
26. Meystre SM, Savova GK, Kipper-Schuler KC, et al. Extracting information from textual documents in the electronic health record: a review of recent research. Yearb Med Inform 2008;1:128-44.
27. Son RY, Taira RK, Kangarloo H. Inter-document coreference resolution of abnormal findings in radiology documents. Stud Health Technol Inform 2004; 107:1388-92.
28. Zheng J, Chapman WW, Crowley RS, et al. Coreference resolution: a review of general methodologies and applications in the clinical domain. J Biomed Inform 2011;44:1113-22.
29. Arnold C, Speier W. A topic model of clinical reports. Proceedings ACM SIGIR 2012:1031-2.
30. Wang X, McCallum A. Topics over time: a non-Markov continuous-time model of topical trends. Proceedings ACM SIGKDD 2006:424-33.
31. Bos J, Markert K. Recognising textual entailment with logical inference. Proceedings Association Comparative Linguistics 2005:628-35.
32. Ramos DR, Ten Teije A, Miksch S, et al. Knowledge representation for health-care. Berlin: Springer-Verlag, 2011.
33. Coden A, Savova G, Sominsky I, et al. Automatically extracting cancer disease characteristics from pathology reports into a disease knowledge representation model. J Biomed Inform 2009;42:937-49.
34. Krallinger M, Valencia A, Hirschman L. Linking genes to literature: text mining, information extraction, and retrieval applications for biology. Genome Biol 2008;9 (Suppl 2):S8.
35. Arnold CW, El-Saden S, Bui AAT, et al. Clinical cased-based retrieval using latent topic analysis. Proceedings AMIA Fall Symposium 2010:26-30.
36. Smith JJ, Sorensen AG, Thrall JH. Biomarkers in imaging: realizing radiology's future. Radiology 2003;227:633-8.
37. Padhani AR, Miles KA. Multiparametric imaging of tumor response to therapy. Radiology 2010;256:348-64.
38. Rutman AM, Kuo MD. Radiogenomics: creating a link between molecular diagnostics and diagnostic imaging. Eur J Radiol 2009;70:232-41.
39. Thompson PM, Martin NG, Wright MJ. Imaging genomics. Curr Opin Neurol 2010;23:368-73.
40. Moffat BA, Chenevert TL, Meyer CR, et al. The functional diffusion map: an imaging biomarker for the early prediction of cancer treatment outcome. Neoplasia 2006;8:259-67.
41. Padhani AR. Diffusion magnetic resonance imaging in cancer patient management. Semin Radiat Oncol 2011;21:119-40.
42. Cyran CC, von Einem JC, Paprottka PM, et al. Dynamic contrast-enhanced computed tomography imaging biomarkers correlated with immunohistochemistry for monitoring the effects of sorafenib on experimental prostate carcinomas. Invest Radiol 2012;47:49-57.
43. Nishino M, Jackman DM, Hatabu H, et al. Imaging of lung cancer in the era of molecular medicine. Acad Radiol 2011;18:424-36.
44. Phan JH, Quo CF, Wang MD. Functional genomics and proteomics in the clinical neurosciences: data mining and bioinformatics. Prog Brain Res 2006;158:83-108.
45. Wang Y, van Klaveren RJ, van der Zaag-Loonen HJ, et al. Effect of nodule characteristics on variability of semiautomated volume measurements in pulmonary nodules detected in a lung cancer screening program. Radiology 2008;248:625-31.
46. Clarke LP, Croft BS, Nordstrom R, et al. Quantitative imaging for evaluation of response to cancer therapy. Transl Oncol 2009;2:195-7.
47. Jack CR Jr, Bernstein MA, Borowski BJ, et al. Update on the magnetic resonance imaging core of the Alzheimer's disease neuroimaging initiative. Alzheimers Dement 2010;6:212-20.
48. Madhavan S, Zenklusen JC, Kotliarov Y, et al. Rembrandt: helping personalized medicine become a reality through integrative translational research. Mol Cancer Res 2009;7:157-67.
49. Van Horn JD, Toga AW. Is it time to re-prioritize neuroimaging databases and digital repositories? Neuroimage 2009;47:1720-34.
50. Gutman DA, Cooper LA, Hwang SN, et al. MR imaging predictors of molecular profile and survival: multi-institutional study of the TCGA glioblastoma data set. Radiology 2013;267:569-96.
51. Ellingson BM, Cloughesy TF, Lai A, et al. Quantitative probabilistic functional diffusion mapping in newly diagnosed glioblastoma treated with radiochemotherapy. Neuro-oncology 2013;15:382-90.
52. Principi M, Italiani M, Guiducci A, et al. Perfusion MRI in the evaluation of the relationship between tumour growth, necrosis and angiogenesis in glioblastomas and grade 1 meningiomas. Neuroradiology 2003;45:205-11.
53. Adams ST, Leveson SH. Clinical prediction rules. BMJ 2012;344;d8312.
54. Pearl J. Causality: models, reasoning, and inference. New York: Cambridge University Press, 2000.
55. Lucas PJ, van der Gaag LC, Abu-Hanna A. Bayesian networks in biomedicine and healthcare. Artif Intell Med 2004;30:201-14.
56. Donkers J, Tuyls K. Belief networks for bioinformatics. Compu Intell Bioinform 2008:75-111.
57. Smith M, Saunders R, Stuckhardt L, et al. Best care at lower cost: the path to continuously learning health care in America. Washington, DC: The National Academies Press, 2012.
58. Chan AW, Altman DG. Epidemiology and reporting of randomised trials published in PubMed journals. Lancet 2005;365:1159-62.
59. Schulz KF, Altman DG, Moher D, et al. CONSORT 2010 statement: updated guidelines for reporting parallel group randomized trials. Ann Intern Med 2010;152:726-32.
60. Haynes RB. Of studies, syntheses, synopses, summaries, and systems: the '5S' evolution of information services for evidence-based healthcare decisions. Evid Based Med 2006;11:162-4.
61. Yoo TS, Ackerman MJ, Lorensen WE, et al. Engineering and algorithm design for an image processing API: a technical report on ITK-The Insight Toolkit. Stud Health Technol Inform 2002;85:586-92.
62. Zhou XS, Zillner S, Moeller M, et al. Semantics and CBIR: a medical imaging perspective. Proceedings 2008 ACM International Conference Content-based Image and Video Retrieval 2008:571-80.
63. Akgul CB, Rubin DL, Napel S, et al. Content-based image retrieval in radiology: current status and future directions. J Digit Imaging 2011;24:208-22.
64. Welter P, Riesmeier J, Fischer B, et al. Bridging the integration gap between imaging and information systems: a uniform data concept for content-based image retrieval in computer-aided diagnosis. J Am Med Inform Assoc 2011;18:506-10.
65. Belden CJ, Valdes PA, Ran C, et al. Genetics of glioblastoma: a window into its imaging and histopathologic variability. Radiographics 2011;31:1717-40.
66. Depeursinge A, Muller H. Sensors, medical images and signal processing: the growth of clinicians' expectations. Yearb Med Inform 2011;6:92-5.
67. Reiner BI, Siegel EL. The clinical imperative of medical imaging informatics. J Digital Imaging 2009;22:345-7.
68. Mollura DJ, Carrino JA, Matuszak DL, et al. Bridging radiology and public health: the emerging field of radiologic public health informatics. J Am Coll Radiol 2008;5:174-81.
69. Maynard CD. Radiologists: physicians or expert image interpreters? Radiology 2008;248:333-6.