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Last Updated: 10/28/16

Collation Goals and Objectives

Slide 1

Cancer Imaging Informatics Workshop
Cancer Imaging Program
National Cancer Institute
25-27 September 2002
Bethesda, MD

Slide 2


  • Who?
  • What?
  • How?
  • Examples...

Slide 3

Cancer Informatics
Essential Technologies for Clinical Trials

2002 - 377 pp. 62 figs. Hardcover
John S. Silva, et al.
Springer-Verlag: New York

Slide 4

Why now?

  • Growing importance of imaging in NCI’s mission
  • Cancer screening by imaging
  • Proliferation of image databases (digital radiology departments; integrated healthcare enterprise)
  • Digital image teaching files for training and certification
  • Image-guided interventions (for cancer diagnosis and therapy)
  • Emerging technologies to support cancer diagnosis and therapy (CT, MRI, US, optical, CAD, microarrays, ...)

Slide 5

Areas of concern

  • Data acquisition capabilities increase faster than infrastructure to organize and use the information we gather
  • Disconnection between in vivo images and ’’mainstream" biological knowledge resources (e.g., genome and text databases, among others)
  • Cancer imaging science appears to lag behind neuroscience and genomics/proteomics in the integrated information infrastructure

Slide 6

Potential consequences of status quo

  • Failure to integrate data sources has serious consequences for cancer imaging science and related applications
    • Lack of tools
    • Delay in translating technical developments into clinical applications
    • Inability to address many fundamental questions
  • Understanding the cancer phenotype and its behavior, especially related to therapy
  • Barrier to innovation and marginalization of imaging

Slide 7

Who are you?

  • World’s experts in biological databases, image repositories, clinical image management, radiotherapy (image-guided) quality assurance, large database architecture and applications, grid & middleware technologies, cancer ontologies, and non-image cancer data management
  • Physicians, engineers, physicists, computer scientists, neuroscientists, ...

Slide 8

  • Foreword — Power to the people — A D Baxevanis & F S Collins
  • Perspective — Genomic empowerment: The importance of public databases
  • H Varmus
  • User’s Guide
  • Question 1
    How does one find a gene of interest and determine that gene’s structure? Once the gene has been located on the map, how does one easily examine other genes in that same region? pp 9 - 17
  • Question 2
    How can sequence-tagged sites within a DNA sequence be identified? pp 18 - 20
  • . . .
  • Question 12
    How does a user find characterized mouse mutants corresponding to human genes? pp 66 - 69
  • Question 13
    A user has identified an interesting phenotype in a mouse model and has been able to narrow down the critical region for the responsible gene to approximately 0.5 cM. How does one find the mouse genes in this region? pp 70 - 73

Slide 9

Article by Harold Varmus, Genomic Empowerment: the Importance of Public Databases
Quoting: ’’...all modern biologists using genomic methods have become dependent on computer science to store, organize, search, manipulate and retrieve the new information. Thus biology has been revolutionized by genomic information and by the methods that permit useful access to it. ’’

Slide 10

Special Supplement to Nature Genetics, September 2002 A user’s guide to the human genome

Slide 11

Workshop Objectives

  • To understand how cancer imaging data can best be managed to fully exploit its potential utility and synergy with existing databases (sequences, arrays, and text)
  • To promote research to predict risk, detect and diagnose cancer, select and tailor treatments, predict outcomes and follow therapy using image repositories, biological databases, and software tools
  • To accelerate the process of testing new agents and therapies using imaging as a surrogate marker of outcome, and employing standards for Clinical Trials
  • To build image repositories that are generally useful for testing and certification of diagnostic agents, especially software post-processing of cancer images for computer aided diagnosis

Slide 12

Who is here?

  • QARC
  • 3D-QA Ctr
  • RCET
  • LIDC
  • NDMA
  • BIRN
  • Industry (Many) WEAR

Federal Agencies (NSF, DOD, NIST, DOE, and especially FDA)

Academia -- NCI-sponsored Cancer Centers and Cooperative Groups

Slide 13

How was the workshop organized?

  • Diversity of ideas; challenge the imaging science / image management community
  • Cancer focus
  • Motivated by cancer screening by imaging and concern about image repositories
    • Avoid loss of in vivo cancer phenotype information
  • Move cancer imaging science into the mainstream - to better reflect its growing importance in screening, diagnosis, treatment and followup of clinical cancer patients
    • Especially at the clinical trial level
    • And to move agents, devices, procedures from lab to clinic more quickly

Slide 14


  • NCBI and the Entrez system
  • Very large databases in science
  • Cancer (and other) imaging databases
  • BIRN
  • Standards and the FDA electronic submission process
  • WEAR

Slide 15

What do we want to accomplish?

  • A new vision of cancer imaging archives
  • What should we do?
  • Where are the opportunities?
  • What have we missed?
  • Which is most important, if we must choose one?
  • Should we work independently, or seek existing group(s) to collaborate with us?

Slide 16

Friday morning is important!

  • We want your ideas. Participate!
  • Input...input...input
  • Try to provide a few key items and as much secondary detail as you care to provide.
  • Not necessary to achieve consensus - it is sufficient to simply help us understand the controversies and alternatives
    • How can we resolve these issues?
  • After Friday, we will continue to be interested in your input. If you want to add something later, please contact us.

Slide 17

Maintaining contact

  • NIH listserver: Archive-Comm-L at
  • You have our e-mail addresses
  • We will publish reports (including web dissemination) via
  • Remember: National Cancer Institute Biomedical Imaging Program office here in Bethesda, MD

Slide 18

Selection of speakers

  • All are world’s experts in their respective areas
  • Many (?most) have never have met, despite strong common interests and potential complementary expertise
  • Integrative, collaborative, broad vision
  • All are working at the frontiers of technology and/or cancer imaging applications

Slide 19


  • in-for-mat-ics Information science [informat(ion) + -ics.]
  • bi-o-in-for-mat-ics The use of computers in solving information problems in the life sciences, mainly, it involves the creation of extensive electronic databases on genomes, protein sequences, etc. Secondarily, it involves techniques such as the three-dimensional modeling of biomolecules and biologic systems.

Slide 20


  • Bioinformatics is conceptualizing bioscientific data and applying ’’informatics techniques’’ (derived from disciplines such as applied mathematics, computer science and statistics) to understand and organize the information associated with the data on a large scale.

Slide 21


  • Neuroinformatics is:
    neuroinformatics = neuroscience + informatics

... combining neuroscience and informatics research to develop and apply advanced tools and approaches essential for a major advancement in understanding the structure and function of the brain.

Neuroinformatics research is uniquely placed at the intersections of medical and behavioral sciences, biology, physical and mathematical sciences, computer science, and engineering. The synergy from combining these approaches will accelerate scientific and technological progress, resulting in major medical, social, and economic benefits.

Slide 22

Cancer imaging informatics

  • Cancer imaging informatics is conceptualizing cancer image and related scientific data, and applying ’’informatics techniques’’ (derived from disciplines such as applied mathematics, computer science and statistics) to understand and organize the information associated with the data on a large scale.

Slide 23

Image-based Screening

The Well Population, who are at low risk for disease, are diagnosed as normal by screening; if the results are clearly abnormal, the patient may go right to treatment.

If the result is suspicious, diagnostic imaging tests are performed.

The result may be benign, so the person is well, or malignant, in which case the person is treated.