June 2010
• Volume 2, Number 2
In this issue:
IN MY
OPINION Larger Databases Critical to Quantitative
Imaging By GUDRUN ZAHLMANN,
PhD
ANALYSIS TOOLS AND
TECHNIQUES Phantoms and the Problem
of Quantification in Medical Computed Tomography By ZACHARY H. LEVINE, PhD
FOCUS
ON RSNA 2010 QIBA
Annual Meeting FDA/SNM/RSNA Two-Topic Imaging
Workshop NCI Launches Centers of
Quantitative Imaging Excellence
QI /
BIOMARKERS IN THE LITERATURE PubMed
Search on Image Archives
IN MY OPINION
Larger Databases Critical
to Quantitative Imaging
By
GUDRUN ZAHLMANN, PhD
Understanding clinically important
biological structures and processes through anatomic and molecular imaging and
developing quantitative assessments of the image content requires not only
well-designed clinical imaging tests but also the generation of open image
archive databases.
Image databases or long-term
archives are typically generated through publicly funded projects or as part of
clinical testing in academia and/or device and pharmaceutical industries. Because
substantial effort is required to build and maintain such high-quality, annotated
medical image databases dedicated to a biological or medical condition, each
database is usually no larger than necessary to prove the underlying hypothesis
of the given project.
Agencies such as the National Cancer
Institutes as well as European research programs are creating larger databases
(e.g. RIDER, ADNI, EORTC) to
further develop medical and imaging fields. These open archives permit multiple
research groups and investigators to develop algorithms and achieve evaluation
objectives faster, at lower cost and in parallel. These efforts are valuable in
helping physicians understand the challenges involved with creating and
sustaining image archives. Current agreements on imaging processes and ontologies
need further development and discussion.
The QIBA mission is to improve the
value and practicality of quantitative imaging biomarkers by reducing variability
across devices, patients and time. The quality of newly developed quantitative
imaging methods is directly dependent on the size and diversity of image
databases used for algorithm development and evaluation. Large collections of
radiologic images and associated metadata are needed to reach scientific
consensus and regulatory approval of quantitative approaches.
The RSNA-coordinated Imaging
Biomarker Roundtable has formed the Image Archive Ad Hoc working group, charged
with improving the creation and sustained growth of image archives and developing
typical use cases (for example, algorithm development and evaluation for
quantitative image analysis). Based on these cases, a review of existing
initiatives will be performed using the expertise of roundtable stakeholders who
have defined, implemented and led some of the ongoing imaging database
activities.
We hope this will lead to building
future databases suitable to fit the needs of the defined use cases on a larger
and international scale.
Questions about QIBA participation
can be directed to Joe Koudelik at jkoudelik@rsna.org
Gudrun Zahlmann, PhD,
is Manager of imaging infrastructure at F. Hoffmann - La Roche in Basel,
Switzerland, and serves as co-chair of the QIBA DCE-MRI subcommittee. Dr.
Zahlmann is also co-chair of the Image Archive Ad Hoc working group of the
Imaging Biomarkers Roundtable.
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ANALYSIS TOOLS & TECHNIQUES
Phantoms and the
Problem of Quantification in Medical Computed Tomography
(CT)
By ZACHARY
H. LEVINE, PhD
The quantification of medical CT
faces many barriers, both social and technical. In part the relatively slow
adoption of more quantitative methods is due to the success of the prevailing
image-oriented practice. Indeed, I have heard it argued forcefully that improving
the accuracy of CT would be a waste of time because the natural variability of
the patients exceeds the variation of the machines already. However, in order to
measure small biologic changes in a given patient, we must reduce the inherent CT
scanner variation to less than the biologic change we think is clinically
meaningful.
A compelling case must be made for
change. As a NIST-University of Maryland collaboration recently demonstrated
[1] the volume of
ellipsoids may be measured with volumetric techniques with ten times less
uncertainty than using linear measurements, as are used in the standard RECIST
(Response Evaluation Criteria in Solid Tumors) method. It is a reasonable
extrapolation to suggest that similar results will be found for real tumors.
Detecting smaller changes in volume should lead to faster cancer diagnosis and
tracking of therapeutic response in clinical practice and research.
One barrier to the acceptance of
volumetric techniques is that the amount of data generated with submillimeter
slices is so great that it will probably require a change in the familiar
slice-by-slice analysis by radiologists which dates to the era of
film.
What is a Hounsfield
Unit? On the technical side, one under-appreciated problem is that
the Hounsfield unit (HU) or CT number does not have a precise definition. As
defined by Hounsfield [2],
the CT number is proportional to the absorption of x-rays per unit length with an
offset so that water has a value of 0 HU and air has a value of -1000 HU. The
spectrum of the x-rays is not considered, even though the result is spectrum
dependent. The problem of "beam hardening" is an indication that the exponential
attenuation model is too simple. Furthermore, Compton scattering — which is
about five times more common than photoabsorption for medical x-rays —
gives rise to the possibility of scattering into a nearby detector or even
scattering back in to the primary beam. Such behavior is also at variance with
the model of exponential attenuation assumed in the definition of the Hounsfield
unit. The arrival of dual energy scanners (which makes the absorption spectrum
variable) and continuing increase in parallelism (which makes the system more
sensitive to scattering) may bring these issues to the fore. Already, some of the
difficulties of understanding small measured variations in CT numbers are
associated with the ambiguities in the definition.
The problem of understanding the
Hounsfield unit is compounded by the fact that most reconstruction kernels do not
have publicly available mathematical definitions. Hence, the CT system is a black
box that is difficult to probe.
Phantoms offer a powerful tool for
probing CT systems. Phantoms are presently used to calibrate CT systems,
typically on a daily basis, although also through multi-year accreditation. The
phantom-calibration system works well enough for image-oriented analysis,
although the variations between manufacturers, models, upgrades, and local
machine settings and practices make longitudinal studies and transfers of
patients from machine to machine problematical, and the variations are not well
quantified. For example, one specific issue is the difficulty of supplying a
single, resolution-independent cut-off value to describe emphysema. Scanning a
carefully crafted phantom on a per-patient basis permit corrections of reported
CT numbers and allow uncertainties to be assigned, assess the interaction of
spatial position and CT number, and indicate the length scale of the smearing
introduced by the measurement and reconstruction process. A phantom combined with
a suitably packaged analysis algorithm could extend the usefulness of our already
impressive CT machines.
Reference: [1] RECIST vs. Volume
Measurement in Medical CT Using Ellipsoids of Known Size. Optics
Express 2010; 18(8):1851-1859. Levine, ZH, Borchardt, BR, Brandenburg,
NJ, et al.
[2] Nobel Award address.
Computed Medical Imaging. Medical Physics. 1980 July/August;
7(4):283-290. Hounsfield, GN.
Zachary H.
Levine, PhD, is a physicist at the National Institute of Standards and Technology
(NIST) and a member of the QIBA COPD/Asthma Committee. His interest in medical
tomography followed several years of study of microtomography of integrated
circuit interconnects. His other research interests involve computation of the
properties of light in solids.
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FOCUS ON
RSNA 2010:
Quantitative Imaging/Imaging Biomarkers and QIBA Meetings and
Activities
MARK YOUR
CALENDAR Quantitative Imaging/Imaging
Biomarkers Focus Session: Imaging Biomarkers for Clinical Care and
Research • Monday, November
29, 4:30 PM–6:00 PM
QIBA Quantitative Committees
Working Meeting • Wednesday, December
1, 3:30 PM–5:30 PM
The Quantitative Imaging
Reading Room Following the success of the RSNA 2009
Toward Quantitative Imaging: Reading Room of the Future, RSNA 2010 will
feature The Quantitative Imaging Reading Room. The educational showcase
will provide visual and experiential exposure to quantitative imaging and
biomarkers through exhibitor products that integrate quantitative analysis into
the image interpretation process. Participants can learn through hands-on
exhibits featuring informational posters, computer-based demonstrations and Meet
the Expert presentations scheduled throughout the week.
QIBA Annual
Meeting, May 25-26, 2010 From its beginning in May 2008, QIBA's
work has focused on its mission to improve the value and practicality of
quantitative imaging biomarkers by reducing variability across devices, patients
and time. Simply put, the emphasis is on building "measuring devices" rather than
"imaging devices". Attendees of QIBA's May 2010 annual working meeting included
stakeholders from the clinical community, imaging equipment manufacturers, the
pharmaceutical industry, government and medical informatics companies, imaging
societies and RSNA leadership. In the past year, QIBA has moved towards contacts
and interactions in the regulatory arena, including the biomarker qualification
pipeline. Dr Goodsaid, the FDA speaker, provided attendees with an overview of
the principles and process of biomarker qualification at the FDA. The two newest
QIBA committees, COPD/Asthma and fMRI, joined the Quantitative CT, MRI and
FDG-PET Committees in discussions and breakout sessions.
FDA/SNM/RSNA
Presentations Available Online More than 40
presentations were given by stakeholders at the FDA/SNM/RSNA "Two-Topic
Imaging Workshop" held in April in Bethesda, MD. The workshop focused on
standards for imaging endpoints in clinical trials and manufacturing of PET
radiopharmaceutical products.
The presentation by RSNA Scientific
Advisor Daniel Sullivan, M.D., on
"Integrating the Imaging Biomarker Enterprise: A Roadmap Proposal Developed by
Stakeholders," explores the premises and challenges of quantitative imaging
along with an overview of RSNA efforts including QIBA.
NCI Launches
Centers of Quantitative Imaging Excellence Program The National Cancer Institute (NCI) has
launched a new program to qualify existing NCI-designated Cancer Centers with an
added attribute as Centers of
Quantitative Imaging Excellence. This program will significantly decrease
potential variability in image procedures performed on patients during
NCI-sponsored clinical trials. Advanced imaging plays a pivotal role in cancer
care by providing the ability to detect tumors early and to guide therapy as well
as subsequent disease monitoring and surveillance. The American College of
Radiology (ACR) Imaging Network (ACRIN) and ACR will coordinate the program for
NCI.
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QI/IMAGING BIOMARKERS IN THE
LITERATURE
PubMed Search on Image
Archives
Each issue of QIBA
Quarterly features a link to a dynamic search in PubMed, the National
Library of Medicine's interface to its MEDLINE database.
Click here to view a PubMed search on image archives.
Take advantage of the My NCBI
feature of PubMed which allows you to save searches and results and includes an
option to automatically update and e-mail search results from your saved
searches.
My NCBI includes additional features for highlighting search terms, storing
an e-mail address, filtering search results and setting LinkOut, a document
delivery service.
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