• Volume 2, Number 1
In this issue:
Quantitative Imaging is Critical Part of COPD Diagnosis,
By PHILLIP F.
ANALYSIS TOOLS AND
Merging CAD and
May 2010 QIBA
BIOMARKERS IN THE LITERATURE
Search on Quantitative Imaging in COPD and Asthma
QIBA in the Literature
IN MY OPINION
Quantitative Imaging is
Critical Part of COPD Diagnosis, Treatment Evaluation
PHILIP F. JUDY, PhD
Through its work characterizing
scanner inconsistencies, QIBA can play an important role in the quantitative
evaluation of COPD using CT.
CT is considered useful in the
diagnosis and evaluation of the treatment of chronic obstructive pulmonary
disease (COPD), which is characterized by chronic inflammation and destruction of
the airways and lung parenchyma. Quantitative changes in airway size and wall
thicknesses and density of lung parenchyma measured by CT are considered primary
Although this narrative has existed
for 20 years, the potential of quantitative CT evaluation of COPD has not been
fully realizedâ€”especially in the clinicâ€”due
to a lack of consistency. There is a premium on consistency (long-term precision
and limited variations from scanner to scanner) because the progression of COPD
is very slow.
Despite efforts to match tube
potential, radiation dose, slice thickness, and reconstruction kernel across
scanners, clinical studies have demonstrated systematic differences between
scanners. Fortunately, specific CT scanners with standard calibrations and
quality assurance are stable and scanner inconsistencies can be statistically
modeled in studies involving a sufficient number of cases per scanner. However,
standard calibration procedures are not sufficient to deal with inconsistencies
in CT emphysema biomarkers. These scanner inconsistencies reduce the power of
multi-institutional studies. More cases are required to achieve the required
statistical power, increasing the cost of studies.
There is a tendency to deal with
scanner inconsistency by specifying that the same scanner be used for COPD drug
treatment clinical trials that follow up CT evaluation of cases. However,
specifying the same scanner for each case becomes impractical for large clinical
trials lasting several years. Statistical modeling corrections are not available
for a clinical exam; the number of cases in such a study is one.
Evaluation of COPD is further
complicated because the preferred emphysema CT
biomarkersâ€”percentage of lung pixels less than -950 and the
15th percentileâ€”are histogram biomarkers. These biomarkers are
lung density quantities that are intuitively and empirically related to
histological quantitative measures. As CT biomarkers of bulk density (the central
tendency of lung CT values), these preferred biomarkers are biased by image
noise. Airway size measurements require super resolution techniques. While
solutions for improving consistency are straightforward, they are demanding and
costly. However, the savings for clinical trials in reducing the number of cases
may lead to net savings for sponsors of clinical trials.
QIBA can aid in overcoming these obstacles by developing a calibration procedure
to deal with scanner inconsistencies in CT emphysema biomarkers. I believe that a
reference standard, or phantom, using a material with the attenuation and spatial
characteristics of the lung parenchyma needs to be developed. Calibration
procedures using the improved reference standard will be incorporated in the
Profile being developed by QIBA's COPD/Asthma Committee. Ultimately, we will need
to demonstrate that these reference standard "biomarkers" track the differences
caused by variations in scanners and protocols.
Because the preferred CT emphysema
biomarkers are biased by image noise, the relationship between standard image
quality metrics (spatial resolution, image noise, and CT number scale) and CT
emphysema biomarkers must be carefully described in the QIBA Profiles.
QIBA members face interesting,
challenging work in creating the QIBA Profiles for COPD and asthma.
Philip F. Judy, PhD,
is an associate professor of radiology at Harvard Medical School and director of
the Physics and Engineering Division, Department of Radiology, Brigham and
Women's Hospital in Boston. Dr Judy is a co-chair of the QIBA COPD/Asthma
Committee and a member of the Physics Committee of the National Lung Screening
ANALYSIS TOOLS & TECHNIQUES
Merging CAD and
MARYELLEN L. GIGER, PhD
In 2009, the RSNA Toward
Quantitative Imaging (TQI) Ad Hoc Committee developed a working definition of
quantitative imaging: "Quantitative imaging is the extraction of quantifiable
features from medical images for the assessment of normal, or severity, degree of
change or status of a disease, injury or chronic condition relative to
Such image-derived metrics may
involve the extraction of lesions from normal anatomical background and the
subsequent analysis of the extracted region over time (or another parameter) in
order to yield a quantitative measure of some anatomical or physiologic
Computational methods that will
benefit these analyses are being developed by researchers in quantitative
imaging, computer-aided detection (CADe) and computer-aided diagnosis (CADx)
fields. Many times investigators in these areas of research may not be aware of
each others' developments.
Computer-aided Detection and
CAD can be defined as a diagnosis made by a radiologist
using a computer algorithm's outputâ€”obtained from an automated
analysis of medical imagesâ€”in the interpretation of image
data. With CAD, the radiologist makes the final diagnostic decision using the
computer output as an aid. Currently, computer-aided detection (CADe), a
localization task, provides a "second opinion" for the radiologist in locating
suspicious regions within images, as in screening mammography, leaving diagnosis
and patient management to the radiologist. However, the development of CAD
methods is expanding beyond screening programs to include applications in
diagnosis, risk assessment, and response to therapy. Computer-aided
diagnosis (CADx) involves the characterization of a suspicious region or
lesion, such that the computer output characterizes each suspicious region or
lesion quantitatively and/or estimates its probability of disease (for example,
malignancy), leaving patient management to the clinician.
For example, in breast cancer
imaging, investigators are developing computer methods that automatically segment
lesions from the background, extract mathematical descriptors of lesion
characteristics, and merge these features into a "malignancy score." It is
important to note that these classifier outputs are based on the knowledge of
diseased and non-diseased cases from a large database obtained from some
population, which is used to train the classifier.
With a sufficiently large database
that spans the population, it is expected that the output will yield a relative
measure that is related to the likelihood of disease. Note that this differs from
image-based metrics in quantitative imaging in which, for example, the image
voxel value, after some specific corrections and standardizations, may be
directly related to some underlying biological phenomenon.
Segmentation and feature extraction
techniques from CAD may benefit quantitative imaging by delineating the lesion
more objectively, by merging multiple quantitative values for a composite
biomarker, or by yielding a relative value (for example, relative to a known
population with similar lesion characteristics and/or response) that might be
more robust that absolute measures of the underlying biology.
Computerized image analyses of the
types used in CAD combined with quantitative imaging techniques are likely to
yield improved methods of diagnosis and triaging for treatment.
Giger, Ph.D. is a professor of radiology and chair of the Committee on Medical
Physics at the University of Chicago. She is vice-chair of radiology for basic
science research and director of the graduate programs in medical physics at the
University. A pioneer in the development of CAD, Dr. Giger is a member of the
RSNA's Imaging Biomarkers Roundtable Advisory Group and Toward Quantitative
Imaging Planning Group.
April 13-14, 2010
Natcher Auditorium on the National Institutes of Health campus, Bethesda,
Registration is open for a two-day
FDA/SNM/RSNA scientific workshop, "Two Topic Imaging Workshop: Day One -
Standards for Imaging Endpoints in Clinical Trials, Day Two - Manufacturing of
Positron Emission Tomography (PET) Radiopharmaceutical Products" to be held at
Natcher Auditorium on the National Institutes of Health campus in Bethesda, MD.
Free online registration and other information on the workshop is available
The 2007 Prescription Drug User Fee
Act (PDUFA) IV called for the development of a guidance document to address
Imaging Standards for Use as an End Point in Clinical Trials. As a step
toward meeting the requirement under PDUFA, and its overall public health mission
of working with stakeholders to facilitate the development of safe and effective
medical products, FDA is stimulating discussion with stakeholder in the imaging
community on key issues of standardization and optimization of imaging techniques
and practices in clinical trials and drug development.
The workshop is expected to generate
discussion and establish consensus on issues associated with using imaging to
assess endpoints in clinical trials.
The first day of the workshop will
focus on general issues of standardization to control variability and
inconsistency in acquisition, interpretation, and analysis of images in clinical
The second day will focus on the
regulatory framework for PET drugs, including the recently issued 21 CFR Part 212
regulations establishing the Current Good Manufacturing Practice (cGMP) for PET
drugs, investigational new drugs applications (INDs), and new drug applications
(NDAs) for PET drug products.
QIBA Third Annual Working
Hyatt Regency O'Hare, Rosemont, IL
QIBA was established late in 2007
with representation from pharmaceutical companies, imaging equipment
manufacturers, imaging informatics companies, government agencies, imaging
societies, RSNA leadership and clinical trialists. QIBA held working meetings in
May 2008 and 2009.
This year's meeting will provide an
opportunity for QIBA Quantitative PET, CT, MRI, fMRI and COPD/Asthma committees
to report on the past year's progress and meet face-to-face to plan next steps
and future activities.
Specifically, committees will define
groundwork activities they plan to accomplish in the coming year (such as data
collection from reference objects), identify Profile details they plan to work
on, and determine how their activities align with emerging clarifications of FDA
regulatory guidances and pathways.
Through its committee work, QIBA is
engaged in understanding and reducing errors so that quantitative results are
accurate and reproducible across patients, timepoints, sites, and imaging
devices/software from vendors.
Summaries of the May 2009 and other
QIBA meetings are posted on the QIBA Web site. Ongoing
committee work is posted on the QIBA
QIBA always welcomes new committee
participants. Contact QIBA@rsna.org for more
Testimony from February 24
House Committee on Science and Technology's Subcommittee on Technology and
Dr. Daniel C. Sullivan was one of the witnesses who testified before the House
Committee on Science and Technology's Subcommittee on Technology and Innovation
on February 24, 2010. Testimony from the hearing
"How Can NIST Better Serve the Needs of the Biomedical Research Community in the
21st Century?" addressed ways the National Institute of Standards and
Technology (NIST) could assist manufacturers, patients, academicians and
regulators by supporting the development of reference objects, procedures and
measurement standards for assessing the performance of biologics, drugs, and
diagnostic tests and devices.
QI/IMAGING BIOMARKERS IN THE
PubMed Search on
Quantitative Imaging in COPD and Asthma
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 quantitative imaging in COPD and
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
My NCBI includes additional features for highlighting search terms, storing
an e-mail address, filtering search results and setting LinkOut, a document
QIBA in the
QIBA's efforts and accomplishments
are the subject of a growing list of journal articles which is posted on the
As of March 2010, the list
Diagnosis: Quality and Standards: Making Bioimaging "Measure Up". Reiss, SM.
BioOptics World. 2010 Jan 1.
The Use of Volumetric CT as an
Imaging Biomarker in Lung Cancer. Buckler AJ, Mulshine JL, Gottlieb R, Zhao B,
Mozley PD, Schwartz L. Acad Radiol. 2010 Jan; 17(1):100-6.
Volumetric CT in Lung Cancer: An
Example for the Qualification of Imaging as a Biomarker. Buckler AJ, Mozley PD,
Schwartz L, Petrick N, McNitt-Gray M, Fenimore C, O'Donnell K, Hayes W, Kim HJ,
Clarke L, Sullivan D. Acad Radiol. 2010 Jan; 17(1):107-15.
Volume CT for Diagnosis of Nodules
Found in Lung-Cancer Screening. Mulshine JL, Jablons DM. N Engl J Med.
2009 Dec 3; 361(23):2281-2.
Quantitative Imaging Biomarkers
Alliance FDG-PET/CT Working Group report. Frank R; FDG-PET/CT Working Group.
Mol Imaging Biol. 2008 Nov-Dec; 10(6):305.
Please contact QIBA@rsna.org with additions to the list.