Give a Scan Mission
Lung Cancer Alliance has developed the Give a Scan
program to empower patients to accelerate the research effort and achieve
better understanding, detection and treatment of lung cancer.
The research effort to better understand, detect, and effectively treat
lung cancer, the leading cause of cancer death, is increasingly relying upon
the acquisition and quantitative interpretation of radiological imaging studies
such as Computed Tomography (CT) and Positron Emission Tomography (PET).
Advancement in this field depends heavily on the analysis and study of image
databases containing large collections of patient data. Although numerous
medical imaging conferences and workshops have made the recommendation to
create a large and freely available image database resource and several
attempts have been made to create one, none have achieved an open collection
with the size and quality needed. A new and more efficient method for creating
an open image database that will rely on patients to donate their medical data to
science is needed.
A large and open imaging database has the potential to accelerate several
important areas of lung cancer research including lung cancer screening,
computer aided detection and diagnosis, and the development of quantitative
methods for drug therapy assessment. All rely heavily on the ability to extract
statistically meaningful insights and observations from real-world clinical
The study of a large collection of data helps researchers
avoid the common pitfall of investing valuable research time and effort on the
study of a biased dataset. A recent review of 60 quantitative imaging papers
covering 20 years of research on MRI bias field correction found that the
median number of datasets used to support claims in publications has risen to
15 . This is far from the numbers of cases needed to make claims on the
diversity of data available in a clinical setting and leaves the conclusions of
many scientific investigations in question.
The field is also in great need of an open image database in
order to objectively compare the performance of developed quantitative methods.
Currently most observations and results are reported on proprietary databases
and, as a result, it is extremely difficult to determine the strengths and
weaknesses of competing methods. A recent article from the Editor-in-Chief of
IEEE Transactions on Image Processing highlighted the critical need for the
field to move more toward reproducible research and the availability of open
datasets . Finally, the utilization of a large and open image database, if
adopted widely, will help build a higher level of scientific consensus and in
so doing help change the clinical standard of care.
Several academic and government projects have attempted to
build such an open imaging resource [3, 4]. However, the patient privacy
requirements and large human labor involved in patient de-identification and
data quality control have resulted in a limited supply of openly available
imaging studies. Many of these obstacles and impediments can be significantly
reduced or avoided if patients and advocacy groups actively support the effort.
Lung cancer patients are eager to help the research effort
and, if provided with the right computational tools, can help reduce costs by
obtaining and preparing their data for donation. The difficulty and additional
cost associated with obtaining approval to use patient data, currently provided
by institutional IRBs with a wide range of policies and procedures, can be
minimized by having patients sign a data donation consent document.
3. Project Overview
The goal of this project is to create a data donation resource that allows
patients to contribute their anonymized imaging records and additional related
information to a public database. Plans for the project are described in
the following sections.
3.1 Data Collection Goals
An advisory board has been established for this project. They will
continuously define the imaging data priorities. For example, the advisory
board may conclude that quantitative therapy assessment for early stage lung
cancers is a database priority. The advisory panel will then set the types of
data requested and the criteria for patient and dataset acceptance.
3.2 Project Management and Patient Mobilization
LCA will utilize its position as a resource for lung cancer patients to
advocate that patients help fight lung cancer through the donation of their
data. Currently, the LCA has assembled a large database of lung cancer patients
and this database will be used to communicate the goals and the status of the
data donation project. In addition, the LCA will support the project with staff
members who will manage the data collection process, with support for patients
who wish to participate, and with recruitment. Particular attention will
be paid to making an efficient data collection process through the use of
automated computational tools and applications.
3.3 Legal and Regulatory Issues
A Washington D.C. law firm has confirmed that patients may request and
obtain their medical data from healthcare providers and donate this data to the
project in accordance with HIPAA regulations. Although patient anonymity is not
required to donate data, de-identification of data will be performed on all
data submitted to the database to minimize any unintended consequences of
providing this information. The law firm has drafted the legal documents
necessary for patients to donate their medical data.
3.4 Central Website
A central web site has been established at www.giveascan.org that provides
information and resources for all individuals involved in the project including
patients, healthcare providers, and public and private scientific
investigators. The goals, motivation, status, and accomplishments of the
project, including the overall size of the database and its main contents, will
be prominently displayed on the front page of the web site so that project
status is well communicated.
3.5 Patient Data Collection & Contribution Tools
When a lung cancer patient registers with the data donation web site they
will first need to agree to a basic set of terms and conditions. The
patient may further be asked to provide basic information on their medical
history, conditions, and imaging studies.
For the initial collection of the data, patients will
request their healthcare providers to prepare a copy on disc of the patient’s
electronic image data (in DICOM format) which the patient will then donate to
LCA in support of the public database. Patients will be asked if they
would also be willing to donate additional data about their diagnosis, stage at
diagnosis, smoking history (if any), familial history of lung cancer and
current status. The patient will be asked to sign the Consent and Authorization
Form. When these are completed, the patient will mail the disc and the forms to
LCA for processing. The LCA will collect the data and the patient forms and
notify patients when the data has been received and processed. When the
de-identified data has been received by the central site it will become part of
the patient record, accessed by the patient code.
Future study of the data collection process will determine
if patients can do some of the data collection and de-identification tasks
using LCA provided software tools installed on their home computers. We will
also explore whether healthcare institutions, such as cancer centers, can be
directly requested to support the project. This will include the request to
recruit more participants and to help establish and use more efficient methods
for patient data submission.
3.6 Data Availability
The data donation web site will contain pages that allow researchers to
download some or all of the data. Search tools will be provided that allow
researchers to explore whether data of interest is available on the database.
Data downloads will mostly be performed over the internet, however. All
download requests will result in a request that all reports, findings, and
publications arising from the use of the donation project data acknowledge both
the project and the data collection name. Users of the site will be required to
consent to an End User Agreement and Disclaimer prior to gaining access to the
When database goals have been met, the lung cancer imaging
research communities will be notified of the availability of new collections.
 Vovk et. Al., A Review of Methods for Correction of
Intensity In homogeneity in MRI, IEEE Transactions on Medical Imaging, Vol. 26,
No. 3, March 2007.
 Kovacevic, From the Editor-In-Chief, IEEE
Transactions on Image Processing, Vol. 15, Issue 12, December 2006.
 Armato SG 3rd, McLennan G, McNitt-Gray MF,
Meyer CR, Yankelevitz D, Aberle DR, Henschke CI, Hoffman EA, Kazerooni EA,
MacMahon H, Reeves AP, Croft BY, Clarke LP; Lung Image Database Consortium
Research Group, Lung image database consortium: developing a resource for the
medical imaging research community. Radiology. 2004 Sep;232(3):739-48.