The Diseases Database software to improve radiologists'
diagnostic ability using game like system
Poster No.:
C-1770
Congress:
ECR 2017
Type:
Educational Exhibit
Authors:
K. Matsunaga , K. Majima ; Aizuwakamatsu City/JP,
1
2 1
2
aizuwakamatu/JP
Keywords:
Radiographers, PACS, Education, Efficacy studies, eLearning,
Image registration
DOI:
10.1594/ecr2017/C-1770
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Learning objectives
We created software to help train radiologists. This self-education software promotes
efficiency and productivity during training. We will explain the features and merits of this
software compared with those of other teaching and learning methods in radiology.#
Background
Many journal articles, textbooks, websites, and case-based radiology educational
programs are available to help radiologists improve their knowledge and diagnostic
abilities. [1,2] Self-directed learning tools are much more popular than textbooks and
journal articles. [3] However, individual users are not completely satisfied with most
websites, as they usually do not meet their needs, and case-based radiology educational
programs often lack well-balanced disease information. [4] Moreover, these sources often
lack the provision of step-by-step radiological training and systematic teaching methods
tend to be boring. In this context, radiologists must be innovative and adopt new teaching
and learning approaches, as modern learners have become accustomed to fun, gamelike, interactive, and engaging materials. [5,6]
Findings and procedure details
We incorporated gaming features into our software to maintain an interest in studying. Of
course, our educational software also provides a systematic understanding of diseases.
The game is run through an avatar, which must collect data on many diseases to go to
the next learning level. The software provides almost 2,000 boxes, each for a particular
disease, that must be filled, which makes the homepage appear like a collection of cards.
These 2,000 diseases are divided into several fields like central nerve, head and neck,
chest, breast, etc. The most basic use of our software involves filling in the disease
images from the PACS viewer into the disease boxes during the interpretation work.
Disease images can also be added from websites or journal articles. The content (e.g.,
image features, clinical findings, pathological findings, and differential diagnoses) must
be compiled by the radiologist in training.
The homepage initially shows a few boxes for common diseases. As the user fills the
disease images and content into the boxes, the avatar gains experience. As a result,
the number of available boxes increases, which is followed by a gradual increase in the
number of rare diseases.
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The main disease screen consists of five screen tags: disease details, patient lists,
image scraps, related files, and questions. The user can switch the screen by clicking
on different tags. The basic screen tag called 'disease details' contains the basic
disease information tags (image features, clinical findings, pathological findings, and the
differential diagnosis).
The 'patient lists' screen stores the DICOM image data. The 'image scraps' screen lists
pictures and notes. Those images can be taken from any image data source derived from
a PACS viewer, website, or journal article. The 'related files' screen can store many kinds
of files, such as PDF, Word, and Excel files. The 'questions' screen lists questions about
the disease to aid understanding.
The 'disease details' screen has a textbook mode, which opens to arrange all information
tags and image scraps as if it were a textbook. The screen can also be printed out as
a PDF file. Thus, a textbook can be made by sending these data to an internet book
printing service.
A status screen is also present, which shows the avatar's level, disease box filling rate,
and position compared with those of other avatars. In addition, each field has its own
character and their appearance changes according to their filling rate.
PC and iPad versions of the software are available and are connected, so the disease
boxes filled in a PC version would be reflected in the iPad version, so the content can
be studied outside the hospital.
Images for this section:
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Fig. 1: The avatar making screen
© - Aizuwakamatsu City/JP
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Fig. 2: Our software's homepage
© - Aizuwakamatsu City/JP
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Fig. 3: The basic usage of our software
© - Aizuwakamatsu City/JP
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Fig. 4: The basic screen called 'disease details' has additional screens.
© - Aizuwakamatsu City/JP
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Fig. 5: The status screen and field characters
© - Aizuwakamatsu City/JP
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Fig. 6: The textbook mode and iPad version
© - Aizuwakamatsu City/JP
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Conclusion
Our software differs from case-based radiology education in two ways. First, unlike casebased education, which usually has no limits regarding the number of elements, our
software has almost 2,000 disease boxes, so long-term goals can be set which maintains
our interest. Second, the distribution, difficulty, and frequency of diseases are always
unbalanced in case-based education. However, our software includes a gaming system
that balances training. Only a few boxes for common diseases are found initially on the
homepage. As the number of filled boxes increases, the number of uncommon diseases
increases along with the total number of disease boxes. That is, common diseases are
studied first, and more difficult and rare diseases are gradually presented. Starting with
rare and difficult diseases would decrease motivation. Therefore, our system maintains
interest and provides well-organized training.
In addition, looking at the filled disease boxes every day will help with filling in the correct
diseases the next day, which aids understanding. Furthermore, the quality of the box
content is evaluated objectively, so it can be improved.
The status screen provides the user's current situation in relation to other people's
avatars. Younger radiologists can change an unknown field into a more well-known field
by filling in the field boxes, to balance their knowledge of diseases. The software allows
older radiologists to focus on their own field intensively.
Our software has many other advantages. The 'image scraps' screen can be used
to align the images according to the sequence to aid understanding of the disease
spectrum. For example, these diseases usually exhibit high intensity on a diffusionweighted image (DWI) or a T2-weighted image (T2WI), are sometimes mass forming, or
are well enhanced, among other features.
The disease boxes are a storage space to enable easier access to reference data,
and they number almost 2000. Putting data into a box itself ensures a well-organized
database.
Other merits include an intuitive understanding of a disease's frequency and distribution.
If the user derives data only from the PACS viewer, the deviation from the norm of the
diseases at the user's institution will lead to imbalanced training. Nonetheless, substantial
information is available from the patients at the user's own institution, such as physical
and laboratory findings and clinical courses, enabling a better understanding of diseases.
Furthermore, whole images can be accessed.
In addition, this self-educational software will reduce teaching time for younger
radiologists. In some cases, radiologists may have difficulty teaching younger radiologists
due to the generation gap and differences in social, environmental, and technological
influences. [6] In such cases, our software may facilitate learning by younger radiologists.
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An active learning process should be promoted and older radiologists should act as
guides. If this approach is not adopted, older and younger radiologists might have
difficulty communicating. Against this background, our software provides a common topic
that facilitates conversation about diseases. In the future, we will use our software to
connect with other institutions and compete in the quality of data we collect on diseases.
That also increases our motivation to study.
In conclusion, our software has many unique merits compared to other training methods
and helps us acquire our knowledge with interest.
Personal information
kenichi matsunaga, M.D.,
aizuwakamatu, japan
Ph.D.,
department
of
radiology,
takeda
hospital,
[email protected]
kazuhiro majima, M.D., Ph.D., department of radiology, takeda hospital, aizuwakamatu,
japan
[email protected]
References
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