HOW IT SUPPORTS RADIOLOGY: How to learn with PACS Introduction

HOW IT SUPPORTS RADIOLOGY:
How to learn with PACS
Introduction
The term “eLearning” includes all forms of learning, where
digital media or communication tools are involved in the
presentation, distribution or communication of learning
content.
Afterwards the DICOMS are sent to the preferred eLearning
application where annotations can be added to key-images
and meta-information (e.g. report, anamnesis, problem,
media,…) can be added to the case.
Didactic basics of eLearning
Learning and examinations
• One may learn by lectures,
by self directed learning or combined
• Self directed learning is up to 4 times
more efficient than listening to a lecture
• Lectures of dedicated clinical experts can stimulate
learning and the combination with self directed learning
proved to be a useful setting (Blended Learning)
• The daily routine in clinical radiology is
the backbone of learning professional radiology
ePACS as a project developed by the Medical University
Vienna in close collaboration with the ESR is an
innovative eLearning tool based on case presentation in
a real-life environment. As a key feature ePACS offers
case collections to various radiological sub-specialties
combined with structured reporting schemes to benefit
from an expert’s approach to the topic.
How do Radiologists learn?
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„Learning-by-doing“ during daily routine
Ward rounds
Discussions among radiologists
Residency training
Systematic reading (books, journals,…)
Meetings: Lectures and self-directed learning
Hard-copy case-collections
ELearning case-collections (Internet, CD,…)
Collaborative eLearning
Basic eLearning features which may be offered
by a standard PACS
• Case collections which can be structured by:
- Difficulty /target group
- Modality
- Scientific work and experimental work/routine cases
- Diagnosis (pattern recognition)
• Interchangeability of cases (e.g. via DICOM nodes)
between distant clinics for
- eLearning/science portals
- Post-graduate training and continuing education
- Student training
- Specialist training
Additional features required for dedicated
eLearning
For an excellent eLearning strategy many different tools
are available, providing useful features which are essential
for integration of teaching files into PACS.
The first step must always be anonymization, which can
already take place in the PACS.
Next the case enters a classification state, in which it is
classified by certain criteria. This can be done for example
with the TCE Selector to which the DICOM Data can be
sent directly from the PACS.
TCE Selector provides vendor independent integration
of PACS and teaching files according to IHE TCE. It
implements RadLex as established categorization system
for efficient keyword based retrieval.
Using IHE related tools, such as TCE, promises
interoperability for sharing cases with other institutions.
Cases offered in an eLearning system such as ePACS and
MIRC are often complex, feature multiple examination
techniques, and frequently show incidental findings. Often
the focus lies on presenting extraordinary cases with
multiple, sometimes very extensive studies. Also follow-ups
are often presented to show the progress within a patient.
Since 2011, a new initiative incented by the ESR is the
European Diploma in Radiology (EDiR) featuring face-to-face
oral exams with dedicated expert-examiners as a vital part.
Here one tries to stay on a daily-routine layout, meaning
that there will be enough pictures and series to show the
pathology, but one tries to keep the extent of images to
a minimum and so close to a clinical standard situation,
where time often is a limiting factor. This fact also
guarantees fast image handling and helps to set the
difficulty right for the candidates.
eLearning References:
http://www.elearningeuropa.info
http://mediendidaktik.uni-duisburg-essen.de/sites/medida/files/
kerres-tu-darmstadt_0.pdf
http://cde.athabascau.ca/online_book/pdf/TPOL_book.pdf
http://www.uni-mainz.de/FB/Medizin/Radiologie/agit/berichte/
dicom2008/vortrag/eLearning_in_Radiology_Grunewald.pdf
Prepared by Peter Pokieser, Ricarda Hofmeister, Alexander Hirsch, Thomas
Moritz, Wolfgang Wiecenec, Martin Tiani, Jürgen Brandstätter, Vienna, Austria