1. Jamie Wright, Alice Nicol, Ravi Jampana
An Android™ app for multi-modality image manipulation during epilepsy MDT meetings
Jamie Wright, Alice Nicol, Ravi Jampana
Nuclear Medicine Department and Institute of Neurological Sciences
Southern General Hospital, NHS Greater Glasgow and Clyde
Introduction
Patients with refractory epilepsy being considered for surgery often have a gamut of imaging examinations as part of their care pathway. These examinations are presented at multi-disciplinary team (MDT) meetings for surgical planning. The facilities at MDT meetings can present a challenge to the reporter as access to a workstation with necessary DICOM image retrieval, manipulation and viewing software is not always guaranteed.
Portable tablet computing hardware has advanced rapidly over the previous years making it now feasible to run responsive real-time multi-modality medical image manipulation software remotely. To this end we have developed an application for Android devices, “epapp", with the intention of making it easier to share the results of imaging data amongst clinical colleagues.
Results
The current status of epapp is as follows. Multi-planar reconstruction of single frame per slice DICOM datasets is fully implemented with image manipulation functionality (scrolling, zoom, panning, rotation) performed with multi-touch gestures. A partial Dropbox client has been implemented allowing for direct download, opening and viewing of zipped DICOM directories. Image fusion of registered datasets with multilevel alpha blending using slider control has also been implemented.
Work is currently ongoing on the development of epapp, with a more robust Dropbox client, loading of multi-frame DICOM datasets and better manipulation of fused datasets being current priorities.
Screenshots of the app showing the multi-planar reconstruction of a T1 weighted MRI scan, image fusion of PET-CT datasets and surface rendered images of publically available MRI and CT datasets. These are included with the app as sample datasets to demonstrate usage.
Method
The Android platform was chosen as a testing and development target as the authors had experience of this system.
An initial search was made to look for possible solutions already in production. This revealed a lack of usable, free options in existence with no support for multi-modality fusion or multi-planar reconstruction found.
An initial set of requirements was drawn up including loading and display of DICOM datasets, viewing of images in the three medical planes, integration of fusion capabilities for pre-registered images and networking support to allow download of data as required.
Software libraries were identified to implement the necessary data visualisation and networking requirements. These were then integrated into an application for use.
The Visualisation Toolkit was chosen as the base library for data visualisation and a Dropbox client implementation was created for image retrieval.
Programming was done in Java and C++ with language integration achieved through the Java Native Interface (JNI).
The software library stack upon which epapp is built. All components are industry standard with mature and thoroughly tested framework components.
Conclusion
An Android application has been created to aid clinicians during epilepsy MDT meetings. Volumetric data is visualised with multi-planar reconstruction and multi-modality fusion of registered images has been implemented. Data can be loaded onto a linked Dropbox account and downloaded through the application. It is hoped that trialling of the app as an adjunct during MDT meetings will begin in the near future.
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