Disease-Matching Software Could Help Determine Optimal Treatment

Software tools being developed within the European Health-e-Child project (HeC) can compare a vast range of structured and unstructured data, including genetic and clinical data.

The CaseReasoner tool enables clinicians to search thousands of disease diagnoses, treatments, and outcomes to find a child similar to their own patients. The clinicians set the search parameters themselves, and the results can be displayed as a "network” with cohorts of patients with similar diagnoses clustered together and color-graded accorded to the level of similarity. Clinicians can then examine the detailed data on any of the patients or clusters to better understand their diagnoses, and the success of the procedures.

The AITION tool developed in cooperation with researchers at the department of informatics at the University of Athens (Greece) uses semantic tools to search medical literature and interviews with clinicians as well as patient data. Drawing on well-established causal-probability algorithms, the tool generates graph-based "knowledge models” that doctors can interactively explore to answer diagnostic and predictive questions, suggesting probable disease development. Doctors using AITION will then be able to test their hypotheses on optimal treatment.

For unstructured data such as images, the HeC project has created tools that translate visual information into machine-readable (and therefore machine-comparable) language. The project's three-dimensional (3D) registration tool for magnetic resonance imaging (MRI) scans, and its MRI "erosion scoring” system for juvenile idiopathic arthritis have been recognized as important advances in their fields.

The Health-e-Child project aims at developing an integrated healthcare platform for European pediatrics, providing seamless integration of traditional and emerging sources of biomedical information. The long-term goal of the project is to provide uninhibited access to universal biomedical knowledge repositories for personalized and preventive healthcare, large-scale information-based biomedical research and training, and informed policy making. Currently, HeC researchers are working on tools for three complex pediatric diseases with at least partly unknown causes: heart diseases resulting from an overload of the right ventricle, juvenile idiopathic arthritis, and brain tumors (gliomas).

"The lack of research into childhood disease adds to the significance of Health-e-Child,” said Jörg Freund, Ph.D., the HEC project coordinator from Siemens Healthcare (Erlangen, Germany). "Because the numbers of children suffering from these diseases are small, there is little incentive for commercial companies to research them. Some pharmaceutical companies calculate drug doses for children simply on weight -- treating the child as a mini-adult. This fails to take account of important differences between children and adults. The most obvious difference is that children are growing.”

Eventually, the Health-e-Child project intends to build a grid-enabled European network of leading clinical centers that will share and annotate biomedical data, validate systems clinically, and diffuse clinical excellence across Europe by setting up new technologies, clinical workflows, and standards.

Related Links:
European Health-e-Child project
University of Athens
Siemens Healthcare