Brisbane

 
Clinic2Cloud - A platform independent graphical user interface for anonymizing and uploading clinical brain scans to an image processing cloud instance
— Steffen Bollmann, Centre For Advanced Imaging, The University of Queensland

   PROBLEM

Current image processing techniques have reached a high level of sophistication and allow the extraction of extensive information from medical imaging data. The problem is that most of these modern post processing techniques are not applied in a clinical setting, because the software developed by scientists is difficult to use, often does not run on operating systems used by clinicians, and requires extensive hardware resources. The integration of new post processing techniques by vendors often takes many years.

 

  SOLUTION

One solution to bring modern image processing into the clinic would be to take the medical data outside of the clinic and utilize a powerful cloud instance where all tools are installed and the clinician can upload the data via a simple graphical user interface. The problem however is that medical data contains sensitive information that cannot be easily removed, such as facial features in magnetic resonance imaging data of the brain. The goal is to create a platform-independent tool that is easy to use, reads standard medical DICOM data, anonymizes the data and uploads the data to a cloud instance to start the image processing in the cloud and sends back results.

 

  CURRENT SOLUTION

Currently no software exists that combines these tasks.

 
 
Prof Naomi Wray

Prof Naomi Wray

PROBLEM

Motor Neuron Disease (MND) is a rare and fatal neurodegenerative disease. Average life expectancy is just 2.5 years after diagnosis but this can range from 1 to 15 years. Symptoms very among patients, but generally include muscle weakness, muscle twitching, and muscle cramping, difficulty with speaking and swallowing, breathing problems, and paralysis. Many patients experience mental health problems.

Despite no available cure, medical advances in care mean that quality of life can be extended through appropriate, individualised multi-disciplinary care. Due to the heterogeneous nature of the disease, timing of access and type of care needed varies from patient to patient.

MND is a neurodegenerative disease and patient’s care is overseen by a specialised neurologist. To improve care, neurologists need to collect individual-level information to personalise relevant allied health care required for each patient. There is a number of reasons a neurologist may fail to collect sufficient information from the patient: patients may not be able to report all relevant symptoms and disease progression to the neurologist during consultation; patients face physical challenges to visit the neurologist; neurologists have time restrictions during consultation hours; patients’ visits to the neurologists are infrequent; the neurologist not being able to structurally record relevant symptoms and disease progression.

Patient care can only be optimal when information about relevant symptoms and disease progression is sufficiently available to the neurologist. Currently, neurologists are lacking relevant information.

 

SOLUTION

We propose an application with a multi-devise interace called ShowMndE. The application is a patient-centered solution to collect data regularly– anywhere, anytime. Use of the application avoids the typical hurdles that impact regular disease tracking (remote locations, impaired patient mobility, hospital visitation cost) but will ensure appropriate support is accessed at the right time.

Our vision is for an application that can be used to track an individual’s disease progression. Patients self-report on a fortnightly basis using validated questionnaires and symptom related questions. The self-report data are scored for various symptoms associated with MND so that any score (or rate of change) can alert the overseeing neurologist and/or help record between clinic visits.

In this manner, the application provides an interface for individual data-analyses and feedback for both the patient and the neurologist. Based on this information, the appropriate healthcare professional can be accessed to ensure quality of life is maximised. Realisation of this novel, precision medicine approach to MND could directly support a reduction of the burden of disease (suffering and premature death) and extend quality of life.

 

CURRENT SOLUTION

Currently there is no other solution than neurologists doing best they can to collect as much relevant information as possible.

banner image courtesy of Dr Nick Hamilton