Tissue Iron Quantification in the Heart and Liver

Description:

Proposal to build a centralised framework for automated T2* mapping in the heart and liver using cloud computing techniques.

Background

Reliable tissue iron quantification is essential for preventing death and for managing chelation therapy in patients with thalassemia, sickle cell disease, plastic anaemia, myelodysplasia, and other transfusion-dependant anaemias. Cardiovascular magnetic resonance T2* has made a great impact on patient survival but there is a great need for improved access to this life-saving technique, especially in the developing world. To this end, analysis software needs to be simple, accurate, preferably automated, and ideally web-based to ensure reliable measurements and easy access. Researchers at St George’s, University of London propose to build a centralised framework based on start-of-the-art cloud computing techniques to provide accurate and standardised T2* mapping for improved healthcare outcomes.

Technology Overview

Current key points of validation achieved to date:

(1) Developed a noise correction model which proves to be accurate and reproducible in liver T2* measurement.

(2) Developed a novel filtering algorithm.

(3) Developed a semi-automatic algorithm for liver iron quantification.

(4) Developed a fully automated technique for cardiac iron assessment with good results.

(5) Calibrated the T2* technique on liver biopsy and post-mortem hearts.

(6) Established cloud computing in health care.

Benefits

The researchers have developed novel data processing methods for T2* mapping of the heart and liver which are accurate, sensitive, time-efficient, automated, easy to use, and clinically calibrated against biopsy liver and post-mortem heart. In addition, they have established cloud computing techniques in bioinformatics and health care. Based on these developments, they propose to build a centralised framework for automated T2* mapping in the heart and liver using cloud computing techniques. The logic in the proposal is straightforward as there is a clinical need to standardise the analysis procedure. The introduction of an automated technique will enable reliable and confident measurement of T2* even at inexperienced centres. The novel algorithm will enable a far more accurate gauge of T2*. The centralised system can streamline clinical workflow with the additional advantage of decreased user interaction. The system can help build a widely accepted protocol for clinicians worldwide.

Applications

The product will be a plain in-browser cloud platform, supporting centralised image storage, secure access from multiple devices, remote data viewing and inter‑stakeholder collaborations. It can be used by clinicians and academic researchers to stream workflow and standardise data analysis, or by pharmaceutical companies for maximising output of clinical trials. This strategy is working in partnership with leading academics and clinical specialists to ensure better outcomes for patients and sustainable support to the society. The researchers will build strategy on public engagement to increase risk awareness of the disease and achieve maximum impact of the product.

Opportunity

St George’s, University of London are looking for development partners to validate technical issues, and build their understanding of what customers really want and how this demand could be better met. They wish to find the right value proposition and construct a viable model with global reach. With a risk‑tolerant partner, the university is well placed to attract follow‑on investment with a practical plan for further clinical development for regulatory approval. The university will initiate a multi‑centre clinical trial to obtain CE marking and MHRA approval.