Beatriz Dominguez Gonzalez December 13, 2019

Non-invasive, accurate and personalized prognosis methods may be making their way into the medical world faster than we think.

This is recently seen by a study done by researchers at the University of Milan for a novel 3D methodology that assess the clinical scenarios after complex heart disease surgery. Their research won the 2019 Mimics Innovation Award for using the 3D visualization software to predict how an individual patient’s heart will react to a stent — a common treatment method if the patient suffers from complications following the repair of complex congenital heart disease. The advantages show that 3D personalized modeling could be a step closer to avoiding peri-procedural risks, and therefore improving patient prognosis.


Congenital heart disease affects 1% of babies around the world

In the United States alone, 40,000 patients are born with congenital heart disease. Of those, 20% suffer from a complication called right ventricular outflow tract (RVOT) dysfunction. A heart valve replacement known as a homograft conduit implantation is the most common surgical treatment to alleviate this condition. Unfortunately, long-term post-operative RVOT dysfunctions are common.

The most common solutions today are to use metal pre-stenting of the conduit and percutaneous pulmonary valve implantation. However, these surgical methods also lead to complications that are often life-threatening. There are a number of factors that increase the risk for adverse events, such as the morphology of the RVOT, the anatomy of each patient, and the mechanical interplay with the metal stent.


Mimics Innovation Suite for 3D personalized finite element modeling

Alessandro Caimi and his colleagues at the University of Milan saw the need for new treatments to increase the life-span of the conduit and saw the potential of using finite element (FE) modeling. They were able to investigate the prediction power of personalized FE models to assess stenting feasibility and clinical risks.

In their research, they used the Materialise Mimics Innovation Suite's segmentation algorithms for the personalized 3D heart reconstruction from CT images and posterior triangulated surface mesh generation. The Mimics Innovation Suite was crucial for the success of his research project due to the high quality and speed of the results, which are decisive when analyzing complex morphologies prior to human treatment.

The FE analysis has been proven to be consistent with the clinical evidence. This opens the door to better prediction of outcomes after stent surgery in patients suffering congenital heart disorders, or even any other dysfunction needing this surgical procedure.


Mimics Innovation Awards

Each year, Materialise hosts the Mimics Innovation Awards to support scientists doing cutting-edge research to make the world a better and healthier place.

The jury for the 2019 awards include Materialise CEO Fried Vancraen, who said the following about the research findings:

If you have been conducting cutting-edge research using the Mimics Innovation Suite, apply for your chance to win the 2021 Mimics Innovation Awards: