Converting MRI Scans to 3D and Other Future Tech

It’s #FantasticTuesday! Welcome to another day in science and technology news of the future.

Converting MRI Scans to 3D

Researchers at Boston Children's Hospital teamed up with MIT to come up with a system that 3D prints an MRI scan of a human heart and produces a physical 3D model for use by surgeons. Generating the 3D CAD model on the computer takes about an hour, with printing taking up a couple of hours at the most.

"In the past, researchers have produced printable models of the heart by manually indicating boundaries in MRI scans. But with the 200 or so cross sections, that process can take eight to 10 hours. The problem with [the traditional] approach is that many of the cardiac patients require surgery precisely because the anatomy of their hearts is irregular. Inferences from a generic model could obscure the very features that matter most to the surgeon," reads MIT’s CSAIL website.

Using this technique’s custom healthcare software solution, surgeons have the ability to visualize a 3D printed model better than having to manually map out the entire design.

Fighting Cancer with Borrowed Immune Cells

Researchers at the Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital have uncovered in a study the fact that ‘borrowed’ T Cells, or immune cells that destroy bad cancerous cells, detect that the cancerous cells are not normal.

"Our study shows that the principle of outsourcing cancer immunity to a donor is sound. However, more work needs to be done before patients can benefit from this discovery. Thus, we need to find ways to enhance the throughput. We are currently exploring high-throughput methods to identify the neo-antigens that the T cells can "see" on the cancer and isolate the responding cells. But the results showing that we can obtain cancer-specific immunity from the blood of healthy individuals are already very promising," said Ton Schumacher, Professor at the Department of Immunology at Oslo University Hospital.

Predicting Age with a Simple Blood Test

Insilico Medicine, a company dealing in bioinformatics using big data, have designed a system with 21 deep neural networks to analyze data and predict a person’s age and gender with an accuracy of around 80%. Using the system, the researchers created an online platform (called www.aging.ai) to allow any user to enter data from a blood test and generate an output instantly.

"We decided to train an ensemble of deep neural networks on a very large number of simple inexpensive historical blood tests linked to age and sex and built a predictor, which is scalable and can include many other data types to build more comprehensive biomarkers of aging. Aging.AI can in principle be extended as a biomarker of biological aging that can be used to assess the efficacy of various therapies," says Poly Mamoshina, a research scientist at the company.

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