Tuesday June 18, 2019
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Missouri University Sets On a Mission To Make a Better MRIs

The researchers estimate the Heart Speed technology will be available for clinical use within five years.

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MRI Scans
Making MRI scanners faster has several benefits, including increased access to these devices for patients. Pixabay

MRI scans help doctors diagnose diseases or injuries without radiation. MRI technology uses powerful magnets, radio waves and a computer to make detailed pictures inside the body.

This is especially important for heart patients. With an MRI, doctors can check to see if blood vessels are blocked. They can also check for heart damage after a heart attack.

The downside is that patients must lie motionless in a long tube for a long period of time, which is especially challenging for people with claustrophobia.

University of Missouri School of Medicine researcher Dr. Talissa Altes says the procedure can be very difficult for some patients.

“It can be very hard. It can be very tiring, and they are often very long exams. We schedule them in 90 minute, an hour and a half, slots, which if you have ever been in an MR scanner, that is a long time,” Altes said.

In order to get a clear picture, patients must hold their breath, over and over.

“In general, an MRI takes a long time to acquire a single image, and if you are moving during the acquisition of that image, you will get blurring,” said Robert Thomen, another researcher on the University of Missouri School of Medicine team.

Thoman and Altes are working on a project called Heart Speed. With Heart Speed, data analysis software pulls out motion information from the magnetic resonance images. Their colleague, Steve Van Doren, says Heart Speed would allow radiologists to see the heart clearly even if a patient is breathing normally.

MRI
Brain tumours can be confused with harmless bright spots, it has never been clear whether finding these abnormalities via MRI should be a cause for concern. Wikimedia Commons

“We found that we could separate breathing motion from the heart motion quite well using the software, and we thought we should try to start applying this to real patient data,” Van Doren said.

The goal? A more comfortable scan for patients who can breathe at a normal pace. Without repeated breath holds, scans would also be much shorter — just 15 to 30 minutes.

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“Patients will benefit because it will be easier for them to do the exam,” Altes said, adding that “hopefully the radiologist who reads it or the cardiologist who reads the MRI will benefit because the images will be much better.”

The researchers estimate the Heart Speed technology will be available for clinical use within five years. (VOA)

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Hackers can Easily Change Patient’s MRI, CT Scan Results

The researchers suggested several solutions, such as enabling encryption between the hosts in the hospital’s radiology network, digital signatures with a secure mark on each scan or hidden digital watermarks

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Patients’ CT and MRI scan results can be easily changed by hackers, thereby deceiving radiologists and Artificial Intelligence (AI) algorithms that diagnose malignant tumours, Israeli researchers have warned.

The researchers from the Ben-Gurion University (BGU) showed that hackers could access to add or remove medical conditions from lung cancer scans for the purposes of insurance fraud, ransom and even murder, Xinhua news agency reported.

As part of the attack, the hacker has full control over the number, size and location of the cancers while preserving the anatomy from the original, full resolution three-dimensional (3D) image.

To prove the feasibility of the attacks, the researchers broke with permission into an actual hospital network to intercept all CT (computed tomography) scans.

Although the hospital internal network is not connected to the internet, hackers can access it via the hospital’s WiFi or physical access to the infrastructure, the researchers said.

hackers, hacking group, military
iDefense said the hackers are likely affiliated with a group known as MUDCARP, and also referred to as TEMP.PERISCOPE, Periscope and Leviathan. Pixabay

To inject and remove medical conditions, the researchers used a deep learning neural network called a generative adversarial network (GAN), which has been used in the past to generate realistic imagery, such as portraits of non-existent people.

After the “attack” the radiologists at the hospital misdiagnosed 99 per cent of the scans showing malignant tumours, and 94 per cent of altered images with cancerous images removed.

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After the radiologists were informed about the attack, they still misdiagnosed 60 per cent of altered scans falsely showing tumours and 87 per cent of those falsely showing no sign of the tumour, the report showed.

The researchers suggested several solutions, such as enabling encryption between the hosts in the hospital’s radiology network, digital signatures with a secure mark on each scan or hidden digital watermarks. (IANS)