Development of AI Technology for Producing CT Images Based on MRI

Transcranial focused ultrasound can be used to treat degenerative movement disorders, intractable pain, and mental disorders by delivering ultrasound energy to a specific area of the brain without opening the skull. This treatment must be performed with an image-based technology that can locate the brain lesions. Doctors typically use CT to obtain information about a patient's skull that is difficult to identify with MRI alone and to accurately focus the ultrasound on the lesions through the skull. However, there have been concerns about the safety of CT scans, during which radiation exposure is inevitable, especially in pediatric and pregnant patients.

Dr. Hyungmin Kim's team at the Bionics Research Center at the Korea Institute of Science and Technology (KIST, President Seok-Jin Yoon) developed an artificial intelligence technology to generate CT images based on MRI images and conducted a simulation experiment. The results showed that the transcranial focused ultrasound procedure could be performed with MRI alone.

Efforts have been made to obtain cranial information from MRI images, but special coils for the MRI or imaging protocols that are not widely available in the medical field are required. As an alternative, interest for acquiring artificial intelligence-based CT images has been high worldwide, but their clinical efficacy has not been proven. The KIST research team proved that CT images obtained by artificial intelligence have clinical utility.

The KIST research team developed a three-dimensional conditional adversarial generative network that learns the nonlinear CT transformation process from T1-weighted MRI images, which is one of the most commonly used images in the medical field. The team devised a loss function that minimizes the Hounsfield unit pixel variation error of the CT images, and also optimized the neural network performance by comparing the changes in quality of the synthetic CT images according to the normalization methods of MRI image signals, such as Z-score normalization and partial linear histogram matching normalization.

For safe and effective ultrasound treatment, it is imperative to understand each patient's skull density ratio and skull thickness in advance, and when these skull factors were obtained via the synthetic CT, both factors showed >0.90 correlation with the actual CT. There was no statistically significant difference. Moreover, when simulated ultrasound treatment was performed, the ultrasound focal distance had an error of less than 1 mm, the intracranial peak acoustic pressure had an error of approximately 3.1%, and the focal volume similarity was approximately 83%. This demonstrated that the transcranial focused ultrasound treatment system can be performed with only the MRI image.

Dr. Hyungmin Kim of KIST stated that "patients can receive focused ultrasound treatment without being worried about radiation exposure, and as the additional imaging and alignment processes can be omitted, this will reduce the staff's workload, leading to a reduction in time and economic costs." He also stated that "through follow-up studies on identifying the error associated with the ultrasound parameters and transducers and understanding the possibility of artificial intelligence CT application in various parts of the body, we plan to continue developing the technology for its applicability in various treatment technologies."

H Koh, TY Park, YA Chung, JH Lee, H Kim.
Acoustic simulation for transcranial focused ultrasound using GAN-based synthetic CT.
IEEE Journal of Biomedical and Health Informatics, 2021. doi: 10.1109/JBHI.2021.3103387

Most Popular Now

Philips and Medtronic Advocacy Partnersh…

Royal Philips (NYSE: PHG, AEX: PHIA), a global leader in health technology, and Medtronic Neurovascular, a leading innovator in neurovascular therapies, today announced a strategic advocacy partnership. Delivering timely stroke...

New AI Tool Predicts Protein-Protein Int…

Scientists from Cleveland Clinic and Cornell University have designed a publicly-available software and web database to break down barriers to identifying key protein-protein interactions to treat with medication. The computational tool...

AI for Real-Rime, Patient-Focused Insigh…

A picture may be worth a thousand words, but still... they both have a lot of work to do to catch up to BiomedGPT. Covered recently in the prestigious journal Nature...

New Research Shows Promise and Limitatio…

Published in JAMA Network Open, a collaborative team of researchers from the University of Minnesota Medical School, Stanford University, Beth Israel Deaconess Medical Center and the University of Virginia studied...

G-Cloud 14 Makes it Easier for NHS to Bu…

NHS organisations will be able to save valuable time and resource in the procurement of technologies that can make a significant difference to patient experience, in the latest iteration of...

Start-Ups will Once Again Have a Starrin…

11 - 14 November 2024, Düsseldorf, Germany. The finalists in the 16th Healthcare Innovation World Cup and the 13th MEDICA START-UP COMPETITION have advanced from around 550 candidates based in 62...

Hampshire Emergency Departments Digitise…

Emergency departments in three hospitals across Hampshire Hospitals NHS Foundation Trust have deployed Alcidion's Miya Emergency, digitising paper processes, saving clinical teams time, automating tasks, and providing trust-wide visibility of...

MEDICA HEALTH IT FORUM: Success in Maste…

11 - 14 November 2024, Düsseldorf, Germany. How can innovations help to master the great challenges and demands with which healthcare is confronted across international borders? This central question will be...

A "Chemical ChatGPT" for New M…

Researchers from the University of Bonn have trained an AI process to predict potential active ingredients with special properties. Therefore, they derived a chemical language model - a kind of...

Siemens Healthineers co-leads EU Project…

Siemens Healthineers is joining forces with more than 20 industry and public partners, including seven leading stroke hospitals, to improve stroke management for patients all over Europe. With a total...

MEDICA and COMPAMED 2024: Shining a Ligh…

11 - 14 November 2024, Düsseldorf, Germany. Christian Grosser, Director Health & Medical Technologies, is looking forward to events getting under way: "From next Monday to Thursday, we will once again...

In 10 Seconds, an AI Model Detects Cance…

Researchers have developed an AI powered model that - in 10 seconds - can determine during surgery if any part of a cancerous brain tumor that could be removed remains...