We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

HospiMedica

Download Mobile App
Recent News AI Critical Care Surgical Techniques Patient Care Health IT Point of Care Business Focus

3D-Printed Models of Human Brain Could Improve and Personalize Neurosurgery

By HospiMedica International staff writers
Posted on 27 Mar 2023
Print article
Image: This diagram shows the AMULIT technique printing the bronchi of a lung model within a bath of supporting material (Photo courtesy of University of Florida)
Image: This diagram shows the AMULIT technique printing the bronchi of a lung model within a bath of supporting material (Photo courtesy of University of Florida)

Neurosurgeons often practice surgeries prior to the actual procedure using patient brain models, but current models lack realism in replicating blood vessels and providing accurate tactile feedback. Additionally, they may not include crucial anatomical structures that affect the surgery. To improve accuracy and reduce errors during actual surgeries, personalized 3D printed replicas of patient brains could be used, as they can replicate the soft texture and structural details needed for effective pre-surgery preparation.

Scientists at the University of Florida (Gainesville, FL, USA) have developed a new 3D printing method using silicone that can create accurate models of blood vessels in the brain, providing neurosurgeons with more realistic simulations for pre-surgical preparation. While embedded 3D printing has been successful for creating various soft materials, such as hydrogels, microparticles, and living cells, printing with silicone has been challenging. Due to the high interfacial tension between oil (which liquid silicone is) and water-based support materials, 3D-printed silicone structures have been prone to deform and small-diameter features break into droplets during the printing process.

Numerous studies have been conducted to produce silicone materials that can be printed without the need for support. However, altering the properties of silicone to achieve this also affects the material's softness and stretchiness, which are significant considerations for users. To address the issue of interfacial tension, researchers from the fields of soft matter physics, mechanical engineering, and materials science have developed a support material using silicone oil. The team hypothesized that most silicone inks would share chemical similarities with their silicone support material, thereby significantly reducing interfacial tension while remaining distinct enough to be printed separately in 3D.

The team of researchers tested various support materials but determined that the most effective solution was to create a dense emulsion of silicone oil and water that resembled a crystal clear mayonnaise, made from packed microdroplets of water in a continuum of silicone oil. The researchers coined the term "additive manufacturing at ultra-low interfacial tension" (AMULIT) for this method. Using the AMULIT support material, the researchers managed to print off-the-shelf silicone at high resolution, producing features as small as 8 micrometers (approximately 0.0003 inches) in diameter. The printed structures were equally durable and stretchy as those produced through traditional molding. This breakthrough allowed the team to create precise 3D models of a patient’s brain blood vessels based on a 3D scan and a functioning heart valve model based on average human anatomy.

Related Links:
University of Florida 

Gold Member
12-Channel ECG
CM1200B
Gold Member
Solid State Kv/Dose Multi-Sensor
AGMS-DM+
Silver Member
Wireless Mobile ECG Recorder
NR-1207-3/NR-1207-E
New
Enterprise Imaging & Reporting Solution
Syngo Carbon

Print article

Channels

Critical Care

view channel
Image: The new risk assessment tool determines patient-specific risks of developing unfavorable outcomes with heart failure (Photo courtesy of 123RF)

Powerful AI Risk Assessment Tool Predicts Outcomes in Heart Failure Patients

Heart failure is a serious condition where the heart cannot pump sufficient blood to meet the body's needs, leading to symptoms like fatigue, weakness, and swelling in the legs and feet, and it can ultimately... Read more

Patient Care

view channel
Image: The portable, handheld BeamClean technology inactivates pathogens on commonly touched surfaces in seconds (Photo courtesy of Freestyle Partners)

First-Of-Its-Kind Portable Germicidal Light Technology Disinfects High-Touch Clinical Surfaces in Seconds

Reducing healthcare-acquired infections (HAIs) remains a pressing issue within global healthcare systems. In the United States alone, 1.7 million patients contract HAIs annually, leading to approximately... Read more

Health IT

view channel
Image: First ever institution-specific model provides significant performance advantage over current population-derived models (Photo courtesy of Mount Sinai)

Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients

Machine learning algorithms have been deployed to create predictive models in various medical fields, with some demonstrating improved outcomes compared to their standard-of-care counterparts.... Read more

Point of Care

view channel
Image: The Quantra Hemostasis System has received US FDA special 510(k) clearance for use with its Quantra QStat Cartridge (Photo courtesy of HemoSonics)

Critical Bleeding Management System to Help Hospitals Further Standardize Viscoelastic Testing

Surgical procedures are often accompanied by significant blood loss and the subsequent high likelihood of the need for allogeneic blood transfusions. These transfusions, while critical, are linked to various... Read more