Emerging technologies are poised to expand IR’s abilities to plan procedures and better view complex systems, according to researchers.
In Sunday’s panel, “The view from the bench: Emerging technologies for interventional radiology,” five researchers shared their developments from the world of technology.
The first speaker, Marites P. Melancon, PhD, of MD Anderson Cancer Center, presented her research on nanoparticle-enhanced medical devices and their applicability to vascular IR. According to Dr. Melancon, vascular device utility is often challenged by some costly effects of device insertion, such as mechanical stress. To avoid this, Dr. Melancon and her team have been focused on absorbable devices, which will eventually hydrolyze, thus eliminating the need for removal or subsequent interventions.
But because absorbable filters cannot be viewed with imaging, Dr. Melancon and her team have begun developing biomaterials, combining polymers and nanoparticles to create viewable, absorbable filters. Early research shows that these biomaterial-infused filters are safe and efficacious, but researchers needed to find a way to increase the amount of nanoparticle they could use.
“We turned to an electrospinning system, which incorporates high amounts of radiopaque agents uniformly,” Dr. Melancon said. This system allowed researchers to incorporate up to 30% of nanoparticles—as opposed to the initial 1%—and can change the physical properties of the nanoparticles as well.
Thus far, these biomaterials have been used in rat models with chronic kidney disease and have shown to inhibit NIH formation.
Dr. Melancon’s lab has also developed radiopaque biodegradable nanoparticle-loaded devices that can be monitored using CT imaging and can be loaded with therapeutics for localized delivery of therapy.
“Our work highlights the potential application of implantable radiopaque and absorbable scaffolds to improve the outcomes of various vascular diseases,” Dr. Melancon said.
Other presenters explored other ways to deliver intravascular drugs, such as Malisa Sarntinoranont, PhD. Dr. Sarntinoranont and her lab have been using computational models to better plan drug delivery by gathering physiological information.
Researchers have created an image-based modeling procedure using contrast agents to determine nonuniform vessel structure leakiness and porosity. Working with a 3-dimensional model of a tumor, they are better able to predict spread within and outside the tumor by accounting for geometries in the surrounding area.
According to Dr. Sarntinoranont, their model is based on one used for calculating ground flow, which allows them to track interstitial fluid pressure and flow.
“The flow field through the interstitial space is important, because we can then see the flow of the contrast agent or biologic,” she said. “These flows will be influenced by the flow patterns within the tumor itself, and you can see the underlying effect of the tissue structure.”
She also noted that interstitial pressure and growth will have opposing effects on structural stress in the tumor interior, but will act synergistically to increase tension at the tumor rim. This effect then tends to concentrate mechanical stress at the tumor boundary, where it has the greatest potential to influence cell proliferation and invasion, she said.
The goal is for physicians to use this model to predict drug delivery. Dr. Sarntinoranont used the example of controlled infusions into the brain, which are traditionally difficult because of the blood brain barrier.
“This is where a computation tool is useful,” she said. “We can predict injections in different locations and predict spread or distribution and also plan where to inject to get 100% coverage.”
Other techniques can be used to guide intervention as well, said Aichi Chien, PhD, who presented her work combining magnetic resonance imaging with artificial intelligence. Dr. Chien and her partners have done extensive research utilizing MRI and AI to track changes in the brain vasculature in order to plan for IR procedures.
“Utilizing 20 years of data, we have essentially created an atlas and a probability map of the human brain,” Dr. Chien said. This model can track cerebrovascular changes in aneurysm patients and identify general trends of vascular shape change over time, and look for changes specific to individual patients.
The AI utilizes technology like gradient ascent, and separates the trajectory of shape changes over time for a group and individual-specific changes, thus allowing identification of patients with high-risk changes beyond the aneurysm site.
This is beneficial for patients, as physicians can then track the average trajectory of cerebrovascular changes over a patient’s life, thus enabling them to better plan the stent location and prepare for any additional interventions that may be needed down the road.
The MRI-AI hybrid model also has potential to be applied in the abdominal space, Dr. Chien said. Abdominal imaging modalities have made great advances, but there are limitations and challenges due to how much movement is present in the abdominal area.
“To have a good visual diagnostic, you need a very good motion calculation model,” Dr. Chien said. But according to her, the AI-MRI model can detect lesions using segmentation methods and can even analyze disease mechanisms and add functional information.
She detailed recent applications, such as one case where the model improved tissue landmark visualization and tissue classification, which provided an advantage for IR procedure planning.
In order to be reliably applied in clinical settings, Dr. Chien says multicenter studies are necessary to ensure reproducibility, and to verify the short-term benefit and long-term impact.
The last presenter, Agata Exner, PhD, switched topics from MRI advances to ultrasound innovations. Dr. Exner says that because ultrasound is low cost and highly accessible, there are many innovations and opportunities in the space, especially in regard to the contrast agents used.
Microbubbles, a unique agent that makes ultrasound easier to interpret, are among many contrast agents on the market, are considered safer than CT or MR contrast, and are known for their real-time movement tracking capabilities.
Dr. Exner’s lab is interested in nanobubbles, however, and have been working on shrinking microbubbles to the size of a nanoparticle. These nanoparticles enable extravascular applications, can be targeted, provide more attenuation at a high concentration and are more stable than most contrast agents, which only last a few minutes. According to Dr. Exner, nanobubbles can last about 20x longer than microbubbles.
Microbubbles may also be effective for cavitation using focused ultrasound, Dr. Exner says, because the bubbles stay in cancer cells for several hours. In a rabbit model, microbubble-guided cavitation stopped tumors from progressing.
“This may be a different paradigm for doing ultrasound ablations,” Dr. Exner says.
They may also be useful for US-guided intertumoral therapeutics, she says, and may support mobile drug delivery for cancer chemotherapy.
Though Dr. Exner believes nanoparticles have very promising applications due to their high specificity, she says these studies are still fully preclinical, and researchers need to do toxicology research and search for industry partners before they can progress to human trials.
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