Established in 2013, the Insight SFI Research Centre for Data Analytics (aka “Insight”) stands as one of Europe's premier data analytics research hubs. With more than 450 researchers, 220 industry partners and a robust funding of more than $165 million, the Centre delves into diverse research areas ranging from health and human performance to business services and sustainable operations. Insight collaboratively operates through four main institutions: DCU, the University of Galway, UCC and UCD, while partnering with esteemed entities like Maynooth University, TCD, Tyndall and UL.
"What's truly exciting for us is exploring how the future potential of AI technologies is enhancing the practices of vascular surgeons."
The obstacles they faced
The aorta, our body's primary artery, efficiently delivers oxygen-rich blood throughout our system. But the silent threat of aortic disease often goes undetected, commonly misdiagnosed in the acute setting in 50% of cases as conditions like coronary syndrome or pulmonary embolism. Despite four decades of research, survival rates have not improved due to the inability to accurately diagnose when intervention is needed.
Stepping up to this challenge is the Virtual Aorta initiative at the University of Galway. Spearheading advancements in diagnostics and the development of new treatments for aortic disease, this groundbreaking project is backed by Open Clouds for Research Environments (OCRE) funding. Since January 2021, Rackspace Technology® has been a leading contributor in the European Open Science Cloud marketplace. Through the OCRE framework, they provide Amazon Web Services (AWS) cloud services to research institutions, universities and NREN members across Europe, aiming to boost cloud adoption and refine the tools available to the education and research communities. With this powerful collaboration, Insight leverages AWS to expedite and streamline diagnosis.
Pooling expertise from diverse fields within University of Galway and its partners, the initiative is on the brink of delivering innovative medical solutions. Through computer simulations tailored to individual patients, the path is cleared for more timely and accurate diagnoses of aortic complications.
Harnessing the cloud, the initiative is revolutionizing secure data management, promoting efficient computational models, fostering seamless collaborations, and championing cloud service adoption in academia. This alignment with EU open data directives isn’t just beneficial for the ongoing research—it's also a beacon for the broader research community.
However, the challenge persists: real-time aortic diagnosis is often hampered by the intricacies of modeling blood flow. But with cutting-edge tools like AI and machine learning in conjunction with Amazon SageMaker, the partnership is gaining ground, unlocking vast resources to virtually model the aorta and swiftly distill vital insights.
Edward Curry, Director at the Insight SFI Research Centre for Data Analytics, University of Galway, said, "Computationally modeling the aorta is resource-intensive, beyond our present compute capabilities. Our collaboration with Rackspace Technology and AWS via OCRE has granted us access to scalable cloud computing infrastructure. This increased compute capacity is a game-changer in reducing the analysis time."
"Rackspace Technology has been very influential, helping us onboard AWS technologies through training, access to expertise and working with us on a daily basis to understand how best to use those technologies within our research activities."
How we helped
The project's goals were multifaceted, but two main challenges stood out: the daunting computational process of modeling blood flow in the aorta and efficiently handling the massive, intricate three-dimensional CT scan images. Niamh Hynes, Consultant Vascular Surgeon and Senior Research Fellow at the University of Galway and Galway Clinic, shed light on the size of the task: “What you have are very large files, hundreds of gigabytes for a full CT scan. If we want to look at the biomechanical properties of the aorta, currently that takes up to 150 hours using a supercomputer.”
Before the partnership, research was often constrained by the limitations of local computing resources, both in cost and technical capability. But with the backing of Rackspace Technology and AWS's cloud infrastructure, the Insight team found solutions for secure storage and scalability. The offerings weren't just about storage space; they also focused on cost optimization, specialized consultation, and valuable training.
The ability to scale computational resources on-demand was a game-changer during the aortic blood flow modeling. Now, the team could seamlessly and securely engage with patient data across various storage solutions. There was a time when processing these models took around 120 hours for each sample. Today, with the leverage of public cloud scalability coupled with AI/ML services, a more streamlined architecture is in place. The use of Amazon SageMaker and Apache Spark has expedited the computational modeling process, offering avenues to fine-tune model construction and achieve enhanced predictive results.
Andy Donald, Research Fellow at the Insight SFI Research Centre for Data Analytics, University of Galway, highlighted the drastic improvements and their implications: “We are researching how to emulate the complex computational modeling process as a ‘surrogate model’ to reduce processing time from approximately 150 hours to around 10 minutes. This near real-time potential advance would allow a surgical team to progress with more informed data.”
The secure storage of diverse patient data — spanning medical images to clinical information — was a priority. Traditionally, such data found its home on university server-based physical hard drives. Cloud storage has transformed this, offering not only fortified security but also quicker, more efficient data distribution to collaborators. Donald went on to emphasize the security aspect: “Given the sensitive nature of this project involving medical patient data, it is especially critical to ensure complete security and anonymity. We store full-body CT scan files of hundreds of gigabytes in Glacier to optimize efficiency and rapid access for further analytics. With Amazon SageMaker, we tackle the most demanding workloads, easily scaling resources as needed.”
While cloud technology offers tremendous potential, harnessing it requires a specific skill set. This led to tailored training for Insight’s data scientists and engineers, ensuring they were proficient with vital cloud technologies for the project.
Curry pointed out the challenges and the solutions. "Ensuring our team had the necessary skills and were up to date in using cloud technologies was vital,” he said. “Partnering with Rackspace Technology and AWS has given us access to the training our data scientists and engineers needed, enabling them to develop cutting-edge AI/ML solutions alongside our industrial partners."
What we achieved together
Before the Virtual Aorta initiative, Insight grappled with infrastructure challenges, making it difficult to focus solely on research without being entangled in the technicalities of project infrastructure. Now, with the transformative power of cloud services facilitated by the OCRE grant, the research team can direct its energies toward pivotal research outputs. This shift has accelerated time to outputs and created opportunities to fortify security.
Donald highlighted the transformative nature of the initiative. "Previously, real-time predictions on such intricate data models were beyond our grasp,” he said. “Now, by harnessing the computational prowess of cloud services, we're breaking barriers. It's a beacon of what's achievable in the realm of aortic disease diagnostics."
Moreover, the scalable nature of cloud resources brings newfound agility to the research process. It's no longer just about accessing vast amounts of data, but about discovering fresh avenues of exploration that would have been previously constrained by traditional resources.
Hynes voiced her optimism about the initiative's impact. "The Virtual Aorta is poised to embed biomechanical factors into daily clinical practice,” she said. “In the upcoming year, I envision our case planning tools being fully integrated into clinical routines, revolutionizing our approach from a mere 2D perspective to a dynamic mechanical concept of the aorta. This shift promises timelier and more precise treatments for aortic patients."
But the benefits of this collaboration aren't just confined to a single project. It's a testament to the broader potential of cloud computing in magnifying research productivity and fostering a collaborative spirit within the global research community.
Curry foresees a vibrant future for the Virtual Aorta that’s focused on validating data and AI in real-world clinical environments, and he stresses the profound synergy that arises when data scientists and clinicians converge: "When these two worlds intersect, you truly understand how technology can uplift patient care,” Curry said. “There is tremendous strength in this multidisciplinary collaboration among diverse stakeholders."
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