CASE STUDY dimensional CT scan images . “ What you have are very large files , hundreds of gigabytes for a full CT scan ,” said Niamh Hynes , Consultant Vascular Surgeon and Senior Research Fellow , University of Galway and Galway Clinic . “ 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 optimisation , specialised consultation and valuable training . The ability to scale computational resources on-demand was a game-changer during the aortic blood flow modelling . 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 modelling process , offering avenues to fine-tune model construction and achieve enhanced predictive results . to tailored training for Insight ’ s data scientists and engineers , ensuring they were proficient with vital cloud technologies for the project .
“ Ensuring our team had the necessary skills and were up to date in using cloud technologies was vital ,” added Curry . “ Partnering with Rackspace Technology and AWS has given us access to the training our data scientists and engineers needed , enabling them to develop cuttingedge AI / ML solutions alongside our industrial partners .”
The achievements
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 towards pivotal research outputs . This shift has accelerated time to outputs and created opportunities to fortify security .
“ Previously , real-time predictions on such intricate data models were beyond our grasp ,” Donald 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 .”
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 modelling 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 emphasise 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 optimise 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
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 .
“ The Virtual Aorta is poised to embed biomechanical factors into daily clinical practice ,” added Hynes . “ In the upcoming year , I envision our case planning tools being fully integrated into clinical routines , revolutionising 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 .” p
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