Machine learning has become a truly revolutionary force in the world of rapidly expanding technology, having a profoundly disruptive impact on several industries, most notably healthcare.
It increases operational effectiveness, reduces the possibility of human error, and frees up crucial time for more urgent issues. The capacity of artificial intelligence (AI) to transform medical scans into interactive 3D and 4D models has enormous promise for surgical planning, particularly in complex situations. This, in turn, has the potential to completely transform how we understand organs, tissues, and tumours. In order to assist in pre-surgical planning for difficult cardiac and cancer situations, a team of researchers is now fervently pursuing the conversion of medical photos into 3D and 4D interactive models, with the eventual objective of 3D printing for virtual reality.
Being a special and dynamic organ, the heart changes shape as it performs its essential job of pumping blood throughout the body. However, problems may occur when the heart’s capacity to effectively pump blood is hampered by aberrant cardiac muscle development. In order to provide surgeons with a comprehensive 4D perspective of this dynamic blockage, current technology falls short. The best way to exercise the muscle to remove the blockage is currently determined by the surgeons after years of experience and trial and error. Currently, a Virtual Reality (VR) viewpoint of the patient’s heart is being created by researchers from OSF HealthCare (Peoria, IL, USA) and Bradley University (Peoria, IL, USA), enabling a 4D picture of its regular contractions and expansions.
Although the idea of visualising the heart in four dimensions had previously been shown, the conversion of four-dimensional heart pictures proved time-consuming and unsustainable. The study team is certain that machine learning can automate this time-consuming procedure and allow surgeons to digitally tour a patient’s beating heart in 4D while properly inspecting the impediment. This innovative pre-surgical analysis tool will provide a thorough visualisation of the anatomy of the heart, greatly enlarging the anatomical details for clear comprehension. Unquestionably, this ground-breaking, 4D, machine-learning-driven visualisation of the beating heart will be remembered as a technical masterpiece of its type.
The researchers have an optimistic expectation that their automated technique will significantly shorten the time needed to convert images from months to hours or even minutes. Additionally, this technology has the potential to be expanded to include pictures of other complicated medical issues, which would be advantageous for people of all ages, including adults, kids, and even newborns. This strategy might potentially be adopted by surgeons all over the globe with the use of AI-enabled software, turning into a scaleable option for pre-surgery planning in various hospitals. Within a year, the study team hopes to automate the process of turning cardiac CT images into virtual reality. With this 4D view, doctors will be able to clearly see patients’ beating hearts and plan surgery in VR before entering the operating room.
Dr. Matthew Bramlet, a paediatric cardiologist at the University of Illinois College of Medicine and expert in congenital cardiac MRI at OSF Children’s Hospital of Illinois, stated that the 4D heart is unlikely to have the biggest effect right away. The essential value of this technology resides in its scalability, which makes it possible for any programme to produce pre-surgical planning models, whether they are 3D printed or created for virtual reality.
