Medicrea has announced that the 3,000th surgery utilising Medicrea’s patient-specific UNiD ASI technology has been successfully completed.
Five years after its initial launch, over 3,000 patients worldwide have benefitted from UNiD ASI, the 100% proprietary, pre-operative planning technologies and services associated with patient-specific spinal realignment rods. This technology has seen a strong acceleration in adoption rate in 2018 especially in the USA (+62% cases in the USA since 1st January, 2018). Medicrea just recorded its highest monthly number of UNiD surgeries with 121 surgeries performed in October 2018.
“Planning a case is a crucial step in any spine surgery. The slightest change at the base of the spine impacts the top of the spine greatly. Therefore, if the base is not fixed properly, the patient has a higher risk of proximal junctional kyphosis (PJK). With Medicrea’s proprietary UNiD ASI platform, I can plan my case pre-operatively.”
He continued: “The artificial intelligence embedded within the platform allows me to visualise the compensatory mechanisms above and below the instrumented spine that will most likely occur based on my surgical plan. I can work hand-in-hand with the UNiD Lab biomedical engineers who create several surgical plans and identify the one that would give my patient the best outcome” said Christopher Kleck, Department of Orthopaedics, University of Colorado SOM, Aurora, USA.
Christopher Kleck recently co-authored the article titled: “Pelvic incidence changes between flexion and extension”. Recent evidence suggests that Pelvic Incidence (PI) changes with age, ethnicity, and body mass index and can be modified following spinal procedures. However, the mechanism of PI changes is still not well understood. “This new study suggests that this mechanism is even more complex than previously thought and reinforces the need for UNiD ASI technology” adds C. Kleck.
Medicrea’s proprietary UNiD ASI technology is a comprehensive suite of services designed to help surgeons improve their patient’s outcomes. By leveraging artificial intelligence and the latest clinical research, the UNiD LAB Engineer provides the surgeon with insights previously not possible within their clinic. UNiD ASI’s unique blend of software and services delivers these insights within the normal pace of a surgeon’s clinic day without slowing them down. This empowering technology allows surgeons to have more impactful patient interactions with visual surgical plans based on technology fuelled by 3,000 past cases.
Christopher Ames, director of spinal tumour and spinal deformity surgery at UCSF Medical Centre, CA, USA said “I fully integrated the UNiD ASI technology within my practice workflow. Before I even see the patient, I can look at the images and the measurements taken by the UNiD LAB biomechanical engineers. For instance, in a patient who has sagittal imbalance and pelvic retroversion I can tell that I am going to need a PSO. I can directly communicate with an engineer to let them know. Within minutes, they will simulate different plans incorporating my feedback. I can review the pre-op measurements sent back to me and decide on the patient’s final operative plan. From there, I can meet the patient, explain the procedure and schedule the surgery.”
Denys Sournac, chief executive officer of Medicrea, stated, “Spine surgery is one of the more complex procedures in healthcare because of the high number of different parameters to take into consideration. It is impossible for the human brain to compute all of them for one single patient. Medicrea has dedicated the past eight years to creating and strengthening a platform based on artificial intelligence with the goal to assist surgeons in building precise surgical planning in order to help them improve their patient’s outcomes.”
Denys Sournac adds: “Today we are celebrating the 3,000th surgery with the UNiD ASI technology, including patient-specific implants. This milestone embodies the power of our platform and the depth of our clinical database collected following rigorous and centralised processes. Clinical data from which our algorithms are designed and continuously refined are extremely homogeneous and exceptionally rich.”
