The Medicrea Group (Euronext Growth Paris: FR0004178572 ALMED, PEA-PME eligible, and OTCQX: MNRTY and MNRTF), pioneering the transformation of spinal surgeries through Artificial Intelligence, predictive modeling and patient specific implants with its UNiD ASI (Adaptive Spine Intelligence) technology, announced today that the Company is attending the NASS 2018 meeting taking place in Los Angeles, California, from September 26th to 28th, where UNiD LAB biomedical engineers will showcase the most recent developments of the Company's UNiD ASI technology.
Denys Sournac, President and Chief Executive Officer, stated, "At NASS 2018, our team of biomedical engineers will show attending spine surgeons how the UNiDASI technology answers the gap left by traditional implant manufacturers through a demonstration of the UNiD HUB, a software platform that fully integrates surgical planning through machine learning to generate personalized implants that are adapted to each individual patient and at the same time to each individual surgeon technique."
Five years after its initial launch in September 2013, over 2,800 patients have benefited from UNiD ASI 100% proprietary pre-operative planning technologies and services associated with patient-specific spinal realignment rods, with a strong acceleration in adoption rate in 2018 (+60% cases in year-to-date 2018) especially in the USA.
Since its inception, the technology supported surgeons specializing in adult indications with planning services and patient-specific implants focused on restoring sagittal alignment.
Christopher Kleck, M.D., University of Colorado, Denver, CO, USA, will present during the Innovative Technology Session, on Thursday, September 27, 2:12pm-2:19pm, Room 403A, a paper titled "Patient-Specific Rods Show a Reduction in Rod Breakage Incidence". He will demonstrate the benefits of the UNiD ASI technology in reducing rod breakage by 85% compared to the rate established in current literature with regards to adult spinal deformity, and 78% reduction in procedures involving a PSO.
More recently, surgeons have found the technology to be fully applicable to the pediatric population as well. As such, surgeons have increasingly published on the application of UNiD ASI in pediatrics and have begun to demonstrate the importance of respecting sagittal parameters in the pediatric population.
Jean-Luc Clément, M.D. of Fondation Lenval (Nice, FRANCE) and UNiDASI user recently published the Article titled "Surgical Increase of Thoracic Kyphosis Increases Unfused Lumbar Lordosis in Selective Fusion for Thoracic Adolescent Idiopathic Scoliosis". In this article, Jean-Luc Clément emphasizes "...the importance of restoring adequate kyphosis and respecting the links between sagittal parameters (thoracic kyphosis, lumbar lordosis and pelvic incidence) specifically in adolescent surgery. A task which is close to impossible for a surgeon without the appropriate tools that are now provided by Medicrea through UNID ASI Platform. Data analytics and predictive modeling are topics that surgeons and healthcare professionals recognize will shape the future of care and the way we view spine surgery."
During the Innovative Technology Session, on Thursday, September 27, 2:05pm-2:12pm, Room 403A, Afshin Aminian, M.D., Children's Hospital Orange County, OC, CA, USA, will demonstrate how the combination of the patient-specific rods and the ST2R technique can decrease rod flattening in comparison to reports of manually contoured rods. This podium presentation will explain how the patient-specific rods designed using the UNID ASI Platform assist in maintaining sagittal profile obtained from pre-operative planning, without sacrificing coronal correction. The presentation is titled "Analysis of Pre-Contoured Patient-Specific Rods in Adolescent Idiopathic Scoliosis Using Computer Software: Does Rod Flattening Occur After Implantations?"
Medicrea's proprietary UNiD ASI technology and services integrates numerous proprietary predictive models, one of which takes into consideration the post-operative compensatory mechanisms occurring on the non-instrumented portion of the spine both above and below the construct. Through the UNiD HUB, the algorithms use large amounts of data to generate intelligent surgical planning through machine learning while simultaneously allowing the surgeon to perform detailed, custom analysis of the cases. Medicrea uses proprietary data science to drive improved outcomes and economic efficiencies in spine surgery.
Meeting attendees are invited to learn more about Medicrea at Booth 1823.
Click here to reach the article: JL Clément, Y Pelletier, F Solla, V Rampal. "Surgical Increase of Thoracic Kyphosis Increases Unfused Lumbar Lordosis in Selective Fusion for Thoracic Adolescent Idiopathic Scoliosis", European Spine Journal, 2018
About Medicrea (www.medicrea.com)
Through the lens of predictive medicine, Medicrea leverages its proprietary software analysis tools with big data and machine learning technologies supported by an expansive collection of clinical and scientific data. The Company is well-placed to streamline the efficiency of spinal care, reduce procedural complications and limit time spent in the operating room.
Operating in a $10 billion marketplace, Medicrea is a Small and Medium sized Enterprise (SME) with 210 employees worldwide, which includes 50 who are based in the U.S. The Company has an ultra-modern manufacturing facility in Lyon, France housing the development and production of 3D- printed titanium patient-specific implants.
For further information, please visit: Medicrea.com.
Connect with Medicrea
FACEBOOK | INSTAGRAM | TWITTER | WEBSITE | YOUTUBE
Medicrea is listed on
EURONEXT Growth Paris
ISIN: FR 0004178572
Ticker: ALMED
LEI: 969500BR1CPTYMTJBA37
Medicrea is traded on
OTCQX Best Market
Tickers: MNRTY MRNTF
View source version on businesswire.com: https://www.businesswire.com/news/home/20180926006069/en/
Contacts:
Medicrea
Denys SOURNAC
Founder, Chairman and CEO
dsournac@medicrea.com
or
Fabrice KILFIGER
Chief Financial Officer
fkilfiger@medicrea.com
Tel: +33 (0)4 72 01 87 87