ThinkMedTek

1. GE HealthCare and Medis Medical Imaging have partnered to enhance precision care for diagnosing and treating coronary artery disease (CAD) through the development and commercialization of the Medis Quantitative Flow Ratio (Medis QFR). This non-invasive diagnostic tool, integrated into GE HealthCare’s interventional cardiology portfolio, aims to improve clinical outcomes by accurately assessing coronary physiology and guiding lesion selection for percutaneous coronary interventions (PCI).
2. Researchers in England have developed a mixture of photopolymerizable materials combined with 3D printing to revolutionize cataract surgery by accelerating the design and manufacture of intraocular lenses (IOLs) and facilitating patient-specific lenses. This new method, using stereolithography, has shown promising results in producing high-quality, biocompatible IOL prototypes, potentially overcoming the time-consuming and labor-intensive drawbacks of current IOL fabrication techniques like molding and lathing.
3. MIT engineers have developed a hydrogel adhesive that prevents fibrosis around medical devices like pacemakers, potentially extending their lifespan and efficacy. By coating devices with this adhesive, which binds them to tissue and prevents immune system attacks, the researchers have found a promising way to eliminate scar tissue buildup, offering a simple and general approach to improve the performance of implanted medical devices.
4. A recent study demonstrates the effectiveness of outpatient laser treatment using the Leonardo Dual Diode Laser in addressing genitourinary syndrome of menopause (GSM) or vulvovaginal atrophy (VVA) symptoms in women who cannot or do not wish to undergo hormone therapy. The treatment resulted in significant improvements in vaginal health index, symptom intensity, and sexual function, with 73.1% of patients reporting symptom improvement and no adverse effects noted.
5. Researchers at the University of Illinois have developed low-cost wearable sensors that could enhance access to care for Parkinson’s disease patients, using machine learning approaches and baseline data from healthy older adults to improve accuracy. By adapting the Movement Disorders Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale and incorporating data from both patients and healthy individuals, the team trained a machine learning model to identify motor impairments, achieving significant improvements in accuracy, particularly in hand movement tasks, and aiming to expand the model in collaboration with clinicians to better understand and quantify changes in Parkinson’s symptoms.

Sources

1. https://www.medicaldesigndevelopment.com/topics/cardiovascular/news/22910345/ge-healthcare-medis-medical-imaging-partner-on-noninvasive-coronary-disease-treatment 
2. https://www.mddionline.com/3d-printing/3d-printed-lens-implant-could-revolutionize-cataract-surgery 
3. https://www.sciencedaily.com/releases/2024/05/240522130429.htm 
4. https://www.med-technews.com/news/latest-medtech-news/leonardo-dual-diode-laser-effective-for-genitourinary-syndro/ 
5. https://www.medicaldesignandoutsourcing.com/small-wearable-low-cost-sensors-parkinsons-disease-treatment/