Discover how an evolution in patient imaging is driving down surgery costs and supporting improved outcomes...

Medical Imaging officially took off in the 1920s, almost 30 years after x-rays were first discovered. Although there were many improvements to x-ray techniques over the first half of the 20th century, early x-rays subjected patients to 50 times more radiation than a standard x-ray today. Not exactly the healthiest way to treat people…

Then, in the 1960s, computer-based image analysis, and the development of sonar during World War II, paved the way for ultrasound scanning which significantly reduced the need to subject the body to harmful x-rays. A decade later we welcomed the computed tomography (CT) scanner, leading to enhanced imagery, smaller radiation doses, and better record storage. CT scanning, alongside magnetic resonance imaging (MRI) scanning, has since been the norm in medical imaging for hospitals across the world.

These advancements in patient imaging have led to improved patient care and outcomes over the course of history, but in all instances they lack one crucial aspect. Depth.

In each case, these examples of patient imaging offer insights into the human body, but even experts in their field will take time processing and analyzing these complex radiographic images to understand the relationship of anatomical structures - and even then there may be an element of variability in interpretation.

The next evolution in patient imaging?

As technology has advanced, so too has our trust in using it. The insurgence of computing across healthcare centres has enabled doctors to diagnose and treat patients much faster and more accurately than through traditional methods alone.

Of all of the new technologies that have the potential to transform healthcare, one of the newest and most exciting evolutions is undoubtedly 3D modeling. This technology is no longer the territory of hobbyists who want to print out figurines or ornaments, it is a disruptive technology with a broad range of applications in many sectors, not least in medicine.

3D printing has allowed surgeons and radiologists across the world to take multiple 2D images of a patient scan and make it a real, tangible object that can be used to give insight into a pathology that is not possible with conventional 2D and 3D CT or MRI visualizations.

The use of these models is proven to positively affect every step of the patient care pathway, from planning, to consent, and procedure to recovery:

• 53% of surgeons change their pre-operative plans when they use an Axial3D anatomical model
• A further 47% confirm their pre-operative plans much faster when using our anatomical models
• Patients in 98% of cases felt that an Axial3D model was a great improvement to discussions with their surgeon over 2D scans alone
• Surgeons report 16% faster recovery times when a patient-specific 3D model is used in treatment
• 62 minutes are saved per case on average when a 3D model is used for planning a procedure

These time savings not only have a knock-on impact on costs (less theatre time, only necessary equipment is sterilized, a reduction in load kits) but impacts directly on scheduling efficiency, increasing the number of patients being treated too.

This latest innovation in patient imaging offers a real solution for hospitals that creates better outcomes, shortens a patient’s stay in the hospital, reduces readmission rates, promotes a better understanding of treatment for the patient and gives your hospital a competitive advantage.

Based on a combination of published studies and analysis of surgeon feedback on actual procedures using Axial3D models.

References:

Medical 3D Printing Cost-Savings in Orthopedic and Maxillofacial Surgery: Cost Analysis of Operating Room Time Saved with 3D Printed Anatomic Models and Surgical Guides

Authors: David H. Ballard MD^aPatrick Mills JD, LLM^bRichard Duszak Jr. MD ^cJeffery A.Weisman MD, PhD, JD^dFrank J. Rybicki MD, PhD^ePamela K. Woodard MD^a

a Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S. Kingshighway Blvd, Campus Box 8131, St. Louis, MO 63110

b Louisiana Tech University, Ruston, Louisiana

c Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia

d University of Illinois at Chicago Occupational Medicine, Chicago, Illinois

e Department of Radiology, University of Cincinnati, Cincinnati, Ohio

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