Muhammad Abd-El-Barr, MD, PhD, and his  team of researchers are focused on improving outcomes for spine surgery patients. Current projects involve:

• Machine learning to determine if a patient is a good candidate for surgery
• Advanced preoperative/intraoperative planning, including the use of augmented reality, nerve segmentation
• Robotics

Contact

Muhammad M. Abd-El-Barr MD, PhD, FAANS
Associate Professor
Spine Fellowship Co-Director
Department of Neurosurgery
m.abdelbarr@duke.edu

Machine Learning to Improve Spine Care

Using Machine Learning to Triage Patients with Low Back Pain

Research funded by a grant from the Duke Institute for Health Innovation

Lower back pain (LBP) is one of the most prevalent health complaints amongst adults, with up to 84% of individuals reporting significant back pain at some point in their life. One of the challenges in triaging patients with low back pain is to make sure that patients go the ‘right’ provider, whether that be general practitioners, spine health practitioners such as chiropractors, invasive proceduralists or spine surgeons.

We hope to implement a machine learning predictive model that will allow patients to be triaged to the most appropriate practitioner. This will enhance patient and practitioner satisfaction and improve health efficiencies – two important missions of the Duke Health System.

The impact on the health system will be profound. There are approximately 70,000 unique patient encounters in the Duke system for low back pain in one given year. For a given surgeon, only 10-20% of the patients that they see ultimately receiving surgery. This leaves a large population that would be best served if they went initially to another provider. Similarly, there are patients that go to non-operative practitioners but would be best served if they went to a surgeon to start.

Advanced Preoperative/Intraoperative Planning

Augmented Reality

Using Augmented Reality Technology to Optimize Transfacet Lumbar Interbody Fusion: A Case Report.

Nerve Segmentation

The Importance of Planning Ahead: A Three-Dimensional Analysis of the Novel Trans-Facet Corridor for Posterior Lumbar Interbody Fusion Using Segmentation Technology.

Using Novel Segmentation Technology to Define Safe Corridors for Minimally Invasive Posterior Lumbar Interbody Fusion.

Novel Approach to Percutaneous Lumbar Surgeries via Kambin's Triangle-Radiographic and Surgical Planning Analysis with Nerve Segmentation Technology.

Novel Merging of CT and MRI to Allow for Safe Navigation into Kambin's Triangle for Percutaneous Lumbar Interbody Fusion-Initial Case Series Investigating Safety and Efficacy.

How dimensions can guide surgical planning and training: a systematic review of Kambin's triangle.

Robotics

Robot-assisted pedicle screw insertion versus navigation-based and freehand techniques for posterior spinal fusion in scoliosis: a systematic review and meta-analysis.

Successful coil embolization of a ruptured pseudoaneurysm of the superior gluteal artery after a percutaneous awake robot-assisted sacroiliac joint fusion: illustrative case.

Successful coil embolization of a ruptured pseudoaneurysm of the superior gluteal artery after a percutaneous awake robot-assisted sacroiliac joint fusion: illustrative case.

Successful coil embolization of a ruptured pseudoaneurysm of the superior gluteal artery after a percutaneous awake robot-assisted sacroiliac joint fusion: illustrative case.

Beyond Placement of Pedicle Screws - New Applications for Robotics in Spine Surgery: A Multi-Surgeon, Single-Institution Experience.

Sacroiliac Joint Fusion Using Robotic Navigation: Technical Note and Case Series.

Robot-assisted versus conventional percutaneous sacroiliac screw fixation for posterior pelvic ring injuries: a systematic review and meta-analysis.

Robotic-Assisted Trajectory Into Kambin's Triangle During Percutaneous Transforaminal Lumbar Interbody Fusion-Initial Case Series Investigating Safety and Efficacy.

Robotic-assisted percutaneous iliac screw fixation for destructive lumbosacral metastatic lesions: an early single-institution experience.