News Release

High-power MRI helps Mayo Clinic surgical team predict outcomes in unusual tumor cases

Peer-Reviewed Publication

Mayo Clinic

ROCHESTER, Minn. -- A Mayo Clinic surgical team has found that using a 3-Tesla MRI in surgical decision making provides a new level of capability to predict surgical outcomes that improves patient care by minimizing the potential for unsuccessful tumor-removal surgeries. The Mayo Clinic report appears in the December issue of the Journal of Neurosurgery www.thejns-net.org/jns/issues/current/toc.html.

In their report, Mayo physicians describe a case study of five patients. Four had neurofibromatosis, a condition with a predisposition to nerve-related tumors. All patients suffered from growths called "sciatic notch dumbbell-shaped" tumors. The tumors were benign, but resulted in neurologic dysfunction and disabling pain.

"In the past, if surgeons couldn't tell prior to surgery where the exact location of the large tumor was in relation to the sciatic nerve, it meant they couldn't predict in which cases surgery could be performed safely," explains Robert Spinner, M.D., the lead neurosurgeon on the Mayo Clinic team.

The team used an advanced magnetic resonance imaging (MRI) system performed on a 3-Tesla magnet to help identify suitable candidates for a difficult tumor-removal surgery. A Tesla is a unit of magnet strength. A 3-Tesla is one of the strongest commercially available.

Significance of the Mayo Clinic Case Study

A standardized surgical approach for safe and complete removal of sciatic notch dumbbell-shaped tumors has been problematic for at least three reasons. These tumors are:

  • relatively rare and therefore hard to study
  • anatomically difficult to reach and remove without injuring the main sciatic nerve
  • difficult to visualize before surgery with enough detail to distinguish tumor boundaries from nerve

The current Mayo Clinic report begins to change this situation by documenting a new multidisciplinary approach for obtaining the desired favorable surgical outcomes.

Surgeons need an accurate picture of how and whether they can remove a tumor while protecting a nerve. Otherwise, patients may be exposed to the risks of surgery without achieving surgical benefits if the tumor is inoperable because complete removal would damage a nerve. "Our experience demonstrates the advantages of predictive imaging at the outset," says Dr. Spinner. "With an integrated team of surgeons from three specialties, and an experienced radiologist specializing in advanced peripheral nerve imaging using the 3-Tesla MRI, we have devised an approach that minimizes unsuccessful tumor-removal surgeries."

About the Study

With the 3-Tesla MRI images, Mayo Clinic surgeons from three specialties -- neurosurgery, colorectal and orthopedic surgery -- obtained sufficiently detailed pictures of the tumor and nerve relationship before surgery in all five cases to accurately predict which patients would benefit from surgery. In three cases the tumor was predicted to be distinct from the main sciatic nerve, and the tumor was safely removed. All three patients experienced relief from pain and had no recurrent growth one year after surgery. In the other two cases, the tumor was predicted to be so entwined in the nerve that surgery would have damaged the nerve. Those patients did not undergo surgery.

Dr. Spinner said the team will continue to refine the approach to improve the care that these patients receive. "This new technology allows a multidisciplinary approach to be performed safely in these rare tumors that were once considered unresectable," he says. "In addition, the same techniques that we have developed have tremendous applications to many patients who have peripheral nerve tumors in more common locations."

###

Collaboration

Other members of the Mayo Clinic team included: Toshiki Endo, M.D.; Kimberly Amrami, M.D.; Eric Dozois, M.D.; Dusica Babovic-Vuksanovic, M.D.; and Franklin Sim, M.D.


Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.