Squishy viscera, such as the liver, can change their shape significantly from the time a CT scan is taken that spots a tumor to when it’s excised during surgery. Various tags have been developed that can be tacked onto tissue in order to use as a point to calibrate against, but this approach still doesn’t quite achieve the desired precision. Researchers at Vanderbilt University have now developed an algorithmic approach that correlates CT scan data with how the soft tissue is manipulated during surgery, guiding the surgeon to the correct location of the target tumor. The software models the movement of the organ as it would be squeezed and moved by the surgical team during a procedure, adjusting the location of the tumor and displaying its new location on a computer screen.
Here’s some detail about the study used to verify the software:
In the study, surgeons were shown six or seven CT images, depending on time, for each of 20 liver tumor patients in the operating room, for a total of 125 images. The CT map would either be aligned to the original Pathfinder or Miga’s [Michael Miga, Professor of Biomedical Engineering] new enhanced CT map that corrected for deformations. The surgeon was not told which display was being presented and would assess the alignment by touching the stylus on the patient’s liver and looking at the display. The surgeon would then provide a score on a scale of +3 to -3 relative to the previous display presented. The display order was randomized and could go from enhanced to original, original back to enhanced, or held constant. The surgeon was able to detect the variations correctly in 73 percent of the 125 different evaluations.
Study in journal Surgery: Deformation correction for image-guided liver surgery: An intraoperative assessment of fidelity…
Via: Vanderbilt…