Robots in the Access Cavity? New Study Compares Accuracy in Calcified Canals

Every endodontist has had that moment. You open a tooth that looks perfectly normal coronally… and then the canal just isn’t there. Calcified. Obliterated. Radiographically visible, clinically elusive. And suddenly, what should have been routine becomes a high-risk search mission.

A new in vitro study published in the International Endodontic Journal (Feb 2026) takes that exact clinical frustration and asks a very relevant question: if we already have static guides and dynamic navigation, does adding robotics actually improve accuracy when preparing access cavities in calcified canals?

Liu and colleagues compared three approaches—robot-guided, static-guided, and dynamic-guided access—using 3D-printed mandibular models with pulp canal obliteration. The focus wasn’t just “did they find the canal?” but how precisely the bur followed the planned path. They measured coronal deviation, apical deviation and angular deviation between the virtual plan and the actual preparation.

Here’s what stands out clinically.

In both the robot-guided and static-guided groups, all 12 canals were located. No misses. In the dynamic navigation group, 10 out of 12 canals were found—and two resulted in root perforations. That alone is worth pausing on.

When it came to deviation values, the robotic system performed comparably to the static guide. No statistically significant difference there. But when compared to dynamic navigation, the robot showed significantly lower apical and angular deviation. And apical accuracy is not a trivial detail—it’s often where things go wrong in calcified cases. A few degrees off at the coronal level can mean a very different outcome at the apex.

So what does this really mean chairside?

Static guides are already well established for managing calcified canals. They’re precise, predictable, but require planning, lab work, and limited intraoperative flexibility. Dynamic navigation gives you real-time tracking but demands coordination and a learning curve. Robotics appears to combine pre-planned precision with controlled execution—reducing dependence on hand stability and real-time manual adjustment.