Digital twins in surgery: An emerging reality or the inevitable future of surgical planning?
For years, the concept of the digital twin was reserved for aerospace, automotive, or advanced engineering industries. Today, however, the term is beginning to appear in a much more intimate environment: the operating room.
And not as a vague promise. As a conversation that is already happening.
What is a digital twin applied to surgery?
At its core, a digital twin is an accurate virtual representation of a physical object. In surgery, this translates into creating a three-dimensional replica of a patient’s anatomy based on imaging tests such as CT scans or MRI.
But we are not talking about a static image. We are talking about an interactive model that allows surgeons to explore structures in 3D, isolate organs, vessels or tumors, simulate different surgical approaches, and anticipate potential complications. In other words: rehearsing the surgery before it happens.
From flat CT scans to real spatial understanding
Historically, surgical planning has depended on the surgeon’s ability to interpret two-dimensional images and mentally reconstruct them. A skill that requires years of experience and that still has limitations when anatomy becomes complex.
Currently, there are platforms that address precisely this need: they convert radiological studies into interactive three-dimensional models using artificial intelligence, making anatomical understanding more intuitive and less dependent on each professional’s accumulated experience
This is where the concept of the digital twin stops being theoretical.
Are they truly digital twins?
A fully developed digital twin, strictly speaking, would involve not only anatomical representation but also dynamic simulation in real time: blood flow, tissue behavior, biomechanical response.
In surgery, we are taking the first steps in that direction. Today it is already possible to generate personalized 3D models, plan resections with millimetric precision, evaluate tumor margins, or study uncommon anatomical variations. The next step will be to integrate predictive models capable of simulating intraoperative scenarios.
Beyond the technological appeal, however, the real value lies in the clinical impact. A personalized 3D model reduces uncertainty before entering the operating room, improves decision-making, can shorten surgical time, and helps avoid risks near critical structures.
Hospitals already working with advanced 3D surgical planning report a clear improvement in surgeons’ confidence before surgery. And in surgery, confidence supported by accurate information translates directly into greater patient safety.
A distant future or an evolving present?
Ten years ago, talking about artificial intelligence in surgical planning sounded premature. Today, it is a regulated and rapidly growing reality.
With advances in automatic segmentation and medical image processing, the development of increasingly sophisticated surgical digital twins is no longer a matter of possibility, but of pace.
What we are witnessing is not a sudden revolution. It is a gradual transition toward more predictive, more personalized, and more data-driven surgery.
The deepest challenge, however, is not technological but cultural. Integrating these models requires changing planning dynamics that have been established for decades, and that takes training, time, and institutional commitment. But as with many other medical innovations, once the difference in understanding and precision is experienced, it becomes difficult to go back.
Surgical digital twins represent today the most solid step yet toward truly personalized surgical planning, where every patient has their own digital representation before the surgeon makes the first incision.
Perhaps the real question is no longer whether they will become standard, but how long it will take before we simply take them for granted.
