The new tool is expected to provide a data-driven approach to surgical planning for more than 270,000 patients a year diagnosed with breast cancer. Credit: Yuganov Konstantin/Shutterstock.com.

SimBioSys has launched TumorSight Plan, a clinical decision support tool designed to help enhance surgical planning for early-stage breast cancer.

It is said to be the first clinical decision support tool for supporting provider-patient decision-making and individualising surgical planning.

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The tool is expected to provide a data-driven approach to surgical planning for more than 270,000 patients a year who are diagnosed with breast cancer at an early stage in the US.

TumorSight Plan provides advanced visualisation, best practices and data-driven insights for surgeons to help support provider-patient interactions.

It leverages the capabilities of the TumorSight Viz, a 3D visualisation tool cleared by the US Food and Drug Administration (FDA) and is designed to support the increasing use of MRI imaging in breast cancer management.

With TumorSight Viz, clinicians can obtain 3D spatial visualisations of breast cancer with the help of standard-of-care medical imaging.

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SimBioSys said the TumorSight Plan and Viz are now accessible to breast surgeons nationwide.

SimBioSys CMO Barry Rosen said: “The reality is that the operation a woman has for breast cancer is often more dependent on the surgeon they see rather than their intrinsic disease due to lack of data-driven tools and approaches.

“Working with top surgeons across the US, we now can harness the power of AI to make surgical planning more of a science than an art. TumorSight Plan gives the breast cancer surgeon a platform and opportunity to enable more analytical patient-centric decision making, which should lead to a higher percentage of women undergoing breast conservation surgery.”

Earlier this year, SimBioSys obtained its 510(k) clearance from the FDA to market its first software application on its cloud-based digital precision medicine platform, TumorSight, which is intended for supporting the end-to-end patient journey.