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.

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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.