  With "contact surface area" (CSA) we refers to the area of contact between a
tumor and an organ. This indicator has been identified as a predictive factor
for surgical peri-operative parameters, particularly in the context of kidney
cancer. However, state-of-the-art algorithms for computing the CSA rely on
assumptions about the tumor shape and require manual human annotation. In this
study, we introduce an innovative method that relies on 3D reconstructions of
tumors and organs to provide an accurate and objective estimate of the CSA. Our
approach consists of a segmentation protocol for reconstructing organs and
tumors from Computed Tomography (CT) images and an algorithm leveraging the
reconstructed meshes to compute the CSA. With the aim to contributing to the
literature with replicable results, we provide an open-source implementation of
our algorithm, along with an easy-to-use graphical user interface to support
its adoption and widespread use. We evaluated the accuracy of our method using
both a synthetic dataset and reconstructions of 87 real tumor-organ pairs.
