A Novel Method to Compute the Contact Surface Area Between an Organ and Cancer Tissue

Area of Science:

• Medical imaging
• Oncology
• Surgical planning

Background:

• Contact surface area (CSA) is crucial for kidney cancer outcomes.
• Current CSA methods are limited by shape assumptions and manual input.
• Accurate CSA measurement is needed for better surgical planning.

Purpose of the Study:

• To introduce a novel, accurate method for estimating kidney tumor contact surface area (CSA) using 3D reconstructions from CT scans.
• To develop and validate an open-source tool for CSA computation.
• To compare the novel method's accuracy against existing techniques and radiologist assessments.

Main Methods:

• Developed a segmentation protocol and mesh processing algorithm for 3D CT reconstructions.
• Created an open-source software with a graphical user interface for CSA calculation.
• Validated the method on synthetic data and retrospectively on 82 patient CT scans.
• Conducted a double-blind study comparing the novel method with Hsieh's method and radiologist measurements.

Main Results:

• The novel algorithm demonstrated minimal error on synthetic data.
• The method showed reliability and consistency when compared to expert radiologist measurements.
• The developed tool provides an accurate and reproducible CSA estimate, outperforming subjective measurements.

Conclusions:

• The proposed 3D CT-based method offers an accurate and reliable approach to estimating kidney tumor contact surface area (CSA).
• This tool has the potential to improve the prediction of perioperative outcomes in kidney cancer.
• The open-source availability facilitates wider adoption and further research in surgical oncology.