Measurement of human peritoneal surface area using artificial intelligence software in abdominal computed tomography

Area of Science:

• Medical imaging
• Artificial intelligence in medicine
• Anatomy

Background:

• Accurate measurement of intraperitoneal organ surface area is vital for anatomical understanding and clinical research.
• Peritoneal surface area is a key factor in abdominal cavity studies.

Purpose of the Study:

• To measure intraperitoneal surface area in vivo using artificial intelligence (AI) and computed tomography (CT).
• To establish clinical indicators for abdominal cavity applications based on AI measurements.

Main Methods:

• CT images of healthy adults and colon cancer patients were analyzed.
• AI medical imaging software segmented and modeled the peritoneal surface.
• Organ surface areas were calculated, and abdominal cavity surface area was determined.

Main Results:

• The mean peritoneal surface area was 10,039 ± 241 cm², with males (10,224 ± 171 cm²) having a significantly larger area than females (9,854 ± 134 cm²).
• A statistically significant difference (P < 0.001) was observed in peritoneal surface area between males and females.

Conclusions:

• AI techniques enable reliable measurement of abdominal cavity surface area.
• This method is expected to provide foundational data for clinical applications.