NCT06469606

Study on Female Patients' Mammographic Texture Features

A Cohort Study on feMale Patients' mammogRaphic texturE featureS: the COMPRESS Trial

• Status: Not Yet Recruiting
• Phase: N/A
• Study type: Interventional
• Enrollment: 200 (estimated)
• Sponsor: Tampere University Hospital · Academic / Other
• Sex: Female
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

Mammography is the most common method for breast imaging, and it provides information for model building and analysis. Radiomics applied to mammography has the potential to revolutionize clinical decision-making by providing valuable insights into risk assessment and disease detection. Despite this, the influence of imaging parameters and clinical and biological factors on radiological texture features remains poorly understood. There is a pressing need to overcome the obstacle of system-inherent effects on mammographic images to facilitate the translation of radiological texture features into routine clinical practice by enabling reliable and robust AI-based or AI-aided decision-making. Furthermore, understanding the relationship between imaging parameters, textural features, and clinical and biological information supports the clinical use of AI. The objective of this study is to evaluate AI methods for clinical practice and to study how it relates to clinical factors and biological features.

Conditions

• Breast Cancer
• Artificial Intelligence
• Mammography

Interventions

Type	Name	Description
DEVICE	AI tool	Both the arms will undergo the use of "AI tool" developed in the group. The tool will be trained to detect outcomes.

Timeline

• Start date: 2024-06-17
• Primary completion: 2035-12-15
• Completion: 2038-12-15
• First posted: 2024-06-21
• Last updated: 2024-06-21