Study on Female Patients' Mammographic Texture Features

Not Applicable

Not yet recruiting

• Conditions: Breast Cancer; Artificial Intelligence; Mammography
• Interventions: Device: AI tool

• Registration Number: NCT06469606
• Lead Sponsor: Tampere University Hospital

Brief 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.

Detailed Description

Not available

Study Timeline

• Study First Submitted: 2024-05-30
• Status Verified: 2024-06
• Study Start: 2024-06-17
• Study First Submitted QC: 2024-06-17
• Last Update Submitted: 2024-06-17
• Study First Posted: 2024-06-21
• Last Update Posted: 2024-06-21
• Primary Completion: 2035-12-15
• Study Completion: 2038-12-15

Recruitment & Eligibility

• Status: NOT_YET_RECRUITING
• Sex: Female
• Target Recruitment: 200

Inclusion Criteria

• Candidate is a biological female aged 18 years or above;
• Candidate is willing and able to give informed consent and gives their written consent for the participation in the study;
• There is a clinical indication for a uni- or bilateral mastectomy

Exclusion Criteria

• Candidate lacks the capacity to provide informed consent;
• Candidate has breast implants

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: SINGLE_GROUP

Arm && Interventions

Group	Intervention	Description
Participant diagnosed with breast cancer	AI tool	Participants diagnosed with breast cancer who will undergo a mastectomy operation
Participant not diagnosed with breast cancer	AI tool	Participants who will undergo a mastectomy operation for a non-breast cancer related clinical indication

Primary Outcome Measures

Name	Time	Method
Mammographic texture features	Through study completion, an average of 5 year	Aim: to evaluate how imaging parameters affect the mammographic texture features

Secondary Outcome Measures

Name	Time	Method
Biological features	through study completion, an average of 10 year	Aim: To evaluate whether there is an interplay between mammographic texture feature parameters and pathological and biological features (e.g., breast cancer biomarkers)