Investigation of Impact of AI on Prostate Cancer Workflow

Обзор

This study will enroll participants who are undergoing an MRI before a prostate biopsy due to suspected prostate cancer. The purpose of this study is to see if the use of Artificial Intelligence (AI) helps detect lesions on an MRI better than a radiologist not using AI. The AI Rad Companion (AIRC) Prostate MRI application is a software that uses measurements of the prostate and will be utilized in this study to help detect potential cancerous lesions. The AI software will assign the lesions a PI-RADS score, which is a way to measure the chance of the lesion being cancer. There are two parts to this study. The first part involves comparing the interpretation of prostate MRI images by a radiologist alone, a radiologist aided by AI, and AI alone. A systematic biopsy will be completed per standard of care. The radiologist may opt to include up to 2 additional AI-identified targets to biopsy in addition to those biopsied for standard of care. The second part of the study involves utilizing the MRI images from the first part of the study in addition to retrospective prostate MRI images. These de-identified images, along with Prostate Image Quality (PI-QUAL) scores, clinical data, and biopsy results will be sent to Siemens in order to aid in the development of methods to identify good or bad image quality in prostate MRI images.

Подробное описание

Prostate cancer is the most diagnosed cancer among men in the United States and the second most prevalent cancer in men worldwide (1,2). MRI can better triage patients to undergo biopsy, while providing information about tumors and treatment progress (4). However, there are challenges with MRI image quality, the interpretation of the images, and the potential for false positives and negatives. With the annual number of prostate exams rapidly increasing (5), there is a need for accurate and reliable prostate MRI interpretation. One proposed approach is to use an AI-based lesion detection software in addition to radiologists' interpretations. The Siemens Healthineers ("Siemens") business lines Digital \& Automation ("D\&A") and Magnetic Resonance ("MR") have developed the AI Rad Companion Prostate MRI (AIRC), which aids in the detection of potential prostate cancer. The goal of this study is to investigate the effects of the use of AIRC in improving the standard of care in prostate cancer detection and treatment. Participation in the study will be about an hour to review the consent form. All other study procedures (MRI, biopsy) will be standard of care.

Вмешательства

• Устройство AI
  Following the completion of a pre-biopsy prostate MRI, the radiologist will interpret the MRI. Once interpreted by the radiologist alone, the radiologist will interpret the scan while aided by AI. A systematic biopsy in conjunction with radiologist-identified targets will be completed per standard of care, with the optional inclusion of up to 2 AI-detected targets. When completing a biopsy per SOC, the prostate is divided into quadrants. In addition to noted targets, samples are taken systemati

Первичные конечные точки

• Readers' (radiologists') mean quadrant-level area under the receiver operating characteristic curve (AUC) in predicting the presence or absence of clinically significant prostate cancer (csPCa) [Срок оценки: One-time MRI, up to 30 days post-enrollment in study.]

Вторичные конечные точки (8)

• Inter-reader agreement on the presence/absence of csPCa at the participant-level [Срок оценки: One-time MRI, up to 30 days post-enrollment in study.]
• Inter-reader agreement on the presence/absence of csPCa at the quadrant-level [Срок оценки: One-time MRI, up to 30 days post-enrollment in study.]
• Participant-level sensitivity for detection of clinically significant prostate cancer [Срок оценки: One-time MRI, up to 30 days post-enrollment in study.]
• Participant-level specificity for detection of clinically significant prostate cancer [Срок оценки: One-time MRI, up to 30 days post-enrollment in study.]
• Quadrant-level sensitivity for detection of clinically significant prostate cancer [Срок оценки: One-time MRI, up to 30 days post-enrollment in study.]
• Quadrant-level specificity for detection of clinically significant prostate cancer [Срок оценки: One-time MRI, up to 30 days post-enrollment in study.]
• Free-response ROC curve for the aided and unaided reads [Срок оценки: One-time MRI, up to 30 days post-enrollment in study.]
• Comparison of the quadrant-level AUC of the unaided vs AI read [Срок оценки: One-time MRI, up to 30 days post-enrollment in study.]

Критерии участия

Критерии включения

• Plan of care is to undergo a biopsy of the prostate after a pre-biopsy MRI
• Age 55-80
• Prostate-specific antigen (PSA) between 3-10 ng/mL
• No prior diagnosis or treatment of prostate cancer

Критерии исключения

• Pre-biopsy MRI is of low quality
• PI-QUAL score of 1 using PI-QUAL version 2

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Распределение

Не применимо

Модель

Одна группа

Маскирование

Открытое

Основная цель

Скрининг

Центры проведения

США · 1 центр

• Cleveland Clinic Foundation — Cleveland

Идентификаторы

NCT: NCT07084779 · CASE3825

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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