AI Algorithm-Informed Biopsy for Prostate Cancer
What You Need to Know Before You Apply
What is the purpose of this trial?
This trial tests a new application of artificial intelligence (AI) to improve prostate cancer detection. The AI, a bi-parametric MRI-based cascaded deep-learning algorithm, analyzes MRI scans to identify potentially cancerous areas. It aims to enhance detection in patients with unclear or low-risk MRI results but who exhibit other high-risk signs, such as elevated PSA levels (a protein in the blood that can indicate prostate cancer). This trial targets men who recently had an MRI showing uncertain areas and have high PSA levels or other risk factors, like a family history of prostate cancer. As an unphased trial, it offers participants the chance to contribute to groundbreaking research that could enhance prostate cancer detection for future patients.
Will I have to stop taking my current medications?
The trial information does not specify whether you need to stop taking your current medications. It's best to discuss this with the trial team or your doctor.
What prior data suggests that this AI algorithm is safe for prostate cancer detection?
Research has shown that deep learning AI, like the one used in this trial, has been tested with promising results. In one study, these AI systems effectively identified cancerous areas on prostate MRI scans. Another study found that the AI's ability to detect prostate cancer matched that of experienced radiologists.
The AI model used in this trial has been tested for its ability to find prostate cancer using MRI scans. It performed well, particularly in identifying cancer in patients with larger prostate glands. While these studies focused on the AI's effectiveness rather than its safety, they suggest that the AI process is safe since it only involves analyzing images, not interacting with the body directly.
Overall, the AI has successfully detected prostate issues without any reported side effects, as it doesn't involve physical contact or invasive procedures. This suggests that participating in a trial using this AI method should be safe regarding the AI component itself.12345Why are researchers excited about this trial?
Researchers are excited about this trial because it explores a cutting-edge AI algorithm designed to enhance prostate cancer detection. Unlike the standard of care, which involves systematic and MRI-targeted biopsies, this AI-driven method uses advanced bi-parametric MRI scans to provide precise segmentations of prostate tissues and lesions. This could potentially improve the accuracy of diagnosing prostate cancer, especially in cases where existing methods may yield ambiguous results. By leveraging deep learning, this approach aims to identify cancerous lesions earlier and with greater accuracy, which could lead to better treatment outcomes for patients with equivocal or negative MRI findings but high clinical risk.
What evidence suggests that the AI algorithm is effective for prostate cancer detection?
This trial will compare a deep learning AI program with standard perilesional prostate biopsy. Studies have shown that the AI program effectively identifies cancerous spots in prostate MRI scans. It uses special MRI images to detect suspicious areas with high accuracy. Research indicates that the AI's results match those of doctors in detecting prostate cancer. This suggests that AI-assisted detection could reliably identify significant prostate cancer cases, especially when MRI results are unclear.16789
Who Is on the Research Team?
Ahmet M Aydin, MD
Principal Investigator
University of Arkansas
Are You a Good Fit for This Trial?
This trial is for men aged 40 or older who have had a recent prostate MRI showing uncertain or low-risk lesions, along with high PSA levels or other risk factors like suspicious exam results, certain genetic risks, family history, or being of Black/African American ancestry. Participants must be in good physical health.Inclusion Criteria
Timeline for a Trial Participant
Screening
Participants are screened for eligibility to participate in the trial
Phase I Feasibility
Assess the acceptance rate of randomization and biopsy recommendations based on study protocol and AI algorithm results by the patients
Phase II Efficacy
Evaluate the per-patient and per-lesion csPCa detection rates of AI algorithm-informed biopsy versus contemporary biopsy
Follow-up
Participants are monitored for safety, adverse events, and quality of life measures after biopsy procedures
What Are the Treatments Tested in This Trial?
Interventions
- Bi-parametric MRI-based cascaded deep-learning AI algorithm
Trial Overview
The study tests whether using an AI algorithm to guide prostate biopsies can better detect significant prostate cancer compared to standard methods in patients with unclear or low-risk MRI findings but higher clinical risk.
How Is the Trial Designed?
2
Treatment groups
Experimental Treatment
Active Control
The AI model inputs biparametric DICOM sequences (T2-weighted images, high-b-value diffusion-weighted images, and apparent diffusion coefficient maps), and the outputs include binary prostate organ and intraprostatic lesion segmentations. This study will assess a recently developed and both internally and externally validated AI algorithm for PCa detection capability in patients with equivocal lesions (PI-RADS 3 lesions) and negative lesions (PI-RADS 1-2 lesions) with higher clinical risk features such as high PSA density.
Standard of care prostate biopsy which is a systematic template biopsy (with 12 biopsy cores) + MRI-targeted biopsy (for PI-RADS category 3 lesions only, with 3 biopsy cores), consistent with current NCCN guideline recommendations
Find a Clinic Near You
Who Is Running the Clinical Trial?
University of Arkansas
Lead Sponsor
Citations
Evaluation of a Cascaded Deep Learning–based Algorithm for ...
A deep learning–based algorithm automatically detected cancerous lesions on prostate biparametric MRI scans with reasonable performance and ...
A Cascaded Deep Learning–Based Artificial Intelligence ...
We aimed to develop and test a cascaded deep learning detection and classification system trained on biparametric prostate MRI using PI-RADS for assisting ...
A Cascaded Deep Learning-Based Artificial ... - PubMed
Our cascaded U-Net, residual network architecture can detect, classify cancer suspicious lesions at prostate MRI with good detection, reasonable classification ...
Evaluation of a Cascaded Deep Learning–based Algorithm ...
A deep learning–based algorithm automatically detected cancerous lesions on prostate biparametric MRI scans with reasonable performance and reliably ...
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bjui-journals.onlinelibrary.wiley.com
bjui-journals.onlinelibrary.wiley.com/doi/full/10.1002/bco2.373Evaluating a deep learning AI algorithm for detecting residual ...
Our study investigates the efficacy of a biparametric MRI (bpMRI)-based deep learning algorithm for post-FT PCa identification. This ...
Evaluating Artificial Intelligence–Assisted Prostate ...
We used a cascaded, deep learning–based AI algorithm for PCa detection, developed within the Molecular Imaging Branch of the National Cancer ...
MRI-based Deep Learning Algorithm for Assisting ...
A commercial MRI-based deep learning algorithm for prostate cancer detection showed greater positive predictive value, despite its lower sensitivity.
Evaluation of a Deep Learning-based Algorithm for Post ...
A bpMRI-based AI model detected most locally radiorecurrent cancers. The AI model performance was comparably better in patients with larger glands.
Evaluation of a Cascaded Deep Learning-based Algorithm ...
Prostate Cancer. Evaluation of a Cascaded Deep Learning-based Algorithm for Prostate Lesion Detection at Biparametric MRI. May 8, 2024.
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