Status
Conditions
Treatments
About
This study is investigating how AI can help doctors outline the prostate on an ultrasound image to make a custom radiation plan during a specialized type of radiation treatment for prostate cancer called brachytherapy.
Full description
This is a Phase II prospective study evaluating the standard U-net, a deep learning AI algorithm for auto-contouring of the prostate during HDR prostate brachytherapy with the needles in place by new learners. Contouring will be done on TRUS. The study will be conducted with a randomized design. Each patient will be assigned to a new learner and then randomized to manual versus AI-assisted contouring. The randomization will be stratified by new learner type: resident versus fellow/new attending. The hypothesis is that AI-assisted learner contours will have improved Dice coefficients with respect to clinically approved contours compared with manual learner contours. All brachytherapy contours will undergo review by the treating radiation oncologist who is the experienced clinician for clinical approval prior to patient treatment. The experienced clinician will be blinded to the randomization.
Enrollment
Sex
Ages
Volunteers
Inclusion criteria
Exclusion criteria
Primary purpose
Allocation
Interventional model
Masking
36 participants in 2 patient groups
Loading...
Central trial contact
Jaime Vladimir Mendoza, BA; Nataliya Moldovan, MD
Data sourced from clinicaltrials.gov
Clinical trials
Research sites
Resources
Legal