The focal radiotherapy (RT) boost technique was shown in a phase III randomized controlled trial (RCT) to improve prostate cancer outcomes without increasing toxicity. This technique relies on the accurate delineation of prostate tumors on MRI. A recent prospective study evaluated radiation oncologists' accuracy when asked to delineate prostate tumors on MRI and demonstrated high variability in tumor contours. We sought to evaluate the impact of contour variability and inaccuracy on predicted clinical outcomes. We hypothesized that radiation oncologists' contour inaccuracies would yield meaningfully worse clinical outcomes.
45 radiation oncologists and 2 expert radiologists contoured prostate tumors on 30 patient cases. Of these cases, those with CT simulation or diagnostic CT available were selected for analysis. A knowledge-based planning model was developed to generate focal RT boost plans for each contour per the RCT protocol. Probability of biochemical failure (BF) was determined using a model from the RCT. The primary metric evaluated was delta BF (ΔBF = Participant BF - Expert BF). An absolute increase in BF ≥5% was considered clinically meaningful.
8 patient cases and 394 target volumes for focal RT boost planning were included in this analysis. In general, participant plans were associated with worse predicted clinical outcomes compared to the expert plan, with an average absolute increase in BF of 4.3%. 37% of participant plans were noted to have an absolute increase in BF of 5% or more.
Radiation oncologists' attempts to contour tumor targets for focal RT boost are frequently inaccurate enough to yield meaningfully inferior clinical outcomes for patients.
International journal of radiation oncology, biology, physics. 2024 Jun 24 [Epub ahead of print]
Allison Y Zhong, Asona J Lui, Svetlana Kuznetsova, Karoline Kallis, Christopher Conlin, Deondre D Do, Mariluz Rojo Domingo, Ryan Manger, Patricia Hua, Roshan Karunamuni, Joshua Kuperman, Anders M Dale, Rebecca Rakow-Penner, Michael E Hahn, Uulke A van der Heide, Xenia Ray, Tyler M Seibert
Department of Radiation Medicine and Applied Sciences, UC San Diego School of Medicine, La Jolla, CA, USA., Department of Radiology, UC San Diego School of Medicine, La Jolla, CA, USA., Department of Bioengineering, UC San Diego Jacobs School of Engineering, La Jolla, CA, USA., Department of Radiology, UC San Diego School of Medicine, La Jolla, CA, USA; Department of Neurosciences, UC San Diego School of Medicine, La Jolla, CA, USA; Halıcıoğlu Data Science Institute, UC San Diego School of Medicine, La Jolla, CA, USA., Department of Radiology, UC San Diego School of Medicine, La Jolla, CA, USA; Department of Bioengineering, UC San Diego Jacobs School of Engineering, La Jolla, CA, USA., Department of Radiation Oncology, The Netherlands Cancer Institute (NKI-AVL), Amsterdam, The Netherlands., Department of Radiation Medicine and Applied Sciences, UC San Diego School of Medicine, La Jolla, CA, USA; Department of Radiology, UC San Diego School of Medicine, La Jolla, CA, USA; Department of Bioengineering, UC San Diego Jacobs School of Engineering, La Jolla, CA, USA. Electronic address: .