In a phase III randomized trial, adding a radiation boost to tumor(s) visible on MRI improved prostate cancer (PCa) disease-free and metastasis-free survival without additional toxicity. Radiation oncologists' ability to identify prostate tumors is critical to widely adopting intraprostatic tumor radiotherapy boost for patients. A diffusion MRI biomarker, called the Restriction Spectrum Imaging restriction score (RSIrs), has been shown to improve radiologists' identification of clinically significant PCa. We hypothesized that (1) radiation oncologists would find accurately delineating PCa tumors on conventional MRI challenging and (2) using RSIrs maps would improve radiation oncologists' accuracy for PCa tumor delineation.
In this multi-institutional, international, prospective study, 44 radiation oncologists (participants) and 2 expert radiologists (experts) contoured prostate tumors on 39 total patient cases using conventional MRI with or without RSIrs maps. Participant volumes were compared to the consensus expert volumes. Contouring accuracy metrics included percent overlap with expert volume, Dice coefficient, conformal number, and maximum distance beyond expert volume.
1604 participant volumes were produced. 40 of 44 participants (91%) completely missed ≥1 expert-defined target lesion without RSIrs, compared to 13 of 44 (30%) with RSIrs maps. On conventional MRI alone, 134 of 762 contour attempts (18%) completely missed the target, compared to 18 of 842 (2%) with RSIrs maps. Use of RSIrs maps improved all contour accuracy metrics by approximately 50% or more. Mixed effects modeling confirmed that RSIrs maps were the main variable driving improvement in all metrics. System Usability Scores indicated RSIrs maps significantly improved the contouring experience (72 vs. 58, p<0.001).
Radiation oncologists struggle with accurately delineating visible PCa tumors on conventional MRI. RSIrs maps improve radiation oncologists' ability to target MRI-visible tumors for prostate tumor boost.
International journal of radiation oncology, biology, physics. 2023 Jul 13 [Epub ahead of print]
Asona J Lui, Karoline Kallis, Allison Y Zhong, Troy S Hussain, Christopher Conlin, Leonardino A Digma, Nikki Phan, Ian T Mathews, Deondre D Do, Mariluz Rojo Domingo, Roshan Karunamuni, Joshua Kuperman, Anders M Dale, Ahmed Shabaik, Rebecca Rakow-Penner, Michael E Hahn, Tyler M Seibert
Department of Radiation Medicine and Applied Sciences, UC San Diego School of Medicine, La Jolla, CA, USA., Department of Radiation Medicine and Applied Sciences, UC San Diego School of Medicine, La Jolla, CA, USA; UC San Diego School of Medicine, La Jolla, CA, USA., 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 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 Pathology, 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 Radiation Medicine and Applied Sciences, 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. Electronic address: .