Comparison between artificial intelligence-based and manual organ delineations in pretreatment computed tomography scans of prostate cancer patients: a visual grading study.
Authors
Affiliations (13)
Affiliations (13)
- Department of Radiology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Medicinaregatan 3, Medicinareberget, 413 90, Gothenburg, Region Västra Götaland, Sweden.
- Department of Radiology, Sahlgrenska University Hospital, Blå Stråket 5, Region Västra Götaland, 413 45, Gothenburg, Sweden.
- Department of Electrical Engineering, Chalmers University of Technology, Hörsalsvägen 9-11, Region Västra Götaland, 412 96, Gothenburg, Sweden.
- Eigenvision AB, Bredgatan 4, 211 30, Region Skåne, Malmö, Sweden.
- Department of Oncology, Sahlgrenska University Hospital, Blå Stråket 2, Region Västra Götaland, 413 45, Gothenburg, Sweden.
- Department of Oncology, Institute of Clinical Sciences, University of Gothenburg, Medicinaregatan 3, Medicinareberget, 413 90, Gothenburg, Region Västra Götaland, Sweden.
- Department of Oncology and Radiotherapy, Region Kronoberg, Central lasarett Växjö, Strandvägen 8, 351 85, Växjö, Sweden.
- Clinical Physiology and Nuclear Medicine, Lund University and Skåne University Hospital, 221 85, Malmö, Region Skåne, Sweden.
- Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Blå Stråket 5, 413 45, Region Västra Götaland, Gothenburg, Sweden.
- Department of Urology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Medicinaregatan 5, Medicinareberget, 413 90, Region Västra Götaland, Gothenburg, Sweden.
- Department of Urology, Sahlgrenska University Hospital, Blå Stråket 5, 413 45, Region Västra Götaland, Gothenburg, Sweden.
- Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Medicinaregatan 5, Medicinareberget, 413 90, Region Västra Götaland, Gothenburg, Sweden.
- Department of Biomedical Engineering and Medical Physics, Sahlgrenska University Hospital, Blå Stråket 5, 413 45, Region Västra Götaland, Gothenburg, Sweden.
Abstract
This study aimed to evaluate the clinical acceptability of artificial intelligence (AI)-based organ segmentations on pretreatment CT images of prostate cancer patients using manual organ delineations as a reference. Paired AI-based segmentations and manual delineations of the prostate, urinary bladder, and rectum were evaluated by three observers, according to a 4-grade Likert-scale, based on quality criteria, developed through a Delphi process. Visual grading characteristics (VGC) analysis was performed. When comparing the ratings of AI-based (n = 360) and manual delineations (n = 360), the area under the VGC-curve (AUCVGC) was 0.36 (95% CI 0.27-0.44), 0.35 (95% CI 0.28-0.41), and 0.3 (95% CI 0.22-0.40) for the prostate, urinary bladder, and rectum, respectively, indicating inferior ratings for the algorithm. Few AI segmentations (8%) were considered clinically unacceptable, while in 67% no or minor changes were needed. Despite superior ratings for manual delineations, most AI-segmentations needed no or minor changes, indicating clinical acceptability.