A1 Journal article – refereed

Validation of automated magnetic resonance image segmentation for radiation therapy planning in prostate cancer




List of Authors: Anna Kuisma, Iiro Ranta, Jani Keyriläinen, Sami Suilamo, Pauliina Wright, Marko Pesola, Lizette Warner, Eliisa Löyttyniemi, Heikki Minn

Publisher: Elsevier Ireland Ltd

Publication year: 2020

Journal: Physics and Imaging in Radiation Oncology

Journal name in source: Physics and Imaging in Radiation Oncology

Volume number: 13

ISSN: 2405-6316

eISSN: 2405-6316

DOI: http://dx.doi.org/10.1016/j.phro.2020.02.004


Abstract

Background and purpose

Magnetic resonance imaging (MRI) is increasingly used in radiation therapy planning of prostate cancer (PC) to reduce target volume delineation uncertainty. This study aimed to assess and validate the performance of a fully automated segmentation tool (AST) in MRI based radiation therapy planning of PC.

Material and methods

Pelvic structures of 65 PC patients delineated in an MRI-only workflow according to established guidelines were included in the analysis. Automatic vs manual segmentation by an experienced oncologist was compared with geometrical parameters, such as the dice similarity coefficient (DSC). Fifteen patients had a second MRI within 15 days to assess repeatability of the AST for prostate and seminal vesicles. Furthermore, we investigated whether hormonal therapy or body mass index (BMI) affected the AST results.

Results

The AST showed high agreement with manual segmentation expressed as DSC (mean, SD) for delineating prostate (0.84, 0.04), bladder (0.92, 0.04) and rectum (0.86, 0.04). For seminal vesicles (0.56, 0.17) and penile bulb (0.69, 0.12) the respective agreement was moderate. Performance of AST was not influenced by neoadjuvant hormonal therapy, although those on treatment had significantly smaller prostates than the hormone-naïve patients (p < 0.0001). In repeat assessment, consistency of prostate delineation resulted in mean DSC of 0.89, (SD 0.03) between the paired MRI scans for AST, while mean DSC of manual delineation was 0.82, (SD 0.05).

Conclusion

Fully automated MRI segmentation tool showed good agreement and repeatability compared with manual segmentation and was found clinically robust in patients with PC. However, manual review and adjustment of some structures in individual cases remain important in clinical use.


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Last updated on 2021-24-06 at 08:50