Quantification of delineation errors of the gross tumor volume on magnetic resonance imaging in uterine cervical cancer using pathology data and deformation correction.

Journal: Acta Oncologica (Stockholm, Sweden)
Published:
Abstract

Background: To safely optimize target volumes using magnetic resonance imaging (MRI) for uterine cervical cancer radiation therapy, MRI findings need to be validated. The aim of this study was to correlate pre-operatively acquired MRI and surgical specimen imaging for uterine cervical cancer patients using deformable image registration and quantify gross tumor volume (GTV) delineation discrepancies.

Methods: For 16 retrospectively selected early-stage uterine cervical cancer patients, the cervix-uterus structure, uterine cavity and the GTV were delineated on 2D pathology photos after macroscopic intersection and corresponding pre-operatively acquired T2-weighted 2D sagittal MR images. Segmentations of pathology photos and MR images were simultaneously registered using a three-step multi-image registration strategy. The registration outcome was evaluated by the Dice similarity coefficient (DSC) and the surface distance error (SDE). In addition, GTV expansions within the cervix-uterus structure needed to obtain 95% GTV coverage were determined.

Results: After three-step multi-image registration, the median DSC and median SDE were 0.98 and 0.4 mm (cervix-uterus) and 0.90 and 0.4 mm (uterine cavity), respectively. The average SDE around the GTV was 0.7 mm (range, 0.1 mm - 2.6 mm). An underestimation of MRI-based GTV delineations was found when no margin was applied, indicated by a mean GTV coverage of 61%. To obtain 95% GTV coverage for 90% of the patients, a minimum 12.0 mm margin around MRI-based GTVs was needed.

Conclusions: The presented three-step multi-image registration strategy was suitable and accurate to correlate MRI and pathology data for uterine cervical cancer patients. To cover the pathology-based GTV, a margin of at least 12.0 mm around GTV delineations on T2-weighted MRI is needed.

Relevant Conditions

Cervical Cancer, Hysterectomy