Abstract
This study aims to investigate the clinical efficacy of AI generated virtual contrast-enhanced MRI (VCE-MRI) in primary gross-tumor-volume (GTV) delineation for patients with nasopharyngeal carcinoma (NPC). We retrospectively retrieved 303 biopsy-proven NPC patients from three oncology centers. 288 patients were used for model training and 15 patients were used to synthesize VCE-MRI for clinical evaluation. Two board-certified oncologists were invited for evaluating the VCE-MRI in two aspects: image quality and effectiveness in primary tumor delineation. Image quality of VCE-MRI evaluation includes distinguishability between real contrast-enhanced MRI (CE-MRI) and VCE-MRI, clarity of tumor-to-normal tissue interface, veracity of contrast enhancement in tumor invasion risk areas, and efficacy in primary tumor staging. For primary tumor delineation, the GTV was manually delineated by oncologists. Results showed the mean accuracy to distinguish VCE-MRI from CE-MRI was 53.33%; no significant difference was observed in clarity of tumor-to-normal tissue interface between VCE-MRI and CE-MRI; for the veracity of contrast enhancement in tumor invasion risk areas and efficacy in primary tumor staging, a Jaccard Index of 76.04% and accuracy of 86.67% were obtained, respectively. The image quality evaluation suggests that the quality of VCE-MRI is approximated to real CE-MRI. In tumor delineation evaluation, the Dice Similarity Coefficient and Hausdorff Distance of the GTVs that delineated from VCE-MRI and CE-MRI were 0.762 (0.673–0.859) and 1.932 mm (0.763 mm–2.974 mm) respectively, which were clinically acceptable according to the experience of the radiation oncologists. This study demonstrated the VCE-MRI is highly promising in replacing the use of gadolinium-based CE-MRI for NPC delineation.
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Data use Declaration:
The use of this dataset was approved by the Institutional Review Board of University of Hong Kong/Hospital Authority Hong Kong West Cluster (HKU/HA HKW IRB) with reference number UW21-412, and the Research Ethics Committee (Kowloon Central/Kowloon East) with reference number KC/KE-18-0085/ER-1. Due to the retrospective nature of this study, patient consent was waived.
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Acknowledgement
This research was partly supported by research grants of General Research Fund (GRF 15102219, GRF 15103520), the University Grants Committee, and Project of Strategic Importance Fund (P0035421), Projects of RISA (P0043001), One-line Budget (P0039824, P0044474), The Hong Kong Polytechnic University, and Shenzhen-Hong Kong-Macau S&T Program (Category C) (SGDX20201103095002019), Shenzhen Basic Research Program (R2021A067), Shenzhen Science and Technology Innovation Committee (SZSTI).
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Li, W. et al. (2023). Clinical Evaluation of AI-Assisted Virtual Contrast Enhanced MRI in Primary Gross Tumor Volume Delineation for Radiotherapy of Nasopharyngeal Carcinoma. In: Greenspan, H., et al. Medical Image Computing and Computer Assisted Intervention – MICCAI 2023. MICCAI 2023. Lecture Notes in Computer Science, vol 14226. Springer, Cham. https://doi.org/10.1007/978-3-031-43990-2_51
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DOI: https://doi.org/10.1007/978-3-031-43990-2_51
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