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Clinical Evaluation of AI-Assisted Virtual Contrast Enhanced MRI in Primary Gross Tumor Volume Delineation for Radiotherapy of Nasopharyngeal Carcinoma

Publication ,  Conference
Li, W; Zhao, D; Chen, Z; Huang, Z; Lam, S; Xie, Y; Qin, W; Cheung, ALY; Xiao, H; Liu, C; Lee, FKH; Au, KH; Lee, VHF; Cai, J; Li, T
Published in: Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics
January 1, 2023

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.

Duke Scholars

Published In

Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

January 1, 2023

Volume

14226 LNCS

Start / End Page

541 / 550

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

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Li, W., Zhao, D., Chen, Z., Huang, Z., Lam, S., Xie, Y., … Li, T. (2023). Clinical Evaluation of AI-Assisted Virtual Contrast Enhanced MRI in Primary Gross Tumor Volume Delineation for Radiotherapy of Nasopharyngeal Carcinoma. In Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics (Vol. 14226 LNCS, pp. 541–550). https://doi.org/10.1007/978-3-031-43990-2_51
Li, W., D. Zhao, Z. Chen, Z. Huang, S. Lam, Y. Xie, W. Qin, et al. “Clinical Evaluation of AI-Assisted Virtual Contrast Enhanced MRI in Primary Gross Tumor Volume Delineation for Radiotherapy of Nasopharyngeal Carcinoma.” In Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 14226 LNCS:541–50, 2023. https://doi.org/10.1007/978-3-031-43990-2_51.
Li W, Zhao D, Chen Z, Huang Z, Lam S, Xie Y, et al. Clinical Evaluation of AI-Assisted Virtual Contrast Enhanced MRI in Primary Gross Tumor Volume Delineation for Radiotherapy of Nasopharyngeal Carcinoma. In: Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics. 2023. p. 541–50.
Li, W., et al. “Clinical Evaluation of AI-Assisted Virtual Contrast Enhanced MRI in Primary Gross Tumor Volume Delineation for Radiotherapy of Nasopharyngeal Carcinoma.” Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, vol. 14226 LNCS, 2023, pp. 541–50. Scopus, doi:10.1007/978-3-031-43990-2_51.
Li W, Zhao D, Chen Z, Huang Z, Lam S, Xie Y, Qin W, Cheung ALY, Xiao H, Liu C, Lee FKH, Au KH, Lee VHF, Cai J, Li T. Clinical Evaluation of AI-Assisted Virtual Contrast Enhanced MRI in Primary Gross Tumor Volume Delineation for Radiotherapy of Nasopharyngeal Carcinoma. Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics. 2023. p. 541–550.

Published In

Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

January 1, 2023

Volume

14226 LNCS

Start / End Page

541 / 550

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences