Gadolinium-Free MR Perfusion Imaging Based on Generative Adversarial Network for Primary Intracranial Tumor Diagnosis: A Multi-Center Study
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ID: 318940
2026
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Abstract
BACKGROUND: Accurate evaluation of tumor vascularity is essential in neuro-oncology, but conventional cerebral blood volume (CBV) mapping depends on gadolinium-based contrast agents. The aim was to develop a gadolinium-free model to synthesize CBV (CBVsyn) maps from non-contrast MRI (NC-MRI). MATERIALS AND METHODS: This multicenter retrospective study analyzed 1227 MRI examinations in patients with primary intracranial tumors, comprising an internal cohort (train/validation/test 438/126/63) and two external cohorts (UPENN-GBM Cohort 464; UCSD-PTGBM cohort 136). A tumor-aware generative adversarial network (TA-GAN) was implemented to synthesize CBVsyn maps from various NC-MRI combinations. Image quality was evaluated using structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and a 4-point Likert scale. The correlation between pathologic markers and CBV parameters was conducted. Diagnostic performance was compared between CBVsyn and DSC-PWI-derived CBV (CBVreal) maps. The incremental diagnostic value of CBVsyn was evaluated. RESULTS: TA-GAN utilizing T2-weighted and diffusion-weighted imaging achieved best performance in CBVsyn synthesis (PSNRGlobal=25.52 ± 1.33dB, SSIMGlobal=67.53 ± 5.88; both P < .05), with 95.34% maps being diagnostically acceptable. CBVsyn parameters showed positive correlation with CD105 markers (r = 0.49, P = .03). CBVsyn maps demonstrated comparable AUC with CBVreal maps for intracranial tumors grading (0.61 vs. 0.66, P = .51), pediatric glioma (0.60 vs. 0.57; P = .57), adult glioma (0.68 vs. 0.73; P = .56), and IDH1 genotype (0.66 vs. 0.81; P = .03). NC-MRI with CBVsyn assistance improved diagnostic accuracy (84.48% vs.75.86%) and consistency (κ = 0.83 vs. 0.62) for glioma grading compared with NC-MRI alone. CONCLUSION: As a gadolinium-free alternative, CBVsyn maps synthesized by TA-GAN correlates with pathologic findings and demonstrates promise for characterizing primary intracranial tumors.
| Reference Key |
openalex_W7166148130
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| Authors | Lin Gj, Wangbin Ding, Yihua Chen, Lukui Xiong, Junhuan Hong, Pingping He, Yuwei Pan, Minxuan Tian, Jiahao Tao, Wei Guo, Yan Su, Ming Chen, Dejun She |
| Journal | journal of neuro-oncology |
| Year | 2026 |
| DOI |
10.1093/neuonc/noag144
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| URL | |
| Keywords | Keywords not found |
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