Work

Diagnostic performance of amide proton transfer-weighted imaging and four advanced diffusion-weighted MRI models for meningioma grading and subtyping

Year: 2025

Type: article

Abstract: OBJECTIVE: To compare the diagnostic performance of amide proton transfer-weighted (APTw), diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI), and mean apparent propagator (MAP) in meningioma grading and subtyping. METHODS: APTw and diffusion spectrum imaging were performed in 110 meningiomas (26 males, 26–84 years), which were classified into 81 low-grade meningiomas (LGMs, grade 1) and 29 high-grade meningiomas (HGMs, grades 2 and 3). Among LGMs, 30 fibrous, 19 meningothelial, and 22 transitional meningiomas were further analyzed. The whole-tumor median values were obtained from APTw and diffusion images. The Mann-Whitney U test and Kruskal-Wallis test were applied for meningioma grading and subtyping, respectively. The receiver operating characteristic (ROC) curve and logistic regression analysis were used to evaluate the diagnostic performance. RESULTS: The APTw_MTRasym (magnetization transfer-ratio asymmetry), DKI_AK (axial kurtosis), DKI_MK (mean kurtosis), DKI_MKT (mean kurtosis tensor), MAP_RTPP (return-to-plane probability), and NODDI_ODI (orientation dispersion index) were significantly higher, while the DTI_AD (axial diffusivity) and DTI_MD (mean diffusivity) were significantly lower in HGMs than those of LGMs (all p < 0.05). Compared with APTw, DTI, DKI, MAP, and NODDI models, the combined model integrating APTw and four diffusion models showed superior diagnostic performance (AUC [area under the curve] = 0.881, all corrected p < 0.05) in meningioma grading, with improved IDI (integrated discrimination improvement, 0.320–0.360). The combined model integrating APTw_MTRasym and DTI_FA (fractional anisotropy) achieved the highest AUC of 0.981 in differentiating fibrous from meningothelial meningiomas, with increased IDI (0.153–0.494). CONCLUSION: Integrating APTw-based molecular information with diffusion-model-derived microstructural data represents a promising approach to meningioma grading and subtyping.

Source: Cancer Imaging

DOI: 10.1186/s40644-025-00963-0