ArticleCancer imaging : the official publication of the International Cancer Imaging Society2025
Diagnostic performance of amide proton transfer-weighted imaging and four advanced diffusion-weighted MRI models for meningioma grading and subtyping.
Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
objectiveTo 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.
methodsAPTw 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.
resultsThe 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).
conclusionIntegrating APTw-based molecular information with diffusion-model-derived microstructural data represents a promising approach to meningioma grading and subtyping.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.