Role of diffusion-weighted imaging in differentiating angiomatous meningioma from atypical meningioma

Liu, Xianwang; Wang, Yuzhu; Wei, Jinyan; Li, Shenglin; Xue, Caiqiang; Deng, Juan; Liu, Hong; Sun, Qing; Zhang, Xueling; Zhou, Junlin

doi:10.1016/j.clineuro.2022.107406

Cited by 7 publications

(5 citation statements)

References 20 publications

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“…The number, volume, proliferation rate, and nuclear atypia of tumor cells increase significantly with an increase in tumor grade. Previous studies have found that the more restricted the intracellular and extracellular water molecules, the lower the ADC values (11)(12)(13)(24)(25)(26).…”

Section: Discussionmentioning

confidence: 99%

“…For the nADC, the ADC of the normal white matter in the center of the semiovale was measured, and the value was divided by the ADC of the solid part of the tumor (nADC = lesion ADC mean /normal white matter ADC mean ). All ADC values were measured three times, and the average value was taken as the final statistic (13).…”

Section: Image Analysismentioning

confidence: 99%

“…Apparent diffusion coefficient (ADC) is a parameter originating from the diffusion-weighted imaging (DWI) sequence that can quantify the heterogeneity of brain tumors. It has been used for the identifying, grading, and predicting the gene statuses of brain tumors (8)(9)(10)(11)(12)(13). The Ki-67 proliferation index is a marker that directly reflects the specific physiological proliferation state of cells expressing Ki-67, which is a nuclear protein (14).…”

Section: Introductionmentioning

confidence: 99%

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The role of apparent diffusion coefficient in the grading of adult isocitrate dehydrogenase-mutant astrocytomas: relationship with the Ki-67 proliferation index

She,

Liu,

Jiang

et al. 2024

Acta Radiol

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Background The grading of adult isocitrate dehydrogenase (IDH)-mutant astrocytomas is a crucial prognostic factor. Purpose To investigate the value of conventional magnetic resonance imaging (MRI) features and apparent diffusion coefficient (ADC) in the grading of adult IDH-mutant astrocytomas, and to analyze the correlation between ADC and the Ki-67 proliferation index. Material and Methods The clinical and MRI data of 82 patients with adult IDH-mutant astrocytoma who underwent surgical resection and molecular genetic testing with IDH and 1p/19q were retrospectively analyzed. The conventional MRI features, ADCmin, ADCmean, and nADC of the tumors were compared using the Kruskal–Wallis single factor ANOVA and chi-square tests. Receiver operating characteristic (ROC) curves were drawn to evaluate conventional MRI and ADC accuracy in differentiating tumor grades. Pearson correlation analysis was performed to determine the correlation between ADC and the Ki-67 proliferation index. Results The difference in enhancement, ADCmin, ADCmean, and nADC among WHO grade 2, 3, and 4 tumors was statistically significant (all P <0.05). ADCmin showed the preferable diagnostic accuracy for grading WHO grade 2 and 3 tumors (AUC=0.724, sensitivity=63.4%, specificity=80%, positive predictive value (PPV)=62.0%; negative predictive value (NPV)=82.5%), and distinguishing grade 3 from grade 4 tumors (AUC=0.764, sensitivity=70%, specificity=76.2%, PPV=75.0%, NPV=71.4%). Enhancement + ADC model showed an optimal predictive accuracy (grade 2 vs. 3: AUC = 0.759; grade 3 vs. 4: AUC = 0.799). The Ki-67 proliferation index was negatively correlated with ADCmin, ADCmean, and nADC (all P <0.05), and positively correlated with tumor grade. Conclusion Conventional MRI features and ADC are valuable to predict pathological grading of adult IDH-mutant astrocytomas.

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Section: Discussionmentioning

confidence: 99%

Section: Image Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The role of apparent diffusion coefficient in the grading of adult isocitrate dehydrogenase-mutant astrocytomas: relationship with the Ki-67 proliferation index

She,

Liu,

Jiang

et al. 2024

Acta Radiol

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“…To better assess tumor heterogeneity, the ROI should encompass all tumor information at each level, including necrosis and cystic differentiation ( Vajapeyam et al, 2022 ). Additionally, the ROI outlined area should be slightly smaller than the visible tumor boundary, considering the effect of partial volume effects ( Liu et al, 2022b ). The outlined area was filled with red, and the software automatically generated a grayscale histogram of the ROI.…”

Section: Methodsmentioning

confidence: 99%

MRI histogram analysis of tumor-infiltrating CD8+ T cell levels in patients with glioblastoma

Xue

Qin

Zhang

et al. 2023

NeuroImage: Clinical

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“…Diffusion-weighted imaging (DWI) enables non-invasive assessment of the tumor microenvironment characteristics by examining the movement of water and is quantified by apparent diffusion coefficient (ADC) ( 9 , 10 ). However, due to tumor heterogeneity, ADC values obtained from the region of interest (ROI) of the local lesion do not fully reflect the overall characteristics of the tumor ( 11 ).…”

Section: Introductionmentioning

confidence: 99%

The value of whole-volume apparent diffusion coefficient histogram analysis in preoperatively distinguishing intracranial solitary fibrous tumor and transitional meningioma

Gang

Zhou

2023

Front. Oncol.

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PurposeTo investigate the value of whole-volume apparent diffusion coefficient (ADC) histogram analysis in preoperatively distinguishing intracranial solitary fibrous tumors (SFT) from transitional meningiomas (TM), thereby assisting the establishment of the treatment protocol.MethodsPreoperative diffusion-weighted imaging datasets of 24 patients with SFT and 28 patients with TM were used to extract whole-volume ADC histogram parameters, including variance, skewness, kurtosis, and mean, as well as 1st (AP1), 10th (AP10), 50th (AP50), 90th (AP90), and 99th (AP99) percentiles of ADC using MaZda software. The independent t-test or Mann–Whitney U test was used to compare the differences between ADC histogram parameters of SFT and TM. Receiver operating characteristic (ROC) curves were generated to evaluate the performance of significant ADC histogram parameters. Spearman’s correlation coefficients were calculated to evaluate correlations between these parameters and the Ki-67 expression levels.ResultsSFT exhibited significantly higher variance, and lower AP1 and AP10 (all P < 0.05) than TM. The best diagnostic performance was obtained by variance, with an area under the ROC curve of 0.848 (0.722–0.933). However, there was no significant difference in skewness, kurtosis, mean, or other percentiles of ADC between the two groups (all P > 0.05). Significant correlations were also observed between the Ki-67 proliferation index and variance (r = 0.519), AP1 (r = -0.425), and AP10 (r = -0.372) (all P < 0.05).ConclusionWhole-volume ADC histogram analysis is a feasible tool for non-invasive preoperative discrimination between intracranial SFT and TM, with variance being the most promising prospective parameter.

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Role of diffusion-weighted imaging in differentiating angiomatous meningioma from atypical meningioma

Cited by 7 publications

References 20 publications

The role of apparent diffusion coefficient in the grading of adult isocitrate dehydrogenase-mutant astrocytomas: relationship with the Ki-67 proliferation index

The role of apparent diffusion coefficient in the grading of adult isocitrate dehydrogenase-mutant astrocytomas: relationship with the Ki-67 proliferation index

MRI histogram analysis of tumor-infiltrating CD8+ T cell levels in patients with glioblastoma

The value of whole-volume apparent diffusion coefficient histogram analysis in preoperatively distinguishing intracranial solitary fibrous tumor and transitional meningioma

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