Initial and follow-up high-resolution vessel wall MRI study of spontaneous cervicocranial artery dissection.

OBJECTIVES: To explore the factors associated with ischemic stroke secondary to spontaneous cervicocranial artery dissection (sCCAD) and evaluate the initial imaging markers related to outcomes. METHODS: Initial and follow-up high-resolution vessel wall MRI (VW-MRI) in consecutive patients with sCCAD were retrospectively analyzed. The associations of clinical and imaging factors and variants of the circle of Willis (COW) with ischemic stroke were evaluated using binary logistic regression analyses. The anatomical outcomes were categorized as complete, partial, and no remodeling based on changes of the vessel wall and lumen. Ordinal logistic regression analysis was used to assess associations between initial features and outcomes. RESULTS: A total of 115 dissected arteries (79 strokes, 36 non-strokes) were detected in 103 patients. Follow-up VW-MRI was available in 46 patients (44.7%, with 51 vessels), with a median interval of 8.5 months. Pseudoaneurysm (odd ratio [OR], 0.178; 95% confidence interval [CI], 0.039-0.810; p = 0.026) tended to rarely cause ischemic stroke, while intraluminal thrombus (OR, 5.558; 95% CI, 1.739-17.765; p = 0.004), incomplete COW (OR, 9.309; 95% CI, 2.122-40.840; p = 0.003), and partial complete COW (OR, 4.463; 95% CI, 1.211-16.453; p = 0.025) were independently associated with stroke occurrence. Furthermore, the presence of double lumen (OR, 5.749; 95% CI, 1.358-24.361; p = 0.018) and occlusion (OR, 12.975; 95% CI, 3.022-55.645; p = 0.001) were associated with no remodeling of sCCAD. CONCLUSIONS: Multiple initial factors were found to be related to stroke occurrence and anatomical outcomes of sCCAD. High-resolution VW-MRI may provide valuable insights into the pathophysiology and evolution of sCCAD. CLINICAL RELEVANCE STATEMENT: Initial and follow-up high-resolution vessel wall MRI may help elucidate the pathophysiology of spontaneous cervicocranial artery dissection and provide important insights into the evolution and further facilitate the optimal management of patients with spontaneous cervicocranial artery dissection. KEY POINTS: • Clinical and imaging factors, as well as the status of primary collateral circulation, are associated with ischemic stroke secondary to spontaneous cervicocranial artery dissection. • The follow-up high-resolution vessel wall MRI provides valuable insights into the long-term evolution and anatomical outcomes of spontaneous cervicocranial artery dissection. • The high-resolution vessel wall MRI features related to ischemic stroke and anatomical outcomes may further facilitate the optimal management of patients with spontaneous cervicocranial artery dissection.

MRI characteristics predict BRAF V600E status in gangliogliomas and pleomorphic xanthoastrocytomas and provide survival prognostication.

BACKGROUND: BRAF V600E mutation is a common genomic alteration in gangliogliomas (GGs) and pleomorphic xanthoastrocytomas (PXAs) with prognostic and therapeutic implications. PURPOSE: To investigate the ability of magnetic resonance imaging (MRI) features to predict BRAF V600E status in GGs and PXAs and their prognostic values. MATERIAL AND METHODS: A cohort of 44 patients with histologically confirmed GGs and PXAs was reviewed retrospectively. BRAF V600E status was determined by immunohistochemistry (IHC) staining and fluorescence quantitative polymerase chain reaction (PCR). Demographics and MRI characteristics of the two groups were evaluated and compared. Univariate and multivariate Cox regression analyses were performed to identify MRI features that were prognostic for progression-free survival (PFS). RESULTS: T1/FLAIR ratio, enhancing margin, and mean relative apparent diffusion coefficient (rADCmea) value showed significant differences between the BRAF V600E-mutant and BRAF V600E-wild groups (all P < 0.05). Binary logistic regression analysis revealed only rADCmea value was the independent predictive factor for BRAF V600E status (P = 0.027). Univariate Cox regression analysis showed age at diagnosis (P = 0.032), WHO grade (P = 0.020), enhancing margin (P = 0.029), and rADCmea value (P = 0.005) were significant prognostic factors for PFS. In multivariate Cox regression analysis, increasing age (P = 0.040, hazard ratio [HR] = 1.04, 95% confidence interval [CI] = 1.002-1.079) and lower rADCmea values (P = 0.021, HR = 0.036, 95% CI = 0.002-0.602) were associated with poor PFS in GGs and PXAs. CONCLUSION: Imaging features are potentially predictive of BRAF V600E status in GGs and PXAs. Furthermore, rADCmea value is a valuable prognostic factor for patients with GGs or PXAs.

Is 3T MR nerve-bone fusion imaging a viable alternative to MRI-CBCT to identify the relationship between the inferior alveolar nerve and mandibular third molar.

OBJECTIVES: To investigate the feasibility of MRI nerve-bone fusion imaging in assessing the relationship between inferior alveolar nerve (IAN) / mandibular canal (MC) and mandibular third molar (MTM) compared with MRI-CBCT fusion. MATERIALS AND METHODS: The MRI nerve-bone fusion and MRI-CBCT fusion imaging were performed in 20 subjects with 37 MTMs. The Hausdorff distance (HD) value and dice similarity coefficient (DSC) was calculated. The relationship between IAN/MC and MTM roots, inflammatory, and fusion patterns were compared between these two fused images. The reliability was assessed using a weighted κ statistic. RESULTS: The mean HD and DSC ranged from 0.62 ~ 1.35 and 0.83 ~ 0.88 for MRI nerve-bone fusion, 0.98 ~ 1.50 and 0.76 ~ 0.83 for MRI-CBCT fusion. MR nerve-bone fusion had considerable reproducibility compared to MRI-CBCT fusion in relation classification (MR nerve-bone fusion κ = 0.694, MRI-CBCT fusion κ = 0.644), direct contact (MR nerve-bone fusion κ = 0.729, MRI-CBCT fusion κ = 0.720), and moderate to good agreement for inflammation detection (MR nerve-bone fusion κ = 0.603, MRI-CBCT fusion κ = 0.532, average). The MR nerve-bone fusion imaging showed a lower ratio of larger pattern compared to MR-CBCT fusion (16.2% VS 27.3% in the molar region, and 2.7% VS 5.4% in the retromolar region). And the average time spent on MR nerve-bone fusion and MRI-CBCT fusion was 1 min and 3 min, respectively. CONCLUSIONS: Both MR nerve-bone fusion and MRI-CBCT fusion exhibited good consistency in evaluating the spatial relationship between IAN/MC and MTM, fusion effect, and inflammation detection. CLINICAL RELEVANCE: MR nerve-bone fusion imaging can be a preoperative one-stop radiation-free examination for patients at high risk for MTM surgery.

Grading meningiomas with diffusion metrics: a comparison between diffusion kurtosis, mean apparent propagator, neurite orientation dispersion and density, and diffusion tensor imaging.

OBJECTIVES: To compare the histogram features of multiple diffusion metrics in predicting the grade and cellular proliferation of meningiomas. METHODS: Diffusion spectrum imaging was performed in 122 meningiomas (30 males, 13-84 years), which were divided into 31 high-grade meningiomas (HGMs, grades 2 and 3) and 91 low-grade meningiomas (LGMs, grade 1). The histogram features of multiple diffusion metrics obtained from diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), mean apparent propagator (MAP), and neurite orientation dispersion and density imaging (NODDI) in the solid tumours were analysed. All values between the two groups were compared with the Man-Whitney U test. Logistic regression analysis was applied to predict meningioma grade. The correlation between diffusion metrics and Ki-67 index was analysed. RESULTS: The DKI_AK (axial kurtosis) maximum, DKI_AK range, MAP_RTPP (return-to-plane probability) maximum, MAP_RTPP range, NODDI_ICVF (intracellular volume fraction) range, and NODDI_ICVF maximum values were lower (p < 0.0001), whilst the DTI_MD (mean diffusivity) minimum values were higher in LGMs than those in HGMs (p < 0.001). Amongst the DTI, DKI, MAP, NODDI, and combined diffusion models, no significant differences were found in areas under the receiver operating characteristic curves (AUCs) for grading meningiomas (AUCs, 0.75, 0.75, 0.80, 0.79, and 0.86, respectively; all corrected p > 0.05, Bonferroni correction). Significant but weak positive correlations were found between the Ki-67 index and DKI, MAP, and NODDI metrics (r = 0.26-0.34, all p < 0.05). CONCLUSIONS: Whole tumour histogram analyses of the multiple diffusion metrics from four diffusion models are promising methods in grading meningiomas. The DTI model has similar diagnostic performance compared with advanced diffusion models. KEY POINTS: • Whole tumour histogram analyses of multiple diffusion models are feasible for grading meningiomas. • The DKI, MAP, and NODDI metrics are weakly associated with the Ki-67 proliferation status. • DTI has similar diagnostic performance compared with DKI, MAP, and NODDI in grading meningiomas.

Whole-tumor histogram analysis of diffusion and perfusion metrics for noninvasive pediatric glioma grading.

PURPOSE: An accurate assessment of the World Health Organization grade is vital for patients with pediatric gliomas to direct treatment planning. We aim to evaluate the diagnostic performance of whole-tumor histogram analysis of diffusion-weighted imaging (DWI) and dynamic susceptibility contrast-enhanced perfusion-weighted imaging (DSC-PWI) for differentiating pediatric high-grade gliomas from pediatric low-grade gliomas. METHODS: Sixty-eight pediatric patients (mean age, 10.47 ± 4.37 years; 42 boys) with histologically confirmed gliomas underwent preoperative MR examination. The conventional MRI features and whole-tumor histogram features extracted from apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) maps were analyzed, respectively. Receiver operating characteristic curves and the binary logistic regression analysis were performed to determine the diagnostic performance of parameters. RESULTS: For conventional MRI features, location, hemorrhage and tumor margin showed significant difference between pediatric high- and low-grade gliomas (all, P < .05). For advanced MRI parameters, ten histogram features of ADC and CBV showed significant differences between pediatric high- and low-grade gliomas (all, P < .05). The diagnostic performance of the combination of DSC-PWI and DWI (AUC = 0.976, sensitivity = 100%, NPV = 100%) is superior to conventional MRI or DWI model, respectively (AUCcMRI = 0.700, AUCDWI = 0.830; both, P < .05). CONCLUSION: The whole-tumor histogram analysis of DWI and DSC-PWI is a promising method for grading pediatric gliomas.

Apparent Diffusion Coefficient in the Differentiation of Common Pediatric Brain Tumors in the Posterior Fossa: Different Region-of-Interest Selection Methods for Time Efficiency, Measurement Reproducibility, and Diagnostic Utility.

OBJECTIVES: This study aimed to explore the diagnostic ability of apparent diffusion coefficient (ADC) values obtained from different region of interest (ROI) measurements in tumor parenchyma for differentiating posterior fossa tumors (PFTs) and the correlations between ADC values and Ki-67. METHODS: Seventy-three pediatric patients with PFTs who underwent conventional diffusion-weighted imaging were recruited in this study. Five different ROIs were manually drawn by 2 radiologists (ROI-polygon, ROI-3 sections, ROI-3-5 ovals, ROI-more ovals, and ROI-whole). The interreader/intrareader repeatability, time required, diagnostic ability, and Ki-67 correlation analysis of the ADC values based on these ROI strategies were calculated. RESULTS: Both interreader and intrareader reliabilities were excellent for ADC values among the different ROI strategies (intraclass correlation coefficient, 0.899-0.992). There were statistically significant differences in time consumption among the 5 ROI selection methods ( P < 0.001). The time required for the ROI-3-5 ovals was the shortest (32.23 ± 5.14 seconds), whereas the time required for the ROI-whole was the longest (204.52 ± 92.34 seconds). The diagnostic efficiency of the ADC values showed no significant differences among the different ROI measurements ( P > 0.05). The ADC value was negatively correlated with Ki-67 ( r = -0.745 to -0.798, all P < 0.0001). CONCLUSIONS: The ROI-3-5 ovals method has the best interobserver repeatability, the shortest amount of time spent, and the best diagnostic ability. Thus, it is considered an effective measurement to produce ADC values in the evaluation of pediatric PFTs.

Gender differences in lateral pterygoid muscle in patients with anterior disk displacement.

OBJECTIVE: To use quantitative MRI to assess gender differences in lateral pterygoid muscle (LPM) characteristics in patients with anterior disk displacement (ADD). METHODS: Lateral pterygoid muscle of 51 patients diagnosed with temporomandibular joint disorders (TMD) who underwent T1-weighted Dixon and T1-mapping sequences were retrospectively analyzed. There were 34 female patients (10 with bilateral normal position disk [NP]; 24 with bilateral ADD) and 17 male patients (eight with bilateral NP; nine with bilateral ADD) among them. After controlling for age, differences in fat fraction, T1 value, volume and histogram features related to gender and disk status were tested with 2-way ANCOVA or Quade ANCOVA with Bonferroni correction. RESULTS: Volume of LPM in NP was significantly smaller than that of ADD (p < 0.001). Fat fraction of LPM in females with NP was significantly higher than males with NP (p < 0.05). Females with ADD showed a significantly higher T1 value (p < 0.05), and higher intramuscular heterogeneity than males with ADD. CONCLUSIONS: Lateral pterygoid muscle in female TMD patients presented more fatty infiltration in the NP stage and might present more fibrosis in the ADD stage compared with males. Together, this leads to more serious intramuscular heterogeneity during the pathogenesis of ADD in females.

Diffusion kurtosis imaging and dynamic contrast-enhanced MRI for the differentiation of parotid gland tumors.

OBJECTIVE: To assess the usefulness of combined diffusion kurtosis imaging (DKI) and dynamic contrast-enhanced MRI (DCE-MRI) in the differentiation of parotid gland tumors. METHODS: Seventy patients with 80 parotid gland tumors who underwent DKI and DCE-MRI were retrospectively enrolled and divided into four groups: pleomorphic adenomas (PAs), Warthin tumors (WTs), other benign tumors (OBTs), and malignant tumors (MTs). DCE-MRI and DKI quantitative parameters were measured. The Kruskal-Wallis H test and post hoc test with Bonferroni correction and ROC curve were used for statistical analysis. RESULTS: WTs demonstrated the highest Kep value (median 1.89, interquartile range [1.46-2.31] min-1) but lowest Ve value (0.20, [0.15-0.25]) compared with PAs (Kep, 0.34 [0.21-0.55] min-1; Ve, 0.36 [0.24-0.43]), OBTs (Kep, 1.22 [0.27-1.67] min-1; Ve, 0.28 [0.25-0.41]), and MTs (Kep, 0.71 [0.50-1.23] min-1; Ve, 0.35 [0.26-0.45]) (all p < .05). MTs had the lower D value (1.10, [0.88-1.29] × 10-3 mm2/s) compared with PAs (1.81, [1.60-2.20] × 10-3 mm2/s) and OBTs (1.57, [1.32-1.89] × 10-3 mm2/s) (both p < .05). PAs had the lower Ktrans value (0.12, [0.07-0.18] min-1) compared with OBTs (0.28, [0.11-0.50] min-1) (p < .05). The cutoff values of combined Kep and Ve, D, and Ktrans to distinguish WTs, MTs, and PAs sequentially were 1.06 min-1, 0.28, 1.46 × 10-3 mm2/s, and 0.21 min-1, respectively (accuracy, 89% [71/80], 91% [73/80], 78% [62/80], respectively). CONCLUSION: The combined use of DKI and DCE-MRI may help differentiate parotid gland tumors. KEY POINTS: • The combined use of DKI and DCE-MRI could facilitate the understanding of the pathophysiological characteristics of parotid gland tumors. • A stepwise diagnostic diagram based on the combined use of DCE-MRI parameters and the diffusion coefficient is helpful for accurate preoperative diagnosis in parotid gland tumors and may further facilitate the clinical management of patients.

Follow-up assessment of atherosclerotic plaques in acute ischemic stroke patients using high-resolution vessel wall MR imaging.

PURPOSE: Data on evolution of intracranial plaques in acute ischemic stroke patients after receiving medical therapy is still limited. We aimed to investigate the plaque features associated with culprit lesions and to explore the plaque longitudinal changes during treatment using high-resolution vessel wall MR imaging (VW-MRI). METHODS: Twenty-three patients (16 men; mean age, 51.4 years ± 11.1) with acute ischemic stroke underwent 3-T VW-MRI for intracranial atherosclerosis and were taken follow-up assessments. Each identified plaque was retrospectively classified as culprit, probably culprit, or nonculprit. Plaque features were analyzed at both baseline and follow-up and were compared using paired t-test, paired Wilcoxon test, or McNemar's test. RESULTS: A total of 87 intracranial plaques were identified (23 [26.4%] culprit, 10 [11.5%] probably culprit, and 54 [62.1%] nonculprit plaques). The median time interval between initial and follow-up MRI scans was 8.0 months. In the multiple ordinal logistic regression analysis, plaque contrast ratio (CR) (OR, 1.037; 95% CI, 1.013-1.062; P = 0.002) and surface irregularity (OR, 4.768; 95% CI, 1.064-21.349; P = 0.041) were independently associated with culprit plaques. During follow-up, plaque length, maximum thickness, normalized wall index (NWI), stenosis degree, and CR significantly decreased (all P-values < 0.05) in the culprit plaque group. The plaque NWI and CR dropped in the probably culprit plaques (P = 0.041, 0.026, respectively). In the nonculprit plaque group, only plaque NWI and stenosis degree showed significant decrement (P = 0.017, 0.037, respectively). CONCLUSION: Follow-up VW-MRI may contribute to plaque risk stratification and may provide valuable insights into the evolution of different plaques in vivo.

Grading of IDH-mutant astrocytoma using diffusion, susceptibility and perfusion-weighted imaging.

BACKGROUND: The accurate grading of IDH-mutant astrocytoma is essential to make therapeutic strategies and assess the prognosis of patients. The purpose of this study was to investigate the usefulness of DWI, SWI and DSC-PWI in grading IDH-mutant astrocytoma. METHODS: One hundred and seven patients with IDH-mutant astrocytoma who underwent DWI, SWI and DSC-PWI were retrospectively reviewed. Minimum apparent diffusion coefficient (ADCmin), intratumoral susceptibility signal intensity(ITSS) and maximum relative cerebral blood volume (rCBVmax) values were assessed. ADCmin, ITSS and rCBVmax values were compared between grade 2 vs. grade 3, grade 3 vs. grade 4 and grade 2 + 3 vs. grade 4 tumors. Logistic regression, tenfold cross-validation,and receiver operating characteristic (ROC) curve analyses were used to assess their diagnostic performances. RESULTS: Grade 4 IDH-mutant astrocytomas showed significantly lower ADCmin and higher rCBVmax as compared to grade 3 tumors (adjusted P < 0.001). IDH-mutant grade 3 astrocytomas showed significantly lower ITSS levels as compared with grade 4 tumors (adjusted P < 0.001). ITSS levels between IDH-mutant grade 2 and grade 3 astrocytomas were significantly different (adjusted P = 0.002). Combined the ADCmin, ITSS and rCBVmax resulted in the highest AUC for differentiation grade 2 and grade 3 tumors from grade 4 tumors. CONCLUSION: ADCmin, rCBVmax and ITSS can be used for grading the IDH-mutant astrocytomas. The combination of ADCmin, ITSS and rCBVmax could improve the diagnostic performance in grading of IDH-mutant astrocytoma.

Evaluation of lateral pterygoid muscle in patients with temporomandibular joint anterior disk displacement using T1-weighted Dixon sequence: a retrospective study.

BACKGROUND: Pathological alterations of lateral pterygoid muscle (LPM) are implicated in temporomandibular joint anterior disk displacement (ADD). However, quantification of the fatty infiltration of LPM and its correlation with ADD have rarely been reported. The aim of this study was to evaluate the fatty infiltration, morphological features and texture features of LPM in patients with ADD using T1-weighted Dixon sequence. METHODS: This retrospective study included patients who underwent temporomandibular joint MRI with T1-weighted Dixon sequence between December 2018 and August 2020. The temporomandibular joints of the included patients were divided into three groups according to the position of disk: Normal position disk (NP) group, Anterior disk displacement with reduction (ADDWR) group and Anterior disk displacement without reduction (ADDWOR) group. Fat fraction, morphological features (Length; Width; Thickness), and texture features (Angular second moment; Contrast; Correlation; Inverse different moment; Entropy) extracted from in-phase image of LPM were evaluated. One-way ANOVA, Welch's ANOVA, Kruskal-Wallis test, Spearman and Pearson correlation analysis were performed. Intra-class correlation coefficient was used to evaluate the reproducibility. RESULTS: A total of 53 patients with 106 temporomandibular joints were evaluated. Anterior disk displacement without reduction group showed higher fat fraction than normal position disk group (P = 0.024). Length of LPM was negatively correlated with fat fraction (r = -0.22, P = 0.026). Angular second moment (ρ = -0.32, P < 0.001), correlation (ρ = -0.28, P = 0.003) and inverse different moment (ρ = -0.27, P = 0.005) were negatively correlated with fat fraction, while positive correlation was found between entropy and fat fraction (ρ = 0.31, P = 0.001). The intra-class correlation coefficients for all values were ranged from 0.80 to 0.97. CONCLUSIONS: Patients with ADDWOR present more fatty infiltration in the LPM compared to NP or ADDWR patients. Fatty infiltration of LPM was associated with more atrophic and higher intramuscular heterogeneity in patients with ADD. Fat fraction of LPM quantitatively and noninvasively evaluated by Dixon sequence may has utility as an imaging-based marker of the structural severity of ADD disease process, which could be clinical helpful for the early diagnose of ADD and predication of disease progression.

Quantitative dynamic contrast-enhanced MRI and readout segmentation of long variable echo-trains diffusion-weighted imaging in differentiating parotid gland tumors.

PURPOSE: To evaluate the ability of quantitative dynamic contrast-enhanced (DCE)-MRI and readout segmentation of long variable echo-trains diffusion-weighted imaging (RESOLVE-DWI) in differentiating parotid tumors (PTs) with different histological types. METHODS: In this retrospective study, 123 patients with 145 histologically proven PTs who underwent both RESOLVE-DWI and DCE-MRI were enrolled including 51 pleomorphic adenomas (PAs), 52 Warthin's tumors (WTs), 27 other benign neoplasms (OBNs), and 15 malignant tumors (MTs). Quantitative parameters of DCE-MRI (Ktrans, Kep, and Ve) and the apparent diffusion coefficient (ADC) of lesions were calculated and analyzed. Kruskal-Wallis tests with Dunn-Bonferroni correction, logistic regression analyses, and receiver operating characteristic curve were used for statistical analyses. RESULTS: PAs exhibited a lowest Ktrans among these four PTs. WTs demonstrated the highest Kep and lowest Ve values. WTs and MTs showed lower ADCmin values than PAs and OBNs. The combination of Kep and Ve provided 98.1% sensitivity, 85% specificity, and 98.7% accuracy for differentiating WTs from the other three PTs. The ADCmin cutoff value of ≤ 0.826 yielded 80.0% sensitivity, 92.3% specificity, and 90.3% accuracy for the differentiation of MTs from PAs and OBNs. Ktrans with a cutoff value of ≤ 0.185 achieved a sensitivity, specificity, and accuracy of 84.3, 70.4, and 79.5%, respectively, for discriminating PAs from OBNs. CONCLUSION: The combination of quantitative DCE-MRI and RESOLVE-DWI is beneficial for characterizing four histological types of PTs.

Predicting 1p/19q codeletion status using diffusion-, susceptibility-, perfusion-weighted, and conventional MRI in IDH-mutant lower-grade gliomas.

BACKGROUND: Isocitrate dehydrogenase (IDH)-mutant lower-grade gliomas (LGGs) are further classified into two classes: with and without 1p/19q codeletion. IDH-mutant and 1p/19q codeleted LGGs have better prognosis compared with IDH-mutant and 1p/19q non-codeleted LGGs. PURPOSE: To evaluate conventional magnetic resonance imaging (cMRI), diffusion-weighted imaging (DWI), susceptibility-weighted imaging (SWI), and dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) for predicting 1p/19q codeletion status of IDH-mutant LGGs. MATERIAL AND METHODS: We retrospectively reviewed cMRI, DWI, SWI, and DSC-PWI in 142 cases of IDH mutant LGGs with known 1p/19q codeletion status. Features of cMRI, relative ADC (rADC), intratumoral susceptibility signals (ITSSs), and the value of relative cerebral blood volume (rCBV) were compared between IDH-mutant LGGs with and without 1p/19q codeletion. Receiver operating characteristic curve and logistic regression were used to determine diagnostic performances. RESULTS: IDH-mutant and 1p/19q non-codeleted LGGs tended to present with the T2/FLAIR mismatch sign and distinct borders (P < 0.001 and P = 0.038, respectively). Parameters of rADC, ITSSs, and rCBVmax were significantly different between the 1p/19q codeleted and 1p/19q non-codeleted groups (P < 0.001, P = 0.017, and P < 0.001, respectively). A combination of cMRI, SWI, DWI, and DSC-PWI for predicting 1p/19q codeletion status in IDH-mutant LGGs resulted in a sensitivity, specificity, positive predictive value, negative predictive value, and an AUC of 80.36%, 78.57%, 83.30%, 75.00%, and 0.88, respectively. CONCLUSION: 1p/19q codeletion status of IDH-mutant LGGs can be stratified using cMRI and advanced MRI techniques, including DWI, SWI, and DSC-PWI. A combination of cMRI, rADC, ITSSs, and rCBVmax may improve the diagnostic performance for predicting 1p/19q codeletion status.

Prognostic value of pretreatment MRI texture features in breast cancer brain metastasis treated with Gamma Knife radiosurgery.

BACKGROUND: Gamma Knife radiosurgery (GKS) was recommended for treating patients with breast cancer brain metastasis (BCBM), but predictions of the existing prognostic models for therapeutic responsiveness vary substantially. PURPOSE: To investigate the prognostic value of pretreatment clinical, MRI radiologic, and texture features in patients with BCBM undergoing GKS. MATERIAL AND METHODS: The data of 81 BCBMs in 44 patients were retrospectively reviewed. Progressive disease was defined as an increase of at least 20% in the longest diameter of the target lesion or the presence of new intracranial lesions on contrast-enhanced T1-weighted (CE-T1W) imaging. Radiomic features were extracted from pretreatment CE-T1W images, T2-weighted (T2W) images, and ADC maps. Cox proportional hazard analyses were performed to identify independent predictors associated with BCBM-specific progression-free survival (PFS). A nomogram was constructed and its calibration ability was assessed. RESULTS: The cumulative BCBM-specific PFS was 52.27% at six months and 11.36% at one year, respectively. Age (hazard ratio [HR] 1.04; 95% confidence interval [CI] 1.01-1.06; P = 0.004) and CE-T1W-based kurtosis (HR 0.72; 95% CI 0.57-0.92; P = 0.008) were the independent predictors. The combination of CE-T1W-based kurtosis and age displayed a higher C-index (C-index 0.70; 95% CI 0.63-0.77) than did CE-T1W-based kurtosis (C-index 0.65; 95% CI 0.57-0.73) or age (C-index 0.63; 95% CI 0.56-0.70) alone. The nomogram based on the combinative model provided a better performance over age (P < 0.05). The calibration curves elucidated good agreement between prediction and observation for the probability of 7- and 12-month BCBM-specific PFS. CONCLUSION: Pretreatment CE-T1W-based kurtosis combined with age could improve prognostic ability in patients with BCBM undergoing GKS.

Comparison of Conventional, Diffusion, and Perfusion MRI Between Low-Grade and Anaplastic Extraventricular Ependymoma.

OBJECTIVE. The purpose of this study was to investigate and compare conventional MRI, DWI, and dynamic susceptibility contrast-enhanced perfusion-weighted imaging (DSC-PWI) characteristics between low-grade and anaplastic extraventricular ependymomas. MATERIALS AND METHODS. Twenty-six patients with extraventricular ependymomas (19 anaplastic and seven low-grade) who underwent preoperative MRI were enrolled in this retrospective study. Conventional MRI and DWI were performed in all patients; DSCPWI was performed in 15 patients (11 with anaplastic ependymoma and four with low-grade ependymoma). Demographics, conventional MRI features, minimum relative apparent diffusion coefficient (rADCmin), and maximum relative cerebral blood volume (rCBVmax) of the low-grade and anaplastic ependymomas were compared. Diagnostic performance with optimal cutoff values was determined. RESULTS. Anaplastic extraventricular ependymomas were more likely to be located in the superficial supratentorial cerebral hemisphere (p = 0.026) and to present with pial and cortical involvement (p = 0.028 and 0.013, respectively) and necrotic degeneration (p = 0.014). The mean rADCmin ± SD of anaplastic ependymoma was significantly lower than that of low-grade ependymoma (0.8 ± 0.2 vs 1.2 ± 0.3, p = 0.002). The mean rCBVmax of anaplastic ependymoma was significantly higher than that of low-grade ependymoma (15.7 ± 5.3 vs 9.0 ± 4.4, p = 0.042). The cutoff values in grading extraventricular ependymoma were 1.02 for rADCmin and 10.43 for rCBVmax. Combining conventional MRI, DWI, and DSC-PWI allowed the best differentiation of low-grade and anaplastic ependymoma (AUC = 1.00). CONCLUSION. Conventional MRI, DWI, and DSC-PWI techniques may aid in assessing and grading extraventricular ependymomas.

Differentiating intracranial solitary fibrous tumor/hemangiopericytoma from meningioma using diffusion-weighted imaging and susceptibility-weighted imaging.

PURPOSE: Intracranial solitary fibrous tumor/hemangiopericytoma (SFT/HPC) and meningioma are difficult to distinguish owing to their overlapping imaging manifestation on routine magnetic resonance imaging. The purpose of this study was to assess whether SFT/HPC can be differentiated from meningioma with diffusion-weighted imaging (DWI) and susceptibility-weighted imaging (SWI). METHODS: We retrospectively reviewed DWI, SWI, conventreional MR, and CT imaging features of 16 patients with SFT/HPC and 96 patients with meningioma. The apparent diffusion coefficient (ADC) value, normalized ADC (nADC) value, and degree of intratumoral susceptibility signal intensity (ITSS) were compared between SFT/HPCs and meningiomas using two-sample t tests, and among SFT/HPCs, low-grade and high-grade meningioma were tested using one-way analysis of variance (ANOVA). Receiver operating characteristic (ROC) curve and logistic regression analyses were performed to determine the differentiation capacity. RESULTS: The ADC value, nADC value, and the degree of ITSS in SFT/HPC were significantly higher than those in low-grade and high-grade meningiomas (all p < 0.05). The threshold value of > 1.15 for nADC provided 75.00% sensitivity and 60.42% specificity for differentiating SFT/HPC from meningioma. Compared with nADC, the degree of ITSS had a moderate sensitivity (62.50%) and a higher specificity (85.42%) using the threshold value of > 1.00. Furthermore, combining DWI and SWI can achieve a relatively high differentiation capacity with a sensitivity of 81.25% and specificity of 78.12%. CONCLUSIONS: The nADC ratios and ITSS are useful for differentiating SFT/HPC from meningioma. Combining ITSS and nADC value appears to be a promising option for differential diagnosis.

Differentiation of Glioblastoma and Solitary Brain Metastasis by Gradient of Relative Cerebral Blood Volume in the Peritumoral Brain Zone Derived from Dynamic Susceptibility Contrast Perfusion Magnetic Resonance Imaging.

OBJECTIVE: The purpose of our study was to evaluate the efficacy of the relative cerebral blood volume (rCBV) gradient in the peritumoral brain zone (PBZ)-the difference in the rCBV values from the area closest to the enhancing lesion to the area closest to the healthy white matter-in differentiating glioblastoma (GB) from solitary brain metastasis (MET). METHODS: A 3.0-T magnetic resonance imaging (MRI) machine was used to perform dynamic susceptibility contrast perfusion MRI (DSC-MRI) on 43 patients with a solitary brain tumor (24 GB, 19 MET). The rCBV ratios were acquired by DSC-MRI data in 3 regions of the PBZ (near the enhancing tumor, G1; intermediate distance from the enhancing tumor, G2; far from the enhancing tumor, G3). The maximum rCBV ratios in the PBZ (rCBVp) and the enhancing tumor were also calculated, respectively. The perfusion parameters were evaluated using the nonparametric Mann-Whitney test. The sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve were identified. RESULTS: The rCBVp ratios and rCBV gradient in the PBZ were significantly higher in GB compared with MET (P < 0.05 for both rCBVp ratios and rCBV gradient). The threshold values of 0.50 or greater for rCBVp ratios provide sensitivity and specificity of 57.69% and 79.17%, respectively, for differentiation of GB from MET. Compared with rCBVp ratios, rCBV gradient had higher sensitivity (94.44%) and specificity (91.67%) using the threshold value of greater than 0.06. CONCLUSIONS: The parameter of rCBV gradient derived from DSC-MRI in the PBZ seems to be the most efficient parameter to differentiate GB from METs.

MR imaging features of spinal pilocytic astrocytoma.

BACKGROUND: The purpose of this retrospective review is to determine the MR imaging features of pilocytic astrocytoma (PA) in the spinal cord to help neuroradiologists preoperatively differentiate PA from other intramedullary tumors. METHODS: Neuro-oncology database review revealed 13 consecutive patients with a pathological spinal PA diagnosis and availability of preoperative MR imaging. Three patients had preoperative diffusion-weighted MR imaging. Demographics and conventional and diffusion MR imaging records were retrospectively evaluated. RESULTS: Among 13 cases of spinal PA, six PAs were located in the cervical region, 4 in the cervical-thoracic region, and 3 in the thoracic region. The average length of vertebral segments involved for the tumors were 4.7 ± 4.6 segments. Six tumors had associated syringomyelia. Eight PAs were located eccentrically in the spinal cord, and eleven had well-defined margins. Eight tumors (61.5%) were intermixed cystic and solid. All were contrast-enhanced, and 53.8% of all PAs showed focal nodule enhancement of the solid components. Two PAs showed intratumoral hemorrhages, and only one demonstrated cap sign. The ADC values (n = 3) of the tumors were 1.40 ± 0.28 × 10- 3 mm2/s (min-max: 1.17-1.71 × 10- 3 mm2/s). CONCLUSIONS: PA should be considered in the differential diagnosis of intramedullary tumors that occur in the cervical and thoracic regions. Eccentric growth pattern, well-defined margin, intermixed cystic and solid appearance, focal nodular enhancement of solid components and syringomyelia are relatively frequent features. Relatively high ADC values compared with normal-appearing spinal cord parenchyma are common in spinal PA.

IDH genotypes differentiation in glioblastomas using DWI and DSC-PWI in the enhancing and peri-enhancing region.

BACKGROUND: Isocitrate dehydrogenase (IDH) mutation has diagnostic and prognostic values in glioblastomas. Peritumoral invasion of glioma cells is a cardinal feature of glioblastomas. PURPOSE: To evaluate the contribution of DWI and DSC-PWI in the enhancing and peri-enhancing region for discriminating glioblastomas IDH genotypes, and the diagnostic values of combining two techniques in the peri-enhancing region compared with those in the enhancing region. MATERIAL AND METHODS: We retrospectively reviewed the conventional MRI (cMRI), DWI and DSC-PWI obtained from 10 patients with IDH-mutated (IDH-m) glioblastomas and 65 patients with IDH wild-type (IDH-w) glioblastomas. Features of cMRI, relative minimum ADC in the enhancing region (rADCmin-t) and peri-enhancing area (rADCmin-p), and relative maximum CBV values in the enhancing region (rCBVmax-t) and peri-enhancing region (rCBVmax-p) were compared between two groups. Receiver operating characteristic curves and logistic regression analysis were used to assess diagnostic performance. RESULTS: IDH-m glioblastomas tended to present in frontal lobes and younger patients. The rADCmin-t (P = 0.042) were significantly lower in IDH-w than IDH-m. Both rCBVmax-t and rCBVmax-p showed significant differences between two subgroups (all P < 0.001). The optimal cutoff values in prediction of IDH-m were >0.98 for rADCmin-t, <7.27 for rCBVmax-t, and < 0.97 for rCBVmax-p. Multivariate logistic regression revealed that the combination of rADCmin-t and rCBVmax-t yielded the highest sensitivity and specificity. CONCLUSION: The rCBVmax-t or rCBVmax-p may serve as preferable and comparable imaging biomarkers for evaluation of glioblastomas IDH status. The combination of rADCmin-t and rCBVmax-t may yield the maximum predictive power for differentiating IDH status.

Presurgical differentiation between malignant haemangiopericytoma and angiomatous meningioma by a radiomics approach based on texture analysis.

PURPOSE: To assess whether a machine-learning model based on texture analysis (TA) could yield a more accurate diagnosis in differentiating malignant haemangiopericytoma (HPC) from angiomatous meningioma (AM). MATERIALS AND METHODS: Sixty-seven pathologically confirmed cases, including 24 malignant HPCs and 43 AMs between May 2013 and September 2017 were retrospectively reviewed. In each case, 498 radiomic features, including 12 clinical features and 486 texture features from MRI sequences (T2-FLAIR, DWI and enhanced T1WI), were extracted. Three neuroradiologists independently made diagnoses by vision. Four Support Vector Machine (SVM) classifiers were built, one based on clinical features and three based on texture features from three MRI sequences after feature selection. The diagnostic abilities of these classifiers and three neuroradiologists were evaluated by receiver operating characteristic (ROC) analysis. RESULTS: Malignant HPCs were found to have larger sizes, slighter degrees of peritumoural oedema compared with AMs (P<0.05), and more serpentine-like vessels. The AUC of the enhanced T1WI-based classifier was 0.90, significantly higher than that of T2-FLAIR-based or DWI-based classifiers (0.77 and 0.73). The AUC of the SVM classifier based on clinical features was 0.66, slightly but not significantly lower than the performances of 3 neuroradiologists (AUC=0.69, 0.70 and 0.73). CONCLUSION: Machine-learning models based on clinical features alone could not provide a better diagnostic performance than that of radiologists. The SVM classifier built by texture features extracted from enhanced T1WI is a promising tool to differentiate malignant HPC from AM before surgery.