Combined texture analysis of dynamic contrast-enhanced MRI with histogram analysis of diffusion kurtosis imaging for predicting IDH mutational status in gliomas.

BACKGROUND: Non-invasive detection of isocitrate dehydrogenase (IDH) mutational status in gliomas is clinically meaningful for molecular stratification of glioma; however, it remains challenging. PURPOSE: To investigate the usefulness of texture analysis (TA) of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and histogram analysis of diffusion kurtosis imaging (DKI) maps for evaluating IDH mutational status in gliomas. MATERIAL AND METHODS: This retrospective study enrolled 84 patients with histologically confirmed gliomas, comprising IDH-mutant (n = 34) and IDH-wildtype (n = 50). TA was performed for the quantitative parameters derived by DCE-MRI. Histogram analysis was performed for the quantitative parameters derived by DKI. Unpaired Student's t-test was used to identify IDH-mutant and IDH-wildtype gliomas. Logistic regression and receiver operating characteristic (ROC) curve analyses were used to compare the diagnostic performance of each parameter and their combination for predicting the IDH mutational status in gliomas. RESULTS: Significant statistical differences in the TA of DCE-MRI and histogram analysis of DKI were observed between IDH-mutant and IDH-wildtype gliomas (all P < 0.05). Using multivariable logistic regression, the entropy of Ktrans, skewness of Ve, and Kapp-90th had higher prediction potential for IDH mutations with areas under the ROC curve (AUC) of 0.915, 0.735, and 0.830, respectively. A combination of these analyses for the identification of IDH mutation improved the AUC to 0.978, with a sensitivity and specificity of 94.1% and 96.0%, respectively, which was higher than the single analysis (P < 0.05). CONCLUSION: Integrating the TA of DCE-MRI and histogram analysis of DKI may help to predict the IDH mutational status.

Diffusion-relaxation correlation spectrum imaging for predicting tumor consistency and gross total resection in patients with pituitary adenomas: a preliminary study.

OBJECTIVE: To evaluate the ability of diffusion-relaxation correlation spectrum imaging (DR-CSI) to predict the consistency and extent of resection (EOR) of pituitary adenomas (PAs). METHODS: Forty-four patients with PAs were prospectively enrolled. Tumor consistency was evaluated at surgery as either soft or hard, followed by histological assessment. In vivo DR-CSI was performed and spectra were segmented following to a peak-based strategy into four compartments, designated A (low ADC), B (mediate ADC, short T2), C (mediate ADC, long T2), and D (high ADC). The corresponding volume fractions ([Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text]) along with the ADC and T2 values were calculated and assessed using univariable analysis for discrimination between hard and soft PAs. Predictors of EOR > 95% were analyzed using logistic regression model and receiver-operating-characteristic analysis. RESULTS: Tumor consistency was classified as soft (n = 28) or hard (n = 16). Hard PAs presented higher [Formula: see text] (p = 0.001) and lower [Formula: see text] (p = 0.013) than soft PAs, while no significant difference was found in other parameters. [Formula: see text] significantly correlated with the level of collagen content (r = 0.448, p = 0.002). Knosp grade (odds ratio [OR], 0.299; 95% confidence interval [CI], 0.124-0.716; p = 0.007) and [Formula: see text] (OR, 0.834, per 1% increase; 95% CI, 0.731-0.951; p = 0.007) were independently associated with EOR > 95%. A prediction model based on these variables yielded an AUC of 0.934 (sensitivity, 90.9%; specificity, 90.9%), outperforming the Knosp grade alone (AUC, 0.785; p < 0.05). CONCLUSION: DR-CSI may serve as a promising tool to predict the consistency and EOR of PAs. CLINICAL RELEVANCE STATEMENT: DR-CSI provides an imaging dimension for characterizing tissue microstructure of PAs and may serve as a promising tool to predict the tumor consistency and extent of resection in patients with PAs. KEY POINTS: • DR-CSI provides an imaging dimension for characterizing tissue microstructure of PAs by visualizing the volume fraction and corresponding spatial distribution of four compartments ([Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text]). • [Formula: see text] correlated with the level of collagen content and may be the best DR-CSI parameter for discrimination between hard and soft PAs. • The combination of Knosp grade and [Formula: see text] achieved an AUC of 0.934 for predicting the total or near-total resection, outperforming the Knosp grade alone (AUC, 0.785).

Temporal changes in plaque characteristics after treatment and their relationship with stroke recurrence: a quantitative study using magnetic resonance imaging.

Background: Intracranial atherosclerotic disease (ICAD) is the major cause of ischemic stroke. Despite aggressive medical therapy, around 15% of patients with ICAD experience recurrence. The aim of the present study was to evaluate the temporal changes in intracranial arteriosclerotic plaques after medical treatment based on vessel wall magnetic resonance imaging (VWMRI) and to explore their relationship with stroke recurrence. Methods: A total of 67 symptomatic patients with ICAD who underwent initial and follow-up VWMRI were recruited into this retrospective cohort study. Stroke recurrence was defined as an ipsilateral stroke symptom after the initial attack. The clinical characteristics and plaque features, including stenosis ratio (measured based on luminal diameter or area), plaque thickness, plaque burden (PB), enhancement ratio (ER), and enhancement grade, were evaluated and compared between the initial and follow-up examinations. Changes in plaque characteristics were compared between patients with or without recurrence by univariable analyses. Multivariable regression was performed to investigate imaging markers for recurrent stroke. Results: The median interval between baseline and follow-up VWMRI was 334 days. A total of 13 cases (19.4%) experienced a stroke recurrence. After treatment, significant decreases in the stenosis ratio (area), PB, and ER were observed in cases without recurrence (all P<0.05), while no significant difference in plaque features was found for cases with recurrence. Univariable analyses showed that changes in stenosis ratio (area), plaque thickness, PB, and ER were significantly different between patients with and without recurrence (all P<0.05). Multivariable regression indicated that PB change was the only significant marker associated with stroke recurrence [odds ratio (OR) =1.112 per 1% increase, 95% confidence interval (CI): 1.010 to 1.224, P=0.031]. Conclusions: Patients with arteriosclerotic plaques who benefit from medical treatment show obvious decreases in stenosis (area), PB, and ER. The progression of PB may serve as an independent marker for predicting stroke recurrence.

Texture Analysis of High b-Value Diffusion-Weighted Imaging for Evaluating Consistency of Pituitary Macroadenomas.

BACKGROUND: Preoperative evaluation of the consistency of pituitary macroadenomas is important for neurosurgeons to prepare the surgical plan. PURPOSE: To evaluate the diagnostic performance of texture analysis (TA) of diffusion-weighted imaging (DWI) at a standard b-value (b = 1000 s/mm2 ) and a high b-value (b = 2000 s/mm2 ) for their ability to assess the tumor consistency of pituitary macroadenomas. STUDY TYPE: Retrospective. POPULATION/SUBJECTS: Fifty patients with histologically confirmed pituitary macroadenomas were classified as soft (n = 37) or hard (n = 13) types. FIELD STRENGTH/SEQUENCE: Coronal T2 -weighted imaging (T2 WI), Readout Segmentation of Long Variable Echo-trains (RESOLVE) DWI at b = 1000 s/mm2 and b = 2000 s/mm2 were acquired with 3.0T MRI. ASSESSMENT: The corresponding apparent diffusion coefficient (ADC) maps (ADC1000 and ADC2000 ) were registered to T2 WI. Regions of interest (ROIs) were manually drawn along the solid part of the tumor from the coregistered T2 WI-ADC images. The texture parameters from T2 WI, ADC1000 , and ADC2000 were acquired. STATISTICAL TESTS: The texture parameters were compared between the two types by using unpaired Student's t-test. Receiver operating characteristic (ROC) curves and logistic regression analyses were used to assess their diagnostic performance. RESULTS: Significant differences in TA parameters of ADC1000 and ADC2000 were observed between soft and hard types (P < 0.05 for all), whereas the TA of T2 WI resulted in no significant difference (P > 0.05 for all). TA of ADC2000 provided a superior diagnostic performance compared with that of ADC1000 (P = 0.038). A combination of mean value and entropy of ADC2000 yielded an AUC, a sensitivity, and a specificity of 0.911, 78.4% and 92.3%, respectively. DATA CONCLUSION: TA of ADC values were useful for assessing the tumor consistency of pituitary macroadenomas. ADC2000 may facilitate better type discrimination. LEVEL OF EVIDENCE: 3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1507-1513.

Intergrating conventional MRI, texture analysis of dynamic contrast-enhanced MRI, and susceptibility weighted imaging for glioma grading.

BACKGROUND: The application of conventional magnetic resonance imaging (MRI) in glioma grading is limited and non-specific. PURPOSE: To investigate the application values of MRI, texture analysis (TA) of dynamic contrast-enhanced MRI (DCE-MRI) and intratumoral susceptibility signal (ITSS) on susceptibility weighted imaging (SWI), alone and in combination, for glioma grading. MATERIAL AND METHODS: Fifty-two patients with pathologically confirmed gliomas who underwent DCE-MRI and SWI were enrolled in this retrospective study. Conventional MRIs were evaluated by the VASARI scoring system. TA of DCE-MRI-derived parameters and the degree of ITSS were compared between low-grade gliomas (LGGs) and high-grade gliomas (HGGs). The diagnostic ability of each parameter and their combination for glioma grading were analyzed. RESULTS: Significant statistical differences in VASARI features were observed between LGGs and HGGs ( P < 0.05), of which the enhancement quality had the highest area under the curve (AUC) (0.873) with 93.3% sensitivity and 80% specificity. The TA of DCE-MRI derived parameters were significantly different between LGGs and HGGs ( P < 0.05), of which the uniformity of Ktrans had the highest AUC (0.917) with 93.3% sensitivity and 90% specificity. The degree of ITSS was significantly different between LGGs and HGGs ( P < 0.001). The AUC of the ITSS was 0.925 with 93.3% sensitivity and 90% specificity. The best discriminative power was obtained from a combination of enhancement quality, Ktrans- uniformity, and ITSS, resulting in 96.7% sensitivity, 100.0% specificity, and AUC of 0.993. CONCLUSION: Combining conventional MRI, TA of DCE-MRI, and ITSS on SWI may help to improve the differentiation between LGGs and HGGs.

Ectopic meningioma in a patient with neurofibromatosis Type 2: a case report and review of the literature.

Ectopic meningioma occurring in the region of parapharyngeal space is rare in clinical practice and brings great challenge in its diagnosis. This report details such a case in a 14-year-old girl with neurofibromatosis Type 2, which is a highly infrequent association. The clinical manifestations, imaging findings, and pathological manifestations are described, and the relevant literature is reviewed to highlight characteristic imaging findings of ectopic meningiomas.

Orbital benign and malignant lymphoproliferative disorders: Differentiation using semi-quantitative and quantitative analysis of dynamic contrast-enhanced magnetic resonance imaging.

OBJECTIVES: To assess the value of dynamic contrast-enhanced MR imaging (DCE-MRI) in differentiating benign from malignant orbital lymphoproliferative disorders (OLPDs). METHODS: Thirty-nine patients with orbital lymphoproliferative disorders (21 malignant and 18 benign) underwent DCE-MRI scan for pre-treatment evaluation from March 2013 to December 2015. Both semi-quantitative (TTP, AUC, Slopemax) and quantitative (Ktrans, kep, ve) parameters were calculated, and compared between two groups. Receiver operating characteristic (ROC) curve analyses were used to determine the diagnostic value of each significant parameter. RESULTS: Malignant OLPDs showed significantly higher kep, lower ve, and lower AUC than benign OLPDs, while no significant differences were found on Ktrans, TTP and Slopemax. ROC analyses indicated that ve exhibited the best diagnostic performance in predicting malignant OLPDs (cutoff value, 0.211; area under the curve, 0.896; sensitivity, 76.2%; specificity, 94.9%), followed by kep (cutoff value, 0.853; area under the curve, 0.839; sensitivity, 85.7%; specificity, 89.9%). CONCLUSION: DCE-MRI and specially its derived quantitative parameters of kep and ve are promising metrics for differentiating malignant from benign OLPDs.

Radiological indeterminate vestibular schwannoma and meningioma in cerebellopontine angle area: differentiating using whole-tumor histogram analysis of apparent diffusion coefficient.

PURPOSE: To assess the role of whole-tumor histogram analysis of apparent diffusion coefficient (ADC) maps in differentiating radiological indeterminate vestibular schwannoma (VS) from meningioma in cerebellopontine angle (CPA). MATERIALS AND METHODS: Diffusion-weighted (DW) images (b = 0 and 1000 s/mm2) of pathologically confirmed and radiological indeterminate CPA meningioma (CPAM) (n = 27) and VS (n = 12) were retrospectively collected and processed with mono-exponential model. Whole-tumor regions of interest were drawn on all slices of the ADC maps to obtain histogram parameters, including the mean ADC (ADCmean), median ADC (ADCmedian), 10th/25th/75th/90th percentile ADC (ADC10, ADC25, ADC75 and ADC90), skewness and kurtosis. The differences of ADC histogram parameters between CPAM and VS were compared using unpaired t-test. Multiple receiver operating characteristic (ROC) curves analysis was used to determine and compare the diagnostic value of each significant parameter. RESULTS: Significant differences were found on the ADCmean, ADCmedian, ADC10, ADC25, ADC75 and ADC90 between CPAM and VS (all p values < 0.001), while no significant difference was found on kurtosis (p = 0.562) and skewness (p = 0.047). ROC curves analysis revealed, a cut-off value of 1.126 × 10-3 mm2/s for the ADC90 value generated highest area under curves (AUC) for differentiating CPAM from VS (AUC, 0.975; sensitivity, 100%; specificity, 88.9%). CONCLUSIONS: Histogram analysis of ADC maps based on whole tumor can be a useful tool for differentiating radiological indeterminate CPAM from VS. The ADC90 value was the most promising parameter for differentiating these two entities.

Utility of histogram analysis of ADC maps for differentiating orbital tumors.

PURPOSE: We aimed to evaluate the role of histogram analysis of apparent diffusion coefficient (ADC) maps for differentiating benign and malignant orbital tumors. METHODS: Fifty-two patients with orbital tumors were enrolled from March 2013 to November 2014. Pretreatment diffusion-weighted imaging was performed on a 3T magnetic resonance scanner with b factors of 0 and 800 s/mm2, and the corresponding ADC maps were generated. Whole-tumor regions of interest were drawn on all slices of the ADC maps to obtain histogram parameters, including ADCmean, ADCmedian, standard deviation (SD), skewness, kurtosis, quartile, ADC10, ADC25, ADC75, and ADC90. Histogram parameter differences between benign and malignant orbital tumors were compared. The diagnostic value of each significant parameter in predicting malignant tumors was established. RESULTS: Age, ADCmean, ADCmedian, quartile, kurtosis, ADC10, ADC25, ADC75, and ADC90 parameters were significantly different between benign and malignant orbital tumor groups, while gender, location, SD, and skewness were not significantly different. The best diagnostic performance in predicting malignant orbital tumors was achieved at the threshold of ADC10=0.990 (AUC, 0.997; sensitivity, 96.2%; specificity, 100%). CONCLUSION: Histogram analysis of ADC maps holds promise for differentiating benign and malignant orbital tumors. ADC10 has the potential to be the most significant parameter for predicting malignant orbital tumors.

Orbital Indeterminate Lesions in Adults: Combined Magnetic Resonance Morphometry and Histogram Analysis of Apparent Diffusion Coefficient Maps for Predicting Malignancy.

RATIONALE AND OBJECTIVES: The aim of this study was to evaluate the added value of histogram analysis of apparent diffusion coefficient (ADC) maps in differentiating indeterminate orbital malignant tumors from benign tumors, compared to using magnetic resonance (MR) morphological features alone. MATERIALS AND METHODS: We retrospectively evaluated 54 patients with orbital tumors from March 2013 to February 2015. All the patients were assessed by both routine MR and diffusion-weighted imaging, and divided into benign group and malignant group. Routine MR imaging features and histogram parameters derived from ADC maps, including mean ADC (ADCmean), median ADC (ADCmedian), standard deviation, skewness, kurtosis, and 10th and 90th percentiles of ADC (ADC10 and ADC90), were compared between two groups. Univariate and multivariate logistic regression analyses were used to identify the most valuable variables in predicting malignancy. Receiver operating characteristic (ROC) curve analysis was used to determine the diagnostic value of significant variables. RESULTS: Multivariate logistic regression analysis indicated that two or more quadrants involved, iso-intense on T2-weighted imaging (T2WI), and ADC10 were significant predictors for orbital malignancy. By using model 2 (iso-intense on T2WI + two or more quadrants involved + ADC10 < 0.990) as the criterion, higher AUC and specificity could be achieved than by using model 1 (iso-intense on T2WI + two or more quadrants involved) alone, (model 2 vs model 1; area under curve (AUC), 0.827 vs 0.793; sensitivity, 65.4% vs 69.2%; specificity, 100% vs 89.3%). CONCLUSIONS: Iso-intense on T2WI, two or more quadrants involved, and ADC10 are risk factors for orbital malignancy. Histogram analysis of ADC map might provide added value in predicting orbital malignancy.

Clinical evaluation and follow-up outcome of diffusion tensor imaging-based functional neuronavigation: a prospective, controlled study in patients with gliomas involving pyramidal tracts.

OBJECTIVE: To evaluate diffusion tensor imaging (DTI)-based functional neuronavigation in surgery of cerebral gliomas with pyramidal tract (PT) involvement with respect to both perioperative assessment and follow-up outcome. METHODS: A prospective, randomized controlled study was conducted between 2001 and 2005. A consecutive series of 238 eligible patients with initial imaging diagnosis of cerebral gliomas involving PTs were randomized into study (n = 118) and control (n = 120) groups. The study cases underwent DTI and three-dimensional magnetic resonance imaging scans. The maps of fractional anisotropy were calculated for PT mapping. Both three-dimensional magnetic resonance imaging data sets and fractional anisotropy maps were integrated by rigid registration, after which the tumor and adjacent PT were segmented and reconstructed for presurgical planning and intraoperative guidance. The control cases were operated on using routine neuronavigation. RESULTS: There was a trend for high-grade gliomas (HGGs) in the study group to be more likely to achieve gross total resection (74.4 versus 33.3%, P < 0.001). There was no significant difference of low-grade gliomas resection between the two groups. Postoperative motor deterioration occurred in 32.8% of control cases, whereas it occurred in only 15.3% of the study cases (P < 0.001). The 6-month Karnofsky Performance Scale score of study cases was significantly higher than that of control cases (86 +/- 20 versus 74 +/- 28 overall, P < 0.001; 93 +/- 10 versus 86 +/- 17 for low-grade gliomas, P = 0.013; and 77 +/- 27 versus 53 +/- 32 for HGGs, P = 0.001). For 81 HGGs, the median survival of study cases was 21.2 months (95% confidence interval, 14.1-28.3 mo) compared with 14.0 months (95% confidence interval, 10.2-17.8 mo) of control cases (P = 0.048). The estimated hazard ratio for the effect of DTI-based functional neuronavigation was 0.570, representing a 43.0% reduction in the risk of death. CONCLUSION: DTI-based functional neuronavigation contributes to maximal safe resection of cerebral gliomas with PT involvement, thereby decreasing postoperative motor deficits for both HGGs and low-grade gliomas while increasing high-quality survival for HGGs.

[Role of diffusion tensor imaging in neuronavigation surgery of brain tumors involving pyramidal tracts].

OBJECTIVE: To explore the role of diffusion tensor imaging (DTI) in neuronavigation surgery of brain tumors involving pyramidal tracts. METHODS: Forty-nine patients with brain tumors involving pyramidal tracts were randomly divided into trial group (DTI navigation) and control group (traditional navigation). The patients in trial group underwent DTI and T1 weighted 3D navigational magnetic resonance imaging (MRI) studies. The main white matter tracts were constructed by the DTI datasets, and merged to the anatomical structure, which was delineated by the T1-weighted three-dimensional fast spoiled gradient recalled sequence (3D/FSPGR). The relationship between the tumors and adjacent pyramidal tracts were segmented and reconstructed for three-dimensional visualization. RESULTS: In 25 patients of trial group and 24 patients of control group, the statistic analysis confirmed well balance of main variations. The tumors were completely resected in 12 patients (50.0%) of control group and in 20 patients (80.0%) of trial group (P < 0.05). Postoperative aggravated contralateral extremities weakness or hemiplegia due to pyramidal tract injury occurring in 75.0% cases of control group whereas only 20.0% patients in trial group (P < 0.01). The mean Karnofsky scale were 69.58 +/- 23.49 and 84.80 +/- 23.49 respectively in control and trial groups (P < 0.05). The excellent outcome ratio (Karnofsky scale = 90 - 100) was 37.5% in control group and 72.0% in trial group respectively (P < 0.05). CONCLUSIONS: DTI allows individual estimation of large fiber tracts of brain. Furthermore, to integrate spatial three-dimensional information concerning the white matter tracts into traditional neuronavigation images during surgery, was valuable in presenting topographical character of involving (shift or erosive) pyramidal tracts and relationship with the margins of neighboring tumors. The mapping of large fiber tracts was a safe, efficient, reliable technique. DTI should be routinely used in neuronavigation surgery of brain tumor involving pyramidal tracts to plan the optimal trajectory and ensure total resection of the lesions during operation, as well as to decrease potential disability after operation and to shorten the length of hospitalization.