Effect of radiochemotherapy on the cognitive function and diffusion tensor and perfusion weighted imaging for high-grade gliomas: A prospective study.
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ABSTRACT:
SUBMITTER: Bian Y
PROVIDER: S-EPMC6461706 | biostudies-literature | 2019 Apr
REPOSITORIES: biostudies-literature
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Project description:PurposeGlioblastoma and anaplastic astrocytoma represent the most commonly encountered high-grade-glioma (HGG) in adults. Although both neoplasms are very distinct entities in context of epidemiology, clinical course and prognosis, their appearance in conventional magnetic resonance imaging (MRI) is very similar. In search for additional information aiding the distinction of potentially confusable neoplasms, histogram analysis of apparent diffusion coefficient (ADC) maps recently proved to be auxiliary in a number of entities. Therefore, our present exploratory retrospective study investigated whether ADC histogram profile parameters differ significantly between anaplastic astrocytoma and glioblastoma, reflect the proliferation index Ki-67, or are associated with the prognostic relevant MGMT (methylguanine-DNA methyl-transferase) promotor methylation status.MethodsPre-surgical ADC volumes of 56 HGG patients were analyzed by histogram-profiling. Association between extracted histogram parameters and neuropathology including WHO-grade, Ki-67 expression and MGMT promotor methylation status was investigated due to comparative and correlative statistics.ResultsGrade IV gliomas were more heterogeneous than grade III tumors. More specifically, ADCmin and the lowest percentile ADCp10 were significantly lower, whereas ADCmax, ADC standard deviation and Skewness were significantly higher in the glioblastoma group. ADCmin, ADCmax, ADC standard deviation, Kurtosis and Entropy of ADC histogram were significantly correlated with Ki-67 expression. No significant difference could be revealed by comparison of ADC histogram parameters between MGMT promotor methylated and unmethylated HGG.ConclusionsADC histogram parameters differ significantly between glioblastoma and anaplastic astrocytoma and show distinct associations with the proliferative activity in both HGG. Our results suggest ADC histogram profiling as promising biomarker for differentiation of both, however, further studies with prospective multicenter design are wanted to confirm and further elaborate this hypothesis.
| S-EPMC8049265 | biostudies-literature
Project description:PURPOSE:Perfusion and diffusion magnetic resonance imaging (MRI) provide important biomarkers for brain tumor analysis. Our aim was to investigate if regions of increased perfusion or tumor with restricted diffusion on the immediate post-operative MRI examination would be predictive of time to tumor progression in patients with high-grade gliomas. MATERIALS AND METHODS:Twenty-three patients with high-grade gliomas were retrospectively analyzed. We measured the perfusion at the resection area and evaluated the presence or absence of the restricted diffusion in residual tumor masses. The associations of the perfusion, diffusion and contrast enhancement (delayed static enhancement (DSE)) characteristics with time to tumor progression were statistically calculated. We also evaluated if the location of the tumor progression was concordant to the areas of the elevated perfusion, tumor type restricted diffusion and enhancement. RESULTS:Patients with >200 days to progression are more likely to have no elevated relative cerebral blood volume (rCBV) ratio (p = 0.0004), no tumor restriction (p = 0.024), and no DSE (p = 0.052). The elevated mean rCBV ratio (p<0.001) and tumor type restricted diffusion (p = 0.002) were significantly associated with a higher risk of progression. All cases with rCBV ratio of >1.5 progressed in 275 days or earlier. Tumors tended to progress at the area where patients with post-operative MRIs showed elevated perfusion (p = 0.006), tumor-type restricted diffusion (p = 0.005) and DSE (p = 0.008). CONCLUSIONS:Post-operative analysis of rCBV, tumor type restricted diffusion and enhancement characteristics are predictive of time to progression, risk of progression and where tumor progression is likely to occur.
| S-EPMC6422263 | biostudies-literature
Project description:The clinical value of MR diffusion tensor imaging (DTI) in grade diagnosis of gliomas was investigated. A total of 31 patients with glioma were administered 3.0T MR convention and DTI examination, with quantitative measurement of anisotropy coefficient fractional anisotropy (FA) and apparent dispersion coefficient (ADC) value, and the comparison of quantitative parameters of glioma between low- and high-grade, which was detected by Mann-Whitney U test. The receiver operation characteristic (ROC) curve was drawn to take the value of ADC and FA in tumor ROI as a critical point, to calculate the area under the curve and to confirm the diagnosis threshold value and evaluate its diagnostic efficiency. The FA value of 14 low-grade glioma cases was 139.4±81.3, with an ADC value of (1.36±0.21) ×10-3 mm2/sec. The FA value of 17 high-grade glioma cases was 103.1±41.5, with ADC value of (1.09±0.28)-3 mm2/sec; the difference between the two groups was statistically significant (P<0.05). The ADC value was taken as the critical point to judge tumor grade and draw the ROC curve; the area under the curve was 0.79. As the diagnosis threshold value, the ADC value of 1.11×10-3 mm2/sec was used to distinguish between low- and high-grade tumor with a sensitivity of 58.8% and specificity of 92.9%. The FA value was taken as a critical point to judge tumor grade and draw the ROC curve; the area under the curve was 0.62. As the diagnosis threshold value, the FA value of 178.9 was applied to distinguish between low- and high-grade tumor sensitivity of 94.1% and specificity of 35.7%. Therefore, the FA value and ADC value in DTI has an important estimated value for the pathological grade of glioma.
| S-EPMC5530196 | biostudies-other
Project description:BACKGROUND:Accurate diagnosis of high-grade glioma and solitary brain metastasis is clinically important because it affects the patient's outcome and alters patient management. PURPOSE:To evaluate the diagnostic performance of DWI and DTI for differentiating high-grade glioma from solitary brain metastasis. DATA SOURCES:A literature search of Ovid MEDLINE and EMBASE was conducted up to November 10, 2017. STUDY SELECTION:Studies evaluating the diagnostic performance of DWI and DTI for differentiating high-grade glioma from solitary brain metastasis were selected. DATA ANALYSIS:Summary sensitivity and specificity were established by hierarchic logistic regression modeling. Multiple subgroup analyses were also performed. DATA SYNTHESIS:Fourteen studies with 1143 patients were included. The individual sensitivities and specificities of the 14 included studies showed a wide variation, ranging from 46.2% to 96.0% for sensitivity and 40.0% to 100.0% for specificity. The pooled sensitivity of both DWI and DTI was 79.8% (95% CI, 70.9%-86.4%), and the pooled specificity was 80.9% (95% CI, 75.1%-85.5%). The area under the hierarchical summary receiver operating characteristic curve was 0.87 (95% CI, 0.84-0.89). The multiple subgroup analyses also demonstrated similar diagnostic performances (sensitivities of 76.8%-84.7% and specificities of 79.7%-84.0%). There was some level of heterogeneity across the included studies (I2 = 36%); however, it did not reach a level of concern. LIMITATIONS:The included studies used various DWI and DTI parameters. CONCLUSIONS:DWI and DTI demonstrated a moderate diagnostic performance for differentiation of high-grade glioma from solitary brain metastasis.
| S-EPMC7655439 | biostudies-literature
Project description:PURPOSE:Diffusion-weighted imaging (DWI) plays an important role in the preoperative assessment of gliomas; however, the diagnostic performance of histogram-derived parameters from mono-, bi-, and stretched-exponential DWI models in the grading of gliomas has not been fully investigated. Therefore, we compared these models' ability to differentiate between high-grade and low-grade gliomas. METHODS:This retrospective study included 22 patients with diffuse gliomas (age, 23-74 years; 12 males; 11 high-grade and 11 low-grade gliomas) who underwent preoperative 3 T-magnetic resonance imaging from October 2014 to August 2019. The apparent diffusion coefficient was calculated from the mono-exponential model. Using 13 b-values, the true-diffusion coefficient, pseudo-diffusion coefficient, and perfusion fraction were obtained from the bi-exponential model, and the distributed-diffusion coefficient and heterogeneity index were obtained from the stretched-exponential model. Region-of-interests were drawn on each imaging parameter map for subsequent histogram analyses. RESULTS:The skewness of the apparent diffusion, true-diffusion, and distributed-diffusion coefficients was significantly higher in high-grade than in low-grade gliomas (0.67?±?0.67 vs. -?0.18?±?0.63, 0.68?±?0.74 vs. -?0.08?±?0.66, 0.63?±?0.72 vs. -?0.15?±?0.73; P?=?0.0066, 0.0192, and 0.0128, respectively). The 10th percentile of the heterogeneity index was significantly lower (0.77?±?0.08 vs. 0.88?±?0.04; P?=?0.0004), and the 90th percentile of the perfusion fraction was significantly higher (12.64?±?3.44 vs. 7.14?±?1.70%: P?<?0.0001), in high-grade than in low-grade gliomas. The combination of the 10th percentile of the true-diffusion coefficient and 90th percentile of the perfusion fraction showed the best area under the receiver operating characteristic curve (0.96). CONCLUSION:The bi-exponential model exhibited the best diagnostic performance for differentiating high-grade from low-grade gliomas.
| S-EPMC7311374 | biostudies-literature
Project description:Introduction Determining the full extent of gliomas during radiotherapy planning can be challenging with conventional T1 and T2 magnetic resonance imaging (MRI). The purpose of this study was to develop a method to automatically calculate differences in the fractional anisotropy (FA) and mean diffusivity (MD) values in target volumes obtained with diffusion tensor imaging (DTI) by comparing with values from anatomically homologous voxels on the contralateral side of the brain. Methods Seven patients with a histologically confirmed glioma underwent postoperative radiotherapy planning with 1.5 T MRI and computed tomography. DTI was acquired using echo planar imaging for 20 noncolinear directions with b = 1000 s/mm2 and one additional image with b = 0, repeated four times for signal averaging. The distribution of FA and MD was calculated in the gross tumor volume (GTV), shells 0-5 mm, 5-10 mm, 10-15 mm, 15-20 mm, and 20-25 mm outside the GTV, and the GTV mirrored in the left-right direction (mirGTV). All images were aligned to a template image, and FA and MD interhemispheric difference images were calculated. The difference in mean FA and MD between the regions of interest was statistically tested using two-sided paired t-tests with ? = 0.05. Results The mean FA in mirGTV was 0.20 ± 0.04, which was larger than the FA in the GTV (0.12 ± 0.03) and shells 0-5 mm (0.15 ± 0.03) and 5-10 mm (0.17 ± 0.03) outside the GTV. The mean MD (×10-3 mm2/s) in mirGTV was 0.93 ± 0.09, which was smaller than the MD in the GTV (1.48 ± 0.19) and the peritumoral shells. The distribution of FA and MD interhemispheric differences followed the same trends as FA and MD values. Conclusions This study successfully implemented a method for calculation of FA and MD differences by comparison of voxel values with anatomically homologous voxels on the contralateral side of the brain. Further research is warranted to determine if radiotherapy planning using these images can be used to improve target delineation.
| S-EPMC5096944 | biostudies-literature
Project description:Background and purposeThe absence of acute ischemic lesions in diffusion-weighted imaging (DWI) in transient ischemic attack (TIA) patients makes it difficult to diagnose the true vascular etiologies. Among patients with DWI-negative TIA, we investigated whether the presence of a perfusion-weighted imaging (PWI) abnormality implied a true vascular event by identifying new acute ischemic lesions in follow-up magnetic resonance imaging (MRI) in areas corresponding to the initial PWI abnormality.MethodsThe included patients underwent DWI and PWI within 72 hours of TIA and also follow-up DWI at 3 days after the initial MRI. These patients had visited the emergency room between July 2009 and May 2015. Patients who demonstrated initial DWI lesions were excluded. The initial PWI abnormalities in the corresponding vascular territory were visually classified into three patterns: no abnormality, focal abnormality, and territorial abnormality.ResultsNo DWI lesions were evident in initial MRI in 345 of the 443 TIA patients. Follow-up DWI was applied to 87 of these 345 DWI-negative TIA patients. Initial PWI abnormalities were significantly associated with follow-up DWI abnormalities: 8 of 43 patients with no PWI abnormalities (18.6%) had new ischemic lesions, whereas 13 of 16 patients with focal perfusion abnormalities (81.2%) had new ischemic lesions in the areas of initial PWI abnormalities [odds ratio (OR)=15.1, 95% confidence interval (CI)=3.6-62.9], and 14 of 28 patients with territorial perfusion abnormalities (50%) had new lesions (OR=3.7, 95% CI=1.2-11.5).ConclusionsPWI is useful in defining whether or not the transient neurological symptoms in DWI-negative TIA are true vascular events, and will help to improve the understanding of the pathomechanism of TIA.
| S-EPMC5392454 | biostudies-literature
Project description:BackgroundDistinction between tumor and treatment related changes is crucial for clinical management of patients with high-grade gliomas. Our purpose was to evaluate whether dynamic susceptibility contrast-enhanced (DSC) and dynamic contrast enhanced (DCE) perfusion-weighted imaging (PWI) metrics can effectively differentiate between recurrent tumor and posttreatment changes within the enhancing signal abnormality on conventional MRI.MethodsA comprehensive literature search was performed for studies evaluating PWI-based differentiation of recurrent tumor and posttreatment changes in patients with high-grade gliomas (World Health Organization grades III and IV). Only studies published in the "temozolomide era" beginning in 2005 were included. Summary estimates of diagnostic accuracy were obtained by using a random-effects model.ResultsOf 1581 abstracts screened, 28 articles were included. The pooled sensitivities and specificities of each study's best performing parameter were 90% and 88% (95% CI: 0.85-0.94; 0.83-0.92) and 89% and 85% (95% CI: 0.78-0.96; 0.77-0.91) for DSC and DCE, respectively. The pooled sensitivities and specificities for detecting tumor recurrence using the 2 most commonly evaluated parameters, mean relative cerebral blood volume (rCBV) (threshold range, 0.9-2.15) and maximum rCBV (threshold range, 1.49-3.1), were 88% and 88% (95% CI: 0.81-0.94; 0.78-0.95) and 93% and 76% (95% CI: 0.86-0.98; 0.66-0.85), respectively.ConclusionsPWI-derived thresholds separating viable tumor from treatment changes demonstrate relatively good accuracy in individual studies. However, because of significant variability in optimal reported thresholds and other limitations in the existing body of literature, further investigation and standardization is needed before implementing any particular quantitative PWI strategy across institutions.
| S-EPMC5193025 | biostudies-literature
Project description:Background1p/19q co-deletion in low-grade gliomas (LGG, World Health Organization grade II and III) is of great significance in clinical decision making. We aim to use radiomics analysis to predict 1p/19q co-deletion in LGG based on amide proton transfer weighted (APTw), diffusion weighted imaging (DWI), and conventional MRI.MethodsThis retrospective study included 90 patients histopathologically diagnosed with LGG. We performed a radiomics analysis by extracting 8454 MRI-based features form APTw, DWI and conventional MR images and applied a least absolute shrinkage and selection operator (LASSO) algorithm to select radiomics signature. A radiomics score (Rad-score) was generated using a linear combination of the values of the selected features weighted for each of the patients. Three neuroradiologists, including one experienced neuroradiologist and two resident physicians, independently evaluated the MR features of LGG and provided predictions on whether the tumor had 1p/19q co-deletion or 1p/19q intact status. A clinical model was then constructed based on the significant variables identified in this analysis. A combined model incorporating both the Rad-score and clinical factors was also constructed. The predictive performance was validated by receiver operating characteristic curve analysis, DeLong analysis and decision curve analysis. P < 0.05 was statistically significant.ResultsThe radiomics model and the combined model both exhibited excellent performance on both the training and test sets, achieving areas under the curve (AUCs) of 0.948 and 0.966, as well as 0.909 and 0.896, respectively. These results surpassed the performance of the clinical model, which achieved AUCs of 0.760 and 0.766 on the training and test sets, respectively. After performing Delong analysis, the clinical model did not significantly differ in predictive performance from three neuroradiologists. In the training set, both the radiomic and combined models performed better than all neuroradiologists. In the test set, the models exhibited higher AUCs than the neuroradiologists, with the radiomics model significantly outperforming resident physicians B and C, but not differing significantly from experienced neuroradiologist.ConclusionsOur results suggest that our algorithm can noninvasively predict the 1p/19q co-deletion status of LGG. The predictive performance of radiomics model was comparable to that of experienced neuroradiologist, significantly outperforming the diagnostic accuracy of resident physicians, thereby offering the potential to facilitate non-invasive 1p/19q co-deletion prediction of LGG.
| S-EPMC11005152 | biostudies-literature
Project description:PurposeDifferentiation of high-grade gliomas and solitary brain metastases is an important clinical issue because the treatment strategies differ greatly. Our study aimed to investigate the potential value of diffusion tensor imaging (DTI) in differentiating high-grade gliomas from brain metastases using a meta-analytic approach.Materials and methodsWe searched Pubmed, Embase and the Cochrane Library for relevant articles published in English. Studies that both investigated high-grade gliomas and brain metastases using DTI were included. Random effect model was used to compare fractional anisotropy (FA) and mean diffusivity (MD) values in the two tumor entities.ResultsNine studies were included into the meta-analysis. In the peritumoral region, compared with brain metastases, high-grade gliomas had a significant increase of FA (SMD = 0.47; 95% CI, 0.22-0.71; P<0.01) and a significant decrease of MD (SMD = -1.49; 95% CI, -1.91 to -1.06; P<0.01). However, in the intratumoral area, no significant change in FA (SMD = 0.16; 95% CI, -0.49 to 0.82; P = 0.73) or MD (SMD = 0.34; 95% CI, -0.91 to 1.60; P = 0.59) was detected between gliomas and metastases.ConclusionsHigh-grade gliomas may be distinguished from brain metastases by comparing the peritumoral FA and MD values. DTI appears to be a promising tool in diagnosing solitary intracranial lesions.
| S-EPMC4224505 | biostudies-literature