scholarly journals Posttreatment High-Grade Glioma: Usefulness of Peak Height Position with Semiquantitative MR Perfusion Histogram Analysis in an Entire Contrast-enhanced Lesion for Predicting Volume Fraction of Recurrence

Radiology ◽  
2010 ◽  
Vol 256 (3) ◽  
pp. 906-915 ◽  
Author(s):  
Ho Sung Kim ◽  
Jang-Hee Kim ◽  
Se-Hyuk Kim ◽  
Kyung-Gi Cho ◽  
Sun Yong Kim
2020 ◽  
Vol 61 (9) ◽  
pp. 1221-1227
Author(s):  
Han-wen Zhang ◽  
Gui-wen Lyu ◽  
Wen-jie He ◽  
Yi Lei ◽  
Fan Lin ◽  
...  

Background In clinical diagnosis, some central nervous system lymphomas (CNSL) are difficult to distinguish from high-grade gliomas (HGG). Purpose To evaluate the diagnostic efficacy of the histogram analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in the identification of CNSL and HGG. Material and Methods In all, 43 patients diagnosed with HGG (n = 28) and CNSL (n = 15) by histopathology underwent DCE-MRI scanning. Differences in histogram parameters based on DCE-MRI between HGG and CNSL were analyzed by Mann–Whitney U test. In addition, receiver operating characteristic (ROC) analysis was performed. Short-term follow-up of patients was performed using Kaplan–Meier analysis to explore the survival rates of HGG and CNSL. Results For the ROC curve analysis, we demonstrate that the 10th percentile of Ktrans (area under the curve [AUC] = 0.912, sensitivity = 86.7%, specificity = 92.9%), Kep (AUC = 0.940, sensitivity = 93.3%, specificity = 79.6%), Ve (AUC = 0.907, sensitivity = 86.7%, specificity = 89.3%), and AUC (AUC = 0.904, sensitivity = 86.7%, specificity = 92.9%) were significantly different between the CNSL and HGG groups ( P < 0.001), with high diagnostic efficiency. Table 2 shows that the histogram features based on AUC maps (10th, 25th, median, 75th, 90th, and mean) were always significantly higher in the CNSL group than in the HGG group ( P < 0.001). There was no significant difference in Vp or in the 75th, 90th and mean of Ktrans, Kep, and Ve between the CNSL and HGG groups ( P > 0.05). Conclusion A histogram analysis of DCE-MRI identified significant differences between HGG and CNSL, and this will help in the clinical differential diagnosis of these conditions.


2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Prativa Sahoo ◽  
Paul Frankel ◽  
Julie Ressler ◽  
Margarita Gutova ◽  
Alexander J. Annala ◽  
...  

Background. The aim of this study was to correlate T1-weighted dynamic contrast-enhanced MRI- (DCE-MRI-) derived perfusion parameters with overall survival of recurrent high-grade glioma patients who received neural stem cell- (NSC-) mediated enzyme/prodrug gene therapy. Methods. A total of 12 patients were included in this retrospective study. All patients were enrolled in a first-in-human study (NCT01172964) of NSC-mediated therapy for recurrent high-grade glioma. DCE-MRI data from all patients were collected and analyzed at three time points: MRI#1—day 1 postsurgery/treatment, MRI#2— day 7 ± 3 posttreatment, and MRI#3—one-month follow-up. Plasma volume (Vp), permeability (Ktr), and leakage (λtr) perfusion parameters were calculated by fitting a pharmacokinetic model to the DCE-MRI data. The contrast-enhancing (CE) volume was measured from the last dynamic phase acquired in the DCE sequence. Perfusion parameters and CE at each MRI time point were recorded along with their relative change between MRI#2 and MRI#3 (Δ32). Cox regression was used to analyze patient survival. Results. At MRI#1 and at MRI#3, none of the parameters showed a significant correlation with overall survival (OS). However, at MRI#2, CE and λtr were significantly associated with OS (p<0.05). The relative λtr and Vp from timepoint 2 to timepoint 3 (Δ32λtr and Δ32Vp) were each associated with a higher hazard ratio (p<0.05). All parameters were highly correlated, resulting in a multivariate model for OS including only CE at MRI#2 and Δ32Vp, with an R2 of 0.89. Conclusion. The change in perfusion parameter values from 1 week to 1 month following NSC-mediated therapy combined with contrast-enhancing volume may be a useful biomarker to predict overall survival in patients with recurrent high-grade glioma.


2016 ◽  
Vol 58 (12) ◽  
pp. 1197-1208 ◽  
Author(s):  
Agne Ulyte ◽  
Vasileios K. Katsaros ◽  
Evangelia Liouta ◽  
Georgios Stranjalis ◽  
Christos Boskos ◽  
...  

2017 ◽  
Vol 19 (suppl_6) ◽  
pp. vi150-vi151
Author(s):  
Kathryn Nevel ◽  
Mark Schreyer ◽  
Katherine Panageas ◽  
Robert J Young ◽  
Mariza Daras

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