Identification of a candidate biomarker from perfusion MRI to anticipate glioblastoma progression after chemoradiation (original) (raw)
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World Neurosurgery, 2018
BACKGROUND: Many prognostic factors influence overall survival (OS) of patients with glioblastoma. Despite gross total resection and Stupp protocol adherence, many patients have poor survival. Perfusion magnetic resonance imaging may assist in diagnosis, treatment monitoring, and prognostication.-METHODS: This retrospective study of 36 patients with glioblastoma assessed influence of preoperative magnetic resonance imaging parameters reflecting tumor cell density and vascularity and patient age on OS.-RESULTS: The area under curve based on optimal receiver operating characteristic curves for the perfusion parameters normalized relative tumor blood volume (n_rTBV) and normalized relative tumor blood flow (n_rTBF) were 0.92 and 0.89, respectively, and the highest among all imaging parameters and age. OS showed strongly negative correlations with corrected n_rTBV (R [ L0.70; P < 0.001) and n_rTBF (R [ L0.67; P < 0.001). The Cox model, which included age and imaging parameters, demonstrated that n_rTBV and n_rTBF were most predictive of OS, with hazard ratios of 5.97 (P [ 0.0001) and 8.76 (P [ 0.0001), respectively, compared with 1.63 (P [ 0.19) for age. Eighteen patients with corrected n_rTBV £2.5 (best cutoff value) had a median OS of 15.1 months (95% confidence interval (CI), 11.34e21.25) compared with 2.8 months (95% CI, 1.48e4.03; P < 0.001) for 18 patients with corrected n_rTBV >2.5. Twenty-four patients with n_rTBF £2.79 had a median OS of 12 months (95% CI, 10.46e17.9) compared with 2.8 months for 12 patients with n_rTBF >2.79 (95% CI, 1.31e4.2; P < 0.001).-CONCLUSIONS: The dominant predictors of OS are normalized perfusion parameters n_rTBV and n_rTBF. Preoperative perfusion imaging may be used as a surrogate to predict glioblastoma aggressiveness and survival independent of treatment.
Purpose: Dynamic contrast enhanced (DCE) MRI is used to grade and to monitor the progression of glioma while on treatment. Usually, a fixed hematocrit (Hct) value for adults is assumed to be ~45%; however, it is actually known for individual variations. Purpose of this study was to investigate the effect of measured Hct values in glioma grading using DCE-MRI. Materials and methods: Fifty glioma patients were included in this study. Kinetic and hemodynamic parameters were estimated for each patient using assumed as well as measured Hct values. To look the changes in Hct value over time, Hct was measured multiple times from 10 of these glioma patients who were on treatment. Simulation was done to look for the effect of extreme variations of Hct values on perfusion metrics. The data was compared to look for significant differences in the perfusion metrics derived from assumed and measured Hct values. Results: The measured Hct value in patients was found to be (40.4 ± 4.28)%. The sensitivity and specificity of DCE-MRI parameters in glioma grading were not significantly influenced by using measured vis-a-vis assumed Hct values. The serial Hct values from 10 patients who were on treatment showed a fluctuation of 15–20% over time. The simulated data showed linear influence of Hct values on kinetic parameters. The tumor grading was altered on altering the Hct values in borderline cases. Conclusion: Hct values influence the hemodynamic and kinetic metrics linearly and may affect glioma grading. However, perfusion metrics values might change significantly with large change in Hct values, especially in patients who are on chemotherapy necessitating its use in the DCE model.
Translational Oncology, 2015
OBJECTIVES: This study evaluates the repeatability of brain perfusion using dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) with a variety of post-processing methods. METHODS: Thirty-two patients with newly diagnosed glioblastoma were recruited. On a 3-T MRI using a dual-echo, gradient-echo spin-echo DSC-MRI protocol, the patients were scanned twice 1 to 5 days apart. Perfusion maps including cerebral blood volume (CBV) and cerebral blood flow (CBF) were generated using two contrast agent leakage correction methods, along with testing normalization to reference tissue, and application of arterial input function (AIF). Repeatability of CBV and CBF within tumor regions and healthy tissues, identified by structural images, was assessed with intra-class correlation coefficients (ICCs) and repeatability coefficients (RCs). Coefficients of variation (CVs) were reported for selected methods. RESULTS: CBV and CBF were highly repeatable within tumor with ICC values up to 0.97. However, both CBV and CBF showed lower ICCs for healthy cortical tissues (up to 0.83), healthy gray matter (up to 0.95), and healthy white matter (WM; up to 0.93). The values of CV ranged from 6% to 10% in tumor and 3% to 11% in healthy tissues. The values of RC relative to the mean value of measurement within healthy WM ranged from 22% to 42% in tumor and 7% to 43% in healthy tissues. These percentages show how much variation in perfusion parameter, relative to that in healthy WM, we expect to observe to www.transonc.com Translational Oncology
Frontiers in aging neuroscience, 2017
To evaluate the feasibility of a simplified method based on diffusion-weighted imaging (DWI) acquired with three b-values to measure tissue perfusion linked to microcirculation, to validate it against from perfusion-related parameters derived from intravoxel incoherent motion (IVIM) and dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging, and to investigate its utility to differentiate low-from high-grade gliomas. Materials and Methods: The prospective study was approved by the local institutional review board and written informed consent was obtained from all patients. From May 2016 and May 2017, 50 patients confirmed with glioma were assessed with multib-value DWI and DCE MR imaging at 3.0 T. Besides conventional apparent diffusion coefficient (ADC 0,1000) map, perfusion-related parametric maps for IVIM-derived perfusion fraction (f) and pseudodiffusion coefficient (D *), DCE MR imaging-derived pharmacokinetic metrics, including K trans , v e and v p , as well as a metric named simplified perfusion fraction (SPF), were generated. Correlation between perfusionrelated parameters was analyzed by using the Spearman rank correlation. All imaging parameters were compared between the low-grade (n = 19) and high-grade (n = 31) groups by using the Mann-Whitney U test. The diagnostic performance for tumor grading was evaluated with receiver operating characteristic (ROC) analysis. Results: SPF showed strong correlation with IVIM-derived f and D * (ρ = 0.732 and 0.716, respectively; both P < 0.001). Compared with f, SPF was more correlated with DCE MR imaging-derived K trans (ρ = 0.607; P < 0.001) and v p (ρ = 0.397; P = 0.004). Among all parameters, SPF achieved the highest accuracy for differentiating low-from high-grade gliomas, with an area under the ROC curve value of 0.942, which was significantly higher than that of ADC 0,1000 (P = 0.004). By using SPF as a discriminative index, the diagnostic sensitivity and specificity were 87.1% and 94.7%, respectively, at the optimal cutoff value of 19.26%. Conclusion: The simplified method to measure tissue perfusion based on DWI by using three b-values may be helpful to differentiate low-from high-grade gliomas. SPF may
Utility of Perfusion Weighted MRI and MR Spectroscopy in Intra Cerebral Glioma Grading
Back ground: Perfusion weighted MRI and MR Spectroscopy are advanced non-invasive imaging techniques.Advanced MR imaging techniques provide physiological information which complements the conventional imaging findings in preoperative glioma grading. Histopathology is gold standard, but invasive technique. Relative cerebral blood volume (rcbv) measurements derived from perfusion MR imaging and metabolite ratios from MR spectroscopy are useful in predicting glioma grading. AIM: To evaluate the role of Perfusion weighted MRI and MR SPECTROSCOPY in preoperative grading of gliomas. Materials And Methods: Fifty patients with primary cerebeal glioma underwent MR perfusion and MR Spectroscopy pre-operatively.The rcbv measurements were obtained from enhancing areas or FLAIR hyperintensities. Metobolite ratios (Cho/CR, Cho/NAAand NAA/Cr) were measured at Te 30 and 135ms.Tumor grade determined with the two methods was then compared with that from histopathological grading. Receiver operating characteristics analysis were performed to determine the optimum thresholds for tumor grading. Sensitivity, specificity, PPV and NPV for identifying high-grade gliomas were also calculated. Results: Statistical analysis demonstrated a threshold value of1.54 for rcbv to provide sensitivity, specificity, PPV and NPV of84.8%,82.4%.90.3% and 73.6%respectively.Threshold values of 1.65 for cHo/cr and 1.42 for Cho/NAA provided the minimum c1,c2 errors, for determining the high-grade glioma.The combination of rcbv,Cho/Cr and Cho/NAA resulted in Sensitivity,specificity,PPV and NPV of 100%,76.5%,89.2% and 100% respectively.Statistically significant difference were noted in rcbv,Cho/Cr.Cho/NAA and NAA/Cr ratios between low-grade and high-grade glioma.(p<0.005) Conclusion: The rcbv measurements and metabolite ratios both in combination can increase sensitivity,specificity and NPV, when compared with PWI alone or MRS alone in detern=mining glioma grade.Threshold values can be used in a clinical setting to evaluate tumors preoperatively for histologic grade and provide a means for guiding treatment and predicting postoperative patient outcome.
AJNR. American journal of neuroradiology, 2004
Relative cerebral blood volume (rCBV) and vascular permeability (K(trans)) permit in vivo assessment of glioma microvasculature. We assessed the associations between rCBV and K(trans) derived from dynamic, susceptibility-weighted, contrast-enhanced (DSC) MR imaging and tumor grade and between rCBV and K(trans). Seventy-three patients with primary gliomas underwent conventional and DSC MR imaging. rCBVs were obtained from regions of maximal abnormality for each lesion on rCBV color maps. K(trans) was derived from a pharmacokinetic modeling algorithm. Histopathologic grade was compared with rCBV and K(trans) (Tukey honestly significant difference). Spearman and Pearson correlation factors were determined between rCBV, K(trans), and tumor grade. The diagnostic utility of rCBV and K(trans) in discriminating grade II or III tumors from grade I tumors was assessed by logistic regression. rCBV was significantly different for all three grades (P </=.0005). K(trans) was significantly diff...
American Journal of Neuroradiology, 2009
BACKGROUND AND PURPOSE: Current classification and grading of primary brain tumors has significant limitations. Our aim was to determine whether the relative cerebral volume (rCBV) measurements in gliomas may serve as an adjunct to histopathologic grading, with a hypothesis that rCBV values are more accurate in predicting 1-year survival and recurrence. MATERIALS AND METHODS: Thirty-four patients with gliomas (WHO grade I-IV, 27 astrocytomas, 7 tumors with oligodendroglial components) underwent contrast-enhanced MR rCBV measurements before treatment. The region of interest and the single pixel with the maximum CBV value within the tumors were normalized relative to the contralateral normal tissue (rCBV mean and rCBV max , respectively). Karnofsky performance score and progression-free survival (PFS) were recorded. Receiver operating characteristic curves and Kaplan-Meier survival analysis were conducted for CBV and histologic grade (WHO grade). RESULTS: Significant correlations were detected only when patients with oligodendrogliomas and oligoastrocytomas were excluded. The rCBV mean and rCBV max in the astrocytomas were 3.5 Ϯ 2.9 and 3.7 Ϯ 2.7. PFS correlated with rCBV parameters (r ϭ Ϫ0.54 to Ϫ0.56, P Յ .009). WHO grade correlated with rCBV values (r ϭ 0.65, P Յ .0002). rCBV max Ͼ4.2 was found to be a significant cutoff value for recurrence prediction with 77.8% sensitivity and 94.4% specificity (P ϭ .0001). rCBV max Յ3.8 was a significant predictor for 1-year survival (93.7% sensitivity, 72.7% specificity, P ϭ .0002). The relative risk for shorter PFS was 11.1 times higher for rCBV max Ͼ4.2 (P ϭ .0006) and 6.7 times higher for WHO grade ϾII (P ϭ .05). The combined CBVϪWHO grade classification enhanced the predictive value for recurrence/progression (P Ͻ .0001). CONCLUSIONS: rCBV values in astrocytomas but not tumors with oligodendroglial components are predictive for recurrence and 1-year survival and may be more accurate than histopathologic grading.