Added Value of Contrast Leakage Information over the CBV Value of DSC Perfusion MRI to Differentiate between Pseudoprogression and True Progression after Concurrent Chemoradiotherapy in Glioblastoma Patients
2
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
Purpose: To evaluate whether the added value of contrast leakage information from dynamic susceptibility contrast magnetic resonance imaging (DSC MRI) is a better prognostic imaging biomarker than the cerebral blood volume (CBV) value in distinguishing true progression from pseudoprogression in glioblastoma patients. Materials and Methods: Forty-nine glioblastoma patients who had undergone MRI after concurrent chemoradiotherapy with temozolomide were enrolled in this retrospective study. Twenty features were extracted from the normalized relative CBV (nCBV) and extraction fraction (EF) map of the contrast-enhancing region in each patient. After univariable analysis, we used multivariable stepwise logistic regression analysis to identify significant predictors for differentiating between pseudoprogression and true progression. Receiver operating characteristic (ROC) analysis was employed to determine the best cutoff values for the nCBV and EF features. Finally, leave-one-out cross-validation was used to validate the best predictor in differentiating between true progression and pseudoprogression. Results: Multivariable stepwise logistic regression analysis showed that MGMT (O6- methylguanine-DNA methyltransferase) and EF max were independent differentiating variables (P = 0.004 and P = 0.02, respectively). ROC analysis yielded the best cutoff value of 95.75 for the EF max value for differentiating the two groups (sensitivity, 61%; specificity, 84.6%; AUC, 0.681 ± 0.08; 95% CI, 0.524-0.837; P = 0.03). In the leave-one-out cross-validation of the EF max value, the cross-validated values for predicting true progression and pseudoprogression accuracies were 69.4% and 71.4%, respectively. Conclusion: We demonstrated that contrast leakage information parameter from DSC MRI showed significance in differentiating true progression from pseudoprogression in glioblastoma patients.
Abstract
Purpose: To evaluate whether the added value of contrast leakage information from dynamic susceptibility contrast magnetic resonance imaging (DSC MRI) is a better prognostic imaging biomarker than the cerebral blood volume (CBV) value in distinguishing true progression from pseudoprogression in glioblastoma patients. Materials and Methods: Forty-nine glioblastoma patients who had undergone MRI after concurrent chemoradiotherapy with temozolomide were enrolled in this retrospective study. Twenty features were extracted from the normalized relative CBV (nCBV) and extraction fraction (EF) map of the contrast-enhancing region in each patient. After univariable analysis, we used multivariable stepwise logistic regression analysis to identify significant predictors for differentiating between pseudoprogression and true progression. Receiver operating characteristic (ROC) analysis was employed to determine the best cutoff values for the nCBV and EF features. Finally, leave-one-out cross-validation was used to validate the best predictor in differentiating between true progression and pseudoprogression. Results: Multivariable stepwise logistic regression analysis showed that MGMT (O6- methylguanine-DNA methyltransferase) and EF max were independent differentiating variables (P = 0.004 and P = 0.02, respectively). ROC analysis yielded the best cutoff value of 95.75 for the EF max value for differentiating the two groups (sensitivity, 61%; specificity, 84.6%; AUC, 0.681 ± 0.08; 95% CI, 0.524-0.837; P = 0.03). In the leave-one-out cross-validation of the EF max value, the cross-validated values for predicting true progression and pseudoprogression accuracies were 69.4% and 71.4%, respectively. Conclusion: We demonstrated that contrast leakage information parameter from DSC MRI showed significance in differentiating true progression from pseudoprogression in glioblastoma patients.
참고문헌 (40)
- de Groot JF, "High-grade gliomas", Continuum(Minneap Minn), 21, pp.332~344 (2015)
- Ellingson BM, "Pseudoprogression, radionecrosis, inflammation or true tumor progression? challenges associated with glioblastoma response assessment in an evolving therapeutic landscape", J Neurooncol, 134, pp.495~504 (2017)
- Fajardo LF, "Radiation pathology" (2001), Oxford University Press
- Hygino da Cruz LC Jr, "Pseudoprogression and pseudoresponse : imaging challenges in the assessment of posttreatment glioma", AJNR Am J Neuroradiol, 32, pp.1978~1985 (2011)
- Linhares P, "Early pseudoprogression following chemoradiotherapy in glioblastoma patients : the value of RANO evaluation", J Oncol, 2013, pp.690585~ (2013)
- Barajas RF Jr, "Differentiation of recurrent glioblastoma multiforme from radiation necrosis after external beam radiation therapy with dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging", Radiology, 253, pp.486~496 (2009)
- Würdinger T, "Glioma angiogenesis : towards novel RNA therapeutics", Cell Adh Migr, 3, pp.230~235 (2009)
- Abbasi AW, "Incidence of tumour progression and pseudoprogression in high-grade gliomas : a systematic review and meta-analysis", Clin Neuroradiol, 28, pp.401~411 (2018)
- Bjørnerud A, "T1-and T2*-dominant extravasation correction in DSC-MRI : part I--theoretical considerations and implications for assessment of tumor hemodynamic properties", J Cereb Blood Flow Metab, 31, pp.2041~2053 (2011)
- Kim SH, "Prognostic predictions for patients with glioblastoma after standard treatment : application of contrast leakage information from DSC-MRI within nonenhancing FLAIR high-signal-intensity lesions", AJNR Am J Neuroradiol, 40, pp.2052~2058 (2019)
- Lee B, "Clinical value of vascular permeability estimates using dynamic susceptibility contrast MRI : improved diagnostic performance in distinguishing hypervascular primary CNS lymphoma from glioblastoma", AJNR Am J Neuroradiol, 39, pp.1415~1422 (2018)
- Emblem KE, "T(1)-and T(2)(*)-dominant extravasation correction in DSC-MRI : part IIpredicting patient outcome after a single dose of cediranib in recurrent glioblastoma patients", J Cereb Blood Flow Metab, 31, pp.2054~2064 (2011)
- Wang S, "Differentiating tumor progression from pseudoprogression in patients with glioblastomas using diffusion tensor imaging and dynamic susceptibility contrast MRI", AJNR Am J Neuroradiol, 37, pp.28~36 (2016)
- Young RJ, "MRI perfusion in determining pseudoprogression in patients with glioblastoma", Clin Imaging, 37, pp.41~49 (2013)
- Wen PY, "Updated response assessment criteria for high-grade gliomas : response assessment in neuro-oncology working group", J Clin Oncol, 28, pp.1963~1972 (2010)
- Yin J, "Comparison of K-means and fuzzy c-means algorithm performance for automated determination of the arterial input function", PLoS One, 9, pp.e85884~ (2014)
- Yan LF, "Perfusion, diffusion, or brain tumor barrier integrity: which represents the glioma features best?", Cancer Manag Res, 11, pp.9989~10000 (2019)
- Wong AM, "Comparison of three-dimensional pseudo-continuous arterial spin labeling perfusion imaging with gradient-echo and spin-echo dynamic susceptibility contrast MRI", J Magn Reson Imaging, 39, pp.427~433 (2014)
- Sanz-Requena R, "Automatic individual arterial input functions calculated from PCA outperform manual and population-averaged approaches for the pharmacokinetic modeling of DCE-MR images", J Magn Reson Imaging, 42, pp.477~487 (2015)
- Rosen BR, "Perfusion imaging with NMR contrast agents", Magn Reson Med, 14, pp.249~265 (1990)
- Ostergaard L, "High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I:mathematical approach and statistical analysis", Magn Reson Med, 36, pp.715~725 (1996)
- Kim JH, "Prognosis prediction of measurable enhancing lesion after completion of standard concomitant chemoradiotherapy and adjuvant temozolomide in glioblastoma patients : application of dynamic susceptibility contrast perfusion and diffusionweighted imaging", PLoS One, 9, pp.e113587~ (2014)
- Sourbron S, "Quantification of cerebral blood flow, cerebral blood volume, and blood-brain-barrier leakage with DCE-MRI", Magn Reson Med, 62, pp.205~217 (2009)
- Boxerman JL, "Relative cerebral blood volume maps corrected for contrast agent extravasation significantly correlate with glioma tumor grade, whereas uncorrected maps do not", AJNR Am J Neuroradiol, 27, pp.859~867 (2006)
- Kim JY, "Radiomics in peritumoral non-enhancing regions : fractional anisotropy and cerebral blood volume improve prediction of local progression and overall survival in patients with glioblastoma", Neuroradiology, 61, pp.1261~1272 (2019)
- Hauck WW, "A proposal for examining and reporting stepwise regressions", Stat Med, 10, pp.711~715 (1991)
- Thust SC, "Pseudoprogression of brain tumors", J Magn Reson Imaging, 48, pp.571~589 (2018)
- Cha J, "Differentiation of tumor progression from pseudoprogression in patients with posttreatment glioblastoma using multiparametric histogram analysis", AJNR Am J Neuroradiol, 35, pp.1309~1317 (2014)
- Park HH, "Pseudoprogression in glioblastoma patients : the impact of extent of resection", J Neurooncol, 126, pp.559~566 (2016)
- Boxerman JL, "Longitudinal DSC-MRI for distinguishing tumor recurrence from pseudoprogression in patients with a high-grade glioma", Am J Clin Oncol, 40, pp.228~234 (2017)
- Neska-Matuszewska M, "Differentiation of glioblastoma multiforme, metastases and primary central nervous system lymphomas using multiparametric perfusion and diffusion MR imaging of a tumor core and a peritumoral zone-Searching for a practical approach", PLoS One, 13, pp.e0191341~ (2018)
- Essig M, "Perfusion MRI : the five most frequently asked technical questions", AJR Am J Roentgenol, 200, pp.24~34 (2013)
- Soliman HM, "Recurrent brain tumor versus radiation necrosis;can dynamic susceptibility contrast(DSC)perfusion magnetic resonance imaging differentiate?", Egypt J Radiol Nucl Med, 49, pp.719~726 (2018)
- 송용섭, "True Progression versus Pseudoprogression in the Treatment of Glioblastomas: A Comparison Study of Normalized Cerebral Blood Volume and Apparent Diffusion Coefficient by Histogram Analysis", Korean Journal of Radiology, 14(4), pp.662~672 (2013), 대한영상의학회[DOI]
- Hu LS, "Relative cerebral blood volume values to differentiate high-grade glioma recurrence from posttreatment radiation effect : direct correlation between image-guided tissue histopathology and localized dynamic susceptibility-weighted contrastenhanced perfusion MR imaging measurements", AJNR Am J Neuroradiol, 30, pp.552~558 (2009)
- Jain R, "Permeability estimates in histopathology-proved treatment-induced necrosis using perfusion CT : can these add to other perfusion parameters in differentiating from recurrent", progressive tumors?, 2011, pp.32, 658~663
- Jain R, "Perfusion CT imaging of brain tumors : an overview", AJNR Am J Neuroradiol, 32, pp.1570~1577 (2011)
- Yong Wonn Kwon, "Dynamic Susceptibility Contrast (DSC) Perfusion MR in the Prediction of Long- Term Survival of Glioblastomas (GBM): Correlation with MGMT Promoter Methylation and 1p", 19q Deletions, 2018, pp.22(3), 158~167[DOI]
- Binabaj MM, "The prognostic value of MGMT promoter methylation in glioblastoma : a meta-analysis of clinical trials", J Cell Physiol, 233, pp.378~386 (2018)
- Brandes AA, "MGMT promoter methylation status can predict the incidence and outcome of pseudoprogression after concomitant radiochemotherapy in newly diagnosed glioblastoma patients", J Clin Oncol, 26, pp.2192~2197 (2008)
