Browse > Article
http://dx.doi.org/10.3348/kjr.2016.17.1.117

Pre-Operative Perfusion Skewness and Kurtosis Are Potential Predictors of Progression-Free Survival after Partial Resection of Newly Diagnosed Glioblastoma  

Paik, Wooyul (Department of Radiology, Dankook University Hospital)
Kim, Ho Sung (Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center)
Choi, Choong Gon (Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center)
Kim, Sang Joon (Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center)
Publication Information
Korean Journal of Radiology / v.17, no.1, 2016 , pp. 117-126 More about this Journal
Abstract
Objective: To determine whether pre-operative perfusion skewness and kurtosis derived from normalized cerebral blood volume (nCBV) histograms are associated with progression-free survival (PFS) of patients after partial resection of newly diagnosed glioblastoma. Materials and Methods: A total of 135 glioblastoma patients who had undergone partial resection of tumor (resection of < 50% of pre-operative tumor volume or surgical biopsy) confirmed with immediate postsurgical MRI and examined with both conventional MRI and dynamic susceptibility contrast (DSC) perfusion MRI before the surgery were retrospectively reviewed in this study. They had been followed up post-surgical chemoradiotherapy for tumor progression. Using histogram analyses of nCBV derived from pre-operative DSC perfusion MRI, patients were sub-classified into the following four groups: positive skewness and leptokurtosis (group 1); positive skewness and platykurtosis (group 2); negative skewness and leptokurtosis (group 3); negative skewness and platykurtosis (group 4). Kaplan-Meier analysis and multivariable Cox proportional hazards regression analysis were performed to determine whether clinical and imaging covariates were associated with PFS or overall survival (OS) of these patients. Results: According to the Kaplan-Meier method, median PFS of group 1, 2, 3, and 4 was 62, 51, 39, and 41 weeks, respectively, with median OS of 82, 77, 77, and 72 weeks, respectively. In multivariable analyses with Cox proportional hazards regression, pre-operative skewness/kurtosis pattern (hazard ratio: 2.98 to 4.64; p < 0.001), Karnofsky performance scale score (hazard ratio: 1.04; p = 0.003), and post-operative tumor volume (hazard ratio: 1.04; p = 0.02) were independently associated with PFS but not with OS. Conclusion: Higher skewness and kurtosis of nCBV histogram before surgery were associated with longer PFS in patients with newly diagnosed glioblastoma after partial tumor resection.
Keywords
Brain; Glioblastoma; Surgery; Chemoradiotherapy; Perfusion; Magnetic resonance imaging;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 Emblem KE, Scheie D, Due-Tonnessen P, Nedregaard B, Nome T, Hald JK, et al. Histogram analysis of MR imaging-derived cerebral blood volume maps: combined glioma grading and identification of low-grade oligodendroglial subtypes. AJNR Am J Neuroradiol 2008;29:1664-1670   DOI
2 Wen PY, Macdonald DR, Reardon DA, Cloughesy TF, Sorensen AG, Galanis E, et al. Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group. J Clin Oncol 2010;28:1963-1972   DOI
3 Rosen BR, Belliveau JW, Vevea JM, Brady TJ. Perfusion imaging with NMR contrast agents. Magn Reson Med 1990;14:249-265   DOI
4 Ostergaard L, Weisskoff RM, Chesler DA, Gyldensted C, Rosen BR. High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I: Mathematical approach and statistical analysis. Magn Reson Med 1996;36:715-725   DOI
5 Boxerman JL, Schmainda KM, Weisskoff RM. 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 2006;27:859-867
6 Pope WB, Kim HJ, Huo J, Alger J, Brown MS, Gjertson D, et al. Recurrent glioblastoma multiforme: ADC histogram analysis predicts response to bevacizumab treatment. Radiology 2009;252:182-189   DOI
7 Nowosielski M, Recheis W, Goebel G, Guler O, Tinkhauser G, Kostron H, et al. ADC histograms predict response to antiangiogenic therapy in patients with recurrent high-grade glioma. Neuroradiology 2011;53:291-302   DOI
8 Bisdas S, Kirkpatrick M, Giglio P, Welsh C, Spampinato MV, Rumboldt Z. Cerebral blood volume measurements by perfusion-weighted MR imaging in gliomas: ready for prime time in predicting short-term outcome and recurrent disease? AJNR Am J Neuroradiol 2009;30:681-688   DOI
9 Barajas RF Jr, Hodgson JG, Chang JS, Vandenberg SR, Yeh RF, Parsa AT, et al. Glioblastoma multiforme regional genetic and cellular expression patterns: influence on anatomic and physiologic MR imaging. Radiology 2010;254:564-576   DOI
10 Oh J, Henry RG, Pirzkall A, Lu Y, Li X, Catalaa I, et al. Survival analysis in patients with glioblastoma multiforme: predictive value of choline-to-N-acetylaspartate index, apparent diffusion coefficient, and relative cerebral blood volume. J Magn Reson Imaging 2004;19:546-554   DOI
11 Law M, Oh S, Babb JS, Wang E, Inglese M, Zagzag D, et al. Low-grade gliomas: dynamic susceptibility-weighted contrastenhanced perfusion MR imaging--prediction of patient clinical response. Radiology 2006;238:658-667   DOI
12 Jahng GH, Li KL, Ostergaard L, Calamante F. Perfusion magnetic resonance imaging: a comprehensive update on principles and techniques. Korean J Radiol 2014;15:554-577   DOI
13 Lev MH, Ozsunar Y, Henson JW, Rasheed AA, Barest GD, Harsh GR 4th, et al. Glial tumor grading and outcome prediction using dynamic spin-echo MR susceptibility mapping compared with conventional contrast-enhanced MR: confounding effect of elevated rCBV of oligodendrogliomas [corrected]. AJNR Am J Neuroradiol 2004;25:214-221
14 Price SJ, Jena R, Burnet NG, Hutchinson PJ, Dean AF, Pena A, et al. Improved delineation of glioma margins and regions of infiltration with the use of diffusion tensor imaging: an image-guided biopsy study. AJNR Am J Neuroradiol 2006;27:1969-1974
15 Smith JS, Jenkins RB. Genetic alterations in adult diffuse glioma: occurrence, significance, and prognostic implications. Front Biosci 2000;5:D213-D231
16 Cao Y, Tsien CI, Nagesh V, Junck L, Ten Haken R, Ross BD, et al. Survival prediction in high-grade gliomas by MRI perfusion before and during early stage of RT [corrected]. Int J Radiat Oncol Biol Phys 2006;64:876-885   DOI
17 Law M, Young RJ, Babb JS, Peccerelli N, Chheang S, Gruber ML, et al. Gliomas: predicting time to progression or survival with cerebral blood volume measurements at dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging. Radiology 2008;247:490-498   DOI
18 Lee EK, Choi SH, Yun TJ, Kang KM, Kim TM, Lee SH, et al. Prediction of response to concurrent chemoradiotherapy with temozolomide in glioblastoma: application of immediate post-operative dynamic susceptibility contrast and diffusionweighted MR imaging. Korean J Radiol 2015;16:e148
19 Emblem KE, Bjornerud A. An automatic procedure for normalization of cerebral blood volume maps in dynamic susceptibility contrast-based glioma imaging. AJNR Am J Neuroradiol 2009;30:1929-1932   DOI
20 Kim HS, Kim JH, Kim SH, Cho KG, Kim SY. 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;256:906-915   DOI
21 Emblem KE, Nedregaard B, Nome T, Due-Tonnessen P, Hald JK, Scheie D, et al. Glioma grading by using histogram analysis of blood volume heterogeneity from MR-derived cerebral blood volume maps. Radiology 2008;247:808-817   DOI
22 Law M, Young R, Babb J, Pollack E, Johnson G. Histogram analysis versus region of interest analysis of dynamic susceptibility contrast perfusion MR imaging data in the grading of cerebral gliomas. AJNR Am J Neuroradiol 2007;28:761-766