Relative cerebral blood volume as response predictor in the treatment of recurrent glioblastoma with anti-angiogenic therapy

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Relative cerebral blood volume as response predictor in the treatment of recurrent glioblastoma with anti-angiogenic therapy

https://doi.org/10.21203/rs.3.rs-2010707/v1

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Introduction

Glioblastoma is one of the most common brain tumors in adult populations, usually carrying a poor prognosis. While several studies have researched the impact of anti-angiogenic therapies, especially anti VEFG treatments in glioblastoma, few have attempted to assess its progress using imaging studies.

Purpose

We attempted to analyze whether cerebral blood volume (rCBV) from dynamic susceptibility-weighted contrast-enhanced MRI (DSC-MRI) could predict a response in patients with glioblastoma undergoing Bevacizumab (BVZ) treatment.

Methods

We performed a retrospective study evaluating patients with recurrent glioblastoma receiving anti-angiogenic therapy with BVZ between 2012 and 2017 in our institution. Patients were scheduled for routine MRI at baseline and first month follow up visits. Studies were processed for DSC-MRI, cT1 and FLAIR images, from which relative cerebral blood volume measurements were obtained. We assessed patient response using the Response Assessment in Neuro-Oncology (RANO) working group criteria and overall survival.

Results

40 patients were included in the study and were classified as Bevacizumab responders and non-responders. Average rCBV before treatment was 4.5 for both groups and average rCBV was 2.5 for responders and 5.4 for non-responders. ROC curve set a cutoff point of 3.7 for rCBV predictive of response to BVZ. Cox Multivariate analysis only showed rCBV as a predictive factor of OS.

Conclusion

A statistically significant difference was found in rCBV between patients who responded and those who did not respond to BVZ treatment. rCBV may be a low cost and effective marker to assess response to Bevacizumab treatment in GBM.

glioblastoma

bevacizumab

relative cerebral blood volume and antiangiogenics

Glioblastoma is the most common primary brain tumor in adults with a dismal prognosis, having a mean survival time between 12 to 14 months [1]. Studies suggest that angiogenesis is a requirement for solid tumor growth [2–5]. Glioblastoma is highly vascularized, partly due to excessive levels of VEGF. This has led to the targeting of VEGF and other angiogenic growth factors by a new class of antiangiogenic drugs, many of which are currently being studied in randomized clinical trials [6–7]. The most studied antiangiogenic drug is Bevacizumab (BVZ), an FDA-approved therapy for patients with recurrent glioblastoma. Bevacizumab treatment commonly results in a longer progression-free survival rate (PFS) and a faster reduction of corticosteroid treatment. However, the role of bevacizumab in overall survival (OS) remains controversial [8]. Although perfusion-weighted MR techniques are exciting new tools for uncovering the change in vascularity that may result from antiangiogenic therapy, very few studies have employed these imaging studies for follow up of these therapies [9–13]. Relative cerebral blood volume (rCBV) imaging, which is obtained from dynamic susceptibility-weighted contrast-enhanced MRI (DSC-MRI), allows the characterization of the blood vessels in the tumor microenvironment and has shown promising results in the evaluation of brain tumors [14].Preclinical studies suggest that rCBV imaging may have the potential to monitor changes in vascularity associated to antiangiogenic treatment [15], even though its role for predicting response to BVZ treatment has not yet been fully evaluated. The aim of the present study was to analyze the relevance of DSC-MRI-derived rCBV analysis for predicting response to BVZ in patients with rGB.

Magnetic Resonance Imaging

Images were acquired in the routine clinical workup using a 3 Tesla MR system (Magnetom Verio/Trio TIM, Siemens Health- care) with a 12-channel head-matrix coil. Acquisition of the DSC-MRI sequence was performed as described previously. Prior dynamic imaging, a 0.1 mmol/kg pre-bolus dose of gadoterate meglumine (Gd-DOTA, DOTAREM, Guerbet, France) was administered to diminish T1 effects that might result from agent extravasation. DSC-PWI was obtained with a T2*-weighted gradient-echo EPI sequence during bolus injection of a standard dose (0.1 mmol/kg) of intravenous gadoterate meglumine. Twenty-six to 28 slices with a thickness of 5 mm were acquired with fat suppression (TE ¼ 36 milliseconds [ms], TR ¼ 2220 ms, FA ¼ 908, field of view ¼ 240× 240 mm, image matrix ¼ 128 × 128 mm). In total, 50 – 75 dynamic measurements were performed. Subsequently, postcontrast T1-weighted 3D magnetization-prepared rapid acquisition gradient echo (cT1; TI ¼ 1100 ms, TE ¼ 4 ms, TR ¼ 1710ms, and FA ¼ 158), and FLAIR (TI ¼ 2400 ms; TE ¼ 85 ms; TR ¼ 8500 ms; section thick- ness, 5 mm; interslice gap, 5%) images were acquired.

Image Post Processing and Analysis

Postprocessing of DSC-MRI, cT1 and FLAIR data was performed with dedicated software (Olea Sphere v 2.3, Olea Medical). First, tumor segmentation on cT1 and FLAIR images at baseline and at the first follow-up after BVZ/alkylating chemotherapy treatment were performed according to a semi-automated region-growing segmentation method. This segmentation approach examines neighboring voxels of an initial seed point/voxel and determines whether the voxel neighbors should be added to the region of interest (ROI). Multiple seed points were used to account for multifocal or discontinuing lesions, and iteration of this process was performed on each slice of the cT1 images until the contrast-enhancing portion of the whole tumor was included. Macroscopic necrosis, cysts, and normal vessels were excluded from the segmented tumor. Similarly, segmentation of the tumor on FLAIR images was performed on each slice until the hyperintense FLAIR abnormality (excluding those resulting from obvious leukoaraiosis) was included. Tumor volume (cm3) was calculated as the sum over all slices of (ROI area×[slice thickness + gap]). Postprocessing of DSC-MRI data included rigid-body registration to correct for motion artefacts. An arterial-input function (AIF) was determined automatically using cluster analysis techniques, 14 and deconvolution of the AIF was performed using a time-insensitive block-circulant singular value decomposition. Mathematically leakage-corrected, whole-brain rCBV maps were generated by using an established tracer kinetic model applied to the first-pass data, with rCBV values computed pixel-by-pixel as the area under the concentration time curve (AUC) divided by the AUC of the AIF. (AIF pixels are assumed to be made of 100% blood if partial volume effects are neglected.). This approach eliminates the need to draw a reference ROI in the contralateral nonaffected white matter for normalization of CBV values. Following automatic co-registration of rCBV maps with corresponding cT1 images that included the previously segmented cT1 ROIs, a mean rCBV (calculated as the mean of all individual rCBV voxels from the segmented tumor on cT1-images) was determined from both baseline and first follow-up after initiation of BVZ treatment.

Patients and Methods

We performed a retrospective study of patients with recurrent GB receiving BVZ from 2012 to 2017 at our institution in Mexico (Instituto Nacional de Neurología y Neurocirugía INNN). All participants met the following criteria: a) Pathologically confirmed recurrent GB on MRI in the period between December 2011 and December 2019 (primary GB only); b) Tumors previously treated with Radiotherapy and Temozolomide (either as concomitant or adjuvant therapy using 6 cycles); c) Undergoing standard treatment for recurrent GB using BVZ monotherapy (Bevacizumab; 15 mg/kg of body weight) every 3 weeks per cycle; d) Patients with MRI studies at baseline prior to chemotherapy with Perfusion MRI pretreatment.

Assessment of response to BVZ

We used the Response Assessment in Neuro-Oncology (RANO) Working Group criteria [16]. Specifically, progressive disease (PD) was established as ≥ 25% increase in the maximal cross-sectional tumor area in T1 contrast or FLAIR MRI or the onset of any new enhancing lesions. The Complete Response was set as complete disappearance of the lesion in T1 contrast. Partial Response was set as a reduction between 50 and 100% of the lesion. The presence of a partial response or a complete response was considered as radiological response.

Statistics

We used frequency tables with absolute counts and percentages to describe the characteristics of our pretreatment population. We correlated the rCBV value and OS using coefficient correlation and calculated the cut off for predicting response to antiangiogenic treatment with ROC curve. Overall survival (OS) was estimated using the Kaplan-Meier method. The significant result was set at p≤ 0.05.

A total of forty patients were included in the study. Average age was 47.6 years, 32.5% of the patients were female. The mean number of BVZ cycles was 6.3. Radiological response was present in 47.5% cases and 52.5% cases were non-responders. Table 1. The rCBV before the treatment was 4.5. We divided the patients into two groups: BVZ responders (partial or complete response according to RANO criteria) and BVZ non-responders (Progression or stable disease according to RANO criteria). In the responders group, the rCBV was 3.5 and in the non-responders group was 5.4 (p = 0.0001,95% CI, -2.4606 to -0.9822). We used the ROC analysis for searching the cut off for predicting the response to BVZ. The ROC analysis showed a sensitivity of 89.4% (95% CI, 66.8–98.4) and specificity of 100% (95% CI 75.1–99.2) with an rCBV value of 3.7, Fig. 1 and Table 2. We performed a correlation coefficient between rCBV and survival Fig. 2 which yielded a R2= -0.633, p < 0.0001 (95CI -0.8824 to -0.6303). We compared the Overall survival between responders and non-responders. In the group of responders, the OS was 8.3 months and 5.9 months in non responders (p = < 0.0001, 95%; HR 3.2317, CI 2.2958 to 10.7729). Figure 3. In the comparative analysis between Responders and Non responders there was no difference between the groups and the Cox Multivariate analysis the rCBV was the only predicting factor for OS in antiangiogenic treatment.

Table 1

General characteristics of the population at the onset of treatment
n=	35
Age (mean)	48.8
Female (n)	10
rCBV pre BVZ (mean)	4.5
Cycles of BVZ (mean)	6.3
Responders (n)	16
Non Responders	19

Table 2

Sensitivity and specificity values according to the value of rCBV
Value	Sensitivity	95% CI	Specificity	95% CI
< 2.8	0.00	0.00-20.8	100.00	82.2–100.0
≤ 3.7	81.25	54.3–95.7	100.00	82.2–100.0
≤ 3.8	81.25	54.3–95.7	94.74	73.9–99.1
≤ 3.9	87.50	61.6–98.1	89.47	66.8–98.4
≤ 4.1	87.50	61.6–98.1	78.95	54.4–93.8
≤ 4.2	93.75	69.7–99.0	78.95	54.4–93.8
≤ 4.6	93.75	69.7–99.0	57.89	33.5–79.7
≤ 4.7	100.00	79.2–100.0	57.89	33.5–79.7
≤ 7.8	100.00	79.2–100.0	0.00	0.0-17.8

In our study, we analyzed a total of 40 patients with recurrent glioblastoma undergoing therapy with BVZ. A meta-analysis published in neuro-oncology in 2016 [17–18] analyzed thirteen articles that studied DCE-MRI as a predictor of response to BVZ in patients with recurrent glioblastoma; however, only seven studies used rCBV as a response predictor, while the other six used various perfusion MRI parameters.

In the studies using rCBV as a responsive predictor included in the meta-analysis, a total of 226 patients were evaluated (with a maximum of 71 patients included in the Kickingereder’s [19]). The HR comparing the progression free survival between responsive and non-responsive patients was 0.46 and was 0.47 overall survival (OS). In our study, we observed a higher HR for OS, set at 0.68, this indicates a longer OS for our patients than what was reported in previous studies.

In the primary outcome, using the ROC analysis, we concluded that the cut off of rCBV to predict a response to BVZ was 3.7. The sensibility and specificity for this ROC was very high (100 and 81.2% respectively [20]). We found comparable results in other reports, for instance, in the Kickingereder et al study published in Neuro-Oncology [19], authors found that the cutoff for rCBV as a response predictor to BVZ treatment was 3.9, with a P < 0.01, something in line with our findings.

We also analyzed the overall survival rate using the correlation coefficient. Results for the responders group showed a 12-month extension in OS in comparison to non-responders (5.9 moths) (P < 0.005 and CI 1.96). In Kickingereder et al, authors demonstrated that rCBV analysis correctively predicts 12-month overall survival in 80% of the patients treated with BVZ and 6 months for progression free survival.

There have been several MRI perfusion techniques that analyze the response to antiangiogenic treatment in patients with malignant glioblastoma [23–27]. Some of these studies (Aquino et al 2014, Harris et al 2015, Kickingereder et al 2015, Schimainda et al 2015) found promising results, yet only a small number (seven) analyzed the rCBV cutoff point as a response predictor to BVZ treatment in these patients, all of them reporting similar results to ours.

Stecco et al [28] performed a similar analysis using rCBV as a predictor of Progression Free Survival (PFS). They observed that patients with an rCBV below 4.5 at T0 were predicted to have a longer PFS (p = 0.04). In this study, the sample size was just 13 patients and no overall survival correlations were performed.

The findings of the Secondary Analysis of the European Organization for Research and Treatment of Cancer 26101 Trial [29] found a nrCBF relative change of -18% and an absolute change of -0.15 points in Bevacizumab treated patients with recurrent GBM compared to a nrCBF relative change of + 1 and an absolute change of 0.01 in non-Bevacizumab treated patients (p < 0.001). This is the largest retrospective study of Bevacizumab treatment follow up using rCBF. While these findings do confirm the impact of Bevacizumab in rCBF and rCBV, no cutoff value was set for rCBV.

When studying response to treatment predictors, early changes in rCBF and rCBV in Bevacizumab treated patients have been used to retrospectively create an algorithm to predict short term response and overall survival in treatment responders vs non responders [30].

Despite the straightforward results of the present study, we must acknowledge the retrospective nature of the present study, which carries certain limitations. We did not have the patients’ molecular biology markers at baseline. We also did not obtain the histopathological results that confirmed recurrence in the patients. Another limitation is that this is a non-randomized study.

rCBV as a predictive/prognostic biomarker has been widely used and is currently the most reliable measurement for assessing the response to antiangiogenic treatment [29, 30]. Pretreatment rCBV is a potential progression-predicting imaging biomarker in BVZ-treated rGB. This is particularly helpful in our population, where the health system has multiple limitations to provide follow up after treatment, as such, this marker could favor the selection of patients who may benefit the most of BVZ therapy.

We know that rCBV is an indirect value of the cerebral blood volume using contrast material, so this is an effective and low-cost way to analyze and adequately select patients who are going to respond to antiangiogenic therapy. Furthermore, Pretreatment rCBV is a potential predicting imaging biomarker in BVZ-treated rGB. More information is needed to demonstrate these results using prospective studies.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Competing Interests

Authors declare no conflict of interest.

Author Contributions

Breda Yerpes was responsible for protocol design and approval from the IRB. Gomez-Figueroa, Arellano-Flores, Perez-Gonzalez, Reyes-Moreno, and Peiro-Osuna reviewed patient history and evolution. Gutierrez-Axayacatl was responsible for the interpretation of the radiologic studies. Mondragón-Soto, Hernandez-Hernandez, Villanueva-Castro, Sangrador-Vieitos, Alvaro-Hereida obtained the clinical and radiologic data for the study.

Guerrero Juarez, Lopez Martinez and Castro Martinez were responsible for patient enrollment. Breda Yerpes wrote the first manuscript. Martinez and Rodriguez-Hernandez revised the manuscript. Gonzalez-Aguilar designed and supervised the study. Cacho helped supervise the study. All authors revised and approved the final manuscript.

Data Availability

The datasets analyzed during the current study are available from the corresponding author upon request.

Ethics approval

This study was performed in line with the principles of the Declaration of Helsinki and the Mexican General Law of Health. Approval was granted by the Internal Research and Ethics Board of the National Institute of Neurology and Neurosurgery (No. 81/18)

Consent to participate

Written Informed consent was obtained from all individual participants included in the study for inclusion and publication.

Stupp R, Mason WP, van den Bent MJ et al (2005) Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N Engl J Med 352(10):987–996
Weidner N, Semple JP, Welch WR, Folkman J (1991 Jan) Tumor angiogenesis and metastasis–correlation in invasive breast carcinoma. N Engl J Med 3(1):1–8
Folkman J, Klagsbrun M Angiogenic factors. Science. 1987 Jan 23;235(4787):442-7
Jain RK, di Tomaso E, Duda DG et al (2007) Angiogenesis in brain tumours. Nat Rev Neurosci 8(8):610–622
Plate KH, Breier G, Weich HA, Risau W Vascular endothelial growth factor is a potential tumour angiogenesis factor in human gliomas in vivo.Nature. 1992 Oct29;359(6398):845–8
Plate KH, Breier G, Risau W (1994) Molecular mechanisms of developmental and tumor angiogenesis. Brain Pathol 4(3):207–218
Winkler F, Kozin SV, Tong RT et al (2004) Kinetics of vascular normalization by VEGFR2 blockade governs brain tumor response to radiation: role of oxygenation, angiopoietin-1, and matrix metalloproteinases. Cancer Cell 6(6):553–563
Wong ET, Brem S (2008) Antiangiogenesis treatment for glioblastoma multiforme: challenges and opportunities. J Natl Compr Canc Netw 6(5):515–522
Bennett IE, Field KM, Hovens CM, Moffat BA, Rosenthal MA, Drummond K, Kaye AH, Morokoff AP (2017 Jan) Early perfusion MRI predicts survival outcome in patients with recurrent glioblastoma treated with bevacizumab and carboplatin. J Neurooncol 131(2):321–329
Boxerman JL, Schmainda KM, Zhang Z, Barboriak DP (2015 Nov) Dynamic susceptibility contrast MRI measures of relative cerebral blood volume continue to show promise as an early response marker in the setting of bevacizumab treatment. Neuro Oncol 17(11):1538–1539
Stadlbauer A, Pichler P, Karl M, Brandner S, Lerch C, Renner B, Heinz G (2015 Jun) Quantification of serial changes in cerebral blood volume and metabolism in patients with recurrent glioblastoma undergoing antiangiogenic therapy. Eur J Radiol 84(6):1128–1136
Ellingson BM, Sahebjam S, Kim HJ et al (2014) Pretreatment ADC histogram analysis is a predictive imaging biomarker for bevacizumab treatment but not chemotherapy in recurrent glioblastoma. AJNR Am J Neuroradiol 35:673–679
Gahramanov S, Muldoon LL, Li X, Neuwelt EA (2011 Dec) Improved perfusion MR imaging assessment of intracerebral tumor blood volume and antiangiogenic therapy efficacy in a rat model with ferumoxytol. Radiology 261(3):796–804
Hu LS1, Eschbacher JM, Dueck AC, Heiserman JE et al (2012 Jan) Correlations between perfusion MR imaging cerebral blood volume, microvessel quantification, and clinical outcome using stereotactic analysis in recurrent high-grade glioma. AJNR Am J Neuroradiol 33(1):69–76
Law M, Young RJ, Babb JS et al (2008) Gliomas: predicting time to progression or survival with cerebral blood volume measurements at dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging. Radiology 247(2):490–498
Wen PY, Macdonald DR, Reardon DA, Cloughesy TF, Sorensen AG, Galanis E, Degroot J, Wick W, Gilbert MR, Lassman AB, Tsien C, Mikkelsen T, Wong ET, Chamberlain MC, Stupp R, Lamborn KR, Vogelbaum MA, van den Bent MJ, Chang SM (2010) Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group. J Clin Oncol. Apr 10;28(11):1963-72
Choi SH, Jung SC, Kim KW, Lee JY, Choi Y, Park SH, Kim HS (2016 Jun) Perfusion MRI as the predictive/prognostic and pharmacodynamic biomarkers in recurrent malignant glioma treated with bevacizumab: a systematic review and a time-to-event meta-analysis. J Neurooncol 128(2):185–194
Daniels D, Guez D, Last D, Hoffmann C, Nass D, Talianski A, Tsarfaty G, Salomon S, Kanner AA, Blumenthal DT, Bokstein F, Harnof S, Yekutieli D, Zamir S, Cohen ZR, Zach L, Mardor Y (2016) Early Biomarkers from Conventional and Delayed-Contrast MRI to Predict the Response to Bevacizumab in Recurrent High-Grade Gliomas.AJNR Am J Neuroradiol. Jul7
Kickingereder P, Wiestler B, Burth S, Wick A, Nowosielski M, Heiland S, Schlemmer HP, Wick W, Bendszus M, Radbruch A (2015 Aug) Relative cerebral blood volume is a potential predictive imaging biomarker of bevacizumab efficacy in recurrent glioblastoma. Neuro Oncol 17(8):1139–1147
Sawlani RN, Raizer J, Horowitz SW, Shin W, Grimm SA, Chandler JP, Levy R, Getch C, Carroll TJ (2010 May) Glioblastoma: a method for predicting response to antiangiogenic chemotherapy by using MR perfusion imaging–pilot study. Radiology 255(2):622–628
Kim BS, Kim SK, Choi SH, Lee SH, Seol HJ, Nam DH, Lee JI, Park CK, Kong DS (2015 Aug) Prognostic implication of progression pattern after anti-VEGF bevacizumab treatment for recurrent malignant gliomas. J Neurooncol 124(1):101–110
Wang Y, Xing D, Zhao M, Wang J, Yang Y (2016) The Role of a Single Angiogenesis Inhibitor in the Treatment of Recurrent Glioblastoma Multiforme: A Meta-Analysis and Systematic Review. PLoS One. Mar 23;11(3): e0152170
Schmainda KM, Zhang Z, Prah M, Snyder BS, Gilbert MR, Sorensen AG, Barboriak DP, Boxerman JL (2015 Aug) Dynamic susceptibility contrast MRI measures of relative cerebral blood volume as a prognostic marker for overall survival in recurrent glioblastoma: results from the ACRIN 6677/RTOG 0625 multicenter trial. Neuro Oncol 17(8):1148–1156
Schmainda KM, Prah M, Connelly J, Rand SD, Hoffman RG, Mueller W, Malkin MG (2014 Jun) Dynamic-susceptibility contrast agent MRI measures of relative cerebral blood volume predict response to bevacizumab in recurrent high-grade glioma. Neuro Oncol 16(6):880–888
Batchelor TT, Reardon DA, de Groot JF, Wick W, Weller M Antiangiogenic therapy for glioblastoma: current status and future prospects.Clin Cancer Res. 2014 Nov15;20(22):5612–9
Prados M, Cloughesy T, Samant M, Fang L, Wen PY, Mikkelsen T, Schiff D, Abrey LE, Yung WK, Paleologos N, Nicholas MK, Jensen R, Vredenburgh J, Das A, Friedman HS (2011 Jan) Response as a predictor of survival in patients with recurrent glioblastoma treated with bevacizumab. Neuro Oncol 13(1):143–151
Aquino D, Di Stefano AL, Scotti A, Cuppini L, Anghileri E, Finocchiaro G, Bruzzone MG, Eoli M (2014) Parametric response maps of perfusion MRI may identify recurrent glioblastomas responsive to bevacizumab and irinotecan. PLoS One. Mar 27;9(3): e90535
Stecco A, Amatuzzo P, Sponghini AP, Platini F, Quagliozzi M, Buemi F, Guenzi E, Carriero A Prognostic value of relative cerebral blood volume in patients with recurrent glioblastoma multiforme treated with bevacizumab.J Neurosurg Sci. 2019Aug; 63(4):394–401. doi: 10.23736/S0390-5616.16.03758-9. Epub 2016 Sep 7. PMID: 27603407.
Kickingereder P, Brugnara G, Hansen MB, Nowosielski M, Pflüger I, Schell M, Isensee F, Foltyn M, Neuberger U, Kessler T, Sahm F, Wick A, Heiland S, Weller M, Platten M, von Deimling A, Maier-Hein KH, Østergaard L, van den Bent MJ, Gorlia T, Wick W, Bendszus M (2020 Oct) Noninvasive Characterization of Tumor Angiogenesis and Oxygenation in Bevacizumab-treated Recurrent Glioblastoma by Using Dynamic Susceptibility MRI: Secondary Analysis of the European Organization for Research and Treatment of Cancer 26101 Trial. Radiology 297(1):164–175. doi: 10.1148/radiol.2020200978. Epub 2020 Jul 28. PMID: 32720870
Petrova L, Korfiatis P, Petr O, LaChance DH, Parney I, Buckner JC, Erickson BJ Cerebral blood volume and apparent diffusion coefficient - Valuable predictors of non-response to bevacizumab treatment in patients with recurrent glioblastoma.J Neurol Sci. 2019 Oct15;405:116433. doi: 10.1016/j.jns.2019.116433. Epub 2019 Aug 23. PMID: 31476621.

No competing interests reported.

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Relative cerebral blood volume as response predictor in the treatment of recurrent glioblastoma with anti-angiogenic therapy

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