Perfusion MRI (dynamic susceptibility contrast imaging) with different measurement approaches for the evaluation of blood flow and blood volume in human gliomas

A multi-reader comparison of normal-appearing white matter normalization techniques for perfusion and diffusion MRI in brain tumors

PURPOSE

There remains no consensus normal-appearing white matter (NAWM) normalization method to compute normalized relative cerebral blood volume (nrCBV) and apparent diffusion coefficient (nADC) in brain tumors. This reader study explored nrCBV and nADC differences using different NAWM normalization methods.

METHODS

Thirty-five newly diagnosed glioma patients were studied. For each patient, two readers created four NAWM regions of interests: (1) a single plane in the centrum semiovale (CSOp), (2) 3 spheres in the centrum semiovale (CSOs), (3) a single plane in the slice of the tumor center (TUMp), and (4) 3 spheres in the slice of the tumor center (TUMs). Readers repeated NAWM segmentations 1 month later. Differences in nrCBV and nADC of the FLAIR hyperintense tumor, inter-/intra-reader variability, and time to segment NAWM were assessed. As a validation step, the diagnostic performance of each method for IDH-status prediction was evaluated.

RESULTS

Both readers obtained significantly different nrCBV (P < .001), nADC (P < .001), and time to segment NAWM (P < .001) between the four normalization methods. nrCBV and nADC were significantly different between CSO and TUM methods, but not between planar and spherical methods in the same NAWM region. Broadly, CSO methods were quicker than TUM methods, and spherical methods were quicker than planar methods. For all normalization techniques, inter-reader reproducibility and intra-reader repeatability were excellent (intraclass correlation coefficient > 0.9), and the IDH-status predictive performance remained similar.

CONCLUSION

The selected NAWM region significantly impacts nrCBV and nADC values. CSO methods, particularly CSOs, may be preferred because of time reduction, similar reader variability, and similar diagnostic performance compared to TUM methods.

Diffusion-weighted imaging and arterial spin labeling radiomics features may improve differentiation between radiation-induced brain injury and glioma recurrence

OBJECTIVES

To determine whether radiomics features derived from diffusion-weighted imaging (DWI) and arterial spin labeling (ASL) can improve the differentiation between radiation-induced brain injury (RIBI) and tumor recurrence (TR) in glioma patients.

METHODS

A total of 4199 radiomics features were extracted from conventional MRI, apparent diffusion coefficient (ADC), and cerebral blood flow (CBF) maps, obtained from 96 pathologically confirmed WHO grade 2~4 gliomas with enhancement after standard treatment. The intraclass correlation coefficient (ICC) was used to test segmentation stability between two doctors. Radiomics features were selected using the Mann-Whitney U test, LASSO regression, and RFE algorithms. Four machine learning classifiers were adopted to establish radiomics models. The diagnostic performance of multiparameter, conventional, and single-parameter MRI radiomics models was compared using the area under the curve (AUC). The models were evaluated in the subsequent independent validation set (n = 30).

RESULTS

Eight important radiomics features (3 from conventional MRI, 1 from ADC, and 4 from CBF) were selected. Support vector machine (SVM) was chosen as the optimal classifier. The diagnostic performance of the multiparameter MRI radiomics model (AUC 0.96) was higher than that of the conventional MRI (AUC 0.88), ADC (AUC 0.91), and CBF (AUC 0.95) radiomics models. For subgroup analysis, the multiparameter MRI radiomics model showed similar performance, with AUCs of 0.98 in WHO grade 2~3 and 0.96 in WHO grade 4.

CONCLUSION

The incorporation of noninvasive DWI and ASL into the MRI radiomics model improved the diagnostic performance in differentiating RIBI from TR; ASL, especially, played a significant role.

KEY POINTS

• The multiparameter MRI radiomics model was superior to the conventional MRI radiomics model in differentiating glioma recurrence from radiation-induced brain injury. • Diffusion and perfusion MRI could improve the ability of the radiomics model in predicting the progression in patients with glioma. • Arterial spin labeling played an important role in predicting glioma progression using radiomics models.

Early Therapeutic Interventions for Newly Diagnosed Glioblastoma: Rationale and Review of the Literature

PURPOSE OF REVIEW

Glioblastoma is the commonest primary brain cancer in adults whose outcomes are amongst the worst of any cancer. The current treatment pathway comprises surgery and postoperative chemoradiotherapy though unresectable diffusely infiltrative tumour cells remain untreated for several weeks post-diagnosis. Intratumoural heterogeneity combined with increased hypoxia in the postoperative tumour microenvironment potentially decreases the efficacy of adjuvant interventions and fails to prevent early postoperative regrowth, called rapid early progression (REP). In this review, we discuss the clinical implications and biological foundations of post-surgery REP. Subsequently, clinical interventions potentially targeting this phenomenon are reviewed systematically.

RECENT FINDINGS

Early interventions include early systemic chemotherapy, neoadjuvant immunotherapy, local therapies delivered during surgery (including Gliadel wafers, nanoparticles and stem cell therapy) and several radiotherapy techniques. We critically appraise and compare these strategies in terms of their efficacy, toxicity, challenges and potential to prolong survival. Finally, we discuss the most promising strategies that could benefit future glioblastoma patients. There is biological rationale to suggest that early interventions could improve the outcome of glioblastoma patients and they should be investigated in future trials.

The history of magnetic resonance imaging and its reflections in Acta Radiologica

The first reports in Acta Radiologica on magnetic resonance imaging (MRI) were published in 1984, four years after the first commercial MR scanners became available. For the first two years, all MR papers originated from the USA. Nordic contributions started in 1986, and until 2020, authors from 44 different countries have published MR papers in Acta Radiologica. Papers on MRI have constituted, on average, 30%-40% of all published original articles in Acta Radiologica, with a high of 49% in 2019. The MR papers published since 1984 document tremendous progress in several areas such as magnet and coil design, motion compensation techniques, faster image acquisitions, new image contrast, contrast-enhanced MRI, functional MRI, and image analysis. In this historical review, all of these aspects of MRI are discussed and related to Acta Radiologica papers.

Cerebral and tumoral blood flow in adult gliomas: a systematic review of results from magnetic resonance imaging

Objective:

Blood flow is the rate of blood movement and relevant to numerous processes, though understudied in gliomas. The aim of this review was to pool blood flow metrics obtained from MRI modalities in adult supratentorial gliomas.

Methods:

MEDLINE, EMBASE and the Cochrane database were queried 01/01/2000–31/12/2019. Studies measuring blood flow in adult Grade II–IV supratentorial gliomas using dynamic susceptibility contrast (DSC) MRI, dynamic contrast enhanced MRI (DCE-MRI) or arterial spin labelling (ASL) were included. Absolute and relative cerebral blood flow (CBF), peritumoral blood flow and tumoral blood flow (TBF) were reported.

Results:

34 studies were included with 1415 patients and 1460 scans. The mean age was 52.4 ± 7.3 years. Most patients had glioblastoma (n = 880, 64.6%). The most common imaging modality was ASL (n = 765, 52.4%) followed by DSC (n = 538, 36.8%). Most studies were performed pre-operatively (n = 1268, 86.8%). With increasing glioma grade (II vs IV), TBF increased (70.8 vs 145.5 ml/100 g/min, p < 0.001) and CBF decreased (85.3 vs 49.6 ml/100 g/min, p < 0.001). In Grade IV gliomas, following treatment, CBF increased in ipsilateral (24.9 ± 1.2 vs 26.1 ± 0.0 ml/100 g/min, p < 0.001) and contralateral white matter (25.6 ± 0.2 vs 26.0± 0.0 ml/100 g/min, p < 0.001).

Conclusion:

Our findings demonstrate that increased mass effect from high-grade gliomas impairs blood flow within the surrounding brain that can improve with surgery.

Advances in knowledge:

This systematic review demonstrates how mass effect from brain tumours impairs blood flow in the surrounding brain parenchyma that can improve with treatment.

Nasopharyngeal carcinoma perfusion MRI: Comparison of arterial spin labeling and dynamic contrast-enhanced MRI

To investigate the feasibility of 3D arterial spin labeling (ASL) as an alternative to dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for the qualitative and quantitative evaluation of nasopharyngeal carcinoma (NPC) perfusion.Fifty-two newly diagnosed NPC patients underwent 3D ASL and DCE-MRI scans on a 3.0-T MRI system. The visual qualitative evaluation of the NPC perfusion level was scored from 0 to 3 (0 = no contrast to normal peripheral soft tissue, 3 = pronounced contrast to normal peripheral soft tissue). The visual evaluation of the NPC outline was scored from 0 to 2 (0 = very vague outline, 2 = clear outline). Comparisons of the ASL-derived blood flow (BF) with the DCE-MRI-derived positive enhancement integral, maximum slope of increase, maximum slope of decrease, and time to peak (TTP) were conducted between NPC and non-NPC areas with independent samples t-tests. The diagnostic performance of these parameters was assessed by receiver operating characteristic curve analysis. The correlations between ASL BF and DCE parameters were assessed by Spearman correlation analysis.There was no difference in the visual scores of the NPC perfusion level between the 2 perfusion methods (P= .963). ASL had a lower visual score for describing the outline of NPC than DCE-MRI (P < .001). The ASL and DCE parameters of the NPC areas were significantly different from those of the non-NPC areas (P < .001). The ASL BF showed the largest area under the receiver operating characteristic curve (AUC) of 0.936 for identifying NPC. When all NPC and non-NPC areas were taken into account, significant correlations were observed between the ASL BF and the DCE parameters positive enhancement integral (r = 0.503, P < .001), maximum slope of increase (r = 0.616, P < .001), maximum slope of decrease (r = 0.380, P < .001), and TTP (r = -0.601, P < .001).3D ASL could reveal the hyperperfusion of NPC in a qualitative and quantitative manner without using contrast agent. Additionally, the ASL BF correlated significantly with the semiquantitative DCE-MRI parameters.

Investigating dynamic susceptibility contrast-enhanced perfusion-weighted magnetic resonance imaging in posterior fossa tumors: differences and similarities with supratentorial tumors

PURPOSE

To assess the accuracy of dynamic susceptibility contrast-enhanced perfusion-weighted magnetic resonance imaging in glioma grading and brain tumor characterization of infratentorial tumors, and to investigate differences from supratentorial tumors.

METHODS

This retrospective study, approved by the institutional review board, included 246 patients with brain tumors (184 supratentorial, 62 infratentorial), grouped by tumor type: high-grade gliomas (HGG), low-grade gliomas (LGG), metastases (Met), and primary central nervous system lymphoma (PCNSL). Relative cerebral blood volume (rCBV) and mean percentage of signal recovery (PSR) were calculated. For statistical analyses, lesions were grouped by location and histology. Differences were tested with Mann-Whitney U tests. From ROC curves, we calculated accuracy, sensitivity, specificity, PPV, and NPV, for rCBV and PSR.

RESULTS

For infratentorial tumors, rCBV was highly accurate in differentiating HGG from LGG (AUC = 0.938). Mean PSR showed high accuracy in differentiating PCNSL and HGG from Met (AUC = 0.978 and AUC = 0.881, respectively). Infratentorial and supratentorial tumors had similarly high rCBV in HGG, high mean PSR in PCNSL, and low mean PSR in Met. The main differences were the optimum threshold rCBV values (3.04 for supratentorial, 1.77 for infratentorial tumors) and the mean PSR, which was significantly higher in LGG than in HGG in supratentorial (p = 0.035), but not infratentorial gliomas. Using infratentorial rCBV threshold values for supratentorial tumors decreased the sensitivity and specificity.

CONCLUSION

rCBV and mean PSR were useful in grading and differentiating infratentorial tumors. Proper cutoff values were important in the accuracy of perfusion-weighted imaging in posterior fossa tumors.

Advanced Neuroimaging Techniques: Basic Principles and Clinical Applications

Advanced neuroimaging techniques are increasingly being implemented in clinical practice as complementary tools to conventional imaging because they can provide crucial functional information about the pathophysiology of a variety of disorders. Therefore, it is important to understand the basic principles underlying them and their role in diagnosis and management. In this review, we will primarily focus on the basic principles and clinical applications of perfusion imaging, diffusion imaging, magnetic resonance spectroscopy, functional MRI, and dual-energy computerized tomography. Our goal is to provide the reader with a basic understanding of these imaging techniques and when they should be used in clinical practice.

Detection of severity in Alzheimer's disease (AD) using computational modeling

The prevalent cause of dementia - Alzheimer's disease (AD) is characterized by an early cholinergic deficit that is in part responsible for the cognitive deficits (especially memory and attention defects). Prolonged AD leads to moderate-to-severe AD, which is one of the leading causes of death. Placebo-controlled, randomized clinical trials have shown significant effects of Acetyl cholin esterase inhibitors (ChEIs) on function, cognition, activities of daily living (ADL) and behavioral symptoms in patients. Studies have shown comparable effects for ChEIs in patients with moderate-to-severe or mild AD. Setting a fixed measurement (e.g. a Mini-Mental State Examination score, as a 'when to stop treatment limit) for the disease is not clinically rational. Detection of changed regional cerebral blood flow in mild cognitive impairment and early AD by perfusion-weighted magnetic resonance imaging has been a challenge. The utility of perfusion-weighted magnetic resonance imaging (PW-MRI) for detecting changes in regional cerebral blood flow (rCBF) in patients with mild cognitive impairment (MCI) and early AD was evaluated. We describe a computer aided prediction model to determine the severity of AD using known data in literature. We designed an automated system for the determination of AD severity. It is used to predict the clinical cases and conditions with disagreements from specialist. The model described is useful in clinical practice to validate diagnosis.

Pseudoprogression of brain tumors

This review describes the definition, incidence, clinical implications, and magnetic resonance imaging (MRI) findings of pseudoprogression of brain tumors, in particular, but not limited to, high-grade glioma. Pseudoprogression is an important clinical problem after brain tumor treatment, interfering not only with day-to-day patient care but also the execution and interpretation of clinical trials. Radiologically, pseudoprogression is defined as a new or enlarging area(s) of contrast agent enhancement, in the absence of true tumor growth, which subsides or stabilizes without a change in therapy. The clinical definitions of pseudoprogression have been quite variable, which may explain some of the differences in reported incidences, which range from 9-30%. Conventional structural MRI is insufficient for distinguishing pseudoprogression from true progressive disease, and advanced imaging is needed to obtain higher levels of diagnostic certainty. Perfusion MRI is the most widely used imaging technique to diagnose pseudoprogression and has high reported diagnostic accuracy. Diagnostic performance of MR spectroscopy (MRS) appears to be somewhat higher, but MRS is less suitable for the routine and universal application in brain tumor follow-up. The combination of MRS and diffusion-weighted imaging and/or perfusion MRI seems to be particularly powerful, with diagnostic accuracy reaching up to or even greater than 90%. While diagnostic performance can be high with appropriate implementation and interpretation, even a combination of techniques, however, does not provide 100% accuracy. It should also be noted that most studies to date are small, heterogeneous, and retrospective in nature. Future improvements in diagnostic accuracy can be expected with harmonization of acquisition and postprocessing, quantitative MRI and computer-aided diagnostic technology, and meticulous evaluation with clinical and pathological data.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Glioma grading by dynamic susceptibility contrast perfusion and 11C-methionine positron emission tomography using different regions of interest

PURPOSE

The use of dynamic susceptibility contrast (DSC) perfusion and ¹¹C-methionine positron emission tomography (MET-PET) for glioma grading is currently not standardized. The purpose of this study was to identify regions of interest (ROIs) that enable the best performance and clinical applicability in both methods, as well as to evaluate the complementarity of DSC perfusion and MET-PET in spatial hotspot definition.

METHODS

In 41 patient PET/MRI datasets, different ROIs were drawn: in T2-hyperintense tumour, in T2-hyperintense tumour and adjacent oedema and in tumour areas with contrast enhancement, altered perfusion or pathological radiotracer uptake. The performance of DSC perfusion and MET-PET using the different ROIs to distinguish high- and low-grade gliomas was assessed. The spatial overlap of hotspots identified by DSC perfusion and MET-PET was assessed visually.

RESULTS

ROIs in T2 fluid attenuated inversion recovery (FLAIR) sequence-hyperintense tumour revealed the most significant differences between high- and low-grade gliomas and reached the highest diagnostic performance in both DSC perfusion (p = 0.046; area under the curve = 0.74) and MET-PET (p = 0.007; area under the curve = 0.80). The combination of methods yielded an area under the curve of 0.80. Hotspots were completely overlapped in one half of the patients, partially overlapped in one third of the patients and present in only one method in approximately 20% of the patients.

CONCLUSIONS

For multi-parametric examinations with DSC perfusion and MET-PET, we recommend an ROI definition based on T2-hyperintense tumour. DSC perfusion and MET-PET contain complementary information concerning the spatial hotspot definition.

Differentiation between radiation-induced brain injury and glioma recurrence using 3D pCASL and dynamic susceptibility contrast-enhanced perfusion-weighted imaging

PURPOSE

This study was performed to validate the efficacy of three-dimensional pseudocontinuous arterial spin labeling (pCASL) compared with dynamic susceptibility contrast-enhanced perfusion-weighted imaging (DSC-PWI) in distinguishing radiation-induced brain injury from glioma recurrence in patients with glioma.

METHODS

Both 3D pCASL and DSC-PWI were performed using a 3.0 Tesla scanner in 69 patients with previously resected and irradiated glioma who displayed newly developed abnormal contrast-enhanced lesions. The included patients were classified into a radiation-induced brain injury group (n = 34) and a glioma recurrence group (n = 35) based on subsequent pathologic analysis or clinical-radiological follow-up. Lesion perfusion parameter values (CBF and nCBF on pCASL, nrCBV and nrCBF on DSC-PWI) were measured and compared between the two groups using Student's t test. Pearson correlation analysis was performed to evaluate the correlation between pCASL (CBF and nCBF) and DSC-PWI (nrCBV and nrCBF) values in the contrast-enhanced lesions and in the perifocal edema regions.

RESULTS

For the contrast-enhanced lesions, the CBF, nCBF, nrCBV, and nrCBF (29.46 ± 15.08 ml/100 g/min, 1.11 ± 0.50, 1.39 ± 1.15, and 1.30 ± 0.74) in the radiation-induced brain injury group were significantly lower than those (64.52 ± 33.92 ml/100 g/min, 2.73 ± 1.71, 3.39 ± 2.12, and 3.20 ± 1.95) in the glioma recurrence group (P < 0.001). The CBF and nCBF demonstrated strong correlation with nrCBV and nrCBF in the contrast-enhanced lesions.

CONCLUSION

Radiation-induced brain injury and glioma recurrence can be reliably distinguished using both 3D pCASL and DSC-PWI. Contrast-free 3D pCASL is a suitable alternative to DSC-PWI for long-term follow-up in glioma patients with postoperative radiotherapy.

Diagnostic accuracy of automatic normalization of CBV in glioma grading using T1- weighted DCE-MRI

PURPOSE

Aim of this retrospective study was to compare diagnostic accuracy of proposed automatic normalization method to quantify the relative cerebral blood volume (rCBV) with existing contra-lateral region of interest (ROI) based CBV normalization method for glioma grading using T1-weighted dynamic contrast enhanced MRI (DCE-MRI).

MATERIAL AND METHODS

Sixty patients with histologically confirmed gliomas were included in this study retrospectively. CBV maps were generated using T1-weighted DCE-MRI and are normalized by contralateral ROI based method (rCBV_contra), unaffected white matter (rCBV_WM) and unaffected gray matter (rCBV_GM), the latter two of these were generated automatically. An expert radiologist with >10years of experience in DCE-MRI and a non-expert with one year experience were used independently to measure rCBVs. Cutoff values for glioma grading were decided from ROC analysis. Agreement of histology with rCBV_WM, rCBV_GM and rCBV_contra respectively was studied using Kappa statistics and intra-class correlation coefficient (ICC).

RESULT

The diagnostic accuracy of glioma grading using the measured rCBV_contra by expert radiologist was found to be high (sensitivity=1.00, specificity=0.96, p<0.001) compared to the non-expert user (sensitivity=0.65, specificity=0.78, p<0.001). On the other hand, both the expert and non-expert user showed similar diagnostic accuracy for automatic rCBV_WM (sensitivity=0.89, specificity=0.87, p=0.001) and rCBV_GM (sensitivity=0.81, specificity=0.78, p=0.001) measures. Further, it was also observed that, contralateral based method by expert user showed highest agreement with histological grading of tumor (kappa=0.96, agreement 98.33%, p<0.001), however; automatic normalization method showed same percentage of agreement for both expert and non-expert user. rCBV_WM showed an agreement of 88.33% (kappa=0.76,p<0.001) with histopathological grading.

CONCLUSION

It was inferred from this study that, in the absence of expert user, automated normalization of CBV using the proposed method could provide better diagnostic accuracy compared to the manual contralateral based approach.

Discrimination between Glioma Grades II and III Using Dynamic Susceptibility Perfusion MRI: A Meta-Analysis

BACKGROUND

DSC perfusion has been evaluated in the discrimination between low-grade and high-grade glioma but the diagnostic potential to discriminate beween glioma grades II and III remains unclear.

PURPOSE

Our aim was to evaluate the diagnostic accuracy of relative maximal CBV from DSC perfusion MR imaging to discriminate glioma grades II and III.

DATA SOURCES

A systematic literature search was performed in PubMed/MEDLINE, Embase, Web of Science, and ClinicalTrials.gov.

STUDY SELECTION

Eligible studies reported on patients evaluated with relative maximal CBV derived from DSC with a confirmed neuropathologic diagnosis of glioma World Health Organization grades II and III. Studies reporting on mean or individual patient data were considered for inclusion.

DATA ANALYSIS

Data were analyzed by using inverse variance with the random-effects model and receiver operating characteristic curves describing optimal cutoffs and areas under the curve. Bivariate diagnostic random-effects meta-analysis was used to calculate diagnostic accuracy.

DATA SYNTHESIS

Twenty-eight studies evaluating 727 individuals were included in the meta-analysis. Individual data were available from 10 studies comprising 190 individuals. The mean difference of relative maximal CBV between glioma grades II and III (n = 727) was 1.76 (95% CI, 1.27-2.24; P < .001). Individual patient data (n = 190) had an area under the curve of 0.77 for discriminating glioma grades II and III at an optimal cutoff of 2.02. When we analyzed astrocytomas separately, the area under the curve increased to 0.86 but decreased to 0.61 when we analyzed oligodendrogliomas.

LIMITATIONS

A substantial heterogeneity was found among included studies.

CONCLUSIONS

Glioma grade III had higher relative maximal CBV compared with glioma grade II. A high diagnostic accuracy was found for all patients and astrocytomas; however, the diagnostic accuracy was substantially reduced when discriminating oligodendroglioma grades II and III.

Evaluation of recurrent high-grade gliomas treated with bevacizumab: A preliminary report of 3D pseudocontinuous artery spin labeling

PURPOSE

To investigate the role of cerebral blood flow (CBF) derived from a 3D fast spin echo (FSE) pseudocontinuous artery spin labeling (pcASL) sequence in evaluating the survival rate of recurrent high-grade gliomas (rHGGs) that were treated with bevacizumab (BEV).

MATERIALS AND METHODS

Sixteen patients with rHGGs who underwent 3T 3D FSE pcASL imaging 1-2 days before (baseline or pre-BEV) and within 1 month after BEV treatment initiation (post-BEV) were included in the study. Average (aCBF) and maximum (mCBF) cerebral blood flow of the enhancing tumor, their respective normalized values to contralateral normal-appearing white matter (rCBF_wm and mCBF_wm) and cerebellum (rCBF_cb and mCBF_cb), and the related changes between baseline and post-BEV were evaluated. Receiver operating characteristic (ROC) curve analysis was utilized to define the optimal cutoff perfusion values for overall survival (OS) and progression-free survival (PFS) stratification. Kaplan-Meier analysis with log-rank test was applied to assess and compare PFS and OS rates.

RESULTS

All the CBF measurements pre-BEV and post-BEV treatment were significantly different except mCBF. The CBF measurements (aCBF, rCBF_wm, rCBF_cb, mCBF_wm and mCBF_cb) pre-BEV all decreased post-BEV treatment. Cutoffs of aCBF (43.72 ml/100g/min) pre-BEV for OS, rCBF_cb (1.09) pre-BEV for PFS and OS, and ΔaCBF (-0.37) for PFS were found to be statistically significant in survival stratification (404 days vs. 140 days, P = 0.026; 251 days vs. 112 days, P = 0.044; 404 days vs. 194 days, P = 0.046; 267 days vs. 116 days, P = 0.048, respectively).

CONCLUSION

Three dimensional FSE pcASL can detect the decrease of perfusion in rHGGs treated with BEV and is a potential promising technique in stratifying survival rate of rHGGs under BEV treatment.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:565-573.

Differentiation between recurrent gliomas and radiation necrosis using arterial spin labeling perfusion imaging

Arterial spin labeling (ASL) magnetic resonance (MR) perfusion imaging has been proposed as an effective method to measure brain tumor perfusion. The aim of the present study was to evaluate the utility of this technique in the differentiation of recurrent gliomas from radiation necrosis. Twenty-one patients with surgically treated primary gliomas, including 16 cases of recurrent glioma and 5 of radiation necrosis were examined using 3.0T MR imaging (MRI). ASL and dynamic susceptibility contrast-weighted (DSC) perfusion MRI scans were performed. Maps of normalized cerebral blood flow (CBF) in ASL imaging and cerebral blood volume (CBV) in DSC imaging were computed and analyzed in the regions of interest. In cases of glioma recurrence, the normalized ASL-CBF ratio (4.45±2.72) was higher than that in cases of radiation injury (1.22±0.61) (P<0.01). The normalized DSC-relative CBV ratio was also significantly higher in glioma recurrence (3.38±2.08) than it was in radiation injury (1.09±0.55) (P<0.05). A close linear correlation was found between the ASL and DSC MRI techniques (linear regression coefficient, R=0.85; P=0.005) in the differentiation of recurrent glioma from radiation injury. The results indicate that ASL perfusion is an accurate method of distinguishing between glioma recurrence and radiation necrosis.

Quantitative measurement of blood flow in paediatric brain tumours-a comparative study of dynamic susceptibility contrast and multi time-point arterial spin labelled MRI

Objective:

Arterial spin-labelling (ASL) MRI uses intrinsic blood water to quantify the cerebral blood flow (CBF), removing the need for the injection of a gadolinium-based contrast agent used for conventional perfusion imaging such as dynamic susceptibility contrast (DSC). Owing to the non-invasive nature of the technique, ASL is an attractive option for use in paediatric patients. This work compared DSC and multi-timepoint ASL measures of CBF in paediatric brain tumours.

Methods:

Patients (n = 23; 20 low-grade tumours and 3 high-grade tumours) had DSC and multi-timepoint ASL with and without vascular crushers (VC). VC removes the contribution from larger vessel blood flow. Mean perfusion metrics were extracted from control and T₁-enhanced tumour regions of interest (ROIs): arterial arrival time (AAT) and CBF from the ASL images with and without VC, relative cerebral blood flow (rCBF), relative cerebral blood volume, delay time (DT) and mean transit time (MTT) from the DSC images.

Results:

Significant correlations existed for: AAT and DT (r = 0.77, p = 0.0002) and CBF and rCBF (r = 0.56, p = 0.02) in control ROIs for ASL-noVC. No significant correlations existed between DSC and ASL measures in the tumour region. Significant differences between control and tumour ROI were found for MTT (p < 0.001) and rCBF (p < 0.005) measures.

Conclusion:

Significant correlations between ASL-noVC and DSC measures in the normal brain suggest that DSC is most sensitive to macrovascular blood flow. The absence of significant correlations within the tumour ROI suggests that ASL is sensitive to different physiological mechanisms compared with DSC measures.

Advances in knowledge:

ASL provides information which is comparable with that of DSC in healthy tissues, but appears to reflect a different physiology in tumour tissues.

Additive antiangiogenesis effect of ginsenoside Rg3 with low-dose metronomic temozolomide on rat glioma cells both in vivo and in vitro

Background

Glioblastoma is the most common and deadly primary brain tumor in adults. Low-dose,metronomic (LDM) temozolomide (TMZ) displays improved efficacy in the treatment of glioblastoma by targeting angiogenesis, but has a limited effect on recurrence. The antiangiogenesis drug ginsenoside Rg3 (RG3) is the main active ingredient of ginseng, a popular herbal medicine.

Methods

Using an in vitro and a rat model of an orthotopic glioma allograft, this study was to determine whether RG3 enhanced the antiangiogenesis activity of LDM TMZ in the treatment of glioblastoma.

Results

Our results showed that combined use of TMZ with RG3 displayed additive inhibition on proliferation of both human umbilical vein endothelial cells (HUVEC) and rat C6 glioma cells in vitro. They additively arrested cell cycle, increased apoptosis, and decreased VEGF-A and BCL-2 expression in HUVEC. Antiangiogenesis effect was also evaluated in the rat model of orthotopic glioma allograft, based upon markers including relative cerebral blood volume (rCBV) by magnetic resonance imaging (MRI), VEGF levels and microvessel density (MVD)/CD34 staining. LDM TMZ alone was potent in suppressing angiogenesis and tumor growth, whereas RG3 alone only had modest antiangiogenesis effects. Combined treatment significantly and additively suppressed angiogenesis, without additive inhibitory effects on allografted tumor growth.

Conclusions

These data provide evidence showing the efficacy of LDM TMZ on glioma treatment. The combined additive antiangiogenesis effect suggests that RG3 has the potential to further increase the efficacy of LDM TMZ in the treatment of glioblastoma.

Electronic supplementary material

The online version of this article (doi:10.1186/s13046-015-0274-y) contains supplementary material, which is available to authorized users.

Arterial input function and gray matter cerebral blood volume measurements in children

Purpose

To investigate how arterial input functions (AIFs) vary with age in children and compare the use of individual and population AIFs for calculating gray matter CBV values. Quantitative measures of cerebral blood volume (CBV) using dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) require measurement of an AIF. AIFs are affected by numerous factors including patient age. Few data presenting AIFs in the pediatric population exists.

Materials and Methods

Twenty‐two previously treated pediatric brain tumor patients (mean age, 6.3 years; range, 2.0–15.3 years) underwent DSC‐MRI scans on a 3T MRI scanner over 36 visits. AIFs were measured in the middle cerebral artery. A functional form of an adult population AIF was fitted to each AIF to obtain parameters reflecting AIF shape. The relationship between parameters and age was assessed. Correlations between gray matter CBV values calculated using the resulting population and individual patient AIFs were explored.

Results

There was a large variation in individual patient AIFs but correlations between AIF shape and age were observed. The center (r = 0.596, P < 0.001) and width of the first‐pass peak (r = 0.441, P = 0.007) were found to correlate significantly with age. Intrapatient coefficients of variation were significantly lower than interpatient values for all parameters (P < 0.001). Differences in CBV values calculated with an overall population and age‐specific population AIF compared to those calculated with individual AIFs were 31.3% and 31.0%, respectively.

Conclusion

Parameters describing AIF shape correlate with patient age in line with expected changes in cardiac output. In pediatric DSC‐MRI studies individual patient AIFs are recommended. J. Magn. Reson. Imaging 2016;43:981–989

Repeatability of Standardized and Normalized Relative CBV in Patients with Newly Diagnosed Glioblastoma

BACKGROUND AND PURPOSE

For more widespread clinical use advanced imaging methods such as relative cerebral blood volume must be both accurate and repeatable. The aim of this study was to determine the repeatability of relative CBV measurements in newly diagnosed glioblastoma multiforme by using several of the most commonly published estimation techniques.

MATERIALS AND METHODS

The relative CBV estimates were calculated from dynamic susceptibility contrast MR imaging in double-baseline examinations for 33 patients with treatment-naïve and pathologically proved glioblastoma multiforme (men = 20; mean age = 55 years). Normalized and standardized relative CBV were calculated by using 6 common postprocessing methods. The repeatability of both normalized and standardized relative CBV, in both tumor and contralateral brain, was examined for each method with metrics of repeatability, including the repeatability coefficient and within-subject coefficient of variation. The minimum sample size required to detect a parameter change of 10% or 20% was also determined for both normalized relative CBV and standardized relative CBV for each estimation method.

RESULTS

When ordered by the repeatability coefficient, methods using postprocessing leakage correction and ΔR2*(t) techniques offered superior repeatability. Across processing techniques, the standardized relative CBV repeatability in normal-appearing brain was comparable with that in tumor (P = .31), yet inferior in tumor for normalized relative CBV (P = .03). On the basis of the within-subject coefficient of variation, tumor standardized relative CBV estimates were less variable (13%-20%) than normalized relative CBV estimates (24%-67%). The minimum number of participants needed to detect a change of 10% or 20% is 118-643 or 30-161 for normalized relative CBV and 109-215 or 28-54 for standardized relative CBV.

CONCLUSIONS

The ΔR2* estimation methods that incorporate leakage correction offer the best repeatability for relative CBV, with standardized relative CBV being less variable and requiring fewer participants to detect a change compared with normalized relative CBV.

Relative percentage signal intensity recovery of perfusion metrics—an efficient tool for differentiating grades of glioma

OBJECTIVE

Glioma classification and characterization may be facilitated by a multiparametric approach of perfusion metrics, which could not be achieved by conventional MRI alone. Our aim is to explore the potential of relative percentage signal intensity recovery (rPSR) values, in addition to relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF) of first-pass T2* dynamic susceptibility contrast (DSC) perfusion MRI, in differentiating high- and low-grade glioma.

METHODS

This prospective study included 39 patients with low-grade and 25 patients with high-grade glioma. rPSR, rCBV and rCBF were calculated from the first-pass T2* DSC perfusion MRI. rPSR was calculated using standard software and validated with dedicated perfusion metrics analysis software. The statistical analysis was performed using analysis of variance and receiver operating characteristic (ROC) curves.

RESULTS

Variation in rPSR, rCBV and rCBF values between low- and high-grade gliomas were statistically significant (p < 0.005). The ROC curve analysis for each of them yielded 96% sensitivity and 71.8% specificity; 88% sensitivity and 69.2% specificity; and 72% sensitivity and 66.7% specificity. The area under the curve (AUC) from the ROC curve analysis yielded 0.893, 0.852 and 0.702 for rPSR, rCBV and rCBF, respectively. The rPSR calculation with the validation software yielded 92.3% sensitivity and 72% specificity with an AUC of 0.864.

CONCLUSION

rPSR inversely correlates while rCBV and rCBF values directly correlate with the tumour grade. Furthermore, the overall diagnostic performance of rPSR is better than rCBV and rCBF values.

ADVANCES IN KNOWLEDGE

rPSR of T2* DSC perfusion is an indicator of blood-brain barrier status and lesion leakiness, which has not been explored yet compared with the usual haemodynamic parameters, rCBV and rCBF.

Astrocytic tumour grading: a comparative study of three-dimensional pseudocontinuous arterial spin labelling, dynamic susceptibility contrast-enhanced perfusion-weighted imaging, and diffusion-weighted imaging

OBJECTIVES

We hypothesized that three-dimensional pseudocontinuous arterial spin labelling (pCASL) may have similar efficacy in astrocytic tumour grading as dynamic susceptibility contrast-enhanced perfusion-weighted imaging (DSC-PWI), and the grading accuracy may be further improved when combined with apparent diffusion coefficient (ADC) values.

METHODS

Forty-three patients with astrocytic tumours were studied using diffusion weighted imaging (DWI), pCASL, and DSC-PWI. Histograms of ADC and normalized tumour cerebral blood flow values (nCBF on pCASL and nrCBF on DSC-PWI) were measured and analyzed.

RESULTS

The mean 10 % ADC value was the DWI parameter that provided the best differentiation between low-grade astrocytoma (LGA) and high-grade astrocytoma (HGA). The nCBF and nrCBF (1.810 ± 0.979 and 2.070 ± 1.048) in LGA were significantly lower than those (4.505 ± 2.270 and 5.922 ± 2.630) in HGA. For differentiation between LGA and HGA, the cutoff values of 0.764 × 10(-3) mm(2)/s for mean 10 % ADC, 2.374 for nCBF, and 3.464 for nrCBF provided the optimal accuracy (74.4 %, 86.1 %, and 88.6 %, respectively). Combining the ADC values with nCBF or nrCBF could further improve the grading accuracy to 97.7 % or 95.3 %, respectively.

CONCLUSIONS

pCASL is an alternative to DSC-PWI for astrocytic tumour grading. The combination of DWI and contrast-free pCASL offers a valuable choice in patients with risk factors.

KEY POINTS

• pCASL shows positive correlation with DSC-PWI in astrocytic tumour grading. • ADC values based on ADC histograms can be an objective method. • Combination of DWI and pCASL or DSC-PWI can improve grading accuracy.

Cerebral Blood Flow Changes in Glioblastoma Patients Undergoing Bevacizumab Treatment Are Seen in Both Tumor and Normal Brain

Bevacizumab (BEV) is increasingly used to treat recurrent glioblastoma (GBM) with some reported improvement in neurocognitive function despite potential neurotoxicities. We examined the effects of BEV on cerebral blood flow (CBF) within recurrent GBM tumor and in the contralateral middle cerebral artery (MCA) territory.Post-chemoradiation patients with histologically confirmed GBM were treated with BEV and underwent routine, serial tumor imaging with additional pseudocontinuous arterial spin labeling (pcASL) following informed consent. Circular regions-of-interest were placed on pcASL images directly over the recurrent tumor and in the contralateral MCA territory. CBF changes before and during BEV treatment were evaluated in tumor and normal tissue. Linear mixed models were used to assess statistical significance.Fifty-three pcASL studies in 18 patients were acquired. Evaluation yielded lower mean tumoral CBF during BEV treatment compared with pre-treatment (45 ± 27 vs. 65 ± 27 ml/100 g/min, p = 0.002), and in the contralateral MCA territory during, compared with pre-BEV treatment (35 ± 8.4 vs. 41 ± 8.4 ml/100 g/min, p = 0.03). The decrease in mean CBF tended to be greater in the tumoral region than in the contralateral MCA, though the difference did not reach statistical significance (31% vs. 13%; p = 0.082).

CONCLUSIONS

BEV administration results in statistically significant global CBF decrease with a potentially preferential decrease in tumor perfusion compared with normal brain tissue.

Comparison of perfusion- and diffusion-weighted imaging parameters in brain tumor studies processed using different software platforms

RATIONALE AND OBJECTIVES

To compare quantitative imaging parameter measures from diffusion- and perfusion-weighted imaging magnetic resonance imaging (MRI) sequences in subjects with brain tumors that have been processed with different software platforms.

MATERIALS AND METHODS

Scans from 20 subjects with primary brain tumors were selected from the Comprehensive Neuro-oncology Data Repository at Washington University School of Medicine (WUSM) and the Swedish Neuroscience Institute. MR images were coregistered, and each subject's data set was processed by three software packages: 1) vendor-specific scanner software, 2) research software developed at WUSM, and 3) a commercially available, Food and Drug Administration-approved, processing platform (Nordic Ice). Regions of interest (ROIs) were chosen within the brain tumor and normal nontumor tissue. The results obtained using these methods were compared.

RESULTS

For diffusion parameters, including mean diffusivity and fractional anisotropy, concordance was high when comparing different processing methods. For perfusion-imaging parameters, a significant variance in cerebral blood volume, cerebral blood flow, and mean transit time (MTT) values was seen when comparing the same raw data processed using different software platforms. Correlation was better with larger ROIs (radii ≥ 5 mm). Greatest variance was observed in MTT.

CONCLUSIONS

Diffusion parameter values were consistent across different software processing platforms. Perfusion parameter values were more variable and were influenced by the software used. Variation in the MTT was especially large suggesting that MTT estimation may be unreliable in tumor tissues using current MRI perfusion methods.

Evaluation of the microenvironmental heterogeneity in high-grade gliomas with IDH1/2 gene mutation using histogram analysis of diffusion-weighted imaging and dynamic-susceptibility contrast perfusion imaging

The purpose of our study was to explore the difference between isocitrate dehydrogenase (IDH)-1/2 gene mutation-positive and -negative high-grade gliomas (HGGs) using histogram analysis of apparent diffusion coefficient (ADC) and normalized cerebral blood volume (nCBV) maps. We enrolled 52 patients with histopathologically confirmed HGGs with IDH1/2 (P) (n = 16) or IDH1/2 (N) (n = 36). Histogram parameters of ADC and nCBV maps were correlated with gene mutations by using the unpaired student's t test and multivariable stepwise logistic regression analysis. The mean ADC value was higher in the IDH1 (P) group than IDH1 (N) (1,282.8 vs. 1,159.6 mm(2)/s, P = .0113). In terms of the cumulative ADC histograms, the 10th and 50th percentile values were also higher in the IDH1 (P) than IDH1 (N) (P = .0104 and .0183, respectively). We observed a higher 90th percentile value (3.121 vs. 2.397, P = .0208) and a steeper slope between the 10th (C10) and 90th (C90) of cumulative nCBV histograms (0.03386 vs. 0.02425/%, P = .0067) in the IDH1 (N) group. Multivariate analysis showed that the mean ADC mean value (P = .0048), the C90 value (P = .0113), and the slope between C10 and C90 (P = .0049) were the significant variables in the differentiation of IDH1 (P) from IDH1 (N). In conclusion, histogram analysis of ADC and nCBV maps based on entire tumor volume can be a useful tool for distinguishing IDH1 (P) and IDH1 (N), and it predicts that IDH (P) tumors have a more heterogeneous microenvironment than IDH (N) ones.

Survival analysis in patients with newly diagnosed primary glioblastoma multiforme using pre- and post-treatment peritumoral perfusion imaging parameters

The objective of this study was to evaluate if peritumoral (PT) perfusion parameters obtained from dynamic susceptibility weighted contrast enhanced perfusion MRI can predict overall survival (OS) and progression free survival (PFS) in patients with newly diagnosed glioblastoma multiforme (GBM). Twenty-eight newly diagnosed GBM patients, who were treated with resection followed by concurrent chemoradiation and adjuvant chemotherapy, were included in this study. Evaluated perfusion parameters were pre- and post-treatment PT relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF). Proportional hazard analysis was used to assess the relationship OS, PFS and perfusion parameters. Kaplan-Meier survival estimates and log-rank test were used to characterize and compare the patient groups with high and low perfusion parameter values in terms of OS and PFS. Pretreatment PT rCBV and rCBF were not associated with OS and PFS whereas there was statistically significant association of both posttreatment PT rCBV and rCBF with OS and posttreatment rCBV with PFS (association of PFS and posttreatment rCBF was not statistically significant). Neither the Kaplan-Meier survival estimates nor the log-rank test demonstrated any differences in OS between high and low pretreatment PT rCBV values and rCBF values; however, high and low post-treatment PT rCBV and rCBF values did demonstrate statistically significant difference in OS and PFS. Our study found posttreatment, not pretreatment, PT perfusion parameters can be used to predict OS and PFS in patients with newly diagnosed GBM.

The evolving role of neurological imaging in neuro-oncology

Neuroimaging has played a critical role in the management of patients with neurological disease, since the first ventriculogram was performed in 1918 by Walter Dandy (Mezger et al. Langenbecks Arch Surg 398(4):501-514, 2013). Over the last century, technology has evolved significantly, and within the last decade, the role of imaging in the management of patients with neuro-oncologic disease has shifted from a tool for gross identification of intracranial pathology, to an integral part of real-time neurological surgery. Current neurological imaging provides detailed information about anatomical structure, neurological function, and metabolic and metabolism-important characteristics that help clinicians and surgeons non-invasively manage patients with brain tumors. It is valuable to review the evolution of neurological imaging over the past several decades, focusing on its role in the management of patients with intracranial tumors. Novel neuro-imaging tools and developing technology with the potential to further transform clinical practice will be discussed, as will the key role neurological imaging plays in neurosurgical planning and intraoperative navigation. With increasingly complex imaging modalities creating growing amounts of raw data, validation of techniques, data analysis, and integrating various pieces of imaging data into individual patient management plans, remain significant challenges for clinicians. We thus suggest mechanisms that might ultimately allow for evidence based integration of imaging in the management of patients with neuro-oncologic disease.

Evaluating the feasibility of an agglomerative hierarchy clustering algorithm for the automatic detection of the arterial input function using DSC-MRI

During dynamic susceptibility contrast-magnetic resonance imaging (DSC-MRI), it has been demonstrated that the arterial input function (AIF) can be obtained using fuzzy c-means (FCM) and k-means clustering methods. However, due to the dependence on the initial centers of clusters, both clustering methods have poor reproducibility between the calculation and recalculation steps. To address this problem, the present study developed an alternative clustering technique based on the agglomerative hierarchy (AH) method for AIF determination. The performance of AH method was evaluated using simulated data and clinical data based on comparisons with the two previously demonstrated clustering-based methods in terms of the detection accuracy, calculation reproducibility, and computational complexity. The statistical analysis demonstrated that, at the cost of a significantly longer execution time, AH method obtained AIFs more in line with the expected AIF, and it was perfectly reproducible at different time points. In our opinion, the disadvantage of AH method in terms of the execution time can be alleviated by introducing a professional high-performance workstation. The findings of this study support the feasibility of using AH clustering method for detecting the AIF automatically.

Comparison of K-means and fuzzy c-means algorithm performance for automated determination of the arterial input function

The arterial input function (AIF) plays a crucial role in the quantification of cerebral perfusion parameters. The traditional method for AIF detection is based on manual operation, which is time-consuming and subjective. Two automatic methods have been reported that are based on two frequently used clustering algorithms: fuzzy c-means (FCM) and K-means. However, it is still not clear which is better for AIF detection. Hence, we compared the performance of these two clustering methods using both simulated and clinical data. The results demonstrate that K-means analysis can yield more accurate and robust AIF results, although it takes longer to execute than the FCM method. We consider that this longer execution time is trivial relative to the total time required for image manipulation in a PACS setting, and is acceptable if an ideal AIF is obtained. Therefore, the K-means method is preferable to FCM in AIF detection.

Perfusion and diffusion MRI combined with ¹¹C-methionine PET in the preoperative evaluation of suspected adult low-grade gliomas

Perfusion and diffusion magnetic resonance imaging (pMRI, dMRI) are valuable diagnostic tools for assessing brain tumors in the clinical setting. The aim of this study was to determine the correlation of pMRI and dMRI with ¹¹C-methionine positron emission tomography (MET PET) in suspected low-grade gliomas (LGG) prior to surgery. Twenty-four adults with suspected LGG were enrolled in an observational study and examined by MET PET, pMRI and dMRI. Histological tumor diagnosis was confirmed in 23/24 patients (18 gliomas grade II, 5 gliomas grade III). The maximum relative cerebral blood volume (rCBV(max)) and the minimum mean diffusivity (MD(min)) were measured in tumor areas with highest MET uptake (hotspot) on PET by using automated co-registration of MRI and PET scans. A clearly defined hotspot on PET was present in all 23 tumors. Regions with rCBV(max) corresponded with hotspot regions in all tumors, regions with MD(min) corresponded with hotspot regions in 20/23 tumors. The correlation between rCBV(max) (r = 0.19, P = 0.38) and MD(min) (r = -0.41, P = 0.053) with MET uptake in the hotspot was not statistically significant. Taken into account the difficulties of measuring perfusion abnormalities in non-enhancing gliomas, this study demonstrates that co-registered MET PET and pMRI facilitates the identification of regions with rCBV(max). Furthermore, the lack of a clear positive correlation between tumor metabolism in terms of MET uptake and tumor vascularity measured as rCBV(max) suggests that combined pMRI/PET provides complementary baseline imaging data in these tumors.

Gliomas: application of cumulative histogram analysis of normalized cerebral blood volume on 3 T MRI to tumor grading

Background

Glioma grading assumes significant importance in that low- and high-grade gliomas display different prognoses and are treated with dissimilar therapeutic strategies. The objective of our study was to retrospectively assess the usefulness of a cumulative normalized cerebral blood volume (nCBV) histogram for glioma grading based on 3 T MRI.

Methods

From February 2010 to April 2012, 63 patients with astrocytic tumors underwent 3 T MRI with dynamic susceptibility contrast perfusion-weighted imaging. Regions of interest containing the entire tumor volume were drawn on every section of the co-registered relative CBV (rCBV) maps and T2-weighted images. The percentile values from the cumulative nCBV histograms and the other histogram parameters were correlated with tumor grades. Cochran’s Q test and the McNemar test were used to compare the diagnostic accuracies of the histogram parameters after the receiver operating characteristic curve analysis. Using the parameter offering the highest diagnostic accuracy, a validation process was performed with an independent test set of nine patients.

Results

The 99th percentile of the cumulative nCBV histogram (nCBV C99), mean and peak height differed significantly between low- and high-grade gliomas (P = <0.001, 0.014 and <0.001, respectively) and between grade III and IV gliomas (P = <0.001, 0.001 and <0.001, respectively). The diagnostic accuracy of nCBV C99 was significantly higher than that of the mean nCBV (P = 0.016) in distinguishing high- from low-grade gliomas and was comparable to that of the peak height (P = 1.000). Validation using the two cutoff values of nCBV C99 achieved a diagnostic accuracy of 66.7% (6/9) for the separation of all three glioma grades.

Conclusion

Cumulative histogram analysis of nCBV using 3 T MRI can be a useful method for preoperative glioma grading. The nCBV C99 value is helpful in distinguishing high- from low-grade gliomas and grade IV from III gliomas.