Magnetic Resonance Perfusion and Permeability Imaging in Brain Tumors

DA, K. KK. Diagnostic Utility of Integration of Dynamic Contrast-Enhanced and Dynamic Susceptibility Contrast MR Perfusion Employing Split Bolus Technique in Differentiating High-Grade Glioma

Background : Despite documented correlation between glioma grades and dynamic contrast-enhanced (DCE) magnetic resonance (MR) perfusion-derived parameters, and its inherent advantages over dynamic susceptibility contrast (DSC) perfusion, the former remains underutilized in clinical practice. Given the inherent spatial heterogeneity in high-grade diffuse glioma (HGG) and assessment of different perfusion parameters by DCE (extravascular extracellular space volume [Ve] and volume transfer constant in unit time [k-trans]) and DSC (rCBV), integration of the two into a protocol could provide a holistic assessment. Considering therapeutic and prognostic implications of differentiating WHO grade 3 from 4, we analyzed the two grades based on a combined DCE and DSC perfusion. Methods : Perfusion sequences were performed on 3-T MR. Cumulative dose of 0.1 mmol/kg of gadodiamide, split into two equal boluses, was administered with an interval of 6 minutes between the DCE and DSC sequences. DCE data were analyzed utilizing commercially available GenIQ software. Results : Of the 41 cases of diffuse gliomas analyzed, 24 were WHO grade III and 17 grade IV gliomas (2016 WHO classification). To differentiate grade III and IV gliomas, Ve cut-off value of 0.178 provided the best combination of sensitivity (88.24%) and specificity (87.50%; AUC: 0.920; p  < 0.001). A relative cerebral blood volume (rCBV) of value 3.64 yielded a sensitivity of 70.59% and specificity of 62.50% ( p  = 0.018). The k-trans value, although higher in grade III than in grade IV gliomas, did not reach statistical significance ( p  = 0.108). Conclusion : Uniqueness of employed combined perfusion technique, treatment naïve patients at imaging, user-friendly postprocessing software utilization, and ability of Ve and rCBV to differentiate between grade III and IV gliomas ( p  < 0.05) are the strengths of the present study, contributing to the existing literature and moving a step closer to achieving accurate MR perfusion-based glioma grading.

Arterial spin labelling MRI for brain tumour surveillance: do we really need cerebral blood flow maps?

OBJECTIVES

Arterial spin labelling (ASL) perfusion MRI is one of the available advanced MRI techniques for brain tumour surveillance. The first aim of this study was to investigate the correlation between quantitative cerebral blood flow (CBF) and non-quantitative perfusion weighted imaging (ASL-PWI) measurements. The second aim was to investigate the diagnostic accuracy of ASL-CBF and ASL-PWI measurements as well as visual assessment for identifying tumour progression.

METHODS

A consecutive cohort of patients who underwent 3-T MRI surveillance containing ASL for treated brain tumours was used. ROIs were drawn in representative parts of tumours in the ASL-CBF maps and copied to the ASL-PWI. ASL-CBF ratios and ASL-PWI ratios of the tumour ROI versus normal appearing white matter (NAWM) were correlated (Pearson correlation) and AUCs were calculated to assess diagnostic accuracy. Additionally, lesions were visually classified as hypointense, isointense, or hyperintense. We calculated accuracy at two thresholds: low threshold (between hypointense-isointense) and high threshold (between isointense-hyperintense).

RESULTS

A total of 173 lesions, both enhancing and non-enhancing, measured in 115 patients (93 glioma, 16 metastasis, and 6 lymphoma) showed a very high correlation of 0.96 (95% CI: 0.88-0.99) between ASL-CBF ratios and ASL-PWI ratios. AUC was 0.76 (95%CI: 0.65-0.88) for ASL-CBF ratios and 0.72 (95%CI: 0.58-0.85) for ASL-PWI ratios. Diagnostic accuracy of visual assessment for enhancing lesions was 0.72.

CONCLUSION

ASL-PWI ratios and ASL-CBF ratios showed a high correlation and comparable AUCs; therefore, quantification of ASL-CBF could be omitted in these patients. Visual classification had comparable diagnostic accuracy to the ASL-PWI or ASL-CBF ratios.

CLINICAL RELEVANCE STATEMENT

This study shows that CBF quantification of ASL perfusion MRI could be omitted for brain tumour surveillance and that visual assessment provides the same diagnostic accuracy. This greatly reduces the complexity of the use of ASL in routine clinical practice.

KEY POINTS

• Arterial spin labelling MRI for clinical brain tumour surveillance is undervalued and underinvestigated. • Non-quantitative and quantitative arterial spin labelling assessments show high correlation and comparable diagnostic accuracy. • Quantification of arterial spin labelling MRI could be omitted to improve daily clinical workflow.

The role and potential of using quantitative MRI biomarkers for imaging guidance in brain cancer radiotherapy treatment planning: A systematic review

Background and purpose

Improving the accuracy of brain tumour radiotherapy (RT) treatment planning is important to optimise patient outcomes. This systematic review investigates primary studies providing clinical evidence for the integration of quantitative magnetic resonance imaging (qMRI) biomarkers and MRI radiomics to optimise brain tumour RT planning.

Materials and methods

PubMed, Scopus, Embase and Web of Science databases were searched for all years until June 21, 2022. The search identified original articles demonstrating clinical evidence for the use of qMRI biomarkers and MRI radiomics for the optimization of brain cancer RT planning. Relevant information was extracted and tabulated, including qMRI metrics and techniques, impact on RT plan optimization and changes in target and normal tissue contouring and dose distribution.

Results

Nineteen articles met the inclusion criteria. Studies were grouped according to the qMRI biomarkers into: 1) diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI; five studies); 2) diffusion tensor imaging (DTI; seven studies); and 3) MR spectroscopic imaging (MRSI; seven studies). No relevant MRI-based radiomics studies were identified. Integration of DTI maps offers the potential for improved organs at risk (OAR) sparing. MRSI metabolic maps are a promising technique for improving delineation accuracy in terms of heterogeneity and infiltration, with OAR sparing. No firm conclusions could be drawn regarding the integration of DWI metrics and PWI maps.

Conclusions

Integration of qMRI metrics into RT planning offers the potential to improve delineation and OAR sparing. Clinical trials and consensus guidelines are required to demonstrate the clinical benefits of such approaches.

Efficacy of three-dimensional arterial spin labeling and how it compares against that of contrast enhanced magnetic resonance imaging in preoperative grading of brain gliomas

PURPOSE

To evaluate the efficacy of three-dimensional arterial spin labeling (3D-ASL) imaging in preoperative grading of brain gliomas, and compare the discrepancy between images obtained from 3D-ASL and contrast enhanced magnetic resonance imaging (CE-MRI) in grading of gliomas.

METHODS

Fifty-one patients with brain gliomas received plain MRI, CE-MRI and 3D-ASL scanning before surgery. In 3D-ASL images, the maximum tumor blood flow (TBF) of tumor parenchyma was measured, relative TBF-M and rTBF-WM were calculated. The cases were categorized into "ASL dominant" and "CE dominant" to compare the discrepancy between 3D-ASL and CE-MRI results. Independent samples t test, Mann-Whitney and U test and one-way analysis of variance (ANOVA) were performed to test the differences of TBF, rTBF-M and rTBF-WM values among brain gliomas with different grades. Spearman rank correlation analysis was performed to assess the correlation between TBF, rTBF-M, rTBF-WM and glioma grades respectively. To compare the discrepancy between 3D-ASL and CE-MRI results.

RESULTS

In high-grade gliomas (HGG) group, TBF, rTBF-M and rTBF-WM values were higher than those in low-grade gliomas (LGG) group (p < .05). Multiple comparison showed TBF and rTBF-WM values were different between grade I and IV gliomas, grade II and IV gliomas (both p < .05), the rTBF-M value was different between grade I and IV gliomas (p < .05). The values of all 3D-ASL derived parameters were positively correlated with gliomas grading (all p < .001). TBF showed highest specificity (89.3%) and rTBF-WM showed highest sensitivity (96.4%) when discriminating LGG and HGG using ROC curve. There were 29 CE dominant cases (23 cases were HGG), 9 ASL dominant cases (4 cases were HGG).  CONCLUSION: 3D-ASL is of significance to preoperative grading of brain gliomas and might be more sensitive than CE-MRI in detection of tumor perfusion.

Mapping glioma heterogeneity using multiparametric 18 F-choline PET/MRI in childhood and teenage-young adults

OBJECTIVE

The heterogeneity of post-treatment imaging remains a significant challenge in children and teenagers/young adults (TYA) diagnosed with glioma. The aim of this study was to evaluate the utility of 18 F-choline PET/MRI in determining intratumoural heterogeneity in paediatric and TYA gliomas.

METHODS

Twenty-six patients (mean age 16 years, range 8-22 years) with suspected glioma disease progression were evaluated with 18 F-choline PET/MRI. Relative cerebral blood volume (rCBV), apparent diffusion coefficient (ADC) and maximum standardised uptake values (SUV max ) in enhancing (enh) and non-enhancing (ne) tumour volumes and normal-appearing white matter (wm) were calculated (rCBV enh , rCBV ne , rCBV wm , ADC enh , ADC ne , ADC wm , SUV enh , SUV ne and SUV wm ).

RESULTS

Significantly higher SUV enh and SUV ne compared with SUV wm were observed [SUV enh 0.89 (0.23-1.90), SUV ne 0.36 (0.16-0.78) versus SUV wm 0.15 (0.04-1.19); P  < 0.001 and P  = 0.004, respectively]. Equivalent results were observed for ADV and rCBV (ADC enh , ADC ne : P  < 0.001 versus ADC wm ; rCBV enh , rCBV ne : P  < 0.001 versus rCBV wm ). The highest values for mean SUV max [0.89 (0.23-1.90)] and mean rCBV [2.1 (0.74-5.08)] were in the enhancing component, while the highest values for ADC [1780 mm 2 /s (863-2811)] were in the necrotic component.

CONCLUSION

18 F-choline PET/MRI is able map imaging heterogeneity in paediatric and TYA gliomas, detecting post-treatment enhancing, non-enhancing, and necrotic tumour components equivalent to ADC and DSC-derived rCBV. This offers potential in the response assessment of diffuse non-enhancing gliomas and in selected cases such as posterior fossa tumours where quantitative MRI is technically difficult.

Prognostication of overall survival in patients with brain metastases using diffusion tensor imaging and dynamic susceptibility contrast-enhanced MRI

OBJECTIVES

To investigate the prognostic utility of DTI and DSC-PWI perfusion-derived parameters in brain metastases patients.

METHODS

Retrospective analyses of DTI-derived parameters (MD, FA, CL, CP, and CS) and DSC-perfusion PWI-derived rCBVmax from 101 patients diagnosed with brain metastases prior to treatment were performed. Using semi-automated segmentation, DTI metrics and rCBVmax were quantified from enhancing areas of the dominant metastatic lesion. For each metric, patients were classified as short- and long-term survivors based on analysis of the best coefficient for each parameter and percentile to separate the groups. Kaplan-Meier analysis was used to compare mOS between these groups. Multivariate survival analysis was subsequently conducted. A correlative histopathologic analysis was performed in a subcohort (n = 10) with DTI metrics and rCBVmax on opposite ends of the spectrum.

RESULTS

Significant differences in mOS were observed for MDmin (p < 0.05), FA (p < 0.01), CL (p < 0.05), and CP (p < 0.01) and trend toward significance for rCBVmax (p = 0.07) between the two risk groups, in the univariate analysis. On multivariate analysis, the best predictive survival model was comprised of MDmin (p = 0.05), rCBVmax (p < 0.05), RPA (p < 0.0001), and number of lesions (p = 0.07). On histopathology, metastatic tumors showed significant differences in the amount of stroma depending on the combination of DTI metrics and rCBVmax values. Patients with high stromal content demonstrated poorer mOS.

CONCLUSION

Pretreatment DTI-derived parameters, notably MDmin and rCBVmax, are promising imaging markers for prognostication of OS in patients with brain metastases. Stromal cellularity may be a contributing factor to these differences.

ADVANCES IN KNOWLEDGE

The correlation of DTI-derived metrics and perfusion MRI with patient outcomes has not been investigated in patients with treatment naïve brain metastasis. DTI and DSC-PWI can aid in therapeutic decision-making by providing additional clinical guidance.

Noninvasive Determination of the IDH Status of Gliomas Using MRI and MRI-Based Radiomics: Impact on Diagnosis and Prognosis

Gliomas are the most common primary malignant brain tumors in adults. The fifth edition of the WHO Classification of Tumors of the Central Nervous System, published in 2021, provided molecular and practical approaches to CNS tumor taxonomy. Currently, molecular features are essential for differentiating the histological subtypes of gliomas, and recent studies have emphasized the importance of isocitrate dehydrogenase (IDH) mutations in stratifying biologically distinct subgroups of gliomas. IDH plays a significant role in gliomagenesis, and the association of IDH status with prognosis is very clear. Recently, there has been much progress in conventional MR imaging (cMRI), advanced MR imaging (aMRI), and radiomics, which are widely used in the study of gliomas. These advances have resulted in an improved correlation between MR signs and IDH mutation status, which will complement the prediction of the IDH phenotype. Although imaging cannot currently substitute for genetic tests, imaging findings have shown promising signs of diagnosing glioma subtypes and evaluating the efficacy and prognosis of individualized molecular targeted therapy. This review focuses on the correlation between MRI and MRI-based radiomics and IDH gene-phenotype prediction, discussing the value and application of these techniques in the diagnosis and evaluation of the prognosis of gliomas.

Evaluation of normal-appearing white matter with perfusion and diffusion MRI in patients with treated glioblastoma

OBJECTIVE

We tried to reveal how the normal appearing white matter (NAWM) was affected in patients with glioblastoma treated with chemo-radiotherapy (CRT) in the period following the treatment, by multiparametric MRI.

MATERIALS AND METHODS

43 multiparametric MRI examinations of 17 patients with glioblastoma treated with CRT were examined. A total of six different series or maps were analyzed in the examinations: Apparent Diffusion Coefficient (ADC) and Fractional Anisotropy (FA) maps, Gradient Echo (GRE) sequence, Dynamic susceptibility contrast (DSC) and Arterial spin labeling (ASL) perfusion sequences. Each sequence in each examination was examined in detail with 14 Region of Interest (ROI) measurements. The obtained values were proportioned to the contralateral NAWM values and the results were recorded as normalized values. Time dependent changes of normalized values were statistically analyzed.

RESULTS

The most prominent changes in follow-up imaging occurred in the perilesional region. In perilesional NAWM, we found a decrease in normalized FA (nFA), rCBV (nrCBV), rCBF (nrCBF), ASL (nASL)values (p < 0.005) in the first 3 months after treatment, followed by a plateau and an increase approaching pretreatment values, although it did not reach. Similar but milder findings were present in other NAWM areas. In perilesional NAWM, nrCBV values were found to be positively high correlated with nrCBF and nASL, and negatively high correlated with nADC values (r: 0.963, 0.736, - 0.973, respectively). We also found high correlations between the mean values of nrCBV, nrCBF, nASL in other NAWM areas (r: 0.891, 0.864, respectively).

DISCUSSION

We showed that both DSC and ASL perfusion values decreased correlatively in the first 3 months and showed a plateau after 1 year in patients with glioblastoma treated with CRT, unlike the literature. Although it was not as evident as perfusion MRI, it was observed that the ADC values also showed a plateau pattern following the increase in the first 3 months. Further studies are needed to explain late pathophysiological changes. Because of the high correlation, our results support ASL perfusion instead of contrast enhanced perfusion methods.

Dynamic contrast-enhanced magnetic resonance imaging for evaluating early response to radiosurgery in patients with vestibular schwannoma

PURPOSE

This study aimed to use dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to evaluate early treatment response in vestibular schwannoma (VS) patients after radiosurgery.

METHODS

Twenty-four VS patients who underwent gamma knife radiosurgery were prospectively followed up for at least four years. DCE-MRI sequences, in addition to standard MRI protocol, were obtained prior to radiosurgery, at 3 and 6 months. Conventionally, treatment responses based on tumor volume changes were classified as regression or stable (RS), transient tumor enlargement (TTE), and continuous tumor enlargement (CTE). DCE-MRI parameters, such as K^trans, K_ep and V_e, were compared according to follow-up periods and between groups. The diagnostic performance was tested using receiver operating characteristic (ROC) curves.

RESULTS

Changes in tumor volume were as follows at the last 48 months of follow-up: RS in 11 patients (45.8%), TTE in 10 patients (41.7%), and CTE in three patients (12.5%). The median time required to distinguish TTE from CTE using conventional MRI was 12 months (range 9-18). The K^trans and V_e were significantly decreased in patients with RS and TTE at 3 and 6 months, but did not differ significantly in patients with CTE. There were no significant differences in K^trans and V_e between patients with RS and TTE at 3 and 6 months. Both K^trans and V_e demonstrated high diagnostic performance in evaluating early treatment response to radiosurgery in patients with VS.

CONCLUSION

DCE-MRI may aid in the monitoring and early prediction of treatment response in patients with VS following radiosurgery.

Advanced Magnetic Resonance Imaging in Pediatric Glioblastomas

The shortly upcoming 5th edition of the World Health Organization Classification of Tumors of the Central Nervous System is bringing extensive changes in the terminology of diffuse high-grade gliomas (DHGGs). Previously "glioblastoma," as a descriptive entity, could have been applied to classify some tumors from the family of pediatric or adult DHGGs. However, now the term "glioblastoma" has been divested and is no longer applied to tumors in the family of pediatric types of DHGGs. As an entity, glioblastoma remains, however, in the family of adult types of diffuse gliomas under the insignia of "glioblastoma, IDH-wildtype." Of note, glioblastomas still can be detected in children when glioblastoma, IDH-wildtype is found in this population, despite being much more common in adults. Despite the separation from the family of pediatric types of DHGGs, what was previously labeled as "pediatric glioblastomas" still remains with novel labels and as new entities. As a result of advances in molecular biology, most of the previously called "pediatric glioblastomas" are now classified in one of the four family members of pediatric types of DHGGs. In this review, the term glioblastoma is still apocryphally employed mainly due to its historical relevance and the paucity of recent literature dealing with the recently described new entities. Therefore, "glioblastoma" is used here as an umbrella term in the attempt to encompass multiple entities such as astrocytoma, IDH-mutant (grade 4); glioblastoma, IDH-wildtype; diffuse hemispheric glioma, H3 G34-mutant; diffuse pediatric-type high-grade glioma, H3-wildtype and IDH-wildtype; and high grade infant-type hemispheric glioma. Glioblastomas are highly aggressive neoplasms. They may arise anywhere in the developing central nervous system, including the spinal cord. Signs and symptoms are non-specific, typically of short duration, and usually derived from increased intracranial pressure or seizure. Localized symptoms may also occur. The standard of care of "pediatric glioblastomas" is not well-established, typically composed of surgery with maximal safe tumor resection. Subsequent chemoradiation is recommended if the patient is older than 3 years. If younger than 3 years, surgery is followed by chemotherapy. In general, "pediatric glioblastomas" also have a poor prognosis despite surgery and adjuvant therapy. Magnetic resonance imaging (MRI) is the imaging modality of choice for the evaluation of glioblastomas. In addition to the typical conventional MRI features, i.e., highly heterogeneous invasive masses with indistinct borders, mass effect on surrounding structures, and a variable degree of enhancement, the lesions may show restricted diffusion in the solid components, hemorrhage, and increased perfusion, reflecting increased vascularity and angiogenesis. In addition, magnetic resonance spectroscopy has proven helpful in pre- and postsurgical evaluation. Lastly, we will refer to new MRI techniques, which have already been applied in evaluating adult glioblastomas, with promising results, yet not widely utilized in children.

Prediction of Intraoperative Fluorescence of Brain Gliomas: Correlation between Tumor Blood Flow and the Fluorescence

INTRODUCTION

The prediction of the fluorescent effect of 5-aminolevulinic acid (5-ALA) in patients with diffuse gliomas can improve the selection of patients. The degree of enhancement of gliomas has been reported to predict 5-ALA fluorescence, while, at the same time, rarer cases of fluorescence have been described in non-enhancing gliomas. Perfusion studies, in particular arterial spin labeling perfusion, have demonstrated high efficiency in determining the degree of malignancy of brain gliomas and may be better for predicting fluorescence than contrast enhancement. The aim of the study was to investigate the relationship between tumor blood flow, measured by ASL, and intraoperative fluorescent glow of gliomas of different grades.

MATERIALS AND METHODS

Tumoral blood flow was assessed in 75 patients by pCASL (pseudo-continuous arterial spin labeling) within 1 week prior to surgery. In all cases of tumor removal, 5-ALA had been administered preoperatively. Maximum values of tumoral blood flow (TBF max) were measured, and normalized tumor blood flow (nTBF) was calculated.

RESULTS

A total of 76% of patients had significant contrast enhancement, while 24% were non-enhancing. The histopathology revealed 17 WHO grade II gliomas, 12 WHO grade III gliomas and 46 glioblastomas. Overall, there was a relationship between the degree of intraoperative tumor fluorescence and ASL-TBF (R_s = 0.28, p = 0.02 or the TBF; R_s = 0.34, p = 0.003 for nTBF). Non-enhancing gliomas were fluorescent in 9/18 patients, with nTBF in fluorescent gliomas being 54.58 ± 32.34 mL/100 mg/s and in non-fluorescent gliomas being 52.99 ± 53.61 mL/100 g/s (p > 0.05). Enhancing gliomas were fluorescent in 53/57 patients, with nTBF being 170.17 ± 107.65 mL/100 g/s in fluorescent and 165.52 ± 141.71 in non-fluorescent gliomas (p > 0.05).

CONCLUSION

Tumoral blood flow levels measured by non-contrast ASL perfusion method predict the fluorescence by 5-ALA; however, the additional value beyond contrast enhancement is not clear. ASL is, however, useful in cases with contraindication to contrast.

Neuroimaging in the Era of the Evolving WHO Classification of Brain Tumors, From the AJR Special Series on Cancer Staging

The inclusion of molecular and genetic information with histopathologic information defines the framework for brain tumor classification and grading. This framework is reflected in the major restructuring of the WHO brain tumor classification system in 2016 and in numerous subsequent proposed updates reflecting ongoing developments in understanding the impact of tumor genotype on classification and grading. This incorporation of molecular and genetic features improves tumor diagnosis and prediction of tumor behavior and response to treatment. Neuroimaging is essential for the noninvasive assessment of pretreatment tumor grading and for identification and determination of therapeutic efficacy. Use of conventional neuroimaging and physiologic imaging techniques, such as diffusion- and perfusion-weighted MRI, can increase diagnostic confidence before and after treatment. Although the use of neuroimaging to consistently determine tumor genetics is not yet robust, promising developments are on the horizon. Given the complexity of the brain tumor microenvironment, the development and implementation of a standardized reporting system can aid in conveying to radiologists, referring providers, and patients important information about brain tumor response to treatment. The purpose of this article is to review the current state and role of neuroimaging in this continuously evolving field.

Glioblastoma post-operative imaging in neuro-oncology: current UK practice (GIN CUP study)

OBJECTIVES

MRI remains the preferred imaging investigation for glioblastoma. Appropriate and timely neuroimaging in the follow-up period is considered to be important in making management decisions. There is a paucity of evidence-based information in current UK, European and international guidelines regarding the optimal timing and type of neuroimaging following initial neurosurgical treatment. This study assessed the current imaging practices amongst UK neuro-oncology centres, thus providing baseline data and informing future practice.

METHODS

The lead neuro-oncologist, neuroradiologist and neurosurgeon from every UK neuro-oncology centre were invited to complete an online survey. Participants were asked about current and ideal imaging practices following initial treatment.

RESULTS

Ninety-two participants from all 31 neuro-oncology centres completed the survey (100% response rate). Most centres routinely performed an early post-operative MRI (87%, 27/31), whereas only a third performed a pre-radiotherapy MRI (32%, 10/31). The number and timing of scans routinely performed during adjuvant TMZ treatment varied widely between centres. At the end of the adjuvant period, most centres performed an MRI (71%, 22/31), followed by monitoring scans at 3 monthly intervals (81%, 25/31). Additional short-interval imaging was carried out in cases of possible pseudoprogression in most centres (71%, 22/31). Routine use of advanced imaging was infrequent; however, the addition of advanced sequences was the most popular suggestion for ideal imaging practice, followed by changes in the timing of EPMRI.

CONCLUSION

Variations in neuroimaging practices exist after initial glioblastoma treatment within the UK. Multicentre, longitudinal, prospective trials are needed to define the optimal imaging schedule for assessment.

KEY POINTS

• Variations in imaging practices exist in the frequency, timing and type of interval neuroimaging after initial treatment of glioblastoma within the UK. • Large, multicentre, longitudinal, prospective trials are needed to define the optimal imaging schedule for assessment.

Better efficacy in differentiating WHO grade II from III oligodendrogliomas with machine-learning than radiologist's reading from conventional T1 contrast-enhanced and fluid attenuated inversion recovery images

Background

The medical imaging to differentiate World Health Organization (WHO) grade II (ODG2) from III (ODG3) oligodendrogliomas still remains a challenge. We investigated whether combination of machine leaning with radiomics from conventional T1 contrast-enhanced (T1 CE) and fluid attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) offered superior efficacy.

Methods

Thirty-six patients with histologically confirmed ODGs underwent T1 CE and 33 of them underwent FLAIR MR examination before any intervention from January 2015 to July 2017 were retrospectively recruited in the current study. The volume of interest (VOI) covering the whole tumor enhancement were manually drawn on the T1 CE and FLAIR slice by slice using ITK-SNAP and a total of 1072 features were extracted from the VOI using 3-D slicer software. Random forest (RF) algorithm was applied to differentiate ODG2 from ODG3 and the efficacy was tested with 5-fold cross validation. The diagnostic efficacy of radiomics-based machine learning and radiologist’s assessment were also compared.

Results

Nineteen ODG2 and 17 ODG3 were included in this study and ODG3 tended to present with prominent necrosis and nodular/ring-like enhancement (P < 0.05). The AUC, ACC, sensitivity, and specificity of radiomics were 0.798, 0.735, 0.672, 0.789 for T1 CE, 0.774, 0.689, 0.700, 0.683 for FLAIR, as well as 0.861, 0.781, 0.778, 0.783 for the combination, respectively. The AUCs of radiologists 1, 2 and 3 were 0.700, 0.687, and 0.714, respectively. The efficacy of machine learning based on radiomics was superior to the radiologists’ assessment.

Conclusions

Machine-learning based on radiomics of T1 CE and FLAIR offered superior efficacy to that of radiologists in differentiating ODG2 from ODG3.

Clinical MR Biomarkers

Non-invasive magnetic resonance imaging (MRI) techniques are increasingly applied in the clinic with a fast growing body of evidence regarding its value for clinical decision making. In contrast to biochemical or histological markers, the key advantages of imaging biomarkers are the non-invasive nature and the spatial and temporal resolution of these approaches. The following chapter focuses on clinical applications of novel MR biomarkers in humans with a strong focus on oncologic diseases. These include both clinically established biomarkers (part 1-4) and novel MRI techniques that recently demonstrated high potential for clinical utility (part 5-7).

Repeatability and reproducibility of relative cerebral blood volume measurement of recurrent glioma in a multicentre trial setting

BACKGROUND

Measurement of relative cerebral blood volume (rCBV) with dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) is used extensively for brain tumour diagnosis and follow-up. The aim of this pilot study was to assess the robustness of rCBV measurement in patients with enhancing recurrent glioma in a European multicentre trial setting.

METHODS

We included pre-treatment postcontrast T1 weighted (T1w) and DSC scans of 20 patients with recurrent glioma from 2 European Organisation for Research and Treatment of Cancer trials (26101 and 26091). Three reviewers independently placed a fixed circular region of interest of 70 mm² in the tumour area of highest rCBV (rCBV_max). To calculate the normalised rCBV_max (nrCBV_max), three ROIs were placed in the anterior, middle and posterior centrum semiovale normal-appearing white matter of the contralateral hemisphere. After several months, each observer repeated the assessments blinded for initial findings. Repeatability and reproducibility were estimated with a mixed model. Each measurement was also classified according to 4 clinically meaningful categories.

RESULTS

Three patients were post hoc excluded from analysis because of lack of enhancing tumour. The mean nrCBV_max repeatability was 49.5%, and reproducibility was 5.5%. In 14 of 17 patients, at least 2 reviewers classified the patient into the same category.

CONCLUSIONS

Our results indicate that a well-established review process needs to be applied upfront to assess perfusion in a multicentre trial setting. While awaiting further validation, we propose as a strategy to measure rCBV in the context of recurrent glioma trials to use two central reviewers and an adjudicator in case of disagreement.

Magnetic Resonance Imaging Parameters and Their Impact on Survival of Patients with Glioblastoma: Tumor Perfusion Predicts Survival

BACKGROUND

Many prognostic factors influence overall survival (OS) of patients with glioblastoma. Despite gross total resection and Stupp protocol adherence, many patients have poor survival. Perfusion magnetic resonance imaging may assist in diagnosis, treatment monitoring, and prognostication.

METHODS

This retrospective study of 36 patients with glioblastoma assessed influence of preoperative magnetic resonance imaging parameters reflecting tumor cell density and vascularity and patient age on OS.

RESULTS

The area under curve based on optimal receiver operating characteristic curves for the perfusion parameters normalized relative tumor blood volume (n_rTBV) and normalized relative tumor blood flow (n_rTBF) were 0.92 and 0.89, respectively, and the highest among all imaging parameters and age. OS showed strongly negative correlations with corrected n_rTBV (R = -0.70; P < 0.001) and n_rTBF (R = -0.67; P < 0.001). The Cox model, which included age and imaging parameters, demonstrated that n_rTBV and n_rTBF were most predictive of OS, with hazard ratios of 5.97 (P = 0.0001) and 8.76 (P = 0.0001), respectively, compared with 1.63 (P = 0.19) for age. Eighteen patients with corrected n_rTBV ≤2.5 (best cutoff value) had a median OS of 15.1 months (95% confidence interval (CI), 11.34-21.25) compared with 2.8 months (95% CI, 1.48-4.03; P < 0.001) for 18 patients with corrected n_rTBV >2.5. Twenty-four patients with n_rTBF ≤2.79 had a median OS of 12 months (95% CI, 10.46-17.9) compared with 2.8 months for 12 patients with n_rTBF >2.79 (95% CI, 1.31-4.2; P < 0.001).

CONCLUSIONS

The dominant predictors of OS are normalized perfusion parameters n_rTBV and n_rTBF. Preoperative perfusion imaging may be used as a surrogate to predict glioblastoma aggressiveness and survival independent of treatment.

Perfusion MRI grading diffuse gliomas: Impact of permeability parameters on molecular biomarkers and survival

BACKGROUND AND PURPOSE

Our objectives were: (1) compare dynamic susceptibility-weighted (DSC) and dynamic contrast-enhanced (DCE) permeability parameters, (2) evaluate diagnostic accuracy of DSC and DCE discriminating high- and low-grade tumors, (3) analyze relationship of permeability parameters with overall (OS) and progression-free survival (PFS) and (4) assess differences in high-grade tumors classified according to molecular biomarkers.

MATERIALS AND METHODS

49 patients with histologically proved diffuse gliomas underwent DSC and DCE imaging. Parametric maps of cerebral blood volume (CBV), CBV-leakage corrected, volume transfer coefficient (Ktrans), fractional volume of the extravascular extracellular space (EES) (Ve), fractional blood plasma volume (Vp) and rate constant between EES and blood plasma (Kep) were calculated. High-grade gliomas were also classified according to isocitrate dehydrogenase (IDH), alpha-thalassemia/mental retardation syndrome X-linked (ATRX) and O6-methylguanine-dna-methyltransferase promoter methylation (MGMT) status.

RESULTS

There is correlation between parameters leakage, Ktrans and Vp. ROC curve analysis showed significance in both Ktrans and Ve for glioma grading. Threshold value of 0.075 for Ve generated the best combination of sensitivity (80%) and specificity (75%) in tumor gradation. Leakage was the only permeability parameter related to OS (P=0.006) and PFS (0.012); with prolonged survival for leakage values lower than 1.2. IDH-mutated high-grade tumors showed lower leakage and Ktrans values. High-grade tumors with loss of ATRX presented lower leakage and Vp values.

CONCLUSIONS

Both DSC and DCE permeability parameters serve as non-invasive method for glioma grading. Leakage was the unique permeability parameter related to survival and the best discriminating high-grade gliomas classified according to IDH and ATRX status.

Perfusion Magnetic Resonance Imaging Changes in Normal Appearing Brain Tissue after Radiotherapy in Glioblastoma Patients may Confound Longitudinal Evaluation of Treatment Response

Background

The aim of this study was assess acute and early delayed radiation-induced changes in normal-appearing brain tissue perfusion as measured with perfusion magnetic resonance imaging (MRI) and the dependence of these changes on the fractionated radiotherapy (FRT) dose level.

Patients and methods

Seventeen patients with glioma WHO grade III-IV treated with FRT were included in this prospective study, seven were excluded because of inconsistent FRT protocol or missing examinations. Dynamic susceptibility contrast MRI and contrast-enhanced 3D-T1-weighted (3D-T1w) images were acquired prior to and in average (standard deviation): 3.1 (3.3), 34.4 (9.5) and 103.3 (12.9) days after FRT. Pre-FRT 3D-T1w images were segmented into white- and grey matter. Cerebral blood volume (CBV) and cerebral blood flow (CBF) maps were calculated and co-registered patient-wise to pre-FRT 3D-T1w images. Seven radiation dose regions were created for each tissue type: 0-5 Gy, 5-10 Gy, 10-20 Gy, 20-30 Gy, 30-40 Gy, 40-50 Gy and 50-60 Gy. Mean CBV and CBF were calculated in each dose region and normalised (nCBV and nCBF) to the mean CBV and CBF in 0-5 Gy white- and grey matter reference regions, respectively.

Results

Regional and global nCBV and nCBF in white- and grey matter decreased after FRT, followed by a tendency to recover. The response of nCBV and nCBF was dose-dependent in white matter but not in grey matter.

Conclusions

Our data suggest that radiation-induced perfusion changes occur in normal-appearing brain tissue after FRT. This can cause an overestimation of relative tumour perfusion using dynamic susceptibility contrast MRI, and can thus confound tumour treatment evaluation.

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 imaging in Europe: A survey of 220 centres and recommendations for best clinical practice

Objectives

At a European Society of Neuroradiology (ESNR) Annual Meeting 2015 workshop, commonalities in practice, current controversies and technical hurdles in glioma MRI were discussed. We aimed to formulate guidance on MRI of glioma and determine its feasibility, by seeking information on glioma imaging practices from the European Neuroradiology community.

Methods

Invitations to a structured survey were emailed to ESNR members (n=1,662) and associates (n=6,400), European national radiologists’ societies and distributed via social media.

Results

Responses were received from 220 institutions (59% academic). Conventional imaging protocols generally include T2w, T2-FLAIR, DWI, and pre- and post-contrast T1w. Perfusion MRI is used widely (85.5%), while spectroscopy seems reserved for specific indications. Reasons for omitting advanced imaging modalities include lack of facility/software, time constraints and no requests. Early postoperative MRI is routinely carried out by 74% within 24–72 h, but only 17% report a percent measure of resection. For follow-up, most sites (60%) issue qualitative reports, while 27% report an assessment according to the RANO criteria. A minority of sites use a reporting template (23%).

Conclusion

Clinical best practice recommendations for glioma imaging assessment are proposed and the current role of advanced MRI modalities in routine use is addressed.

Key Points

• We recommend the EORTC-NBTS protocol as the clinical standard glioma protocol.

• Perfusion MRI is recommended for diagnosis and follow-up of glioma.

• Use of advanced imaging could be promoted with increased education activities.

• Most response assessment is currently performed qualitatively.

• Reporting templates are not widely used, and could facilitate standardisation.

Electronic supplementary material

The online version of this article (10.1007/s00330-018-5314-5) contains supplementary material, which is available to authorized users.

Differentiation of grade II/III and grade IV glioma by combining "T1 contrast-enhanced brain perfusion imaging" and susceptibility-weighted quantitative imaging

PURPOSE

MRI is a useful method for discriminating low- and high-grade glioma using perfusion MRI and susceptibility-weighted imaging (SWI). The purpose of this study is to evaluate the usefulness of T1-perfusion MRI and SWI in discriminating among grade II, III, and IV gliomas.

METHODS

T1-perfusion MRI was used to measure relative cerebral blood volume (rCBV) in 129 patients with glioma (70 grade IV, 33 grade III, and 26 grade II tumors). SWI was also used to measure the intratumoral susceptibility signal intensity (ITSS) scores for each tumor in these patients. rCBV and ITSS values were compared to seek differences between grade II vs. grade III, grade III vs. grade IV, and grade III+II vs. grade IV tumors.

RESULTS

Significant differences in rCBV values of the three grades of the tumors were noted and pairwise comparisons showed significantly higher rCBV values in grade IV tumors as compared to grade III tumors, and similarly increased rCBV was seen in the grade III tumors as compared to grade II tumors (p < 0.001). Grade IV gliomas showed significantly higher ITSS scores on SWI as compared to grade III tumors (p < 0.001) whereas insignificant difference was seen on comparing ITSS scores of grade III with grade II tumors. Combining the rCBV and ITSS resulted in significant improvement in the discrimination of grade III from grade IV tumors.

CONCLUSION

The combination of rCBV values derived from T1-perfusion MRI and SWI derived ITSS scores improves the diagnostic accuracy for discrimination of grade III from grade IV gliomas.

Technical Aspects of Contrast-enhanced MR Angiography: Current Status and New Applications

This article is based on a presentation at the meeting of the Japanese Society of Magnetic Resonance in Medicine in September 2016. The purpose is to review the technical developments which have contributed to the current status of contrast-enhanced magnetic resonance angiography (CE-MRA) and to indicate related emerging areas of study. Technical developments include MRI physics-based innovations as well as improvements in MRI engineering. These have collectively addressed not only early issues of timing and venous suppression but more importantly have led to an improvement in spatiotemporal resolution of CE-MRA of more than two orders of magnitude compared to early results. This has allowed CE-MRA to be successfully performed in virtually all vascular territories of the body. Contemporary technical areas of study include improvements in implementation of high rate acceleration, extension of high performance first-pass CE-MRA across multiple imaging stations, expanded use of compressive sensing techniques, integration of Dixon-based fat suppression into CE-MRA sequences, and application of CE-MRA sequences to dynamic-contrast-enhanced perfusion imaging.

Advanced MRI Techniques in the Monitoring of Treatment of Gliomas

OPINION STATEMENT

With advances in treatments and survival of patients with glioblastoma (GBM), it has become apparent that conventional imaging sequences have significant limitations both in terms of assessing response to treatment and monitoring disease progression. Both 'pseudoprogression' after chemoradiation for newly diagnosed GBM and 'pseudoresponse' after anti-angiogenesis treatment for relapsed GBM are well-recognised radiological entities. This in turn has led to revision of response criteria away from the standard MacDonald criteria, which depend on the two-dimensional measurement of contrast-enhancing tumour, and which have been the primary measure of radiological response for over three decades. A working party of experts published RANO (Response Assessment in Neuro-oncology Working Group) criteria in 2010 which take into account signal change on T2/FLAIR sequences as well as the contrast-enhancing component of the tumour. These have recently been modified for immune therapies, which are associated with specific issues related to the timing of radiological response. There has been increasing interest in quantification and validation of physiological and metabolic parameters in GBM over the last 10 years utilising the wide range of advanced imaging techniques available on standard MRI platforms. Previously, MRI would provide structural information only on the anatomical location of the tumour and the presence or absence of a disrupted blood-brain barrier. Advanced MRI sequences include proton magnetic resonance spectroscopy (MRS), vascular imaging (perfusion/permeability) and diffusion imaging (diffusion weighted imaging/diffusion tensor imaging) and are now routinely available. They provide biologically relevant functional, haemodynamic, cellular, metabolic and cytoarchitectural information and are being evaluated in clinical trials to determine whether they offer superior biomarkers of early treatment response than conventional imaging, when correlated with hard survival endpoints. Multiparametric imaging, incorporating different combinations of these modalities, improves accuracy over single imaging modalities but has not been widely adopted due to the amount of post-processing analysis required, lack of clinical trial data, lack of radiology training and wide variations in threshold values. New techniques including diffusion kurtosis and radiomics will offer a higher level of quantification but will require validation in clinical trial settings. Given all these considerations, it is clear that there is an urgent need to incorporate advanced techniques into clinical trial design to avoid the problems of under or over assessment of treatment response.

Advanced MRI for Pediatric Brain Tumors with Emphasis on Clinical Benefits

Conventional anatomic brain MRI is often limited in evaluating pediatric brain tumors, the most common solid tumors and a leading cause of death in children. Advanced brain MRI techniques have great potential to improve diagnostic performance in children with brain tumors and overcome diagnostic pitfalls resulting from diverse tumor pathologies as well as nonspecific or overlapped imaging findings. Advanced MRI techniques used for evaluating pediatric brain tumors include diffusion-weighted imaging, diffusion tensor imaging, functional MRI, perfusion imaging, spectroscopy, susceptibility-weighted imaging, and chemical exchange saturation transfer imaging. Because pediatric brain tumors differ from adult counterparts in various aspects, MRI protocols should be designed to achieve maximal clinical benefits in pediatric brain tumors. In this study, we review advanced MRI techniques and interpretation algorithms for pediatric brain tumors.

Brain Vascular Imaging Techniques

Recent major improvements in a number of imaging techniques now allow for the study of the brain in ways that could not be considered previously. Researchers today have well-developed tools to specifically examine the dynamic nature of the blood vessels in the brain during development and adulthood; as well as to observe the vascular responses in disease situations in vivo. This review offers a concise summary and brief historical reference of different imaging techniques and how these tools can be applied to study the brain vasculature and the blood-brain barrier integrity in both healthy and disease states. Moreover, it offers an overview on available transgenic animal models to study vascular biology and a description of useful online brain atlases.

Multiparametric MR Imaging in the Assessment of Brain Tumors

Functional MR imaging methods make possible the quantification of dynamic physiologic processes that occur in the brain. Moreover, the use of these advanced imaging techniques in the setting of oncologic treatment of the brain is widely accepted and has found worldwide routine clinical use.

Comparison of Cerebral Blood Volume and Plasma Volume in Untreated Intracranial Tumors

Purpose

Plasma volume and blood volume are imaging-derived parameters that are often used to evaluation intracranial tumors. Physiologically, these parameters are directly related, but their two different methods of measurements, T1-dynamic contrast enhanced (DCE)- and T2-dynamic susceptibility contrast (DSC)-MR utilize different model assumptions and approaches. This poses the question of whether the interchangeable use of T1-DCE-MRI derived fractionated plasma volume (vp) and relative cerebral blood volume (rCBV) assessed using DSC-MRI, particularly in glioblastoma, is reliable, and if this relationship can be generalized to other types of brain tumors. Our goal was to examine the hypothetical correlation between these parameters in three most common intracranial tumor types.

Methods

Twenty-four newly diagnosed, treatment naïve brain tumor patients, who had undergone DCE- and DSC-MRI, were classified in three histologically proven groups: glioblastoma (n = 7), meningioma (n = 9), and intraparenchymal metastases (n = 8). The rCBV was obtained from DSC after normalization with the normal-appearing anatomically symmetrical contralateral white matter. Correlations between these parameters were evaluated using Pearson (r), Spearman's (ρ) and Kendall’s tau-b (τ_B) rank correlation coefficient.

Results

The Pearson, Spearman and Kendall’s correlation between vp with rCBV were r = 0.193, ρ = 0.253 and τ_B = 0.33 (p-_Pearson = 0.326, p-_Spearman= 0.814 and p-_Kendall= 0.823) in glioblastoma, r = -0.007, ρ = 0.051 and τ_B = 0.135 (p-_Pearson = 0.970, p-_Spearman= 0.765 and p-_Kendall= 0.358) in meningiomas, and r = 0.289, ρ = 0.228 and τ_B = 0.239 (p-_Pearson = 0.109, p-_Spearman= 0.210 and p-_Kendall= 0.095) in metastasis.

Conclusion

Results indicate that no correlation exists between vp with rCBV in glioblastomas, meningiomas and intraparenchymal metastatic lesions. Consequently, these parameters, as calculated in this study, should not be used interchangeably in either research or clinical practice.

Leakage decrease detected by dynamic susceptibility-weighted contrast-enhanced perfusion MRI predicts survival in recurrent glioblastoma treated with bevacizumab

BACKGROUND AND PURPOSE

In glioblastoma, tumor progression appears to be triggered by expression of VEGF, a regulator of blood vessel permeability. Bevacizumab is a monoclonal antibody that inhibits angiogenesis by clearing circulating VEGF, resulting in a decline in the contrast-enhancing tumor, which does not always correlate with treatment response. Our objectives were: (1) to evaluate whether changes in DSC perfusion MRI-derived leakage could predict survival in recurrent glioblastoma, and (2) to estimate whether leakage at baseline was related to treatment outcome.

MATERIALS AND METHODS

We retrospectively analyzed DSC perfusion MRI in 24 recurrent glioblastomas treated with bevacizumab as second line chemotherapy. Leakage at baseline and changes in maximum leakage between baseline and the first follow-up after treatment were selected for quantitative analysis. Survival univariate analysis was made constructing survival curves using Kaplan-Meier method and comparing subgroups by log rank probability test.

RESULTS

Leakage reduction at 8 weeks after initiation of bevacizumab treatment had a significant influence on overall survival (OS) and progression-free survival (PFS). Median OS and PFS were 2.4 and 2.8 months longer for patients with leakage reduction at the first follow-up. Higher leakage at baseline was associated with leakage reduction after treatment. Odds ratio of treatment response was 9 for patients with maximum leakage at baseline >5.

CONCLUSIONS

Leakage decrease may predict OS and PFS in recurrent glioblastomas treated with bevacizumab. Leakage reduction postulates as a potential biomarker for treatment response evaluation. Leakage at baseline seems to predict response to treatment, but was not independently associated with survival.

Dynamic contrast-enhanced and dynamic susceptibility contrast perfusion MR imaging for glioma grading: Preliminary comparison of vessel compartment and permeability parameters using hotspot and histogram analysis

INTRODUCTION

Dynamic susceptibility contrast (DSC)-MRI is a perfusion technique with high diagnostic accuracy for glioma grading, despite limitations due to inherent susceptibility effects. Dynamic contrast-enhanced (DCE)-MRI has been proposed as an alternative technique able to overcome the DSC-MRI shortcomings. This pilot study aimed at comparing the diagnostic accuracy of DSC and DCE-MRI for glioma grading by evaluating two estimates of blood volume, the DCE-derived plasma volume (Vp) and the DSC-derived relative cerebral blood volume (rCBV), and a measure of vessel permeability, the DCE-derived volume transfer constant K(trans).

METHODS

Twenty-six newly diagnosed glioma patients underwent 3T-MR DCE and DSC imaging. Parametric maps of CBV, Vp and K(trans) were calculated and the region of highest value (hotspot) was measured on each map. Histograms of rCBV, Vp and K(trans) values were calculated for the tumor volume. Statistical differences according to WHO grade were assessed. The diagnostic accuracy for tumor grading of the two techniques was determined by ROC analysis.

RESULTS

rCBV, Vp and K(trans) measures differed significantly between high and low-grade gliomas. Hotspot analysis showed the highest correlation with grading. K(trans) hotspots co-localized with Vp hotspots only in 56% of enhancing gliomas. For differentiating high from low-grade gliomas the AUC was 0.987 for rCBVmax, and 1.000 for Vpmax and K(trans)max. Combination of DCE-derived Vp and K(trans) parameters improved the diagnostic performance of the histogram method.

CONCLUSION

This initial experience of DCE-derived Vp evaluation shows that this parameter is as accurate as the well-established DSC-derived rCBV for glioma grading. DCE-derived K(trans) is equally useful for grading, providing different informations with respect to Vp.

Imaging of the Posttherapeutic Brain

This review covers important topics relating to the imaging evaluation of glioblastoma multiforme after therapy. An overview of the Macdonald and Response Assessment in Neuro-Oncology criteria as well as important questions and limitations regarding their use are provided. Pseudoprogression and pseudoresponse as well as the use of advanced magnetic resonance imaging techniques such as perfusion, diffusion, and spectroscopy in the evaluation of the posttherapeutic brain are also reviewed.

Imaging of oligodendroglioma

Oligodendroglioma are glial tumours, predominantly occurring in adults. Their hallmark molecular feature is codeletion of the 1p and 19q chromosome arms, which is not only of diagnostic but also of prognostic and predictive relevance. On imaging, these tumours characteristically show calcification, and they have a cortical–subcortical location, most commonly in the frontal lobe. Owing to their superficial location, there may be focal thinning or remodelling of the overlying skull. In contrast to other low-grade gliomas, minimal to moderate enhancement is commonly seen and perfusion may be moderately increased. This complicates differentiation from high-grade, anaplastic oligodendroglioma, in which enhancement and increased perfusion are also common. New enhancement in a previously non-enhancing, untreated tumour, however, is suggestive of malignant transformation, as is high growth rate. MR spectroscopy may further aid in the differentiation between low- and high-grade oligodendroglioma. A relatively common feature of recurrent disease is leptomeningeal dissemination, but extraneural spread is rare. Tumours with the 1p/19q codeletion more commonly show heterogeneous signal intensity, particularly on T₂ weighted imaging; calcifications; an indistinct margin; and mildly increased perfusion and metabolism than 1p/19q intact tumours. For the initial diagnosis of oligodendroglioma, MRI and CT are complementary; MRI is superior to CT in assessing tumour extent and cortical involvement, whereas CT is most sensitive to calcification. Advanced and functional imaging techniques may aid in grading and assessing the molecular genotype as well as in differentiating between tumour recurrence and radiation necrosis, but so far no unequivocal method or combination of methods is available.

Differentiating Tumor Progression from Pseudoprogression in Patients with Glioblastomas Using Diffusion Tensor Imaging and Dynamic Susceptibility Contrast MRI

BACKGROUND AND PURPOSE

Early assessment of treatment response is critical in patients with glioblastomas. A combination of DTI and DSC perfusion imaging parameters was evaluated to distinguish glioblastomas with true progression from mixed response and pseudoprogression.

MATERIALS AND METHODS

Forty-one patients with glioblastomas exhibiting enhancing lesions within 6 months after completion of chemoradiation therapy were retrospectively studied. All patients underwent surgery after MR imaging and were histologically classified as having true progression (>75% tumor), mixed response (25%-75% tumor), or pseudoprogression (<25% tumor). Mean diffusivity, fractional anisotropy, linear anisotropy coefficient, planar anisotropy coefficient, spheric anisotropy coefficient, and maximum relative cerebral blood volume values were measured from the enhancing tissue. A multivariate logistic regression analysis was used to determine the best model for classification of true progression from mixed response or pseudoprogression.

RESULTS

Significantly elevated maximum relative cerebral blood volume, fractional anisotropy, linear anisotropy coefficient, and planar anisotropy coefficient and decreased spheric anisotropy coefficient were observed in true progression compared with pseudoprogression (P < .05). There were also significant differences in maximum relative cerebral blood volume, fractional anisotropy, planar anisotropy coefficient, and spheric anisotropy coefficient measurements between mixed response and true progression groups. The best model to distinguish true progression from non-true progression (pseudoprogression and mixed) consisted of fractional anisotropy, linear anisotropy coefficient, and maximum relative cerebral blood volume, resulting in an area under the curve of 0.905. This model also differentiated true progression from mixed response with an area under the curve of 0.901. A combination of fractional anisotropy and maximum relative cerebral blood volume differentiated pseudoprogression from nonpseudoprogression (true progression and mixed) with an area under the curve of 0.807.

CONCLUSIONS

DTI and DSC perfusion imaging can improve accuracy in assessing treatment response and may aid in individualized treatment of patients with glioblastomas.

Quantitative Evaluation of Diffusion and Dynamic Contrast-Enhanced MR in Tumor Parenchyma and Peritumoral Area for Distinction of Brain Tumors

Purpose

To quantitatively evaluate the diagnostic efficiency of parameters from diffusion and dynamic contrast-enhanced MR which based on tumor parenchyma (TP) and peritumoral (PT) area in classification of brain tumors.

Methods

45 patients (male: 23, female: 22; mean age: 46 y) were prospectively recruited and they underwent conventional, DCE-MR and DWI examination. With each tumor, 10–15 regions of interest (ROIs) were manually placed on TP and PT area. ADC and permeability parameters (K^trans, Ve, Kep and iAUC) were calculated and their diagnostic efficiency was assessed.

Results

In TP, all permeability parameters and ADC value could significantly discriminate Low- from High grade gliomas (HGG) (p<0.001); among theses parameters, Ve demonstrated the highest diagnostic power (iAUC: 0.79, cut-off point: 0.15); the most sensitive and specific index for gliomas grading were K^trans (84%) and Kep (89%). While, in PT area, only K^trans could help in gliomas grading (P = 0.009, cut-off point: 0.03 min^-1). Moreover, in TP, mean Ve and iAUC of primary central nervous system lymphoma (PCNSL) and metastases were significantly higher than that in HGG (p<0.003). Further, in PT area, mean K^trans (p≤0.004) could discriminate PCNSL from HGG and ADC (p≤0.003) could differentiate metastases with HGG.

Conclusions

Quantitative ADC and permeability parameters from Diffusion and DCE-MR in TP and PT area, especially DCE-MR, can aid in gliomas grading and brain tumors discrimination. Their combined application is strongly recommended in the differential diagnosis of these tumor entities.

Novel Magnetic Resonance Imaging Techniques in Brain Tumors

Magnetic resonance imaging is a powerful, noninvasive imaging technique with exquisite sensitivity to soft tissue composition. Magnetic resonance imaging is primary tool for brain tumor diagnosis, evaluation of drug response assessment, and clinical monitoring of the patient during the course of their disease. The flexibility of magnetic resonance imaging pulse sequence design allows for a variety of image contrasts to be acquired, including information about magnetic resonance-specific tissue characteristics, molecular dynamics, microstructural organization, vascular composition, and biochemical status. The current review highlights recent advancements and novel approaches in MR characterization of brain tumors.

Glioma grading by microvascular permeability parameters derived from dynamic contrast-enhanced MRI and intratumoral susceptibility signal on susceptibility weighted imaging

BACKGROUND

Dynamic contrast-enhanced MRI (DCE-MRI) estimates vascular permeability of brain tumors, and susceptibility-weighted imaging (SWI) may demonstrate tumor vascularity by intratumoral susceptibility signals (ITSS). This study assessed volume transfer constant (Ktrans) accuracy, the volume of extravascular extracellular space (EES) per unit volume of tissue (Ve) derived from DCE-MRI, and the degree of ITSS in glioma grading.

METHODS

Thirty-two patients with different glioma grades were enrolled in this retrospective study. Patients underwent DCE-MRI and non-contrast enhanced SWI by three-tesla scanning. Ktrans values, Ve, and the degree of ITSS in glioma were compared. Receiver operating characteristic (ROC) curve analysis determined diagnostic performances of Ktrans and Ve in glioma grading, and Spearman's correlation analysis determined the associations between Ktrans, Ve, ITSS, and tumor grade.

RESULTS

Ktrans and Ve values were significantly different between low grade gliomas (LGGs) and both high grade gliomas (HGGs) and grade II, III and IV gliomas (P<0.01). The degree of ITSS of LGGs was lower than HGGs (P<0.01), and the ITSS of grade II gliomas was lower than grade III or IV gliomas. Ktrans and Ve were correlated with glioma grade (P<0.01), while ITSS was moderately correlated (P<0.01). Ktrans values were moderately correlated with ITSS in the same segments (P<0.01).

CONCLUSION

Ktrans and Ve values, and ITSS helped distinguish the differences between LGGs and HGGs and between grade II, III and IV gliomas. There was a moderate correlation between Ktrans and ITSS in the same tumor segments.

Delayed contrast extravasation MRI: a new paradigm in neuro-oncology

BACKGROUND

Conventional magnetic resonance imaging (MRI) is unable to differentiate tumor/nontumor enhancing tissues. We have applied delayed-contrast MRI for calculating high resolution treatment response assessment maps (TRAMs) clearly differentiating tumor/nontumor tissues in brain tumor patients.

METHODS

One hundred and fifty patients with primary/metastatic tumors were recruited and scanned by delayed-contrast MRI and perfusion MRI. Of those, 47 patients underwent resection during their participation in the study. Region of interest/threshold analysis was performed on the TRAMs and on relative cerebral blood volume maps, and correlation with histology was studied. Relative cerebral blood volume was also assessed by the study neuroradiologist.

RESULTS

Histological validation confirmed that regions of contrast agent clearance in the TRAMs >1 h post contrast injection represent active tumor, while regions of contrast accumulation represent nontumor tissues with 100% sensitivity and 92% positive predictive value to active tumor. Significant correlation was found between tumor burden in the TRAMs and histology in a subgroup of lesions resected en bloc (r(2) = 0.90, P < .0001). Relative cerebral blood volume yielded sensitivity/positive predictive values of 51%/96% and there was no correlation with tumor burden. The feasibility of applying the TRAMs for differentiating progression from treatment effects, depicting tumor within hemorrhages, and detecting residual tumor postsurgery is demonstrated.

CONCLUSIONS

The TRAMs present a novel model-independent approach providing efficient separation between tumor/nontumor tissues by adding a short MRI scan >1 h post contrast injection. The methodology uses robust acquisition sequences, providing high resolution and easy to interpret maps with minimal sensitivity to susceptibility artifacts. The presented results provide histological validation of the TRAMs and demonstrate their potential contribution to the management of brain tumor patients.

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.

Advanced magnetic resonance imaging methods for planning and monitoring radiation therapy in patients with high-grade glioma

This review explores how the integration of advanced imaging methods with high-quality anatomical images significantly improves the characterization, target definition, assessment of response to therapy, and overall management of patients with high-grade glioma. Metrics derived from diffusion-, perfusion-, and susceptibility-weighted magnetic resonance imaging in conjunction with magnetic resonance spectroscopic imaging, allows us to characterize regions of edema, hypoxia, increased cellularity, and necrosis within heterogeneous tumor and surrounding brain tissue. Quantification of such measures may provide a more reliable initial representation of tumor delineation and response to therapy than changes in the contrast-enhancing or T2 lesion alone and have a significant effect on targeting resection, planning radiation, and assessing treatment effectiveness. In the long term, implementation of these imaging methodologies can also aid in the identification of recurrent tumor and its differentiation from treatment-related confounds and facilitate the detection of radiationinduced vascular injury in otherwise normal-appearing brain tissue.

Permeability imaging in pediatric brain tumors

While traditional computed tomography (CT) and magnetic resonance (MR) imaging illustrate the structural morphology of brain pathology, newer, dynamic imaging techniques are able to show the movement of contrast throughout the brain parenchyma and across the blood-brain barrier (BBB). These data, in combination with pharmacokinetic models, can be used to investigate BBB permeability, which has wide-ranging applications in the diagnosis and management of central nervous system (CNS) tumors in children. In the first part of this paper, we review the technical principles underlying four imaging modalities used to evaluate BBB permeability: PET, dynamic CT, dynamic T1-weighted contrast-enhanced MR imaging, and dynamic T2-weighted susceptibility contrast MR. We describe the data that can be derived from each method, provide some caveats to data interpretation, and compare the advantages and disadvantages of the different techniques. In the second part of this paper, we review the clinical applications that have been reported with permeability imaging data, including diagnosing the nature of a lesion found on imaging (neoplastic versus non-neoplastic, tumor type, tumor grade, recurrence versus pseudoprogression), predicting the natural history of a tumor, monitoring angiogenesis and tracking response to anti-angiogenic agents, optimizing chemotherapy agent selection, and aiding in the development of new antineoplastic drugs and methods to increase local delivery of chemotherapeutics.

A prognostic model based on preoperative MRI predicts overall survival in patients with diffuse gliomas

BACKGROUND AND PURPOSE

Diffuse gliomas are classified as grades II-IV on the basis of histologic features, with prognosis determined mainly by clinical factors and histologic grade supported by molecular markers. Our aim was to evaluate, in patients with diffuse gliomas, the relationship of relative CBV and ADC values to overall survival. In addition, we also propose a prognostic model based on preoperative MR imaging findings that predicts survival independent of histopathology.

MATERIALS AND METHODS

We conducted a retrospective analysis of the preoperative diffusion and perfusion MR imaging in 126 histologically confirmed diffuse gliomas. Median relative CBV and ADC values were selected for quantitative analysis. Survival univariate analysis was made by constructing survival curves by using the Kaplan-Meier method and comparing subgroups by log-rank probability tests. A Cox regression model was made for multivariate analysis.

RESULTS

The study included 126 diffuse gliomas (median follow-up of 14.5 months). ADC and relative CBV values had a significant influence on overall survival. Median overall survival for patients with ADC < 0.799 × 10(-3) mm(2)/s was <1 year. Multivariate analysis revealed that patient age, relative CBV, and ADC values were associated with survival independent of pathology. The preoperative model provides greater ability to predict survival than that obtained by histologic grade alone.

CONCLUSIONS

ADC values had a better correlation with overall survival than relative CBV values. A preoperative prognostic model based on patient age, relative CBV, and ADC values predicted overall survival of patients with diffuse gliomas independent of pathology. This preoperative model provides a more accurate predictor of survival than histologic grade alone.