DCE and DSC MR perfusion imaging in the differentiation of recurrent tumour from treatment-related changes in patients with glioma

Beyond conventional imaging: Advancements in MRI for glioma malignancy prediction and molecular profiling

This review examines the advancements in magnetic resonance imaging (MRI) techniques and their pivotal role in diagnosing and managing gliomas, the most prevalent primary brain tumors. The paper underscores the importance of integrating modern MRI modalities, such as diffusion-weighted imaging and perfusion MRI, which are essential for assessing glioma malignancy and predicting tumor behavior. Special attention is given to the 2021 WHO Classification of Tumors of the Central Nervous System, emphasizing the integration of molecular diagnostics in glioma classification, significantly impacting treatment decisions. The review also explores radiogenomics, which correlates imaging features with molecular markers to tailor personalized treatment strategies. Despite technological progress, MRI protocol standardization and result interpretation challenges persist, affecting diagnostic consistency across different settings. Furthermore, the review addresses MRI's capacity to distinguish between tumor recurrence and pseudoprogression, which is vital for patient management. The necessity for greater standardization and collaborative research to harness MRI's full potential in glioma diagnosis and personalized therapy is highlighted, advocating for an enhanced understanding of glioma biology and more effective treatment approaches.

ASL, DSC, DCE perfusion MRI and 18F-DOPA PET/CT in differentiating glioma recurrence from post-treatment changes

OBJECTIVES

To discriminate between post-treatment changes and tumor recurrence in patients affected by glioma undergoing surgery and chemoradiation with a new enhancing lesion is challenging. We aimed to evaluate the role of ASL, DSC, DCE perfusion MRI, and 18F-DOPA PET/CT in distinguishing tumor recurrence from post-treatment changes in patients with glioma.

MATERIALS AND METHODS

We prospectively enrolled patients with treated glioma (surgery plus chemoradiation) and a new enhancing lesion doubtful for recurrence or post-treatment changes. Each patient underwent a 1.5T MRI examination, including ASL, DSC, and DCE PWI, and an 18F-DOPA PET/CT examination. For each lesion, we measured ASL-derived CBF and normalized CBF, DSC-derived rCBV, DCE-derived Ktrans, Vp, Ve, Kep, and PET/CT-derived SUV maximum. Clinical and radiological follow-up determined the diagnosis of tumor recurrence or post-treatment changes.

RESULTS

We evaluated 29 lesions (5 low-grade gliomas and 24 high-grade gliomas); 14 were malignancies, and 15 were post-treatment changes. CBF ASL, nCBF ASL, rCBV DSC, and PET SUVmax were associated with tumor recurrence from post-treatment changes in patients with glioma through an univariable logistic regression. Whereas the multivariable logistic regression results showed only nCBF ASL (p = 0.008) was associated with tumor recurrence from post-treatment changes in patients with glioma with OR = 22.85, CI95%: (2.28-228.77).

CONCLUSION

In our study, ASL was the best technique, among the other two MRI PWI and the 18F-DOPA PET/CT PET, in distinguishing disease recurrence from post-treatment changes in treated glioma.

Simultaneous quantification of perfusion, permeability, and leakage effects in brain gliomas using dynamic spin-and-gradient-echo echoplanar imaging MRI

OBJECTIVE

To determine the feasibility and biologic correlations of dynamic susceptibility contrast (DSC), dynamic contrast enhanced (DCE), and quantitative maps derived from contrast leakage effects obtained simultaneously in gliomas using dynamic spin-and-gradient-echo echoplanar imaging (dynamic SAGE-EPI) during a single contrast injection.

MATERIALS AND METHODS

Thirty-eight patients with enhancing brain gliomas were prospectively imaged with dynamic SAGE-EPI, which was processed to compute traditional DSC metrics (normalized relative cerebral blood flow [nrCBV], percentage of signal recovery [PSR]), DCE metrics (volume transfer constant [Ktrans], extravascular compartment [ve]), and leakage effect metrics: ΔR2,ss* (reflecting T2*-leakage effects), ΔR1,ss (reflecting T1-leakage effects), and the transverse relaxivity at tracer equilibrium (TRATE, reflecting the balance between ΔR2,ss* and ΔR1,ss). These metrics were compared between patient subgroups (treatment-naïve [TN] vs recurrent [R]) and biological features (IDH status, Ki67 expression).

RESULTS

In IDH wild-type gliomas (IDHwt-i.e., glioblastomas), previous exposure to treatment determined lower TRATE (p = 0.002), as well as higher PSR (p = 0.006), Ktrans (p = 0.17), ΔR1,ss (p = 0.035), ve (p = 0.006), and ADC (p = 0.016). In IDH-mutant gliomas (IDHm), previous treatment determined higher Ktrans and ΔR1,ss (p = 0.026). In TN-gliomas, dynamic SAGE-EPI metrics tended to be influenced by IDH status (p ranging 0.09-0.14). TRATE values above 142 mM-1s-1 were exclusively seen in TN-IDHwt, and, in TN-gliomas, this cutoff had 89% sensitivity and 80% specificity as a predictor of Ki67 > 10%.

CONCLUSIONS

Dynamic SAGE-EPI enables simultaneous quantification of brain tumor perfusion and permeability, as well as mapping of novel metrics related to cytoarchitecture (TRATE) and blood-brain barrier disruption (ΔR1,ss), with a single contrast injection.

CLINICAL RELEVANCE STATEMENT

Simultaneous DSC and DCE analysis with dynamic SAGE-EPI reduces scanning time and contrast dose, respectively alleviating concerns about imaging protocol length and gadolinium adverse effects and accumulation, while providing novel leakage effect metrics reflecting blood-brain barrier disruption and tumor tissue cytoarchitecture.

KEY POINTS

• Traditionally, perfusion and permeability imaging for brain tumors requires two separate contrast injections and acquisitions. • Dynamic spin-and-gradient-echo echoplanar imaging enables simultaneous perfusion and permeability imaging. • Dynamic spin-and-gradient-echo echoplanar imaging provides new image contrasts reflecting blood-brain barrier disruption and cytoarchitecture characteristics.

Low rCBV values in glioblastoma tumor progression under chemoradiotherapy

PURPOSE

After standard treatment for glioblastoma, perfusion MRI remains challenging for differentiating tumor progression from post-treatment changes. Our objectives were (1) to correlate rCBV values at diagnosis and at first tumor progression and (2) to analyze the relationship of rCBV values at tumor recurrence with enhancing volume, localization of tumor progression, and time elapsed since the end of radiotherapy in tumor recurrence.

METHODS

Inclusion criteria were (1) age > 18 years, (2) histologically confirmed glioblastoma treated with STUPP regimen, and (3) tumor progression according to RANO criteria > 12 weeks after radiotherapy. Co-registration of segmented enhancing tumor VOIs with dynamic susceptibility contrast perfusion MRI was performed using Olea Sphere software. For tumor recurrence, we correlated rCBV values with enhancing tumor volume, with recurrence localization, and with time elapsed from the end of radiotherapy to progression. Analyses were performed with SPSS software.

RESULTS

Sixty-four patients with glioblastoma were included in the study. Changes in rCBV values between diagnosis and first tumor progression were significant (p < 0.001), with a mean and median decreases of 32% and 46%, respectively. Mean rCBV values were also different (p < 0.01) when tumors progressed distally (radiation field rCBV values of 1.679 versus 3.409 distally). However, changes and, therefore, low rCBV values after radiotherapy in tumor recurrence were independent of time.

CONCLUSION

Chemoradiation alters tumor perfusion and rCBV values may be decreased in the setting of tumor progression. Changes in rCBV values with respect to diagnosis, with low rCBV in tumor progression, are independent of time but related to the site of recurrence.

Standardized brain tumor imaging protocols for clinical trials: current recommendations and tips for integration

Standardized MRI acquisition protocols are crucial for reducing the measurement and interpretation variability associated with response assessment in brain tumor clinical trials. The main challenge is that standardized protocols should ensure high image quality while maximizing the number of institutions meeting the acquisition requirements. In recent years, extensive effort has been made by consensus groups to propose different "ideal" and "minimum requirements" brain tumor imaging protocols (BTIPs) for gliomas, brain metastases (BM), and primary central nervous system lymphomas (PCSNL). In clinical practice, BTIPs for clinical trials can be easily integrated with additional MRI sequences that may be desired for clinical patient management at individual sites. In this review, we summarize the general concepts behind the choice and timing of sequences included in the current recommended BTIPs, we provide a comparative overview, and discuss tips and caveats to integrate additional clinical or research sequences while preserving the recommended BTIPs. Finally, we also reflect on potential future directions for brain tumor imaging in clinical trials.

Head-To-Head Comparison of PET and Perfusion Weighted MRI Techniques to Distinguish Treatment Related Abnormalities from Tumor Progression in Glioma

The post-treatment imaging surveillance of gliomas is challenged by distinguishing tumor progression (TP) from treatment-related abnormalities (TRA). Sophisticated imaging techniques, such as perfusion-weighted magnetic resonance imaging (MRI PWI) and positron-emission tomography (PET) with a variety of radiotracers, have been suggested as being more reliable than standard imaging for distinguishing TP from TRA. However, it remains unclear if any technique holds diagnostic superiority. This meta-analysis provides a head-to-head comparison of the diagnostic accuracy of the aforementioned imaging techniques. Systematic literature searches on the use of PWI and PET imaging techniques were carried out in PubMed, Embase, the Cochrane Library, ClinicalTrials.gov and the reference lists of relevant papers. After the extraction of data on imaging technique specifications and diagnostic accuracy, a meta-analysis was carried out. The quality of the included papers was assessed using the QUADAS-2 checklist. Nineteen articles, totaling 697 treated patients with glioma (431 males; mean age ± standard deviation 50.5 ± 5.1 years) were included. The investigated PWI techniques included dynamic susceptibility contrast (DSC), dynamic contrast enhancement (DCE) and arterial spin labeling (ASL). The PET-tracers studied concerned [S-methyl-¹¹C]methionine, 2-deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]FDG), O-(2-[¹⁸F]fluoroethyl)-L-tyrosine ([¹⁸F]FET) and 6-[¹⁸F]-fluoro-3,4-dihydroxy-L-phenylalanine ([¹⁸F]FDOPA). The meta-analysis of all data showed no diagnostic superior imaging technique. The included literature showed a low risk of bias. As no technique was found to be diagnostically superior, the local level of expertise is hypothesized to be the most important factor for diagnostically accurate results in post-treatment glioma patients regarding the distinction of TRA from TP.

Imaging biomarkers for clinical applications in neuro-oncology: current status and future perspectives

Biomarker discovery and development are popular for detecting the subtle diseases. However, biomarkers are needed to be validated and approved, and even fewer are ever used clinically. Imaging biomarkers have a crucial role in the treatment of cancer patients because they provide objective information on tumor biology, the tumor's habitat, and the tumor's signature in the environment. Tumor changes in response to an intervention complement molecular and genomic translational diagnosis as well as quantitative information. Neuro-oncology has become more prominent in diagnostics and targeted therapies. The classification of tumors has been actively updated, and drug discovery, and delivery in nanoimmunotherapies are advancing in the field of target therapy research. It is important that biomarkers and diagnostic implements be developed and used to assess the prognosis or late effects of long-term survivors. An improved realization of cancer biology has transformed its management with an increasing emphasis on a personalized approach in precision medicine. In the first part, we discuss the biomarker categories in relation to the courses of a disease and specific clinical contexts, including that patients and specimens should both directly reflect the target population and intended use. In the second part, we present the CT perfusion approach that provides quantitative and qualitative data that has been successfully applied to the clinical diagnosis, treatment and application. Furthermore, the novel and promising multiparametric MR imageing approach will provide deeper insights regarding the tumor microenvironment in the immune response. Additionally, we briefly remark new tactics based on MRI and PET for converging on imaging biomarkers combined with applications of bioinformatics in artificial intelligence. In the third part, we briefly address new approaches based on theranostics in precision medicine. These sophisticated techniques merge achievable standardizations into an applicatory apparatus for primarily a diagnostic implementation and tracking radioactive drugs to identify and to deliver therapies in an individualized medicine paradigm. In this article, we describe the critical principles for imaging biomarker characterization and discuss the current status of CT, MRI and PET in finiding imaging biomarkers of early disease.

Model-free dynamic contrast-enhanced MRI analysis: differentiation between active tumor and necrotic tissue in patients with glioblastoma

OBJECTIVE

Treatment response assessment in patients with high-grade gliomas (HGG) is heavily dependent on changes in lesion size on MRI. However, in conventional MRI, treatment-related changes can appear as enhancing tissue, with similar presentation to that of active tumor tissue. We propose a model-free data-driven method for differentiation between these tissues, based on dynamic contrast-enhanced (DCE) MRI.

MATERIALS AND METHODS

The study included a total of 66 scans of patients with glioblastoma. Of these, 48 were acquired from 1 MRI vendor and 18 scans were acquired from a different MRI vendor and used as test data. Of the 48, 24 scans had biopsy results. Analysis included semi-automatic arterial input function (AIF) extraction, direct DCE pharmacokinetic-like feature extraction, and unsupervised clustering of the two tissue types. Validation was performed via (a) comparison to biopsy result (b) correlation to literature-based DCE curves for each tissue type, and (c) comparison to clinical outcome.

RESULTS

Consistency between the model prediction and biopsy results was found in 20/24 cases. An average correlation of 82% for active tumor and 90% for treatment-related changes was found between the predicted component and population-based templates. An agreement between the predicted results and radiologist's assessment, based on RANO criteria, was found in 11/12 cases.

CONCLUSION

The proposed method could serve as a non-invasive method for differentiation between lesion tissue and treatment-related changes.

Opportunities for improving brain cancer treatment outcomes through imaging-based mathematical modeling of the delivery of radiotherapy and immunotherapy

Immunotherapy has become a fourth pillar in the treatment of brain tumors and, when combined with radiation therapy, may improve patient outcomes and reduce the neurotoxicity. As with other combination therapies, the identification of a treatment schedule that maximizes the synergistic effect of radiation- and immune-therapy is a fundamental challenge. Mechanism-based mathematical modeling is one promising approach to systematically investigate therapeutic combinations to maximize positive outcomes within a rigorous framework. However, successful clinical translation of model-generated combinations of treatment requires patient-specific data to allow the models to be meaningfully initialized and parameterized. Quantitative imaging techniques have emerged as a promising source of high quality, spatially and temporally resolved data for the development and validation of mathematical models. In this review, we will present approaches to personalize mechanism-based modeling frameworks with patient data, and then discuss how these techniques could be leveraged to improve brain cancer outcomes through patient-specific modeling and optimization of treatment strategies.

Volumetric Measurement of Relative CBV Using T1-Perfusion-Weighted MRI with High Temporal Resolution Compared with Traditional T2*-Perfusion-Weighted MRI in Postoperative Patients with High-Grade Gliomas

BACKGROUND AND PURPOSE

T1-PWI with high temporal resolution may provide a reliable relative CBV value as a valid alternative to T2*-PWI under increased susceptibility. The purpose of this study was to assess the technical and clinical performance of T1-relative CBV in patients with postoperative high-grade gliomas.

MATERIALS AND METHODS

Forty-five MRIs of 34 patients with proved high-grade gliomas were included. In all MRIs, T1- and T2*-PWIs were both acquired and processed semiautomatically to generate relative CBV maps using a released commercial software. Lesion masks were overlaid on the relative CBV maps, followed by a histogram of the whole VOI. The intraclass correlation coefficient and Bland-Altman plots were used for quantitative and qualitative comparisons. Signal loss from both methods was compared using the Wilcoxon signed-rank test of zero voxel percentage. The MRIs were divided into a progression group (n = 20) and a nonprogression group (n = 14) for receiver operating characteristic curve analysis.

RESULTS

Fair intertechnique consistency was observed between the 90th percentiles of the T1- and T2*-relative CBV values (intraclass correlation coefficient = 0.558, P < .001). T2*-PWI revealed a significantly higher percentage of near-zero voxels than T1-PWI (17.7% versus 3.1%, P < .001). There was no statistically significant difference between the area under the curve of T1- and T2*-relative CBV (0.811 versus 0.793, P = .835). T1-relative CBV showed 100% sensitivity and 57.1% specificity for the detection of progressive lesions.

CONCLUSIONS

T1-relative CBV demonstrated exquisite diagnostic performance for detecting progressive lesions in postoperative patients with high-grade gliomas, suggesting the potential role of T1-PWI as a valid alternative to the traditional T2*-PWI.

Hemodynamic Imaging in Cerebral Diffuse Glioma-Part A: Concept, Differential Diagnosis and Tumor Grading

Diffuse gliomas are the most common primary malignant intracranial neoplasms. Aside from the challenges pertaining to their treatment-glioblastomas, in particular, have a dismal prognosis and are currently incurable-their pre-operative assessment using standard neuroimaging has several drawbacks, including broad differentials diagnosis, imprecise characterization of tumor subtype and definition of its infiltration in the surrounding brain parenchyma for accurate resection planning. As the pathophysiological alterations of tumor tissue are tightly linked to an aberrant vascularization, advanced hemodynamic imaging, in addition to other innovative approaches, has attracted considerable interest as a means to improve diffuse glioma characterization. In the present part A of our two-review series, the fundamental concepts, techniques and parameters of hemodynamic imaging are discussed in conjunction with their potential role in the differential diagnosis and grading of diffuse gliomas. In particular, recent evidence on dynamic susceptibility contrast, dynamic contrast-enhanced and arterial spin labeling magnetic resonance imaging are reviewed together with perfusion-computed tomography. While these techniques have provided encouraging results in terms of their sensitivity and specificity, the limitations deriving from a lack of standardized acquisition and processing have prevented their widespread clinical adoption, with current efforts aimed at overcoming the existing barriers.

Hemodynamic Imaging in Cerebral Diffuse Glioma-Part B: Molecular Correlates, Treatment Effect Monitoring, Prognosis, and Future Directions

Gliomas, and glioblastoma in particular, exhibit an extensive intra- and inter-tumoral molecular heterogeneity which represents complex biological features correlating to the efficacy of treatment response and survival. From a neuroimaging point of view, these specific molecular and histopathological features may be used to yield imaging biomarkers as surrogates for distinct tumor genotypes and phenotypes. The development of comprehensive glioma imaging markers has potential for improved glioma characterization that would assist in the clinical work-up of preoperative treatment planning and treatment effect monitoring. In particular, the differentiation of tumor recurrence or true progression from pseudoprogression, pseudoresponse, and radiation-induced necrosis can still not reliably be made through standard neuroimaging only. Given the abundant vascular and hemodynamic alterations present in diffuse glioma, advanced hemodynamic imaging approaches constitute an attractive area of clinical imaging development. In this context, the inclusion of objective measurable glioma imaging features may have the potential to enhance the individualized care of diffuse glioma patients, better informing of standard-of-care treatment efficacy and of novel therapies, such as the immunotherapies that are currently increasingly investigated. In Part B of this two-review series, we assess the available evidence pertaining to hemodynamic imaging for molecular feature prediction, in particular focusing on isocitrate dehydrogenase (IDH) mutation status, MGMT promoter methylation, 1p19q codeletion, and EGFR alterations. The results for the differentiation of tumor progression/recurrence from treatment effects have also been the focus of active research and are presented together with the prognostic correlations identified by advanced hemodynamic imaging studies. Finally, the state-of-the-art concepts and advancements of hemodynamic imaging modalities are reviewed together with the advantages derived from the implementation of radiomics and machine learning analyses pipelines.

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques

Objective

Summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments.

Methods

Experts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics).

Results

High-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies.

Conclusion

Considerable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.

Diagnostic performance of DSC perfusion MRI to distinguish tumor progression and treatment-related changes: a systematic review and meta-analysis

Background

In patients with high-grade glioma (HGG), true disease progression and treatment-related changes often appear similar on magnetic resonance imaging (MRI), making it challenging to evaluate therapeutic response. Dynamic susceptibility contrast (DSC) MRI has been extensively studied to differentiate between disease progression and treatment-related changes. This systematic review evaluated and synthesized the evidence for using DSC MRI to distinguish true progression from treatment-related changes.

Methods

We searched Ovid MEDLINE and the Ovid MEDLINE in-process file (January 2005-October 2019) and the reference lists. Studies on test performance of DSC MRI using relative cerebral blood volume in HGG patients were included. One investigator abstracted data, and a second investigator confirmed them; two investigators independently assessed study quality. Meta-analyses were conducted to quantitatively synthesize area under the receiver operating curve (AUROC), sensitivity, and specificity.

Results

We screened 1177 citations and included 28 studies with 638 patients with true tumor progression, and 430 patients with treatment-related changes. Nineteen studies reported AUROC and the combined AUROC is 0.85 (95% CI, 0.81-0.90). All studies contributed data for sensitivity and specificity, and the pooled sensitivity and specificity are 0.84 (95% CI, 0.80-0.88), and 0.78 (95% CI, 0.72-0.83). Extensive subgroup analyses based on study, treatment, and imaging characteristics generally showed similar results.

Conclusions

There is moderate strength of evidence that relative cerebral blood volume obtained from DSC imaging demonstrated "excellent" ability to discriminate true tumor progression from treatment-related changes, with robust sensitivity and specificity.

Transformational Role of Medical Imaging in (Radiation) Oncology

Simple Summary

Onboard, imaging techniques have brought about a huge transformation in the ability to deliver targeted radiation therapies. Each generation of these technologies enables us to better visualize where to deliver lethal doses of radiation and thus allows the shrinking of necessary geometric margins leading to reduced toxicities. Alongside improvements in treatment delivery, advances in medical imaging have also allowed us to better define the volumes we wish to target. The development of imaging techniques that can capture aspects of the tumor’s biology before, during and after therapy is transforming how treatment can be delivered. Technological changes have further made these biological imaging techniques available in real-time providing the opportunity to monitor a patient’s response to treatment closely and often before any volume changes are visible on conventional radiological images. Here we discuss the development of robust quantitative imaging biomarkers and how they can personalize therapy towards meaningful clinical endpoints.

Abstract

Onboard, real-time, imaging techniques, from the original megavoltage planar imaging devices, to the emerging combined MRI-Linear Accelerators, have brought a huge transformation in the ability to deliver targeted radiation therapies. Each generation of these technologies enables lethal doses of radiation to be delivered to target volumes with progressively more accuracy and thus allows shrinking of necessary geometric margins, leading to reduced toxicities. Alongside these improvements in treatment delivery, advances in medical imaging, e.g., PET, and MRI, have also allowed target volumes themselves to be better defined. The development of functional and molecular imaging is now driving a conceptually larger step transformation to both better understand the cancer target and disease to be treated, as well as how tumors respond to treatment. A biological description of the tumor microenvironment is now accepted as an essential component of how to personalize and adapt treatment. This applies not only to radiation oncology but extends widely in cancer management from surgical oncology planning and interventional radiology, to evaluation of targeted drug delivery efficacy in medical oncology/immunotherapy. Here, we will discuss the role and requirements of functional and metabolic imaging techniques in the context of brain tumors and metastases to reliably provide multi-parametric imaging biomarkers of the tumor microenvironment.

Pseudoprogression versus true progression in glioblastoma patients: A multiapproach literature review. Part 2 - Radiological features and metric markers

After chemoradiotherapy for glioblastoma, pseudoprogression can occur and must be distinguished from true progression to correctly manage glioblastoma treatment and follow-up. Conventional treatment response assessment is evaluated via conventional MRI (contrast-enhanced T1-weighted and T2/FLAIR), which is unreliable. The emergence of advanced MRI techniques, MR spectroscopy, and PET tracers has improved pseudoprogression diagnostic accuracy. This review presents a literature review of the different imaging techniques and potential imaging biomarkers to differentiate pseudoprogression from true progression.

Differentiation of recurrent diffuse glioma from treatment-induced change using amide proton transfer imaging: incremental value to diffusion and perfusion parameters

PURPOSE

To evaluate the incremental value of amide proton transfer (APT) imaging to diffusion tensor imaging (DTI), dynamic susceptibility contrast (DSC) imaging, and dynamic contrast-enhanced (DCE) imaging in differentiating recurrent diffuse gliomas (World Health Organization grade II-IV) from treatment-induced change after concurrent chemoradiotherapy or radiotherapy.

METHODS

This study included 36 patients (25 patients with recurrent gliomas and 11 with treatment-induced changes) with post-treatment gliomas. The mean values of apparent diffusion coefficient (ADC), fractional anisotropy (FA), normalized cerebral blood volume (nCBV), normalized cerebral blood flow, volume transfer constant, rate transfer coefficient, extravascular extracellular volume fraction, plasma volume fraction, and APT asymmetry index were assessed. Independent quantitative parameters were investigated to predict recurrent glioma using multivariable logistic regression. The incremental value of APT signal to other parameters was assessed by the increase of the area under the curve, net reclassification index, and integrated discrimination improvement.

RESULTS

Univariable analysis showed that lower ADC (p = 0.018), higher FA (p = 0.031), higher nCBV (p = 0.021), and higher APT signal (p = 0.009) were associated with recurrent gliomas. In multivariable logistic regression, the diagnostic performance of the model with ADC, FA, and nCBV significantly increased when APT signal was added, with areas under the curve of 0.87 and 0.92, respectively (net reclassification index of 0.77 and integrated discrimination improvement of 0.13).

CONCLUSION

APT imaging may be a useful imaging biomarker that adds value to DTI, DCE, and DSC parameters for distinguishing between recurrent gliomas and treatment-induced changes.

Diagnostic Performance of PET and Perfusion-Weighted Imaging in Differentiating Tumor Recurrence or Progression from Radiation Necrosis in Posttreatment Gliomas: A Review of Literature

Tumor resection followed by chemoradiation remains the current criterion standard treatment for high-grade gliomas. Regardless of aggressive treatment, tumor recurrence and radiation necrosis are 2 different outcomes. Differentiation of tumor recurrence from radiation necrosis remains a critical problem in these patients because of considerable overlap in clinical and imaging presentations. Contrast-enhanced MR imaging is the universal imaging technique for diagnosis, treatment evaluation, and detection of recurrence of high-grade gliomas. PWI and PET with novel radiotracers have an evolving role for monitoring treatment response in high-grade gliomas. In the literature, there is no clear consensus on the superiority of either technique or their complementary information. This review aims to elucidate the diagnostic performance of individual and combined use of functional (PWI) and metabolic (PET) imaging modalities to distinguish recurrence from posttreatment changes in gliomas.

Role of Radiological Intervention in Brain Tumor: A Meta-Analysis

Background

This meta-analysis highlights the diagnostic efficacy of computed tomography (CT), computed tomography angiography (CTA), magnetic resonance image (MRI), as well as magnetic resonance spectroscopy (MRS). This paper assesses the detection of the primary outcome comprising choline/creatine ratio, relative cerebral blood volume (rCBV), as well as choline/N-acetyl aspartate. Cochrane, Medline, ScienceDirect, Google Scholar, and EMBASE databases were searched for extracting the relevant studies.

Methods

A sample of 12 studies on radiologic assessment of brain tumors was selected.

Results

The evidence provides that the heterogeneity exists concerning the CBV of 311.623, I2 = 96.12%, with a significance value of P &lt; 0.001. The pooled difference showed rCBV mean (as 2.18, 95% confidence interval = 0.85 to 3.50) substantially enhances lesion.

Conclusion

The study concluded that radiological interventions, particularly the combination of MRS and MRI, help in the brain patient's precise diagnosis and treatment.

Clinical Imaging for Diagnostic Challenges in the Management of Gliomas: A Review

Neuroimaging plays a critical role in the management of patients with gliomas. While conventional magnetic resonance imaging (MRI) remains the standard imaging modality, it is frequently insufficient to inform clinical decision-making. There is a need for noninvasive strategies for reliably distinguishing low-grade from high-grade gliomas, identifying important molecular features of glioma, choosing an appropriate target for biopsy, delineating target area for surgery or radiosurgery, and distinguishing tumor progression (TP) from pseudoprogression (PsP). One recent advance is the identification of the T2/fluid-attenuated inversion recovery mismatch sign on standard MRI to identify isocitrate dehydrogenase mutant astrocytomas. However, to meet other challenges, neuro-oncologists are increasingly turning to advanced imaging modalities. Diffusion-weighted imaging modalities including diffusion tensor imaging and diffusion kurtosis imaging can be helpful in delineating tumor margins and better visualization of tissue architecture. Perfusion imaging including dynamic contrast-enhanced MRI using gadolinium or ferumoxytol contrast agents can be helpful for grading as well as distinguishing TP from PsP. Positron emission tomography is useful for measuring tumor metabolism, which correlates with grade and can distinguish TP/PsP in the right setting. Magnetic resonance spectroscopy can identify tissue by its chemical composition, can distinguish TP/PsP, and can identify molecular features like 2-hydroxyglutarate. Finally, amide proton transfer imaging measures intracellular protein content, which can be used to identify tumor grade/progression and distinguish TP/PsP.

Diagnostic accuracy of dynamic contrast-enhanced perfusion MRI in stratifying gliomas: A systematic review and meta-analysis

Background

T1‐weighted dynamic contrast‐enhanced (DCE) perfusion magnetic resonance imaging (MRI) has been broadly utilized in the evaluation of brain tumors. We aimed at assessing the diagnostic accuracy of DCE‐MRI in discriminating between low‐grade gliomas (LGGs) and high‐grade gliomas (HGGs), between tumor recurrence and treatment‐related changes, and between primary central nervous system lymphomas (PCNSLs) and HGGs.

Methods

We performed this study based on the Preferred Reporting Items for Systematic Reviews and Meta‐Analysis of Diagnostic Test Accuracy Studies criteria. We systematically surveyed studies evaluating the diagnostic accuracy of DCE‐MRI for the aforementioned entities. Meta‐analysis was conducted with the use of a random effects model.

Results

Twenty‐seven studies were included after screening of 2945 possible entries. We categorized the eligible studies into three groups: those utilizing DCE‐MRI to differentiate between HGGs and LGGs (14 studies, 546 patients), between recurrence and treatment‐related changes (9 studies, 298 patients) and between PCNSLs and HGGs (5 studies, 224 patients). The pooled sensitivity, specificity, and area under the curve for differentiating HGGs from LGGs were 0.93, 0.90, and 0.96, for differentiating tumor relapse from treatment‐related changes were 0.88, 0.86, and 0.89, and for differentiating PCNSLs from HGGs were 0.78, 0.81, and 0.86, respectively.

Conclusions

Dynamic contrast‐enhanced‐Magnetic resonance imaging is a promising noninvasive imaging method that has moderate or high accuracy in stratifying gliomas. DCE‐MRI shows high diagnostic accuracy in discriminating between HGGs and their low‐grade counterparts, and moderate diagnostic accuracy in discriminating recurrent lesions and treatment‐related changes as well as PCNSLs and HGGs.

Using Magnetic Resonance Perfusion to Stratify Overall Survival in Treated High-Grade Gliomas

BACKGROUND

MR perfusion imaging is a relatively new technique that may aid in identifying recurrent tumor (RT) in those with radically treated high-grade gliomas (HGG). We aim to assess the relationship between dynamic susceptibility contrast-enhanced MR perfusion (DSC-MRP) and overall survival to establish a baseline for future research and to determine the utility of DSC-MRP as a clinical decision-making and prognostic tool.

METHODS

We conducted a retrospective cohort study. Adults with pathologically confirmed HGG at the Juravinski Cancer Centre, Ontario between January 2011 and April 2014 with at least one post-treatment DSC-MRP were included. DSC-MRP was interpreted as positive or negative for tumor recurrence by experienced radiologists. The primary outcome was overall survival.

RESULTS

Sixty-one patients were enrolled. Median survival for patients with a positive DSC-MRP scan was 4.5 months compared with 10.2 months for those with a negative DSC-MRP scan (hazard ratio [unadjusted] = 2.51; 95% confidence interval = 1.10-5.67; p-value = 0.03). Multivariable modeling (adjusted) that included all pre-selected variables showed similar results.

CONCLUSION

Survival time in patients with HGG is generally low, and almost all patients will demonstrate RT. Our data suggest a positive DSC-MRP correlates with lower overall survival and may signify the presence of highly active RT. These results generate a hypothesis that there may be a prognostic role for the use of serial DSC-MRP for tumor surveillance. More importantly, this biomarker may aid in decision making for treatment plans and palliation.

DCE and DSC perfusion MRI diagnostic accuracy in the follow-up of primary and metastatic intra-axial brain tumors treated by radiosurgery with cyberknife

Background

The differential diagnosis between radiation necrosis, tumor recurrence and tumor progression is crucial for the evaluation of treatment response and treatment planning.

The appearance of treatment-induced tissue necrosis on conventional Magnetic Resonance Imaging (MRI) is similar to brain tumor recurrence and it could be difficult to differentiate the two entities on follow-up MRI examinations.

Dynamic Susceptibility Contrast-enhanced (DSC) and Dynamic Contrast-Enhanced (DCE) are MRI perfusion techniques that use an exogenous, intravascular, non-diffusible gadolinium-based contrast agent.

The aim of this study was to compare the diagnostic accuracy of DSC and DCE perfusion MRI in the differential diagnosis between radiation necrosis and tumor recurrence, in the follow-up of primary and metastatic intra-axial brain tumors after Stereotactic RadioSurgery (SRS) performed with CyberKnife.

Methods

A total of 72 enhancing lesions (57 brain metastases and 15 primary brain tumors) were analyzed with DCE and DSC, by means of MRI acquisition performed by 1,5 Tesla MR scanner. The statistical relationship between the diagnosis of tumor recurrence or radiation necrosis, decided according to clinicoradiologically criteria, rCBV and Ktrans was evaluated by the point-biserial correlation coefficient respectively.

Results

The statistical analysis showed a correlation between the diagnosis of radiation necrosis or recurrent tumor with Ktrans (rpb = 0.54, p < 0.001) and with rCBV (rpb = 0.37, p = 0.002).

The ROC analysis of rCBV values demonstrated a good classification ability in differentiating radiation necrosis from tumour recurrence as well as the Ktrans. The optimal cut-off value for rCBV was k = 1.23 with 0.88 of sensitivity and 0.75 of specificity while for Ktrans was k = 28.76 with 0.89 of sensitivity and 0.97 of specificity.

Conclusions

MRI perfusion techniques, particularly DCE, help in the differential diagnosis by tumor recurrence and radiation necrosis during the follow-up after radiosurgery.

Prospective comparative diagnostic accuracy evaluation of dynamic contrast-enhanced (DCE) vs. dynamic susceptibility contrast (DSC) MR perfusion in differentiating tumor recurrence from radiation necrosis in treated high-grade gliomas

BACKGROUND

The appearance of a new enhancing lesion after surgery and chemoradiation for high-grade glioma (HGG) presents a common diagnostic dilemma. Histopathological analysis remains the reference standard in this situation.

PURPOSE

To prospectively compare the diagnostic accuracy of dynamic contrast-enhanced (DCE) vs. dynamic susceptibility contrast (DSC) in differentiating tumor recurrence (TR) from radiation necrosis (RN).

STUDY TYPE

Prospective diagnostic accuracy study.

POPULATION

In all, 98 consecutive treated HGG patients with new enhancing lesion. We excluded 32 patients due to inadequate follow-up or technical limitation.

FIELD STRENGTH/SEQUENCE

3 T DCE and DSC MR.

ASSESSMENT

Histogram and hot-spot analysis of cerebral blood volume (CBV), corrected CBV, K^trans , area under the curve (AUC), and plasma volume (Vp). The reference standard of TR and/or RN was determined by histopathology in 43 surgically resected lesions or by clinical/imaging follow-up in the rest.

STATISTICAL TESTS

Mann-Whitney U-tests, receiver operating characteristic (ROC) curve, and logistic regression analysis.

RESULTS

A total of 68 lesions were included. There were 37 TR, 28 RN, and three lesions with equal proportions of TR and RN. TR had significantly higher CBV, corrected CBV, CBV ratio, corrected CBV ratio, AUC ratio, and Vp ratio (P < 0.05) than RN on hot-spot analysis. CBV had the highest diagnostic accuracy (AUROC 0.71). On histogram analysis, TR had higher CBV and corrected CBV maximal value compared with RN (P = 0.006, AUROC = 0.70). Only CBV on hot-spot analysis remained significant after correction for multiple comparison, with no significant improvement in diagnostic accuracy when using a combination of parameters (AUROC 0.71 vs. 0.76, P = 0.24).

DATA CONCLUSION

DSC-derived CBV is the most accurate perfusion parameter in differentiating TR and RN. DSC and DCE-derived parameters reflecting the blood volume in an enhancing lesion are more accurate than the DCE-derived parameter K^trans . Clinical practice may be best guided by blood volume measurements, rather than permeability assessment for differentiation of TR from RN.

LEVEL OF EVIDENCE

1 Technical Efficacy Stage: 4 J. Magn. Reson. Imaging 2019;50:573-582.

Current concepts and challenges in the radiologic assessment of brain tumors in children: part 2

Assessing tumor response is a large part of everyday clinical work in neuroradiology. However in the setting of tumor treatment, distinguishing tumor progression from treatment-related changes is difficult on conventional MRI sequences. This is made even more challenging in children where mainstay advanced imaging techniques that are often used to decipher progression versus treatment-related changes have technical limitations. In this review, we highlight the challenges in pediatric neuro-oncologic tumor assessment with discussion of pseudophenomenon including pseudoresponse and pseudoprogression. Additionally, we discuss the advanced imaging techniques often employed in neuroradiology to distinguish between pseudophenomenon and true progressive disease.

The Use of Quantitative Imaging in Radiation Oncology: A Quantitative Imaging Network (QIN) Perspective

Modern radiation therapy is delivered with great precision, in part by relying on high-resolution multidimensional anatomic imaging to define targets in space and time. The development of quantitative imaging (QI) modalities capable of monitoring biologic parameters could provide deeper insight into tumor biology and facilitate more personalized clinical decision-making. The Quantitative Imaging Network (QIN) was established by the National Cancer Institute to advance and validate these QI modalities in the context of oncology clinical trials. In particular, the QIN has significant interest in the application of QI to widen the therapeutic window of radiation therapy. QI modalities have great promise in radiation oncology and will help address significant clinical needs, including finer prognostication, more specific target delineation, reduction of normal tissue toxicity, identification of radioresistant disease, and clearer interpretation of treatment response. Patient-specific QI is being incorporated into radiation treatment design in ways such as dose escalation and adaptive replanning, with the intent of improving outcomes while lessening treatment morbidities. This review discusses the current vision of the QIN, current areas of investigation, and how the QIN hopes to enhance the integration of QI into the practice of radiation oncology.

Glioma response assessment: Classic pitfalls, novel confounders, and emerging imaging tools

Neuroimaging plays a pivotal role in the care of patients with infiltrating gliomas, in whom imaging changes are often the first indications of tumor response or progression. Unfortunately, evaluation of glioma response is often not straightforward, even for experienced radiologists. Post-surgical or radiation-related changes may mimic the appearance of disease progression, while medications such as corticosteroids and antiangiogenic agents may mimic tumor response without truly arresting tumor growth or improving patient survival. Immunotherapy response can result in inflammatory changes which manifest as progressively increasing tumor enhancement and edema over months. Many of these pitfalls can be minimized or avoided altogether by the use of modern brain tumor response criteria, while others will require new imaging tools before they can be fully addressed. Advanced MRI methods and novel positron emission tomography (PET) agents are proving important for this purpose, and their role will undoubtedly continue to grow in the future.

Differentiation between glioblastomas and brain metastases and regarding their primary site of malignancy using dynamic susceptibility contrast MRI at 3T

BACKGROUND

Differentiation between glioblastoma and brain metastasis may be challenging in conventional contrast-enhanced MRI.

PURPOSE

To investigate if perfusion-weighted MRI is able to differentiate glioblastoma from metastasis and, as a second aim was to see if it was possible in the latter group, to predict the primary site of neoplasm.

MATERIAL AND METHODS

Hundred and fourteen patients with newly discovered tumor lesion (76 metastases and 38 glioblastomas) underwent conventional contrast-enhanced MRI including dynamic susceptibility contrast perfusion sequence. The calculated relative cerebral blood volumes were analyzed in the solid tumor area, peritumoral area, area adjacent to peritumoral area, and normal appearing white matter in contralateral semioval center. The Student t-test was used to detect statistically significant differences in relative cerebral blood volume between glioblastomas and metastases in the aforementioned areas. Furthermore, the metastasis group was divided in four sub groups (lung-, breast-, melanoma-, and gastrointestinal origin) and using one-way ANOVA test. P-values < 0.05 were considered significant.

RESULTS

Relative cerebral blood volume (rCBV) in the peritumoral edema was significantly higher in glioblastomas than in metastases (mean 3.2 ± 1.4 and mean 0.9 ± 0.7), respectively, (P < 0.0001). No significant differences in the solid tumor area or the area adjacent to edema were found, (P = 0.28 and 0.21 respectively). There were no significant differences among metastases in the four groups.

CONCLUSION

It is possible to differentiate glioblastomas from metastases by measuring the CBV in the peritumoral edema. It is not possible to differentiate between brain metastases from different primaries (lung-, breast-, melanoma or gastrointestinal) using CBV-measurements in the solid tumor area, peritumoral edema or area adjacent to edema.

Assessment of the Agreement between Cerebral Hemodynamic Indices Quantified Using Dynamic Susceptibility Contrast and Dynamic Contrast-enhanced Perfusion Magnetic Resonance Imagings

Background:

Brain tumor is one of the most common tumors. A successful treatment might be achieved with an early identification. Pathological investigation as the gold standard method for tumor identification has some limitations. Noninvasive assessment of tumor specifications may be possible using perfusion-weighted magnetic resonance imaging (MRI). Cerebral blood volume (CBV) and cerebral blood flow (CBF) could be calculated based on dynamic contrast-enhanced MRI (DCE-MRI) in addition to dynamic susceptibility contrast MRI (DSC-MRI) modality. Each category of the cerebral hemodynamic and permeability indices revealed the specific tumor characteristics and their collection could help for better identification of the tumor. Some mathematical methods were developed to determine both cerebral hemodynamic and permeability indices based on a single-dose DCE perfusion MRI. There are only a few studies available on the comparison of DSC- and DCE-derived cerebral hemodynamic indices such as CBF and CBV.

Aim:

The objective of the study was to validate first-pass perfusion parameters derived from T1-based DCE method in comparison to the routine T2*-based DSC protocol.

Materials and Methods:

Twenty-nine patients with brain tumor underwent DCE- and DSC-MRIs to evaluate the agreement between DSC- and DCE-derived cerebral hemodynamic parameters. Agreement between DSC- and DCE-derived cerebral hemodynamic indices was determined using the statistical method described by Bland and Altman. The reliability between DSC- and DCE-derived cerebral hemodynamic indices was measured using the intraclass correlation analysis.

Results:

The achieved magnitudes for DCE-derived CBV (gray matter [GM]: 5.01 ± 1.40 mL/100 g vs. white matter [WM]: 1.84 ± 0.74 mL/100 g) and DCE-derived CBF (GM: 60.53 ± 12.70 mL/100 g/min vs. WM: 32.00 ± 6.00 mL/100 g/min) were in good agreement with other studies. The intraclass correlation coefficients showed that the cerebral hemodynamic indices could accurately be estimated based on the DCE-MRI using a single-compartment model (>0.87), and DCE-derived cerebral hemodynamic indices are significantly similar to the magnitudes achieved based on the DSC-MRI (P < 0.001). Furthermore, an acceptable agreement was observed between DSC- and DCE-derived cerebral hemodynamic indices.

Conclusion:

Based on the measurement of the cerebral hemodynamic and blood–brain barrier permeability using DCE-MRI, a more comprehensive collection of the physiological parameters cloud be achieved for tumor evaluations.

Optimized inversion-time schedules for quantitative T1 measurements based on high-resolution multi-inversion EPI

PURPOSE

Demonstrate an optimized multi-inversion echo-planar imaging technique to accelerate quantitative T₁ mapping by judicious selection of inversion times for each slice.

METHODS

Slice ordering is optimized to maximize discrimination between tissues with different T₁ values. The optimized slice orderings are tested in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology phantom and compared with an unoptimized 21-measurement acquisition. The utility of the method is demonstrated in a healthy subject in vivo at 3 T and validated with a gold-standard inversion-recovery sequence. The in vivo precision of our technique was tested by repeated scans of the same subject within a scan session and across scan sessions, occurring 28 days apart.

RESULTS

Phantom measurements yielded good agreement (R²  = 0.99) between the T₁ estimates from the proposed optimized protocol, reference values from the National Institute of Standards and Technology phantom and gold-standard inversion-recovery values, as well as a negligible estimation bias that was slightly lower than that from the unoptimized 21-measurement protocol (0.74 versus 19 ms). The range of values for the scan-rescan coefficient of variation was 0.86 to 0.93 (within session) and 0.83 to 0.92 (across sessions) across all scan durations tested.

CONCLUSIONS

Optimized slice orderings allow faster quantitative T₁ mapping. The optimized sequence yielded accurate and precise T₁ maps. Magn Reson Med 79:2101-2112, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Relative cerebral blood volume is a potential biomarker in late delayed radiation-induced brain injury

PURPOSE

To assess whether relative cerebral blood volume (rCBV) can provide information to reliably evaluate the stages of late delayed radiation-induced brain injury.

MATERIALS AND METHODS

Forty patients diagnosed with late delayed radiation-induced brain injury were enrolled. The patients were examined using a 1.5T magnetic resonance imaging (MRI) system equipped with an 8-channel head coil. An echo planar imaging (EPI) sequence was used in perfusion-weighted imaging (PWI). The location of 1H-MR spectroscopy scanning was acquired by a point-resolved spectroscopy sequence. Lesions of the temporal lobe were divided into one of two groups according to rCBV value: rCBV<1 (low rCBV [group 1; n = 45]); and rCBV>1 (elevated rCBV [group 2; n = 14]). PWI and MRS parameters, as well as morphological lesion types, in these two groups were compared. Morphological severity was assessed independently and agreed on by two imaging specialists (J.L. and H.X.S., with 16 and 24 years' experience, respectively). If necessary, a third imaging professor (Z.M.H.) with 30 years' experience resolved disagreement(s). Standards for evaluating morphological lesion types were based on previously published criteria. After testing the skewness of data, the Mann-Whitney U-test or Student's t-test was used, as appropriate.

RESULTS

rCBV, relative cerebral blood flow (rCBF), and relative mean transit time (rMTT) in group 2 (n = 14) were significantly higher than in group 1 (n = 45) (rCBV: 1.21 ± 0.38 vs. 0.72 ± 0.32, respectively; P < 0.001; rCBF: 1.13 ± 0.02 vs. 0.74 ± 0.04, respectively; P < 0.001; rMTT: 1.10 ± 0.26 vs. 0.96 ± 0.20, P < 0.001). The levels of choline-containing compounds (CHO) / creatine (Cr) and CHO/N-acetylaspartate (NAA) in group 1 were significantly greater than in group 2 (CHO/Cr: 1.89 ± 1.83 vs. 1.22 ± 1.31, respectively; P = 0.016; CHO/NAA: 1.85 ± 3.50 vs. 1.17 ± 0.75, respectively; P = 0.022). More severe morphological lesions were present in lesions with low rCBV compared with elevated rCBV (overall severity: 7.00 ± 4.25 vs. 5.00 ± 5.13, respectively; P = 0.029).

CONCLUSION

Elevated rCBV accompanied by a more conservative metabolic pattern and milder lesion(s) may represent a less advanced stage in the development of late delayed radiation-induced brain injury.

LEVEL OF EVIDENCE

4 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1112-1118.

A Pilot Study Evaluating the Use of Dynamic Contrast-Enhanced Perfusion MRI to Predict Local Recurrence After Radiosurgery on Spinal Metastases

Purpose:

Dynamic contrast-enhanced magnetic resonance imaging offers noninvasive characterization of the vascular microenvironment and hemodynamics. Stereotactic radiosurgery, or stereotactic body radiation therapy, engages a vascular component of the tumor response which may be detectable using dynamic contrast-enhanced magnetic resonance imaging. The purpose of this study is to examine whether dynamic contrast-enhanced magnetic resonance imaging can be used to predict local tumor recurrence in patients with spinal bone metastases who undergo high-dose radiotherapy with stereotactic radiosurgery.

Materials and Methods:

We conducted a study of 30 patients with spinal metastases who underwent dynamic contrast-enhanced magnetic resonance imaging before and after radiotherapy. Twenty patients received single-fraction stereotactic radiosurgery (24 Gy), while 10 received hypofractionated stereotactic radiosurgery (3-5 fractions, 27-30 Gy total). Kaplan-Meier analysis was used to estimate the actuarial local recurrence rates. Two perfusion parameters (K^trans: permeability and V_p: plasma volume) were measured for each metastasis. Percentage change in parameter values from pre- to posttreatment was calculated and compared.

Results:

At 20-month median follow-up, 5 of the 30 patients had pathological evidence of local recurrence. One- and 3-year actuarial local recurrence rates were 24% and 44% for the hypofractionated stereotactic radiosurgery cohort versus 5% and 16% for the single-fraction stereotactic radiosurgery cohort (P = .20). The average change in V_p and K^trans for patients without local recurrence versus those with local recurrence was −76% and −66% versus +28% and −14% (P < .01 for both). With a cutoff point of −20%, V_p had a sensitivity, specificity, positive predictive value, and negative predictive value of 100%, 98%, 91%, and 100%, respectively, for the detection of local recurrence following high-dose radiotherapy. Using this definition, dynamic contrast-enhanced magnetic resonance imaging identified local recurrence up to 18 months (mean [standard deviation], 6.6 [6.8] months) earlier than standard magnetic resonance imaging.

Conclusions:

We demonstrated that changes in perfusion parameters, particularly V_p, after high-dose radiotherapy to spinal bone metastases were predictive of local tumor recurrence. These changes predicted local recurrence on average >6 months earlier than standard imaging did.

Diagnostic accuracy of magnetic resonance imaging techniques for treatment response evaluation in patients with high-grade glioma, a systematic review and meta-analysis

Objective

Treatment response assessment in high-grade gliomas uses contrast enhanced T1-weighted MRI, but is unreliable. Novel advanced MRI techniques have been studied, but the accuracy is not well known. Therefore, we performed a systematic meta-analysis to assess the diagnostic accuracy of anatomical and advanced MRI for treatment response in high-grade gliomas.

Methods

Databases were searched systematically. Study selection and data extraction were done by two authors independently. Meta-analysis was performed using a bivariate random effects model when ≥5 studies were included.

Results

Anatomical MRI (five studies, 166 patients) showed a pooled sensitivity and specificity of 68% (95%CI 51–81) and 77% (45–93), respectively. Pooled apparent diffusion coefficients (seven studies, 204 patients) demonstrated a sensitivity of 71% (60–80) and specificity of 87% (77–93). DSC-perfusion (18 studies, 708 patients) sensitivity was 87% (82–91) with a specificity of 86% (77–91). DCE-perfusion (five studies, 207 patients) sensitivity was 92% (73–98) and specificity was 85% (76–92). The sensitivity of spectroscopy (nine studies, 203 patients) was 91% (79–97) and specificity was 95% (65–99).

Conclusion

Advanced techniques showed higher diagnostic accuracy than anatomical MRI, the highest for spectroscopy, supporting the use in treatment response assessment in high-grade gliomas.

Key points

• Treatment response assessment in high-grade gliomas with anatomical MRI is unreliable

• Novel advanced MRI techniques have been studied, but diagnostic accuracy is unknown

• Meta-analysis demonstrates that advanced MRI showed higher diagnostic accuracy than anatomical MRI

• Highest diagnostic accuracy for spectroscopy and perfusion MRI

• Supports the incorporation of advanced MRI in high-grade glioma treatment response assessment

Electronic supplementary material

The online version of this article (doi:10.1007/s00330-017-4789-9) contains supplementary material, which is available to authorized users.

Clinical Applications of Contrast-Enhanced Perfusion MRI Techniques in Gliomas: Recent Advances and Current Challenges

Gliomas possess complex and heterogeneous vasculatures with abnormal hemodynamics. Despite considerable advances in diagnostic and therapeutic techniques for improving tumor management and patient care in recent years, the prognosis of malignant gliomas remains dismal. Perfusion-weighted magnetic resonance imaging techniques that could noninvasively provide superior information on vascular functionality have attracted much attention for evaluating brain tumors. However, nonconsensus imaging protocols and postprocessing analysis among different institutions impede their integration into standard-of-care imaging in clinic. And there have been very few studies providing a comprehensive evidence-based and systematic summary. This review first outlines the status of glioma theranostics and tumor-associated vascular pathology and then presents an overview of the principles of dynamic contrast-enhanced MRI (DCE-MRI) and dynamic susceptibility contrast-MRI (DSC-MRI), with emphasis on their recent clinical applications in gliomas including tumor grading, identification of molecular characteristics, differentiation of glioma from other brain tumors, treatment response assessment, and predicting prognosis. Current challenges and future perspectives are also highlighted.

The diagnostic performance of perfusion MRI for differentiating glioma recurrence from pseudoprogression: A meta-analysis

BACKGROUND

The purpose of this meta-analysis was to evaluate the diagnostic accuracy of perfusion magnetic resonance imaging (MRI) as a method for differentiating glioma recurrence from pseudoprogression.

METHODS

The PubMed, Embase, Cochrane Library, and Chinese Biomedical databases were searched comprehensively for relevant studies up to August 3, 2016 according to specific inclusion and exclusion criteria. The quality of the included studies was assessed according to the quality assessment of diagnostic accuracy studies (QUADAS-2). After performing heterogeneity and threshold effect tests, pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were calculated. Publication bias was evaluated visually by a funnel plot and quantitatively using Deek funnel plot asymmetry test. The area under the summary receiver operating characteristic curve was calculated to demonstrate the diagnostic performance of perfusion MRI.

RESULTS

Eleven studies covering 416 patients and 418 lesions were included in this meta-analysis. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 0.88 (95% confidence interval [CI] 0.84-0.92), 0.77 (95% CI 0.69-0.84), 3.93 (95% CI 2.83-5.46), 0.16 (95% CI 0.11-0.22), and 27.17 (95% CI 14.96-49.35), respectively. The area under the summary receiver operating characteristic curve was 0.8899. There was no notable publication bias. Sensitivity analysis showed that the meta-analysis results were stable and credible.

CONCLUSION

While perfusion MRI is not the ideal diagnostic method for differentiating glioma recurrence from pseudoprogression, it could improve diagnostic accuracy. Therefore, further research on combining perfusion MRI with other imaging modalities is warranted.

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.

Diffusion and perfusion weighted magnetic resonance imaging for tumor volume definition in radiotherapy of brain tumors

Accurate target volume delineation is crucial for the radiotherapy of tumors. Diffusion and perfusion magnetic resonance imaging (MRI) can provide functional information about brain tumors, and they are able to detect tumor volume and physiological changes beyond the lesions shown on conventional MRI. This review examines recent studies that utilized diffusion and perfusion MRI for tumor volume definition in radiotherapy of brain tumors, and it presents the opportunities and challenges in the integration of multimodal functional MRI into clinical practice. The results indicate that specialized and robust post-processing algorithms and tools are needed for the precise alignment of targets on the images, and comprehensive validations with more clinical data are important for the improvement of the correlation between histopathologic results and MRI parameter images.

Demonstration of DCE-MRI as an early pharmacodynamic biomarker of response to VEGF Trap in glioblastoma

Glioblastoma (GBM) is an incurable brain tumor characterized by the expression of pro-angiogenic cytokines. A recent phase II clinical trial studied VEGF Trap in adult patients with temozolomide-resistant GBM. We sought to explore changes in [¹⁸F]Fluorodeoxyglucose positron emission tomography (FDG-PET) or magnetic resonance imaging (MRI) in trial participants correlating these changes with disease response. FDG-PET and MRI images obtained before and after the first dose of VEGF Trap were spatially co-registered. Regions of interest on each image slice were combined to produce a volume of interest representative of the entire tumor. Percent and absolute changes in maximum FDG-avidity, mean apparent diffusion coefficient (ADC), K_trans, and Ve were calculated per lesion. Among the 12 participants that underwent dynamic contrast enhanced MRI (DCE-MRI), there were large, statistically significant reductions in K_trans and Ve (median difference = -41.8 %, p < 0.02 and -42.6 %, p < 0.04, respectively). In contrast, there were no significant reductions in ADC or FDG-PET SUVmax values. DCE-MRI is a useful measure of early pharmacodynamic effects of VEGF Trap on tumor vasculature. The absence of significant changes in FDG-PET and DW-MRI suggest that the early pharmacodynamic effects are specific to tumor perfusion and/or permeability and do not directly inhibit metabolism or induce cell death. DCE-MRI in conjunction with standard imaging may be promising for the identification of anti-angiogenic effects in this patient population with this therapeutic target. Further studies are needed to evaluate the relationship between DCE-MRI response and clinical outcome.

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.

Differentiating Radiation-Induced Necrosis from Recurrent Brain Tumor Using MR Perfusion and Spectroscopy: A Meta-Analysis

Purpose

This meta-analysis examined roles of several metabolites in differentiating recurrent tumor from necrosis in patients with brain tumors using MR perfusion and spectroscopy.

Methods

Medline, Cochrane, EMBASE, and Google Scholar were searched for studies using perfusion MRI and/or MR spectroscopy published up to March 4, 2015 which differentiated between recurrent tumor vs. necrosis in patients with primary brain tumors or brain metastasis. Only two-armed, prospective or retrospective studies were included. A meta-analysis was performed on the difference in relative cerebral blood volume (rCBV), ratios of choline/creatine (Cho/Cr) and/or choline/N-acetyl aspartate (Cho/NAA) between participants undergoing MRI evaluation. A χ²-based test of homogeneity was performed using Cochran’s Q statistic and I².

Results

Of 397 patients in 13 studies who were analyzed, the majority had tumor recurrence. As there was evidence of heterogeneity among 10 of the studies which used rCBV for evaluation (Q statistic = 31.634, I² = 97.11%, P < 0.0001) a random-effects analysis was applied. The pooled difference in means (2.18, 95%CI = 0.85 to 3.50) indicated that the average rCBV in a contrast-enhancing lesion was significantly higher in tumor recurrence compared with radiation injury (P = 0.001). Based on a fixed-effect model of analysis encompassing the six studies which used Cho/Cr ratios for evaluation (Q statistic = 8.388, I² = 40.39%, P = 0.137), the pooled difference in means (0.77, 95%CI = 0.57 to 0.98) of the average Cho/Cr ratio was significantly higher in tumor recurrence than in tumor necrosis (P = 0.001). There was significant difference in ratios of Cho to NAA between recurrent tumor and necrosis (1.02, 95%CI = 0.03 to 2.00, P = 0.044).

Conclusions

MR spectroscopy and MR perfusion using Cho/NAA and Cho/Cr ratios and rCBV may increase the accuracy of differentiating necrosis from recurrent tumor in patients with primary brain tumors or metastases.

T1-Weighted Dynamic Contrast-Enhanced MRI as a Noninvasive Biomarker of Epidermal Growth Factor Receptor vIII Status

BACKGROUND AND PURPOSE

Epidermal growth factor receptor variant III is a common mutation in glioblastoma, found in approximately 25% of tumors. Epidermal growth factor receptor variant III may accelerate angiogenesis in malignant gliomas. We correlated T1-weighted dynamic contrast-enhanced MR imaging perfusion parameters with epidermal growth factor receptor variant III status.

MATERIALS AND METHODS

Eighty-two consecutive patients with glioblastoma and known epidermal growth factor receptor variant III status who had dynamic contrast-enhanced MR imaging before surgery were evaluated. Volumes of interest were drawn around the entire enhancing tumor on contrast T1-weighted images and then were transferred onto coregistered dynamic contrast-enhanced MR imaging perfusion maps. Histogram analysis with normalization was performed to determine the relative mean, 75th percentile, and 90th percentile values for plasma volume and contrast transfer coefficient. A Wilcoxon rank sum test was applied to assess the relationship between baseline perfusion parameters and positive epidermal growth factor receptor variant III status. The receiver operating characteristic method was used to select the cutoffs of the dynamic contrast-enhanced MR imaging perfusion parameters.

RESULTS

Increased relative plasma volume and increased relative contrast transfer coefficient parameters were both significantly associated with positive epidermal growth factor receptor variant III status. For epidermal growth factor receptor variant III-positive tumors, relative plasma volume mean was 9.3 and relative contrast transfer coefficient mean was 6.5; for epidermal growth factor receptor variant III-negative tumors, relative plasma volume mean was 3.6 and relative contrast transfer coefficient mean was 3.7 (relative plasma volume mean, P < .001, and relative contrast transfer coefficient mean, P = .008). The predictive powers of relative plasma volume histogram metrics outperformed those of the relative contrast transfer coefficient histogram metrics (P < = .004).

CONCLUSIONS

Dynamic contrast-enhanced MR imaging shows greater perfusion and leakiness in epidermal growth factor receptor variant III-positive glioblastomas than in epidermal growth factor receptor variant III-negative glioblastomas, consistent with the known effect of epidermal growth factor receptor variant III on angiogenesis. Quantitative evaluation of dynamic contrast-enhanced MR imaging may be useful as a noninvasive tool for correlating epidermal growth factor receptor variant III expression and related tumor neoangiogenesis. This potential may have implications for monitoring response to epidermal growth factor receptor variant III-targeted therapies.

Case-Based Review: newly diagnosed glioblastoma

Glioblastoma (WHO grade IV astrocytoma) is the most common and most aggressive primary brain tumor in adults. Optimal treatment of a patient with glioblastoma requires collaborative care across numerous specialties. The diagnosis of glioblastoma may be suggested by the symptomatic presentation and imaging, but it must be pathologically confirmed via surgery, which can have dual diagnostic and therapeutic roles. Standard of care postsurgical treatment for newly diagnosed patients involves radiation therapy and oral temozolomide chemotherapy. Despite numerous recent trials of novel therapeutic approaches, this standard of care has not changed in over a decade. Treatment options under active investigation include molecularly targeted therapies, immunotherapeutic approaches, and the use of alternating electrical field to disrupt tumor cell division. These trials may be aided by new insights into glioblastoma heterogeneity, allowing for focused evaluation of new treatments in the patient subpopulations most likely to benefit from them. Because glioblastoma is incurable by current therapies, frequent clinical and radiographic assessment is needed after initial treatment to allow for early intervention upon progressive tumor when it occurs.

Pixel-by-Pixel Comparison of Volume Transfer Constant and Estimates of Cerebral Blood Volume from Dynamic Contrast-Enhanced and Dynamic Susceptibility Contrast-Enhanced MR Imaging in High-Grade Gliomas

BACKGROUND AND PURPOSE

Estimates of blood volume and volume transfer constant are parameters commonly used to characterize hemodynamic properties of brain lesions. The purposes of this study were to compare values of volume transfer constant and estimates of blood volume in high-grade gliomas on a pixel-by-pixel basis to comprehend whether they provide different information and to compare estimates of blood volume obtained by dynamic contrast-enhanced MR imaging and dynamic susceptibility contrast-enhanced MR imaging.

MATERIALS AND METHODS

Thirty-two patients with biopsy-proved grade IV gliomas underwent dynamic contrast-enhanced MR imaging and dynamic susceptibility contrast-enhanced MR imaging, and parametric maps of volume transfer constant, plasma volume, and CBV maps were calculated. The Spearman rank correlation coefficients among matching values of CBV, volume transfer constant, and plasma volume were calculated on a pixel-by-pixel basis. Comparison of median values of normalized CBV and plasma volume was performed.

RESULTS

Weak-but-significant correlation (P < .001) was noted for all comparisons. Spearman rank correlation coefficients were as follows: volume transfer constant versus CBV, ρ = 0.113; volume transfer constant versus plasma volume, ρ = 0.256; CBV versus plasma volume, ρ = 0.382. We found a statistically significant difference (P < .001) for the estimates of blood volume obtained by using dynamic contrast-enhanced MR imaging (mean normalized plasma volume, 13.89 ± 11.25) and dynamic susceptibility contrast-enhanced MR imaging (mean normalized CBV, 4.37 ± 4.04).

CONCLUSIONS

The finding of a very weak correlation between estimates of microvascular density and volume transfer constant suggests that they provide different information. Estimates of blood volume obtained by using dynamic contrast-enhanced MR imaging are significantly higher than those obtained by dynamic susceptibility contrast-enhanced MR imaging in human gliomas, most likely due to the effect of contrast leakage.

Dynamic Contrast-Enhanced Perfusion MRI of High Grade Brain Gliomas Obtained with Arterial or Venous Waveform Input Function

BACKGROUND AND PURPOSE

The aim of this study was to evaluate the differences in dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) perfusion estimates of high-grade brain gliomas (HGG) due to the use of an input function (IF) obtained respectively from arterial (AIF) and venous (VIF) approaches by two different commercially available software applications.

METHODS

This prospective study includes 20 patients with pathologically confirmed diagnosis of high-grade gliomas. The data source was processed by using two DCE dedicated commercial packages, both based on the extended Toft model, but the first customized to obtain input function from arterial measurement and the second from sagittal sinus sampling. The quantitative parametric perfusion maps estimated from the two software packages were compared by means of a region of interest (ROI) analysis. The resulting input functions from venous and arterial data were also compared.

RESULTS

No significant difference has been found between the perfusion parameters obtained with the two different software packages (P-value < .05). The comparison of the VIFs and AIFs obtained by the two packages showed no statistical differences.

CONCLUSIONS

Direct comparison of DCE-MRI measurements with IF generated by means of arterial or venous waveform led to no statistical difference in quantitative metrics for evaluating HGG. However, additional research involving DCE-MRI acquisition protocols and post-processing would be beneficial to further substantiate the effectiveness of venous approach as the IF method compared with arterial-based IF measurement.

Dynamic Contrast-Enhanced Perfusion MRI and Diffusion-Weighted Imaging in Grading of Gliomas

PURPOSE

Accurate glioma grading is crucial for treatment planning and predicting prognosis. We performed a quantitative volumetric analysis to assess the diagnostic accuracy of histogram analysis of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) T1-weighted perfusion imaging in the preoperative evaluation of gliomas.

METHODS

Sixty-three consecutive patients with pathologically confirmed gliomas who underwent baseline DWI and DCE-MRI were enrolled. The patients were classified by histopathology according to tumor grade: 20 low-grade gliomas (grade II) and 43 high-grade gliomas (grades III and IV). Volumes-of-interest were calculated and transferred to DCE perfusion and apparent diffusion coefficient (ADC) maps. Histogram analysis was performed to determine mean and maximum values for Vp and Ktrans , and mean and minimum values for ADC. Comparisons between high-grade and low-grade gliomas, and between grades II, III, and IV, were performed. A Mann-Whitney U test at a significance level of corrected P ≤ .01 was used to assess differences.

RESULTS

All perfusion parameters could differentiate between high-grade and low-grade gliomas (P < .001) and between grades II and IV, grades II and III, and grades III and IV. Significant differences in minimum ADC were also found (P < .01). Mean ADC only differed significantly between high and low grades and grades II and IV (P < .01). There were no differences between grades II and III (P = .1) and grades III and IV (P = .71).

CONCLUSION

When derived from whole-tumor histogram analysis, DCE-MRI perfusion parameters performed better than ADC in noninvasively discriminating low- from high-grade gliomas.