Performance of Standardized Relative CBV for Quantifying Regional Histologic Tumor Burden in Recurrent High-Grade Glioma: Comparison against Normalized Relative CBV Using Image-Localized Stereotactic Biopsies

Multisite Benchmark Study for Standardized Relative CBV in Untreated Brain Metastases Using the DSC-MRI Consensus Acquisition Protocol

BACKGROUND AND PURPOSE

A national consensus recommendation for the collection of DSC-MRI perfusion data, used to create maps of relative CBV (rCBV), has been recently established for primary and metastatic brain tumors. The goal was to reduce intersite variability and improve ease of comparison across time and sites, fostering widespread use of this informative measure. To translate this goal into practice, the prospective collection of consensus DSC-MRI data and characterization of derived rCBV maps in brain metastases is needed. The purpose of this multisite study was to determine rCBV in untreated brain metastases in comparison to glioblastoma (GBM) and normal-appearing brain by using the national consensus protocol.

MATERIALS AND METHODS

Subjects from 3 sites with untreated enhancing brain metastases underwent DSC-MRI according to a recommended option that uses a midrange flip angle, GRE-EPI acquisition, and the administration of both a preload and second DSC-MRI dose of 0.1 mmol/kg gadolinium-based contrast agent. Quantitative maps of standardized relative CBV (srCBV) were generated and enhancing lesion ROIs determined from postcontrast T1-weighted images alone or calibrated difference maps, termed Δ T1 (dT1) maps. Mean srCBV for metastases were compared with normal-appearing white matter (NAWM) and GBM from a previous study. Comparisons were performed by using either the Wilcoxon signed-rank test for paired comparisons or the Mann-Whitney U nonparametric test for unpaired comparisons.

RESULTS

Forty-nine patients with a primary histology of lung (n = 25), breast (n = 6), squamous cell carcinoma (n = 1), melanoma (n = 5), gastrointestinal (GI) (n = 3), and genitourinary (GU) (n = 9) were included in comparison to GBM (n = 31). The mean srCBV of all metastases (1.83±1.05) were significantly lower (P = .0009) than mean srCBV for GBM (2.67 ± 1.34) with both statistically greater (P < .0001) than NAWM (0.68 ± 0.18). Histologically distinct metastases are each statistically greater than NAWM (P < .0001) with lung (P = .0002) and GU (P = .02) srCBV being significantly different from GBM srCBV.

CONCLUSIONS

Using the consensus DSC-MRI protocol, mean srCBV values were determined for treatment-naïve brain metastases in comparison to normal-appearing white matter and GBM thus setting the benchmark for all subsequent studies adherent to the national consensus recommendation.

Advances in Glioblastoma Diagnosis: Integrating Genetics, Noninvasive Sampling, and Advanced Imaging

Glioblastoma is the most common primary brain tumor in adult patients, and despite standard-of-care treatment, median survival has remained less than two years. Advances in our understanding of molecular mutations have led to changes in the diagnostic criteria of glioblastoma, with the WHO classification integrating important mutations into the grading system in 2021. We sought to review the basics of the important genetic mutations associated with glioblastoma, including known mechanisms and roles in disease pathogenesis/treatment. We also examined new advances in image processing as well as less invasive and noninvasive diagnostic tools that can aid in the diagnosis and surveillance of those undergoing treatment for glioblastoma. Our review is intended to serve as an overview of the current state-of-the-art in the diagnosis and management of glioblastoma.

Advanced Imaging in the Diagnosis and Response Assessment of High-Grade Glioma: AJR Expert Panel Narrative Review

This AJR Expert Panel Narrative Review explores the current status of advanced MRI and PET techniques for the posttherapeutic response assessment of high-grade adult-type gliomas, focusing on ongoing clinical controversies in current practice. Discussed techniques that complement conventional MRI and aid the differentiation of recurrent tumor from posttreatment effects include DWI and diffusion-tensor imaging; perfusion MRI techniques including dynamic susceptibility contrast (DSC), dynamic contrast-enhanced, and arterial spin labeling MRI; MR spectroscopy (MRS) including assessment of 2-hydroxyglutarate (2HG) concentration; glucose- and amino acid (AA)-based PET; and amide proton transfer imaging. Updated criteria for the Response Assessment in Neuro-Oncology are presented. Given the abundant supporting clinical evidence, the panel supports a recommendation that routine response assessment after high-grade glioma treatment should include perfusion MRI, particularly given the development of a consensus recommended DSC-MRI protocol. Although published studies support 2HG MRS and AA PET, these techniques' widespread adoption will likely require increased availability (for 2HG MRS) or increased insurance funding in the United States (for AA PET). The review concludes with a series of consensus opinions from the author panel, centered on the clinical integration of the advanced imaging techniques into posttreatment surveillance protocols.

Identification of a Single-Dose, Low-Flip-Angle-Based CBV Threshold for Fractional Tumor Burden Mapping in Recurrent Glioblastoma

BACKGROUND AND PURPOSE

DSC-MR imaging can be used to generate fractional tumor burden (FTB) maps via application of relative CBV thresholds to spatially differentiate glioblastoma recurrence from posttreatment radiation effects (PTRE). Image-localized histopathology was previously used to validate FTB maps derived from a reference DSC-MR imaging protocol by using preload, a moderate flip angle (MFA, 60°), and postprocessing leakage correction. Recently, a DSC-MR imaging protocol with a low flip angle (LFA, 30°) with no preload was shown to provide leakage-corrected relative CBV (rCBV) equivalent to the reference protocol. This study aimed to identify the rCBV thresholds for the LFA protocol that generate the most accurate FTB maps, concordant with those obtained from the reference MFA protocol.

MATERIALS AND METHODS

Fifty-two patients with grade-IV glioblastoma who had prior surgical resection and received chemotherapy and radiation therapy were included in the study. Two sets of DSC-MR imaging data were collected sequentially first by using LFA protocol with no preload, which served as the preload for the subsequent MFA protocol. Standardized relative CBV maps (sRCBV) were obtained for each patient and coregistered with the anatomic postcontrast T1-weighted images. The reference MFA-based FTB maps were computed by using previously published sRCBV thresholds (1.0 and 1.56). A receiver operating characteristics (ROC) analysis was conducted to identify the optimal, voxelwise LFA sRCBV thresholds, and the sensitivity, specificity, and accuracy of the LFA-based FTB maps were computed with respect to the MFA-based reference.

RESULTS

The mean sRCBV values of tumors across patients exhibited strong agreement (concordance correlation coefficient = 0.99) between the 2 protocols. Using the ROC analysis, the optimal lower LFA threshold that accurately distinguishes PTRE from tumor recurrence was found to be 1.0 (sensitivity: 87.77%; specificity: 90.22%), equivalent to the ground truth. To identify aggressive tumor regions, the ROC analysis identified an upper LFA threshold of 1.37 (sensitivity: 90.87%; specificity: 91.10%) for the reference MFA threshold of 1.56.

CONCLUSIONS

For LFA-based FTB maps, an sRCBV threshold of 1.0 and 1.37 can differentiate PTRE from recurrent tumors. FTB maps aid in surgical planning, guiding pathologic diagnosis and treatment strategies in the recurrent setting. This study further confirms the reliability of single-dose LFA-based DSC-MR imaging.

Fractional tumor burden maps increase the confidence of reading brain MR perfusion

RATIONALE AND OBJECTIVES

Various methods exist to perform and post-process perfusion weighted MR imaging in the post-treatment imaging of glioma patients to differentiate tumor progression from tumor-related abnormalities. One of these post-processing methods produces 'fractional tumor burden' maps. This multi-reader study investigated the clinical feasibility of fractional tumor burden maps on real world data from radiological follow-up of high-grade astrocytoma patients.

METHODS

Five readers with background in radiology and varying levels of experience were tasked with assessing 30 astrocytoma and glioblastoma patients during one reader session. First, they were provided with a dataset of conventional MRI sequences, including perfusion MRI with regional cerebral blood volume maps. Then the dataset was expanded with a corresponding fractional tumor burden maps. Diagnostic accuracy, duration of post-processing, duration of the assessment of the fractional tumor burden maps, the diagnostic confidence reported by the readers and their diagnoses were recorded. Final diagnosis was determined by clinical and radiological follow-up and/or histopathological data used as gold standard.

RESULTS

A mean sensitivity of 83.3 % and mean specificity of 55.1 % was obtained without the use of fractional tumor burden maps, whereas their additional of fractional tumor burden maps resulted in a mean sensitivity and specificity of 79.5 % and 54.2 %, respectively. Diagnostic accuracies with and without fractional tumor burden maps were not significantly different (Z = 0.76, p = 0.450). The median time spent post-processing was 313 s, while the median duration of the assessment of the FTB maps was 19 s. Interestingly, reader confidence increased significantly after adding the fractional tumor burden-maps to the assessment (Z = 454, p < 0.01).

CONCLUSIONS

While the use of fractional tumor burden maps does not carry additional value in the radiological follow-up of post-operative high-grade astrocytoma and glioblastoma patients, it does give readers more confidence in their diagnosis.

A 3D dual-echo spiral sequence for simultaneous dynamic susceptibility contrast and dynamic contrast-enhanced MRI with single bolus injection

PURPOSE

Perfusion MRI reveals important tumor physiological and pathophysiologic information, making it a critical component in managing brain tumor patients. This study aimed to develop a dual-echo 3D spiral technique with a single-bolus scheme to simultaneously acquire both dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) data and overcome the limitations of current EPI-based techniques.

METHODS

A 3D spiral-based technique with dual-echo acquisition was implemented and optimized on a 3T MRI scanner with a spiral staircase trajectory and through-plane SENSE acceleration for improved speed and image quality, in-plane variable-density undersampling combined with a sliding-window acquisition and reconstruction approach for increased speed, and an advanced iterative deblurring algorithm. Four volunteers were scanned and compared with the standard of care (SOC) single-echo EPI and a dual-echo EPI technique. Two patients were scanned with the spiral technique during a preload bolus and compared with the SOC single-echo EPI collected during the second bolus injection.

RESULTS

Volunteer data demonstrated that the spiral technique achieved high image quality, reduced geometric artifacts, and high temporal SNR compared with both single-echo and dual-echo EPI. Patient perfusion data showed that the spiral acquisition achieved accurate DSC quantification comparable to SOC single-echo dual-dose EPI, with the additional DCE information.

CONCLUSION

A 3D dual-echo spiral technique was developed to simultaneously acquire both DSC and DCE data in a single-bolus injection with reduced contrast use. Preliminary volunteer and patient data demonstrated increased temporal SNR, reduced geometric artifacts, and accurate perfusion quantification, suggesting a competitive alternative to SOC-EPI techniques for brain perfusion MRI.

Challenges, limitations, and pitfalls of PET and advanced MRI in patients with brain tumors: A report of the PET/RANO group

Brain tumor diagnostics have significantly evolved with the use of positron emission tomography (PET) and advanced magnetic resonance imaging (MRI) techniques. In addition to anatomical MRI, these modalities may provide valuable information for several clinical applications such as differential diagnosis, delineation of tumor extent, prognostication, differentiation between tumor relapse and treatment-related changes, and the evaluation of response to anticancer therapy. In particular, joint recommendations of the Response Assessment in Neuro-Oncology (RANO) Group, the European Association of Neuro-oncology, and major European and American Nuclear Medicine societies highlighted that the additional clinical value of radiolabeled amino acids compared to anatomical MRI alone is outstanding and that its widespread clinical use should be supported. For advanced MRI and its steadily increasing use in clinical practice, the Standardization Subcommittee of the Jumpstarting Brain Tumor Drug Development Coalition provided more recently an updated acquisition protocol for the widely used dynamic susceptibility contrast perfusion MRI. Besides amino acid PET and perfusion MRI, other PET tracers and advanced MRI techniques (e.g. MR spectroscopy) are of considerable clinical interest and are increasingly integrated into everyday clinical practice. Nevertheless, these modalities have shortcomings which should be considered in clinical routine. This comprehensive review provides an overview of potential challenges, limitations, and pitfalls associated with PET imaging and advanced MRI techniques in patients with gliomas or brain metastases. Despite these issues, PET imaging and advanced MRI techniques continue to play an indispensable role in brain tumor management. Acknowledging and mitigating these challenges through interdisciplinary collaboration, standardized protocols, and continuous innovation will further enhance the utility of these modalities in guiding optimal patient care.

Tumor treating fields increases blood-brain barrier permeability and relative cerebral blood volume in patients with glioblastoma

BACKGROUND AND OBJECTIVE

200 kHz tumor treating fields (TTFields) is clinically approved for newly-diagnosed glioblastoma (nGBM). Because its effects on conventional surveillance MRI brain scans are equivocal, we investigated its effects on perfusion MRI (pMRI) brain scans.

METHODS

Each patient underwent institutional standard pMRI: dynamic contrast-enhanced (DCE) and dynamic susceptibility contrast (DSC) pMRI at three time points: baseline, 2-, and 6-months on-adjuvant therapy. At each timepoint, the difference between T1 pre- versus post-contrast tumor volume (ΔT1) and these pMRI metrics were evaluated: normalized and standardized relative cerebral blood volume (nRCBV, sRCBV); fractional plasma volume (Vp), volume of extravascular extracellular space (EES) per volume of tissue (Ve), blood-brain barrier (BBB) permeability (Ktrans), and time constant for gadolinium reflux from EES back into the vascular system (Kep). Between-group comparisons were performed using rank-sum analysis, and bootstrapping evaluated likely reproducibility of the results.

RESULTS

Among 13 pMRI datasets (11 nGBM, 2 recurrent GBM), therapies included temozolomide-only (n = 9) and temozolomide + TTFields (n = 4). No significant differences were found in patient or tumor characteristics. Compared to temozolomide-only, temozolomide + TTFields did not significantly affect the percent-change in pMRI metrics from baseline to 2 months. But during the 2- to 6-month period, temozolomide + TTFields significantly increased the percent-change in nRCBV (+26.9% [interquartile range 55.1%] vs -39.1% [37.0%], p = 0.049), sRCBV (+9.5% [39.7%] vs -30.5% [39.4%], p = 0.049), Ktrans (+54.6% [1768.4%] vs -26.9% [61.2%], p = 0.024), Ve (+111.0% [518.1%] vs -13.0% [22.5%], p = 0.048), and Vp (+98.8% [2172.4%] vs -24.6% [53.3%], p = 0.024) compared to temozolomide-only.

CONCLUSION

Using pMRI, we provide initial in-human validation of pre-clinical studies regarding the effects of TTFields on tumor blood volume and BBB permeability in GBM.

Added prognostic value of DCE blood volume imaging in patients with suspected recurrent or residual glioblastoma-A hybrid [18F]FET PET/MRI study

Background

Magnetic resonance imaging (MRI) cerebral blood volume (CBV) measurements improve the diagnosis of recurrent gliomas. The study investigated the prognostic value of dynamic contrast-enhanced (DCE) CBV imaging in treated IDH wildtype glioblastoma when added to MRI or amino acid positron emission tomography (PET).

Methods

Hybrid [18F]FET PET/MRI with 2CXM (2-compartment exchange model) DCE from 86 adult patients with suspected recurrent or residual glioblastoma were retrospectively analyzed. High CBV tumor volume (VOLCBV), and contrast-enhancing (VOLCE) and [18F]FET active tumor (VOLFET) volumes were delineated. Absolute and fractional high CBV subvolumes within VOLCE and VOLFET were determined. Associations with overall survival (OS) were assessed by Cox analysis.

Results

Adjusted for methyltransferase gene status and steroid use all total tumor volumes were individually associated with shorter OS. Adding VOLCBV to VOLCE or VOLFET only the effect of VOLCBV was prognostic of OS (hazard ratio [HR] 1.327, P = .042 and 1.352, P = .011, respectively). High CBV subvolumes within both VOLCE and VOLFET were associated with shorter survival (HR 1.448, P = .042 and 1.416, P = .011, respectively), and the low CBV subvolumes with longer survival (HR 0.504, P = .002 and .365, P = .001, respectively). The fraction of VOLCE and VOLFET with high CBV was a strong predictor of OS with shorter median OS in upper versus lower tertiles (8.3 vs 14.5 months and 7.1 vs 15.6 months, respectively, both P < .001).

Conclusions

The high CBV tumor volume was a strong prognosticator of survival and allowed for the separation of high- and low-risk subvolumes underlining the heterogeneous physiological environment represented in the contrast-enhancing or metabolically active tumor volumes of treated glioblastoma.

Integrated molecular and multiparametric MRI mapping of high-grade glioma identifies regional biologic signatures

Sampling restrictions have hindered the comprehensive study of invasive non-enhancing (NE) high-grade glioma (HGG) cell populations driving tumor progression. Here, we present an integrated multi-omic analysis of spatially matched molecular and multi-parametric magnetic resonance imaging (MRI) profiling across 313 multi-regional tumor biopsies, including 111 from the NE, across 68 HGG patients. Whole exome and RNA sequencing uncover unique genomic alterations to unresectable invasive NE tumor, including subclonal events, which inform genomic models predictive of geographic evolution. Infiltrative NE tumor is alternatively enriched with tumor cells exhibiting neuronal or glycolytic/plurimetabolic cellular states, two principal transcriptomic pathway-based glioma subtypes, which respectively demonstrate abundant private mutations or enrichment in immune cell signatures. These NE phenotypes are non-invasively identified through normalized K2 imaging signatures, which discern cell size heterogeneity on dynamic susceptibility contrast (DSC)-MRI. NE tumor populations predicted to display increased cellular proliferation by mean diffusivity (MD) MRI metrics are uniquely associated with EGFR amplification and CDKN2A homozygous deletion. The biophysical mapping of infiltrative HGG potentially enables the clinical recognition of tumor subpopulations with aggressive molecular signatures driving tumor progression, thereby informing precision medicine targeting.

Amine-weighted chemical exchange saturation transfer magnetic resonance imaging in brain tumors

Amine-weighted chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) is particularly valuable as an amine- and pH-sensitive imaging technique in brain tumors, targeting the intrinsically high concentration of amino acids with exchangeable amine protons and reduced extracellular pH in brain tumors. Amine-weighted CEST MRI contrast is dependent on the glioma genotype, likely related to differences in degree of malignancy and metabolic behavior. Amine-weighted CEST MRI may provide complementary value to anatomic imaging in conventional and exploratory therapies in brain tumors, including chemoradiation, antiangiogenic therapies, and immunotherapies. Continual improvement and clinical testing of amine-weighted CEST MRI has the potential to greatly impact patients with brain tumors by understanding vulnerabilities in the tumor microenvironment that may be therapeutically exploited.

Assessment and prediction of glioblastoma therapy response: challenges and opportunities

Glioblastoma is the most aggressive type of primary adult brain tumour. The median survival of patients with glioblastoma remains approximately 15 months, and the 5-year survival rate is <10%. Current treatment options are limited, and the standard of care has remained relatively constant since 2011. Over the last decade, a range of different treatment regimens have been investigated with very limited success. Tumour recurrence is almost inevitable with the current treatment strategies, as glioblastoma tumours are highly heterogeneous and invasive. Additionally, another challenging issue facing patients with glioblastoma is how to distinguish between tumour progression and treatment effects, especially when relying on routine diagnostic imaging techniques in the clinic. The specificity of routine imaging for identifying tumour progression early or in a timely manner is poor due to the appearance similarity of post-treatment effects. Here, we concisely describe the current status and challenges in the assessment and early prediction of therapy response and the early detection of tumour progression or recurrence. We also summarize and discuss studies of advanced approaches such as quantitative imaging, liquid biomarker discovery and machine intelligence that hold exceptional potential to aid in the therapy monitoring of this malignancy and early prediction of therapy response, which may decisively transform the conventional detection methods in the era of precision medicine.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Identification of single-dose, dual-echo based CBV threshold for fractional tumor burden mapping in recurrent glioblastoma

Background

Relative cerebral blood volume (rCBV) obtained from dynamic susceptibility contrast (DSC) MRI is widely used to distinguish high grade glioma recurrence from post treatment radiation effects (PTRE). Application of rCBV thresholds yield maps to distinguish between regional tumor burden and PTRE, a biomarker termed the fractional tumor burden (FTB). FTB is generally measured using conventional double-dose, single-echo DSC-MRI protocols; recently, a single-dose, dual-echo DSC-MRI protocol was clinically validated by direct comparison to the conventional double-dose, single-echo protocol. As the single-dose, dual-echo acquisition enables reduction in the contrast agent dose and provides greater pulse sequence parameter flexibility, there is a compelling need to establish dual-echo DSC-MRI based FTB mapping. In this study, we determine the optimum standardized rCBV threshold for the single-dose, dual-echo protocol to generate FTB maps that best match those derived from the reference standard, double-dose, single-echo protocol.

Methods

The study consisted of 23 high grade glioma patients undergoing perfusion scans to confirm suspected tumor recurrence. We sequentially acquired single dose, dual-echo and double dose, single-echo DSC-MRI data. For both protocols, we generated leakage-corrected standardized rCBV maps. Standardized rCBV (sRCBV) thresholds of 1.0 and 1.75 were used to compute single-echo FTB maps as the reference for delineating PTRE (sRCBV < 1.0), tumor with moderate angiogenesis (1.0 < sRCBV < 1.75), and tumor with high angiogenesis (sRCBV > 1.75) regions. To assess the sRCBV agreement between acquisition protocols, the concordance correlation coefficient (CCC) was computed between the mean tumor sRCBV values across the patients. A receiver operating characteristics (ROC) analysis was performed to determine the optimum dual-echo sRCBV threshold. The sensitivity, specificity, and accuracy were compared between the obtained optimized threshold (1.64) and the standard reference threshold (1.75) for the dual-echo sRCBV threshold.

Results

The mean tumor sRCBV values across the patients showed a strong correlation (CCC = 0.96) between the two protocols. The ROC analysis showed maximum accuracy at thresholds of 1.0 (delineate PTRE from tumor) and 1.64 (differentiate aggressive tumors). The reference threshold (1.75) and the obtained optimized threshold (1.64) yielded similar accuracy, with slight differences in sensitivity and specificity which were not statistically significant (1.75 threshold: Sensitivity = 81.94%; Specificity: 87.23%; Accuracy: 84.58% and 1.64 threshold: Sensitivity = 84.48%; Specificity: 84.97%; Accuracy: 84.73%).

Conclusions

The optimal sRCBV threshold for single-dose, dual-echo protocol was found to be 1.0 and 1.64 for distinguishing tumor recurrence from PTRE; however, minimal differences were observed when using the standard threshold (1.75) as the upper threshold, suggesting that the standard threshold could be used for both protocols. While the prior study validated the agreement of the mean sRCBV values between the protocols, this study confirmed that their voxel-wise agreement is suitable for reliable FTB mapping. Dual-echo DSC-MRI acquisitions enable robust single-dose sRCBV and FTB mapping, provide pulse sequence parameter flexibility and should improve reproducibility by mitigating variations in preload dose and incubation time.

Case report: Fractional brain tumor burden magnetic resonance mapping to assess response to pulsed low-dose-rate radiotherapy in newly-diagnosed glioblastoma

Background

Pulsed low-dose-rate radiotherapy (pLDR) is a commonly used reirradiation technique for recurrent glioma, but its upfront use with temozolomide (TMZ) following primary resection of glioblastoma is currently under investigation. Because standard magnetic resonance imaging (MRI) has limitations in differentiating treatment effect from tumor progression in such applications, perfusion-weighted MRI (PWI) can be used to create fractional tumor burden (FTB) maps to spatially distinguish active tumor from treatment-related effect.

Methods

We performed PWI prior to re-resection in four patients with glioblastoma who had undergone upfront pLDR concurrent with TMZ who had radiographic suspicion for tumor progression at a median of 3 months (0-5 months or 0-143 days) post-pLDR. The pathologic diagnosis was compared to retrospectively-generated FTB maps.

Results

The median patient age was 55.5 years (50-60 years). All were male with IDH-wild type (n=4) and O6-methylguanine-DNA methyltransferase (MGMT) hypermethylated (n=1) molecular markers. Pathologic diagnosis revealed treatment effect (n=2), a mixture of viable tumor and treatment effect (n=1), or viable tumor (n=1). In 3 of 4 cases, FTB maps were indicative of lesion volumes being comprised predominantly of treatment effect with enhancing tumor volumes comprised of a median of 6.8% vascular tumor (6.4-16.4%).

Conclusion

This case series provides insight into the radiographic response to upfront pLDR and TMZ and the role for FTB mapping to distinguish tumor progression from treatment effect prior to redo-surgery and within 20 weeks post-radiation.

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.

Conventional and Advanced Imaging Techniques in Post-treatment Glioma Imaging

Despite decades of advancement in the diagnosis and therapy of gliomas, the most malignant primary brain tumors, the overall survival rate is still dismal, and their post-treatment imaging appearance remains very challenging to interpret. Since the limitations of conventional magnetic resonance imaging (MRI) in the distinction between recurrence and treatment effect have been recognized, a variety of advanced MR and functional imaging techniques including diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), perfusion-weighted imaging (PWI), MR spectroscopy (MRS), as well as a variety of radiotracers for single photon emission computed tomography (SPECT) and positron emission tomography (PET) have been investigated for this indication along with voxel-based and more quantitative analytical methods in recent years. Machine learning and radiomics approaches in recent years have shown promise in distinguishing between recurrence and treatment effect as well as improving prognostication in a malignancy with a very short life expectancy. This review provides a comprehensive overview of the conventional and advanced imaging techniques with the potential to differentiate recurrence from treatment effect and includes updates in the state-of-the-art in advanced imaging with a brief overview of emerging experimental techniques. A series of representative cases are provided to illustrate the synthesis of conventional and advanced imaging with the clinical context which informs the radiologic evaluation of gliomas in the post-treatment setting.

DSC Perfusion MRI-Derived Fractional Tumor Burden and Relative CBV Differentiate Tumor Progression and Radiation Necrosis in Brain Metastases Treated with Stereotactic Radiosurgery

BACKGROUND AND PURPOSE

Differentiation between tumor and radiation necrosis in patients with brain metastases treated with stereotactic radiosurgery is challenging. We hypothesized that MR perfusion and metabolic metrics can differentiate radiation necrosis from progressive tumor in this setting.

MATERIALS AND METHODS

We retrospectively evaluated MRIs comprising DSC, dynamic contrast-enhanced, and arterial spin-labeling perfusion imaging in subjects with brain metastases previously treated with stereotactic radiosurgery. For each lesion, we obtained the mean normalized and standardized relative CBV and fractional tumor burden, volume transfer constant, and normalized maximum CBF, as well as the maximum standardized uptake value in a subset of subjects who underwent FDG-PET. Relative CBV thresholds of 1 and 1.75 were used to define low and high fractional tumor burden.

RESULTS

Thirty subjects with 37 lesions (20 radiation necrosis, 17 tumor) were included. Compared with radiation necrosis, tumor had increased mean normalized and standardized relative CBV (P = .002) and high fractional tumor burden (normalized, P = .005; standardized, P = .003) and decreased low fractional tumor burden (normalized, P = .03; standardized, P = .01). The area under the curve showed that relative CBV (normalized = 0.80; standardized = 0.79) and high fractional tumor burden (normalized = 0.77; standardized = 0.78) performed the best to discriminate tumor and radiation necrosis. For tumor prediction, the normalized relative CBV cutoff of ≥1.75 yielded a sensitivity of 76.5% and specificity of 70.0%, while the standardized cutoff of ≥1.75 yielded a sensitivity of 41.2% and specificity of 95.0%. No significance was found with the volume transfer constant, normalized CBF, and standardized uptake value.

CONCLUSIONS

Increased relative CBV and high fractional tumor burden (defined by a threshold relative CBV of ≥1.75) best differentiated tumor from radiation necrosis in subjects with brain metastases treated with stereotactic radiosurgery. Performance of normalized and standardized approaches was similar.

Advanced MRI Protocols to Discriminate Glioma From Treatment Effects: State of the Art and Future Directions

In the follow-up treatment of high-grade gliomas (HGGs), differentiating true tumor progression from treatment-related effects, such as pseudoprogression and radiation necrosis, presents an ongoing clinical challenge. Conventional MRI with and without intravenous contrast serves as the clinical benchmark for the posttreatment surveillance imaging of HGG. However, many advanced imaging techniques have shown promise in helping better delineate the findings in indeterminate scenarios, as posttreatment effects can often mimic true tumor progression on conventional imaging. These challenges are further confounded by the histologic admixture that can commonly occur between tumor growth and treatment-related effects within the posttreatment bed. This review discusses the current practices in the surveillance imaging of HGG and the role of advanced imaging techniques, including perfusion MRI and metabolic MRI.

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.

Magnetic Resonance Imaging Mapping of Brain Tumor Burden: Clinical Implications for Neurosurgical Management: Case Report

BACKGROUND AND IMPORTANCE

Distinction of brain tumor progression from treatment effect on postcontrast magnetic resonance imaging (MRI) is an ongoing challenge in the management of brain tumor patients. A newly emerging MRI biomarker called fractional tumor burden (FTB) has demonstrated the ability to spatially distinguish high-grade brain tumor from treatment effect with important implications for surgical management and pathological diagnosis.

CLINICAL PRESENTATION

A 58-yr-old male with glioblastoma was treated with standard concurrent chemoradiotherapy (CRT) after initial resection. Throughout follow-up imaging, the distinction of tumor progression from treatment effect was of concern. The surgical report from a redo resection indicated recurrent glioblastoma, while the tissue sent for pathological diagnosis revealed no tumor. Presurgical FTB maps confirmed the spatial variation of tumor and treatment effect within the contrast-agent enhancing lesion. Unresected lesion, shown to be an active tumor on FTB, was the site of substantial tumor growth postresection.

CONCLUSION

This case report introduces the idea that a newly developed MRI biomarker, FTB, can provide information of tremendous benefit for surgical management, pathological diagnosis as well as subsequent treatment management decisions in high-grade glioma.

Update on neuroimaging in brain tumours

PURPOSE OF REVIEW

To highlight some of the recent advances in magnetic resonance imaging (MRI), in terms of acquisition, analysis, and interpretation for primary diagnosis, treatment planning, and surveillance of patients with a brain tumour.

RECENT FINDINGS

The rapidly emerging field of radiomics associates large numbers of imaging features with clinical characteristics. In the context of glioma, attempts are made to correlate such imaging features with the tumour genotype, using so-called radiogenomics. The T2-fluid attenuated inversion recovery (FLAIR) mismatch sign is an easy to apply imaging feature for identifying isocitrate dehydrogenase-mutant 1p/19q intact glioma with very high specificity.For treatment planning, resting state functional MRI (fMRI) may become as powerful as task-based fMRI. Functional ultrasound has shown the potential to identify functionally active cortex during surgery.For tumour response assessment automated techniques have been developed. Multiple new guidelines have become available, including those for adult and paediatric glioma and for leptomeningeal metastases, as well as on brain metastasis and perfusion imaging.

SUMMARY

Neuroimaging plays a central role but still often falls short on essential questions. Advanced imaging acquisition and analysis techniques hold great promise for answering such questions, and are expected to change the role of neuroimaging for patient management substantially in the near future.

Clinical Review of Computed Tomography and MR Perfusion Imaging in Neuro-Oncology

Neuroimaging plays an essential role in the initial diagnosis and continued surveillance of intracranial neoplasms. The advent of perfusion techniques with computed tomography and MR imaging have proven useful in neuro-oncology, offering enhanced approaches for tumor grading, guiding stereotactic biopsies, and monitoring treatment efficacy. Perfusion imaging can help to identify treatment-related processes, such as radiation necrosis, pseudoprogression, and pseudoregression, and can help to inform treatment-related decision making. Perfusion imaging is useful to differentiate between tumor types and between tumor and nonneoplastic conditions. This article reviews the clinical relevance and implications of perfusion imaging in neuro-oncology and highlights promising perfusion biomarkers.