Multi-Site Benchmark Study for Standardized Relative Cerebral Blood Volume in Untreated Brain Metastases Using the DSC-MRI Consensus Acquisition Protocol.

BACKGROUND AND PURPOSE: A national consensus recommendation for the collection of DSC (dynamic susceptibility contrast) MRI perfusion data, used to create maps of relative cerebral blood volume (rCBV), has been recently established for primary and metastatic brain tumors. The goal was to reduce inter-site 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 multi-site study was to determine rCBV in untreated brain metastases in comparison to glioblastoma and normal appearing brain using the national consensus protocol. MATERIALS AND METHODS: Subjects from three sites with untreated enhancing brain metastases underwent DSC-MRI according to a recommended option that uses a mid-range flip angle, GRE-EPI acquisition and the administration of both a pre-load and 2nd DSC-MRI dose of 0.1 mmol/kg GBCA. Quantitative maps of standardized rCBV (sRCBV) were generated and enhancing lesion ROIs determined from post-contrast T1-weighted images alone or calibrated difference maps, termed delta T1 (dT1) maps. Mean sRCBV for metastases were compared to normal appearing white matter (NAWM) and glioblastoma (GBM) from a previous study. Comparisons were performed using either the Wilcoxon signed-rank test for paired comparisons or the Mann-Whitney nonparametric test for unpaired comparisons. RESULTS: 49 patients with a primary histology of lung (n=25), breast (n=6), squamous cell carcinoma (SCC) (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=0.0009) than mean sRCBV for GBM (2.67±1.34) with both statistically greater (p<0.0001) than NAWM (0.68 +/- 0.18). Histologically distinct metastases are each statistically greater than NAWM (p<0.0001) with lung (p=0.0002) and GU (p=.02) sRCBV being significantly different than GBM sRCBV. CONCLUSIONS: 49 patients with a primary histology of lung (n=25), breast (n=6), squamous cell carcinoma (SCC) (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=0.0009) than mean sRCBV for GBM (2.67+1.34) with both statistically greater (p<0.0001) than NAWM (0.68 +/- 0.18). Histologically distinct metastases are each statistically greater than NAWM (p<0.0001) with lung (p=0.0002) and GU (p=.02) sRCBV being significantly different than GBM sRCBV. ABBREVIATIONS: dT1=delta T1; GBCA=gadolinium-based contrast agent; NAWM=normal appearing white matter; normalized relative cerebral blood volume=nRCBV; relative cerebral blood volume=rCBV; standardized relative cerebral blood volume=sRCBV.

Deep Learning Segmentation of Infiltrative and Enhancing Cellular Tumor at Pre- and Posttreatment Multishell Diffusion MRI of Glioblastoma.

Purpose To develop and validate a deep learning (DL) method to detect and segment enhancing and nonenhancing cellular tumor on pre- and posttreatment MRI scans in patients with glioblastoma and to predict overall survival (OS) and progression-free survival (PFS). Materials and Methods This retrospective study included 1397 MRI scans in 1297 patients with glioblastoma, including an internal set of 243 MRI scans (January 2010 to June 2022) for model training and cross-validation and four external test cohorts. Cellular tumor maps were segmented by two radiologists on the basis of imaging, clinical history, and pathologic findings. Multimodal MRI data with perfusion and multishell diffusion imaging were inputted into a nnU-Net DL model to segment cellular tumor. Segmentation performance (Dice score) and performance in distinguishing recurrent tumor from posttreatment changes (area under the receiver operating characteristic curve [AUC]) were quantified. Model performance in predicting OS and PFS was assessed using Cox multivariable analysis. Results A cohort of 178 patients (mean age, 56 years ± 13 [SD]; 116 male, 62 female) with 243 MRI timepoints, as well as four external datasets with 55, 70, 610, and 419 MRI timepoints, respectively, were evaluated. The median Dice score was 0.79 (IQR, 0.53-0.89), and the AUC for detecting residual or recurrent tumor was 0.84 (95% CI: 0.79, 0.89). In the internal test set, estimated cellular tumor volume was significantly associated with OS (hazard ratio [HR] = 1.04 per milliliter; P < .001) and PFS (HR = 1.04 per milliliter; P < .001) after adjustment for age, sex, and gross total resection (GTR) status. In the external test sets, estimated cellular tumor volume was significantly associated with OS (HR = 1.01 per milliliter; P < .001) after adjustment for age, sex, and GTR status. Conclusion A DL model incorporating advanced imaging could accurately segment enhancing and nonenhancing cellular tumor, distinguish recurrent or residual tumor from posttreatment changes, and predict OS and PFS in patients with glioblastoma. Keywords: Segmentation, Glioblastoma, Multishell Diffusion MRI Supplemental material is available for this article. © RSNA, 2024.

Application of Delta T1 maps for quantitative and objective assessment of extent of resection and survival prediction in glioblastoma.

Background and Objectives: Gross-total resection (GTR) and low residual tumor volume (RTV) have been associated with increased survival in glioblastoma. Largely due to the subjectivity involved, the determination of GTR and RTV remains difficult in the postoperative setting. In response, the objective of this study is to evaluate the clinical efficacy of an easy-to-use MRI metric, called delta T1 (dT1), to quantify extent of resection (EOR) and RTV, in comparison to radiologist impression, to predict overall survival (OS) in glioblastoma patients. Methods: 59 patients who underwent resection of glioblastoma were retrospectively identified. Delta T1 (dT1) images, automatically created from the difference between calibrated post- and pre-contrast T1-weighted images, were used to quantify EOR and RTV. Kaplan-Meier survival estimates were determined for EOR categories, an RTV cutoff of 5cm3 and radiologist interpretation of EOR. Multivariate Cox proportional hazard regression analysis was used to evaluate RTV and EOR along with effects related to sex, KPS, MGMT, and age on OS. Results: Kaplan-Meier analysis revealed a statistically significant difference in median OS for a dT1-determined RTV cutoff of 5 cm3 (P=.0024, HR=2.18 (1.232-3.856)), but not for radiological impression (P=0.666) or dT1-determined EOR (P=0.0803), which was limited to a comparison between partial and subtotal resections. Furthermore, when covariates were accounted for in multivariate Cox regression, significant differences in OS were retained for dT1-determined RTV. Additionally, a significantly strong yet short-term effect of MGMT methylation status on OS was revealed for each RTV and EOR model. Conclusion: The utility of dT1 maps to quantify EOR and RTV in glioblastoma and predict survival, suggests an emerging role for dT1s with relevance for intraoperative MRI, neuro-navigation and postoperative disease surveillance.

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.

Practical guidance to identify and troubleshoot suboptimal DSC-MRI results.

Relative cerebral blood volume (rCBV) derived from dynamic susceptibility contrast (DSC) perfusion MR imaging (pMRI) has been shown to be a robust marker of neuroradiological tumor burden. Recent consensus recommendations in pMRI acquisition strategies have provided a pathway for pMRI inclusion in diverse patient care centers, regardless of size or experience. However, even with proper implementation and execution of the DSC-MRI protocol, issues will arise that many centers may not easily recognize or be aware of. Furthermore, missed pMRI issues are not always apparent in the resulting rCBV images, potentiating inaccurate or missed radiological diagnoses. Therefore, we gathered from our database of DSC-MRI datasets, true-to-life examples showcasing the breakdowns in acquisition, postprocessing, and interpretation, along with appropriate mitigation strategies when possible. The pMRI issues addressed include those related to image acquisition and postprocessing with a focus on contrast agent administration, timing, and rate, signal-to-noise quality, and susceptibility artifact. The goal of this work is to provide guidance to minimize and recognize pMRI issues to ensure that only quality data is interpreted.

Magnetic resonance imaging-derived relative cerebral blood volume characteristics in a case of pathologically confirmed neurocysticercosis: illustrative case.

BACKGROUND: Neurocysticercosis (NCC) is a parasitic infection of the brain caused by ingesting water or food contaminated with tapeworm eggs. When it presents as a solitary mass, differentiation from a primary brain tumor on imaging can be difficult. Magnetic resonance imaging (MRI)-derived relative cerebral blood volume (rCBV) is a newer imaging technique used to identify areas of neovascularization in tumors, which may advance the differential diagnosis. OBSERVATIONS: A 25-year-old male presented after a seizure. Computed tomography (CT) and MRI demonstrated a partially enhancing lesion with microcalcifications and vasogenic edema. Follow-up rCBV assessment demonstrated mild hyperperfusion and/or small vessels at the lesional margins consistent with either an intermediate grade glioma or infection. Given the radiological equipoise, surgical accessibility, and differential diagnosis including primary neoplasm, metastatic disease, NCC, and abscess, resection was pursued. The calcified mass was excised en bloc and was confirmed as larval-stage NCC. LESSONS: CT or MRI may not always provide sufficient information to distinguish NCC from brain tumors. Although reports have suggested that rCBV may aid in identifying NCC, here the authors describe a case of pathologically confirmed NCC in which preoperative, qualitative, standardized rCBV findings raised concern for a primary neoplasm. This case documents the first standardized rCBV values reported in a pathologically confirmed case of NCC in the United States.

A cross-sectional study to test equivalence of low- versus intermediate-flip angle dynamic susceptibility contrast MRI measures of relative cerebral blood volume in patients with high-grade gliomas at 1.5 Tesla field strength.

Introduction: 1.5 Tesla (1.5T) remain a significant field strength for brain imaging worldwide. Recent computer simulations and clinical studies at 3T MRI have suggested that dynamic susceptibility contrast (DSC) MRI using a 30° flip angle ("low-FA") with model-based leakage correction and no gadolinium-based contrast agent (GBCA) preload provides equivalent relative cerebral blood volume (rCBV) measurements to the reference-standard acquisition using a single-dose GBCA preload with a 60° flip angle ("intermediate-FA") and model-based leakage correction. However, it remains unclear whether this holds true at 1.5T. The purpose of this study was to test this at 1.5T in human high-grade glioma (HGG) patients. Methods: This was a single-institution cross-sectional study of patients who had undergone 1.5T MRI for HGG. DSC-MRI consisted of gradient-echo echo-planar imaging (GRE-EPI) with a low-FA without preload (30°/P-); this then subsequently served as a preload for the standard intermediate-FA acquisition (60°/P+). Both normalized (nrCBV) and standardized relative cerebral blood volumes (srCBV) were calculated using model-based leakage correction (C+) with IBNeuro™ software. Whole-enhancing lesion mean and median nrCBV and srCBV from the low- and intermediate-FA methods were compared using the Pearson's, Spearman's and intraclass correlation coefficients (ICC). Results: Twenty-three HGG patients composing a total of 31 scans were analyzed. The Pearson and Spearman correlations and ICCs between the 30°/P-/C+ and 60°/P+/C+ acquisitions demonstrated high correlations for both mean and median nrCBV and srCBV. Conclusion: Our study provides preliminary evidence that for HGG patients at 1.5T MRI, a low FA, no preload DSC-MRI acquisition can be an appealing alternative to the reference standard higher FA acquisition that utilizes a preload.

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.

Advanced MR Techniques for Preoperative Glioma Characterization: Part 2.

Preoperative clinical MRI protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this second part, we review magnetic resonance spectroscopy (MRS), chemical exchange saturation transfer (CEST), susceptibility-weighted imaging (SWI), MRI-PET, MR elastography (MRE), and MR-based radiomics applications. The first part of this review addresses dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) MRI, arterial spin labeling (ASL), diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting (MRF). EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

Early post-bevacizumab change in rCBV from DSC-MRI identifies pseudoresponse in recurrent glioblastoma: Results from ACRIN 6677/RTOG 0625.

Background: Progressive enhancement predicted poor survival in ACRIN 6677/RTOG 0625, a multi-center trial of bevacizumab with irinotecan or temozolomide in recurrent glioblastoma, but pseudoresponse likely limited enhancement-based survival prognostication in T1 non-progressors. We aimed to determine whether early change in cerebral blood volume from baseline (ΔCBV) could further stratify the T1 non-progressors according to overall (OS) and progression-free (PFS) survival. Methods: 37/123 enrolled patients had DSC-MRI, including 13, 15, and 8 patients without 2D-T1 progression at 2, 8, and 16 weeks post-treatment initiation, respectively. Mean CBV normalized to white matter (nRCBV) and mean standardized CBV (sRCBV) were extracted from enhancing tumor. ROC curves were derived for ΔCBV using six-month PFS and one-year OS as reference standards. Kaplan-Meier survival estimates and log-rank test compared PFS and OS for both ΔCBV (increase vs. decrease) and T1 response status (stable vs. decreasing enhancement). Results: PFS and OS were significantly worse for increasing CBV at 2 weeks (p=0.003 and p=0.002 for nRCBV, and p=0.03 and p=0.03 for sRCBV, respectively), but not for 2D-T1 patients with stable vs. decreasing enhancement (p=0.44 and p=0.86, respectively). ΔCBV at week 2 was also a good prognostic marker for OS-1 and PFS-6 using ROC analysis. By contrast, 2D-T1 response status at weeks 2, 8, and 16 was not associated with PFS-6. ΔCBV at 16 weeks (p=0.008 for sRCBV) but not 8 weeks (p=0.74 for nRCBV and p=0.56 for sRCBV) was associated with significant difference in median survival, but no difference in survival was observed for 2D-T1 patients with stable vs. decreasing enhancement at 8 weeks (p=0.69) or 16 weeks (p=0.21). At 16 weeks, OS did not differ significantly between 2D-T1 progressors and 2D-T1 non-progressors with increasing CBV (median survival 3.3 months post week 16 scan vs. 9.2 months, respectively; p=0.13), suggesting that 2D-T1 non-progressors with increasing CBV may have a prognosis like that of 2D-T1 progressors. Conclusion: After 2 weeks of anti-angiogenic therapy, ΔCBV in 2D-T1 non-progressors significantly prognosticated PFS and OS, whereas 2D-T1 response status did not, identifying a subpopulation that benefits from bevacizumab. Combining 2D-T1 progression and ΔCBV may yield a response assessment paradigm with 3-tiered OS stratification.

Potent in vivo efficacy of oral gallium maltolate in treatment-resistant glioblastoma.

Background: Treatment-resistant glioblastoma (trGBM) is an aggressive brain tumor with a dismal prognosis, underscoring the need for better treatment options. Emerging data indicate that trGBM iron metabolism is an attractive therapeutic target. The novel iron mimetic, gallium maltolate (GaM), inhibits mitochondrial function via iron-dependent and -independent pathways. Methods: In vitro irradiated adult GBM U-87 MG cells were tested for cell viability and allowed to reach confluence prior to stereotactic implantation into the right striatum of male and female athymic rats. Advanced MRI at 9.4T was carried out weekly starting two weeks after implantation. Daily oral GaM (50mg/kg) or vehicle were provided on tumor confirmation. Longitudinal MRI parameters were processed for enhancing tumor ROIs in OsiriX 8.5.1 (lite) with Imaging Biometrics Software (Imaging Biometrics LLC). Statistical analyses included Cox proportional hazards regression models, Kaplan-Meier survival plots, linear mixed model comparisons, and t-statistic for slopes comparison as indicator of tumor growth rate. Results: In this study we demonstrate non-invasively, using longitudinal MRI surveillance, the potent antineoplastic effects of GaM in a novel rat xenograft model of trGBM, as evidenced by extended suppression of tumor growth (23.56 mm3/week untreated, 5.76 mm3/week treated, P < 0.001), a blunting of tumor perfusion, and a significant survival benefit (median overall survival: 30 days untreated, 56 days treated; P < 0.001). The therapeutic effect was confirmed histologically by the presence of abundant cytotoxic cellular swelling, a significant reduction in proliferation markers (P < 0.01), and vessel normalization characterized by prominent vessel pruning, loss of branching, and uniformity of vessel lumina. Xenograft tumors in the treatment group were further characterized by an absence of an invasive edge and a significant reduction in both, MIB-1% and mitotic index (P < 0.01 each). Transferrin receptor and ferroportin expression in GaM-treated tumors illustrated cellular iron deprivation. Additionally, treatment with GaM decreased the expression of pro-angiogenic markers (von Willebrand Factor and VEGF) and increased the expression of anti-angiogenic markers, such as Angiopoietin-2. Conclusion: Monotherapy with the iron-mimetic GaM profoundly inhibits trGBM growth and significantly extends disease-specific survival in vivo.

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.

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.

Basal Ganglia Iron Content Increases with Glioma Severity Using Quantitative Susceptibility Mapping: A Potential Biomarker of Tumor Severity.

BACKGROUND AND PURPOSE: Gliomas have been found to alter iron metabolism and transport in ways that result in an expansion of their intracellular iron compartments to support aggressive tumor growth. This study used deep neural network trained quantitative susceptibility mapping to assess basal ganglia iron concentrations in glioma patients. MATERIALS AND METHODS: Ninety-two patients with brain lesions were initially enrolled in this study and fifty-nine met the inclusion criteria. Susceptibility-weighted images were collected at 3.0 T and used to construct quantitative susceptibility maps via a deep neural network-based method. The regions of interest were manually drawn within basal ganglia structures and the mean voxel intensities were extracted and averaged across multiple slices. One-way ANCOVA tests were conducted to compare the susceptibility values of groups of patients based on tumor grade while controlling for age, sex, and tumor type. RESULTS: The mean basal ganglia susceptibility for patients with grade IV tumors was higher than that for patients with grade II tumors (p = 0.00153) and was also higher for patients with grade III tumors compared to patients with grade II tumors (p = 0.020), after controlling for age, sex, and tumor type. Patient age influenced susceptibility values (p = 0.00356), while sex (p = 0.69) and tumor type (p = 0.11) did not. CONCLUSIONS: The basal ganglia iron content increased with glioma severity. Basal ganglia iron levels may thus be a useful biomarker in glioma prognosis and treatment, especially with regard to iron-based cancer therapies.

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.

Multi-Site Concordance of Diffusion-Weighted Imaging Quantification for Assessing Prostate Cancer Aggressiveness.

BACKGROUND: Diffusion-weighted imaging (DWI) is commonly used to detect prostate cancer, and a major clinical challenge is differentiating aggressive from indolent disease. PURPOSE: To compare 14 site-specific parametric fitting implementations applied to the same dataset of whole-mount pathologically validated DWI to test the hypothesis that cancer differentiation varies with different fitting algorithms. STUDY TYPE: Prospective. POPULATION: Thirty-three patients prospectively imaged prior to prostatectomy. FIELD STRENGTH/SEQUENCE: 3 T, field-of-view optimized and constrained undistorted single-shot DWI sequence. ASSESSMENT: Datasets, including a noise-free digital reference object (DRO), were distributed to the 14 teams, where locally implemented DWI parameter maps were calculated, including mono-exponential apparent diffusion coefficient (MEADC), kurtosis (K), diffusion kurtosis (DK), bi-exponential diffusion (BID), pseudo-diffusion (BID*), and perfusion fraction (F). The resulting parametric maps were centrally analyzed, where differentiation of benign from cancerous tissue was compared between DWI parameters and the fitting algorithms with a receiver operating characteristic area under the curve (ROC AUC). STATISTICAL TEST: Levene's test, P < 0.05 corrected for multiple comparisons was considered statistically significant. RESULTS: The DRO results indicated minimal discordance between sites. Comparison across sites indicated that K, DK, and MEADC had significantly higher prostate cancer detection capability (AUC range = 0.72-0.76, 0.76-0.81, and 0.76-0.80 respectively) as compared to bi-exponential parameters (BID, BID*, F) which had lower AUC and greater between site variation (AUC range = 0.53-0.80, 0.51-0.81, and 0.52-0.80 respectively). Post-processing parameters also affected the resulting AUC, moving from, for example, 0.75 to 0.87 for MEADC varying cluster size. DATA CONCLUSION: We found that conventional diffusion models had consistent performance at differentiating prostate cancer from benign tissue. Our results also indicated that post-processing decisions on DWI data can affect sensitivity and specificity when applied to radiological-pathological studies in prostate cancer. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 3.

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.

Assessment of tumor hypoxia and perfusion in recurrent glioblastoma following bevacizumab failure using MRI and 18F-FMISO PET.

Tumoral hypoxia correlates with worse outcomes in glioblastoma (GBM). While bevacizumab is routinely used to treat recurrent GBM, it may exacerbate hypoxia. Evofosfamide is a hypoxia-targeting prodrug being tested for recurrent GBM. To characterize resistance to bevacizumab and identify those with recurrent GBM who may benefit from evofosfamide, we ascertained MRI features and hypoxia in patients with GBM progression receiving both agents. Thirty-three patients with recurrent GBM refractory to bevacizumab were enrolled. Patients underwent MR and 18F-FMISO PET imaging at baseline and 28 days. Tumor volumes were determined, MRI and 18F-FMISO PET-derived parameters calculated, and Spearman correlations between parameters assessed. Progression-free survival decreased significantly with hypoxic volume [hazard ratio (HR) = 1.67, 95% confidence interval (CI) 1.14 to 2.46, P = 0.009] and increased significantly with time to the maximum value of the residue (Tmax) (HR = 0.54, 95% CI 0.34 to 0.88, P = 0.01). Overall survival decreased significantly with hypoxic volume (HR = 1.71, 95% CI 1.12 to 12.61, p = 0.01), standardized relative cerebral blood volume (srCBV) (HR = 1.61, 95% CI 1.09 to 2.38, p = 0.02), and increased significantly with Tmax (HR = 0.31, 95% CI 0.15 to 0.62, p < 0.001). Decreases in hypoxic volume correlated with longer overall and progression-free survival, and increases correlated with shorter overall and progression-free survival. Hypoxic volume and volume ratio were positively correlated (rs = 0.77, P < 0.0001), as were hypoxia volume and T1 enhancing tumor volume (rs = 0.75, P < 0.0001). Hypoxia is a key biomarker in patients with bevacizumab-refractory GBM. Hypoxia and srCBV were inversely correlated with patient outcomes. These radiographic features may be useful in evaluating treatment and guiding treatment considerations.

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 2: Spectroscopy, Chemical Exchange Saturation, Multiparametric Imaging, and Radiomics.

Objective: To summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and to highlight the latest bench-to-bedside developments. Methods: The current evidence regarding the potential for monitoring biomarkers was reviewed and individual modalities of metabolism and/or chemical composition imaging discussed. Perfusion, permeability, and microstructure imaging were similarly analyzed in Part 1 of this two-part review article and are valuable reading as background to this article. We appraise the clinic readiness of all the individual modalities and consider methodologies involving machine learning (radiomics) and the combination of MRI approaches (multiparametric imaging). Results: The biochemical composition of high-grade gliomas is markedly different from healthy brain tissue. Magnetic resonance spectroscopy allows the simultaneous acquisition of an array of metabolic alterations, with choline-based ratios appearing to be consistently discriminatory in treatment response assessment, although challenges remain despite this being a mature technique. Promising directions relate to ultra-high field strengths, 2-hydroxyglutarate analysis, and the use of non-proton nuclei. Labile protons on endogenous proteins can be selectively targeted with chemical exchange saturation transfer to give high resolution images. The body of evidence for clinical application of amide proton transfer imaging has been building for a decade, but more evidence is required to confirm chemical exchange saturation transfer use as a monitoring biomarker. Multiparametric methodologies, including the incorporation of nuclear medicine techniques, combine probes measuring different tumor properties. Although potentially synergistic, the limitations of each individual modality also can be compounded, particularly in the absence of standardization. Machine learning requires large datasets with high-quality annotation; there is currently low-level evidence for monitoring biomarker clinical application. Conclusion: Advanced MRI techniques show huge promise in treatment response assessment. The clinical readiness analysis highlights that most monitoring biomarkers require standardized international consensus guidelines, with more facilitation regarding technique implementation and reporting in the clinic.

Value of dynamic contrast perfusion MRI to predict early response to bevacizumab in newly diagnosed glioblastoma: results from ACRIN 6686 multicenter trial.

BACKGROUND: In Radiation Therapy Oncology Group (RTOG) 0825, a phase III trial of standard therapy with bevacizumab or without (placebo) in newly diagnosed glioblastoma, 44 patients underwent dynamic contrast enhanced (DCE) and/or dynamic susceptibility contrast (DSC) MRI in the American College of Radiology Imaging Network (ACRIN) trial 6686. The association between early changes in relative cerebral blood volume (rCBV) and volume transfer constant (Ktrans) with overall survival (OS) was evaluated. METHODS: MRI was performed at postop baseline (S0), immediately before (S1), 1 day after (S2), and 7 weeks after (S3) bevacizumab or placebo initiation. Mean normalized and standardized rCBV (nRCBV, sRCBV) and Ktrans were measured within contrast-enhancing lesion. Wilcoxon rank sum tests compared parameter changes from S1-S2 and S1-S3. Association with OS and progression-free survival (PFS) were determined using Kaplan-Meier and log-rank tests. Treatment response for groups stratified by pretreatment nRCBV (S0, S1) was explored. The intraclass correlation coefficient and repeatability coefficient for the placebo arm (S1-S2) were used to assess repeatability. RESULTS: Evaluable were 27-36 datasets per time point. Significant differences between treatment arms were found for changes in nRCBV and sRCBV from S1-S2 and S1-S3, and in Ktrans for S1-S3. Improved PFS (P = 0.05) but not OS (P = 0.46) was observed. High pretreatment rCBV predicted improved OS for bevacizumab-treated patients. Based on the intraclass correlation coefficient, sRCBV (0.92) was more repeatable than nRCBV (0.71) and Ktrans (0.75), consistent with repeatability coefficient values. CONCLUSIONS: Bevacizumab significantly changes rCBV but not Ktrans as early as 1 day posttreatment in newly diagnosed glioblastoma unrelated to outcomes. Improvements in clinical trial design to maximize rCBV benefit are indicated.