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BACKGROUND Tumor-associated macrophages (TAMs) are a key component of glioblastoma (GBM) tumor microenvironment. Considering the differential role of different TAM phenotypes in iron metabolism with the M1 phenotype storing intracellular iron, and M2 phenotype releasing iron in the tumor microenvironment, here we investigated non-invasive quantitative susceptibility mapping (QSM) and T2* MRI relaxometry to quantify iron as imaging biomarkers for TAMs in adult patients with GBM. METHODS In this prospective study, 21 adult patients with GBM were enrolled between 2016 to 2019. Patients underwent a 3D single echo gradient echo sequence in addition to standard anatomical sequences on a 3 Tesla MRI. QSM images were reconstructed using the morphology-enabled dipole inversion (MEDI) algorithm. In 3 subjects, ex vivo imaging of surgical specimens was performed on a Bruker 9.4 Tesla 8.9 cm vertical bore MR using 3D multi-echo GRE scans, and R2* (1/T2*) maps were generated by a pixel-wise monoexponential fitting. Each specimen was stained with hematoxylin and eosin, as well as with CD68, CD86, CD206, and L-Ferritin. RESULTS Significant positive correlation was observed between mean susceptibility for the tumor enhancing zone and the L-ferritin positivity percent (r =0.56, p=0.018) and the combination of tumor’s enhancing zone and necrotic core and the L-Ferritin positivity percent (r=0.72; p=0.001). Moreover, the mean susceptibility significantly correlated with positivity percent for CD68 (ρ=0.52, p=0.034) and CD86 (r=0.7 p=0.001), but not for CD206 (ρ=0.09; p=0.7). There was a positive correlation between mean R2* values and CD68 positive cell counts (r =0.6, p=0.016). Similarly, mean R2* values significantly correlated with CD86 (r=0.54, p=0.03) but not with CD206 (r=0.15, p=0.5). High mean susceptibility in the necrotic core was associated with inferior PFS (hazard ratio,4.5, p=0.016). CONCLUSION MR Susceptibility Imaging can quantify the iron content of GBM and provide a non-invasive method for TAM quantification and phenotyping.

Glioblastoma (GBM) has high metabolic demands, which can lead to acidification of the tumor microenvironment. We hypothesize that a machine learning model built on temporal principal component analysis (PCA) of dynamic susceptibility contrast-enhanced (DSC) perfusion MRI can be used to estimate tumor acidity in GBM, as estimated by pH-sensitive amine chemical exchange saturation transfer echo-planar imaging (CEST-EPI). We analyzed 78 MRI scans in 32 treatment naïve and post-treatment GBM patients. All patients were imaged with DSC-MRI, and pH-weighting that was quantified from CEST-EPI estimation of the magnetization transfer ratio asymmetry (MTRasym) at 3 ppm. Enhancing tumor (ET), non-enhancing core (NC), and peritumoral T2 hyperintensity (namely, edema, ED) were used to extract principal components (PCs) and to build support vector machines regression (SVR) models to predict MTRasym values using PCs. Our predicted map correlated with MTRasym values with Spearman’s r equal to 0.66, 0.47, 0.67, 0.71, in NC, ET, ED, and overall, respectively (p

Background Plasma cell-free DNA (cfDNA) concentration is lower in glioblastoma (GBM) compared to other solid tumors, which can lead to low circulating tumor DNA (ctDNA) detection. In this study, we investigated the relationship between multimodality magnetic resonance imaging (MRI) and histopathologic features with plasma cfDNA concentration and ctDNA detection in patients with treatment-naive GBM. Methods We analyzed plasma cfDNA concentration, MRI scans, and tumor histopathology from 42 adult patients with newly diagnosed GBM. Linear regression analysis was used to examine the relationship of plasma cfDNA concentration before surgery to imaging and histopathologic characteristics. In a subset of patients, imaging and histopathologic metrics were also compared between patients with and without a detected tumor somatic mutation. Results Tumor volume with elevated (>1.5 times contralateral white matter) rate transfer constant (Kep, a surrogate of blood–brain barrier [BBB] permeability) was independently associated with plasma cfDNA concentration (P = .001). Histopathologic characteristics independently associated with plasma cfDNA concentration included CD68+ macrophage density (P = .01) and size of tumor vessels (P = .01). Patients with higher (grade ≥3) perivascular CD68+ macrophage density had lower volume transfer constant (Ktrans, P = .01) compared to those with lower perivascular CD68+ macrophage density. Detection of at least 1 somatic mutation in plasma cfDNA was associated with significantly lower perivascular CD68+ macrophages (P = .01). Conclusions Metrics of BBB disruption and quantity and distribution of tumor-associated macrophages are associated with plasma cfDNA concentration and ctDNA detection in GBM patients. These findings represent an important step in understanding the factors that determine plasma cfDNA concentration and ctDNA detection.

BACKGROUND: Over the last quarter-century, the number of publications using vessel wall MR imaging has increased. Although many narrative reviews offer insight into technique and diagnostic applications, a systematic review of publication trends and reporting quality has not been conducted to identify unmet needs and future directions. PURPOSE: We aimed to identify which intracranial vasculopathies need more data and to highlight areas of strengths and weaknesses in reporting. DATA SOURCES: PubMed, EMBASE, and MEDLINE databases were searched up to September 2018 in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. DATA ANALYSIS: Two independent reviewers screened and extracted data from 128 articles. The Strengthening the Reporting of Observational Studies in Epidemiology guidelines were used to assess the reporting quality of analytic observational studies. DATA SYNTHESIS: There has been an exponentially increasing trend in the number of vessel wall MR imaging publications during the past 24 years (P

BACKGROUND: Quantitative susceptibility mapping (QSM) uses prior information to reconstruct maps, but prior information may not show pathology and introduce inconsistencies with susceptibility maps, degrade image quality and inadvertently smoothing image features. PURPOSE: To develop a local field data-driven QSM reconstruction that does not depend on spatial edge prior information. STUDY TYPE: Retrospective. SUBJECTS, ANIMAL MODELS: A dataset from 2016 ISMRM QSM Challenge, 11 patients with glioblastoma, a patient with microbleeds and porcine heart. SEQUENCE/FIELD STRENGTH: 3D gradient echo sequence on 3T and 7T scanners. ASSESSMENT: Accuracy was compared to Calculation of Susceptibility through Multiple Orientation Sampling (COSMOS), and several published techniques using region of interest (ROI) measurements, root-mean-squared error (RMSE), structural similarity index metric (SSIM), and high-frequency error norm (HFEN). Numerical ranking and semiquantitative image grading was performed by three expert observers to assess overall image quality (IQ) and image sharpness (IS). STATISTICAL TESTS: Bland–Altman, Friedman test, and Conover multiple comparisons. RESULTS: Loss adaptive dipole inversion (LADI) (β = 0.82, R(2) = 0.96), morphology-enabled dipole inversion (MEDI) (β = 0.91, R(2) = 0.97), and fast nonlinear susceptibility inversion (FANSI) (β = 0.81, R(2) = 0.98) had excellent correlation with COSMOS and no bias was detected (bias = 0.006 ± 0.014, P < 0.05). In glioblastoma patients, LADI showed consistently better performance (IQ(Grade) = 2.6 ± 0.4, IS(Grade) = 2.6 ± 0.3, IQ(Rank) = 3.5 ± 0.4, IS(Rank) = 3.9 ± 0.2) compared with MEDI (IQ(Grade) = 2.1 ± 0.3, IS(Grade) = 2 ± 0.5, IQ(Rank) = 2.4 ± 0.5, IS(Rank) = 2.8 ± 0.2) and FANSI (IQ(Grade) = 2.2 ± 0.5, IS(Grade) = 2 ± 0.4, IQ(Rank) = 2.8 ± 0.3, IS(Rank) = 2.1 ± 0.2). Dark artifact visible near the infarcted region in MEDI (Inf(MEDI) = −0.27 ± 0.06 ppm) was better mitigated by FANSI (Inf(FANSI-TGV) = −0.17 ± 0.05 ppm) and LADI (Inf(LADI) = −0.18 ± 0.05 ppm). CONCLUSION: For neuroimaging applications, LADI preserved image sharpness and fine features in glioblastoma and microbleed patients. LADI performed better at mitigating artifacts in cardiac QSM. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY STAGE: 1

Purpose: The clinical utility of plasma cell-free DNA (cfDNA) has not been assessed prospectively in patients with glioblastoma (GBM). We aimed to determine the prognostic impact of plasma cfDNA in GBM, as well as its role as a surrogate of tumor burden and substrate for next-generation sequencing (NGS). Experimental Design: We conducted a prospective cohort study of 42 patients with newly diagnosed GBM. Plasma cfDNA was quantified at baseline prior to initial tumor resection and longitudinally during chemoradiotherapy. Plasma cfDNA was assessed for its association with progression-free survival (PFS) and overall survival (OS), correlated with radiographic tumor burden, and subjected to a targeted NGS panel. Results: Prior to initial surgery, GBM patients had higher plasma cfDNA concentration than age-matched healthy controls (mean 13.4 vs. 6.7 ng/mL, P < 0.001). Plasma cfDNA concentration was correlated with radiographic tumor burden on patients' first post-radiation magnetic resonance imaging scan (ρ = 0.77, P = 0.003) and tended to rise prior to or concurrently with radiographic tumor progression. Preoperative plasma cfDNA concentration above the mean (>13.4 ng/mL) was associated with inferior PFS (median 4.9 vs. 9.5 months, P = 0.038). Detection of ≥1 somatic mutation in plasma cfDNA occurred in 55% of patients and was associated with nonstatistically significant decreases in PFS (median 6.0 vs. 8.7 months, P = 0.093) and OS (median 5.5 vs. 9.2 months, P = 0.053). Conclusions: Plasma cfDNA may be an effective prognostic tool and surrogate of tumor burden in newly diagnosed GBM. Detection of somatic alterations in plasma is feasible when samples are obtained prior to initial surgical resection.

Glioblastoma (GBM) is the most common primary malignant brain tumor in adults and carries a dismal prognosis. Significant challenges in the care of patients with GBM include marked vascular heterogeneity and arteriovenous (AV) shunting, which results in tumor hypoxia and inadequate delivery of systemic treatments to reach tumor cells. In this study, we investigated the utility of different MR perfusion techniques to detect and quantify arteriovenous (AV) shunting and tumor hypoxia in patients with GBM. Macrovascular shunting was present in 33% of subjects, with the degree of shunting ranging from (37–60%) using arterial spin labeling perfusion. Among the dynamic susceptibility contrast-enhanced perfusion curve features, there were a strong negative correlation between hypoxia score, DSC perfusion curve recovery slope (r = −0.72, P = 0.018) and angle (r = −0.73, P = 0.015). The results of this study support the possibility of using arterial spin labeling and pattern analysis of dynamic susceptibility contrast-enhanced MR Imaging for evaluation of arteriovenous shunting and tumor hypoxia in glioblastoma.