Cross-vendor multiparametric mapping of the human brain using 3D-QALAS: A multicenter and multivendor study

PURPOSE

To evaluate a vendor-agnostic multiparametric mapping scheme based on 3D quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS) for whole-brain T1, T2, and proton density (PD) mapping.

METHODS

This prospective, multi-institutional study was conducted between September 2021 and February 2022 using five different 3T systems from four prominent MRI vendors. The accuracy of this technique was evaluated using a standardized MRI system phantom. Intra-scanner repeatability and inter-vendor reproducibility of T1, T2, and PD values were evaluated in 10 healthy volunteers (6 men; mean age ± SD, 28.0 ± 5.6 y) who underwent scan-rescan sessions on each scanner (total scans = 100). To evaluate the feasibility of 3D-QALAS, nine patients with multiple sclerosis (nine women; mean age ± SD, 48.2 ± 11.5 y) underwent imaging examination on two 3T MRI systems from different manufacturers.

RESULTS

Quantitative maps obtained with 3D-QALAS showed high linearity (R2  = 0.998 and 0.998 for T1 and T2, respectively) with respect to reference measurements. The mean intra-scanner coefficients of variation for each scanner and structure ranged from 0.4% to 2.6%. The mean structure-wise test-retest repeatabilities were 1.6%, 1.1%, and 0.7% for T1, T2, and PD, respectively. Overall, high inter-vendor reproducibility was observed for all parameter maps and all structure measurements, including white matter lesions in patients with multiple sclerosis.

CONCLUSION

The vendor-agnostic multiparametric mapping technique 3D-QALAS provided reproducible measurements of T1, T2, and PD for human tissues within a typical physiological range using 3T scanners from four different MRI manufacturers.

Noninvasive Magnetic Resonance Imaging Measures of Glymphatic System Activity

The comprehension of the glymphatic system, a postulated mechanism responsible for the removal of interstitial solutes within the central nervous system (CNS), has witnessed substantial progress recently. While direct measurement techniques involving fluorescence and contrast agent tracers have demonstrated success in animal studies, their application in humans is invasive and presents challenges. Hence, exploring alternative noninvasive approaches that enable glymphatic research in humans is imperative. This review primarily focuses on several noninvasive magnetic resonance imaging (MRI) techniques, encompassing perivascular space (PVS) imaging, diffusion tensor image analysis along the PVS, arterial spin labeling, chemical exchange saturation transfer, and intravoxel incoherent motion. These methodologies provide valuable insights into the dynamics of interstitial fluid, water permeability across the blood-brain barrier, and cerebrospinal fluid flow within the cerebral parenchyma. Furthermore, the review elucidates the underlying concept and clinical applications of these noninvasive MRI techniques, highlighting their strengths and limitations. It addresses concerns about the relationship between glymphatic system activity and pathological alterations, emphasizing the necessity for further studies to establish correlations between noninvasive MRI measurements and pathological findings. Additionally, the challenges associated with conducting multisite studies, such as variability in MRI systems and acquisition parameters, are addressed, with a suggestion for the use of harmonization methods, such as the combined association test (COMBAT), to enhance standardization and statistical power. Current research gaps and future directions in noninvasive MRI techniques for assessing the glymphatic system are discussed, emphasizing the need for larger sample sizes, harmonization studies, and combined approaches. In conclusion, this review provides invaluable insights into the application of noninvasive MRI methods for monitoring glymphatic system activity in the CNS. It highlights their potential in advancing our understanding of the glymphatic system, facilitating clinical applications, and paving the way for future research endeavors in this field. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 5.

The glymphatic system as a potential biomarker and therapeutic target in secondary progressive multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) is a refractory immune-mediated inflammatory disease of the central nervous system, and some cases of the major subtype, relapsing-remitting (RR), transition to secondary progressive (SP). However, the detailed pathogenesis, biomarkers, and effective treatment strategies for secondary progressive multiple sclerosis have not been established. The glymphatic system, which is responsible for waste clearance in the brain, is an intriguing avenue for investigation and is primarily studied through diffusion tensor image analysis along the perivascular space (DTI-ALPS). This study aimed to compare DTI-ALPS indices between patients with RRMS and SPMS to uncover potential differences in their pathologies and evaluate the utility of the glymphatic system as a possible biomarker.

METHODS

A cohort of 26 patients with MS (13 RRMS and 13 SPMS) who met specific criteria were enrolled in this prospective study. Magnetic resonance imaging (MRI), including diffusion MRI, 3D T1-weighted imaging, and relaxation time quantification, was conducted. The ALPS index, a measure of glymphatic function, was calculated using diffusion-weighted imaging data. Demographic variables, MRI metrics, and ALPS indices were compared between patients with RRMS and those with SPMS.

RESULTS

The ALPS index was significantly lower in the SPMS group. Patients with SPMS exhibited longer disease duration and higher Expanded Disability Status Scale (EDSS) scores than those with RRMS. Despite these differences, the correlations between the EDSS score, disease duration, and ALPS index were minimal, suggesting that the impact of these clinical variables on ALPS index variations was negligible.

DISCUSSION

Our study revealed the potential microstructural and functional differences between RRMS and SPMS related to glymphatic system impairment. Although disease severity and duration vary among subtypes, their influence on ALPS index differences appears to be limited. This highlights the stronger association between SP conversion and changes in the ALPS index. These findings align with those of previous research, indicating the involvement of the glymphatic system in the progression of MS.

CONCLUSION

Although the causality remains uncertain, our study suggests that a reduced ALPS index, reflecting glymphatic system dysfunction, may contribute to MS progression, particularly in SPMS. This suggests the potential of the ALPS index as a diagnostic biomarker for SPMS and underscores the potential of the glymphatic system as a therapeutic target to mitigate MS progression. Future studies with larger cohorts and pathological validation are necessary to confirm these findings. This study provides new insights into the pathogenesis of SPMS and the potential for innovative therapeutic strategies.

Reduced Diffusivity Along Perivascular Spaces on Magnetic Resonance Imaging Associated with Younger Age of First Use and Cognitive Impairment in Recreational Marijuana Users

BACKGROUND AND PURPOSE: The impairment of the glymphatic system, a perivascular network crucial for brain waste clearance, has been linked to cognitive impairment, potentially attributed to the accumulation of brain waste. Although marijuana use has been associated with poorer cognitive performance, particularly in adolescents, its influence on the glymphatic system remains unexplored. This study evaluated the influence of the age of first marijuana use and the total number of lifetime uses on the glymphatic system, measured using the index of diffusion tensor imaging along the perivascular space (DTI-ALPS). Furthermore, we explored the correlation between glymphatic clearance and cognitive performance among marijuana users.MATERIALS AND METHODS: In this study, 125 individuals who reported using marijuana at least once in their lifetime (43 men; mean age, 28.60 ± 3.84 years) and 125 individuals with zero lifetime cannabis use (nonusers; 44 men; mean age, 28.82 ± 3.56 years) were assessed. ALPS indices of all study participants were calculated using 3T diffusion MRI data (b = 1,000 s/mm2).RESULTS: After adjusting for age, sex, education years, Pittsburgh Sleep Quality Index, alcohol use, tobacco use, and intracranial volume, our analysis using a univariate general linear model revealed no significant difference in the ALPS index among nonusers and marijuana users with different ages of first use or various frequencies of lifetime usage. However, in marijuana users, multiple linear regression analyses showed associations between a lower ALPS index and earlier age of first marijuana use (standardized β, -0.20; P = 0.041), lower accuracy in the working memory 0-back task (standardized β, 0.20; P = 0.042), and fewer correct responses in the fluid intelligence test (standardized β, 0.19; P = 0.045).CONCLUSIONS: This study shows the potential use of DTI-ALPS as a noninvasive indirect indicator of the glymphatic clearance in young adults. Our findings show novel adverse effects of younger age at first use of marijuana on glymphatic system function, which is associated with impaired working memory and fluid intelligence. Gaining insights into alterations in glymphatic function following marijuana use could initiate novel strategies to reduce risk of cognitive impairment.ABBREVIATIONS: ALPS = Along the perivascular space; FA = Fractional anisotropy; ICV = Intracranial volume; ISF = Interstitial fluid; MLR = Multiple linear regression; PSQI = Pittsburgh Sleep Quality Index; ROI = Region of interest; SSAGA = Semi-Structured Assessment for the Genetics of Alcoholism; VIF = Variance inflation factor.

Diffusion histogram profiles predict molecular features of grade 4 in histologically lower-grade adult diffuse gliomas following WHO classification 2021

OBJECTIVES

In the latest World Health Organization classification 2021, grade 4 adult diffuse gliomas can be diagnosed with several molecular features even without histological evidence of necrosis or microvascular proliferation. We aimed to explore whole tumor histogram-derived apparent diffusion coefficient (ADC) histogram profiles for differentiating between the presence (Mol-4) and absence (Mol-2/3) of grade 4 molecular features in histologically lower-grade gliomas.

METHODS

Between June 2019 and October 2022, 184 adult patients with diffuse gliomas underwent MRI. After excluding 121 patients, 18 (median age, 64.5 [range, 37-84 years]) Mol-4 and 45 (median 40 [range, 18-73] years) Mol-2/3 patients with histologically lower-grade gliomas were enrolled. Whole tumor volume-of-interest-derived ADC histogram profiles were calculated and compared between the two groups. Stepwise logistic regression analysis with Akaike's information criterion using the ADC histogram profiles with p values < 0.01 and age at diagnosis was used to identify independent variables for predicting the Mol-4 group.

RESULTS

The 90th percentile (p < 0.001), median (p < 0.001), mean (p < 0.001), 10th percentile (p = 0.014), and entropy (p < 0.001) of normalized ADC were lower, and kurtosis (p < 0.001) and skewness (p = 0.046) were higher in the Mol-4 group than in the Mol-2/3 group. Multivariate logistic regression analysis revealed that the entropy of normalized ADC and age at diagnosis were independent predictive parameters for the Mol-4 group with an area under the curve of 0.92.

CONCLUSION

ADC histogram profiles may be promising preoperative imaging biomarkers to predict molecular grade 4 among histologically lower-grade adult diffuse gliomas.

CLINICAL RELEVANCE STATEMENT

This study highlighted the diagnostic usefulness of ADC histogram profiles to differentiate histologically lower grade adult diffuse gliomas with the presence of molecular grade 4 features and those without.

KEY POINTS

• ADC histogram profiles to predict molecular CNS WHO grade 4 status among histologically lower-grade adult diffuse gliomas were evaluated. • Entropy of ADC and age were independent predictive parameters for molecular grade 4 status. • ADC histogram analysis is useful for predicting molecular grade 4 among histologically lower-grade gliomas.

Advancements in Diffusion MRI Tractography for Neurosurgery

ABSTRACT

Diffusion magnetic resonance imaging tractography is a noninvasive technique that enables the visualization and quantification of white matter tracts within the brain. It is extensively used in preoperative planning for brain tumors, epilepsy, and functional neurosurgical procedures such as deep brain stimulation. Over the past 25 years, significant advancements have been made in imaging acquisition, fiber direction estimation, and tracking methods, resulting in considerable improvements in tractography accuracy. The technique enables the mapping of functionally critical pathways around surgical sites to avoid permanent functional disability. When the limitations are adequately acknowledged and considered, tractography can serve as a valuable tool to safeguard critical white matter tracts and provides insight regarding changes in normal white matter and structural connectivity of the whole brain beyond local lesions. In functional neurosurgical procedures such as deep brain stimulation, it plays a significant role in optimizing stimulation sites and parameters to maximize therapeutic efficacy and can be used as a direct target for therapy. These insights can aid in patient risk stratification and prognosis. This article aims to discuss state-of-the-art tractography methodologies and their applications in preoperative planning and highlight the challenges and new prospects for the use of tractography in daily clinical practice.

Single-nucleus expression characterization of non-enhancing region of recurrent high-grade glioma

Background

Non-enhancing (NE) infiltrating tumor cells beyond the contrast-enhancing (CE) bulk of tumor are potential propagators of recurrence after gross total resection of high-grade glioma.

Methods

We leveraged single-nucleus RNA sequencing on 15 specimens from recurrent high-grade gliomas (n = 5) to compare prospectively identified biopsy specimens acquired from CE and NE regions. Additionally, 24 CE and 22 NE biopsies had immunohistochemical staining to validate RNA findings.

Results

Tumor cells in NE regions are enriched in neural progenitor cell-like cellular states, while CE regions are enriched in mesenchymal-like states. NE glioma cells have similar proportions of proliferative and putative glioma stem cells relative to CE regions, without significant differences in % Ki-67 staining. Tumor cells in NE regions exhibit upregulation of genes previously associated with lower grade gliomas. Our findings in recurrent GBM paralleled some of the findings in a re-analysis of a dataset from primary GBM. Cell-, gene-, and pathway-level analyses of the tumor microenvironment in the NE region reveal relative downregulation of tumor-mediated neovascularization and cell-mediated immune response, but increased glioma-to-nonpathological cell interactions.

Conclusions

This comprehensive analysis illustrates differing tumor and nontumor landscapes of CE and NE regions in high-grade gliomas, highlighting the NE region as an area harboring likely initiators of recurrence in a pro-tumor microenvironment and identifying possible targets for future design of NE-specific adjuvant therapy. These findings also support the aggressive approach to resection of tumor-bearing NE regions.

Glymphatic System Dysfunction in Myelin Oligodendrocyte Glycoprotein Immunoglobulin G Antibody-Associated Disorders: Association with Clinical Disability

BACKGROUND AND PURPOSE

Impaired glymphatic function has been suggested to be implicated in the pathophysiology of MS and aquaporin-4 immunoglobulin G-positive neuromyelitis optica spectrum disorder. This study aimed to investigate the interstitial fluid dynamics in the brain in patients with myelin oligodendrocyte glycoprotein antibody disorders (MOGAD), another demyelinating disorder, using a noninvasive imaging technique called the diffusivity along the perivascular space (ALPS) index.

MATERIALS AND METHODS

A prospective study was conducted on 16 patients with MOGAD in remission and 22 age- and sex-matched healthy control subjects. MR imaging was performed using a 3T scanner, and the ALPS index was calculated using diffusion MR imaging data with a b-value of 1000 s/mm2. The ALPS index and gray matter volumes were compared between the 2 groups, and these parameters were correlated with the Expanded Disability Status Scale.

RESULTS

The mean ALPS index of patients with MOGAD was significantly lower than that of healthy controls (Cohen d = 0.93, false discovery rate-corrected P = .02). The lower mean ALPS index was significantly associated with a worse Expanded Disability Status Scale score (Spearman ρ = -0.51; 95% CI, -0.85 to -0.02; P = .03). However, cortical volume and deep gray matter volume were not significantly different between the 2 groups, and they were not correlated with the Expanded Disability Status Scale.

CONCLUSIONS

This study suggests that patients with MOGAD may have impaired glymphatic function, as measured by the ALPS index, which is associated with patient disability. Further study is warranted with a larger sample size.

Traveling Subject-Informed Harmonization Increases Reliability of Brain Diffusion Tensor and Neurite Mapping

Diffusion-weighted magnetic resonance imaging (dMRI) of brain has helped elucidate the microstructural changes of psychiatric and neurodegenerative disorders. Inconsistency between MRI models has hampered clinical application of dMRI-based metrics. Using harmonized dMRI data of 300 scans from 69 traveling subjects (TS) scanning the same individuals at multiple conditions with 13 MRI models and 2 protocols, the widely-used metrics such as diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) were evaluated before and after harmonization with a combined association test (ComBat) or TS-based general linear model (TS-GLM). Results showed that both ComBat and TS-GLM significantly reduced the effects of the MRI site, model, and protocol for diffusion metrics while maintaining the intersubject biological effects. The harmonization power of TS-GLM based on TS data model is more powerful than that of ComBat. In conclusion, our research demonstrated that although ComBat and TS-GLM harmonization approaches were effective at reducing the scanner effects of the site, model, and protocol for DTI and NODDI metrics in WM, they exhibited high retainability of biological effects. Therefore, we suggest that, after harmonizing DTI and NODDI metrics, a multisite study with large cohorts can accurately detect small pathological changes by retaining pathological effects.

Fiber-Specific White Matter Alterations in Parkinson's Disease Patients with GBA Gene Mutations

BACKGROUND

Patients with Parkinson's disease (PD) carrying GBA gene mutations (GBA-PD) have a more aggressive disease course than those with idiopathic PD (iPD).

OBJECTIVE

The objective of this study was to investigate fiber-specific white matter (WM) differences in nonmedicated patients with early-stage GBA-PD and iPD using fixel-based analysis, a novel technique to assess tract-specific WM microstructural and macrostructural features comprehensively.

METHODS

Fixel-based metrics, including microstructural fiber density (FD), macrostructural fiber-bundle cross section (FC), and a combination of FD and FC (FDC), were compared among 30 healthy control subjects, 16 patients with GBA-PD, and 35 patients with iPD. Associations between FDC and clinical evaluations were also explored using multiple linear regression analyses.

RESULTS

Patients with GBA-PD showed significantly lower FD in the fornix and superior longitudinal fasciculus than healthy control subjects, and lower FC in the corticospinal tract (CST) and lower FDC in the CST, middle cerebellar peduncle, and striatal-thalamo-cortical pathways than patients with iPD. Contrarily, patients with iPD showed significantly higher FC and FDC in the CST and striatal-thalamo-cortical pathways than healthy control subjects. In addition, lower FDC in patients with GBA-PD was associated with reduced glucocerebrosidase enzyme activity, lower cerebrospinal fluid total α-synuclein levels, lower Montreal Cognitive Assessment scores, lower striatal binding ratio, and higher Unified Parkinson's Disease Rating Scale Part III scores.

CONCLUSIONS

We report reduced fiber-specific WM density and bundle cross-sectional size in patients with GBA-PD, suggesting neurodegeneration linked to glucocerebrosidase deficiency, α-synuclein accumulation, and poorer cognition and motor functions. Conversely, patients with iPD showed increased fiber bundle size, likely because of WM reorganization. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

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

OBJECTIVE

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

CLINICAL RELEVANCE STATEMENT

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

KEY POINTS

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

Deep Learning-Driven Transformation: A Novel Approach for Mitigating Batch Effects in Diffusion MRI Beyond Traditional Harmonization

BACKGROUND

"Batch effect" in MR images, due to vendor-specific features, MR machine generations, and imaging parameters, challenges image quality and hinders deep learning (DL) model generalizability.

PURPOSE

We aim to develop a DL model using contrast adjustment and super-resolution to reduce diffusion-weighted images (DWIs) diversity across magnetic field strengths and imaging parameters.

STUDY TYPE

Retrospective.

SUBJECTS

The DL model was built using an open dataset from one individual. The MR machine identification model was trained and validated on a dataset of 1134 adults (54% females, 46% males), with 1050 subjects showing no DWI abnormalities and 84 with conditions like stroke and tumors. The 21,000 images were divided into 80% for training, 20% for validation, and 3500 for testing.

FIELD STRENGTH/SEQUENCE

Seven MR scanners from four manufacturers with 1.5 T and 3 T magnetic field strengths. DWIs were acquired using spin-echo sequences and high-resolution T2WIs using the T2-SPACE sequence.

ASSESSMENT

An experienced, board-certified radiologist evaluated the effectiveness of restoring high-resolution T2WI and harmonizing diverse DWI with metrics such as PSNR and SSIM, and the texture and frequency attributes were further analyzed using gray-level co-occurrence matrix and 1-dimensional power spectral density. The model's impact on machine-specific characteristics was gauged through the performance metrics of a ResNet-50 model. Comprehensive statistical tests were employed for statistical robustness, including McNemar's test and the Dice index.

RESULTS

Our DL protocol reduced DWI contrast and resolution variation. ResNet-50 model's accuracy decreased from 0.9443 to 0.5786, precision from 0.9442 to 0.6494, recall from 0.9443 to 0.5786, and F1 score from 0.9438 to 0.5587. The t-SNE visualization indicated more consistent image features across multiple MR devices. Autoencoder halved learning iterations; Dice coefficient >0.74 confirmed signal reproducibility in 84 lesions.

CONCLUSION

This study presents a DL strategy to mitigate batch effects in diffusion MR images, improving their quality and generalizability.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 1.

Depth of Radiographic Response and Time to Tumor Regrowth Predicts Overall Survival Following Anti-VEGF Therapy in Recurrent Glioblastoma

PURPOSE

Antiangiogenic therapies are known to cause high radiographic response rates due to reduction in vascular permeability resulting in a lower degree of contrast extravasation. In this study, we investigate the prognostic ability for model-derived parameters describing enhancing tumor volumetric dynamics to predict survival in recurrent glioblastoma treated with antiangiogenic therapy.

EXPERIMENTAL DESIGN

N = 276 patients in two phase II trials were used as training data, including bevacizumab ± irinotecan (NCT00345163) and cabozantinib (NCT00704288), and N = 74 patients in the bevacizumab arm of a phase III trial (NCT02511405) were used for validation. Enhancing volumes were estimated using T1 subtraction maps, and a biexponential model was used to estimate regrowth (g) and regression (d) rates, time to tumor regrowth (TTG), and the depth of response (DpR). Response characteristics were compared to diffusion MR phenotypes previously shown to predict survival.

RESULTS

Optimized thresholds occurred at g = 0.07 months-1 (phase II: HR = 0.2579, P = 5 × 10-20; phase III: HR = 0.2197, P = 5 × 10-5); d = 0.11 months-1 (HR = 0.3365, P < 0.0001; HR = 0.3675, P = 0.0113); TTG = 3.8 months (HR = 0.2702, P = 6 × 10-17; HR = 0.2061, P = 2 × 10-5); and DpR = 11.3% (HR = 0.6326, P = 0.0028; HR = 0.4785, P = 0.0206). Multivariable Cox regression controlling for age and baseline tumor volume confirmed these factors as significant predictors of survival. Patients with a favorable pretreatment diffusion MRI phenotype had a significantly longer TTG and slower regrowth.

CONCLUSIONS

Recurrent glioblastoma patients with a large, durable radiographic response to antiangiogenic agents have significantly longer survival. This information is useful for interpreting activity of antiangiogenic agents in recurrent glioblastoma.

Accuracy of skull stripping in a single-contrast convolutional neural network model using eight-contrast magnetic resonance images

In automated analyses of brain morphometry, skull stripping or brain extraction is a critical first step because it provides accurate spatial registration and signal-intensity normalization. Therefore, it is imperative to develop an ideal skull-stripping method in the field of brain image analysis. Previous reports have shown that convolutional neural network (CNN) method is better at skull stripping than non-CNN methods. We aimed to evaluate the accuracy of skull stripping in a single-contrast CNN model using eight-contrast magnetic resonance (MR) images. A total of 12 healthy participants and 12 patients with a clinical diagnosis of unilateral Sturge-Weber syndrome were included in our study. A 3-T MR imaging system and QRAPMASTER were used for data acquisition. We obtained eight-contrast images produced by post-processing T1, T2, and proton density (PD) maps. To evaluate the accuracy of skull stripping in our CNN method, gold-standard intracranial volume (ICVG) masks were used to train the CNN model. The ICVG masks were defined by experts using manual tracing. The accuracy of the intracranial volume obtained from the single-contrast CNN model (ICVE) was evaluated using the Dice similarity coefficient [= 2(ICVE ⋂ ICVG)/(ICVE + ICVG)]. Our study showed significantly higher accuracy in the PD-weighted image (WI), phase-sensitive inversion recovery (PSIR), and PD-short tau inversion recovery (STIR) compared to the other three contrast images (T1-WI, T2-fluid-attenuated inversion recovery [FLAIR], and T1-FLAIR). In conclusion, PD-WI, PSIR, and PD-STIR should be used instead of T1-WI for skull stripping in the CNN models.

Fiber-specific micro- and macroscopic white matter alterations in progressive supranuclear palsy and corticobasal syndrome

Progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS) are characterized by progressive white matter (WM) alterations associated with the prion-like spreading of four-repeat tau, which has been pathologically confirmed. It has been challenging to monitor the WM degeneration patterns underlying the clinical deficits in vivo. Here, a fiber-specific fiber density and fiber cross-section, and their combined measure estimated using fixel-based analysis (FBA), were cross-sectionally and longitudinally assessed in PSP (n = 20), CBS (n = 17), and healthy controls (n = 20). FBA indicated disease-specific progression patterns of fiber density loss and subsequent bundle atrophy consistent with the tau propagation patterns previously suggested in a histopathological study. This consistency suggests the new insight that FBA can monitor the progressive tau-related WM changes in vivo. Furthermore, fixel-wise metrics indicated strong correlations with motor and cognitive dysfunction and the classifiability of highly overlapping diseases. Our findings might also provide a tool to monitor clinical decline and classify both diseases.

Multiparametric MRI: From Simultaneous Rapid Acquisition Methods and Analysis Techniques Using Scoring, Machine Learning, Radiomics, and Deep Learning to the Generation of Novel Metrics

ABSTRACT

With the recent advancements in rapid imaging methods, higher numbers of contrasts and quantitative parameters can be acquired in less and less time. Some acquisition models simultaneously obtain multiparametric images and quantitative maps to reduce scan times and avoid potential issues associated with the registration of different images. Multiparametric magnetic resonance imaging (MRI) has the potential to provide complementary information on a target lesion and thus overcome the limitations of individual techniques. In this review, we introduce methods to acquire multiparametric MRI data in a clinically feasible scan time with a particular focus on simultaneous acquisition techniques, and we discuss how multiparametric MRI data can be analyzed as a whole rather than each parameter separately. Such data analysis approaches include clinical scoring systems, machine learning, radiomics, and deep learning. Other techniques combine multiple images to create new quantitative maps associated with meaningful aspects of human biology. They include the magnetic resonance g-ratio, the inner to the outer diameter of a nerve fiber, and the aerobic glycolytic index, which captures the metabolic status of tumor tissues.

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.

Multi-nuclear sodium, diffusion, and perfusion MRI in human gliomas

PURPOSE

There is limited knowledge about the associations between sodium and proton MRI measurements in brain tumors. The purpose of this study was to quantify intra- and intertumoral correlations between sodium, diffusion, and perfusion MRI in human gliomas.

METHODS

Twenty glioma patients were prospectively studied on a 3T MRI system with multinuclear capabilities. Three mutually exclusive tumor volumes of interest (VOIs) were segmented: contrast-enhancing tumor (CET), T2/FLAIR hyperintense non-enhancing tumor (NET), and necrosis. Median and voxel-wise associations between apparent diffusion coefficient (ADC), normalized relative cerebral blood volume (nrCBV), and normalized sodium measurements were quantified for each VOI.

RESULTS

Both relative sodium concentration and ADC were significantly higher in areas of necrosis compared to NET (P = 0.003 and P = 0.008, respectively) and CET (P = 0.02 and P = 0.02). Sodium concentration was higher in CET compared to NET (P = 0.04). Sodium and ADC were higher in treated compared to treatment-naïve gliomas within NET (P = 0.006 and P = 0.01, respectively), and ADC was elevated in CET (P = 0.03). Median ADC and sodium concentration were positively correlated across patients in NET (r = 0.77, P < 0.0001) and CET (r = 0.84, P < 0.0001), but not in areas of necrosis (r = 0.45, P = 0.12). Median nrCBV and sodium concentration were negatively correlated across patients in areas of NET (r=-0.63, P = 0.003). Similar associations were observed when examining voxel-wise correlations within VOIs.

CONCLUSION

Sodium MRI is positively correlated with proton diffusion MRI measurements in gliomas, likely reflecting extracellular water. Unique areas of multinuclear MRI contrast may be useful in future studies to understand the chemistry of the tumor microenvironment.

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.

Analysis of synthetic magnetic resonance images by multi-channel segmentation increases accuracy of volumetry in the putamen and decreases mis-segmentation in the dural sinuses

BACKGROUND

Voxel-based morphometry (VBM) using magnetic resonance imaging (MR) has been used to estimate cortical atrophy associated with various diseases. However, there are mis-segmentations of segmented gray matter image in VBM.

PURPOSE

To study a twofold evaluation of single- and multi-channel segmentation using synthetic MR images: (1) mis-segmentation of segmented gray matter images in transverse and cavernous sinuses; and (2) accuracy and repeatability of segmented gray matter images.

MATERIAL AND METHODS

A total of 13 healthy individuals were scanned with 3D quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS) sequence on a 1.5-T scanner. Three of the 13 healthy participants were scanned five consecutive times for evaluation of repeatability. We used SyMRI software to create images with three contrasts: T1-weighted (T1W), T2-weighted (T2W), and proton density-weighted (PDW) images. Manual regions of interest (ROI) on T1W imaging were individually set as the gold standard in the transverse sinus, cavernous sinus, and putamen. Single-channel (T1W) and multi-channel (T1W + T2W, T1W + PDW, and T1W + T2W + PDW imaging) segmentations were performed with statistical parametric mapping 12 software.

RESULTS

We found that mis-segmentations in both the transverse and cavernous sinuses were large in single-channel segmentation compared with multi-channel segmentations. Furthermore, the accuracy of segmented gray matter images in the putamen was high in both multi-channel T1W + PDW and T1W + T2W + PDW segmentations compared with other segmentations. Finally, the highest repeatability of left putamen volumetry was found with multi-channel segmentation T1WI + PDWI.

CONCLUSION

Multi-channel segmentation with T1WI + PDWI provides good results for VBM compared with single-channel and other multi-channel segmentations.

Investigation of time-dependent diffusion in extra-axial brain tumors using oscillating-gradient spin-echo

Oscillating gradient spin-echo (OGSE) sequences provide access to short diffusion times and may provide insight into micro-scale internal structures of pathologic lesions based on an analysis of changes in diffusivity with differing diffusion times. We hypothesized that changes in diffusivity acquired with a shorter diffusion time may permit elucidation of properties related to the internal structure of extra-axial brain tumors. This study aimed to investigate the utility of changes in diffusivity between short and long diffusion times for characterizing extra-axial brain tumors. In total, 12 patients with meningothelial meningiomas, 13 patients with acoustic neuromas, and 11 patients with pituitary adenomas were scanned with a 3 T magnetic resonance imaging (MRI) scanner with diffusion-weighted imaging (DWI) using OGSE and pulsed gradient spin-echo (PGSE) (effective diffusion times [Δ_eff]: 6.5 ms and 35.2 ms) with b-values of 0 and 1000 s/mm². Relative percentage changes between shorter and longer diffusion times were calculated using region-of-interest (ROI) analysis of brain tumors on λ₁, λ₂, λ₃, and mean diffusivity (MD) maps. The diffusivities of PGSE, OGSE, and relative percentage changes were compared among each tumor type using a multiple comparisons Steel-Dwass test. The mean (standard deviation) MD at Δ_eff of 6.5 ms was 1.07 ± 0.23 10^-3 mm²/s, 1.19 ± 0.18 10^-3 mm²/s, 1.19 ± 0.21 10^-3 mm²/s for meningothelial meningiomas, acoustic neuromas, and pituitary adenomas, respectively. The mean (standard deviation) MD at Δ_eff of 35.2 ms was 0.93 ± 0.22 10^-3 mm²/s, 1.07 ± 0.19 10^-3 mm²/s, 0.82 ± 0.21 10^-3 mm²/s for meningothelial meningiomas, acoustic neuromas, and pituitary adenomas, respectively. The mean (standard deviation) of the relative percentage change was 15.7 ± 4.4%, 12.4 ± 8.2%, 46.8 ± 11.3% for meningothelial meningiomas, acoustic neuromas, and pituitary adenomas, respectively. Compared to meningiomas and acoustic neuromas, pituitary adenoma exhibited stronger diffusion time-dependence with diffusion times between 6.5 ms and 35.2 ms (P < 0.05). In conclusion, differences in diffusion time-dependence may be attributed to differences in the internal structures of brain tumors. DWI with a short diffusion time may provide additional information on the microstructure of each tumor and contribute to tumor diagnosis.

Change in volumetric tumor growth rate after cytotoxic therapy is predictive of overall survival in recurrent glioblastoma

Background

Alterations in tumor growth rate (TGR) in recurrent glioblastoma (rGBM) after treatment may be useful for identifying therapeutic activity. The aim of this study was to assess the impact of volumetric TGR alterations on overall survival (OS) in rGBM treated with chemotherapy with or without radiation therapy (RT).

Methods

Sixty-one rGBM patients treated with chemotherapy with or without concomitant radiation therapy (RT) at 1st or 2nd recurrence were retrospectively examined. Pre- and post-treatment contrast enhancing volumes were computed. Patients were considered "responders" if they reached progression-free survival at 6 months (PFS6) and showed a decrease in TGR after treatment and "non-responders" if they didn't reach PFS6 or if TGR increased.

Results

Stratification by PFS6 and based on TGR resulted in significant differences in OS both for all patients and for patients without RT (P < 0.05). A decrease of TGR (P = 0.009), smaller baseline tumor volume (P = 0.02), O6-methylguanine-DNA methyltransferase promoter methylation (P = 0.048) and fewer number of recurrences (P = 0.048) were significantly associated with longer OS after controlling for age, sex and concomitant RT.

Conclusion

A decrease in TGR in patients with PFS6, along with smaller baseline tumor volume, were associated with a significantly longer OS in rGBM treated with chemotherapy with or without radiation. Importantly, all patients that exhibited PFS6 also showed a measurable decrease in TGR.

Association of MRI Indices of Glymphatic System With Amyloid Deposition and Cognition in Mild Cognitive Impairment and Alzheimer Disease

BACKGROUND AND OBJECTIVES

The glymphatic system is a whole-brain perivascular network, which promotes CSF/interstitial fluid exchange. Alterations to this system may play a pivotal role in amyloid β (Aβ) accumulation. However, its involvement in Alzheimer disease (AD) pathogenesis is not fully understood. Here, we investigated the changes in noninvasive MRI measurements related to the perivascular network in patients with mild cognitive impairment (MCI) and AD. Additionally, we explored the associations of MRI measures with neuropsychological score, PET standardized uptake value ratio (SUVR), and Aβ deposition.

METHODS

MRI measures, including perivascular space (PVS) volume fraction (PVSVF), fractional volume of free water in white matter (FW-WM), and index of diffusivity along the perivascular space (ALPS index) of patients with MCI, those with AD, and healthy controls from the Alzheimer's Disease Neuroimaging Initiative database were compared. MRI measures were also correlated with the levels of CSF biomarkers, PET SUVR, and cognitive score in the combined subcohort of patients with MCI and AD. Statistical analyses were performed with age, sex, years of education, and APOE status as confounding factors.

RESULTS

In total, 36 patients with AD, 44 patients with MCI, and 31 healthy controls were analyzed. Patients with AD had significantly higher total, WM, and basal ganglia PVSVF (Cohen d = 1.15-1.48; p < 0.001) and FW-WM (Cohen d = 0.73; p < 0.05) and a lower ALPS index (Cohen d = 0.63; p < 0.05) than healthy controls. Meanwhile, the MCI group only showed significantly higher total (Cohen d = 0.99; p < 0.05) and WM (Cohen d = 0.91; p < 0.05) PVSVF. Low ALPS index was associated with lower CSF Aβ42 (r s = 0.41, p fdr = 0.026), FDG-PET uptake (r s = 0.54, p fdr < 0.001), and worse multiple cognitive domain deficits. High FW-WM was also associated with lower CSF Aβ42 (r s = -0.47, p fdr = 0.021) and worse cognitive performances.

DISCUSSION

Our study indicates that changes in PVS-related MRI parameters occur in MCI and AD, possibly due to impairment of the glymphatic system. We also report the associations between MRI parameters and Aβ deposition, neuronal change, and cognitive impairment in AD.

Federated learning enables big data for rare cancer boundary detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.

NIMG-34. QUANTIFICATION OF GLYCOLYTIC FLUX REDUCTION IN RECURRENT GLIOBLASTOMA AFTER EGFR INHIBITION USING MOLECULAR MR-PET

In recently published work, we demonstrated that acute inhibition of the EGFR – the most frequently altered oncogene in GBM – can rapidly reduce glycolysis in a subset of GBM. To quantify this effect, we propose a new combination metabolic MR-PET imaging biomarker that combines 18F-FDG PET, DSC perfusion MRI, diffusion MRI, and pH- and oxygen-sensitive amine CEST-SAGE-EPI. Specifically, this “glycolytic index” or GI, can be defined as elevated glucose uptake (18F-FDG standard uptake value), elevated tumor acidity (MTRasym@3ppm), and lower oxygen utilization (relative cerebral metabolic rate of oxygen, rCMRO2, defined as R2’ x rCBF/rCBV from oxygen-sensitive SAGE-EPI and DSC perfusion), normalized to cell density (using ADC from diffusion MRI). In the current study, we explored the use of Tagrisso® (Osimertinib or AZD9291), which has very high brain to plasma ratios (&gt; 1) and has proven effective in CNS metastasis of EGFR mutant lung cancer, as a potential treatment for EGFR amplified recurrent GBM. We have conducted a clinical trial (NCT03732352) to determine whether we observe similar metabolic imaging changes in EGFR mutated or amplified recurrent glioblastoma patients after treatment with osimertinib. Consistent with prior in vitro and in vivo results, treated patients exhibited a reduced glycolytic flux as indicated by reduction in 18F-FDG PET uptake (-3% change in SUV), tumor acidity (-19% change in MTRasym@3ppm) on pH-weighted CEST MRI, and glycolytic index (GI) (-25% change) in EGFR amplified recurrent GBM within 24 hours of treatment. Preliminary data suggests early change in GI correlates with and predicts both PFS (Pearson correlation, R2=0.3463, P=0.0441; Log-rank, P=0.0467) and OS (R2=0.6368, P=0.0019; Log-rank, P=0.0192). These preliminary data establish the scientific premise that a “glycolytic index” created using 18F-FDG PET, DSC perfusion, diffusion MRI, and pH- and oxygen-weighted amine CEST-SAGE-EPI may be an important tool for quantifying and visualizing glycolytic flux in GBM.

NIMG-48. MULTI-ECHO SPIN-AND-GRADIENT ECHO (SAGE) PERFUSION MRI TO EVALUATE BRAIN TUMOR MICROSTRUCTURE AND MICROVASCULATURE

BACKGROUND

In a classic DSC perfusion sequence, T1 and T2* leakage effects compete in determining the post-bolus signal, and are influenced by tissue geometry (i.e. cell density, cell size). Different DSC sequences can be variously influenced by these effects, depending on the different degree of T1 weighting and the pre-bolus administration. Multi-echo spin-and-gradient echo (SAGE) perfusion MRI enables to disentangle T2* and T1 components that contribute to the classic DSC curve, and to simultaneously compute DSC and DCE perfusion metrics.

METHODS

We retrospectively selected patients with: diagnosis of primary brain tumor, availability of SAGE-based DSC perfusion and DWI datasets, availability of histopathological images from targeted biopsies located within contrast-enhancing tissue. Post-processing allowed to distinguish the pure T2* component from the pure T1 component, and to perform a DCE analysis on the latter. Quantitative perfusion MRI measurements were then evaluated with respect to underlying histopathology.

RESULTS

Histopathological images were available for 22 targeted biopsies (across 10 patients) meeting the inclusion criteria. The following novel MRI quantitative maps were successfully computed voxelwise: ΔR2* at steady state (reflecting T2* leakage effects), ΔR1 at steady state (reflecting T1 leakage effects), transverse relaxivity at tracer equilibrium (TRATE, reflecting the combination of T2* and T1 leakage effects). In addition, Ve and ktrans were computed from the DCE analysis, and the percentage of signal recovery (PSR) was computed from the second echo of the multi-echo DSC (comparable to a classic single-echo DSC sequence).

CONCLUSIONS

Histopathological validation will assess the usefulness of these novel multi-echo derived quantitative maps for the non-invasive prediction of tumor microstructure. This would be particularly relevant for: 1) differential diagnosis between brain tumors with different cell size and cell density (e.g. lymphoma vs glioblastoma); 2) treatment response assessment (as pre-existing studies proved that cell shrinkage is an early event in treatment response).

NIMG-50. ASSOCIATION BETWEEN SALINITY, ACIDITY, DIFFUSIVITY, AND HYPOXIA IN HUMAN GLIOMAS USING MULTI-NUCLEAR MRI

INTRODUCTION

Sodium MRI has been recently explored in brain tumors to potentially reveal complementary information with proton MRI about the tumor microenvironment. However, there remains limited investigation combining sodium and quantitative proton MRI techniques. This pilot study explored the associations of sodium MRI with diffusion-, pH-, and hypoxia-weighted MRI biomarkers in gliomas.

METHODS

Eleven patients with gliomas (n=8 IDH-wild-type; n=3 IDH-mutant) who obtained sodium, anatomical, diffusion-, pH-, and hypoxia-weighted MRI were studied. All images were obtained on a 3T Siemens Prisma with a dedicated multi-nuclear head coil. Regions-of-interest were segmented on the contrast-enhancing (CE) (n=10), FLAIR (n=11), and necrotic regions (n=9). Sodium values were normalized to the mean values of the eyes. Median sodium, apparent diffusion coefficient (ADC), ADC(L) from bimodal histogram analyses, MTRasym (acidity), and R2’ (hypoxia) values were obtained.

RESULTS

There was increased sodium in necrosis compared to FLAIR regions (mean difference=0.24; P/i&gt;&lt; 0.05) and compared to CE regions (mean difference=0.17; P/i&gt;=0.07). There were significant positive correlations between sodium and ADC in CE (R=0.94; P/i&gt;&lt; 0.0001) and FLAIR regions (ρ=0.77; P/i&gt;&lt; 0.01), but not in necrosis (R=0.44; P/i&gt;=0.24). There was also a significant positive correlation with ADC(L) in CE regions (R=0.90; P&lt; 0.001) but not in FLAIR regions (ρ=0.50; P/i&gt;=0.12). Furthermore, there was a significant positive correlation between sodium and MTRasym in necrosis (R=0.74; P/i&gt;&lt; 0.05) and a positive trend in CE regions (R=0.55; P=0.10). There was also a negative trend between sodium and R2’ in FLAIR regions (ρ=-0.58; P/i&gt;=0.11).

CONCLUSIONS

Because ADC and ADC(L) are inversely related to cell density, increased sodium in gliomas may reflect increased extracellular space stemming from lower cell density, as sodium concentration is higher extracellularly. Positive associations between sodium and acidity as well as negative associations between sodium and hypoxia may reflect alterations in coupled sodium-pH and sodium-hypoxia homeostasis in gliomas.

Relapse patterns and radiation dose exposure in IDH wild-type glioblastoma at first radiographic recurrence following chemoradiation

PURPOSE

To quantify the radiation dose distribution and lesion morphometry (shape) at baseline, prior to chemoradiation, and at the time of radiographic recurrence in patients with glioblastoma (GBM).

METHODS

The IMRT dose distribution, location of the center of mass, sphericity, and solidity of the contrast enhancing tumor at baseline and the time of tumor recurrence was quantified in 48 IDH wild-type GBM who underwent postoperative IMRT (2 Gy daily for total of 60 Gy) with concomitant and adjuvant temozolomide.

RESULTS

Average radiation dose within enhancing tumor at baseline and recurrence was ≥ 60 Gy. Centroid location of the enhancing tumor shifted an average of 11.3 mm at the time of recurrence with respect to pre-IMRT location. A positive correlation was observed between change in centroid location and PFS in MGMT methylated patients (P = 0.0007) and Cox multivariate regression confirmed centroid distance from baseline was associated with PFS when accounting for clinical factors (P = 0.0189). Lesion solidity was higher at recurrence compared to baseline (P = 0.0118). Tumors that progressed > 12 weeks after IMRT were significantly more spherical (P = 0.0094).

CONCLUSION

Most GBMs recur local within therapeutic IMRT doses; however, tumors with longer PFS occurred further from the original tumor location and were more solid and/or nodular.

Low rank off-resonance correction for double half-echo k-space acquisitions

The present study describes a model-based approach for correcting off-resonance in the context of double half-echo k-space acquisitions. This technique employs center-out readouts in forward and reverse directions to reduce echo-times but is sensitive to off-resonance, which manifests as pixel shifts in both directions. Demodulating the k-space signal with a constant off-resonance term per slice removes pixel shifts and results in a marked reduction in blurring. Phantom and in vivo datasets are demonstrated from low bandwidth sodium imaging.

Early volumetric, perfusion, and diffusion MRI changes after mutant isocitrate dehydrogenase (IDH) inhibitor treatment in IDH1-mutant gliomas

Background

Inhibition of the isocitrate dehydrogenase (IDH)-mutant enzyme is a novel therapeutic target in IDH-mutant gliomas. Imaging biomarkers of IDH inhibitor treatment efficacy in human IDH-mutant gliomas are largely unknown. This study investigated early volumetric, perfusion, and diffusion MRI changes in IDH1-mutant gliomas during IDH inhibitor treatment.

Methods

Twenty-nine IDH1-mutant glioma patients who received IDH inhibitor and obtained anatomical, perfusion, and diffusion MRI pretreatment at 3-6 weeks (n = 23) and/or 2-4 months (n = 14) of treatment were retrospectively studied. Normalized relative cerebral blood volume (nrCBV), apparent diffusion coefficient (ADC), and fluid-attenuated inversion recovery (FLAIR) hyperintensity volume were analyzed.

Results

After 3-6 weeks of treatment, nrCBV was significantly increased (P = .004; mean %change = 24.15%) but not FLAIR volume (P = .23; mean %change = 11.05%) or ADC (P = .52; mean %change = -1.77%). Associations between shorter progression-free survival (PFS) with posttreatment nrCBV > 1.55 (P = .05; median PFS, 240 vs 55 days) and increased FLAIR volume > 4 cm³ (P = .06; 227 vs 29 days) trended toward significance. After 2-4 months, nrCBV, FLAIR volume, and ADC were not significantly different from baseline, but an nrCBV increase > 0% (P = .002; 1121 vs 257 days), posttreatment nrCBV > 1.8 (P = .01; 1121 vs. 270 days), posttreatment ADC < 1.15 μm²/ms (P = .02; 421 vs 215 days), median nrCBV/ADC ratio increase > 0% (P = .02; 1121 vs 270 days), and FLAIR volume change > 4 cm³ (P = .03; 421 vs 226.5 days) were associated with shorter PFS.

Conclusions

Increased nrCBV at 3-6 weeks of treatment may reflect transient therapeutic and/or tumor growth changes, whereas nrCBV, ADC, and FLAIR volume changes occurring at 2-4 months of treatment may more accurately reflect antitumor response to IDH inhibition.

Diagnostic and Prognostic Value of pH- and Oxygen-Sensitive Magnetic Resonance Imaging in Glioma: A Retrospective Study

Characterization of hypoxia and tissue acidosis could advance the understanding of glioma biology and improve patient management. In this study, we evaluated the ability of a pH- and oxygen-sensitive magnetic resonance imaging (MRI) technique to differentiate glioma genotypes, including isocitrate dehydrogenase (IDH) mutation, 1p/19q co-deletion, and epidermal growth factor receptor (EGFR) amplification, and investigated its prognostic value. A total of 159 adult glioma patients were scanned with pH- and oxygen-sensitive MRI at 3T. We quantified the pH-sensitive measure of magnetization transfer ratio asymmetry (MTRasym) and oxygen-sensitive measure of R2’ within the tumor region-of-interest. IDH mutant gliomas showed significantly lower MTRasym × R2’ (p < 0.001), which differentiated IDH mutation status with sensitivity and specificity of 90.0% and 71.9%. Within IDH mutants, 1p/19q codeletion was associated with lower tumor acidity (p < 0.0001, sensitivity 76.9%, specificity 91.3%), while IDH wild-type, EGFR-amplified gliomas were more hypoxic (R2’ p = 0.024, sensitivity 66.7%, specificity 76.9%). Both R2’ and MTRasym × R2’ were significantly associated with patient overall survival (R2’: p = 0.045; MTRasym × R2’: p = 0.002) and progression-free survival (R2’: p = 0.010; MTRasym × R2’: p < 0.0001), independent of patient age, treatment status, and IDH status. The pH- and oxygen-sensitive MRI is a clinically feasible and potentially valuable imaging technique for distinguishing glioma subtypes and providing additional prognostic value to clinical practice.

Paradoxical Association Between Relative Cerebral Blood Volume Dynamics Following Chemoradiation and Increased Progression-Free Survival in Newly Diagnosed IDH Wild-Type MGMT Promoter Methylated Glioblastoma With Measurable Disease

Background and Purpose

While relative cerebral blood volume (rCBV) may be diagnostic and prognostic for survival in glioblastoma (GBM), changes in rCBV during chemoradiation in the subset of newly diagnosed GBM with subtotal resection and the impact of MGMT promoter methylation status on survival have not been explored. This study aimed to investigate the association between rCBV response, MGMT methylation status, and progression-free (PFS) and overall survival (OS) in newly diagnosed GBM with measurable enhancing lesions.

Methods

1,153 newly diagnosed IDH wild-type GBM patients were screened and 53 patients (4.6%) had measurable post-surgical tumor (>1mL). rCBV was measured before and after patients underwent chemoradiation. Patients with a decrease in rCBV >10% were considered rCBV Responders, while patients with an increase or a decrease in rCBV <10% were considered rCBV Non-Responders. The association between change in enhancing tumor volume, change in rCBV, MGMT promotor methylation status, and PFS or OS were explored.

Results

A decrease in tumor volume following chemoradiation trended towards longer OS (p=0.12; median OS=26.8 vs. 16.3 months). Paradoxically, rCBV Non-Responders had a significantly improved PFS compared to Responders (p=0.047; median PFS=9.6 vs. 7.2 months). MGMT methylated rCBV Non-Responders exhibited a significantly longer PFS compared to MGMT unmethylated rCBV Non-Responders (p<0.001; median PFS=0.5 vs. 7.1 months), and MGMT methylated rCBV Non-Responders trended towards longer PFS compared to methylated rCBV Responders (p=0.089; median PFS=20.5 vs. 13.8 months).

Conclusions

This preliminary report demonstrates that in newly diagnosed IDH wild-type GBM with measurable enhancing disease after surgery (5% of patients), an enigmatic non-response in rCBV was associated with longer PFS, particularly in MGMT methylated patients.

Rigid real-time prospective motion-corrected three-dimensional multiparametric mapping of the human brain

PURPOSE

To develop a rigid real-time prospective motion-corrected multiparametric mapping technique and to test the performance of quantitative estimates.

METHODS

Motion tracking and correction were performed by integrating single-shot spiral navigators into a multiparametric imaging technique, three-dimensional quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS). The spiral navigator was optimized, and quantitative measurements were validated using a standard system phantom. The effect of motion correction on whole-brain T1 and T2 mapping under different types of head motion during the scan was evaluated in 10 healthy volunteers. Finally, six patients with Parkinson's disease, which is known to be associated with a high prevalence of motion artifacts, were scanned to evaluate the effectiveness of our method in the real world.

RESULTS

The phantom study demonstrated that the proposed motion correction method did not introduce quantitative bias. Improved parametric map quality and repeatability were shown in volunteer experiments with both in-plane and through-plane motions, comparable to the no-motion ground truth. In real-life validation in patients, the approach showed improved parametric map quality compared to images obtained without motion correction.

CONCLUSIONS

Real-time prospective motion-corrected multiparametric relaxometry based on 3D-QALAS provided robust and repeatable whole-brain multiparametric mapping.

Multimodal magnetic resonance imaging quantification of gray matter alterations in relapsing-remitting multiple sclerosis and neuromyelitis optica spectrum disorder

Herein, we combined neurite orientation dispersion and density imaging (NODDI) and synthetic magnetic resonance imaging (SyMRI) to evaluate the spatial distribution and extent of gray matter (GM) microstructural alterations in patients with relapsing-remitting multiple sclerosis (RRMS) and neuromyelitis optica spectrum disorder (NMOSD). The NODDI (neurite density index [NDI], orientation dispersion index [ODI], and isotropic volume fraction [ISOVF]) and SyMRI (myelin volume fraction [MVF]) measures were compared between age- and sex-matched groups of 30 patients with RRMS (6 males and 24 females; mean age, 51.43 ± 8.02 years), 18 patients with anti-aquaporin-4 antibody-positive NMOSD (2 males and 16 females; mean age, 52.67 ± 16.07 years), and 19 healthy controls (6 males and 13 females; mean age, 51.47 ± 9.25 years) using GM-based spatial statistical analysis. Patients with RRMS showed reduced NDI and MVF and increased ODI and ISOVF, predominantly in the limbic and paralimbic regions, when compared with healthy controls, while only increases in ODI and ISOVF were observed when compared with NMOSD. Compared to NDI and MVF, the changes in ODI and ISOVF were observed more widely, including in the cerebellar cortex. These abnormalities were associated with disease progression and disability. In contrast, patients with NMOSD only showed reduced NDI mainly in the cerebellar, limbic, and paralimbic cortices when compared with healthy controls and patients with RRMS. Taken together, our study supports the notion that GM pathologies in RRMS are distinct from those of NMOSD. However, owing to the limitations of the study, the results should be cautiously interpreted.

Radiomics with 3-dimensional magnetic resonance fingerprinting: influence of dictionary design on repeatability and reproducibility of radiomic features

Objectives

We aimed to investigate the influence of magnetic resonance fingerprinting (MRF) dictionary design on radiomic features using in vivo human brain scans.

Methods

Scan-rescans of three-dimensional MRF and conventional T1-weighted imaging were performed on 21 healthy volunteers (9 males and 12 females; mean age, 41.3 ± 14.6 years; age range, 22–72 years). Five patients with multiple sclerosis (3 males and 2 females; mean age, 41.2 ± 7.3 years; age range, 32–53 years) were also included. MRF data were reconstructed using various dictionaries with different step sizes. First- and second-order radiomic features were extracted from each dataset. Intra-dictionary repeatability and inter-dictionary reproducibility were evaluated using intraclass correlation coefficients (ICCs). Features with ICCs > 0.90 were considered acceptable. Relative changes were calculated to assess inter-dictionary biases.

Results

The overall scan-rescan ICCs of MRF-based radiomics ranged from 0.86 to 0.95, depending on dictionary step size. No significant differences were observed in the overall scan-rescan repeatability of MRF-based radiomic features and conventional T1-weighted imaging (p = 1.00). Intra-dictionary repeatability was insensitive to dictionary step size differences. MRF-based radiomic features varied among dictionaries (overall ICC for inter-dictionary reproducibility, 0.62–0.99), especially when step sizes were large. First-order and gray level co-occurrence matrix features were the most reproducible feature classes among different step size dictionaries. T1 map-derived radiomic features provided higher repeatability and reproducibility among dictionaries than those obtained with T2 maps.

Conclusion

MRF-based radiomic features are highly repeatable in various dictionary step sizes. Caution is warranted when performing MRF-based radiomics using datasets containing maps generated from different dictionaries.

Key Points

• MRF-based radiomic features are highly repeatable in various dictionary step sizes.

• Use of different MRF dictionaries may result in variable radiomic features, even when the same MRF acquisition data are used.

• Caution is needed when performing radiomic analysis using data reconstructed from different dictionaries.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-022-08555-3.

Simultaneous relaxometry and morphometry of human brain structures with 3D magnetic resonance fingerprinting: a multicenter, multiplatform, multifield-strength study

Relaxation times and morphological information are fundamental magnetic resonance imaging-derived metrics of the human brain that reflect the status of the underlying tissue. Magnetic resonance fingerprinting (MRF) enables simultaneous acquisition of T1 and T2 maps inherently aligned to the anatomy, allowing whole-brain relaxometry and morphometry in a single scan. In this study, we revealed the feasibility of 3D MRF for simultaneous brain structure-wise morphometry and relaxometry. Comprehensive test-retest scan analyses using five 1.5-T and three 3.0-T systems from a single vendor including different scanner types across 3 institutions demonstrated that 3D MRF-derived morphological information and relaxation times are highly repeatable at both 1.5 T and 3.0 T. Regional cortical thickness and subcortical volume values showed high agreement and low bias across different field strengths. The ability to acquire a set of regional T1, T2, thickness, and volume measurements of neuroanatomical structures with high repeatability and reproducibility facilitates the ability of longitudinal multicenter imaging studies to quantitatively monitor changes associated with underlying pathologies, disease progression, and treatments.

Advanced Diffusion MR Imaging for Multiple Sclerosis in the Brain and Spinal Cord

Diffusion tensor imaging (DTI) has been established its usefulness in evaluating normal-appearing white matter (NAWM) and other lesions that are difficult to evaluate with routine clinical MRI in the evaluation of the brain and spinal cord lesions in multiple sclerosis (MS), a demyelinating disease. With the recent advances in the software and hardware of MRI systems, increasingly complex and sophisticated MRI and analysis methods, such as q-space imaging, diffusional kurtosis imaging, neurite orientation dispersion and density imaging, white matter tract integrity, and multiple diffusion encoding, referred to as advanced diffusion MRI, have been proposed. These are capable of capturing in vivo microstructural changes in the brain and spinal cord in normal and pathological states in greater detail than DTI.

This paper reviews the current status of recent advanced diffusion MRI for assessing MS in vivo as part of an issue celebrating two decades of magnetic resonance in medical sciences (MRMS), an official journal of the Japanese Society of Magnetic Resonance in Medicine.

Pretreatment ADC Histogram Analysis as a Prognostic Imaging Biomarker for Patients with Recurrent Glioblastoma Treated with Bevacizumab: A Systematic Review and Meta-analysis

BACKGROUND

The mean ADC value of the lower Gaussian curve (ADC_L) derived from the bi-Gaussian curve-fitting histogram analysis has been reported as a predictive/prognostic imaging biomarker in patients with recurrent glioblastoma treated with bevacizumab; however, its systematic summary has been lacking.

PURPOSE

We applied a systematic review and meta-analysis to investigate the predictive/prognostic performance of ADC_L in patients with recurrent glioblastoma treated with bevacizumab.

DATA SOURCES

We performed a literature search using PubMed, Scopus, and EMBASE.

STUDY SELECTION

A total of 1344 abstracts were screened, of which 83 articles were considered potentially relevant. Data were finally extracted from 6 studies including 578 patients.

DATA ANALYSIS

Forest plots were generated to illustrate the hazard ratios of overall survival and progression-free survival. The heterogeneity across the studies was assessed using the Cochrane Q test and I² values.

DATA SYNTHESIS

The pooled hazard ratios for overall survival and progression-free survival in patients with an ADC_L lower than the cutoff values were 1.89 (95% CI, 1.53-2.31) and 1.98 (95% CI, 1.54-2.55) with low heterogeneity among the studies. Subgroup analysis of the bevacizumab-free cohort showed a pooled hazard ratio for overall survival of 1.20 (95% CI, 1.08-1.34) with low heterogeneity.

LIMITATIONS

The conclusions are limited by the difference in the definition of recurrence among the included studies.

CONCLUSIONS

This systematic review with meta-analysis supports the prognostic value of ADC_L in patients with recurrent glioblastoma treated with bevacizumab, with a low ADC_L demonstrating decreased overall survival and progression-free survival. On the other hand, the predictive role of ADC_L for bevacizumab treatment was not confirmed.

"Aerobic glycolytic imaging" of human gliomas using combined pH-, oxygen-, and perfusion-weighted magnetic resonance imaging

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Aerobic glycolytic imaging combines pH-, oxygen-, and perfusion-weighted MRI.

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Aerobic glycolytic imaging depicts abnormal glucose metabolism of gliomas.

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IDH wild-type gliomas show higher aerobic glycolytic index compared with mutants.

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Aerobic glycolytic index in IDH wild-type glioma is correlated with glucose uptake.

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Aerobic glycolytic index in IDH mutant glioma is correlated to lactate transporters.

Purpose

To quantify abnormal metabolism of diffuse gliomas using “aerobic glycolytic imaging” and investigate its biological correlation.

Methods

All subjects underwent a pH-weighted amine chemical exchange saturation transfer spin-and-gradient-echo echoplanar imaging (CEST-SAGE-EPI) and dynamic susceptibility contrast perfusion MRI. Relative oxygen extraction fraction (rOEF) was estimated as the ratio of reversible transverse relaxation rate R₂′ to normalized relative cerebral blood volume. An aerobic glycolytic index (AGI) was derived by the ratio of pH-weighted image contrast (MTR_asym at 3.0 ppm) to rOEF. AGI was compared between different tumor types (N = 51, 30 IDH mutant and 21 IDH wild type). Metabolic MR parameters were correlated with ¹⁸F-FDG uptake (N = 8, IDH wild-type glioblastoma), expression of key glycolytic proteins using immunohistochemistry (N = 38 samples, 21 from IDH mutant and 17 from IDH wild type), and bioenergetics analysis on purified tumor cells (N = 7, IDH wild-type high grade).

Results

AGI was significantly lower in IDH mutant than wild-type gliomas (0.48 ± 0.48 vs. 0.70 ± 0.48; P = 0.03). AGI was strongly correlated with ¹⁸F-FDG uptake both in non-enhancing tumor (Spearman, ρ = 0.81; P = 0.01) and enhancing tumor (ρ = 0.81; P = 0.01). AGI was significantly correlated with glucose transporter 3 (ρ = 0.71; P = 0.004) and hexokinase 2 (ρ = 0.73; P = 0.003) in IDH wild-type glioma, and monocarboxylate transporter 1 (ρ = 0.59; P = 0.009) in IDH mutant glioma. Additionally, a significant correlation was found between AGI derived from bioenergetics analysis and that estimated from MRI (ρ = 0.79; P = 0.04).

Conclusion

AGI derived from molecular MRI was correlated with glucose uptake (¹⁸F-FDG and glucose transporter 3/hexokinase 2) and cellular AGI in IDH wild-type gliomas, whereas AGI in IDH mutant gliomas appeared associated with monocarboxylate transporter density.

Visualization of tumor heterogeneity and prediction of isocitrate dehydrogenase mutation status for human gliomas using multiparametric physiologic and metabolic MRI

This study aimed to differentiate isocitrate dehydrogenase (IDH) mutation status with the voxel-wise clustering method of multiparametric magnetic resonance imaging (MRI) and to discover biological underpinnings of the clusters. A total of 69 patients with treatment-naïve diffuse glioma were scanned with pH-sensitive amine chemical exchange saturation transfer MRI, diffusion-weighted imaging, fluid-attenuated inversion recovery, and contrast-enhanced T1-weighted imaging at 3 T. An unsupervised two-level clustering approach was used for feature extraction from acquired images. The logarithmic ratio of the labels in each class within tumor regions was applied to a support vector machine to differentiate IDH status. The highest performance to predict IDH mutation status was found for 10-class clustering, with a mean area under the curve, accuracy, sensitivity, and specificity of 0.94, 0.91, 0.90, and 0.91, respectively. Targeted biopsies revealed that the tissues with labels 7-10 showed high expression levels of hypoxia-inducible factor 1-alpha, glucose transporter 3, and hexokinase 2, which are typical of IDH wild-type glioma, whereas those with labels 1 showed low expression of these proteins. In conclusion, A machine learning model successfully predicted the IDH mutation status of gliomas, and the resulting clusters properly reflected the metabolic status of the tumors.

Advantages of Using Both Voxel- and Surface-based Morphometry in Cortical Morphology Analysis: A Review of Various Applications

Surface-based morphometry (SBM) is extremely useful for estimating the indices of cortical morphology, such as volume, thickness, area, and gyrification, whereas voxel-based morphometry (VBM) is a typical method of gray matter (GM) volumetry that includes cortex measurement. In cases where SBM is used to estimate cortical morphology, it remains controversial as to whether VBM should be used in addition to estimate GM volume. Therefore, this review has two main goals. First, we summarize the differences between the two methods regarding preprocessing, statistical analysis, and reliability. Second, we review studies that estimate cortical morphological changes using VBM and/or SBM and discuss whether using VBM in conjunction with SBM produces additional values. We found cases in which detection of morphological change in either VBM or SBM was superior, and others that showed equivalent performance between the two methods. Therefore, we concluded that using VBM and SBM together can help researchers and clinicians obtain a better understanding of normal neurobiological processes of the brain. Moreover, the use of both methods may improve the accuracy of the detection of morphological changes when comparing the data of patients and controls.

In addition, we introduce two other recent methods as future directions for estimating cortical morphological changes: a multi-modal parcellation method using structural and functional images, and a synthetic segmentation method using multi-contrast images (such as T1- and proton density-weighted images).

Automation of a Rule-based Workflow to Estimate Age from Brain MR Imaging of Infants and Children Up to 2 Years Old Using Stacked Deep Learning

PURPOSE

Myelination-related MR signal changes in white matter are helpful for assessing normal development in infants and children. A rule-based myelination evaluation workflow regarding signal changes on T1-weighted images (T1WIs) and T2-weighted images (T2WIs) has been widely used in radiology. This study aimed to simulate a rule-based workflow using a stacked deep learning model and evaluate age estimation accuracy.

METHODS

The age estimation system involved two stacked neural networks: a target network-to extract five myelination-related images from the whole brain, and an age estimation network from extracted T1- and T2WIs separately. A dataset was constructed from 119 children aged below 2 years with two MRI systems. A four-fold cross-validation method was adopted. The correlation coefficient (CC), mean absolute error (MAE), and root mean squared error (RMSE) of the corrected chronological age of full-term birth, as well as the mean difference and the upper and lower limits of 95% agreement, were measured. Generalization performance was assessed using datasets acquired from different MR images. Age estimation was performed in Sturge-Weber syndrome (SWS) cases.

RESULTS

There was a strong correlation between estimated age and corrected chronological age (MAE: 0.98 months; RMSE: 1.27 months; and CC: 0.99). The mean difference and standard deviation (SD) were -0.15 and 1.26, respectively, and the upper and lower limits of 95% agreement were 2.33 and -2.63 months. Regarding generalization performance, the performance values on the external dataset were MAE of 1.85 months, RMSE of 2.59 months, and CC of 0.93. Among 13 SWS cases, 7 exceeded the limits of 95% agreement, and a proportional bias of age estimation based on myelination acceleration was exhibited below 12 months of age (P = 0.03).

CONCLUSION

Stacked deep learning models automated the rule-based workflow in radiology and achieved highly accurate age estimation in infants and children up to 2 years of age.

Diffusion MRI is an early biomarker of overall survival benefit in IDH wild-type recurrent glioblastoma treated with immune checkpoint inhibitors

BACKGROUND

Diffusion MRI estimates of the apparent diffusion coefficient (ADC) have been shown to be useful in predicting treatment response in patients with glioblastoma (GBM), with ADC elevations indicating tumor cell death. We aimed to investigate whether the ADC values measured before and after treatment with immune checkpoint inhibitors (ICIs) and the changes in these ADC values could predict overall survival (OS) in patients with recurrent IDH wild-type GBM.

METHODS

Forty-four patients who met the following inclusion criteria were included in this retrospective study: (i) diagnosed with recurrent IDH wild-type GBM and treated with either pembrolizumab or nivolumab and (ii) availability of diffusion data on pre- and post-ICI MRI. Tumor volume and the median relative ADC (rADC) with respect to the normal-appearing white matter within the enhancing tumor were calculated.

RESULTS

Median OS among all patients was 8.1 months (range, 1.0-22.5 months). Log-rank test revealed that higher post-treatment rADC was associated with a significantly longer OS (median, 10.3 months for rADC ≧ 1.63 versus 6.1 months for rADC < 1.63; P = 0.02), whereas tumor volume, pre-treatment rADC, and changes in rADC after treatment were not significantly associated with OS. Cox regression analysis revealed that post-treatment rADC significantly influenced OS (P = 0.02, univariate analysis), even after controlling for age and sex (P =0.01, multivariate analysis), and additionally controlling for surgery after ICI treatment (P = 0.045, multivariate analysis).

CONCLUSIONS

Elevated post-treatment rADC may be an early imaging biomarker for OS benefits in GBM patients receiving ICI treatment.

NIMG-44. PROGNOSTIC VALUE OF PH- AND OXYGEN-SENSITIVE MRI IN GLIOMA PATIENTS

Hypoxia and tissue acidosis are two key features of the glioma microenvironment, both associated with a more aggressive phenotype through promotion of invasion, angiogenesis, and resistance to a vast number of therapies. In the current study, we demonstrate that higher levels of acidity and hypoxia in glioma are associated with worse prognosis by using simultaneous pH- and oxygen-sensitive amine chemical exchange saturation transfer spin-and-gradient echo echo-planar imaging (CEST-SAGE-EPI). A total of 159 histologically confirmed adult glioma patients (WHO grade II: N = 42; grade III: N = 38; grade IV, N = 79) were retrospectively evaluated. All patients were scanned with a custom amine CEST-SAGE-EPI MRI pulse sequence at 3T. Magnetization transfer ratio asymmetry (MTRasym) at 3ppm was used as a measure of relative acidity, R2’ was used as a surrogate of hypoxia, and their product MTRasym×R2' was used to quantify the degree of both acidity and hypoxia. Cox regression was performed to evaluate prognostic factors for OS and PFS. Univariate results suggested higher hypoxia, R2' (HR = 1.44, p = 0.0002), and higher combined measure of acidity and hypoxia, MTRasym×R2' (HR = 1.14, p = 0.0008), were associated with a shorter OS. When considering age, treatment status, and IDH mutation status as covariates, R2' and MTRasym×R2' remained significantly associated with patient OS (R2': HR = 1.27, p = 0.045; MTRasym×R2': HR = 1.17, p = 0.002). Within the treatment naïve patients, tumor acidity MTRasym, was also associated with OS (HR = 3.72, p = 0.003). R2' and MTRasym×R2' were significantly associated with PFS, both using univariate (R2': p &lt; 0.0001; MTRasym×R2': p &lt; 0.0001) and multivariate analyses including clinical factors (R2': p = 0.010; MTRasym×R2': p &lt; 0.0001). In summary, tumor acidity and hypoxia measured using pH- and oxygen-sensitive metabolic MRI are significant prognostic factors in glioma.

NIMG-41. PH-WEIGHTED MOLECULAR MRI AS AN EARLY BIOMARKER OF METABOLIC RESPONSE TO IDH INHIBITION IN IDH MUTANT GLIOMAS

The current study tested the hypotheses that (1) pH-weighted MRI measurements of tumor acidity reflect glycolytic activity in human gliomas, (2) that tumor acidity, and thus glycolytic activity, differs between human IDH mutant (mIDH) and wild type gliomas, and (3) that an increase in tumor acidity, suggestive of increased glycolytic activity, occurs after inhibition of mutant IDH enzyme activity and reduction in 2HG, an oncometabolite. To test these hypotheses, we employed a custom pH-weighted amine chemical exchange saturation transfer echoplanar (CEST-EPI) technique in 152 patients with IDH mutant or wildtype glioma prior to surgery and 11 patients before and after treatment with AG120 or AG881 enrolled at our institution in a phase 1 perioperative study in patients with recurrent, non-enhancing, IDH mutant low-grade gliomas (NCT03343197). Results from image-guided biopsies in more than 100 patients demonstrated a significant correlation between MTRasym at 3ppm, a measure of tumor acidity from pH-weighted amine CEST-EPI, and expression of key glycolytic proteins including GLUT3 (R2=0.2188,P=0.0105), HK2 (R2=0.1788,P=0.0314), LDHA (R2=0.1111,P=0.0071), and MCT1 (R2=0.1228,P=0.0039) as well as ex vivo extracellular flux analysis estimates of ATP consumption from glycolysis (R2=0.6684,P=0.0021). Data suggests a significantly lower acidity (MTRasym@3ppm) within non-enhancing tumor in IDH mutant gliomas when compared to IDH wild type gliomas (P&lt; 0.0001). Patients in a phase 1 perioperative study showed a shift toward higher tumor acidity (i.e. higher glycolytic activity) following inhibition of IDH based on 2HG suppression in resected tumors, but at levels below that of IDH wild type gliomas. Levels of 2HG within the tumor after IDH inhibition were inversely correlated with post-treatment tumor acidity (R2=0.6342, P=0.0180). Overall, results suggest mIDH gliomas have low levels of glycolytic activity, and successful inhibition of the mutant IDH enzyme results in reduction in 2HG and a measurable metabolic shift toward elevated glycolysis as evidenced using pH-weighted molecular MRI.

NIMG-45. DIFFUSION MRI AS AN EARLY BIOMARKER OF OVERALL SURVIVAL BENEFIT IN RECURRENT GLIOBLASTOMA TREATED WITH IMMUNE CHECKPOINT INHIBITORS

Diffusion magnetic resonance imaging (MRI) estimates of the apparent diffusion coefficient (ADC) has been revealed to be useful for predicting treatment response in patients with glioblastoma (GBM), with an increase in ADC indicating tumor cell death. The aim of the current study was to investigate whether quantitative changes in diffusion MRI after treatment with immune checkpoint inhibitors (ICI) could predict OS in patients with recurrent GBM. A total of 61 patients were included in this retrospective study with the following inclusion criteria: (i) diagnosis of recurrent GBM treated either with pembrolizumab or nivolumab and (ii) availability of diffusion data in pre- and post-ICI MRI. Tumor volume and median relative apparent diffusion coefficient (rADC) within enhancing tumor with respect to normal-appearing white matter were calculated. Median OS for all patients was 7.6 months (range, 1.0–30.6 months). Results showed that higher post-treatment rADC was associated with significantly longer OS (median, 372 days for rADC ≧ 1.42 versus 211 days for rADC &lt; 1.42; P = 0.01, log-rank test), whereas tumor volume and pre-treatment rADC were not significantly associated with OS. Cox regression analysis revealed post-treatment rADC significantly influences OS (P = 0.02, univariate analysis), even after controlling for age, sex, and IDH status (P = 0.007, multivariate analysis), and additionally controlling for whether surgery was performed after ICI treatment (P = 0.049, multivariate analysis). In conclusion, a high post-treatment rADC may be an early imaging biomarker for identifying OS benefit in recurrent GBM patients receiving ICI treatment.