Early biomarkers from dynamic contrast-enhanced magnetic resonance imaging to predict the response to antiangiogenic therapy in high-grade gliomas

Dynamic Contrast-Enhanced MRI in the Abdomen of Mice with High Temporal and Spatial Resolution Using Stack-of-Stars Sampling and KWIC Reconstruction

Application of quantitative dynamic contrast-enhanced (DCE) MRI in mouse models of abdominal cancer is challenging due to the effects of RF inhomogeneity, image corruption from rapid respiratory motion and the need for high spatial and temporal resolutions. Here we demonstrate a DCE protocol optimized for such applications. The method consists of three acquisitions: (1) actual flip-angle B₁ mapping, (2) variable flip-angle T₁ mapping and (3) acquisition of the DCE series using a motion-robust radial strategy with k-space weighted image contrast (KWIC) reconstruction. All three acquisitions employ spoiled radial imaging with stack-of-stars sampling (SoS) and golden-angle increments between the views. This scheme is shown to minimize artifacts due to respiratory motion while simultaneously facilitating view-sharing image reconstruction for the dynamic series. The method is demonstrated in a genetically engineered mouse model of pancreatic ductal adenocarcinoma and yielded mean perfusion parameters of K^trans = 0.23 ± 0.14 min⁻¹ and v_e = 0.31 ± 0.17 (n = 22) over a wide range of tumor sizes. The SoS-sampled DCE method is shown to produce artifact-free images with good SNR leading to robust estimation of DCE parameters.

Vascular Normalization: A New Window Opened for Cancer Therapies

Preclinical and clinical antiangiogenic approaches, with multiple side effects such as resistance, have not been proved to be very successful in treating tumor blood vessels which are important targets for tumor therapy. Meanwhile, restoring aberrant tumor blood vessels, known as tumor vascular normalization, has been shown not only capable of reducing tumor invasion and metastasis but also of enhancing the effectiveness of chemotherapy, radiation therapy, and immunotherapy. In addition to the introduction of such methods of promoting tumor vascular normalization such as maintaining the balance between proangiogenic and antiangiogenic factors and targeting endothelial cell metabolism, microRNAs, and the extracellular matrix, the latest molecular mechanisms and the potential connections between them were primarily explored. In particular, the immunotherapy-induced normalization of blood vessels further promotes infiltration of immune effector cells, which in turn improves immunotherapy, thus forming an enhanced loop. Thus, immunotherapy in combination with antiangiogenic agents is recommended. Finally, we introduce the imaging technologies and serum markers, which can be used to determine the window for tumor vascular normalization.

Feasibility Study on Using Dynamic Contrast Enhanced MRI to Assess the Effect of Tyrosine Kinase Inhibitor Therapy within the STAR Trial of Metastatic Renal Cell Cancer

Objective: To identify dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters predictive of early disease progression in patients with metastatic renal cell cancer (mRCC) treated with anti-angiogenic tyrosine kinase inhibitors (TKI). Methods: The study was linked to a phase II/III randomised control trial. Patients underwent DCE-MRI before, at 4- and 10-weeks after initiation of TKI. DCE-MRI parameters at each time-point were derived from a single-compartment tracer kinetic model, following semi-automated tumour segmentation by two independent readers. Primary endpoint was correlation of DCE-MRI parameters with disease progression at 6-months. Receiver operating characteristic (ROC) curve analysis and area under the curve (AUC) values were calculated for parameters associated with disease progression at 6 months. Inter-observer agreement was assessed using the intraclass correlation coefficient (ICC). Results: 23 tumours in 14 patients were measurable. Three patients had disease progression at 6 months. The percentage (%) change in perfused tumour volume between baseline and 4-week DCE-MRI (p = 0.016), mean transfer constant K^trans change (p = 0.038), and % change in extracellular volume (p = 0.009) between 4- and 10-week MRI, correlated with early disease progression (AUC 0.879 for each parameter). Inter-observer agreement was excellent for perfused tumour volume, K^trans and extracellular volume (ICC: 0.928, 0.949, 0.910 respectively). Conclusions: Early measurement of DCE-MRI biomarkers of tumour perfusion at 4- and 10-weeks predicts disease progression at 6-months following TKI therapy in mRCC.

DCE-MRI in Glioma, Infiltration Zone and Healthy Brain to Assess Angiogenesis: A Biopsy Study

Purpose

To explore the focal predictability of vascular growth factor expression and neovascularization using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in glioma.

Methods

120 brain biopsies were taken in vital tumor, infiltration zone and normal brain tissue of 30 glioma patients: 17 IDH(isocitrate dehydrogenase)-wildtype glioblastoma (GBM), 1 IDH-wildtype astrocytoma °III (together prognostic group 1), 3 IDH-mutated GBM (group 2), 3 anaplastic astrocytomas IDH-mutated (group 3), 4 anaplastic oligodendrogliomas and 2 low-grade oligodendrogliomas (together prognostic group 4). A mixed linear model evaluated the predictabilities of microvessel density (MVD), vascular area ratio (VAR), mean vessel size (MVS), vascular endothelial growth factor and receptors (VEGF-A, VEGFR‑2) and vascular endothelial-protein tyrosine phosphatase (VE-PTP) expression from Tofts model kinetic and model-free curve parameters.

Results

All kinetic parameters were associated with VEGF‑A (all p < 0.001) expression. K^trans, k_ep and v_e were associated with VAR (p = 0.006, 0.004 and 0.01, respectively) and MVS (p = 0.0001, 0.02 and 0.003, respectively) but not MVD (p = 0.84, 0.74 and 0.73, respectively). Prognostic groups differed in K^trans (p = 0.007) and v_e (p = 0.004) values measured in the infiltration zone. Despite significant differences of VAR, MVS, VEGF‑A, VEGFR‑2, and VE-PTP in vital tumor tissue and the infiltration zone (p = 0.0001 for all), there was no significant difference between kinetic parameters measured in these zones.

Conclusion

The DCE-MRI kinetic parameters show correlations with microvascular parameters in vital tissue and also reveal blood-brain barrier abnormalities in the infiltration zones adequate to differentiate glioma prognostic groups.

Supplementary Information

The online version of this article (10.1007/s00062-021-01015-3) contains supplementary material, which is available to authorized users.

Dynamic contrast-enhanced MRI may be helpful to predict response and prognosis after bevacizumab treatment in patients with recurrent high-grade glioma: comparison with diffusion tensor and dynamic susceptibility contrast imaging

PURPOSE

We aimed to evaluate the utility of diffusion tensor imaging (DTI), dynamic contrast-enhanced (DCE), and dynamic susceptibility contrast (DSC) imaging for stratifying bevacizumab treatment outcomes in patients with recurrent high-grade glioma.

METHODS

Fifty-three patients with recurrent high-grade glioma who underwent baseline magnetic resonance imaging including DTI, DCE, and DSC before bevacizumab treatment were included. The mean apparent diffusion coefficient, fractional anisotropy, normalized cerebral blood volume, normalized cerebral blood flow, volume transfer constant, rate transfer coefficient (K_ep), extravascular extracellular volume fraction, and plasma volume fraction were assessed. Predictors of response status, progression-free survival (PFS), and overall survival (OS) were determined using logistic regression and Cox proportional hazard modeling.

RESULTS

Responders (n = 16) showed significantly longer PFS and OS (P < 0.001) compared with nonresponders (n = 37). Multivariable analysis revealed that lower mean K_ep (odds ratio = 0.01, P = 0.008) was the only independent predictor of favorable response after adjustment for age, isocitrate dehydrogenase (IDH) mutation status, and O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. Multivariable Cox proportional hazard modeling showed that a higher mean K_ep was the only variable associated with shorter PFS (hazard ratio [HR] = 7.90, P = 0.006) and OS (HR = 9.71, P = 0.020) after adjustment for age, IDH mutation status, and MGMT promoter methylation status.

CONCLUSION

Baseline mean K_ep may be a useful biomarker for predicting response and stratifying patient outcomes following bevacizumab treatment in patients with recurrent high-grade glioma.

Data-Driven Regularization Parameter Selection in Dynamic MRI

In dynamic MRI, sufficient temporal resolution can often only be obtained using imaging protocols which produce undersampled data for each image in the time series. This has led to the popularity of compressed sensing (CS) based reconstructions. One problem in CS approaches is determining the regularization parameters, which control the balance between data fidelity and regularization. We propose a data-driven approach for the total variation regularization parameter selection, where reconstructions yield expected sparsity levels in the regularization domains. The expected sparsity levels are obtained from the measurement data for temporal regularization and from a reference image for spatial regularization. Two formulations are proposed. Simultaneous search for a parameter pair yielding expected sparsity in both domains (S-surface), and a sequential parameter selection using the S-curve method (Sequential S-curve). The approaches are evaluated using simulated and experimental DCE-MRI. In the simulated test case, both methods produce a parameter pair and reconstruction that is close to the root mean square error (RMSE) optimal pair and reconstruction. In the experimental test case, the methods produce almost equal parameter selection, and the reconstructions are of high perceived quality. Both methods lead to a highly feasible selection of the regularization parameters in both test cases while the sequential method is computationally more efficient.

Non-invasive monitoring of the kinetic infiltration and therapeutic efficacy of nanoparticle-labeled chimeric antigen receptor T cells in glioblastoma via 7.0-Tesla magnetic resonance imaging

BACKGROUND AIMS

Chimeric antigen receptor (CAR) T-cell therapy is a promising treatment strategy in solid tumors. In vivo cell tracking techniques can help us better understand the infiltration, persistence and therapeutic efficacy of CAR T cells. In this field, magnetic resonance imaging (MRI) can achieve high-resolution images of cells by using cellular imaging probes. MRI can also provide various biological information on solid tumors.

METHODS

The authors adopted the amino alcohol derivatives of glucose-coated nanoparticles, ultra-small superparamagnetic particles of iron oxide (USPIOs), to label CAR T cells for non-invasive monitoring of kinetic infiltration and persistence in glioblastoma (GBM). The specific targeting CARs included anti-human epidermal growth factor receptor variant III and IL13 receptor subunit alpha 2 CARs.

RESULTS

When using an appropriate concentration, USPIO labeling exerted no negative effects on the biological characteristics and killing efficiency of CAR T cells. Increasing hypointensity signals could be detected in GBM models by susceptibility-weighted imaging MRI ranging from 3 days to 14 days following the injection of USPIO-labeled CAR T cells. In addition, nanoparticles and CAR T cells were found on consecutive histopathological sections. Moreover, diffusion and perfusion MRI revealed significantly increased water diffusion and decreased vascular permeability on day 3 after treatment, which was simultaneously accompanied by a significant decrease in tumor cell proliferation and increase in intercellular tight junction on immunostaining sections.

CONCLUSION

These results establish an effective imaging technique that can track CAR T cells in GBM models and validate their early therapeutic effects, which may guide the evaluation of CAR T-cell therapies in solid tumors.

Advanced magnetic resonance imaging to support clinical drug development for malignant glioma

Even though the treatment options and survival of patients with glioblastoma multiforme (GBM), the most common type of malignant glioma, have improved over the past decade, there is still a high unmet medical need to develop novel therapies. Complexity in pathology and therapy require biomarkers to characterize tumors, to define malignant and active areas, to assess disease prognosis, and to quantify and monitor therapy response. While conventional magnetic resonance imaging (MRI) techniques have improved these assessments, limitations remain. In this review, we evaluate the role of various non-invasive biomarkers based on advanced structural and functional MRI techniques in the context of GBM drug development over the past 5 years.

Evaluation of tumor response to antiangiogenic therapy in patients with recurrent gliomas using contrast-enhanced perfusion-weighted magnetic resonance imaging techniques: A meta-analysis

BACKGROUND

It is of vital importance to find radiologic biomarkers that can accurately predict treatment response. Usually, the initiation of antiangiogenic therapy causes a rapid decrease in the contrast enhancing tumor. However, the treatment response is observed only in a fraction of patients due to the partial radiological response secondary to stabilization of abnormal vessels which does not essentially indicate a true antitumor effect. Perfusion-weighted magnetic resonance imaging (PW-MRI) techniques have shown implicitness as a strong imaging biomarker for gliomas since they give hemodynamic information of blood vessels. Hence, there is a rapid expansion of PW-MRI related studies and clinical applications.

AIM

To determine the diagnostic performance of PW-MRI techniques including: (A) dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI); and (B) dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) for evaluating response to antiangiogenic therapy in patients with recurrent gliomas.

METHODS

Databases such as PubMed (MEDLINE included), EMBASE, and Google Scholar were searched for relevant original articles. The included studies were assessed for methodological quality with the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Medical imaging follow-up or histopathological analysis was used as the reference standard. The data were extracted by two reviewers independently, and then the sensitivity, specificity, summary receiver operating characteristic curve, area under the curve (AUC), and heterogeneity were calculated using Meta-Disc 1.4 software.

RESULTS

This study analyzed a total of six articles. The overall sensitivity for DCE-MRI and DSC-MRI was 0.69 [95% confidence interval (CI): 0.53-0.82], and the specificity was 0.99 (95%CI: 0.93-1) by a random effects model (DerSimonianee-Laird model). The likelihood ratio (LR) +, LR-, and diagnostic odds ratio (DOR) were 12.84 (4.54-36.28), 0.35 (0.22-0.53), and 24.44 (7.19-83.06), respectively. The AUC (± SE) was 0.9921 (± 0.0120), and the Q* index (± SE) was 0.9640 (± 0.0323). For DSC-MRI, the sensitivity was 0.73, the specificity was 0.98, the LR+ was 7.82, the LR- was 0.32, the DOR was 31.65, the AUC (± SE) was 0.9925 (± 0.0132), and the Q* index was 0.9649 (± 0.0363). For DCE-MRI, the sensitivity was 0.41, the specificity was 0.97, the LR+ was 5.34, the LR- was 0.71, the DOR was 8.76, the AUC (± SE) was 0.9922 (± 0.2218), and the Q* index was 0.8935 (± 0.3037).

CONCLUSION

This meta-analysis demonstrated a beneficial value of PW-MRI (DSC-MRI and DCE-MRI) in monitoring the response of recurrent gliomas to antiangiogenic therapy, with reasonable sensitivity, specificity, +LR, and -LR.

Repeatability of dynamic contrast enhanced vp parameter in healthy subjects and patients with brain tumors

PURPOSE

To study the repeatability of plasma volume (v_p) extracted from dynamic-contrast-enhanced (DCE) MRI in order to define threshold values for significant longitudinal changes, and to assess changes in patients with high-grade-glioma (HGG).

METHODS

Twenty eight healthy subjects, of which eleven scanned twice, were used to assess the repeatability of v_p within the normal-appearing brain tissue and to define threshold values for significant changes based on least-detected-differences (LDD) of mean v_p values and histogram comparisons using earth-mover's-distance (EMD). Sixteen patients with HGG were scanned longitudinally with eight patients scanned before and following bevacizumab therapy. Longitudinal changes were assessed based on defined threshold values in comparison to RANO criteria.

RESULTS

The threshold values for significant changes were: LDD = 0.0024 (ml/100 ml, 21%) for mean v_p and EMD = 4.14. In patients, in 20/24 comparisons, no significant longitudinal changes were detected for v_p within the normal-appearing brain tissue. Concurring results were obtained between changes in lesion volume (RANO criteria) and LDD or EMD values in cases diagnosed with progressive-disease, yet in about 50% of cases diagnosed with partial-response preliminary results demonstrated significant increase in v_p despite significant reductions in lesion volume. In two patients, these changes preceded progression detected at follow-up scans. In general, a good concordance was obtained between LDD and EMD.

CONCLUSION

This study shows high repeatability of v_p and provides threshold values for significant changes in longitudinal assessment of patients with brain tumors. Preliminary results suggest the use of v_p-DCE parameter to improve assessment of therapy response in patients with high-grade-glioma.

The antitumour growth and antiangiogenesis effects of xanthatin in murine glioma dynamically evaluated by dynamic contrast-enhanced magnetic resonance imaging

To investigate the suppressive effects of xanthatin on glioma growth in a nude mouse xenograft model and rat orthotopic implantation model using magnetic resonance imaging (MRI) to dynamically monitor the antitumour growth and antiangiogenesis effects of xanthatin. The nude mouse xenograft tumour model and rat orthotopic implantation model were established to observe the antitumour effects of xanthatin in vivo. In the rat orthotopic implanted tumour model, MRI scanning was used to dynamically monitor the antitumour growth effect and evaluate the antiangiogenesis effect of xanthatin. We found that xanthatin at a dose of 0.4 mg/10 g dramatically decreased the growth of xenograft tumours in nude mice. The antiangiogenesis effect of xanthatin C6 glioma was evaluated by dynamic contrast-enhanced (DCE) MRI via comparison of the volume transfer constant (K^trans ) value, a parameter that reflects vessel permeability. We found that xanthatin at the doses of 8 and 16 mg/kg significantly decreased the K^trans value, which suggests that xanthatin has antiangiogenesis effects. These data demonstrate the suppressive effects of xanthatin on C6 glioma occur via antiangiogenesis. Meanwhile, this study also provides evidence for the application of quantitative parameters of DCE-MRI for dynamically evaluating the growth and angiogenesis of intracranial tumours and for experimental and clinical research.

Antiangiogenic therapy: Markers of response, "normalization" and resistance

Currently in cancer treatment, one premise is to use antiangiogenic therapies in association with chemotherapy or radiotherapy to augment their efficacy by benefiting from the vascular "normalization" induced by antiangiogenic therapy. This concept defines the time during which the tumor blood vessels adopt normal-like morphology and functionality, i.e. the blood vessels become more mature, the perfusion augments and hypoxia decreases. To date, there is such a diversity of treatment protocols where the type of antiangiogenic to adopt, its dose and duration of administration are different, that knowing when and how to treat is problematic. In this review, we analyzed thoroughly preclinical and clinical studies that use antiangiogenic treatments to benefit from the "normalization" and showed that the effects depend on the type of antiangiogenic administrated (anti-VEGF, anti-VEGFR, Multi-Kinase Inhibitor) and on the duration of treatment. Finally, biomarkers of "normalization" and resistance that could be used in the clinic are presented.

Imaging biomarkers from multiparametric magnetic resonance imaging are associated with survival outcomes in patients with brain metastases from breast cancer

OBJECTIVES

The aim of this study is to investigate the correlation of survival outcomes with imaging biomarkers from multiparametric magnetic resonance imaging (MRI) in patients with brain metastases from breast cancer (BMBC).

METHODS

This study was approved by the institutional review board. Twenty-two patients with BMBC who underwent treatment involving bevacizumab on day 1, etoposide on days 2-4, and cisplatin on day 2 in 21-day cycles were prospectively enrolled for a phase II study. Three brain MRIs were performed: before the treatment, on day 1, and on day 21. Eight imaging biomarkers were derived from dynamic contrast-enhanced MRI (Peak, IAUC₆₀, K^trans, k_ep, v_e), diffusion-weighted imaging [apparent diffusion coefficient (ADC)], and MR spectroscopy (choline/N-acetylaspartate and choline/creatine ratios). The relative changes (Δ) in these biomarkers were correlated with the central nervous system (CNS)-specific progression-free survival (PFS) and overall survival (OS) using the Kaplan-Meier and Cox proportional hazard models.

RESULTS

There were no significant differences in the survival outcomes as per the changes in the biomarkers on day 1. On day 21, those with a low ΔK^trans (p = 0.024) or ΔADC (p = 0.053) reduction had shorter CNS-specific PFS; further, those with a low ΔPeak (p = 0.012) or ΔIAUC₆₀ (p = 0.04) reduction had shorter OS compared with those with high reductions. In multivariate analyses, ΔK^trans and ΔPeak were independent prognostic factors for CNS-specific PFS and OS, respectively, after controlling for age, size, hormone receptors, and performance status.

CONCLUSIONS

Multiparametric MRI may help predict the survival outcomes in patients with BMBC.

KEY POINTS

• Decreased angiogenesis after chemotherapy on day 21 indicated good survival outcome. • ΔK ^trans was an independent prognostic factors for CNS-specific PFS. • ΔPeak was an independent prognostic factors for OS. • Multiparametric MRI helps clinicians to assess patients with BMBC. • High-risk patients may benefit from more intensive follow-up or treatment strategies.

Can dynamic contrast-enhanced MRI evaluate VEGF expression in brain glioma? An MRI-guided stereotactic biopsy study

PURPOSE

To investigate whether pharmacokinetic parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can be used to evaluate vascular endothelial growth factor (VEGF) expression in brain glioma based on a point-to-point basis.

MATERIALS AND METHODS

Forty-seven patients with treatment-naïve glioma received preoperative DCE-MRI before stereotactic biopsy. We histologically quantified VEGF from section of stereotactic biopsies, and co-registered biopsy locations with localized measurements of DCE-MRI parameters including volume transfer coefficient (K^trans), reverse reflux rate constant (Kep), extracellular extravascular volume fraction (Ve) and blood plasma volume (Vp). The correlations between DCE-MRI parameters (K^trans, Kep, Ve and Vp) and VEGF were determined using Spearman correlation coefficient. P≤.05 was considered statistically significant.

RESULTS

Seventy-nine biopsy samples were obtained and graded into 45 high-grade gliomas (HGGs) and 34 low-grade gliomas (LGGs). K^trans showed a significant positive correlation with VEGF expression in HGGs group (ρ=0.505, P<0.001) and in combined group (LGGs+HGGs) (ρ=0.549, P<0.001), but not in LGGs group (P>0.05). Kep, Ve or Vp was not correlated with VEGF even though a positive trend showed (P>0.05).

CONCLUSIONS

DCE-MRI is a useful, non-invasive imaging technique for quantitative evaluation of VEGF, and its parameter K^trans other than Kep, Ve or Vp may be used as a surrogate for VEGF expression in brain gliomas.

Dynamic magnetic resonance imaging method based on golden-ratio cartesian sampling and compressed sensing

Dynamic magnetic resonance imaging (DMRI) is used to noninvasively trace the movements of organs and the process of drug delivery. The results can provide quantitative or semiquantitative pathology-related parameters, thus giving DMRI great potential for clinical applications. However, conventional DMRI techniques suffer from low temporal resolution and long scan time owing to the limitations of the k-space sampling scheme and image reconstruction algorithm. In this paper, we propose a novel DMRI sampling scheme based on a golden-ratio Cartesian trajectory in combination with a compressed sensing reconstruction algorithm. The results of two simulation experiments, designed according to the two major DMRI techniques, showed that the proposed method can improve the temporal resolution and shorten the scan time and provide high-quality reconstructed images.

Differentiation between vasogenic edema and infiltrative tumor in patients with high-grade gliomas using texture patch-based analysis

BACKGROUND

High-grade gliomas (HGGs) induce both vasogenic edema and extensive infiltration of tumor cells, both of which present with similar appearance on conventional MRI. Using current radiological criteria, differentiation between these tumoral and nontumoral areas within the nonenhancing lesion area remains challenging.

PURPOSE

To use radiomics patch-based analysis, based on conventional MRI, for the classification of the nonenhancing lesion area in patients with HGG into tumoral and nontumoral components.

STUDY TYPE

Prospective.

SUBJECTS

In all, 179 MRI scans were obtained from 102 patients: 67 patients with HGG and 35 patients with brain metastases. A subgroup of 15 patients with HGG were scanned before and following administration of bevacizumab.

FIELD STRENGTH/SEQUENCE

Pre and postcontrast agent T1 -weighted-imaging (WI), T2 WI, FLAIR, diffusion-tensor-imaging (DTI), and dynamic-contrast-enhanced (DCE)-MRI at 3T.

ASSESSMENT

A total of 225 histograms and gray-level-co-occurrence matrix-based features were extracted from the nonenhancing lesion area. Tumoral volumes of interest (VOIs) were defined at the peritumoral area in patients with HGG; nontumoral VOIs were defined in patients with brain metastasis. Twenty machine-learning algorithms including support-vector-machine (SVM), k-nearest neighbor, decision-trees, and ensemble classifiers were tested. The best classifier was trained on the entire labeled data, and was used to classify the entire data.

STATISTICAL TESTS

Dimensional reduction was performed on the 225 features using principal component analysis. Classification results were evaluated based on the sensitivity, specificity, and accuracy of each of the 20 classifiers, first based on a training and testing dataset (80% of the labeled data) in a 5-fold manner, and next by applying the best classifier to the validation data (the remaining 20% of the labeled data). Results were additionally evaluated by assessing differences in dynamic-contrast-enhanced plasma-volume (vp ) and volume-transfer-constant (ktrans ) values between the two components using Mann-Whitney U-test/t-test.

RESULTS

The best classification into tumoral and nontumoral lesion components was obtained using a linear SVM classifier, with average accuracy of 87%, sensitivity 86%, and specificity of 89% (for the training and testing data). Significantly higher vp and ktrans values (P < 0.0001) were detected in the tumoral compared to the nontumoral component. Preliminary classification results in a subgroup of patients treated with bevacizumab demonstrated a reduction mainly in the nontumoral component following administration of bevacizumab, enabling early assessment of disease progression in some patients.

DATA CONCLUSION

A radiomics patch-based analysis enables classification of the nonenhancing lesion area in patients with HGG. Preliminary results were promising and the proposed method has the potential to assist in clinical decision-making and to improve therapy response assessment in patients with HGG.

LEVEL OF EVIDENCE

1 Technical Efficacy Stage 4 J. Magn. Reson. Imaging 2018.

New Directions in Anti-Angiogenic Therapy for Glioblastoma

Anti-angiogenic therapy has become an important component in the treatment of many solid tumors given the importance of adequate blood supply for tumor growth and metastasis. Despite promising preclinical data and early clinical trials, anti-angiogenic agents have failed to show a survival benefit in randomized controlled trials of patients with glioblastoma. In particular, agents targeting vascular endothelial growth factor (VEGF) appear to prolong progression free survival, possibly improve quality of life, and decrease steroid usage, yet the trials to date have demonstrated no extension of overall survival. In order to improve duration of response and convey a survival benefit, additional research is still needed to explore alternative pro-angiogenic pathways, mechanisms of resistance, combination strategies, and biomarkers to predict therapeutic response.

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

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

Dynamic contrast-enhanced MR imaging pharmacokinetic parameters as predictors of treatment response of brain metastases in patients with lung cancer

OBJECTIVES

To determine the diagnostic accuracy of pharmacokinetic parameters measured by dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in predicting the response of brain metastases to antineoplastic therapy in patients with lung cancer.

METHODS

Forty-four consecutive patients with lung cancer, harbouring 123 newly diagnosed brain metastases prospectively underwent conventional 3-T MRI at baseline (within 1 month before treatment), during the early (7-10 weeks) and midterm (5-7 months) post-treatment period. An additional DCE MRI sequence was performed during baseline and early post-treatment MRI to evaluate baseline pharmacokinetic parameters (K ^trans, k _ep, v _e, v _p) and their early variation (∆K ^trans, ∆k _ep, ∆v _e, ∆v _p). The objective response was judged by the volume variation of each metastasis from baseline to midterm MRI. ROC curve analysis determined the best DCE MRI parameter to predict the objective response.

RESULTS

Baseline DCE MRI parameters were not associated with the objective response. Early ∆K ^trans, ∆v _e and ∆v _p were significantly associated with the objective response (p = 0.02, p = 0.001 and p = 0.02, respectively). The best predictor of objective response was ∆v _e with an area under the curve of 0.93 [95% CI = 0.87, 0.99].

CONCLUSIONS

DCE MRI and early ∆v _e may be a useful tool to predict the objective response of brain metastases in patients with lung cancer.

KEY POINTS

• DCE MRI could predict the response of brain metastases from lung cancer • ∆v _e was the best predictor of response • DCE MRI could be used to individualize patients' follow-up.

Reproducibility of dynamic contrast-enhanced MRI and dynamic susceptibility contrast MRI in the study of brain gliomas: a comparison of data obtained using different commercial software

PURPOSE

Dynamic susceptibility contrast MRI (DSC) and dynamic contrast-enhanced MRI (DCE) are useful tools in the diagnosis and follow-up of brain gliomas; nevertheless, both techniques leave the open issue of data reproducibility. We evaluated the reproducibility of data obtained using two different commercial software for perfusion maps calculation and analysis, as one of the potential sources of variability can be the software itself.

METHODS

DSC and DCE analyses from 20 patients with gliomas were tested for both the intrasoftware (as intraobserver and interobserver reproducibility) and the intersoftware reproducibility, as well as the impact of different postprocessing choices [vascular input function (VIF) selection and deconvolution algorithms] on the quantification of perfusion biomarkers plasma volume (Vp), volume transfer constant (K ^trans) and rCBV. Data reproducibility was evaluated with the intraclass correlation coefficient (ICC) and Bland-Altman analysis.

RESULTS

For all the biomarkers, the intra- and interobserver reproducibility resulted in almost perfect agreement in each software, whereas for the intersoftware reproducibility the value ranged from 0.311 to 0.577, suggesting fair to moderate agreement; Bland-Altman analysis showed high dispersion of data, thus confirming these findings. Comparisons of different VIF estimation methods for DCE biomarkers resulted in ICC of 0.636 for K ^trans and 0.662 for Vp; comparison of two deconvolution algorithms in DSC resulted in an ICC of 0.999.

CONCLUSIONS

The use of single software ensures very good intraobserver and interobservers reproducibility. Caution should be taken when comparing data obtained using different software or different postprocessing within the same software, as reproducibility is not guaranteed anymore.

Defining the endpoints: how to measure the efficacy of drugs that are active against central nervous system metastases

Brain metastases (BMs) are the most common cause of malignant central nervous system (CNS) tumors in adults. In the recent past, patients with BMs were excluded from clinical trials, but now, with the advent of new biological and immunological drugs, their inclusion is more common. In the last era response and progression criteria used across clinical trials have defined the importance to consider not only measurement changes of brain lesions but also the modification of parameters related to the metastases such as metabolism of tissue and its pathological features. Magnetic resonance imaging (MRI) represents the first choice in the evaluation of BMs; the computed tomography (CT) scan will be made only in case of MRI's contraindication. CT, MRI and positron emission tomography (PET-CT), may be used to monitor response to treatment as part of clinical and radiological follow up. In the evaluation of response to treatment, MRI shows superior accuracy in comparison to CT; PET-CT is useful in particularly in cases of BMs underwent to locoregional therapies in the differential diagnosis between recurrence or radionecrosis. Now is possible to use functional imaging as CT-perfusion, dynamic susceptibility contrast (DSC) MR imaging, dynamic contrast-enhanced (DCE) MR imaging, diffusion-weighted MR imaging and MR-Spectroscopy in the evaluation of treatment response; these imaging techniques can provide qualitative and quantitative imaging parameters that allow pathophysiologic correlation. In the evaluation of the response to immunotherapy treatments, the immune-related response criteria (irRC) are considered as the gold standard. The irRC utilizes bidimensional measurements, quantifying the tumor dimension using a product of the longest diameter and the longest perpendicular diameter. We analyze clinical and radiological criteria to better define outcome of drugs for BMs from solid tumors in the new era of biological and immunological therapies.

Bloch-Siegert B1-Mapping Improves Accuracy and Precision of Longitudinal Relaxation Measurements in the Breast at 3 T

Variable flip angle (VFA) sequences are a popular method of calculating T₁ values, which are required in a quantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI). B₁ inhomogeneities are substantial in the breast at 3 T, and these errors negatively impact the accuracy of the VFA approach, thus leading to large errors in the DCE-MRI parameters that could limit clinical adoption of the technique. This study evaluated the ability of Bloch–Siegert B₁ mapping to improve the accuracy and precision of VFA-derived T₁ measurements in the breast. Test–retest MRI sessions were performed on 16 women with no history of breast disease. T₁ was calculated using the VFA sequence, and B₁ field variations were measured using the Bloch–Siegert methodology. As a gold standard, inversion recovery (IR) measurements of T₁ were performed. Fibroglandular tissue and adipose tissue from each breast were segmented using the IR images, and the mean T₁ was calculated for each tissue. Accuracy was evaluated by percent error (%err). Reproducibility was assessed via the 95% confidence interval (CI) of the mean difference and repeatability coefficient (r). After B₁ correction, %err significantly (P < .001) decreased from 17% to 8.6%, and the 95% CI and r decreased from ±94 to ±38 milliseconds and from 276 to 111 milliseconds, respectively. Similar accuracy and reproducibility results were observed in the adipose tissue of the right breast and in both tissues of the left breast. Our data show that Bloch–Siegert B₁ mapping improves accuracy and precision of VFA-derived T₁ measurements in the breast.

Evaluation of recurrent high-grade gliomas treated with bevacizumab: A preliminary report of 3D pseudocontinuous artery spin labeling

PURPOSE

To investigate the role of cerebral blood flow (CBF) derived from a 3D fast spin echo (FSE) pseudocontinuous artery spin labeling (pcASL) sequence in evaluating the survival rate of recurrent high-grade gliomas (rHGGs) that were treated with bevacizumab (BEV).

MATERIALS AND METHODS

Sixteen patients with rHGGs who underwent 3T 3D FSE pcASL imaging 1-2 days before (baseline or pre-BEV) and within 1 month after BEV treatment initiation (post-BEV) were included in the study. Average (aCBF) and maximum (mCBF) cerebral blood flow of the enhancing tumor, their respective normalized values to contralateral normal-appearing white matter (rCBF_wm and mCBF_wm) and cerebellum (rCBF_cb and mCBF_cb), and the related changes between baseline and post-BEV were evaluated. Receiver operating characteristic (ROC) curve analysis was utilized to define the optimal cutoff perfusion values for overall survival (OS) and progression-free survival (PFS) stratification. Kaplan-Meier analysis with log-rank test was applied to assess and compare PFS and OS rates.

RESULTS

All the CBF measurements pre-BEV and post-BEV treatment were significantly different except mCBF. The CBF measurements (aCBF, rCBF_wm, rCBF_cb, mCBF_wm and mCBF_cb) pre-BEV all decreased post-BEV treatment. Cutoffs of aCBF (43.72 ml/100g/min) pre-BEV for OS, rCBF_cb (1.09) pre-BEV for PFS and OS, and ΔaCBF (-0.37) for PFS were found to be statistically significant in survival stratification (404 days vs. 140 days, P = 0.026; 251 days vs. 112 days, P = 0.044; 404 days vs. 194 days, P = 0.046; 267 days vs. 116 days, P = 0.048, respectively).

CONCLUSION

Three dimensional FSE pcASL can detect the decrease of perfusion in rHGGs treated with BEV and is a potential promising technique in stratifying survival rate of rHGGs under BEV treatment.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:565-573.

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

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

Non-parametric intravoxel incoherent motion analysis in patients with intracranial lesions: Test-retest reliability and correlation with arterial spin labeling

Intravoxel incoherent motion (IVIM) analysis of diffusion imaging data provides biomarkers of true passive water diffusion and perfusion properties. A new IVIM algorithm with variable adjustment of the b-value threshold separating diffusion and perfusion effects was applied for cerebral tissue characterization in healthy volunteers, computation of test-retest reliability, correlation with arterial spin labeling, and assessment of applicability in a small cohort of patients with malignant intracranial masses. The main results of this study are threefold: (i) accounting for regional differences in the separation of the perfusion and the diffusion components improves the reliability of the model parameters; (ii) if differences in the b-value threshold are not accounted for, a significant tissue-dependent systematic bias of the IVIM parameters occurs; (iii) accounting for voxel-wise differences in the b-value threshold improves the correlation with CBF measurements in healthy volunteers and patients. The proposed algorithm provides a robust characterization of regional micro-vascularization and cellularity without a priori assumptions on tissue diffusion properties. The glioblastoma multiforme with its inherently high variability of tumor vascularization and tumor cell density may benefit from a non-invasive clinical characterization of diffusion and perfusion properties.

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The novel IVIM algorithm accounts for regional differences in the separation of the perfusion and the diffusion components.

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The algorithm improves the reliability of IVIM parameters.

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The algorithm improves the correlation with CBF in healthy volunteers and patients.