Diagnostic utility of restriction spectrum imaging (RSI) in glioblastoma patients after concurrent radiation-temozolomide treatment: A pilot study

Diagnostic Utility of Restriction Spectrum Imaging in Head and Neck Tumors: A Pilot Study

OBJECTIVE

Imaging is crucial in the assessment of head and neck cancers for site, extension, and enlarged lymph nodes. Restriction spectrum imaging (RSI) is a new diffusion-weighted magnetic resonance imaging (MRI) technique that enhances the ability to differentiate aggressive cancer from low-grade or benign tumors and helps guide treatment and biopsy. Its contribution to imaging of brain and prostate tumors has been previously published. However, there are no prior studies using RSI sequence in head and neck tumors. The purpose of this study was to evaluate the feasibility of performing RSI in head and neck cancer.

METHODS

An additional RSI sequence was added in the routine MRI neck protocol for 13 patients diagnosed with head and neck cancer between November 2018 and April 2019. Restriction spectrum imaging sequence was performed with b values of 0, 500, 1500, and 3000 s/mm 2 and 29 directions on 1.5T magnetic resonance scanners.Diffusion-weighted imaging (DWI) images and RSI images were compared according to their ability to detect the primary malignancy and possible metastatic lymph nodes.

RESULTS

In 71% of the patients, RSI outperformed DWI in detecting the primary malignancy and possible metastatic lymph nodes, whereas in the remaining cases, the 2 were comparable. In 66% of the patients, RSI detected malignant lymph nodes that DWI/apparent diffusion coefficient failed to detect.

CONCLUSIONS

This is the first study of RSI in head and neck imaging and showed its superiority over the conventional DWI sequence. Because of its ability to differentiate benign and malignant lymph nodes in some cases, the addition of RSI to routine head and neck MRI should be considered.

Multivariate genome-wide association study on tissue-sensitive diffusion metrics highlights pathways that shape the human brain

The molecular determinants of tissue composition of the human brain remain largely unknown. Recent genome-wide association studies (GWAS) on this topic have had limited success due to methodological constraints. Here, we apply advanced whole-brain analyses on multi-shell diffusion imaging data and multivariate GWAS to two large scale imaging genetic datasets (UK Biobank and the Adolescent Brain Cognitive Development study) to identify and validate genetic association signals. We discover 503 unique genetic loci that have impact on multiple regions of human brain. Among them, more than 79% are validated in either of two large-scale independent imaging datasets. Key molecular pathways involved in axonal growth, astrocyte-mediated neuroinflammation, and synaptogenesis during development are found to significantly impact the measured variations in tissue-specific imaging features. Our results shed new light on the biological determinants of brain tissue composition and their potential overlap with the genetic basis of neuropsychiatric disorders.

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques

Objective

Summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments.

Methods

Experts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics).

Results

High-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies.

Conclusion

Considerable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.

Effects of Multi-Shell Free Water Correction on Glioma Characterization

Diffusion MRI is a useful tool to investigate the microstructure of brain tumors. However, the presence of fast diffusing isotropic signals originating from non-restricted edematous fluids, within and surrounding tumors, may obscure estimation of the underlying tissue characteristics, complicating the radiological interpretation and quantitative evaluation of diffusion MRI. A multi-shell regularized free water (FW) elimination model was therefore applied to separate free water from tissue-related diffusion components from the diffusion MRI of 26 treatment-naïve glioma patients. We then investigated the diagnostic value of the derived measures of FW maps as well as FW-corrected tensor-derived maps of fractional anisotropy (FA). Presumed necrotic tumor regions display greater mean and variance of FW content than other parts of the tumor. On average, the area under the receiver operating characteristic (ROC) for the classification of necrotic and enhancing tumor volumes increased by 5% in corrected data compared to non-corrected data. FW elimination shifts the FA distribution in non-enhancing tumor parts toward higher values and significantly increases its entropy (p ≤ 0.003), whereas skewness is decreased (p ≤ 0.004). Kurtosis is significantly decreased (p < 0.001) in high-grade tumors. In conclusion, eliminating FW contributions improved quantitative estimations of FA, which helps to disentangle the cancer heterogeneity.

Diagnostic accuracy of diffusion-weighted imaging in differentiating glioma recurrence from posttreatment-related changes: a meta-analysis

BACKGROUND

Magnetic resonance imaging (MRI) is the most commonly used imaging method to evaluate glioma recurrence. However, conventional MRI has difficulty distinguishing glioma accurately. This study aimed to explore the value of diffusion weighted imaging (DWI) in evaluating glioma recurrence and post-treatment-related changes.

RESEARCH DESIGN AND METHODS

PubMed, Cochrane Library, Embase, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Database and China Science and Technology Journal Database were extensively searched in accordance with inclusion criteria and exclusion criteria to obtain appropriate included studies. The quality of the included studies was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Combined sensitivity and specificity and the area under the summary receiver operating characteristic curve (SROC) with the 95% confidence interval (CI) were calculated.

RESULTS

Seventeen high-quality studies were included. The combined sensitivity was 0.82 (95% CI: 0.76-0.87), the specificity was 0.83 (95% CI: 0.76-0.89), the positive likelihood ratio was 4.9 (95% CI: 3.2-7.5), the negative likelihood ratio was 0.21 (95% CI: 0.15-0.30), the diagnostic odds ratio was 23 (95%: CI 11-48), and the area under the SROC was 0.90 (95% CI: 0.87-0.92).

CONCLUSIONS

This meta-analysis suggests that DWI has high sensitivity, specificity and accuracy in differentiating glioma recurrence.

Clinical outcomes as a function of the number of samples taken during stereotactic needle biopsies: a meta-analysis

BACKGROUND

Stereotactic needle biopsy remains the cornerstone for tissue diagnosis for tumors located in regions of the brain that are difficult to access through open surgery.

OBJECTIVE

We perform a meta-analysis of the literature to examine the relation between number of samples taken during biopsy and diagnostic yield, morbidity and mortality.

METHODS

We identified 2416 patients from 28 cohorts in studies published in PubMed database that studied stereotactic needle biopsies for tumor indications. Meta-analysis by proportions and meta-regression analyses were performed.

RESULTS

On meta-analysis, the morbidity profile of the published needle biopsy studies clustered into three groups: studies that performed < 3 samples (n = 8), 3-6 samples (n = 13), and > 6 samples during biopsy (n = 7). Pooled estimates for biopsy related morbidity were 4.3%, 16.3%, and 17% for studies reporting < 3, 3-6, and > 6 biopsy samples, respectively. While these morbidity estimates significantly differed (p < 0.001), the diagnostic yields reported for studies performing < 3 biopsies, 3-6 samples, and > 6 samples were comparable. Pooled estimates of diagnostic yield for these three groups were 90.4%, 93.8%, and 88.1%, respectively. Mortality did not significantly differ between studies reporting differing number of samples taken during biopsy.

CONCLUSIONS

Our meta-analysis suggests that morbidity risk in needle biopsy is non-linearly associated with the number of samples taken. There was no association between the number of biopsies taken, and diagnostic yield or mortality.

Predicting Survival in Glioblastoma Patients Using Diffusion MR Imaging Metrics-A Systematic Review

Simple Summary

An accurate survival analysis is crucial for disease management in glioblastoma (GBM) patients. Due to the ability of the diffusion MRI techniques of providing a quantitative assessment of GBM tumours, an ever-growing number of studies aimed at investigating the role of diffusion MRI metrics in survival prediction of GBM patients. Since the role of diffusion MRI in prediction and evaluation of survival outcomes has not been fully addressed and results are often controversial or unsatisfactory, we performed this systematic review in order to collect, summarize and evaluate all studies evaluating the role of diffusion MRI metrics in predicting survival in GBM patients. We found that quantitative diffusion MRI metrics provide useful information for predicting survival outcomes in GBM patients, mainly in combination with other clinical and multimodality imaging parameters.

Abstract

Despite advances in surgical and medical treatment of glioblastoma (GBM), the medium survival is about 15 months and varies significantly, with occasional longer survivors and individuals whose tumours show a significant response to therapy with respect to others. Diffusion MRI can provide a quantitative assessment of the intratumoral heterogeneity of GBM infiltration, which is of clinical significance for targeted surgery and therapy, and aimed at improving GBM patient survival. So, the aim of this systematic review is to assess the role of diffusion MRI metrics in predicting survival of patients with GBM. According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, a systematic literature search was performed to identify original articles since 2010 that evaluated the association of diffusion MRI metrics with overall survival (OS) and progression-free survival (PFS). The quality of the included studies was evaluated using the QUIPS tool. A total of 52 articles were selected. The most examined metrics were associated with the standard Diffusion Weighted Imaging (DWI) (34 studies) and Diffusion Tensor Imaging (DTI) models (17 studies). Our findings showed that quantitative diffusion MRI metrics provide useful information for predicting survival outcomes in GBM patients, mainly in combination with other clinical and multimodality imaging parameters.

Long intergenic noncoding RNA 00021 promotes glioblastoma temozolomide resistance by epigenetically silencing p21 through Notch pathway

Increasing findings are suggesting the vital roles of long noncoding RNAs (lncRNAs) in the glioblastoma tumorigenesis. However, whether the novel lncRNA LINC00021 modulates temozolomide (TMZ) resistance of glioblastoma is still unclear. Clinically, lncRNA LINC00021 was significantly up-regulated in glioblastoma, especially the TMZ-resistant tissue and cells, and the LINC00021 overexpression was closely correlated to TMZ resistance and unfavorable prognosis. Functionally, LINC00021 positively promoted the TMZ resistance and reduced apoptosis. Mechanistically, transcription factor E2F1 activated the expression of LINC00021. Moreover, LINC00021 regulated the glioblastoma TMZ resistance through Notch pathway and epigenetically silenced p21 expression via recruiting EZH2. Collectively, present research indicates the critical roles of lncRNA LINC00021 in glioblastoma genesis, providing a novel insight for TMZ resistance in glioblastoma.

Radiation-induced extracellular vesicle (EV) release of miR-603 promotes IGF1-mediated stem cell state in glioblastomas

Background

Recurrence after radiation therapy is nearly universal for glioblastomas, the most common form of adult brain cancer. The study aims to define clinically pertinent mechanisms underlying this recurrence.

Methods

microRNA (miRNA) profiling was performed using matched pre- and post-radiation treatment glioblastoma specimens from the same patients. All specimens harbored unmethylated O⁶-methylguanine-DNA methyltransferase promoters (umMGMT) and wild-type isocitrate dehydrogenase (wtIDH). The most altered miRNA, miR-603, was characterized.

Findings

While nearly all miRNAs remained unchanged after treatment, decreased levels of few, select miRNAs in the post-treatment specimens were observed, the most notable of which involved miR-603. Unbiased profiling of miR-603 targets revealed insulin-like growth factor 1 (IGF1) and IGF1 receptor (IGF1R). Ionizing radiation (IR) induced cellular export of miR-603 through extracellular vesicle (EV) release, thereby de-repressing IGF1 and IGF1R. This de-repression, in turn, promoted cancer stem-cell (CSC) state and acquired radiation resistance in glioblastomas. Export of miR-603 additionally de-repressed MGMT, a DNA repair protein responsible for detoxifying DNA alkylating agents, to promote cross-resistance to these agents. Ectopic miR-603 expression overwhelmed cellular capacity for miR-603 export and synergized with the tumoricidal effects of IR and DNA alkylating agents.

Interpretation

Profiling of matched pre- and post-treatment glioblastoma specimens revealed altered homeostasis of select miRNAs in response to radiation. Radiation-induced EV export of miR-603 simultaneously promoted the CSC state and up-regulated DNA repair to promote acquired resistance. These effects were abolished by exogenous miR-603 expression, suggesting potential for clinical translation.

Funding

NIH 1R01NS097649-01, 9R44GM128223-02, 1R01CA240953-01, the Doris Duke Charitable Foundation Clinical Scientist Development Award, The Sontag Foundation Distinguished Scientist Award, the Kimmel Scholar Award, and BWF 1006774.01 (C.C.C).