Apparent Diffusion Coefficient Metrics to Differentiate between Treatment-Related Abnormalities and Tumor Progression in Post-Treatment Glioblastoma Patients: A Retrospective Study

Distinguishing treatment-related abnormalities (TRA) from tumor progression (TP) in glioblastoma patients is a diagnostic imaging challenge due to the identical morphology of conventional MR imaging sequences. Diffusion-weighted imaging (DWI) and its derived images of the apparent diffusion coefficient (ADC) have been suggested as diagnostic tools for this problem. The aim of this study is to determine the diagnostic accuracy of different cut-off values of the ADC to differentiate between TP and TRA. In total, 76 post-treatment glioblastoma patients with new contrast-enhancing lesions were selected. Lesions were segmented using a T1-weighted, contrast-enhanced scan. The mean ADC values of the segmentations were compared between TRA and TP groups. Diagnostic accuracy was compared by use of the area under the curve (AUC) and the derived sensitivity and specificity values from cutoff points. Although ADC values in TP (mean = 1.32 × 10-3 mm2/s; SD = 0.31 × 10-3 mm2/s) were significantly different compared to TRA (mean = 1.53 × 10-3 mm2/s; SD = 0.28 × 10-3 mm2/s) (p = 0.003), considerable overlap in their distributions exists. The AUC of ADC values to distinguish TP from TRA was 0.71, with a sensitivity and specificity of 65% and 70%, respectively, at an ADC value of 1.47 × 10-3 mm2/s. These findings therefore indicate that ADC maps should not be used in discerning between TP and TRA at a certain timepoint without information on temporal evolution.

Stereotactic laser ablation in neuro-oncology - A survey among European neurosurgeons

Introduction

In the last decades, the application of stereotactic laser ablation (SLA) for the treatment of intracranial tumours has been growing, even though comparative trials are lacking. Our aim was to investigate the familiarity with SLA of neurosurgeons in Europe and their opinion regarding potential neuro-oncological indications. Furthermore, we investigated treatment preferences and variability for three exemplar neuro-oncological cases and willingness to refer for SLA.

Material and methods

A 26-questions survey was mailed to members of the EANS neuro-oncology section. We presented three clinical cases of respectively deep-seated glioblastoma, recurrent metastasis and recurrent glioblastoma. Descriptive statistics was applied to report results.

Results

110 respondents completed all questions. Recurrent glioblastoma and recurrent metastases were regarded as the most feasible indications for SLA (chosen by 69% and 58% of the respondents) followed by newly diagnosed high-grade gliomas (31%). Seventy percent of respondents would refer patients for SLA. The majority of respondents would consider SLA as a treatment option for all three presented cases: 79% for the deep-seated glioblastoma case, 65% for the recurrent metastasis case and 76% for the recurrent glioblastoma case. Among respondents who wouldn't consider SLA, preference for standard treatment and lack of clinical evidence were reported as the main reasons.

Conclusions

Most of respondents considered SLA as a treatment option for recurrent glioblastoma, recurrent metastases and newly diagnosed deep-seated glioblastoma. At the moment the current evidence to support such a treatment is very low. Comparative prospective trials are needed to support the use of SLA and determine proper indications.

Subclassification of the Koos grade 2 vestibular schwannoma into 2a and 2b for individualized patient care: a validity and reliability study

OBJECTIVE

Vestibular schwannoma (VS) growth of ≥2 mm during serial MRI observation, irrespective of size, is the benchmark for treatment initiation in almost all centers. Although the probability of less optimal outcomes significantly increases in VS closer to the brainstem, early intervention does not improve long-term quality of life. Moving beyond the recommendation of definitive treatment for all VS after detected growth, we subclassified Koos 2 tumors based on extrameatal extension and relation to the brainstem. The aim of the current study was to evaluate the Koos 2 subclassification's validity and the inter-and intra-rater reliability of the entire Koos classification.

METHODS

Six experts, including neurosurgeons, otorhinolaryngologists and radiologists from two tertiary referral centers, classified 43 VS MRI scans. Validity of the Koos 2 subclassification was evaluated by the percentage agreement against the multidisciplinary skull base tumor board management advice. Inter- and intra-rater reliability were calculated using the intraclass correlation coefficient (ICC).

RESULTS

Validity was almost perfect in Koos 2a VSs with a 100% agreement and 87.5% agreement for Koos 2b. Inter-rater reliability for all Koos grades was significantly excellent (ICC 0.91; 95%CI 0.866 to 0.944, p= <0.001). Five raters had an excellent intra-rater reliability (ICC > 0.90; p= <0.01) and one rater had a good intra-rater reliability (ICC 0.88; 95% CI 0.742 to 0.949).

CONCLUSIONS

Although multiple factors influence decision-making, the classification of Koos 2a and 2b with excellent inter- and intra-rater reliability, can aid in recommending treatment initiation, moving beyond detected tumor growth, aiming to optimize patient centered care.

The Aftercare Survey: Assessment and intervention practices after brain tumor surgery in Europe

Background

People with gliomas need specialized neurosurgical, neuro-oncological, psycho-oncological, and neuropsychological care. The role of language and cognitive recovery and rehabilitation in patients' well-being and resumption of work is crucial, but there are no clear guidelines for the ideal timing and character of assessments and interventions. The goal of the present work was to describe representative (neuro)psychological practices implemented after brain surgery in Europe.

Methods

An online survey was addressed to professionals working with individuals after brain surgery. We inquired about the assessments and interventions and the involvement of caregivers. Additionally, we asked about recommendations for an ideal assessment and intervention plan.

Results

Thirty-eight European centers completed the survey. Thirty of them offered at least one postsurgical (neuro)psychological assessment, mainly for language and cognition, especially during the early recovery stage and at long term. Twenty-eight of the participating centers offered postsurgical therapies. Patients who stand the highest chances of being included in evaluation and therapy postsurgically are those who underwent awake brain surgery, harbored a low-grade glioma, or showed poor recovery. Nearly half of the respondents offer support programs to caregivers, and all teams recommend them. Treatments differed between those offered to individuals with low-grade glioma vs those with high-grade glioma. The figure of caregiver is not yet fully recognized in the recovery phase.

Conclusion

We stress the need for more complete rehabilitation plans, including the emotional and health-related aspects of recovery. In respondents' opinions, assessment and rehabilitation plans should also be individually tailored and goal-directed (eg, professional reinsertion).

Accuracy of Machine Learning Algorithms for the Classification of Molecular Features of Gliomas on MRI: A Systematic Literature Review and Meta-Analysis

Simple Summary

Glioma prognosis and treatment are based on histopathological characteristics and molecular profile. Following the World Health Organization (WHO) guidelines (2016), the most important molecular diagnostic markers include IDH1/2-genotype and 1p/19q codeletion status, although more recent publications also include ARTX genotype and TERT- and MGMT promoter methylation. Machine learning algorithms (MLAs), however, were described to successfully determine these molecular characteristics non-invasively by using magnetic resonance imaging (MRI) data. The aim of this review and meta-analysis was to define the diagnostic accuracy of MLAs with regard to these different molecular markers. We found high accuracies of MLAs to predict each individual molecular marker, with IDH1/2-genotype being the most investigated and the most accurate. Radiogenomics could therefore be a promising tool for discriminating genetically determined gliomas in a non-invasive fashion. Although encouraging results are presented here, large-scale, prospective trials with external validation groups are warranted.

Abstract

Treatment planning and prognosis in glioma treatment are based on the classification into low- and high-grade oligodendroglioma or astrocytoma, which is mainly based on molecular characteristics (IDH1/2- and 1p/19q codeletion status). It would be of great value if this classification could be made reliably before surgery, without biopsy. Machine learning algorithms (MLAs) could play a role in achieving this by enabling glioma characterization on magnetic resonance imaging (MRI) data without invasive tissue sampling. The aim of this study is to provide a performance evaluation and meta-analysis of various MLAs for glioma characterization. Systematic literature search and meta-analysis were performed on the aggregated data, after which subgroup analyses for several target conditions were conducted. This study is registered with PROSPERO, CRD42020191033. We identified 724 studies; 60 and 17 studies were eligible to be included in the systematic review and meta-analysis, respectively. Meta-analysis showed excellent accuracy for all subgroups, with the classification of 1p/19q codeletion status scoring significantly poorer than other subgroups (AUC: 0.748, p = 0.132). There was considerable heterogeneity among some of the included studies. Although promising results were found with regard to the ability of MLA-tools to be used for the non-invasive classification of gliomas, large-scale, prospective trials with external validation are warranted in the future.

Laser Interstitial Thermal Therapy in Patients with Newly Diagnosed Glioblastoma: A Systematic Review

BACKGROUND

Laser interstitial thermal therapy (LITT) is a minimal invasive neurosurgical technique for the treatment of brain tumors. Results of LITT have been reported in a case series of patients with deep seated and/or recurrent glioblastoma or cerebral metastases. With this review we aim to summarize the currently available evidence regarding safety and effectiveness of LITT in patients with newly diagnosed glioblastoma (nGBM).

METHODS

A literature search was performed using electronic databases (PubMed and Embase). Papers were assessed for the methodological quality using the Risk Of Bias In Non- randomised Studies - of Interventions (ROBINS-I) tool, and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) was used to assess the quality of the evidence.

RESULTS

We identified 835 papers of which only 11 articles were eligible for our review. All papers suffered from serious or critical risk of bias, and the quality of evidence was graded as very low according to the GRADE criteria. None of the studies was randomized and reporting of confounders and other parameters was poor. Median overall survival (OS) ranged from 4.1 to 32 months and progression free survival (PFS) from 2 to 31 months. The mean complication rate was 33.7%. No quality of life or cost-effectiveness data were reported.

CONCLUSIONS

Due to the low quality of the studies, it is not possible to draw firm conclusions regarding the (cost) effectiveness of LITT in patients with newly diagnosed glioblastoma. The low quality of evidence shows the need for a well-designed prospective multicenter randomized controlled trial.

Information Recall in Pre-Operative Consultation for Glioma Surgery Using Actual Size Three-Dimensional Models

Three-dimensional (3D) technologies are being used for patient education. For glioma, a personalized 3D model can show the patient specific tumor and eloquent areas. We aim to compare the amount of information that is understood and can be recalled after a pre-operative consult using a 3D model (physically printed or in Augmented Reality (AR)) versus two-dimensional (2D) MR images. In this explorative study, healthy individuals were eligible to participate. Sixty-one participants were enrolled and assigned to either the 2D (MRI/fMRI), 3D (physical 3D model) or AR groups. After undergoing a mock pre-operative consultation for low-grade glioma surgery, participants completed two assessments (one week apart) testing information recall using a standardized questionnaire. The 3D group obtained the highest recall scores on both assessments (Cohen’s d = 1.76 and Cohen’s d = 0.94, respectively, compared to 2D), followed by AR and 2D, respectively. Thus, real-size 3D models appear to improve information recall as compared to MR images in a pre-operative consultation for glioma cases. Future clinical studies should measure the efficacy of using real-size 3D models in actual neurosurgery patients.

Mapping actionable pathways and mutations in brain tumours using targeted RNA next generation sequencing

Many biology-based precision drugs are available that neutralize aberrant molecular pathways in cancer. Molecular heterogeneity and the lack of reliable companion diagnostic biomarkers for many drugs makes targeted treatment of cancer inaccurate for many individuals. Identifying actionable hyperactive biological pathways in individual cancers may improve this situation.

To achieve this we applied a novel targeted RNA next generation sequencing (t/RNA-NGS) technique to surgically obtained glioma tissues. The test combines mutation detection with analysis of biological pathway activities that are involved in tumour behavior in many cancer types (e.g. tyrosine kinase signaling, angiogenesis signaling, immune response, metabolism), via quantitative measurement of transcript levels and splice variants of hundreds of genes. We here present proof of concept that the technique, which uses molecular inversion probes, generates a histology-independent molecular diagnosis and identifies classifiers that are strongly associated with conventional histopathology diagnoses and even with patient prognosis. The test not only confirmed known glioma-associated molecular aberrations but also identified aberrant expression levels of actionable genes and mutations that have so far been considered not to be associated with glioma, opening up the possibility of drug repurposing for individual patients. Its cost-effectiveness makes t/RNA-NGS to an attractive instrument to aid oncologists in therapy decision making.

NIMG-65. PREDICTING PROGNOSIS AND CANCER HOTSPOT MUTATIONS USING QUALITATIVE MR IMAGING ANALYSIS IN GLIOBLASTOMA

INTRODUCTION

Tumor heterogeneity poses one of the major limitations in improving the treatment for glioblastoma (GBM), which calls for new clinically relevant predictive models. This study aims to investigate non-invasive diagnostic methods, including patient characteristics and qualitative imaging analysis as a prognostic classifier and predictor for druggable oncogenes.

METHODS

We performed a retrospective analysis on 143 GBM patients (discovery cohort). Diagnostic MRIs were re-analyzed for qualitative imaging features (VASARI features). DNA was extracted from formalin-fixed, paraffin-embedded GBM tissue of the discovery cohort for next-generation sequencing (Ion Torrent Cancer Hotspot panel v2Plus), TERT-promoter mutation and MGMT-methylation analysis. Multivariable regression analysis was used to determine the prognostic and predictive value of VASARI features.

RESULTS

Of the 143 patients, median age was 61.4 years (range 15.5–84.6) with a median overall survival of 12 months (range 0–142). We observed IDH1 R132H mutation in 8.5%, MGMT-promotor methylation in 26.1%, TERT-promotor mutation (C250T;C228T) in 69.5%, EGFR mutation in 20.3% and EGFR amplification in 37.5% of all patients. A set of eight VASARI features was identified to be associated with overall survival (p< 0.001), which is currently being validated in an external dataset (n= 184). Interestingly, VASARI features appeared to be associated with IDH1-mutation (four features, p=0.004), TERT-promotor mutation (five features, p-value < 0.001), EGFR mutation (five features, p-value < 0.001) and EGFR amplification (seven features, p-value < 0.001) but not with MGMT-methylation (two features, p-value=0.054). Additional cancer hotspots are currently being analyzed and internal validation is ongoing.

CONCLUSION AND FUTURE PERSPECTIVES

We propose an integrated prognostic classifier comprising MRI features, also associated with GBM-specific molecular alterations. Additionally, quantitative MRI radiomics features are being extracted from the discovery and validation set and incorporated in the prognostic classifier. Subsequently, radiomics and VASARI features will be correlated to intratumoral heterogeneity, assessed by tissue micro-array analysis of the discovery cohort.

Pilot feasibility study of in vivo intraoperative quantitative optical coherence tomography of human brain tissue during glioma resection

This study investigates the feasibility of in vivo quantitative optical coherence tomography (OCT) of human brain tissue during glioma resection surgery in six patients. High-resolution detection of glioma tissue may allow precise and thorough tumor resection while preserving functional brain areas, and improving overall survival. In this study, in vivo 3D OCT datasets were collected during standard surgical procedure, before and after partial resection of the tumor, both from glioma tissue and normal parenchyma. Subsequently, the attenuation coefficient was extracted from the OCT datasets using an automated and validated algorithm. The cortical measurements yield a mean attenuation coefficient of 3.8 ± 1.2 mm-1 for normal brain tissue and 3.6 ± 1.1 mm-1 for glioma tissue. The subcortical measurements yield a mean attenuation coefficient of 5.7 ± 2.1 and 4.5 ± 1.6 mm-1 for, respectively, normal brain tissue and glioma. Although the results are inconclusive with respect to trends in attenuation coefficient between normal and glioma tissue due to the small sample size, the results are in the range of previously reported values. Therefore, we conclude that the proposed method for quantitative in vivo OCT of human brain tissue is feasible during glioma resection surgery.

Glioma: experimental models and reality

In theory, in vitro and in vivo models for human gliomas have great potential to not only enhance our understanding of glioma biology, but also to facilitate the development of novel treatment strategies for these tumors. For reliable prediction and validation of the effects of different therapeutic modalities, however, glioma models need to comply with specific and more strict demands than other models of cancer, and these demands are directly related to the combination of genetic aberrations and the specific brain micro-environment gliomas grow in. This review starts with a brief introduction on the pathological and molecular characteristics of gliomas, followed by an overview of the models that have been used in the last decades in glioma research. Next, we will discuss how these models may play a role in better understanding glioma development and especially in how they can aid in the design and optimization of novel therapies. The strengths and weaknesses of the different models will be discussed in light of genotypic, phenotypic and metabolic characteristics of human gliomas. The last part of this review provides some examples of how therapy experiments using glioma models can lead to deceptive results when such characteristics are not properly taken into account.

Differentiation between nerve and adipose tissue using wide-band (350-1,830 nm) in vivo diffuse reflectance spectroscopy

BACKGROUND

Intraoperative nerve localization is of great importance in surgery. In certain procedures, where nerves show visual resemblance to surrounding adipose tissue, this can be particularly challenging for the human eye. An example of such a delicate procedure is thyroid and parathyroid surgery, where iatrogenic injury of the recurrent laryngeal nerve can result in transient or permanent vocal problems (0.5-2.0% reported incidence). A camera system, enabling nerve-specific image enhancement, would be useful in preventing such complications. This might be realized with hyperspectral camera technology using silicon (Si) or indium gallium arsenide (InGaAs) sensor chips.

METHODS

As a first step towards such a camera, we evaluated the performance of diffuse reflectance spectroscopy by analysing spectra collected during 18 thyroid and parathyroid resections. We assessed the contrast information present in two different spectral ranges, for respectively Si and InGaAs sensors. Two hundred fifty three in vivo, wide-band diffuse reflectance spectra (350-1,830 nm range, 1 nm resolution) were acquired on 52 tissue spots, including nerve (n = 22), muscle (n = 12), and adipose tissue (n = 18). We extracted 36 features from these spectroscopic data: 18 gradients and 18 amplitude differences at predefined points in the tissue spectra. Best distinctive feature combinations were established using binary logistic regression. Classification performance was evaluated in a cross-validation (CV) approach by leave-one-out (LOO). To generalize nerve recognition applicability, we performed a train-test (TT) validation using the thyroid and parathyroid surgery data for training purposes and carpal tunnel release surgery data (10 nerve spots and 5 adipose spots) for classification purposes.

RESULTS

For combinations of two distinctive spectral features, LOO revealed an accuracy of respectively 78% for Si-sensors and 95% for InGaAs-sensors. TT revealed accuracies of respectively 67% and 100%.

CONCLUSIONS

Using diffuse reflectance spectroscopy we have identified that InGaAs sensors are better suited for automated discrimination between nerves and surrounding adipose tissue than Si sensors.

Concordant Symptomatic Intracranial Aneurysm in a Monozygotic Twin: A Case Report and Review of the Literature

The development of an intracranial aneurysm (IA) is a multifactorial process, involving genetic and environmental factors. The presence of IA or aneurysmal subarachnoid hemorrhage (aSAH) in twins is particularly interesting, since both genetic and environmental factors can be studied. It also raises the question of whether, when one twin is affected, the other asymptomatic twin should be examined for an IA. We report on a monozygotic (MZ) twin-pair with aSAH in both twins and we review all reported cases of IA in MZ twins. Including our case, we found only 14 MZ twin-pairs in which both twins harbored an IA, suggesting a heavy underreporting in the medical literature. In this small group, a high concordance was noted in the sites of IAs. In MZ twins, the preferred sites for IAs are the branching arteries, while aneurysms arising from fusion arteries are rare. These sites differ from the preferential sites seen in series of familial IAs and series of sporadic IAs. We therefore hypothesize that the twinning process might play a significant role in the development of IAs in MZ twins. To further explore and substantiate this, the large twin registries should be studied. Although IAs in MZ twins with a negative family history for IAs should not be regarded as familial IAs, screening of the asymptomatic twin should be seriously considered if one MZ twin presents with an aSAH or an IA, because of the high fatality rates reported in asymptomatic (and not screened) MZ twin-halves.

The influence of transcutaneous electrical neurostimulation (TENS) on human cerebral blood flow velocities

BACKGROUND

It has been shown that transcutaneous electrical neurostimulation (TENS) reduces sympathetic tone. Spinal cord stimulation (SCS) has proven qualities to improve coronary, peripheral, and cerebral blood circulation. Therefore, we postulate that TENS and SCS affect the autonomic nervous system in analogous ways. In this line of thought, cervical application of TENS might be a useful and simple adjunct in the treatment of cerebrovascular disease by improving cerebral blood flow. Experiments were performed in order to assess whether cervical TENS is safe and whether an effect on cerebral blood flow velocity (CBFV) can be shown in healthy subjects.

METHOD

A controlled, non-randomized, phase 1 study was performed with 20 healthy volunteers. Cervical TENS was applied in several frequencies, with and without hyperventilation. Continuous registration of blood pressure, pulse, CBFV (estimated by transcranial Doppler sonography) and end-tidal carbon dioxide concentration was performed.

FINDINGS

Cervical TENS was well-tolerated by all subjects. Despite small effects on heart rate (HR) and mean arterial blood pressure (MAP), a significant effect on middle cerebral artery (MCA) blood flow velocity was not demonstrated. No effect of age, gender, current or session order on MCA, HR, or MAP was found. TENS did not influence the effect of hyperventilation.

CONCLUSIONS

In these experiments, application of cervical TENS is proven to be a safe procedure. However, no effects on cerebral blood flow velocity could be detected, perhaps due to the intact cerebral autoregulation in the healthy volunteers.