Fractional tumor burden maps increase the confidence of reading brain MR perfusion.

RATIONALE AND OBJECTIVES: Various methods exist to perform and post-process perfusion weighted MR imaging in the post-treatment imaging of glioma patients to differentiate tumor progression from tumor-related abnormalities. One of these post-processing methods produces 'fractional tumor burden' maps. This multi-reader study investigated the clinical feasibility of fractional tumor burden maps on real world data from radiological follow-up of high-grade astrocytoma patients. METHODS: Five readers with background in radiology and varying levels of experience were tasked with assessing 30 astrocytoma and glioblastoma patients during one reader session. First, they were provided with a dataset of conventional MRI sequences, including perfusion MRI with regional cerebral blood volume maps. Then the dataset was expanded with a corresponding fractional tumor burden maps. Diagnostic accuracy, duration of post-processing, duration of the assessment of the fractional tumor burden maps, the diagnostic confidence reported by the readers and their diagnoses were recorded. Final diagnosis was determined by clinical and radiological follow-up and/or histopathological data used as gold standard. RESULTS: A mean sensitivity of 83.3 % and mean specificity of 55.1 % was obtained without the use of fractional tumor burden maps, whereas their additional of fractional tumor burden maps resulted in a mean sensitivity and specificity of 79.5 % and 54.2 %, respectively. Diagnostic accuracies with and without fractional tumor burden maps were not significantly different (Z = 0.76, p = 0.450). The median time spent post-processing was 313 s, while the median duration of the assessment of the FTB maps was 19 s. Interestingly, reader confidence increased significantly after adding the fractional tumor burden-maps to the assessment (Z = 454, p < 0.01). CONCLUSIONS: While the use of fractional tumor burden maps does not carry additional value in the radiological follow-up of post-operative high-grade astrocytoma and glioblastoma patients, it does give readers more confidence in their diagnosis.

Clinical applicability of signal heterogeneity and tumor border assessment on T2-weighted MR images to distinguish astrocytic from oligodendroglial origin of gliomas.

BACKGROUND AND PURPOSE: Radiological features on magnetic resonance imaging (MRI) were attributed to oligodendroglioma, although the diagnostic accuracy in a real-world clinical setting remains partially elusive. This study investigated the accuracy and robustness of tumor heterogeneity and tumor border delineation on T2-weighted MRI to distinguish oligodendroglioma from astrocytoma. MATERIALS AND METHODS: Eight readers from three different specialties (radiology, neurology, neurosurgery) with varying levels of experience blindly rated 79 T2-weighted MR images of patients with either oligodendroglioma or astrocytoma. After the first reading session, all readers were re-invited for a second reading session within three weeks. Diagnostic accuracy, including area under the receiver operator characteristics curve (AUC), and intra-observer variability and inter-observer variability were used as outcome measures. RESULTS: Pooled sensitivity and specificity to distinguish oligodendroglioma from astrocytoma for the use of tumor heterogeneity were 59.9 % respectively 74.5 %, and 85.7 % respectively 40.1 % for tumor border. A second reading session did not result in a significant change in sensitivity or specificity for tumor heterogeneity (P = 0.752 and P = 0.733, respectively) or tumor border (P = 0.309 and P = 0.271, respectively). An AUC of 0.825 was achieved with regard to predicting oligodendroglial origin of gliomas. Intra-observer agreement ranged from moderate to very good for tumor heterogeneity (kappa-value 0.43-0.87) and tumor border (0.40-0.84). A moderate inter-oberserver agreement was achieved for tumor heterogeneity and tumor border (kappa-value of 0.50 and 0.45, respectively). CONCLUSION: This study demonstrates that tumor heterogeneity and tumor borders on T2-weighted MRI could be used with moderate Finter-observer agreement to non-invasively distinguish oligodendroglioma from astrocytoma.

How to evaluate perfusion imaging in post-treatment glioma: a comparison of three different analysis methods.

INTRODUCTION: Dynamic susceptibility contrast (DSC) perfusion weighted (PW)-MRI can aid in differentiating treatment related abnormalities (TRA) from tumor progression (TP) in post-treatment glioma patients. Common methods, like the 'hot spot', or visual approach suffer from oversimplification and subjectivity. Using perfusion of the complete lesion potentially offers an objective and accurate alternative. This study aims to compare the diagnostic value and assess the subjectivity of these techniques. METHODS: 50 Glioma patients with enhancing lesions post-surgery and chemo-radiotherapy were retrospectively included. Outcome was determined by clinical/radiological follow-up or biopsy. Imaging analysis used the 'hot spot', volume of interest (VOI) and visual approach. Diagnostic accuracy was compared using receiving operator characteristics (ROC) curves for the VOI and 'hot spot' approach, visual assessment was analysed with contingency tables. Inter-operator agreement was determined with Cohens kappa and intra-class coefficient (ICC). RESULTS: 29 Patients suffered from TP, 21 had TRA. The visual assessment showed poor to substantial inter-operator agreement (κ = -0.72 - 0.68). Reliability of the 'hot spot' placement was excellent (ICC = 0.89), while reference placement was variable (ICC = 0.54). The area under the ROC (AUROC) of the mean- and maximum relative cerebral blood volume (rCBV) (VOI-analysis) were 0.82 and 0.72, while the rCBV-ratio ('hot spot' analysis) was 0.69. The VOI-analysis had a more balanced sensitivity and specificity compared to visual assessment. CONCLUSIONS: VOI analysis of DSC PW-MRI data holds greater diagnostic accuracy in single-moment differentiation of TP and TRA than 'hot spot' or visual analysis. This study underlines the subjectivity of visual placement and assessment.

Quantification of perineural satellitosis in pretreatment glioblastoma with structural MRI and a diffusion tensor imaging template.

Background: Survival outcomes for glioblastoma (GBM) patients remain unfavorable, and tumor recurrence is often observed. Understanding the radiological growth patterns of GBM could aid in improving outcomes. This study aimed to examine the relationship between contrast-enhancing tumor growth direction and white matter, using an image registration and deformation strategy. Methods: In GBM patients 2 pretreatment scans (diagnostic and neuronavigation) were gathered retrospectively, and coregistered to a template and diffusion tensor imaging (DTI) atlas. The GBM lesions were segmented and coregistered to the same space. Growth vectors were derived and divided into vector populations parallel (Φ = 0-20°) and perpendicular (Φ = 70-90°) to white matter. To test for statistical significance between parallel and perpendicular groups, a paired samples Student's t-test was performed. O6-methylguanine-DNA methyltransferase (MGMT) methylation status and its correlation to growth rate were also tested using a one-way ANOVA test. Results: For 78 GBM patients (mean age 61 years ±â€…13 SD, 32 men), the included GBM lesions showed a predominant preference for perineural satellitosis (P < .001), with a mean percentile growth of 30.8% (95% CI: 29.6-32.0%) parallel (0°â€…< |Φ| < 20°) to white matter. Perpendicular tumor growth with respect to white matter microstructure (70°â€…< |Φ| < 90°) showed to be 22.7% (95% CI: 21.3-24.1%) of total tumor growth direction. Conclusions: The presented strategy showed that tumor growth direction in pretreatment GBM patients correlated with white matter architecture. Future studies with patient-specific DTI data are required to verify the accuracy of this method prospectively to identify its usefulness as a clinical metric in pre and posttreatment settings.

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.

Head-To-Head Comparison of PET and Perfusion Weighted MRI Techniques to Distinguish Treatment Related Abnormalities from Tumor Progression in Glioma.

The post-treatment imaging surveillance of gliomas is challenged by distinguishing tumor progression (TP) from treatment-related abnormalities (TRA). Sophisticated imaging techniques, such as perfusion-weighted magnetic resonance imaging (MRI PWI) and positron-emission tomography (PET) with a variety of radiotracers, have been suggested as being more reliable than standard imaging for distinguishing TP from TRA. However, it remains unclear if any technique holds diagnostic superiority. This meta-analysis provides a head-to-head comparison of the diagnostic accuracy of the aforementioned imaging techniques. Systematic literature searches on the use of PWI and PET imaging techniques were carried out in PubMed, Embase, the Cochrane Library, ClinicalTrials.gov and the reference lists of relevant papers. After the extraction of data on imaging technique specifications and diagnostic accuracy, a meta-analysis was carried out. The quality of the included papers was assessed using the QUADAS-2 checklist. Nineteen articles, totaling 697 treated patients with glioma (431 males; mean age ± standard deviation 50.5 ± 5.1 years) were included. The investigated PWI techniques included dynamic susceptibility contrast (DSC), dynamic contrast enhancement (DCE) and arterial spin labeling (ASL). The PET-tracers studied concerned [S-methyl-11C]methionine, 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG), O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET) and 6-[18F]-fluoro-3,4-dihydroxy-L-phenylalanine ([18F]FDOPA). The meta-analysis of all data showed no diagnostic superior imaging technique. The included literature showed a low risk of bias. As no technique was found to be diagnostically superior, the local level of expertise is hypothesized to be the most important factor for diagnostically accurate results in post-treatment glioma patients regarding the distinction of TRA from TP.

Challenges and opportunities for advanced neuroimaging of glioblastoma.

Glioblastoma is the most aggressive of glial tumours in adults. On conventional magnetic resonance (MR) imaging, these tumours are observed as irregular enhancing lesions with areas of infiltrating tumour and cortical expansion. More advanced imaging techniques including diffusion-weighted MRI, perfusion-weighted MRI, MR spectroscopy and positron emission tomography (PET) imaging have found widespread application to diagnostic challenges in the setting of first diagnosis, treatment planning and follow-up. This review aims to educate readers with regard to the strengths and weaknesses of the clinical application of these imaging techniques. For example, this review shows that the (semi)quantitative analysis of the mentioned advanced imaging tools was found useful for assessing tumour aggressiveness and tumour extent, and aids in the differentiation of tumour progression from treatment-related effects. Although these techniques may aid in the diagnostic work-up and (post-)treatment phase of glioblastoma, so far no unequivocal imaging strategy is available. Furthermore, the use and further development of artificial intelligence (AI)-based tools could greatly enhance neuroradiological practice by automating labour-intensive tasks such as tumour measurements, and by providing additional diagnostic information such as prediction of tumour genotype. Nevertheless, due to the fact that advanced imaging and AI-diagnostics is not part of response assessment criteria, there is no harmonised guidance on their use, while at the same time the lack of standardisation severely hampers the definition of uniform guidelines.

Bifurcation occlusions and endovascular treatment outcome in acute ischemic stroke.

BACKGROUND: A thrombus in the M1 segment of the middle cerebral artery (MCA) can occlude this main stem only or extend into the M1-M2 bifurcation. The occlusion pattern may affect endovascular treatment (EVT) success, as a bifurcated thrombus may be more prone to fragmentation during retrieval. OBJECTIVE: To investigate whether bifurcated thrombus patterns are associated with EVT procedural and clinical outcomes. METHODS: Occlusion patterns of MCA thrombi on CT angiography from MR CLEAN Registry patients were classified into three groups: main stem occlusion, bifurcation occlusion extending into one M2 branch, and bifurcation occlusion extending into both M2 branches. Procedural parameters, procedural outcomes (reperfusion grade and embolization to new territory), and clinical outcomes (24-48 hour National Institutes of Health Stroke Scale [NIHSSFU] score, change in NIHSS scores between 24 and 48 hours and baseline ∆ [NIHSS], and 90-day modified Rankin Scale [mRS] scores) were compared between occlusion patterns. RESULTS: We identified 1023 patients with an MCA occlusion of whom 370 (36%) had a main stem occlusion, 151 (15%) a single branch, and 502 (49%) a double branch bifurcation occlusion. There were no statistically significant differences in retrieval method, procedure time, number of retrieval attempts, reperfusion grade, and embolization to new territory between occlusion patterns. Patients with main stem occlusions had lower NIHSSFU scores than patients with single (7 vs 11, p=0.01) or double branch occlusions (7 vs 9, p=0.04). However, there were no statistically significant differences in ∆ NIHSS or in 90-day mRS scores. CONCLUSIONS: In our population, EVT procedural and long-term clinical outcomes were similar for MCA bifurcation occlusions and MCA main stem occlusions.

Diffusion imaging could aid to differentiate between glioma progression and treatment-related abnormalities: a meta-analysis.

BACKGROUND: In a considerable subgroup of glioma patients treated with (chemo) radiation new lesions develop either representing tumor progression (TP) or treatment-related abnormalities (TRA). Quantitative diffusion imaging metrics such as the Apparent Diffusion Coefficient (ADC) and Fractional Anisotropy (FA) have been reported as potential metrics to noninvasively differentiate between these two phenomena. Variability in performance scores of these metrics and absence of a critical overview of the literature contribute to the lack of clinical implementation. This meta-analysis therefore critically reviewed the literature and meta-analyzed the performance scores. METHODS: Systematic searching was carried out in PubMed, EMBASE and The Cochrane Library. Using predefined criteria, papers were reviewed. Diagnostic accuracy values of suitable papers were meta-analyzed quantitatively. RESULTS: Of 1252 identified papers, 10 ADC papers, totaling 414 patients, and 4 FA papers, with 154 patients were eligible for meta-analysis. Mean ADC values of the patients in the TP/TRA groups were 1.13 × 10-3mm2/s (95% CI 0.912 × 10-3-1.32 × 10-3mm2/s) and 1.38 × 10-3mm2/s (95% CI 1.33 × 10-3-1.45 × 10-3mm2/s, respectively. Mean FA values of TP/TRA was 0.19 (95% CI 0.189-0.194) and 0.14 (95% CI 0.137-0.143) respectively. A significant mean difference between ADC and FA values in TP versus TRA was observed (p = 0.005). CONCLUSIONS: Quantitative ADC and FA values could be useful for distinguishing TP from TRA on a meta-level. Further studies using serial imaging of individual patients are warranted to determine the role of diffusion imaging in glioma patients.

Assessing radiation-induced carotid vasculopathy using ultrasound after unilateral irradiation: a cross-sectional study.

BACKGROUND: Increased head and neck cancer (HNC) survival requires attention to long-term treatment sequelae. Irradiated HNC survivors have a higher ischemic stroke risk. However, the pathophysiology of radiation-induced vasculopathy is unclear. Arterial stiffness could be a biomarker. This study examined alterations in intima-media thickness (IMT) and stiffness-related parameters, shear wave (SWV) and pulse wave velocity (PWV), in irradiated compared to control carotids in unilateral irradiated patients. METHODS: Twenty-six patients, median 40.5 years, 5-15 years after unilateral irradiation for head and neck neoplasms underwent a bilateral carotid ultrasound using an Aixplorer system with SL18-5 and SL10-2 probes. IMT, SWV, and PWV were assessed in the proximal, mid, and distal common (CCA) and internal carotid artery (ICA). Plaques were characterized with magnetic resonance imaging. Measurements were compared between irradiated and control sides, and radiation dose effects were explored. RESULTS: CCA-IMT was higher in irradiated than control carotids (0.54 [0.50-0.61] vs. 0.50 [0.44-0.54] mm, p = 0.001). For stiffness, only anterior mid-CCA and posterior ICA SWV were significantly higher in the irradiated side. A radiation dose-effect was only (weakly) apparent for PWV (R2: end-systolic = 0.067, begin-systolic = 0.155). Ultrasound measurements had good-excellent intra- and interobserver reproducibility. Plaques had similar characteristics but were more diffuse in the irradiated side. CONCLUSIONS: Increased CCA-IMT and SWV in some segments were seen in irradiated carotids. These alterations, even in young patients, mark the need for surveillance of radiation-induced vasculopathy. TRIAL REGISTRATION: clinicaltrials.gov ( https://clinicaltrials.gov/ct2/show/NCT04257968 ).

A systematic review and meta-analysis on the differentiation of glioma grade and mutational status by use of perfusion-based magnetic resonance imaging.

BACKGROUND: Molecular characterization plays a crucial role in glioma classification which impacts treatment strategy and patient outcome. Dynamic susceptibility contrast (DSC) and dynamic contrast enhanced (DCE) perfusion imaging have been suggested as methods to help characterize glioma in a non-invasive fashion. This study set out to review and meta-analyze the evidence on the accuracy of DSC and/or DCE perfusion MRI in predicting IDH genotype and 1p/19q integrity status. METHODS: After systematic literature search on Medline, EMBASE, Web of Science and the Cochrane Library, a qualitative meta-synthesis and quantitative meta-analysis were conducted. Meta-analysis was carried out on aggregated AUC data for different perfusion metrics. RESULTS: Of 680 papers, twelve were included for the qualitative meta-synthesis, totaling 1384 patients. It was observed that CBV, ktrans, Ve and Vp values were, in general, significantly higher in IDH wildtype compared to IDH mutated glioma. Meta-analysis comprising of five papers (totaling 316 patients) showed that the AUC of CBV, ktrans, Ve and Vp were 0.85 (95%-CI 0.75-0.93), 0.81 (95%-CI 0.74-0.89), 0.84 (95%-CI 0.71-0.97) and 0.76 (95%-CI 0.61-0.90), respectively. No conclusive data on the prediction of 1p/19q integrity was available from these studies. CONCLUSIONS: Future research should aim to predict 1p/19q integrity based on perfusion MRI data. Additionally, correlations with other clinically relevant outcomes should be further investigated, including patient stratification for treatment and overall survival.

Reliability of dynamic susceptibility contrast perfusion metrics in pre- and post-treatment glioma.

BACKGROUND: In neuro-oncology, dynamic susceptibility contrast magnetic resonance (DSC-MR) perfusion imaging emerged as a tool to aid in the diagnostic work-up and to surveil effectiveness of treatment. However, it is believed that a significant variability exists with regard to the measured in DSC-MR perfusion parameters. The aim of this study was to assess the observer variability in measured DSC-MR perfusion parameters in patients before and after treatment. In addition, we investigated whether region-of-interest (ROI) shape impacted the observer variability. MATERIALS AND METHODS: Twenty non-treated patients and a matched group of twenty patients post-treatment (neurosurgical resection and post-chemoradiotherapy) were included. Six ROIs were independently placed by three readers: circular ROIs and polygonal ROIs covering 1) the tumor hotspot; 2) the peritumoral region (T2/FLAIR-hyperintense region) and 3) the whole tumor region. A two-way random Intra-class coefficient (ICC) model was used to assess variability in measured DSC-MRI perfusion parameters. The perfusion metrics as assessed by the circular and the polygonal ROI were compared by use of the dependent T-test. RESULTS: In the non-treated group, circular ROIs showed good-excellent overlap (ICC-values ranging from 0.741-0.963) with the exception of those representing the tumor hotspot. Polygonal ROIs showed lower ICC-values, ranging from 0.113 till 0.856. ROI-placement in the posttreatment group showed to be highly variable with a significant deterioration of ICC-values. Furthermore, perfusion metric assessment in similar tumor regions was not impacted by ROI shape. DISCUSSION: This study shows that posttreatment quantitative interpretation of DSC-MR perfusion imaging is highly variable and should be carried out with precaution. Pretreatment assessment of DSC-MR images, however, could be carried out be a single reader in order to provide valid data for further analyses.

Long-term cognitive, psychosocial, and neurovascular complications of unilateral head and neck irradiation in young to middle-aged adults.

BACKGROUND: With a growing, younger population of head and neck cancer survivors, attention to long-term side-effects of prior, often radiotherapeutic, treatment is warranted. Therefore, we studied the long-term cognitive effects in young adult patients irradiated for head and neck neoplasms (HNN). METHODS: Young to middle-aged adults with HNN (aged 18-40 years) and treated with unilateral neck irradiation ≥ 5 years before inclusion underwent cardiovascular risk and neuropsychological assessments and answered validated questionnaires regarding subjective cognitive complaints, fatigue, depression, quality of life, and cancer-specific distress. Additionally, magnetic resonance imaging (MRI) of the brain was performed to assess white matter hyperintensities (WMH), infarctions, and atrophy. RESULTS: Twenty-nine patients (aged 24-61, 13 men) median 9.2 [7.3-12.9] years post-treatment were included. HNN patients performed worse in episodic memory (Z-score = -1.16 [-1.58-0.34], p < 0.001) and reported more fatigue symptoms (Z-score = 1.75 [1.21-2.00], p < 0.001) compared to normative data. Furthermore, patients had a high level of fear of tumor recurrence (13 patients [44.8%]) and a heightened speech handicap index (13 patients [44.8%]). Only a small number of neurovascular lesions were found (3 infarctions in 2 patients and 0.11 [0.00-0.40] mL WMH), unrelated to the irradiated side. Cognitive impairment was not associated with WMH, brain atrophy, fatigue, or subjective speech problems. CONCLUSIONS: HNN patients showed impairments in episodic memory and an increased level of fatigue ≥ 5 years after radiotherapy compared to normative data. Cognitive impairments could not be explained by WMH or brain atrophy on brain MRI or psychological factors. TRIAL REGISTRATION: Clinicaltrials.gov ( https://clinicaltrials.gov/ct2/show/NCT04257968 ).

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

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.

Performance of machine learning algorithms for glioma segmentation of brain MRI: a systematic literature review and meta-analysis.

OBJECTIVES: Different machine learning algorithms (MLAs) for automated segmentation of gliomas have been reported in the literature. Automated segmentation of different tumor characteristics can be of added value for the diagnostic work-up and treatment planning. The purpose of this study was to provide an overview and meta-analysis of different MLA methods. METHODS: A systematic literature review and meta-analysis was performed on the eligible studies describing the segmentation of gliomas. Meta-analysis of the performance was conducted on the reported dice similarity coefficient (DSC) score of both the aggregated results as two subgroups (i.e., high-grade and low-grade gliomas). This study was registered in PROSPERO prior to initiation (CRD42020191033). RESULTS: After the literature search (n = 734), 42 studies were included in the systematic literature review. Ten studies were eligible for inclusion in the meta-analysis. Overall, the MLAs from the included studies showed an overall DSC score of 0.84 (95% CI: 0.82-0.86). In addition, a DSC score of 0.83 (95% CI: 0.80-0.87) and 0.82 (95% CI: 0.78-0.87) was observed for the automated glioma segmentation of the high-grade and low-grade gliomas, respectively. However, heterogeneity was considerably high between included studies, and publication bias was observed. CONCLUSION: MLAs facilitating automated segmentation of gliomas show good accuracy, which is promising for future implementation in neuroradiology. However, before actual implementation, a few hurdles are yet to be overcome. It is crucial that quality guidelines are followed when reporting on MLAs, which includes validation on an external test set. KEY POINTS: • MLAs from the included studies showed an overall DSC score of 0.84 (95% CI: 0.82-0.86), indicating a good performance. • MLA performance was comparable when comparing the segmentation results of the high-grade gliomas and the low-grade gliomas. • For future studies using MLAs, it is crucial that quality guidelines are followed when reporting on MLAs, which includes validation on an external test set.

Prognostic and Predictive Value of Integrated Qualitative and Quantitative Magnetic Resonance Imaging Analysis in Glioblastoma.

Glioblastoma (GBM) is the most malignant primary brain tumor for which no curative treatment options exist. Non-invasive qualitative (Visually Accessible Rembrandt Images (VASARI)) and quantitative (radiomics) imaging features to predict prognosis and clinically relevant markers for GBM patients are needed to guide clinicians. A retrospective analysis of GBM patients in two neuro-oncology centers was conducted. The multimodal Cox-regression model to predict overall survival (OS) was developed using clinical features with VASARI and radiomics features in isocitrate dehydrogenase (IDH)-wild type GBM. Predictive models for IDH-mutation, 06-methylguanine-DNA-methyltransferase (MGMT)-methylation and epidermal growth factor receptor (EGFR) amplification using imaging features were developed using machine learning. The performance of the prognostic model improved upon addition of clinical, VASARI and radiomics features, for which the combined model performed best. This could be reproduced after external validation (C-index 0.711 95% CI 0.64-0.78) and used to stratify Kaplan-Meijer curves in two survival groups (p-value < 0.001). The predictive models performed significantly in the external validation for EGFR amplification (area-under-the-curve (AUC) 0.707, 95% CI 0.582-8.25) and MGMT-methylation (AUC 0.667, 95% CI 0.522-0.82) but not for IDH-mutation (AUC 0.695, 95% CI 0.436-0.927). The integrated clinical and imaging prognostic model was shown to be robust and of potential clinical relevance. The prediction of molecular markers showed promising results in the training set but could not be validated after external validation in a clinically relevant manner. Overall, these results show the potential of combining clinical features with imaging features for prognostic and predictive models in GBM, but further optimization and larger prospective studies are warranted.

Clinical Presentation, Management, and Outcomes of Idiopathic Pain in Percutaneous Bone-anchored Hearing Implants.

OBJECTIVE: To identify clinical features and investigate treatment outcomes of patients with idiopathic pain related to a percutaneous bone-anchored hearing implant (BAHI) and to propose management recommendations. STUDY DESIGN: Retrospective chart analysis. SETTING: Tertiary referral center. PATIENTS: The clinical data of 14 patients who were treated for idiopathic pain around their percutaneous BAHI between May 2007 and February 2018 at our tertiary referral center were reviewed. MAIN OUTCOME MEASURES: Pain after treatment and implant loss. RESULTS: All 14 patients received treatment with oral antibiotics. Nine patients received oral antibiotic combination therapy for 4 weeks, whereafter pain resolved in 4. Out of the five other patients, receiving either antibiotic monotherapy or shortened antibiotic combination therapy, pain resolved in two. In case of persistent pain (57.1%) after initial treatment, other pain management therapies were attempted, however all with only limited effect. Six patients (42.8%) underwent elective removal of the implant. In two patients spontaneous implant loss occurred. In two of the four patients who underwent reimplantation, pain relapsed. In one of these, pain resolved after the removal of the new implant. In the other patient, pain persisted, despite abutment removal. With exception of this latter patient, all other 13 patients were pain free at the latest follow-up. Cone beam computed tomography did not offer additional information regarding diagnosis or treatment. CONCLUSION: Idiopathic pain in BAHI is a rare but bothersome symptom which can result in implant removal. After oral antibiotic combination treatment, symptoms resolved in approximately 40% of patients. Therefore, we think conservative treatment with these antibiotics before implant removal surgery, is worth considering.

[Consider the diagnosis 'Bell's palsy' carefully]. / Overweeg de diagnose 'Bellse parese' zorgvuldig.

Patients with facial palsy present with both cosmetic and functional symptoms. When a facial palsy develops quickly (within 72 hours) with no other symptoms, and no cause can be identified, it is probably an idiopathic facial palsy or 'Bell's palsy'. The diagnosis Bell's palsy is, thus, to a certain extent a diagnosis 'per exclusionem'. We present three cases with an incorrectly diagnosed Bell's palsy or inadequate diagnostics or treatment: a 5-year-old male with recurrent facial palsy caused by acute otitis media; a 46-year-old male with facial palsy caused by a malignant parotid tumour; and a 75-year-old female with facial palsy caused by a facial nerve schwannoma in the mastoid segment of the facial nerve. We, therefore, emphasize the importance of thorough history-taking and adequate diagnostics and imaging when patients present with facial palsy.

Presence of inflammatory proteins S100A8 and S100A9 in a giant intracranial aneurysm after flow diverter treatment.

We demonstrate the presence of S100A8 and S100A9 proteins in the wall and thrombosed lumen of an enlarged intracranial aneurysm after flow diverter treatment. These proteins have shown to play an important role in vascular inflammation and may serve as a biomarker and potential therapeutic target for intracranial aneurysms.

The interobserver agreement in the detection of recurrent HNSCC using MRI including diffusion weighted MRI.

INTRODUCTION: For the detection of local recurrences of head and neck squamous cell carcinomas (HNSCC) after (chemo)radiation, diagnostic imaging is generally performed. Diffusion weighted magnetic resonance imaging (DW-MRI) has been proven to be able to adequately diagnose the presence of cancer. However evaluation of DW-MR images for recurrences is difficult and could be subject to individual interpretation. AIM: To determine the interobserver agreement, intraobserver agreement and influence of experience of radiologists in the assessment of DW-MRI in patients clinically suspected of local recurrent HNSCC after (chemo)radiation. METHODS: Ten experienced head and neck radiologists assessed follow-up MRI including DW-MRI series of 10 patients for the existence of local recurrence on a two point decision scale (local recurrence or local control). Patients were clinically suspected for a recurrence of laryngeal (n = 3), hypopharyngeal (n = 3) or oropharyngeal (n = 4) cancer after (chemo)radiation with curative intent. Fleiss' and Cohen's Kappa were used to determine interobserver agreement and intraobserver agreement, respectively. RESULTS: Interobserver agreement was κ = 0.55. Intraobserver agreement was κ = 0.80. Prior experience within the field of radiology and with DW-MRI had no significant influence on the scoring. CONCLUSION: For the assessment of HNSCC recurrence after (chemo)radiation by DW-MRI, moderate interobserver agreement and substantial intraobserver agreement was found.