Defining tumor growth in vestibular schwannomas:a volumetric inter-observer variability study in contrast-enhanced T1-weighted MRI

Introduction:For patients with vestibular schwannomas (VS), the need for reliable volumetric tumor monitoring is important. Currently, a volumetric cutoff of 20% increase in tumor volume is widely used to define tumor growth in VS. This study investigates the volumetric limits of agreement (LoA) of VS by an inter-observer study.Methods:This retrospective study included 100 VS patients who underwent contrast-enhanced T1-weighted MRI. Five observers volumetrically annotated the images. Observer agreement and reliability was measured using the LoA, estimated using the limits of agreement with the mean (LOAM) method, and the intraclass correlation coefficient (ICC). Influence of imaging parameters and tumor characteristics were assessed using univariable and multivariable linear regression analysis.Results:The 100 patients had an average median tumor volume of 903 mm3 (IQR: 193-3101). Peritumoral cysts were found in 6 patients. Patients were divided into four volumetric size categories based on tumor volume quartile. The smallest tumor volume quartile showed a LOAM relative to the mean of 26.8%, whereas for the largest tumor volume quartile this figure was found to be 7.3% and when excluding peritumoral cysts: 4.8%. Of all imagingparameters and tumor characteristics, only tumor volume was associated with the LoA (adjusted B=-0.001 [P=0.003]).Conclusion:Agreement limits within volumetric annotation of VS are affected by tumor volume, since the LoA improves with increasing tumor volume. As a result, for tumors larger than 200 mm3, growth can reliably be detected at an earlier stage, compared to the currently widely used cutoff of 20%.

Defining tumor growth in vestibular schwannomas:a volumetric inter-observer variability study in contrast-enhanced T1-weighted MRI

Objective: For patients with vestibular schwannomas (VS), a conservative observational approach is increasingly used. Therefore, the need for accurate and reliable volumetric tumor monitoring is important. Currently, a volumetric cutoff of 20% increase in tumor volume is widely used to define tumor growth in VS. The goal of this study is to investigate the tumor volume dependency on the limits of agreement (LoA) for volumetric measurements of VS by means of an inter-observer study. Methods: This retrospective study included 100 VS patients who underwent contrast-enhanced T1-weighted MRI. Five observers volumetrically annotated the images. Observer agreement and reliability was measured using the LoA, estimated using the limits of agreement with the mean (LOAM) method, and the intraclass correlation coefficient (ICC). Influence of imaging parameters and tumor characteristics were assessed using univariable and multivariable linear regression analysis. Results: The 100 patients had an average median tumor volume of 903 mm3 (IQR: 193-3101). Peritumoral cysts were found in 6 (6%) patients. Patients were divided into four volumetric size categories based on tumor volume quartile. The smallest tumor volume quartile showed a LOAM relative to the mean of 26.8% (95% CI: 23.7, 33.6), whereas for the largest tumor volume quartile this figure was found to be 7.3% (95% CI: 6.5, 9.7) and when excluding peritumoral cysts: 4.8% (95% CI: 4.2, 6.2). Of all imaging parameters and tumor characteristics, only tumor volume was associated with the LoA (adjusted B=-0.001 [95% CI: -0.001, 0.000; P=0.003]). Conclusions: Agreement limits within volumetric annotation of VS are affected by tumor volume, since the LoA improves with increasing tumor volume. As a result, for tumors larger than 200 mm3, growth can reliably be detected at an earlier stage, compared to the currently widely used cutoff of 20%. However, for very small tumors, growth should be assessed with higher agreement limits than previously thought

Autosomal dominant optic neuropathy and sensorineual hearing loss associated with a novel mutation of WFS1

PURPOSE: To describe the phenotype of a novel Wolframin (WFS1) mutation in a family with autosomal dominant optic neuropathy and deafness. The study is designed as a retrospective observational case series. METHODS: Seven members of a Dutch family underwent ophthalmological, otological, and genetical examinations in one institution. Fasting serum glucose was assessed in the affected family members. RESULTS: All affected individuals showed loss of neuroretinal rim of the optic nerve at fundoscopy with enlarged blind spots at perimetry. They showed a red-green color vision defect at color vision tests and deviations at visually evoked response tests. The audiograms of the affected individuals showed hearing loss and were relatively flat. The unaffected individuals showed no visual deviations or hearing impairment. The affected family members had no glucose intolerance. Leber hereditary optic neuropathy (LHON) mitochondrial mutations and mutations in the Optic atrophy-1 gene (OPA1) were excluded. In the affected individuals, a novel missense mutation c.2508G>C (p.Lys836Asn) in exon 8 of WFS1 was identified. CONCLUSIONS: This study describes the phenotype of a family with autosomal dominant optic neuropathy and hearing impairment associated with a novel missense mutation in WFS1

Defining tumor growth in vestibular schwannomas:a volumetric inter-observer variability study in contrast-enhanced T1-weighted MRI

Introduction:For patients with vestibular schwannomas (VS), the need for reliable volumetric tumor monitoring is important. Currently, a volumetric cutoff of 20% increase in tumor volume is widely used to define tumor growth in VS. This study investigates the volumetric limits of agreement (LoA) of VS by an inter-observer study.Methods:This retrospective study included 100 VS patients who underwent contrast-enhanced T1-weighted MRI. Five observers volumetrically annotated the images. Observer agreement and reliability was measured using the LoA, estimated using the limits of agreement with the mean (LOAM) method, and the intraclass correlation coefficient (ICC). Influence of imaging parameters and tumor characteristics were assessed using univariable and multivariable linear regression analysis.Results:The 100 patients had an average median tumor volume of 903 mm3 (IQR: 193-3101). Peritumoral cysts were found in 6 patients. Patients were divided into four volumetric size categories based on tumor volume quartile. The smallest tumor volume quartile showed a LOAM relative to the mean of 26.8%, whereas for the largest tumor volume quartile this figure was found to be 7.3% and when excluding peritumoral cysts: 4.8%. Of all imagingparameters and tumor characteristics, only tumor volume was associated with the LoA (adjusted B=-0.001 [P=0.003]).Conclusion:Agreement limits within volumetric annotation of VS are affected by tumor volume, since the LoA improves with increasing tumor volume. As a result, for tumors larger than 200 mm3, growth can reliably be detected at an earlier stage, compared to the currently widely used cutoff of 20%.

Wait-and-Scan management in sporadic Koos grade 4 vestibular schwannomas:A longitudinal volumetric study

BackgroundVolumetric natural history studies specifically on large vestibular schwannomas (VSs), commonly classified as Koos grade 4, are lacking. The aim of the current study is to present the volumetric tumor evolution in sporadic Koos grade 4 VSs and possible predictors for tumor growth.MethodsVolumetric tumor measurements and tumor evolution patterns from serial MRI studies were analyzed from selected consecutive patients with Koos grade 4 VS undergoing initial wait-and-scan management between January 2001 and July 2020. The significant volumetric threshold was defined as a change in volume of ≥10%.ResultsAmong 215 tumors with a median size (IQR) of 2.7cm3 (1.8-4.2), 147 tumors (68%) demonstrated growth and 75 tumors (35%) demonstrated shrinkage during follow-up. Growth-free survival rates (95% CI) at 1, 2, 5, and 10 years were 55% (48-61), 36% (29-42), 29% (23-36), and 28% (21-34), respectively and did not significantly differ in tumors >20 mm (Chi-square=.40; P-value=.53). Four tumor evolution patterns (% of total) were observed: continued growth (60); initial growth then shrinkage (7); continued shrinkage (27); and stability (5). Good hearing (adjusted HR 2.21, 95% CI 1.48-3.30; P<.001) and peritumoral edema (adjusted HR 2.22, 95% CI 1.18-4.13; P.01) at diagnosis were significantly associated with an increased likelihood of growth.ConclusionsKoos grade 4 VSs show a wide variety in size and growth. Due to variable growth patterns, an initial wait-and-scan strategy with short scan intervals may be an acceptable option in selected tumors, if no significant clinical symptoms of mass effect that warrant treatment are present

Computer-aided prediction of short-term tumor growth in sporadic vestibular schwannomas using both structural and dynamic-contrast enhanced MR imaging

Introduction:Recent studies have demonstrated that microvascular parameters derived from dynamic-contrast enhanced (DCE) MR imaging significantly correlate with tumor growth in vestibularschwannomas (VS). Other studies provide evidence that the use of artificial intelligence (AI)on structural MR data provides similar predictive value for tumor growth.Methods: This prospective study investigates the combination of structural and DCE imaging data for AI to predict short-term tumor growth in VS. A total of 110 newly diagnosed unilateral sporadic VS patients underwent both T2-weighted and DCE MR imaging. Established pipelines were used to estimate the values of DCE-derived parameters Ktrans, ve, and vp. Subsequently, tumors were delineated and only voxel values within the delineation were considered for the AI model development. Radiomic features were extracted from both the structural images and DCE-derived parameter maps. A classifier was trained on the radiomic features to predict tumor growth.Results: Growth was observed in 69 (63%) of the 110 patients during follow-up. A support vector machine (SVM) model was trained on Ktrans and ve radiomic features using five-fold-crossvalidation. This model resulted in an accuracy of 82.5%, sensitivity of 81.2%, specificity of 82.9%, and area-under-the-curve of 0.85. The predictive value of structural MR imaging features is currently under investigation, as well as the use of more complex AI models. It is hypothesized that the addition of structural features and increase in model complexity will improve the model's predictive power. Conclusion: Preliminary results have shown that DCE-derived parameter values exhibit a high predictive value for tumor growth prediction in sporadic VS. Other radiomic features and model types will be analyzed in order to investigate whether they improve the current AI model. These results will be presented during the conference.<br/

Computer-aided prediction of short-term tumor growth in sporadic vestibular schwannomas using both structural and dynamic-contrast enhanced MR imaging

Introduction:Recent studies have demonstrated that microvascular parameters derived from dynamic-contrast enhanced (DCE) MR imaging significantly correlate with tumor growth in vestibularschwannomas (VS). Other studies provide evidence that the use of artificial intelligence (AI)on structural MR data provides similar predictive value for tumor growth.Methods: This prospective study investigates the combination of structural and DCE imaging data for AI to predict short-term tumor growth in VS. A total of 110 newly diagnosed unilateral sporadic VS patients underwent both T2-weighted and DCE MR imaging. Established pipelines were used to estimate the values of DCE-derived parameters Ktrans, ve, and vp. Subsequently, tumors were delineated and only voxel values within the delineation were considered for the AI model development. Radiomic features were extracted from both the structural images and DCE-derived parameter maps. A classifier was trained on the radiomic features to predict tumor growth.Results: Growth was observed in 69 (63%) of the 110 patients during follow-up. A support vector machine (SVM) model was trained on Ktrans and ve radiomic features using five-fold-crossvalidation. This model resulted in an accuracy of 82.5%, sensitivity of 81.2%, specificity of 82.9%, and area-under-the-curve of 0.85. The predictive value of structural MR imaging features is currently under investigation, as well as the use of more complex AI models. It is hypothesized that the addition of structural features and increase in model complexity will improve the model's predictive power. Conclusion: Preliminary results have shown that DCE-derived parameter values exhibit a high predictive value for tumor growth prediction in sporadic VS. Other radiomic features and model types will be analyzed in order to investigate whether they improve the current AI model. These results will be presented during the conference.<br/

Radiomics-Based Prediction of Long-Term Treatment Response of Vestibular Schwannomas Following Stereotactic Radiosurgery

OBJECTIVE: Stereotactic radiosurgery (SRS) is one of the treatment modalities for vestibular schwannomas (VSs). However, tumor progression can still occur after treatment. Currently, it remains unknown how to predict long-term SRS treatment outcome. This study investigates possible magnetic resonance imaging (MRI)-based predictors of long-term tumor control following SRS. STUDY DESIGN: Retrospective cohort study. SETTING: Tertiary referral center. PATIENTS: Analysis was performed on a database containing 735 patients with unilateral VS, treated with SRS between June 2002 and December 2014. Using strict volumetric criteria for long-term tumor control and tumor progression, a total of 85 patients were included for tumor texture analysis. INTERVENTION(S): All patients underwent SRS and had at least 2 years of follow-up. MAIN OUTCOME MEASURE(S): Quantitative tumor texture features were extracted from conventional MRI scans. These features were supplied to a machine learning stage to train prediction models. Prediction accuracy, sensitivity, specificity, and area under the receiver operating curve (AUC) are evaluated. RESULTS: Gray-level co-occurrence matrices, which capture statistics from specific MRI tumor texture features, obtained the best prediction scores: 0.77 accuracy, 0.71 sensitivity, 0.83 specificity, and 0.93 AUC. These prediction scores further improved to 0.83, 0.83, 0.82, and 0.99, respectively, for tumors larger than 5 cm. CONCLUSIONS: Results of this study show the feasibility of predicting the long-term SRS treatment response of VS tumors on an individual basis, using MRI-based tumor texture features. These results can be exploited for further research into creating a clinical decision support system, facilitating physicians, and patients to select a personalized optimal treatment strategy

Heterozygous missense variants of LMX1A lead to nonsyndromic hearing impairment and vestibular dysfunction

Unraveling the causes and pathomechanisms of progressive disorders is essential for the development of therapeutic strategies. Here, we identified heterozygous pathogenic missense variants of LMX1A in two families of Dutch origin with progressive nonsyndromic hearing impairment (HI), using whole exome sequencing. One variant, c.721G > C (p.Val241Leu), occurred de novo and is predicted to affect the homeodomain of LMX1A, which is essential for DNA binding. The second variant, c.290G > C (p.Cys97Ser), predicted to affect a zinc-binding residue of the second LIM domain that is involved in protein–protein interactions. Bi-allelic deleterious variants of Lmx1a are associated with a complex phenotype in mice, including deafness and vestibular defects, due to arrest of inner ear development. Although Lmx1a mouse mutants demonstrate neurological, skeletal, pigmentation and reproductive system abnormalities, no syndromic features were present in the participating subjects of either family. LMX1A has previously been suggested as a candidate gene for intellectual disability, but our data do not support this, as affected subjects displayed normal cognition. Large variability was observed in the age of onset (a)symmetry, severity and progression rate of HI. About half of the affected individuals displayed vestibular dysfunction and experienced symptoms thereof. The late-onset progressive phenotype and the absence of cochleovestibular malformations on computed tomography scans indicate that heterozygous defects of LMX1A do not result in severe developmental abnormalities in humans. We propose that a single LMX1A wild-type copy is sufficient for normal development but insufficient for maintenance of cochleovestibular function. Alternatively, minor cochleovestibular developmental abnormalities could eventually lead to the progressive phenotype seen in the families

Lateralization of facial emotion processing and facial paresis in Vestibular Schwannoma patients

Objective: This study investigates whether there exist differences in lateralization of facial emotion processing in patients suffering from Vestibular Schwannoma (VS) based on the presence of a facial paresis and their degree of facial functioning as measured by the House Brackmann Grading scale (HBG). Methods: Forty-four VS patients, half of them with a facial paresis and half of them without a facial paresis, rated how emotive they considered images of faces showing emotion in the left versus right visual field. Stimuli consisted of faces with a neutral half and an emotional (happy or angry) half. The study had a mixed design with emotional expression (happy vs. angry) and emotional half (left vs. right visual field) of the faces as repeated measures, and facial paresis (present vs. absent) and HBG as between subjects’ factors. The visual field bias was the main dependent variable. Results: In line with typical findings in the normal population, a left visual field bias showed in the current sample: patients judged emotional expressions shown in the left visual field as more emotive than those shown in the right visual field. No differences in visual field bias showed based on the presence of a facial paresis nor based on patients’ HBG. Conclusion: VS patients show a left visual field bias when processing facial emotion. No differences in lateralization showed based on the presence of a facial paresis or on patients’ HBG. Based on this study, facial paresis thus does not affect the lateralization of facial emotion processing in patients with VS