Transoperative Magnetic Resonance Imaging in Awake Glioma Surgery: Experience in a Latin American Tertiary-Level Center.

OBJECTIVE: Analyze the usefulness, efficacy, and safety of transoperative magnetic resonance imaging (tMRI) in glioma surgery in awake patients. METHODS: Retrospective, single-center, analytical study of a cohort of patients who underwent awake surgery for gliomas by the same surgeon in a third-level Argentine center, in the period between 2012 and 2022. Only patients with pathology-confirmed gliomas, with 6-month follow-up, who had preoperative and postoperative volumetric magnetic resonance imaging, were included in this sample. Subsequently, we analyzed which patients received surgery with the tMRI protocol and the results using multivariate regression analysis. RESULTS: A total of 71 patients were included. A tMRI study was performed on 22 (31%) of these patients. The use of tMRI increased the percentage of resection by 20% (P = 0.03), thereby increasing the possibility of gross total resection. However, using tMRI significantly extended surgical time by 84 minutes (P < 0.001). In 55% of the patients in whom tMRI was performed, the resection was continued after it. The use of tMRI did not increase the rate of infections or the development of surgically associated neurological deficits in the long term, despite the fact that 47% of the patients showed the development of a new deficit or worsening of a previous one during the intraoperative period. CONCLUSIONS: The use of tMRI in awake glioma surgery proved to be a safe tool that contributes to increasing the degree of tumor resection, compared to the use of neurophysiological mapping and neuronavigation, at the expense of increased surgical times and costs. We consider tMRI in awake glioma surgery should be used in properly selected cases.

Assessing robustness and generalization of a deep neural network for brain MS lesion segmentation on real-world data.

OBJECTIVES: Evaluate the performance of a deep learning (DL)-based model for multiple sclerosis (MS) lesion segmentation and compare it to other DL and non-DL algorithms. METHODS: This ambispective, multicenter study assessed the performance of a DL-based model for MS lesion segmentation and compared it to alternative DL- and non-DL-based methods. Models were tested on internal (n = 20) and external (n = 18) datasets from Latin America, and on an external dataset from Europe (n = 49). We also examined robustness by rescanning six patients (n = 6) from our MS clinical cohort. Moreover, we studied inter-human annotator agreement and discussed our findings in light of these results. Performance and robustness were assessed using intraclass correlation coefficient (ICC), Dice coefficient (DC), and coefficient of variation (CV). RESULTS: Inter-human ICC ranged from 0.89 to 0.95, while spatial agreement among annotators showed a median DC of 0.63. Using expert manual segmentations as ground truth, our DL model achieved a median DC of 0.73 on the internal, 0.66 on the external, and 0.70 on the challenge datasets. The performance of our DL model exceeded that of the alternative algorithms on all datasets. In the robustness experiment, our DL model also achieved higher DC (ranging from 0.82 to 0.90) and lower CV (ranging from 0.7 to 7.9%) when compared to the alternative methods. CONCLUSION: Our DL-based model outperformed alternative methods for brain MS lesion segmentation. The model also proved to generalize well on unseen data and has a robust performance and low processing times both on real-world and challenge-based data. CLINICAL RELEVANCE STATEMENT: Our DL-based model demonstrated superior performance in accurately segmenting brain MS lesions compared to alternative methods, indicating its potential for clinical application with improved accuracy, robustness, and efficiency. KEY POINTS: • Automated lesion load quantification in MS patients is valuable; however, more accurate methods are still necessary. • A novel deep learning model outperformed alternative MS lesion segmentation methods on multisite datasets. • Deep learning models are particularly suitable for MS lesion segmentation in clinical scenarios.

The central vein sign is present in most infratentorial multiple sclerosis plaques.

BACKGROUND AND PURPOSE: There is growing evidence supporting the presence of the central vein sign (CVS) in the supratentorial brain as an imaging biomarker for multiple sclerosis (MS) diagnosis. Recently, using optimized susceptibility-weighted angiography (SWAN-venule), we detected CVS in 86% of supratentorial white matter lesions (WMLs) in the clinical setting on images obtained in a 3T MRI scanner. Despite the relevance of the infratentorial compartment, CVS prevalence in infratentorial MS plaques has not been investigated in detail. Our objective was to determine the proportion of MS infratentorial lesions showing CVS positivity. MATERIALS AND METHODS: We included subjects with MS and other brain diseases showing at least one infratentorial lesion larger than 3 mm on 3D-FLAIR. Patients were scanned in a 3T MRI scanner (GE Medical Systems, discovery-MR750), applying a comprehensive protocol including post-contrast 3D-FLAIR and SWAN-venule sequences. CVS presence was confirmed by two trained raters. RESULTS: Thirty MRIs of subjects with MS were analyzed. One hundred and one infratentorial lesions were detected on FLAIR, and 86% were centered by a vein. Fifteen MRIs from the non-MS group were analyzed, 19 lesions were visible ion FLAIR and 16% were positive for the CVS. CONCLUSIONS: SWAN-venule detects infratentorial lesions and highlights the central vein in MS plaques at 3T MRI. As occurs in the supratentorial brain, most infratentorial lesions are perivenular.

Biomarcadores radiológicos en RM para una aproximación al diagnóstico molecular en gliomas IDH-mutados (grado II y III) / MR Imaging Biomarkers for a Diagnostic Approach of IDH-mutated Gliomas (Grades II/III)

Resumen Objetivo: Analizar características por resonancia magnética (RM) de gliomas IDH-mutados (grado II y III) en base a parámetros cualitativos, a fin de valorar el rendimiento del signo del mismatch T2-FLAIR y otras características morfológicas de los tumores, en predecir el estado del 1p/19q y su reproducibilidad interobservador. Métodos Estudio retrospectivo, descriptivo y analítico sobre una cohorte de 53 gliomas IDH-mutados (grado II y III) y molecularmente definidos respecto al 1p/19q, seleccionados a partir de la base de datos de la institución, durante el periodo 2014- 2019. Dos neuroradiólogos evaluaron características imagenológicas de forma independiente y enmascarada al diagnóstico: mismatch T2-FLAIR, localización tumoral, bordes, señal, infiltración cortical e inhomogeneidad en T2. Los casos discordantes fueron evaluados por un tercer neuroradiólogo de mayor experiencia. Resultados: Treinta de 53 (56,6%) gliomas fueron no codelecionados, y 23/53 (43,4%) codelecionados. El signo del mismatch T2-FLAIR fue positivo en 16/53 (30,18%) pacientes, 15/16 (93,75%) no codelecionados y 1/16 (6,25%) codelecionado (Exacto de Fisher p = <,0001). Los dos evaluadores demostraron una concordancia interobservador casi perfecta para ese signo, κ =,907 (95% CI, 0,781 a 1,0). La especificidad y el valor predictivo positivo del signo para predecir la ausencia de la codeleción fue de un 95,7% y un 93,8% respectivamente. Discusión: La reciente actualización en la clasificación de los gliomas los clasifica acorde a su perfil molecular. En los últimos años, varios investigadores han estudiado características morfológicas por RM de los tumores con la intención de predecir las características moleculares de los mismos. Conclusión: En nuestra población, el signo del mismatch T2-FLAIR es el único biomarcador radiológico que muestra asociación estadísticamente significativa en predecir la ausencia de codeleción en los gliomas IDH-mutados (grado II y III), con una alta especificidad y un alto valor predictivo positivo.

Abstract Objective: To analyze magnetic resonance (MR) characteristics of IDH-mutated gliomas (grades II/III) utilizing qualitative parameters with the goal of assessing the performance of the T2-FLAIR mismatch sign and other morphological characteristics of tumors in predicting the 1p/19q co-deletion status as well as inter-observer reproducibility. Methods: Retrospective and descriptive study analyzing a cohort of 53 IDH-mutated lower-grade (grades II/III) gliomas with known 1p/19q co-deletion status. Patients meeting selection criteria for this study were taken from our institutional data from 2014-2019. Two neuroradiologists assessed the following imaging characteristics independently, and blinded from the diagnosis: T2-FLAIR mismatch, tumor location, borders, signal characteristics, cortical infiltration and T2* inhomogeneity. In the event of discordant interpretations, a third senior neuroradiologist also evaluated the case. Results: 23 of the 53 (43.4%) gliomas demonstrated 1p/19q co-deletion and 30 of 53 (56.6%) did not. T2-FLAIR mismatch was positive in 16 of 53 cases (30.2%) with 15 of 16 (93.8%) demonstrating no co-deletion and 1/16 (6.25%) with co-deletion (Fisher's exact p = < .0001). The two readers showed an almost perfect interreader agreement for this sign κ = 0.907 (95% CI, 0.781 to 1.0). Specificity and positive predictive value of the sign to predict the absence of co-deletion was 95.7% and 93.8% respectively. Discussion: The recent update in classification of lower-grade gliomas segregates gliomas according to molecular profile. In the recent past, many researchers have studied MR morphologic characteristics of these tumors with the intention of predicting molecular features of said tumors Conclusion: In our patient population, T2-FLAIR mismatch sign is the only radiologic biomarker that shows statistically significant association with the absence of 1p/19q co-deletion in lower-grade gliomas, with high specificity and positive predictive value.

Brain volumes quantification from MRI in healthy controls: Assessing correlation, agreement and robustness of a convolutional neural network-based software against FreeSurfer, CAT12 and FSL.

BACKGROUND AND PURPOSE: There are instances in which an estimate of the brain volume should be obtained from MRI in clinical practice. Our objective is to calculate cross-sectional robustness of a convolutional neural network (CNN) based software (Entelai Pic) for brain volume estimation and compare it to traditional software such as FreeSurfer, CAT12 and FSL in healthy controls (HC). MATERIALS AND METHODS: Sixteen HC were scanned four times, two different days on two different MRI scanners (1.5 T and 3 T). Volumetric T1-weighted images were acquired and post-processed with FreeSurfer v6.0.0, Entelai Pic v2, CAT12 v12.5 and FSL v5.0.9. Whole-brain, grey matter (GM), white matter (WM) and cerebrospinal fluid (CSF) volumes were calculated. Correlation and agreement between methods was assessed using intraclass correlation coefficient (ICC) and Bland Altman plots. Robustness was assessed using the coefficient of variation (CV). RESULTS: Whole-brain volume estimation had better correlation between FreeSurfer and Entelai Pic (ICC (95% CI) 0.96 (0.94-0.97)) than FreeSurfer and CAT12 (0.92 (0.88-0.96)) and FSL (0.87 (0.79-0.91)). WM, GM and CSF showed a similar trend. Compared to FreeSurfer, Entelai Pic provided similarly robust segmentations of brain volumes both on same-scanner (mean CV 1.07, range 0.20-3.13% vs. mean CV 1.05, range 0.21-3.20%, p = 0.86) and on different-scanner variables (mean CV 3.84, range 2.49-5.91% vs. mean CV 3.84, range 2.62-5.13%, p = 0.96). Mean post-processing times were 480, 5, 40 and 5 min for FreeSurfer, Entelai Pic, CAT12 and FSL respectively. CONCLUSION: Based on robustness and processing times, our CNN-based model is suitable for cross-sectional volumetry on clinical practice.

White cord syndrome in a pediatric patient: A case report and review.

White cord syndrome is a rare condition involving sudden neurological deterioration following a decompressive cervical spinal surgery and characterized by the appearance of hyperintensity on T2-weighted magnetic resonance imaging. We present a report of a pediatric male patient who presented with the condition. This case shows that white cord syndrome can also be present in pediatric patients. We provide a brief review of the literature highlighting the main radiologic findings.

Multinodular and Vacuolating Neuronal Tumor of the Cerebrum (MVNT): A case series and review of the literature.

BACKGROUND AND PURPOSE: Multinodular and Vacuolating Neuronal Tumor of the cerebrum (MVNT) is a benign -seizure associated- lesion affecting mostly adults. This new entity has been included in the 2016 World Health Organization classification of tumors of the central nervous system. Its pathologic hallmark consist of a subcortical cluster of nodular lesions located on the subcortical white matter. We aim to report a series of cases of presumed MVNT observed in our institution and review the literature. MATERIALS AND METHODS: In this retrospective study, a search was performed on our hospital information system. Sixteen cases were included. Demographic, clinical and radiological features were detailed in a table. All patients had an MRI acquired either on a 1.5 or a 3 Tesla scanner. Sequences performed included T1, T2, GRE/SWI, T2 FLAIR and DWI. Gadolinium enhanced T1-WI wer available in 11 patients and follow-up MRI were available in 7 patients. RESULTS: Patient ages ranged from 16 to 77 years (mean 42 years). Seizure and non-focal headache were by far the most common neurological complaints for which MRI was requested. All lesions consisted of clusters of multiple, discrete, round or ovoid, intra-axial, FLAIR and T2-WI hyperintense nodules. Follow-up MRI scans showed no changes between studies. CONCLUSIONS: MVNT is a benign, stable lesion that exhibits a typical radiological pattern that most of the times sufficed to arrive to a diagnosis, without the need of pathological confirmation. We confirm that our demographic, clinical and radiological findings are in accordance with those published in international literature.

Volumetría hipocampal: análisis comparativo de los métodos de evaluación en enfermedad de Alzheimer / Hippocampal Volumetry: Comparative Analysis of Evaluation Methods in Alzheimer's Disease

Objetivo La atrofia hipocampal es uno de los biomarcadores radiológicos más sensibles de la enfermedad de Alzheimer (EA) y existen diferentes métodos para evaluarla: análisis subjetivo visual (ASV), análisis objetivo manual (AOM) y análisis objetivo automático (AOA). Nos proponemos comparar esos métodos, y evaluar si el AOA presenta una confiabilidad cercana al AOM (método de referencia) y superior al ASV. Materiales y Métodos Se seleccionaron retrospectivamente imágenes de resonancia magnética (RM) fast spoiled gradient-echo (FSPGR) de 28 sujetos (14 con deterioro cognitivo leve, 7 con EAy 7 controles). El ASV fue realizado por 10 radiólogos, clasificando la atrofia hipocampal en: nula, leve, moderada o severa. El AOM se basó en la segmentación manual de los hipocampos por dos operadores. El AOA fue realizada por medio del software FreeSurfer 5.3. Se calcularon coeficientes de correlación rho de Spearman para las variables discretas y coeficientes de correlación intraclase para las variables continuas. Resultados Los coeficientes de correlación entre los dos operadores que realizaron el AOM fueron de 0,88 (p < 0,0001) para los hipocampos izquierdos y de 0,86 (p < 0,0001) para los hipocampos derechos. El coeficiente de correlación entre todos los ASV (promediados) y AOM fue de-0,81 (IC 95%-0,96- -0,66). Los coeficientes de correlación entre el AOA y el AOM fue de 0,54 (p < 0,0001) para los hipocampos izquierdos y de 0,61 (p < 0,0001) para los hipocampos derechos. Conclusión Si bien el AOA tiene moderada correlación con el método de referencia, no es superior al ASV promedio y se deberían tomar recaudos antes de ser implementado en la práctica asistencial.

Objective Hippocampal atrophy is one of the most sensible radiological biomarkers of Alzheimer's disease. There are different methods to evaluate atrophy: visual subjective analysis (VSA), manual objective analysis (MOA) and automatic objective analysis (AOA). We will compare these methods and evaluate if AOA has a confidence similar to MOA (gold standard), and better than VSA. Materials and Methods We retrospectively selected 3D FSPGR MRI from 28 subjects of whom 14 had mild cognitive impairment, 7 Alzheimer's disease and 7 controls. VSA was performed by 10 radiologists who classified hippocampal atrophy in none, mild, moderate and severe. ForMOA, two operatorsmanually segmented both hippocampus from all subjects. AOA was performed by FreeSurfer 5.3. Spearman's rho correlation coefficient was calculated for discrete variables and intraclass correlation coefficient was calculated for continuous variables. Results Correlation coefficients between the operators that performed MOA was 0.88 (p < 0.0001) for left hippocampi and 0.86 (p < 0,0001) for right hippocampi. Correlation coefficients between mean VSA and MOA was-0,81 (95% CI-0,96- -0,66). Correlation coefficients between AOA and AOM was 0.54 (p < 0.0001) for left hippocampi and 0.61 (p < 0.0001) for right hippocampi. Conclusion Even though AOA has moderate correlation with the gold standard it is not superior to average VSA and should be implemented with care in clinical practice.

MIP Improves Detection of Brain Metastases.

PURPOSE: This study aimed to compare the sensitivity for detection of brain metastases using postcontrast 3-dimensional, T1W-gradient echo sequence (3DT1W) and maximum intensity projections (MIPs) obtained from the same data set. MATERIALS AND METHODS: A prospective analysis of patients with known brain metastases was performed. We compared 1-mm postcontrast 3DT1W with 6-mm MIP reconstructions obtained from the same images (MIP-3DT1) in 95 patients using 1.5 (42 patients) and 3 T (53 patient). Two independent readers analyzed all studies and the examinations were presented in anonymized and random fashion for a total of 190 interpretations per observer. One reader had more than 20 years of experience and the second reader had 1 year of experience. RESULTS: The least experienced observer found 542 brain metastases on postcontrast non-MIP 3DT1W and 605 with the MIP-3DT1 technique. For this observer, use of MIP resulted in increased number of detected metastases in 36% of patients regardless of field strength. The more experienced observer found 589 brain metastases on non-MIP 3DT1W and 621 with the MIP-3DT1 technique and the use of the latter also resulted in increased detection of metastases in 33% of patients regardless of field strength. CONCLUSIONS: In our study, we found that using MIP-3DT1 reconstructions of previously obtained postcontrast 3DT1W improved detection of brain metastases. This improvement was experienced by both the junior and experienced neuroradiologists and was also better at 3.0 T than at 1.5 T.

Fiabilidad diagnóstica de la doble lectura en RM cráneoespinal: evaluación retrospectiva / Diagnostic reliability of the double reading in craniospinal MRI: retrospective evaluation

Objetivo: Evaluar en forma retrospectiva la fiabilidad diagnóstica del sistema de doble lectura en RM craneoespinal a fin de obtener datos que permitan valorar su impacto sobre la calidad del informe final. Material y Métodos: Sobre un total de 13.460 RM craneoespinales realizadas en 2007 se revisaron en forma retrospectiva y aleatoria 450 informes de RM de columna y 900 informes de RM de cráneo. Entre la primera y la segunda lectura se juzgaron unicamente cambios de fondo, es decir aquellos pasibles de modificar la interpretación de las imágenes y consecuentemente, el diagnóstico final. Resultados: Se realizaron modificaciones en 75 informes de columna (17%) y en 115 de cráneo (13%). Conclusión: el sistema de doble lectura modifica de manera significativa la calidad del informe final.

Purpose:The aim of this paper is to evaluate retrospectively the diagnostic reliability of the double reading system in Spinal and Brain MRI. Material and Methods: Along 2007, 13460 Spinal andBrain MRI were performed, we reviewed 450 reports of Spinal MRI and 900 Brain MRI reports.Between the firstand the second report we paid attention only at major modifications that can modify the final diagnosis. Results: We founded major modifications in 75 (17%) of Spinal MRI reports and in 115 (13%) of the MRI brain reports. Conclusion: The double reading system improve significatively the quality of the final report.