Umbrella review and network meta-analysis of diagnostic imaging test accuracy studies in Differentiating between brain tumor progression versus pseudoprogression and radionecrosis.

PURPOSE: In this study we gathered and analyzed the available evidence regarding 17 different imaging modalities and performed network meta-analysis to find the most effective modality for the differentiation between brain tumor recurrence and post-treatment radiation effects. METHODS: We conducted a comprehensive systematic search on PubMed and Embase. The quality of eligible studies was assessed using the Assessment of Multiple Systematic Reviews-2 (AMSTAR-2) instrument. For each meta-analysis, we recalculated the effect size, sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio from the individual study data provided in the original meta-analysis using a random-effects model. Imaging technique comparisons were then assessed using NMA. Ranking was assessed using the multidimensional scaling approach and by visually assessing surface under the cumulative ranking curves. RESULTS: We identified 32 eligible studies. High confidence in the results was found in only one of them, with a substantial heterogeneity and small study effect in 21% and 9% of included meta-analysis respectively. Comparisons between MRS Cho/NAA, Cho/Cr, DWI, and DSC were most studied. Our analysis showed MRS (Cho/NAA) and 18F-DOPA PET displayed the highest sensitivity and negative likelihood ratios. 18-FET PET was ranked highest among the 17 studied techniques with statistical significance. APT MRI was the only non-nuclear imaging modality to rank higher than DSC, with statistical insignificance, however. CONCLUSION: The evidence regarding which imaging modality is best for the differentiation between radiation necrosis and post-treatment radiation effects is still inconclusive. Using NMA, our analysis ranked FET PET to be the best for such a task based on the available evidence. APT MRI showed promising results as a non-nuclear alternative.

Management and Molecular Characterization of Intraventricular Glioblastoma: A Single-Institution Case Series.

While the central nervous system (CNS) tumor classification has increasingly incorporated molecular parameters, there is a paucity of literature reporting molecular alterations found in intraventricular glioblastoma (IVGBM), which are rare. We present a case series of nine IVGBMs, including molecular alterations found in standardized next-generation sequencing (NGS). We queried the clinical charts, operative notes, pathology reports, and radiographic images of nine patients with histologically confirmed IVGBM treated at our institution (1995-2021). Routine NGS was performed on resected tumor tissue of two patients. In this retrospective case series of nine patients (22% female, median (range) age: 64.3 (36-85) years), the most common tumor locations were the atrium of the right lateral ventricle (33%) and the septum pellucidum (33%). Five patients had preoperative hydrocephalus, which was managed with intraoperative external ventricular drains in three patients and ventriculoperitoneal shunts in one patient. Hydrocephalus was managed with subtotal resection of a fourth ventricular IVGBM in one patient. The most common surgical approach was transcortical intraventricular (56%). Gross total resection was achieved in two patients, subtotal resection was achieved in six patients, and one patient received a biopsy only. Immunohistochemistry for IDH1 R132H mutant protein was performed in four cases and was negative in all four. Genetic alterations common in glioblastoma, IDH-wildtype, were seen in two cases with available NGS data, including EGFR gene amplification, TERT promoter mutation, PTEN mutation, trisomy of chromosome 7, and monosomy of chromosome 10. Following surgical resection, four patients received adjuvant chemoradiation. Median survival among our cohort was 4.7 months (IQR: 0.9-5.8 months). Management of IVGBM is particularly challenging due to their anatomical location, presentation with obstructive hydrocephalus, and fast growth, necessitating prompt intervention. Additional studies are needed to better understand the genetic landscape of IVGBM compared to parenchymal glioblastoma and may further elucidate the unique pathophysiology of these rare tumors.

Identification of the Somatomotor Network from Language Task-based fMRI Compared with Resting-State fMRI in Patients with Brain Lesions.

Background Resting-state functional MRI (rs-fMRI) is a potential alternative to task-based functional MRI (tb-fMRI) for somatomotor network (SMN) identification. Brain networks can also be generated from tb-fMRI by using independent component analysis (ICA). Purpose To investigate whether the SMN can be identified by using ICA from a language task without a motor component, the sentence completion functional MRI (sc-fMRI) task, compared with rs-fMRI. Materials and Methods The sc-fMRI and rs-fMRI scans in patients who underwent presurgical brain mapping between 2012 and 2016 were analyzed, using the same imaging parameters (other than scanning time) on a 3.0-T MRI scanner. ICA was performed on rs-fMRI and sc-fMRI scans with use of a tool to separate data sets into their spatial and temporal components. Two neuroradiologists independently determined the presence of the dorsal SMN (dSMN) and ventral SMN (vSMN) on each study. Groups were compared by using t tests, and logistic regression was performed to identify predictors of the presence of SMNs. Results One hundred patients (mean age, 40.9 years ± 14.8 [standard deviation]; 61 men) were evaluated. The dSMN and vSMN were identified in 86% (86 of 100) and 76% (76 of 100) of rs-fMRI scans and 85% (85 of 100) and 69% (69 of 100) of sc-fMRI scans, respectively. The concordance between rs-fMRI and sc-fMRI for presence of dSMN and vSMN was 75% (75 of 100 patients) and 53% (53 of 100 patients), respectively. In 10 of 14 patients (71%) where rs-fMRI did not show the dSMN, sc-fMRI demonstrated it. This rate was 67% for the vSMN (16 of 24 patients). Conclusion In the majority of patients, independent component analysis of sentence completion task functional MRI scans reliably demonstrated the somatomotor network compared with resting-state functional MRI scans. Identifying target networks with a single sentence completion scan could reduce overall functional MRI scanning times by eliminating the need for separate motor tasks. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Field and Birn in this issue.

The effect of regadenoson on the integrity of the human blood-brain barrier, a pilot study.

Regadenoson is an FDA approved adenosine receptor agonist which increases blood-brain barrier (BBB) permeability in rodents. Regadenoson is used clinically for pharmacologic cardiac stress testing using SPECT or CT imaging agents that do not cross an intact BBB. This study was conducted to determine if standard doses of regadenoson transiently disrupt the human BBB allowing higher concentrations of systemically administered imaging agents to enter the brain. Patients without known intracranial disease undergoing clinically indicated pharmacologic cardiac stress tests were eligible for this study. They received regadenoson (0.4 mg) followed by brain imaging with either 99mTc-sestamibi for SPECT or visipaque for CT imaging. Pre- and post-regadenoson penetration of imaging agents into brain were quantified [SPECT: radioactive counts, CT: Hounsfield units (HU)] and compared using a matched-pairs t-test. Twelve patients (33% male, median 60 yo) were accrued: 7 SPECT and 5 CT. No significant differences were noted in pre- and post-regadenoson values using mean radionuclide counts (726 vs. 757) or HU (29 vs. 30). While animal studies have demonstrated that regadenoson transiently increases the permeability of the BBB to dextran and temozolomide, we were unable to document changes in the penetration of contrast agents in humans with intact BBB using the FDA approved doses of regadenoson for cardiac evaluation. Further studies are needed exploring alternate regadenoson dosing, schedules, and studies in patients with brain tumors; as transiently disrupting the BBB to improve drug entry into the brain is critical to improving the care of patients with CNS malignancies.

Presurgical brain mapping of the language network in patients with brain tumors using resting-state fMRI: Comparison with task fMRI.

PURPOSE: To compare language networks derived from resting-state fMRI (rs-fMRI) with task-fMRI in patients with brain tumors and investigate variables that affect rs-fMRI vs task-fMRI concordance. MATERIALS AND METHODS: Independent component analysis (ICA) of rs-fMRI was performed with 20, 30, 40, and 50 target components (ICA20 to ICA50) and language networks identified for patients presenting for presurgical fMRI mapping between 1/1/2009 and 7/1/2015. 49 patients were analyzed fulfilling criteria for presence of brain tumors, no prior brain surgery, and adequate task-fMRI performance. Rs-vs-task-fMRI concordance was measured using Dice coefficients across varying fMRI thresholds before and after noise removal. Multi-thresholded Dice coefficient volume under the surface (DiceVUS) and maximum Dice coefficient (MaxDice) were calculated. One-way Analysis of Variance (ANOVA) was performed to determine significance of DiceVUS and MaxDice between the four ICA order groups. Age, Sex, Handedness, Tumor Side, Tumor Size, WHO Grade, number of scrubbed volumes, image intensity root mean square (iRMS), and mean framewise displacement (FD) were used as predictors for VUS in a linear regression. RESULTS: Artificial elevation of rs-fMRI vs task-fMRI concordance is seen at low thresholds due to noise. Noise-removed group-mean DiceVUS and MaxDice improved as ICA order increased, however ANOVA demonstrated no statistically significant difference between the four groups. Linear regression demonstrated an association between iRMS and DiceVUS for ICA30-50, and iRMS and MaxDice for ICA50. CONCLUSION: Overall there is moderate group level rs-vs-task fMRI language network concordance, however substantial subject-level variability exists; iRMS may be used to determine reliability of rs-fMRI derived language networks.

BRAF V600E-Mutant Glioblastoma with Extracranial Metastases Responsive to Combined BRAF and MEK Targeted Inhibition: A Case Report.

Recent advancements in understanding the biology of glioblastomas (GBM) and increasing adoption of genomic sequencing in oncology practice have led to the discovery of several targetable mutations in these cancers. Among them, the BRAF V600E mutation can be found in approximately 3% of GBM. Despite the aggressive nature of GBM, metastatic disease is rarely observed. While there are growing data utilizing BRAF-targeting strategies in patients with GBM, data examining their efficacy in cases of metastatic GBM are lacking. We present the case of a 46-year-old female with GBM, isocitrate dehydrogenase (IDH)-wildtype and O6-methylguanine-DNA methyltransferase promoter (MGMT) unmethylated, BRAF V600E-mutant, and MYC amplified with extra-central nervous system spread to the spine and lung. Four months after completion of treatment with standard chemoradiation and temozolomide, the patient developed severe back pain, leading to the eventual discovery of her metastatic disease. Based on the presence of the BRAF V600E mutation, the patient was treated with and achieved an intracranial and systemic response to combination BRAF-MEK targeted inhibition for 9 months before evidence of progression.

Catheter-directed venography for evaluating internal jugular vein pseudo-occlusion.

The incidence and effects of stenosis of the cerebral venous system are poorly understood. When noninvasive computed tomography venography (CTV) of the head and neck suggests complete internal jugular vein (IJV) occlusion, invasive catheter-directed venography can discordantly show venous patency. We compared CTV vs digital subtraction venography (DSV) in the evaluation of patency/occlusion in the suspected IJV and contralateral IJV. We queried the venous intervention database of our U.S. academic tertiary-care hospital to identify patients with complete or near-complete IJV occlusion per CTV from March 1, 2019 to March 1, 2020. We included patients with both noninvasive and invasive imaging of the target segment and the contralateral IJV. Four patients had suspected occlusion of the IJV at the skull base. Invasive catheter-directed venography consisted of DSV to assess direction of flow and vessel caliber, as well as manometry proximal and distal to areas of suspected stenosis. DSV showed patency in all 4 IJVs for which CTV had shown suspected occlusions. CTV findings of the contralateral IJVs were patency (n = 2), moderate stenosis (n = 1), and severe/critical stenosis (n = 1). Contralateral IJV caliber, measured by DSV, was concordant with CTV findings. Median mean-pressure gradients across the apparent occlusion and contralateral segments were 1 (range, 1-4) mmHg and 0 (range, 0-5) mmHg, respectively. Although noninvasive CTV may suggest absence of or attenuated flow within the IJV, this technique may be insufficient to establish complete occlusion. Catheter-directed venography can be used to evaluate patency, vessel caliber, and mean-pressure gradient.

The Role of Preoperative Magnetic Resonance Imaging in Assessing Neurovascular Compression Before Microvascular Decompression in Trigeminal Neuralgia.

BACKGROUND: Preoperative magnetic resonance imaging (MRI) is a standard component of the preoperative clinical workup for patients before microvascular decompression (MVD). However, its ability to accurately exclude neurovascular compression of the trigeminal nerve is not well understood. METHODS: We retrospectively reviewed 1020 patients with available preoperative MRI data before microvascular decompression. General patient demographics and clinical characteristics were collected for each case. We recorded both evidence of neurovascular conflict on preoperative MRI radiology notes and intraoperative compression from operative notes. Sensitivity, specificity, positive predictive value, and negative predictive value were determined for general MRI, high-resolution MRI, and non-high resolution. RESULTS: Overall, preoperative MRI before MVD showed a sensitivity of 75.8%, specificity of 65.8%, positive predictive value of 92.4%, and negative predictive value of 33.3% in predicting neurovascular compression of the trigeminal nerve. In particular, MRI was unable to identify 21.0% cases of sole arterial compression, 42.5% cases of sole venous compression, and combined arterial and venous compression in 18.5% of cases. A total of 958 patients (93.9%) underwent high-resolution preoperative MRI with skull base sequences. This imaging showed a sensitivity of 75.6%, specificity of 66.9%, positive predictive value of 92.5% and a negative predictive value of 33.4% in predicting trigeminal nerve neurovascular compression. Non-high-resolution MRI showed a sensitivity of 78.8%, specificity of 50.0%, positive predictive value of 89.1%, and negative predictive value of 31.3%. The negative predictive values of general, high-resolution, and non-high-resolution MRIs were all <50%. CONCLUSIONS: Preoperative MRI may offer a high predictive value for neurovascular conflict and should be part of the standard preoperative care workup for patients with trigeminal neuralgia. However, lack of neurovascular conflict on preoperative imaging is not sufficient to exclude patients from undergoing MVD.

Dynamic Brain Connectivity in Resting State Functional MR Imaging.

Dynamic functional connectivity adds another dimension to resting-state functional MR imaging analysis. In recent years, dynamic functional connectivity has been increasingly used in resting-state functional MR imaging, and several studies have demonstrated that dynamic functional connectivity patterns correlate with different physiologic and pathologic brain states. In fact, evidence suggests that dynamic functional connectivity is a more sensitive marker than static functional connectivity; therefore, it might be a promising tool to add to clinical functional neuroimaging. This article provides a broad overview of dynamic functional connectivity and reviews its general principles, techniques, and potential clinical applications.

Automated eloquent cortex localization in brain tumor patients using multi-task graph neural networks.

Localizing the eloquent cortex is a crucial part of presurgical planning. While invasive mapping is the gold standard, there is increasing interest in using noninvasive fMRI to shorten and improve the process. However, many surgical patients cannot adequately perform task-based fMRI protocols. Resting-state fMRI has emerged as an alternative modality, but automated eloquent cortex localization remains an open challenge. In this paper, we develop a novel deep learning architecture to simultaneously identify language and primary motor cortex from rs-fMRI connectivity. Our approach uses the representational power of convolutional neural networks alongside the generalization power of multi-task learning to find a shared representation between the eloquent subnetworks. We validate our method on data from the publicly available Human Connectome Project and on a brain tumor dataset acquired at the Johns Hopkins Hospital. We compare our method against feature-based machine learning approaches and a fully-connected deep learning model that does not account for the shared network organization of the data. Our model achieves significantly better performance than competing baselines. We also assess the generalizability and robustness of our method. Our results clearly demonstrate the advantages of our graph convolution architecture combined with multi-task learning and highlight the promise of using rs-fMRI as a presurgical mapping tool.

A Multi-Scale Spatial and Temporal Attention Network on Dynamic Connectivity to Localize The Eloquent Cortex in Brain Tumor Patients.

We present a deep neural network architecture that combines multi-scale spatial attention with temporal attention to simultaneously localize the language and motor areas of the eloquent cortex from dynamic functional connectivity data. Our multi-scale spatial attention operates on graph-based features extracted from the connectivity matrices, thus honing in on the inter-regional interactions that collectively define the eloquent cortex. At the same time, our temporal attention model selects the intervals during which these interactions are most pronounced. The final stage of our model employs multi-task learning to differentiate between the eloquent subsystems. Our training strategy enables us to handle missing eloquent class labels by freezing the weights in those branches while updating the rest of the network weights. We evaluate our method on resting-state fMRI data from one synthetic dataset and one in-house brain tumor dataset while using task fMRI activations as ground-truth labels for the eloquent cortex. Our model achieves higher localization accuracies than conventional deep learning approaches. It also produces interpretable spatial and temporal attention features which can provide further insights for presurgical planning. Thus, our model shows translational promise for improving the safety of brain tumor resections.

Role of Functional Magnetic Resonance Imaging in the Presurgical Mapping of Brain Tumors.

When planning for brain tumor resection, a balance between maximizing resection and minimizing injury to eloquent brain parenchyma is paramount. The advent of blood oxygenation level-dependent functional magnetic resonance (fMR) imaging has allowed researchers and clinicians to reliably measure physiologic fluctuations in brain oxygenation related to neuronal activity with good spatial resolution. fMR imaging can offer a unique insight into preoperative planning for brain tumors by identifying eloquent areas of the brain affected or spared by the neoplasm. This article discusses the fMR imaging techniques and their applications in neurosurgical planning.

A novel radiographic marker of sarcopenia with prognostic value in glioblastoma.

OBJECTIVE: Sarcopenia is an important prognostic consideration in surgical oncology that has received relatively little attention in brain tumor patients. Temporal muscle thickness (TMT) has recently been proposed as a novel radiographic marker of sarcopenia that can be efficiently obtained within existing workflows. We investigated the prognostic value of TMT in primary and progressive glioblastoma. METHODS: TMT measurements were performed on magnetic resonance images of 384 patients undergoing 541 surgeries for glioblastoma. Relationships between TMT and clinical characteristics were examined on bivariate analysis. Optimal TMT cutpoints were established using maximally selected rank statistics. Predictive value of TMT upon postoperative survival (PS) was assessed using Cox proportional hazards regression adjusted for age, sex, Karnofsky performance status (KPS), Stupp protocol completion, extent of resection, and tumor molecular markers. RESULTS: Average TMT for the primary and progressive glioblastoma cohorts was 9.55 mm and 9.40 mm, respectively. TMT was associated with age (r = -0.14, p = 0.0008), BMI (r = 0.29, p < 0.0001), albumin (r = 0.11, p = 0.0239), and KPS (r = 0.11, p = 0.0101). Optimal TMT cutpoints for the primary and progressive cohorts were ≤ 7.15 mm and ≤ 7.10 mm, respectively. High TMT was associated with increased Stupp protocol completion (p = 0.001). On Cox proportional hazards regression, high TMT predicted increased PS in progressive [HR 0.47 (95% confidence interval (CI)) 0.25-0.90), p = 0.023] but not primary [HR 0.99 (95% CI 0.64-1.51), p = 0.949] glioblastoma. CONCLUSIONS: TMT correlates with important prognostic variables in glioblastoma and predicts PS in patients with progressive, but not primary, disease. TMT may represent a pragmatic neurosurgical biomarker in glioblastoma that could inform treatment planning and perioperative optimization.

Head and neck cancers on CT: preliminary study of treatment response assessment based on computerized volume analysis.

OBJECTIVE: The objective of our study was to investigate the feasibility of computerized segmentation of lesions on head and neck CT scans and evaluate its potential for estimating changes in tumor volume in response to treatment of head and neck cancers. MATERIALS AND METHODS: Twenty-six CT scans were retrospectively collected from the files of 13 patients with 35 head and neck lesions. The CT scans were obtained from an examination performed before treatment (pretreatment scan) and an examination performed after one cycle of chemotherapy (posttreatment scan). Thirteen lesions were primary site cancers and 22 were metastatic lymph nodes. An experienced radiologist (radiologist 1) marked the 35 lesions and outlined each lesion's 2D contour on the best slice on both the pre- and posttreatment scans. Full 3D contours were also manually extracted for the 13 primary tumors. Another experienced radiologist (radiologist 2) verified and modified, if necessary, all manually drawn 2D and 3D contours. An in-house-developed computerized system performed 3D segmentation based on a level set model. RESULTS: The computer-estimated change in tumor volume and percentage change in tumor volume between the pre- and posttreatment scans achieved a high correlation (intraclass correlation coefficient [ICC] = 0.98 and 0.98, respectively) with the estimates from manual segmentation for the 13 primary tumors. The average error in estimating the percentage change in tumor volume by automatic segmentation relative to the radiologists' average error was -1.5% +/- 5.4% (SD). For the 35 lesions, the ICC between the automatic and manual estimates of change in pre- to posttreatment tumor area was 0.93 and of percentage change in pre- to posttreatment tumor area was 0.85. The average error in estimating the percentage change in tumor area by automatic segmentation was -3.2% +/- 15.3%. CONCLUSION: Preliminary results indicate that this computerized segmentation system can reliably estimate changes in tumor size on CT scans relative to radiologists' manual segmentation. This information can be used to calculate changes in tumor size on pre- and posttreatment scans to assess response to treatment.

Motion of a cadaver model of cervical injury during endotracheal intubation with a Bullard laryngoscope or a Macintosh blade with and without in-line stabilization.

BACKGROUND: Endotracheal intubation in patients with potential cervical injury is a common dilemma in trauma. Although direct laryngoscopy (DL) with manual in-line stabilization (MILS) is a standard technique there is little data on the effect of MILS on cervical motion. Likewise there is little data available regarding alternative airway techniques in this setting. This study compared intubations with and without MILS in a cadaver model of cervical instability. We also used this model to compare intubations using DL with a Macintosh blade versus a Bullard laryngoscope (BL). METHODS: Complete C4-C5 disarticulations were surgically created in 10 fresh human cadavers. The cadavers were then intubated in a random order with either BL or DL with and without MILS. The motion at the unstable interspace was measured for subluxation, angulation, and distraction. RESULTS: MILS did not significantly affect maximal motion of this model in any of the three measures using either DL or BL. There were no clinically significant differences in maximal median motion in any of the three measures when comparing the two blades. However, there was significantly more variance in the subluxation caused by DL than by BL. CONCLUSIONS: We were unable to demonstrate any significant effect of MILS on the motion of an unstable cervical spine in this cadaver model. The BL appears to be a viable alternative to DL in the setting of an unstable lower cervical spine.

Dynamic Functional Connectivity States Between the Dorsal and Ventral Sensorimotor Networks Revealed by Dynamic Conditional Correlation Analysis of Resting-State Functional Magnetic Resonance Imaging.

Functional connectivity in resting-state functional magnetic resonance imaging (rs-fMRI) has received substantial attention since the initial findings of Biswal et al. Traditional network correlation metrics assume that the functional connectivity in the brain remains stationary over time. However, recent studies have shown that robust temporal fluctuations of functional connectivity among as well as within functional networks exist, challenging this assumption. In this study, these dynamic correlation differences were investigated between the dorsal and ventral sensorimotor networks by applying the dynamic conditional correlation model to rs-fMRI data of 20 healthy subjects. k-Means clustering was used to determine an optimal number of discrete connectivity states (k = 10) of the sensorimotor system across all subjects. Our analysis confirms the existence of differences in dynamic correlation between the dorsal and ventral networks, with highest connectivity found within the ventral motor network.

Reporting of Resting-State Functional Magnetic Resonance Imaging Preprocessing Methodologies.

There has been a rapid increase in resting-state functional magnetic resonance imaging (rs-fMRI) literature in the past few years. We aim to highlight the variability in the current reporting practices of rs-fMRI acquisition and preprocessing parameters. The PubMed database was searched for the selection of appropriate articles in the rs-fMRI literature and the most recent 100 articles were selected based on our criteria. These articles were evaluated based on a checklist for reporting of certain preprocessing steps. All of the studies reported the temporal resolution for the scan and the software used for the analysis. Less than half of the studies reported physiologic monitoring, despiking, global signal regression, framewise displacement, and volume censoring. A majority of the studies mentioned the scanning duration, eye status, and smoothing kernel. Overall, we demonstrate the wide variability in reporting of preprocessing methods in rs-fMRI studies. Although there might be potential variability in reporting across studies due to individual requirements for a study, we suggest the need for standardizing reporting guidelines to ensure reproducibility.

Radiation-induced cavernomas of the brain.

The purpose of this report is to add support to the growing literature that there is a correlation between radiation and cavernomas of the brain, particularly if the radiation is received in childhood, as well as to increase awareness of this correlation in the radiology community. Retrospective review of our experience returned five patients who received radiation therapy while they were children and developed cavernomas in the irradiated tissues 3-41 years later. Cavernomas should be considered in the differential diagnosis of a hemorrhagic lesion in any patient who has received previous CNS radiation, particularly if he or she underwent radiation therapy in childhood.