PURPOSE:In this prospective observational study, we evaluated dose-response relationships between radiation dose to the brain's resting-state networks (RSNs) and changes in neurocognitive function (NCF) following radiation therapy (RT) in adult patients with diffuse glioma. METHODS AND MATERIALS:Adult patients with isocitrate dehydrogenase-wildtype and isocitrate dehydrogenase-mutant gliomas underwent NCF testing using the National Institutes of Health Toolbox Cognition Battery and resting-state functional magnetic resonance imaging (rs-fMRI) before (baseline) and 6 months after RT. The battery assessed 5 cognitive domains and generated a fluid cognition composite score. NCF change was defined as the percent change in age-adjusted scores from baseline to follow-up. Radiation dosimetric parameters were extracted for 13 RSNs and 3 subcortical regions, defined by 300 rs-fMRI-derived regions of interest. Correlations between NCF change and dosimetric parameters were assessed using Spearman's rank correlation test (ρ). Linear regression models were compared using a nested analysis of variance, the Akaike information criterion, and adjusted R2. RESULTS:Of the 48 patients enrolled, 36 were evaluable with paired rs-fMRI and NCF data. Moderate negative correlations were observed between changes in episodic memory and the mean dose to the medial temporal lobe network (ρ = -0.41; 95% CI, -0.66, -0.08; P = .01), visual network (ρ = -0.42; 95% CI, -0.67, -0.09; P = .01), and parietal memory network (ρ = -0.40; 95% CI, -0.65, -0.07; P = .01). No significant correlations were found for other RSNs or NCF domains. A linear regression model incorporating medial temporal lobe dose and its interaction with age outperformed the age-only model in explaining variance in episodic memory change (P = .046; Akaike information criterion change = -2.95; adjusted R2 = 0.313). CONCLUSIONS:Focal dose-response relationships were observed between radiation dose to specific RSNs and episodic memory changes following RT, highlighting the prognostic and therapeutic potential of rs-fMRI in identifying targets for cognitive preservation in patients undergoing RT.

Infant (p21) mice were subjected to fractionated whole-brain radiotherapy (RT) then evaluated several months later using wide-field optical imaging. While RT broadly altered functional network organization, the largest effects occurred within higher-order cognitive regions.

Objectives/Goals: Cognitive decline is a known sequalae of intracranial radiation in the treatment of brain metastases. In this study, we investigate global structural changes in the brain akin to accelerated aging and compare aging kinetics between patients treated with whole-brain radiation therapy (WBRT) and stereotactic radiosurgery (SRS). Methods/Study Population: This retrospective study consists of patients with brain metastases treated with WBRT and SRS at our institution. Brain MRI images collected prior to radiation therapy and at approximately three and six months following radiation will be analyzed, excluding patients with evidence of worsening disease burden in the brain. Surface morphology of the cerebral cortex and sub-cortical structures will be extracted using Freesurfer and converted to graphs. Data will then be input into a validated graph convolutional neural network model to estimate brain age at each time point. A generalized linear model will be used to estimate the aging pace between baseline and follow-up for each subject within the whole brain as well as the sub-cortical structures, which will be compared between WBRT and SRS treatment groups. Results/Anticipated Results: We anticipate that intracranial radiation will accelerate brain aging to a greater extent following WBRT compared to SRS. Additionally, this accelerated aging will occur globally in the whole brain as well as within individual substructures, including the cerebral cortex, nucleus accumbens, amygdala, caudate, hippocampus, pallidum, putamen, and thalamus. Discussion/Significance of Impact: This study will demonstrate structural changes in the brain analogous to accelerated aging, supporting its potential use as an imaging biomarker to monitor cognitive decline after radiation therapy. Future work will explore the relationship between structural brain aging and assessments of neurocognitive function.

PURPOSE:This prospective observational study employed resting-state functional magnetic resonance imaging (rs-fMRI) to investigate network-level disturbances associated with neurocognitive function (NCF) changes in patients with gliomas following partial-brain radiation therapy (RT). METHODS AND MATERIALS:Adult postoperative patients with either isocitrate dehydrogenase (IDH)-wild-type or IDH-mutant gliomas underwent computerized NCF testing and rs-fMRI at baseline and 6 months post-RT. rs-fMRI data were assessed using seed-based functional connectivity (FC). NCF changes were quantified by the percent change in age-normalized composite scores from baseline (ΔNCFcomp). Connectivity regression analysis assessed the association between network FC changes and NCF changes, using a split-sample approach with a 26-patient training set and a 6-patient validation set, iterated 200 times. Permutation tests evaluated the significance of network selection. RESULTS:Between September 2020 and December 2023, 43 patients were enrolled, with 32 completing both baseline and follow-up evaluations. The mean ΔNCFcomp was 2.9% (SD, 13.7%), with 38% experiencing a decline. Patients with IDH-mutant glioma had similar NCF changes compared with those with IDH-wild-type glioma. Intrahemispheric FC was similar between ipsilateral and contralateral hemispheres for 91% of patients at baseline, and 69% had similar intrahemispheric FC change posttreatment. FC changes accounted for a moderate fraction of variance in NCF changes (mean R2, 0.301; SD, 0.249), with intranetwork FC of the parietal memory network (PMN-PMN, P = .001) and internetwork FC between the PMN and the visual network (PMN-VN, P = .002) as the most significant factors. Similar findings were obtained by sensitivity analyses using only the FC data from the hemisphere contralateral to the tumor. CONCLUSIONS:Post-RT rs-fMRI changes significantly reflected NCF decline, highlighting rs-fMRI as a promising imaging biomarker for neurocognitive decline after RT.

Cognitive dysfunction following radiotherapy (RT) is one of the most common complications associated with RT delivered to the brain, but the precise mechanisms behind this dysfunction are not well understood, and to date, there are no preventative measures or effective treatments. To improve patient outcomes, a better understanding of the effects of radiation on the brain's functional systems is required. Functional magnetic resonance imaging (fMRI) has shown promise in this regard, however, compared to neural activity, hemodynamic measures of brain function are slow and indirect. Understanding how RT acutely and chronically affects functional brain organization requires more direct examination of temporally evolving neural dynamics as they relate to cerebral hemodynamics for bridging with human studies. In order to adequately study the underlying mechanisms of RT-induced cognitive dysfunction, the development of clinically mimetic RT protocols in animal models is needed. To address these challenges, we developed a fractionated whole-brain RT protocol (3Gy/day for 10 days) and applied longitudinal wide field optical imaging (WFOI) of neural and hemodynamic brain activity at 1, 2, and 3 months post RT. At each time point, mice were subject to repeated behavioral testing across a variety of sensorimotor and cognitive domains. Disruptions in cortical neuronal and hemodynamic activity observed 1 month post RT were significantly worsened by 3 months. While broad changes were observed in functional brain organization post RT, brain regions most impacted by RT occurred within those overlapping with the mouse default mode network and other association areas similar to prior reports in human subjects. Further, significant cognitive deficits were observed following tests of novel object investigation and responses to auditory and contextual cues after fear conditioning. Our results fill a much-needed gap in understanding the effects of whole-brain RT on systems level brain organization and how RT affects neuronal versus hemodynamic signaling in the cortex. Having established a clinically-relevant injury model, future studies can examine therapeutic interventions designed to reduce neuroinflammation-based injury following RT. Given the overlap of sequelae that occur following RT with and without chemotherapy, these tools can also be easily incorporated to examine chemotherapy-related cognitive impairment.

Purpose: Pediatric brain tumor patients often experience significant cognitive sequelae. Resting-state functional MRI (rsfMRI) provides a measure of brain network organization, and we hypothesize that pediatric brain tumor patients treated with proton therapy will demonstrate abnormal brain network architecture related to cognitive outcome and radiation dosimetry.Participants and Methods: Pediatric brain tumor patients treated with proton therapy were enrolled on a prospective study of cognitive assessment using the NIH Toolbox Cognitive Domain. rsfMRI was obtained in participants able to complete unsedated MRI. Brain system segregation (BSS), a measure of brain network architecture, was calculated for the whole brain, the high-level cognition association systems, and the sensory-motor systems.Results: Twenty-six participants were enrolled in the study for cognitive assessment, and 18 completed rsfMRI. There were baseline cognitive deficits in attention and inhibition and processing speed prior to radiation with worsening performance over time in multiple domains. Average BSS across the whole brain was significantly decreased in participants compared with healthy controls (1.089 and 1.101, respectively; P = 0.001). Average segregation of association systems was significantly lower in participants than in controls (P < 0.001) while there was no difference in the sensory motor networks (P = 0.70). Right hippocampus dose was associated with worse attention and inhibition (P < 0.05) and decreased segregation in the dorsal attention network (P < 0.05).Conclusion: Higher mean dose to the right hippocampus correlated with worse dorsal attention network segregation and worse attention and inhibition cognitive performance. Patients demonstrated alterations in brain network organization of association systems measured with rsfMRI; however, somatosensory system segregation was no different from healthy children. Further work with preradiation rsfMRI is needed to assess the effects of surgery and presence of a tumor on brain network architecture.

PURPOSE:The annual quality assurance (QA) of Leksell Gamma Knife® (LGK) systems are typically performed using films. Film is a good candidate for small field dosimetry due to its high spatial resolution and availability. However, there are multiple challenges with using film; film does not provide real-time measurement and requires batch-specific calibration. Our findings show that active detector-based QA can simplify the procedure and save time without loss of accuracy.METHODS:Annual QA tests for a LGK Icon™ system were performed using both film-based and filmless techniques. Output calibration, relative output factors (ROF), radiation profiles, sector uniformity/source counting, and verification of the unit center point (UCP) and radiation focal point (RFP) coincidence tests were performed. Radiochromic films, two ionization chambers, and a synthetic diamond detector were used for the measurements. Results were compared and verified with the treatment planning system (TPS).RESULTS:The measured dose rate of the LGK Icon was within 0.4% of the TPS value set at the time of commissioning using an ionization chamber. ROF for the 8 and 4-mm collimators were found to be 0.3% and 1.8% different from TPS values using the MicroDiamond detector and 2.6% and 1.9% different for film, respectively. Excellent agreement was found between TPS and measured dose profiles using the MicroDiamond detector which was within 1%/1 mm vs 2%/1 mm for film. Sector uniformity was found to be within 1% for all eight sectors measured using an ionization chamber. Verification of UCP and RFP coincidence using the MicroDiamond detector and pinprick film test was within 0.3 mm at isocenter for both.CONCLUSION:The annual QA of a LGK Icon was successfully performed by employing filmless techniques. Comparable results were obtained using radiochromic films. Utilizing active detectors instead of films simplifies the QA process and saves time without loss of accuracy.

Radiation therapy (RT) plays a vital role in the treatment of brain cancers, but it frequently results in cognitive decline in the patients who receive it. Because the underlying mechanisms for this decline remain poorly understood, the brain is typically treated as a single, uniform volume when evaluating the toxic effects of RT plans. This ignorance represents a significant deficit in the field of radiation oncology, as the technology exists to manipulate dose distributions to spare regions of the brain, but there exists no body of knowledge regarding what is critical to spare. This deficit exists due to the numerous confounding factors that are frequently associated with radiotherapy, including the tumors themselves, other treatments such as surgery and chemotherapy, and dose gradients across the brain. Here, we present a case in which a 57-year-old male patient received a uniform dose of radiation across the whole brain, did not receive concurrent chemotherapy, had minimal surgical intervention and a small tumor burden, and received resting-state functional magnetic resonance imaging (fMRI) scans both before and after RT. To our knowledge, this is the first study on the effects of whole-brain radiotherapy on functional network organization, and this patient's treatment regimen represents a rare and non-replicable opportunity to isolate the effects of radiation on functional connectivity. We observed substantial changes in the subject's behavior and functional network organization over a 12-month timeframe. Interestingly, the homogenous radiation dose to the brain had a heterogeneous effect on cortical networks, and the functional networks most affected correspond with observed cognitive behavioral deficits. This novel study suggests that the cognitive decline that occurs after whole-brain radiation therapy may be network specific and related to the disruption of large-scale distributed functional systems, and it indicates that fMRI is a promising avenue of study for optimizing cognitive outcomes after RT.

Abstract Purpose Characterize the intra‐fraction motion management (IFMM) system found on the Gamma Knife Icon (GKI), including spatial accuracy, latency, temporal performance, and overall effect on delivered dose. Methods A phantom was constructed, consisting of a three‐axis translation mount, a remote motorized flipper, and a thermoplastic sphere surrounding a radiation detector. An infrared marker was placed on the translation mount secured to the flipper. The spatial accuracy of the IFMM was measured via the translation mount in all Cartesian planes. The detector was centered at the radiation focal point. A remote signal was used to move the marker out of the IFMM tolerance and pause the beam. A two‐channel electrometer was used to record the signals from the detector and the flipper when motion was signaled. These signals determined the latency and temporal performance of the GKI. Results The spatial accuracy of the IFMM was found to be <0.1 mm. The measured latency was <200 ms. The dose difference with five interruptions was <0.5%. Conclusion This work provides a quantitative characterization of the GKI IFMM system as required by the Nuclear Regulatory Commission. This provides a methodology for GKI users to satisfy these requirements using common laboratory equipment in lieu of a commercial solution.

Currently, functional magnetic resonance imaging (fMRI) facilitates a preoperative awareness of an association of an eloquent region with a tumor. This information gives the neurosurgeon helpful information that can aid in creating a surgical strategy. Typically, task-based fMRI has been employed to preoperatively localize speech and motor function. Task-based fMRI depends on the patient's ability to comply with the task paradigm, which often is impaired in the setting of a brain tumor. This problem is overcome by using resting-state fMRI (rs-fMRI) to localize function. rs-fMRI measures spontaneous fluctuations in the blood oxygen level-dependent (BOLD) signal, representing the brain's functional organization. In a neurosurgical context, it allows noninvasive simultaneous assessment of multiple large-scale distributed networks. Compared with task-related fMRI, rs-fMRI provides more comprehensive information on the functional architecture of the brain and is applicable in settings where task-related fMRI may provide inadequate information or could not be performed. Taken together, rs-fMRI substantially expands the preoperative mapping capability in efficiency, effectiveness, and scope. In this article, a brief introduction into rs-fMRI processing methods is followed by a detailed discussion on the role rs-fMRI plays in presurgical planning.

Purpose: Task-based fMRI has traditionally been used to locate eloquent regions of the brain that are relevant to specific cognitive tasks. These locations have, in turn, been used successfully to inform surgical planning. Resting-state functional MRI (fMRI) uses alternative methods to find networks, but does not require any task performance by a patient. Materials and Methods: Resting-state fMRI uses correlations in the blood oxygen level–dependent (BOLD) signal to identify connected regions across the brain that form networks. Several methods of analyzing the data have been applied to calculate resting-state networks. In particular, seed-based correlation mapping and independent component analysis (ICA) are two commonly used techniques. Results: Several studies using these analysis techniques are described in this chapter. Resting-state data has been used successfully as a presurgical planning tool in tumor patients and epilepsy patients. Conclusions: Resting-state fMRI has been compared favorably to other methods of determining functional connectivity, including task-based fMRI and electrocortical stimulation. These results demonstrate great promise for the future of resting-state fMRI in presurgical planning.

Functional magnetic resonance imaging (fMRI) has become a common tool for pre-surgical sensorimotor mapping, and is a significant preoperative asset for tumors located adjacent to the central sulcus. fMRI has changed surgical options for many patients. This noninvasive tool allows for easy display and integration with other neuroimaging techniques. Although fMRI is a useful preoperative tool, it is not perfect. Tumors that affect the normal vascular coupling of neuronal activity will affect fMRI measurements. This article discusses the usefulness of blood oxygen level dependent (BOLD) fMRI with regard to preoperative motor mapping.

BACKGROUND:Recent findings associated with resting-state cortical networks have provided insight into the brain's organizational structure. In addition to their neuroscientific implications, the networks identified by resting-state functional magnetic resonance imaging (rs-fMRI) may prove useful for clinical brain mapping.OBJECTIVE:To demonstrate that a data-driven approach to analyze resting-state networks (RSNs) is useful in identifying regions classically understood to be eloquent cortex as well as other functional networks.METHODS:This study included 6 patients undergoing surgical treatment for intractable epilepsy and 7 patients undergoing tumor resection. rs-fMRI data were obtained before surgery and 7 canonical RSNs were identified by an artificial neural network algorithm. Of these 7, the motor and language networks were then compared with electrocortical stimulation (ECS) as the gold standard in the epilepsy patients. The sensitivity and specificity for identifying these eloquent sites were calculated at varying thresholds, which yielded receiver-operating characteristic (ROC) curves and their associated area under the curve (AUC). RSNs were plotted in the tumor patients to observe RSN distortions in altered anatomy.RESULTS:The algorithm robustly identified all networks in all patients, including those with distorted anatomy. When all ECS-positive sites were considered for motor and language, rs-fMRI had AUCs of 0.80 and 0.64, respectively. When the ECS-positive sites were analyzed pairwise, rs-fMRI had AUCs of 0.89 and 0.76 for motor and language, respectively.CONCLUSION:A data-driven approach to rs-fMRI may be a new and efficient method for preoperative localization of numerous functional brain regions.

Objective: To implement an automated analysis of EEG recordings from prematurely-born infants and thus provide objective, reproducible results.Methods: Bayesian probability theory is employed to compute the posterior probability for developmental features of interest in EEG recordings. Currently, these features include smooth delta waves (0.51.5 Hz, > 100 mu V), delta brushes (delta portion: 0.5-1.5 Hz, > 100 mu V; "brush" portion: 8-22 Hz, <75 mu V), and interburst intervals (<10 mu V), though the approach taken can be generalized to identify other EEG features of interest.Results: When compared with experienced electroencephalographers, the algorithm had a true positive rate between 72% and 79% for the identification of delta waves (smooth or "brush") and interburst intervals, which is comparable to the inter-rater reliability. When distinguishing between smooth delta waves and delta brushes, the algorithm's true positive rate was between 53% and 88%, which is slightly less than the inter-rater reliability.Conclusion: Bayesian probability theory can be employed to consistently identify features of EEG recordings from premature infants. Significance: The identification of features in EEG recordings provides a first step towards the automated analysis of EEG recordings from premature infants. (C) 2012 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.