Follow-up report of fundus findings of tuberous sclerosis-associated retinal astrocytoma of two siblings.

A late adolescent with tuberous sclerosis (TS) presented with reduced vision in one eye to our tertiary care university hospital 4 years ago. Fundus examination revealed multiple retinal astrocytic hamartomas (RAHs) in both eyes. His younger sibling, who also had TS, was found to have RAH on retinal screening. The swept-source optical coherence tomography (SS-OCT) findings were typical of RAH. We further noted that some of the RAH lesions showed segmental whitening of the outer walls of the arterioles, which traversed through them. The segmental whitening may suggest the enveloping of normal retinal vessels by the tumour. En-face and B-scan SS-OCT angiography of patients with TS showed vascularity within the tumour. The vessels within the tumour appeared to be in continuity with the retinal vasculature. Both siblings were reviewed annually. At the end of 4 years, there was no change in visual acuity, tumour size, number, vascularity and behaviour.

Sporadic subependymal giant cell astrocytoma with somatic TSC2 mutation: A case report.

Subependymal giant cell astrocytoma (SEGA) is a rare circumscribed astrocytic glioma that occurs in approximately 25% of all tuberous sclerosis (TSC) cases. Herein, we discuss an atypical presentation of SEGA, including the genetic alterations, impact on clinical presentation, and the determinants of each medical and surgical treatment option. A 14-year-old girl presented with intermittent headache and a right intraventricular mass originating near the foramen of Monro. The tumor's proximity to critical structures necessitated maximum safe resection, which improved her symptoms. Histological findings indicated SEGA, and genetic sequencing revealed a TSC2 mutation. However, complete clinical and radiological evaluations failed to reveal TSC. Two months later, a new subependymal nodule was incidentally found. She had a recurrent left occipital horn lesion and diffuse smooth leptomeningeal enhancement with no spine drop metastases. She was administered everolimus as the tumor was considered unresectable. Subsequent imaging revealed a reduction in both residual and new lesions.

Association of Clinical, Tumor, and Treatment Characteristics With Seizure Control in Patients With IDH1/2-Mutant Lower-Grade Glioma.

BACKGROUND AND OBJECTIVES: Patients with IDH1/2-mutant lower-grade glioma have a high frequency of seizures. We aimed to investigate the correlations between seizures and tumor/patient characteristics and the impact of surgery and adjuvant treatments (AT) on seizure control along the disease trajectory. METHODS: We retrospectively included patients with IDH1/2-mutant lower-grade glioma who underwent surgery at the neurosurgery divisions of the University of Turin and Milan and were treated at the Division of Neuro-Oncology of Turin. Inclusion criteria were a diagnosis according to the 2021 WHO Classification and presentation with seizures; exclusion criteria were presence of CDKN2A/B homozygous deletion, intense/ring contrast enhancement on MRI at presentation, and small tissue biopsy. We evaluated seizure freedom for 2 months after surgery, 6 months from starting observation or AT, at recurrence, and for 6 months after treatments of recurrence. RESULTS: We included 150 patients. There were 77 (51%) and 31 (21%) patients with IDH-mutant/1p19q-codeleted grade 2 and 3 oligodendroglioma and 30 (20%) and 12 (8%) with IDH-mutant grade 2 and 3 astrocytoma, respectively. Total resection was accomplished in 68 (45%). Seventy-five patients (50%) received AT while the remaining 75 were observed with MRI. After 6 months after AT, 28 of 29 patients (96.5%) displayed seizure reduction, 5 of 28 (18%) being seizure-free. 66 of 124 patients (53%) had seizures at recurrence. After 6 months after second-line treatments, 60 of 66 patients (91%) had seizure reduction, 11 (17%) being seizure-free. In multivariable analyses, grade 3 histology positively correlated with seizure freedom at 2 months after surgery (OR 3.5, 1.4-8.9, p = 0.008), 6 months after AT (OR 9.0, 1.5-54.9, p = 0.017), and 6 months after treatment of recurrence (OR 4.9, 1.5-16.5, p = 0.009). Adjuvant radiotherapy reduced seizures at recurrence in a univariate analysis (OR 0.14, 0.03-0.7, p = 0.020). Patients with seizure freedom after surgery and AT displayed longer progression-free survival (PFS) (65, 24.5-105, vs 48 months, 32-63.5, p = 0.037). DISCUSSION: This study analyzed seizure control in patients with IDH1/2-mutant lower-grade glioma across multiple time points. Grade 3 correlated with better seizure control throughout the entire disease trajectory, and seizure freedom after surgery and AT correlated with a longer PFS regardless of tumor grade. These results could serve as an external control arm in clinical trials evaluating the efficacy on seizures of antitumor agents in patients with IDH-mutant lower-grade glioma.

How does deep learning/machine learning perform in comparison to radiologists in distinguishing glioblastomas (or grade IV astrocytomas) from primary CNS lymphomas?: a meta-analysis and systematic review.

BACKGROUND: Several studies have been published comparing deep learning (DL)/machine learning (ML) to radiologists in differentiating PCNSLs from GBMs with equivocal results. We aimed to perform this meta-analysis to evaluate the diagnostic accuracy of ML/DL versus radiologists in classifying PCNSL versus GBM using MRI. METHODOLOGY: The study was performed in accordance with PRISMA guidelines. Data was extracted and interpreted by two researchers with 12 and 23 years' experience, respectively, and QUADAS-2 tool was used for quality and risk-bias assessment. We constructed contingency tables to derive sensitivity, specificity accuracy, summary receiver operating characteristic (SROC) curve, and the area under the curve (AUC). RESULTS: Our search identified 11 studies, of which 8 satisfied our inclusion criteria and restricted the analysis in each study to reporting the model showing highest accuracy, with a total sample size of 1159 patients. The random effects model showed a pooled sensitivity of 0.89 [95% CI:0.84-0.92] for ML and 0.82 [95% CI:0.76-0.87] for radiologists. Pooled specificity was 0.88 [95% CI: 0.84-0.91] for ML and 0.90 [95% CI: 0.81-0.95] for radiologists. Pooled accuracy was 0.88 [95% CI: 0.86-0.90] for ML and 0.86 [95% CI: 0.78-0.91] for radiologists. Pooled AUC of ML was 0.94 [95% CI:0.92-0.96]and for radiologists, it was 0.90 [95% CI: 0.84-0.93]. CONCLUSIONS: MRI-based ML/DL techniques can complement radiologists to improve the accuracy of classifying GBMs from PCNSL, possibly reduce the need for a biopsy, and avoid any unwanted neurosurgical resection of a PCNSL.

High-Grade Astrocytoma with Piloid Features: A Dual Institutional Review of Imaging Findings of a Novel Entity.

High-grade astrocytoma with piloid features (HGAP) is a recently identified brain tumor characterized by a distinct DNA methylation profile. Predominantly located in the posterior fossa of adults, HGAP is notably prevalent in individuals with neurofibromatosis type 1. We present an image-centric review of HGAP and explore the association between HGAP and neurofibromatosis type 1. Data were collected from 8 HGAP patients treated at two tertiary care institutions between January 2020 and October 2023. Demographic details, clinical records, management, and tumor molecular profiles were analyzed. Tumor characteristics, including location and imaging features on MR imaging, were reviewed. Clinical or imaging features suggestive of neurofibromatosis 1 or the presence of NF1 gene alteration were documented. The mean age at presentation was 45.5 years (male/female = 5:3). Tumors were midline, localized in the posterior fossa (n = 4), diencephalic/thalamic (n = 2), and spinal cord (n = 2). HGAP lesions were T1 hypointense, T2-hyperintense, mostly without diffusion restriction, predominantly peripheral irregular enhancement with central necrosis (n = 3) followed by mixed heterogeneous enhancement (n = 2). Two NF1 mutation carriers showed signs of neurofibromatosis type 1 before HGAP diagnosis, with one diagnosed during HGAP evaluation, strengthening the HGAP-NF1 link, particularly in patients with posterior fossa masses. All tumors were IDH1 wild-type, often with ATRX, CDKN2A/B, and NF1 gene alteration. Six patients underwent surgical resection followed by adjuvant chemoradiation. Six patients were alive, and two died during the last follow-up. Histone H3 mutations were not detected in our cohort, such as the common H3K27M typically seen in diffuse midline gliomas, linked to aggressive clinical behavior and poor prognosis. HGAP lesions may involve the brain or spine and tend to be midline or paramedian in location. Underlying neurofibromatosis type 1 diagnosis or imaging findings are important diagnostic cues.

Exploring prognostic factors and treatment strategies for long-term survival in pleomorphic xanthoastrocytoma patients.

Pleomorphic xanthoastrocytomas (PXA) are rare, accounting for < 1% of all astrocytomas. Literature on the clinical course and treatment outcomes of PXAs is limited. The study aimed to determine prognosis and treatment strategies for PXAs. Patients who had PXAs surgery between 2000-2021 were retrospectively analyzed for demographics and radiological characteristics. Initial and salvage treatment outcomes were recorded. Overall, 40 and 9 patients had grade 2 and 3 PXAs; their 5-year progression-free survival (PFS) rates were 75.8% and 37.0%, respectively (p = 0.003). Univariate analysis revealed that strong T1 enhancement (p = 0.036), infiltrative tumor margins (p < 0.001), peritumoral edema (p = 0.003), WHO grade (p = 0.005), and gross total resection (p = 0.005) affected the PFS. Multivariate analysis revealed that the WHO grade (p = 0.010) and infiltrative tumor margins (p = 0.008) influenced the PFS. The WHO grade (p = 0.027) and infiltrative tumor margins (p = 0.027) also affected the overall survival (OS). Subgroup analysis for grade 2 PXAs revealed no significant associations between adjuvant radiation therapy and the PFS and OS. This study highlighted the heterogeneous nature of PXAs and its impact on patient prognosis. Infiltrative tumor margins emerged as a key prognostic factor. Our findings have emphasized the prognostic relevance of radiological features and the need for larger studies on comprehensive management.

Bilateral thalamic high-grade astrocytomas in an early-adolescent child: A case report.

An early-adolescent girl presented with incoordination, headache, vomiting and dysphonia. MRI brain demonstrated diffuse increased T2 and FLAIR signal in bilateral thalami, consistent with anaplastic astrocytomas. A stereotactic burr-hole biopsy provided frozen tissues sections demonstrating an IDH-1 wildtype astrocytoma (anaplastic grade III according to prior WHO classification 2016-21). Chemoradiotherapy was commenced. Bilateral thalamic high-grade astrocytomas are very rare in the paediatric population and require timely diagnosis and interdisciplinary management. CT and MR imaging help point towards this diagnosis in the correct clinical context.

Resection of an Intradural Intramedullary C7-T1 Tumor: Technical Nuances and Complication Management.

Primary spinal cord tumors are relatively rare, comprising approximately 4%-16% of all tumors originating from the central nervous system. These tumors are anatomically separable into 2 broad categories: intradural intramedullary and intradural extramedullary. Intramedullary tumors are composed predominantly of gliomas (infiltrative astrocytoma) and ependymomas.1-4 The primary treatment approach for these tumors is surgical resection, aiming to preserve neurologic function.5-9 In Video 1, the authors showcase a step-by-step approach for microsurgical resection of a primary spinal ependymoma, with emphasis on microsurgical technique and utility of adjunct equipment, such as intraoperative ultrasound and neuromonitoring.10,11 The patient consented to the procedure.

Comparison of diagnostic performance of radiologist- and AI-based assessments of T2-FLAIR mismatch sign and quantitative assessment using synthetic MRI in the differential diagnosis between astrocytoma, IDH-mutant and oligodendroglioma, IDH-mutant and 1p/19q-codeleted.

PURPOSE: This study aimed to compare assessments by radiologists, artificial intelligence (AI), and quantitative measurement using synthetic MRI (SyMRI) for differential diagnosis between astrocytoma, IDH-mutant and oligodendroglioma, and IDH-mutant and 1p/19q-codeleted and to identify the superior method. METHODS: Thirty-three cases (men, 14; women, 19) comprising 19 astrocytomas and 14 oligodendrogliomas were evaluated. Four radiologists independently evaluated the presence of the T2-FLAIR mismatch sign. A 3D convolutional neural network (CNN) model was trained using 50 patients outside the test group (28 astrocytomas and 22 oligodendrogliomas) and transferred to evaluate the T2-FLAIR mismatch lesions in the test group. If the CNN labeled more than 50% of the T2-prolonged lesion area, the result was considered positive. The T1/T2-relaxation times and proton density (PD) derived from SyMRI were measured in both gliomas. Each quantitative parameter (T1, T2, and PD) was compared between gliomas using the Mann-Whitney U-test. Receiver-operating characteristic analysis was used to evaluate the diagnostic performance. RESULTS: The mean sensitivity, specificity, and area under the curve (AUC) of radiologists vs. AI were 76.3% vs. 94.7%; 100% vs. 92.9%; and 0.880 vs. 0.938, respectively. The two types of diffuse gliomas could be differentiated using a cutoff value of 2290/128 ms for a combined 90th percentile of T1 and 10th percentile of T2 relaxation times with 94.4/100% sensitivity/specificity with an AUC of 0.981. CONCLUSION: Compared to the radiologists' assessment using the T2-FLAIR mismatch sign, the AI and the SyMRI assessments increased both sensitivity and objectivity, resulting in improved diagnostic performance in differentiating gliomas.

A 3-Year-Old Girl with Brain Imaging Findings Suggesting Arachnoid Cyst, and Biopsy Diagnosis of Extra-Axial Multicystic Pilocytic Astrocytoma.

BACKGROUND Arachnoid cysts and pilocytic astrocytomas are distinct intracranial entities with differing clinical presentations, origins, and management strategies. Arachnoid cysts are benign fluid-filled sacs associated with congenital or acquired causes, while pilocytic astrocytomas are low-grade brain tumors, primarily affecting pediatric and young adult populations, originating from astrocytes. However, diagnosing pilocytic astrocytomas can be challenging due to their radiological features, sometimes resembling more common intracranial lesions, such as arachnoid cysts. This case underscores the need for vigilance and a multidisciplinary approach when confronted with neuroimaging findings that diverge from typical patterns. CASE REPORT We present a case of a 3-year-old girl who presented with persistent headaches, vomiting, and difficulty walking. Initial radiological assessment suggested an arachnoid cyst, given the patient's symptoms and imaging characteristics. Subsequently, the patient underwent a craniotomy, with intraoperative findings revealing a cystic lesion without a solid mural nodule, which was excised completely. Postoperatively, histopathological examination confirmed a diagnosis of extra-axial pilocytic astrocytoma. The patient's symptoms resolved, and she was discharged without neurological deficits. CONCLUSIONS Diagnosing extra-axial pilocytic astrocytomas presents challenges, due to their radiological similarities with more common intracranial lesions, like arachnoid cysts. This case underscores the importance of histopathological examination to confirm the diagnosis accurately. Surgical resection remains the primary treatment for extra-axial pilocytic astrocytomas, often resulting in a favorable prognosis.

Development and External Validation of an MRI-based Radiomics Nomogram to Distinguish Circumscribed Astrocytic Gliomas and Diffuse Gliomas: A Multicenter Study.

RATIONALE AND OBJECTIVES: The 5th edition of the World Health Organization classification of tumors of the Central Nervous System (WHO CNS) has introduced the term "diffuse" and its counterpart "circumscribed" to the category of gliomas. This study aimed to develop and validate models for distinguishing circumscribed astrocytic gliomas (CAGs) from diffuse gliomas (DGs). MATERIALS AND METHODS: We retrospectively analyzed magnetic resonance imaging (MRI) data from patients with CAGs and DGs across three institutions. After tumor segmentation, three volume of interest (VOI) types were obtained: VOItumor and peritumor, VOIwhole, and VOIinterface. Clinical and combined models (incorporating radiomics and clinical features) were also established. To address imbalances in training dataset, Synthetic Minority Oversampling Technique was employed. RESULTS: A total of 475 patients (DGs: n = 338, CAGs: n = 137) were analyzed. The VOIinterface model demonstrated the best performance for differentiating CAGs from DGs, achieving an area under the curve (AUC) of 0.806 and area under the precision-recall curve (PRAUC)of 0.894 in the cross-validation set. Using analysis of variance (ANOVA) feature selector and Support Vector Machine (SVM) classifier, seven features were selected. The model achieved an AUC and AUPRC of 0.912 and 0.972 in the internal validation dataset, and 0.897 and 0.930 in the external validation dataset. The combined model, incorporating interface radiomics and clinical features, showed improved performance in the external validation set, with an AUC of 0.94 and PRAUC of 0.959. CONCLUSION: Radiomics models incorporating the peritumoral area demonstrate greater potential for distinguishing CAGs from DGs compared to intratumoral models. These findings may hold promise for evaluating tumor nature before surgery and improving clinical management of glioma patients.

Isolated subependymal giant cell astrocytoma (SEGA) in the absence of clinical tuberous sclerosis: two case reports and literature review.

PURPOSE: Subependymal giant cell astrocytoma (SEGA) is a WHO grade I pediatric glioma arising in 5-15% of patients with tuberous sclerosis (TSC). Rare cases of isolated SEGA without TSC have been described. The etiology, genetic mechanisms, natural history, and response to treatment of these lesions are currently unknown. We describe two such cases of isolated SEGA with follow-up. METHODS: Retrospective review was performed at a single institution to describe the clinical course of pathology-confirmed SEGA in patients with germline testing negative for TSC mutations. RESULTS: Two cases of isolated SEGA were identified. Genetic analysis of the tumor specimen was available for one, which revealed an 18 base pair deletion in TSC1. Both cases were managed with surgical resection, one with preoperative embolization. In spite of a gross total resection, one patient experienced recurrence after three years. Treatment with an mTOR inhibitor led to a significant interval reduction of the mass on follow-up MRI. The patient tolerated the medication well for 6 years and is now off of treatment for 2 years with a stable lesion. CONCLUSION: Cases of SEGA outside of the context of TSC are exceedingly rare, with only 48 cases previously described. The genetic mechanisms and treatment response of these lesions are poorly understood. To date, these lesions appear to respond well to mTOR inhibitors and may behave similarly to SEGAs associated with TSC. However, given that experience is extremely limited, these cases should be followed long term to better understand their natural history and treatment response.

Preoperative Discrimination of CDKN2A/B Homozygous Deletion Status in Isocitrate Dehydrogenase-Mutant Astrocytoma: A Deep Learning-Based Radiomics Model Using MRI.

BACKGROUND: Cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) homozygous deletion has been verified as an independent and critical biomarker of negative prognosis and short survival in isocitrate dehydrogenase (IDH)-mutant astrocytoma. Therefore, noninvasive and accurate discrimination of CDKN2A/B homozygous deletion status is essential for the clinical management of IDH-mutant astrocytoma patients. PURPOSE: To develop a noninvasive, robust preoperative model based on MR image features for discriminating CDKN2A/B homozygous deletion status of IDH-mutant astrocytoma. STUDY TYPE: Retrospective. POPULATION: Two hundred fifty-one patients: 107 patients with CDKN2A/B homozygous deletion and 144 patients without CDKN2A/B homozygous deletion. FIELD STRENGTH/SEQUENCE: 3.0 T/1.5 T: Contrast-enhanced T1-weighted spin-echo inversion recovery sequence (CE-T1WI) and T2-weighted fluid-attenuation spin-echo inversion recovery sequence (T2FLAIR). ASSESSMENT: A total of 1106 radiomics and 1000 deep learning features extracted from CE-T1WI and T2FLAIR were used to develop models to discriminate the CDKN2A/B homozygous deletion status. Radiomics models, deep learning-based radiomics (DLR) models and the final integrated model combining radiomics features with deep learning features were developed and compared their preoperative discrimination performance. STATISTICAL TESTING: Pearson chi-square test and Mann Whitney U test were used for assessing the statistical differences in patients' clinical characteristics. The Delong test compared the statistical differences of receiver operating characteristic (ROC) curves and area under the curve (AUC) of different models. The significance threshold is P < 0.05. RESULTS: The final combined model (training AUC = 0.966; validation AUC = 0.935; test group: AUC = 0.943) outperformed the optimal models based on only radiomics or DLR features (training: AUC = 0.916 and 0.952; validation: AUC = 0.886 and 0.912; test group: AUC = 0.862 and 0.902). DATA CONCLUSION: Whether based on a single sequence or a combination of two sequences, radiomics and DLR models have achieved promising performance in assessing CDKN2A/B homozygous deletion status. However, the final model combining both deep learning and radiomics features from CE-T1WI and T2FLAIR outperformed the optimal radiomics or DLR model. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Nomograms Based on MRI Radiomics for Differential Diagnosis and Predicting BRAFV600E Expression in Pleomorphic Xanthoastrocytoma and Ganglioglioma.

RATIONALE AND OBJECTIVES: This study was designed to investigate the value of nomograms based on MRI radiomics and clinical semantic features in identifying pleomorphic xanthoastrocytoma (PXA) and ganglioglioma (GG) as well as predicting BRAFV600E expression. MATERIALS AND METHODS: This study included 265 patients histologically diagnosed with PXA (n = 113) and GG (n = 152). T1WI, T2WI, and CET1 sequences were utilized to extract radiomics features. Univariate analysis, Spearman correlation analysis, and the least absolute shrinkage and selection operator were used for dimensionality reduction and feature selection. Following this, logistic regression was utilized to establish the radiomics model. Univariate and multivariate analyses of clinical semantic features were applied, and clinical models were constructed. The nomograms were established by merging radiomics and clinical features. Furthermore, ROC curve analysis was used for examining the model performance, whereas the decision curve analysis (DCA) examined the clinical utility of the nomograms. RESULTS: Nomograms achieved the best predictive efficacy compared to clinical and radiomics models alone. Concerning the differentiation between PXA and GG, the area under the curve (AUC) values of the nomogram were 0.879 (0.828-0.930) and 0.887 (0.805-0.969) for the training and testing cohorts, respectively. For predicting BRAFV600E expression, the AUC values of the nomogram were 0.873 (0.811-0.936) and 0.851 (0.740-0.963) for the training and testing cohorts, respectively. DCA confirmed the clinical utility of the nomograms. CONCLUSION: Nomograms based on radiomics and clinical semantic features were noninvasive tools for differential diagnosis of PXA and GG and predicting BRAFV600E expression, which may be helpful for assessing patient prognosis and developing individualized treatment strategies.

A novel MRI-based deep learning networks combined with attention mechanism for predicting CDKN2A/B homozygous deletion status in IDH-mutant astrocytoma.

OBJECTIVES: To develop a high-accuracy MRI-based deep learning method for predicting cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) homozygous deletion status in isocitrate dehydrogenase (IDH)-mutant astrocytoma. METHODS: Multiparametric brain MRI data and corresponding genomic information of 234 subjects (111 positives for CDKN2A/B homozygous deletion and 123 negatives for CDKN2A/B homozygous deletion) were obtained from The Cancer Imaging Archive (TCIA) and The Cancer Genome Atlas (TCGA) respectively. Two independent multi-sequence networks (ResFN-Net and FN-Net) are built on the basis of ResNet and ConvNeXt network combined with attention mechanism to classify CDKN2A/B homozygous deletion status using MR images including contrast-enhanced T1-weighted imaging (CE-T1WI) and T2-weighted imaging (T2WI). The performance of the network is summarized by three-way cross-validation; ROC analysis is also performed. RESULTS: The average cross-validation accuracy (ACC) of ResFN-Net is 0.813. The average cross-validation area under curve (AUC) of ResFN-Net is 0.8804. The average cross-validation ACC and AUC of FN-Net is 0.9236 and 0.9704, respectively. Comparing all sequence combinations of the two networks (ResFN-Net and FN-Net), the sequence combination of CE-T1WI and T2WI performed the best, and the ACC and AUC were 0.8244, 0.8975 and 0.8971, 0.9574, respectively. CONCLUSIONS: The FN-Net deep learning networks based on ConvNeXt network achieved promising performance for predicting CDKN2A/B homozygous deletion status of IDH-mutant astrocytoma. CLINICAL RELEVANCE STATEMENT: A novel deep learning network (FN-Net) based on preoperative MRI was developed to predict the CDKN2A/B homozygous deletion status. This network has the potential to be a practical tool for the noninvasive characterization of CDKN2A/B in glioma to support personalized classification and treatment planning. KEY POINTS: • CDKN2A/B homozygous deletion status is an important marker for glioma grading and prognosis. • An MRI-based deep learning approach was developed to predict CDKN2A/B homozygous deletion status. • The predictive performance based on ConvNeXt network was better than that of ResNet network.

The use of sodium MRI in the diagnosis of an anaplastic astrocytoma during immunotherapy: a case report.

Gliomas in the pediatric population are targeted with immune-modulating therapies. The gold standard imaging modality for diagnosis and monitoring treatment response is magnetic resonance imaging (MRI); however, the complex post-therapy-induced changes can make treatment response assessment difficult. These include radiation necrosis, pseudoresponse, and pseudoprogression, as well as more complex responses in the setting of immunotherapy. We report a case of an 11-year-old male with a supratentorial astrocytoma (WHO grade 3) that underwent treatment with immunotherapy. There was a clinical concern for progression due to increased fluid-attenuated inversion recovery (FLAIR) hyperintensity at the site of the primary neoplasm during immunotherapy. However, the Sodium (23Na) MRI continued demonstrating decreased total sodium concentrations, supporting pseudoprogression over true progression, which was confirmed clinicaly. This case reports the capability of 23Na MRI to differentiate between progression, recurrence, and other posttreatment changes.