68 Ga-DOTATATE and 18 F-FDG PET Imaging of a Rare Chordoid Meningioma With Intracranial Recurrence and Extracranial Metastases.

ABSTRACT: Chordoid meningiomas, rare meningioma variants, are characterized by their histopathological features and clinical behavior resembling that of other chondroid/myxoid neoplasms. We present a case of pathology-proven chordoid meningioma imaged with both 68 Ga-DOTATATE and 18 F-FDG PET images during a complicated postoperative course with multiple episodes of local recurrence and, ultimately, extracranial metastasis. This case underscores the aggressive behavior of chordoid meningiomas while highlighting how molecular imaging plays an important role in clinical monitoring and guidance of management.

Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm.

BACKGROUND AND OBJECTIVE: Glioblastoma (GBM) is one of the most aggressive and lethal human cancers. Intra-tumoral genetic heterogeneity poses a significant challenge for treatment. Biopsy is invasive, which motivates the development of non-invasive, MRI-based machine learning (ML) models to quantify intra-tumoral genetic heterogeneity for each patient. This capability holds great promise for enabling better therapeutic selection to improve patient outcome. METHODS: We proposed a novel Weakly Supervised Ordinal Support Vector Machine (WSO-SVM) to predict regional genetic alteration status within each GBM tumor using MRI. WSO-SVM was applied to a unique dataset of 318 image-localized biopsies with spatially matched multiparametric MRI from 74 GBM patients. The model was trained to predict the regional genetic alteration of three GBM driver genes (EGFR, PDGFRA and PTEN) based on features extracted from the corresponding region of five MRI contrast images. For comparison, a variety of existing ML algorithms were also applied. Classification accuracy of each gene were compared between the different algorithms. The SHapley Additive exPlanations (SHAP) method was further applied to compute contribution scores of different contrast images. Finally, the trained WSO-SVM was used to generate prediction maps within the tumoral area of each patient to help visualize the intra-tumoral genetic heterogeneity. RESULTS: WSO-SVM achieved 0.80 accuracy, 0.79 sensitivity, and 0.81 specificity for classifying EGFR; 0.71 accuracy, 0.70 sensitivity, and 0.72 specificity for classifying PDGFRA; 0.80 accuracy, 0.78 sensitivity, and 0.83 specificity for classifying PTEN; these results significantly outperformed the existing ML algorithms. Using SHAP, we found that the relative contributions of the five contrast images differ between genes, which are consistent with findings in the literature. The prediction maps revealed extensive intra-tumoral region-to-region heterogeneity within each individual tumor in terms of the alteration status of the three genes. CONCLUSIONS: This study demonstrated the feasibility of using MRI and WSO-SVM to enable non-invasive prediction of intra-tumoral regional genetic alteration for each GBM patient, which can inform future adaptive therapies for individualized oncology.

Virtual Planning and Augmented Reality-Guided Microsurgical Resection of a Frontal Arteriovenous Malformation.

Arteriovenous malformations (AVMs) are complex vascular lesions that can pose significant risk for spontaneous hemorrhage, seizures, and symptoms related to ischemia and venous hypertension.1 Microsurgical management of AVMs requires a deep understanding of the surrounding anatomy and precise identification of the lesion characteristics. We demonstrate the use of augmented reality in the localization of arterial feeders and draining veins in relation to bordering normal structures (Video 1). A 66-year-old man presented with several episodes of severe right frontal headaches. Magnetic resonance imaging revealed an AVM along the right frontal pole. Subsequent computed tomography angiography demonstrated arterial supply from the right anterior cerebral artery with venous drainage to the superior sagittal sinus. Due to the size, noneloquent location, and superficial pattern of venous drainage, the patient elected to proceed with microsurgery. A virtual planning platform was used in preparation for surgery. Augmented reality integrated with neuronavigation was used during microsurgical resection. Postoperative angiography showed complete resection of the AVM. The patient was discharged home on postoperative day 3 with no complications. He remains neurologically well at 4 months of follow-up.

Microsurgical Treatment of Pineal Tumors: Anatomy and Techniques.

Pineal region tumors are challenging lesions in terms of surgical accessibility and removal.1 The complexity is compounded by the infrequency and heterogeneity of pineal neoplasms.2,3 In Video 1, we present the case of a 39-year-old woman who presented with progressive headaches and vision impairment. She underwent microsurgical resection for a pineal parenchymal tumor of intermediate differentiation. We discuss the rationale, risks, and benefits of treatment for this patient, as well as provide a detailed overview of the alternative approaches that may be considered. Additionally, we discuss the unique anatomic considerations for each approach and include a virtual reality-compatible 3-dimensional fly-through to highlight the relationship between the tumor and relevant venous anatomy. The patient tolerated the procedure well with excellent neurologic outcome, and her follow-up imaging showed no evidence of tumor recurrence.

The clinical presentation of PIT1 positive pituitary neuroendocrine tumor immunonegative for growth hormone, prolactin, and thyroid stimulating hormone with analysis of clinical and immunostaining dissociation.

BACKGROUND: PIT1 is a pituitary transcription factor that is associated with either growth hormone (GH), prolactin (PRL), or thyroid-stimulating hormone (TSH) production. However, PIT1-positive pituitary neuroendocrine tumors (PitNETs) are occasionally immunonegative for GH, PRL, and TSH. This paper describes the clinical presentation of PIT1 positive however immunonegative PitNETs. METHODS: We conducted a retrospective analysis, identifying 228 PIT1-positive PitNET patients between 2017 and 2022. Out of these, ten (4%) tested negative for GH, PRL, and TSH. Functioning PitNETs were defined as those causing hormonal excess symptoms or hormonal overproduction. RESULTS: As for 10 patients immunonegative for all three hormones however PIT1-positive, the mean ( ± standard deviation) age was 46 ± 13 years with 70% women. Six patients exhibited signs of excess GH or PRL, and three had visual problems. Additionally, one patient had secondary hypothyroidism and adrenal insufficiency resulting from the mass effect. All tumors were macroadenoma, with a median volume of 2.1 cm3 (range, 0.8-17.5 cm3). Gross total resection was attained in six patients by trans-sphenoidal surgery. Postoperatively, eight patients experienced clinical improvement: three in vision, two in amenorrhea, two in headache, and one in acromegaly symptoms. Biochemical improvement was observed in six patients, with all experiencing remission in hormonal excess and one showing improvement in secondary hypothyroidism. Stereotactic radiosurgery was performed in three patients. CONCLUSIONS: Patients with functioning PitNETs may exhibit PIT1 staining without GH, PRL, or TSH staining. Hormonally active tumors exist in this patient population; therefore, close endocrine follow-up is necessary despite the lack of staining for GH, PRL, and TSH.

Extent of Surgical Resection as a Predictor of Tumor Progression in Skull Base Chordomas: A Multicenter Volumetric Analysis.

INTRODUCTION: Skull-base chordomas are aggressive tumors with a propensity for recurrence/progression. Even with standard of care (SoC), 5-year recurrence rates are variable (19%-54%). This high recurrence/progression rate correlates with increased morbidity and mortality. We sought to analyze a multicenter cohort of skull base chordomas to identify predictors of progression in patients receiving SoC. METHODS: The [Blinded]-Neurosurgery data registry was queried for skull base chordomas treated from 2008-2020. Patients with the histopathologic diagnosis of chordoma were included. The cohort was composed of patients with preoperative and postoperative magnetic resonance imaging. Tumor volume and radiologic characteristics were obtained from axial T2 sequences using a Digital Imaging and Communications in Medicine viewer. Survival analysis was performed using Kaplan-Meier method, and time-to-event multivariate regression was performed to identify independent predictors of progression. RESULTS: The cohort included 195 patients, of which 66 patients met inclusion criteria; median age was 44, and 28 (42%) were females. Fifty-four (82%) received SoC, 7 (11%) resection only, and 5 (8%) radiotherapy only. Median preoperative and postoperative tumor volumes were 11.55 cm3 (0.33-54.89) and 0.34 cm3 (0-42.52), respectively. Recurrence rate with SoC was 37%. Postoperative tumor volume (P = 0.010) correlated with progression. A postoperative volume of >4.9 cm3 (P = 0.044), ≤81.3% of tumor resection (P = 0.02), and lower-clivus location (P < 0.005) correlated with decreased time to progression. CONCLUSIONS: Skull base chordomas can be challenging to resect. Even though maximal resection and radiotherapy improve rate of tumor progression, many of these lesions eventually recur. We have identified a postoperative tumor volume of ≥4.9 cm3 and extent of resection of ≤81.3% in this cohort as predictors of progression in patients receiving SoC.

Image-localized biopsy mapping of brain tumor heterogeneity: A single-center study protocol.

Brain cancers pose a novel set of difficulties due to the limited accessibility of human brain tumor tissue. For this reason, clinical decision-making relies heavily on MR imaging interpretation, yet the mapping between MRI features and underlying biology remains ambiguous. Standard (clinical) tissue sampling fails to capture the full heterogeneity of the disease. Biopsies are required to obtain a pathological diagnosis and are predominantly taken from the tumor core, which often has different traits to the surrounding invasive tumor that typically leads to recurrent disease. One approach to solving this issue is to characterize the spatial heterogeneity of molecular, genetic, and cellular features of glioma through the intraoperative collection of multiple image-localized biopsy samples paired with multi-parametric MRIs. We have adopted this approach and are currently actively enrolling patients for our 'Image-Based Mapping of Brain Tumors' study. Patients are eligible for this research study (IRB #16-002424) if they are 18 years or older and undergoing surgical intervention for a brain lesion. Once identified, candidate patients receive dynamic susceptibility contrast (DSC) perfusion MRI and diffusion tensor imaging (DTI), in addition to standard sequences (T1, T1Gd, T2, T2-FLAIR) at their presurgical scan. During surgery, sample anatomical locations are tracked using neuronavigation. The collected specimens from this research study are used to capture the intra-tumoral heterogeneity across brain tumors including quantification of genetic aberrations through whole-exome and RNA sequencing as well as other tissue analysis techniques. To date, these data (made available through a public portal) have been used to generate, test, and validate predictive regional maps of the spatial distribution of tumor cell density and/or treatment-related key genetic marker status to identify biopsy and/or treatment targets based on insight from the entire tumor makeup. This type of methodology, when delivered within clinically feasible time frames, has the potential to further inform medical decision-making by improving surgical intervention, radiation, and targeted drug therapy for patients with glioma.

Integrated molecular and multiparametric MRI mapping of high-grade glioma identifies regional biologic signatures.

Sampling restrictions have hindered the comprehensive study of invasive non-enhancing (NE) high-grade glioma (HGG) cell populations driving tumor progression. Here, we present an integrated multi-omic analysis of spatially matched molecular and multi-parametric magnetic resonance imaging (MRI) profiling across 313 multi-regional tumor biopsies, including 111 from the NE, across 68 HGG patients. Whole exome and RNA sequencing uncover unique genomic alterations to unresectable invasive NE tumor, including subclonal events, which inform genomic models predictive of geographic evolution. Infiltrative NE tumor is alternatively enriched with tumor cells exhibiting neuronal or glycolytic/plurimetabolic cellular states, two principal transcriptomic pathway-based glioma subtypes, which respectively demonstrate abundant private mutations or enrichment in immune cell signatures. These NE phenotypes are non-invasively identified through normalized K2 imaging signatures, which discern cell size heterogeneity on dynamic susceptibility contrast (DSC)-MRI. NE tumor populations predicted to display increased cellular proliferation by mean diffusivity (MD) MRI metrics are uniquely associated with EGFR amplification and CDKN2A homozygous deletion. The biophysical mapping of infiltrative HGG potentially enables the clinical recognition of tumor subpopulations with aggressive molecular signatures driving tumor progression, thereby informing precision medicine targeting.

Immunohistochemical markers predicting long-term recurrence following clival and spinal chordoma resection: a multicenter study.

OBJECTIVE: Chordomas are rare tumors from notochordal remnants and account for 1%-4% of all primary bone malignancies, often arising from the clivus and sacrum. Despite margin-negative resection and postoperative radiotherapy, chordomas often recur. Further, immunohistochemical (IHC) markers have not been assessed as predictive of chordoma recurrence. The authors aimed to identify the IHC markers that are predictive of postoperative long-term (≥ 1 year) chordoma recurrence by using trained multiple tree-based machine learning (ML) algorithms. METHODS: The authors reviewed the records of patients who had undergone treatment for clival and spinal chordomas between January 2017 and June 2021 across the Mayo Clinic enterprise (Minnesota, Florida, and Arizona). Demographics, type of treatment, histopathology, and other relevant clinical factors were abstracted from each patient record. Decision tree and random forest classifiers were trained and tested to predict long-term recurrence based on unseen data using an 80/20 split. RESULTS: One hundred fifty-one patients diagnosed and treated for chordomas were identified: 58 chordomas of the clivus, 48 chordomas of the mobile spine, and 45 chordomas sacrococcygeal in origin. Patients diagnosed with cervical chordomas were the oldest among all groups (58 ± 14 years, p = 0.009). Most patients were male (n = 91, 60.3%) and White (n = 139, 92.1%). Most patients underwent resection with or without radiation therapy (n = 129, 85.4%). Subtotal resection followed by radiation therapy (n = 51, 33.8%) was the most common treatment modality, followed by gross-total resection then radiation therapy (n = 43, 28.5%). Multivariate analysis showed that S100 and pan-cytokeratin are more likely to predict the increase in the risk of postoperative recurrence (OR 3.67, 95% CI 1.09-12.42, p= 0.03; and OR 3.74, 95% CI 0.05-2.21, p = 0.02, respectively). In the decision tree analysis, a clinical follow-up > 1897 days was found in 37% of encounters and a 90% chance of being classified for recurrence (accuracy = 77%). Random forest analysis (n = 500 trees) showed that patient age, type of surgical treatment, location of tumor, S100, pan-cytokeratin, and EMA are the factors predicting long-term recurrence. CONCLUSIONS: The IHC and clinicopathological variables combined with tree-based ML tools successfully demonstrated a high capacity to identify recurrence patterns with an accuracy of 77%. S100, pan-cytokeratin, and EMA were the IHC drivers of recurrence. This shows the power of ML algorithms in analyzing and predicting outcomes of rare conditions of a small sample size.

Image-based models of T-cell distribution identify a clinically meaningful response to a dendritic cell vaccine in patients with glioblastoma.

BACKGROUND: Glioblastoma is an extraordinarily heterogeneous tumor, yet the current treatment paradigm is a "one size fits all" approach. Hundreds of glioblastoma clinical trials have been deemed failures because they did not extend median survival, but these cohorts are comprised of patients with diverse tumors. Current methods of assessing treatment efficacy fail to fully account for this heterogeneity. METHODS: Using an image-based modeling approach, we predicted T-cell abundance from serial MRIs of patients enrolled in the dendritic cell (DC) vaccine clinical trial. T-cell predictions were quantified in both the contrast-enhancing and non-enhancing regions of the imageable tumor, and changes over time were assessed. RESULTS: A subset of patients in a DC vaccine clinical trial, who had previously gone undetected, were identified as treatment responsive and benefited from prolonged survival. A mere two months after initial vaccine administration, responsive patients had a decrease in model-predicted T-cells within the contrast-enhancing region, with a simultaneous increase in the T2/FLAIR region. CONCLUSIONS: In a field that has yet to see breakthrough therapies, these results highlight the value of machine learning in enhancing clinical trial assessment, improving our ability to prospectively prognosticate patient outcomes, and advancing the pursuit towards individualized medicine.

Current Role of Endoscopic Endonasal Approach for Craniopharyngiomas: A 10-Year Systematic Review and Meta-Analysis Comparison with the Open Transcranial Approach.

In recent years, the endoscopic endonasal approach (EEA) for craniopharyngiomas has proven to be a safe option for extensive tumor resection, with minimal or no manipulation of the optic nerves and excellent visualization of the superior hypophyseal branches when compared to the Transcranial Approach (TCA). However, there is an ongoing debate regarding the criteria for selecting different approaches. To explore the current results of EEA and discuss its role in the management of craniopharyngiomas, we performed MEDLINE, Embase, and LILACS searches from 2012 to 2022. Baseline characteristics, the extent of resection, and clinical outcomes were evaluated. Statistical analysis was performed through an X2 and Fisher exact test, and a comparison between quantitative variables through a Kruskal-Wallis and verified with post hoc Bonferroni. The tumor volume was similar in both groups (EEA 11.92 cm3, -TCA 13.23 cm3). The mean follow-up in months was 39.9 for EEA and 43.94 for TCA, p = 0.76). The EEA group presented a higher visual improvement rate (41.96% vs. 25% for TCA, p < 0.0001, OR 7.7). Permanent DI was less frequent with EEA (29.20% vs. 67.40% for TCA, p < 0.0001, OR 0.2). CSF Leaks occurred more frequently with EEA (9.94% vs. 0.70% for TCA, p < 0.0001, OR 15.8). Recurrence rates were lower in the EEA group (EEA 15.50% vs. for TCA 21.20%, p = 0.04, OR 0.7). Our results demonstrate that, in selected cases, EEA for resection of craniopharyngiomas is associated with better results regarding visual preservation and extent of tumor resection. Postoperative CSF leak rates associated with EEA have improved compared to the historical series. The decision-making process should consider each person's characteristics; however, it is noticeable that recent data regarding EEA justify its widespread application as a first-line approach in centers of excellence for skull base surgery.

Cerebrospinal Venous Fistula Presenting with Cognitive Decline: Systematic Literature Review and Report of Two Cases.

OBJECTIVE: A cerebrospinal fluid (CSF) venous fistula (CVF) is an aberrant connection between the subarachnoid space and a vein resulting in CSF loss. The presentation and management of CVF with cognitive decline is incompletely understood. METHODS: A systematic review was completed following the PRISMA guidelines. Articles that included at least 1 case of imaging-confirmed CVF with details on patient treatment were included. A separate review of cases of patients with spontaneous intracranial hypotension (SIH) with frontotemporal dementia (FTD) or dementia symptoms was also completed. RESULTS: Ten CVF articles (69 patients; average age, 51.5 years) and 5 SIH with FTD or dementia articles (n = 41; average age, 55.9 years) were identified. Only 1 patients with CVF with cognitive abnormalities was identified. The most common symptom was headache in both reviews. Brain sag was identified in all patients, whereas CSF leak was identified in only 2 patients with SIH with FTD or dementia (4.9%). An epidural blood or fibrin glue patch was used in all patients with CVF and in 33 patients with SIH with FTD or dementia. Fifty-five patients with CVF (79.7%) and 27 patients with SIH with FTD or dementia (65.9%) had surgery. CONCLUSIONS: The 2 cases and literature reviews show the difficulty in diagnosis and treatment of CVF with cognitive decline. Novel imaging techniques should be used in patients with cognitive decline in whom a CSF leak is suspected. Transvenous embolization or surgery should be considered before patching for treatment of CVF-induced brain sag and resulting dementia.