Differential kinetics of α-[11C]methyl-l-tryptophan on PET in low-grade brain tumors

OBJECTIVEResection of brain tumors may lead to new-onset seizures but may also reduce seizure rates in patients presenting with seizures. Seizures are seen at presentation in about 24% of patients with brain tumors. For lesional epilepsy in general, early resection is associated with improved seizure control. However, the literature is limited regarding the occurrence of new-onset postoperative seizures, or rates of seizure control in those presenting with seizures, following resections of extratemporal low-grade gliomas (LGGs) in children.METHODSData were collected retrospectively from 4 large tertiary centers for children (< 18 years of age) who underwent resection of a supratentorial extratemporal (STET) LGG. The patients were divided into 4 groups based on preoperative seizure history: no seizures, up to 2 seizures, more than 2 seizures, and uncontrolled or refractory epilepsy. The authors analyzed the postoperative occurrence of seizures and the need for antiepileptic drugs (AEDs) over time for the various subgroups.RESULTSThe study included 98 children. Thirty patients had no preoperative seizures, 18 had up to 2, 16 had more than 2, and 34 had refractory or uncontrolled epilepsy. The risk for future seizures was higher if the patient had seizures within 1 month of surgery. The risk for new-onset seizures among patients with no seizures prior to surgery was low. The rate of seizures decreased over time for children with uncontrolled or refractory seizures. The need for AEDs was higher in the more active preoperative seizure groups; however, it decreased with time.CONCLUSIONSThe resection of STET LGGs in children is associated with a low rate of postoperative new-onset epilepsy. For children with preoperative seizures, even with uncontrolled epilepsy, most have a significant improvement in the seizure activity, and many may be weaned off their AEDs.

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The integration of metabolic imaging in stereotactic procedures including radiosurgery: a review

Journal of Neurosurgery ◽

10.3171/jns.2002.97.supplement_5.0542 ◽

2002 ◽

Vol 97 ◽

pp. 542-550 ◽

Cited By ~ 35

Author(s):

Marc Levivier ◽

David Wikler ◽

Nicolas Massager ◽

Philippe David ◽

Daniel Devriendt ◽

...

Keyword(s):

Positron Emission Tomography ◽

Brain Tumors ◽

Treatment Planning ◽

Target Volume ◽

Emission Tomography ◽

Low Grade ◽

Content Type ◽

Positron Emission ◽

Pet Scanning ◽

Fine Print

Object. The authors review their experience with the clinical development and routine use of positron emission tomography (PET) during stereotactic procedures, including the use of PET-guided gamma knife radiosurgery (GKS). Methods. Techniques have been developed for the routine use of stereotactic PET, and accumulated experience using PET-guided stereotactic procedures over the past 10 years includes more than 150 stereotactic biopsies, 43 neuronavigation procedures, and 34 cases treated with GKS. Positron emission tomography—guided GKS was performed in 24 patients with primary brain tumors (four pilocytic astrocytomas, five low-grade astrocytomas or oligodendrogliomas, seven anaplastic astrocytomas or ependymomas, five glioblastomas, and three neurocytomas), five patients with metastases (single or multiple lesions), and five patients with pituitary adenomas. Conclusions. Data obtained with PET scanning can be integrated with GKS treatment planning, enabling access to metabolic information with high spatial accuracy. Positron emission tomography data can be successfully combined with magnetic resonance imaging data to provide specific information for defining the target volume for the radiosurgical treatment in patients with recurrent brain tumors, such as glioma, metastasis, and pituitary adenoma. This approach is particularly useful for optimizing target selection for infiltrating or ill-defined brain lesions. The use of PET scanning contributed data in 31 cases (93%) and information that was specifically utilized to adapt the target volume in 25 cases (74%). It would seem that the integration of PET data into GKS treatment planning may represent an important step toward further developments in radiosurgery: this approach provides additional information that may open new perspectives for the optimization of the treatment of brain tumors.

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BIOM-62 SENSITIVE DETECTION AND DISCRIMINATION OF INTRACRANIAL TUMORS BY BLOOD

Neuro-Oncology ◽

10.1093/neuonc/noaa215.059 ◽

2020 ◽

Vol 22 (Supplement_2) ◽

pp. ii15-ii15

Author(s):

Farshad Nassiri ◽

Ankur Chakravarthy ◽

Shengrui Feng ◽

Roxana Shen ◽

Romina Nejad ◽

...

Keyword(s):

Dna Methylation ◽

Brain Tumors ◽

Model Performance ◽

High Sensitivity ◽

Circulating Tumor Dna ◽

Low Grade ◽

Learning Approaches ◽

Intracranial Tumors ◽

Cell Of Origin ◽

Tumor Dna

Abstract BACKGROUND The diagnosis of intracranial tumors relies on tissue specimens obtained by invasive surgery. Non-invasive diagnostic approaches, particularly for patients with brain tumours, provide an opportunity to avoid surgery and mitigate unnecessary risk to patients. We reasoned that DNA methylation profiles of circulating tumor DNA in blood can be used as a clinically useful biomarker for patients with brain tumors, given the specificity of DNA methylation profiles for cell-of-origin. METHODS We generated methylation profiles on the plasma of 608 patients with cancer (219 intracranial, 388 extracranial) and 60 healthy controls using a cell-free methylated DNA immunoprecipitation combined with deep sequencing (cfMeDIP-seq) approach. Using machine-learning approaches we generated and evaluated models to distinguish brain tumors from extracranial cancers that may metastasize to the brain, as well as additional models to discriminate common brain tumors included in the differential diagnosis of solitary extra-axial and intra-axial tumors. RESULTS We observed high sensitivity and discriminative capacity for our models to distinguish gliomas from other cancerous and healthy patients (AUC=0.99, 95%CI 0.96–1), with similar performance in IDH mutant and wildtype gliomas as well as in lower- and high-grade gliomas. Excluding non-malignant contributors to plasma methylation did not change model performance (AUC=0.982, 95%CI 0.93–1). Models generated to discriminate intracranial tumors from each other also demonstrated high accuracy for common extra-axial tumors (AUCmeningioma=0.89, 95%CI 0.80–0.97; AUChemangiopericytoma=0.95, 95%CI 0.73–1) as well as intra-axial tumors ranging from low-grade indolent glial-neuronal tumors (AUC 0.93, 95%CI 0.80 – 1) to diffuse intra-axial gliomas with distinct molecular composition (AUCIDH-mutant glioma = 0.82, 95%CI 0.66 -0.98; AUCIDH-wildtype-glioma = 0.71, 95%CI 0.53 – 0.9). Plasma cfMeDIP-seq signals originated from corresponding tumor tissue DNA methylation signals (r=0.37, p< 2.2e-16). CONCLUSIONS These results demonstrate the potential for cfMeDIP-seq profiles to not only detect circulating tumor DNA, but to accurately discriminate common intracranial tumors that share cell-of-origin lineages.

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NCOG-42. INITIAL PRESENTATION AND OUTPATIENT VISIT COMPLIANCE OF INMATES WITH BRAIN TUMORS

Neuro-Oncology ◽

10.1093/neuonc/noaa215.580 ◽

2020 ◽

Vol 22 (Supplement_2) ◽

pp. ii138-ii138

Author(s):

Iyad Alnahhas ◽

Appaji Rayi ◽

Yasmeen Rauf ◽

Shirley Ong ◽

Pierre Giglio ◽

...

Keyword(s):

Brain Tumors ◽

Civil Liberties ◽

Delayed Diagnosis ◽

Low Grade ◽

Small Series ◽

Initial Symptoms ◽

The Ohio State University ◽

American Civil Liberties Union ◽

Lost To Follow Up

Abstract INTRODUCTION While advocacy for inmates with cancer has recently gained momentum, little is known about management of brain tumors in inmates. Delays in acknowledging or recognizing nonspecific initial symptoms can lead to delayed diagnosis and treatment. Inmates with cancer are reported to either be ignored or receive substandard care due in part to cost or logistics (American Civil Liberties Union; ASCO Post 2018). METHODS In this retrospective study, we identified inmates with gliomas seen in the Ohio State University Neuro-oncology Center between 1/1/2010-4/20/2019. RESULTS Twelve patients were identified. Median age at presentation was 39.5 years (range 28-62). Eleven patients were Caucasian and one was African American. Diagnoses included glioblastoma (GBM) (n=6), anaplastic astrocytoma (n=1), anaplastic oligodendroglioma (n=1), low-grade astrocytoma (n=3) and anaplastic pleomorphic xanthroastrocytoma (n=1). Patients were more likely to present early after seizures or focal neurologic deficits (9/12) than after headaches alone. Patients with GBM started RT 12-71 days after surgery (median 34.5). One patient’s post-RT MRI was delayed by a month and another with GBM had treatment held after 4 cycles of adjuvant temozolomide (TMZ) due to “incarceration issues”. For one patient who received adjuvant TMZ, the facility failed to communicate with the primary team throughout treatment. Two patients suffered significant nausea while on chemotherapy due to inability to obtain ondansetron in prison, or due to wrong timing. 7/12 (58%) patients were lost to follow-up for periods of 3-15 months during treatment. Three patients refused adjuvant treatment. CONCLUSIONS Although this is a small series, our results highlight the inequities and challenges faced by inmates with gliomas who are more likely to forego treatments or whose incarceration prevents them from keeping appropriate treatment and follow-up schedules. Additional studies are needed to define and address these deficiencies in the care of inmates with brain tumors and other cancers.

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Amide proton transfer weighted (APTw) imaging based radiomics allows for the differentiation of gliomas from metastases

Scientific Reports ◽

10.1038/s41598-021-85168-8 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Elisabeth Sartoretti ◽

Thomas Sartoretti ◽

Michael Wyss ◽

Carolin Reischauer ◽

Luuk van Smoorenburg ◽

...

Keyword(s):

Machine Learning ◽

Random Forest ◽

Brain Tumors ◽

Proton Transfer ◽

Multilayer Perceptron ◽

Random Forest Classifier ◽

Amide Proton ◽

Low Grade ◽

Who Grade ◽

Amide Proton Transfer

AbstractWe sought to evaluate the utility of radiomics for Amide Proton Transfer weighted (APTw) imaging by assessing its value in differentiating brain metastases from high- and low grade glial brain tumors. We retrospectively identified 48 treatment-naïve patients (10 WHO grade 2, 1 WHO grade 3, 10 WHO grade 4 primary glial brain tumors and 27 metastases) with either primary glial brain tumors or metastases who had undergone APTw MR imaging. After image analysis with radiomics feature extraction and post-processing, machine learning algorithms (multilayer perceptron machine learning algorithm; random forest classifier) with stratified tenfold cross validation were trained on features and were used to differentiate the brain neoplasms. The multilayer perceptron achieved an AUC of 0.836 (receiver operating characteristic curve) in differentiating primary glial brain tumors from metastases. The random forest classifier achieved an AUC of 0.868 in differentiating WHO grade 4 from WHO grade 2/3 primary glial brain tumors. For the differentiation of WHO grade 4 tumors from grade 2/3 tumors and metastases an average AUC of 0.797 was achieved. Our results indicate that the use of radiomics for APTw imaging is feasible and the differentiation of primary glial brain tumors from metastases is achievable with a high degree of accuracy.

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Predicting Neurocognitive Function (NCF) Impairment following Fractionated Stereotactic Radiotherapy (FSRT) for Benign or Low-Grade Adult Brain Tumors

International Journal of Radiation Oncology*Biology*Physics ◽

10.1016/j.ijrobp.2011.06.1751 ◽

2011 ◽

Vol 81 (2) ◽

pp. S285-S286 ◽

Cited By ~ 1

Author(s):

V. Gondi ◽

B.P. Hermann ◽

M.P. Mehta ◽

W.A. Tome

Keyword(s):

Brain Tumors ◽

Stereotactic Radiotherapy ◽

Neurocognitive Function ◽

Adult Brain ◽

Fractionated Stereotactic Radiotherapy ◽

Low Grade

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Long-term surgical outcomes of temporal lobe epilepsy associated with low-grade brain tumors

Cancer ◽

10.1002/cncr.24666 ◽

2009 ◽

Vol 115 (24) ◽

pp. 5771-5779 ◽

Cited By ~ 44

Author(s):

Ji Hoon Phi ◽

Seung-Ki Kim ◽

Byung-Kyu Cho ◽

Seo Young Lee ◽

Su Yeon Park ◽

...

Keyword(s):

Brain Tumors ◽

Temporal Lobe Epilepsy ◽

Temporal Lobe ◽

Surgical Outcomes ◽

Low Grade

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Imaging Experimental Brain Tumors with 1-Aminocyclopentane Carboxylic Acid and Alpha-Aminoisobutyric Acid: Comparison to Fluorodeoxyglucose and Diethylenetriaminepentaacetic Acid in Morphologically Defined Tumor Regions

Journal of Cerebral Blood Flow & Metabolism ◽

10.1097/00004647-199711000-00013 ◽

1997 ◽

Vol 17 (11) ◽

pp. 1239-1253 ◽

Cited By ~ 26

Author(s):

Hisao Uehara ◽

Tadashi Miyagawa ◽

Juri Tjuvajev ◽

Revathi Joshi ◽

Bradley Beattie ◽

...

Keyword(s):

Carboxylic Acid ◽

Brain Tumors ◽

Vascular Permeability ◽

Cell Density ◽

Low Grade ◽

Acid Uptake ◽

Diethylenetriaminepentaacetic Acid ◽

Experimental Brain Tumors ◽

Walker 256 ◽

Walker 256 Tumors

The goal of this study was to evaluate the differences and define the advantages of imaging experimental brain tumors in rats with two nonmetabolized amino acids, 1-aminocyclopentane carboxylic (ACPC) acid and α-aminoisobutyric (AIB) acid compared with imaging with fluorodeoxyglucose (FDG) or the gallium-diethylenetriaminepentaacetic acid chelate (Ga-DTPA). 1-aminocyclopentane carboxylic acid, AIB, and FDG autoradiograms were obtained 60 minutes after intravenous injection to simulate positron emission tomography (PET) imaging, whereas the Ga-DTPA autoradiograms were obtained 5 or 10 minutes after injection to simulate gadolinium (Gd)-DTPA–enhanced magnetic resonance (MR) images. Three experimental tumors were studied (C6, RG2, and Walker 256) to provide a range of tumor types. Triple-label quantitative autoradiography was performed, and parametric images of the apparent distribution volume (Va, mL/g) for ACPC or AIB, relative glucose metabolism (R, μmol/100 g/min), vascular permeability to Ga-DTPA (K1, μL/min/g), and histology were obtained from the same tissue section. The four images were registered in an image array processor, and regions of interest in tumor and contralateral brain were defined on morphologic criteria (histology) and were transferred to the autoradiographic images. A comparative analysis of all measured values was performed. The location and morphologic characteristics of the tumor had an effect on the images and measurements of Va, R, and K1. Meningeal extensions of all three tumors consistently had the highest amino acid uptake (Va) and vascular permeability (K1) values, and subcortical portions of the tumors usually had the lowest values. Va and R (FDG) values generally were higher in tumor regions with high-cell density and lower in regions with low-cell density. Tumor areas identified as “impending” necrosis on morphologic criteria consistently had high R values, but little or no change in Va or K1. Tumor necrosis was seen consistently only in the larger Walker 256 tumors; low values of R and Va for AIB (less for ACPC) were measured in the necrotic-appearing regions, whereas K1 was not different from the mean tumor value. The highest correlations were observed between vascular permeability (K1 for Ga-DTPA) and Va for AIB in all three tumors; little or no correlation between vascular permeability and R was observed. The advantages of ACPC and AIB imaging were most convincingly demonstrated in C6 gliomas and in Walker 256 tumors. 1-aminocyclopentane was substantially better than FDG or Ga-DTPA for identifying tumor infiltration of adjacent brain tissue beyond the macroscopic border of the tumor; ACPC also may be useful for identifying low-grade tumors with an intact blood–brain barrier. Contrast-enhancing regions of the tumors were visualized more clearly with AIB than with FDG or Ga-DTPA; viable and necrotic-appearing tumor regions could be distinguished more readily with AIB than with FDG. [11C]-labeled ACPC and AIB are likely to have similar advantages for imaging human brain tumors with PET.

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IBRDM: An Intelligent Framework for Brain Tumor Classification Using Radiomics- and DWT-based Fusion of MRI Sequences

ACM Transactions on Internet Technology ◽

10.1145/3434775 ◽

2022 ◽

Vol 22 (1) ◽

pp. 1-30

Author(s):

Rahul Kumar ◽

Ankur Gupta ◽

Harkirat Singh Arora ◽

Balasubramanian Raman

Keyword(s):

Brain Tumor ◽

Brain Tumors ◽

Performance Metrics ◽

Tumor Classification ◽

Training Dataset ◽

Tumor Segmentation ◽

Discrete Wavelet ◽

Low Grade ◽

Brain Tumor Segmentation ◽

Mri Sequences

Brain tumors are one of the critical malignant neurological cancers with the highest number of deaths and injuries worldwide. They are categorized into two major classes, high-grade glioma (HGG) and low-grade glioma (LGG), with HGG being more aggressive and malignant, whereas LGG tumors are less aggressive, but if left untreated, they get converted to HGG. Thus, the classification of brain tumors into the corresponding grade is a crucial task, especially for making decisions related to treatment. Motivated by the importance of such critical threats to humans, we propose a novel framework for brain tumor classification using discrete wavelet transform-based fusion of MRI sequences and Radiomics feature extraction. We utilized the Brain Tumor Segmentation 2018 challenge training dataset for the performance evaluation of our approach, and we extract features from three regions of interest derived using a combination of several tumor regions. We used wrapper method-based feature selection techniques for selecting a significant set of features and utilize various machine learning classifiers, Random Forest, Decision Tree, and Extra Randomized Tree for training the model. For proper validation of our approach, we adopt the five-fold cross-validation technique. We achieved state-of-the-art performance considering several performance metrics, 〈 Acc , Sens , Spec , F1-score , MCC , AUC 〉 ≡ 〈 98.60%, 99.05%, 97.33%, 99.05%, 96.42%, 98.19% 〉, where Acc , Sens , Spec , F1-score , MCC , and AUC represents the accuracy, sensitivity, specificity, F1-score, Matthews correlation coefficient, and area-under-the-curve, respectively. We believe our proposed approach will play a crucial role in the planning of clinical treatment and guidelines before surgery.

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BRMP-01. Awake cranial surgery with intraoperative language mapping for brain tumors. A single-center experience

Neuro-Oncology ◽

10.1093/neuonc/noab196.894 ◽

2021 ◽

Vol 23 (Supplement_6) ◽

pp. vi223-vi223

Author(s):

Andrés Cervio ◽

Sebastían Giovannini ◽

Sonia Hasdeu ◽

Lucía Pertierra ◽

Blanca Diez

Keyword(s):

Brain Tumors ◽

Functional Mri ◽

Tumor Resection ◽

Awake Surgery ◽

Anesthetic Technique ◽

Low Grade ◽

Safe Procedure ◽

Language Mapping ◽

Cranial Surgery

Abstract BACKGROUND Maximal safe resection of brain tumors affecting language areas has been a matter of increasing interest worldwide in the last decades. Functional MRI, tractography, and awake cranial surgery are standard procedures in our department since 2006. The aim of this study was to describe our experience in a series of 58 patients who underwent awake cranial surgery with intraoperative language mapping. METHODS Retrospective study of 58 adult patients who underwent awake surgery for brain tumors between January 2006 and January 2021. Preoperative neuropsychological assessment served as inclusion criteria. Language was evaluated according to the BDAE (Boston diagnostic aphasia examination) and WAB (Western aphasia battery) and strength according to the MRC (Medical Research Council) motor scale in the preoperative, immediate postoperative, and 3-months follow up. Functional MRI and tractography depicting white-matter tracts, neuronavigation, cortical and subcortical stimulation were performed in all cases. Conscious sedation was the anesthetic technique (propofol, fentanyl, and NSAIDs). Minimum follow-up was 6 months. FINDINGS The average age was 35 years (16–74). The anatomopathological findings were: low-grade glioma in 75,8% (n = 44), high-grade glioma in 15,6% (n = 9) and others in 8,6% (n = 5). No complications were registered during postoperative course. At the immediate postoperative evaluation 65% of patients presented with speech disturbances but at the 3-months follow up speech recovery was observed in all cases. Only 1 patient remained with moderate aphasia. mRS score at 3- months follow up was ≤ 1 in 96% of patients. Two patients had a persistent moderate hemiparesis. CONCLUSION Tumor resection in awake patients showed to be a safe procedure, and well tolerated by the patients. Preoperative planning of anatomical and functional aspects and intraoperative neurophysiological assessment are the cornerstones for pursuing maximal safe resection.

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