RADT-12. USE OF FDOPA PET FOR RADIATION THERAPY TARGETING IN GRADE 2 IDH MUTANT GLIOMA

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi43-vi43
Author(s):  
James Cordova ◽  
Thomas Mazur ◽  
Timothy Mitchell ◽  
Gloria Perez-Carrillo ◽  
Qing Wang ◽  
...  
Keyword(s):  
Low Grade ◽  
Normal Brain ◽  
Dice Coefficient ◽  
Target Delineation ◽  
Prospective Pilot Study ◽  
Target Volumes ◽  
Amino Acid Pet ◽  
Clinical Target Volumes ◽  
Pet System ◽  
Surface Metrics

Abstract BACKGROUND Low-grade, IDH mutant (IDHmt) gliomas typically do not enhance on MRI complicating radiotherapy (RT) target delineation. Amino acid PET using 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (FDOPA) has demonstrated avidity in IDHmt gliomas and may assist in RT planning for non-enhancing tumors. This study aims to compare conventional and FDOPA-defined target volumes in grade 2 IDHmt gliomas. METHODS In a prospective pilot study, patients underwent MRI and FDOPA PET using a 3T MRI/PET system followed by standard therapy. Gross tumor volumes (GTV) included the T2/FLAIR abnormality and surgical cavity; clinical target volumes (CTV) included a 1 cm expansion constrained anatomically. Metabolic target volumes (MTVs) were generated using the FDOPA SUV > 1.5-fold normal brain isocurve. Union of GTV and MTV generated a fusion GTV (fGTV); expanding fGTV by 1 cm yielded the fusion CTV (fCTV). Target volumes were compared volumetrically with overlap (Dice coefficient) and surface metrics (Hausdorff distance). Medians are reported with ranges. RESULTS Four patients with grade 2 IDHmt glioma (3 1p/19q codeleted oligodendrogliomas, 1 non-codeleted astrocytoma) received MRI/PET before treatment. All oligodendrogliomas exhibited FDOPA avidity; the astrocytoma showed no avidity. GTV and CTV measured 16.1 cc (4.9 - 82.2 cc) and 76.7 cc (29.5 - 256.1 cc), respectively. The MTV volume outside of GTV was 0.8 cc (0.2 – 6.1 cc), but was covered in each case by the CTV. Addition of FDOPA increased fGTV and fCTV volumes by 5.4% and 17.5%, respectively. Dice coefficient and Hausdorff distances for GTV vs fGTV were 0.96 (0.95 - 0.99) and 11.2 mm (10.0 – 11.9 mm), respectively, and for CTV vs fCTV were 0.87 (0.81 – 0.95) and 10.2 mm (10.0 - 11.0), respectively. CONCLUSIONS FDOPA PET identified tracer-avid regions outside of MRI-defined GTVs in a group of IDHmt gliomas. FDOPA PET provides useful metabolic information for RT planning and warrants further investigation.

scholarly journals Volumetric and dosimetric impact of Post-Surgical MRI guided radiotherapy for Glioblastoma: A pilot study

BJR|Open ◽  
2021 ◽  
Author(s):  
Marcus Tyyger ◽  
Suchandana Bhaumik ◽  
Michael Nix ◽  
Stuart Currie ◽  
Chandran Nallathambi ◽  
...  
Keyword(s):  
Normal Brain ◽  
Dose Volume Histogram ◽  
Target Delineation ◽  
Post Surgery ◽  
Dose Volume ◽  
Target Volumes ◽  
Ct Simulation ◽  
Organ At Risk ◽  
Mri Guided ◽  
Dedicated Mri

Objectives: Glioblastoma (GBM) radiotherapy (RT) target delineation requires MRI, ideally concurrent with CT simulation (pre-RT MRI). Due to limited MRI availability, <72 h post-surgery MRI is commonly used instead. Whilst previous investigations assessed volumetric differences between post-surgical and pre-RT delineations, dosimetric impact remains unknown. We quantify volumetric and dosimetric impact of using post-surgical MRI for GBM target delineation. Methods: Gross tumour volumes (GTVs) for five GBM patients receiving chemo-RT with post-surgical and pre-RT MRIs were delineated by three independent observers. Planning target volumes (PTVs) and RT plans were generated for each GTV. Volumetric and dosimetric differences were assessed through: absolute volumes, volume-distance histograms, and dose-volume histogram statistics. Results: Post-surgical MRI delineations had significantly (p < 0.05) larger GTV and PTV volumes (median 16.7 and 64.4 cm3 respectively). Post-surgical RT plans, applied to pre-RT delineations, had significantly decreased (p < 0.01) median PTV doses (ΔD99% = −8.1 Gy and ΔD95% = −2.0 Gy). Median organ at risk (OAR) dose increases (brainstem ΔD5% =+0.8, normal brain mean dose =+2.9 and normal brain ΔD10% = 5.3 Gy) were observed. Conclusion: Post-surgical MRI delineation significantly impacted RT planning, with larger normal-appearing tissue volumes irradiated and increased OAR doses, despite a reduced coverage of the pre-RT defined target. Advances in knowledge: We believe this is the first investigation assessing the dosimetric impact of using post-surgical MRI for GBM target delineation. It highlights the potential of significantly degraded RT plans, showing the clinical-need for dedicated MRI for GBM RT.

PSA-Net: Deep Learning–based Physician Style–Aware Segmentation Network for Postoperative Prostate Cancer Clinical Target Volumes

2021 ◽  
pp. 102195
Author(s):  
Anjali Balagopal ◽  
Howard Morgan ◽  
Michael Dohopoloski ◽  
Ramsey Timmerman ◽  
Jie Shan ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Deep Learning ◽  
Target Volumes ◽  
Clinical Target Volumes

Auto-delineation of oropharyngeal clinical target volumes using 3D convolutional neural networks

2018 ◽  
Vol 63 (21) ◽  
pp. 215026 ◽  
Author(s):  
Carlos E Cardenas ◽  
Brian M Anderson ◽  
Michalis Aristophanous ◽  
Jinzhong Yang ◽  
Dong Joo Rhee ◽  
...  
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Target Volumes ◽  
Clinical Target Volumes

scholarly journals Determination of SOX9 Gene Expression In Brain Tumours Among East Coast Malaysia Population

2020 ◽  
Vol 18 (2) ◽  
Author(s):  
Md Dzali NB ◽  
Wan Taib WR ◽  
Zahary MN ◽  
Abu Bakar NH ◽  
Abd Latif AZ ◽  
...  
Keyword(s):  
Brain Tissue ◽  
Brain Tumour ◽  
Brain Tumours ◽  
East Coast ◽  
Rna Extraction ◽  
Slight Modification ◽  
Low Grade ◽  
Normal Brain ◽  
Sox9 Expression ◽  
Sox9 Gene

Introduction: SOX9, a members of SOX family, plays a significant roles in developmental processes during embryogenesis, including brain tissue. Few studies have shown that SOX9 has been involved in tumourigenesis of several types of cancer including brain tumour. However, such studies are still lacking in the Malaysian population. The aim of this study was to determine SOX9 expression level in several types of brain tumours in East Coast Malaysia. Materials and Methods: Five formalin-fixed pariffin-embedded brain tumour samples of Malay descendants were sectioned by using microtome. RNA extraction was performed with slight modification by adding Trizol during tissue lysis. The RNA was converted to cDNA using reverse transcription technique before SOX9 expression was detected using RT q-PCR assay in brain tumours normalized to non-neoplastic brain tissues. Results: Overall results displayed that SOX9 gene in all samples were up-regulated. SOX9 overexpression was found in both high and low grade glioma (anaplastic and pilocytic astrocytoma respectively). This is consistence with both low grade (benign) and atypical meningioma. Secondary brain tumour also showed up-regulation when compared to normal brain tissue. Conclusion: Up-regulation in SOX9 expression in selected brain tumours in Malay patients revealed its significant roles in brain tumourigenesis. Functional studies should be carried out to observe the SOX9 functions and mechanism whether they should reflect their diverse roles in Malaysia population.

Automated Early Detection of Astrocytomas Tumor Based on Optimized Adaptive Cluster with Super Pixel Model

2021 ◽  
Vol 30 (06n08) ◽  
Author(s):  
V. K. Deepak ◽  
R. Sarath
Keyword(s):  
Brain Tumor ◽  
Medical Image ◽  
Automatic Segmentation ◽  
Tumor Segmentation ◽  
Low Grade ◽  
Grey Wolf ◽  
Dice Coefficient ◽  
Grey Wolf Optimization ◽  
Brain Tumor Segmentation ◽  
Better Than

In the medical image-processing field brain tumor segmentation is aquintessential task. Thereby early diagnosis gives us a chance of increasing survival rate. It will be way much complex and time consuming when comes to processing large amount of MRI images manually, so for that we need an automatic way of brain tumor image segmentation process. This paper aims to gives a comparative study of brain tumor segmentation, which are MRI-based. So recent methods of automatic segmentation along with advanced techniques gives us an improved result and can solve issue better than any other methods. Therefore, this paper brings comparative analysis of three models such as Deformable model of Fuzzy C-Mean clustering (DMFCM), Adaptive Cluster with Super Pixel Segmentation (ACSP) and Grey Wolf Optimization based ACSP (GWO_ACSP) and these are tested on CANCER IMAGE ACHRCHIEVE which is a preparation information base containing High Grade and Low-Grade astrocytoma tumors. Here boundaries including Accuracy, Dice coefficient, Jaccard score and MCC are assessed and along these lines produce the outcomes. From this examination the test consequences of Grey Wolf Optimization based ACSP (GWO_ACSP) gives better answer for mind tumor division issue.

scholarly journals 3131 ONCOSTREAMS: NOVEL DYNAMICS PATHOLOGICAL MULTICELLULAR STRUCTURES INVOLVED IN GLIOBLATOMA GROWTH AND INVASION

2019 ◽  
Vol 3 (s1) ◽  
pp. 111-111 ◽  
Author(s):  
Andrea Comba ◽  
Patrick Dunn ◽  
Anna E Argento ◽  
Padma Kadiyala ◽  
Sebastien Motsch ◽  
...  
Keyword(s):  
Extracellular Matrix ◽  
Target Genes ◽  
Collective Motion ◽  
Malignant Tumors ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Genetically Engineered ◽  
Functional Enrichment ◽  
Low Grade ◽  
Normal Brain

OBJECTIVES/SPECIFIC AIMS: Oncostreams represent a novel growth pattern of GBM. In this study we uncovered the cellular and molecular mechanism that regulates the oncostreams function in GBM growth and invasion. METHODS/STUDY POPULATION: We studied oncostreams organization and function using genetically engineered mouse gliomas models (GEMM), mouse primary patient derived GBM model and human glioma biopsies. We evaluated the molecular landscape of oncostreams by laser capture microdissection (LCM) followed by RNA-Sequencing and bioinformatics analysis. RESULTS/ANTICIPATED RESULTS: Oncostreams are multicellular structures of 10-20 cells wide and 2-400 μm long. They are distributed throughout the tumors in mouse and human GBM. Oncostreams are heterogeneous structures positive for GFAP, Nestin, Olig2 and Iba1 cells and negative for Neurofilament. Using GEMM we found a negative correlation between oncostream density and animal survival. Moreover, examination of patient’s glioma biopsies evidenced that oncostreams are present in high grade but no in low grade gliomas. This suggests that oncostreams may play a role in tumor malignancy. Our data also indicated that oncostreams aid local invasion of normal brain. Transcriptome analysis of oncostreams revealed 43 differentially expressed (DE) genes. Functional enrichment analysis of DE genes showed that “collagen catabolic processes”, “positive regulation of cell migration”, and “extracellular matrix organization” were the most over-represented GO biological process. Network analysis indicated that Col1a1, ACTA2, MMP9 and MMP10 are primary target genes. These genes were also overexpressed in more malignant tumors (WT-IDH) compared to the less malignant (IDH1- R132H) tumors. Confocal time lapse imagining of 3D tumor slices demonstrated that oncostreams display a collective motion pattern within gliomas that has not been seen before. DISCUSSION/SIGNIFICANCE OF IMPACT: In summary, oncostreams are anatomically and molecularly distinctive, regulate glioma growth and invasion, display collective motion and are regulated by the extracellular matrix. We propose oncostreams as novel pathological markers valuable for diagnosis, prognosis and designing therapeutics for GBM patients.

scholarly journals C.03 Deformation-based morphometry analysis of longitudinal low-grade glioma growth

2019 ◽  
Vol 46 (s1) ◽  
pp. S12
Author(s):  
C Gui ◽  
JC Lau ◽  
J Kai ◽  
AR Khan ◽  
JF Megyesi
Keyword(s):  
Tissue Expansion ◽  
Mass Effect ◽  
Low Grade ◽  
Normal Brain ◽  
Primary Brain Tumours ◽  
Morphometry Analysis ◽  
Glioma Growth ◽  
Deformation Based Morphometry ◽  
Over Time ◽  
Nonlinear Registration

Background: Diffuse low-grade gliomas (LGGs) are primary brain tumours with infiltrative, anisotropic growth related to surrounding white and grey matter structures. Deformation-based morphometry (DBM) is a simple and objective image analysis method that can identify areas of local volume change over time. In this study, we illustrate the use of DBM to study the local expansion patterns of LGGs monitored by serial magnetic resonance imaging (MRI). Methods: We developed an image processing pipeline optimized for the study of LGG growth involving the fusion of follow-up MRIs for a given patient into an average template space using nonlinear registration. The displacement maps derived from nonlinear registration were converted to Jacobian maps, which estimate local tissue expansion and contraction over time. Results: Our results demonstrate that neoplastic growth occurs primarily around the edges of the tumour while the lesion core and areas adjacent to obstacles, such as the skull, show no significant expansion. Regions of normal brain tissue surrounding the lesion show slight contraction over time, representing compression due to mass effect of the tumour. Conclusions: DBM is a useful tool to understand the long-term clinical course of individual tumours and identify areas of rapid growth, which may explain the current presentation and/or predict future symptoms.

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