scholarly journals Serial MR diffusion to predict treatment response in high-grade pediatric brain tumors: a comparison of regional and voxel-based diffusion change metrics

2013 ◽  
Vol 15 (8) ◽  
pp. 981-989 ◽  
Author(s):  
D. Rodriguez Gutierrez ◽  
M. Manita ◽  
T. Jaspan ◽  
R. A. Dineen ◽  
R. G. Grundy ◽  
...  
Keyword(s):  
Brain Tumors ◽  
Treatment Response ◽  
Pediatric Brain Tumors ◽  
High Grade ◽  
Mr Diffusion ◽  
Change Metrics ◽  
Pediatric Brain ◽  
Predict Treatment Response

scholarly journals Comparison of Diffusion and Perfusion Techniques in Differentiating High Versus Low Grade Pediatric Brain Tumors

2020 ◽  
Vol 3 ◽  
Author(s):  
Eric Chen ◽  
Chang Ho ◽  
Benjamin Gray ◽  
Jason Parker ◽  
Emily Diller ◽  
...  
Keyword(s):  
Brain Tumors ◽  
Tumor Grade ◽  
Pediatric Brain Tumors ◽  
Solid Cancer ◽  
Low Grade ◽  
Dynamic Susceptibility ◽  
High Grade ◽  
Dynamic Contrast Enhancement ◽  
Significant Difference ◽  
Pediatric Brain

Background/Objective: Brain tumors are the most common solid cancer in children and cause significant mortality and morbidity. We compare the effectiveness of different parameters in predicting tumor grade between dynamic contrast enhancement (DCE), intravoxel incoherent motion (IVIM), dynamic susceptibility contrast (DSC) perfusion and diffusion weighted imaging (DWI).    Methods: A retrospective blinded review of pediatric brain tumors with DCE, IVIM, DWI, and DSC was performed. Parametric maps were registered to T2 weighted images. Volumetric regions of interest (ROI) were manually segmented from solid tumor components for each patient by a neuroradiologist (CH), neuroradiology fellow (BG), and medical student (EC). Resulting mean values for parameters from DCE (Ktrans, Kep, Ve, Vp,), IVIM (D, D*, f), DSC (rCBV) and DWI (ADC) were compared using Student’s t-test for high- and low-grade tumor groups based on WHO grading from pathology. For significant parameters, receiver operating characteristic (ROC) analysis with area under curve (AUC) was performed.     Results: 20 subjects were included with 9 low grade and 11 high grade tumors. Significant differences between low versus high grade were demonstrated for D (10−3 mm2/s) (1.4±0.4 vs 0.9±0.2, p=0.01), f (0.04±0.02 vs 0.07±0.02, p=0.02), ADC (10−3 mm2/s) (1.4±0.4 vs 0.9±0.3, p=0.009) and rCBV (2.2±0.9 vs 4.7±2.1, p=0.003). No significant difference was found for D* or any DCE parameter. AUC from ROC was similar for all significant parameters [D (0.81, p=0.003); f (0.80, p=0.003); ADC (0.83, p=0.001); rCBV (0.83, p=0.0005)].    Conclusion: D and f parameters from IVIM can significantly differentiate high versus low grade pediatric brain tumors similar to ADC and rCBV. Conversely, no DCE parameter was significant.    Scientific Implications: The results will assist the selection of MRI sequences that best predict tumor grade, as well as guide tumor biopsy for the most aggressive tumor portions. Further study of these techniques may correlate with molecular profiling and predict outcome. 

scholarly journals Differentiation of Low- and High-Grade Pediatric Brain Tumors with Highb-Value Diffusion-weighted MR Imaging and a Fractional Order Calculus Model

Radiology ◽  
2015 ◽  
Vol 277 (2) ◽  
pp. 489-496 ◽  
Author(s):  
Yi Sui ◽  
He Wang ◽  
Guanzhong Liu ◽  
Frederick W. Damen ◽  
Christian Wanamaker ◽  
...  
Keyword(s):  
Brain Tumors ◽  
Mr Imaging ◽  
Fractional Order ◽  
Pediatric Brain Tumors ◽  
High Grade ◽  
Fractional Order Calculus ◽  
Diffusion Weighted ◽  
Pediatric Brain

scholarly journals Do Intratumoral And Peritumoral Apparent Diffusion Coefficient (ADC) Values Have A Role In The Diagnosis Of Pediatric Brain Tumors?

2020 ◽  
Author(s):  
Güleç Mert Doğan ◽  
Ahmet Sığırcı ◽  
Sevgi Taşolar ◽  
Aslınur Cengiz ◽  
Hilal Er Ulubaba ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Brain Tumors ◽  
Magnetic Resonance Image ◽  
Pediatric Patients ◽  
Pediatric Brain Tumors ◽  
Low Grade ◽  
High Grade ◽  
Apparent Diffusion ◽  
Adc Values ◽  
Pediatric Brain

INTRODUCTION: The motion of water particles within biological tissues, which is called random Brownian motion, is detected at the microscopic level by Diffusion-Weighted Imaging (DWI) sequence of Magnetic Resonance Image technique. The Apparent Diffusion Coefficient (ADC) calculated on DWI has been used for tumor diagnosis and grading. The purpose of this study was to evaluate of ADC values in the differential diagnosis of supratentorial and infratentorial pediatric brain tumors and to reveal the difference of peritumoral ADC measurements of pediatric patients from adult patients. METHODS: All of the 56 pediatric patients included in this retrospective study had lesions >1 cm in diameter on magnetic resonance image and all of the diagnosies were confirmed by histopathology. Intratumoral and peritumoral ADC values and ratios were measured in diffusion weighted Magnetic Resonance Image. RESULTS: The 58.9% (n=33) of these tumors were supratentorial and 41.1% (n=23) were infratentorial. ADC values and ADC ratios were significantly lower in high-grade tumors than low-grade tumors (p<0.05). Peritumoral ADC values in high-grade tumors were lower than low grade tumors (p<0.05). The cut-off value of the ADC ratio between these two groups was 1 and the ADC cut-off value was 1.1*10-3 mm2/s. DISCUSSION AND CONCLUSION: In the differentiation of low and high-grade pediatric brain tumors, cut-off values of 1.1*10_3mm2/s for ADC Value and 1.0 for ADC Ratio may be useful. Although, peritumoral ADC values differ in children compared to the adult group, both intratumoral and peritumoral ADC values can help for grading pediatric brain tumors.

Diffusion Basis Spectrum Imaging with Deep Neural Network Differentiates Distinct Histology in Pediatric Brain Tumors

2020 ◽  
Author(s):  
Zezhong Ye ◽  
Komal Srinivasa ◽  
Joshua Lin ◽  
Jeffrey D. Viox ◽  
Chunyu Song ◽  
...  
Keyword(s):  
Neural Network ◽  
Brain Tumor ◽  
Brain Tumors ◽  
Deep Neural Network ◽  
Unmet Need ◽  
Pediatric Brain Tumors ◽  
High Grade ◽  
Tumor Histology ◽  
Spectrum Imaging ◽  
Pediatric Brain

AbstractHigh-grade pediatric brain tumors constitute the highest mortality of cancer-death in children. While conventional MRI has been widely adopted for examining pediatric high-grade brain tumor clinically, accurate neuroimaging detection and differentiation of tumor histopathology for improved diagnosis, surgical planning, and treatment evaluation, remains an unmet need in the clinical management of pediatric brain tumor. We employed a novel Diffusion Histology Imaging (DHI) approach that incorporates diffusion basis spectrum imaging (DBSI) and deep neural network. DHI aims to detect, differentiate, and quantify heterogenous areas in pediatric high-grade brain tumors, which include normal white matter (WM), densely cellular tumor (DC tumor), less densely cellular tumor (LDC tumor), infiltrating edge, necrosis, and hemorrhage. Distinct diffusion metric combination would thus indicate the unique distributions of each distinct tumor histology features. DHI, by incorporating DBSI metrics and the deep neural network algorithm, classified pediatric tumor histology with an overall accuracy of 83.3%. Receiver operating analysis (ROC) analysis suggested DHI’s great capability in distinguishing individual tumor histology with AUC values (95%CI) of 0.983 (0.985-0.989), 0.961 (0.957-0.964), 0.993 (0.992-0.994), 0.953 (0.947-0.958), 0.974 (0.970-0.978) and 0.980 (0.977-0.983) for normal WM, DC tumor, LDC tumor, infiltrating edge, necrosis and hemorrhage, respectively. Our results suggest that DBSI-DNN, or DHI, accurately characterized and classified multiple tumor histologic features in pediatric high-grade brain tumors. If further validated in patients, the novel DHI might emerge as a favorable alternative to the current neuroimaging techniques to better guide biopsy and resection as well as monitor therapeutic response in patients with high-grade brain tumors.

scholarly journals Magnetic resonance–guided stereotactic laser ablation therapy for the treatment of pediatric brain tumors: a multiinstitutional retrospective study

2020 ◽  
Vol 26 (1) ◽  
pp. 13-21
Author(s):  
Elsa V. Arocho-Quinones ◽  
Sean M. Lew ◽  
Michael H. Handler ◽  
Zulma Tovar-Spinoza ◽  
Matthew Smyth ◽  
...  
Keyword(s):  
Laser Ablation ◽  
Brain Tumors ◽  
Adjuvant Treatment ◽  
Pediatric Brain Tumors ◽  
Tumor Location ◽  
Neurological Deficits ◽  
Low Grade ◽  
High Grade ◽  
Pediatric Brain

OBJECTIVEThis study aimed to assess the safety and efficacy of MR-guided stereotactic laser ablation (SLA) therapy in the treatment of pediatric brain tumors.METHODSData from 17 North American centers were retrospectively reviewed. Clinical, technical, and radiographic data for pediatric patients treated with SLA for a diagnosis of brain tumor from 2008 to 2016 were collected and analyzed.RESULTSA total of 86 patients (mean age 12.2 ± 4.5 years) with 76 low-grade (I or II) and 10 high-grade (III or IV) tumors were included. Tumor location included lobar (38.4%), deep (45.3%), and cerebellar (16.3%) compartments. The mean follow-up time was 24 months (median 18 months, range 3–72 months). At the last follow-up, the volume of SLA-treated tumors had decreased in 80.6% of patients with follow-up data. Patients with high-grade tumors were more likely to have an unchanged or larger tumor size after SLA treatment than those with low-grade tumors (OR 7.49, p = 0.0364). Subsequent surgery and adjuvant treatment were not required after SLA treatment in 90.4% and 86.7% of patients, respectively. Patients with high-grade tumors were more likely to receive subsequent surgery (OR 2.25, p = 0.4957) and adjuvant treatment (OR 3.77, p = 0.1711) after SLA therapy, without reaching significance. A total of 29 acute complications in 23 patients were reported and included malpositioned catheters (n = 3), intracranial hemorrhages (n = 2), transient neurological deficits (n = 11), permanent neurological deficits (n = 5), symptomatic perilesional edema (n = 2), hydrocephalus (n = 4), and death (n = 2). On long-term follow-up, 3 patients were reported to have worsened neuropsychological test results. Pre-SLA tumor volume, tumor location, number of laser trajectories, and number of lesions created did not result in a significantly increased risk of complications; however, the odds of complications increased by 14% (OR 1.14, p = 0.0159) with every 1-cm3 increase in the volume of the lesion created.CONCLUSIONSSLA is an effective, minimally invasive treatment option for pediatric brain tumors, although it is not without risks. Limiting the volume of the generated thermal lesion may help decrease the incidence of complications.

Tumor molecular profiling in advanced pediatric brain tumors.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e21516-e21516
Author(s):  
Gargi D. Basu ◽  
Thanemozhi G Natarajan ◽  
Szabolcs Szelinger ◽  
Candyce M Bair ◽  
Tracey White ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Brain Tumors ◽  
Pediatric Brain Tumors ◽  
Molecular Profiling ◽  
Small Sample ◽  
Braf V600e ◽  
Low Grade ◽  
High Grade ◽  
Clinical Sequencing ◽  
Pediatric Brain

e21516 Background: With the advent of high-throughput molecular profiling, clinical outcome in pediatric cancers has greatly improved due to our greater understanding of genetic origin of pediatric cancer, and availability of biomarker specific treatment options. However, pediatric brain tumors continue to be challenging in terms of therapy. The goal of this study was to evaluate the utility of integrative clinical sequencing in pediatric patients with brain tumors. Methods: Targeted exome sequencing of 562 genes in paired tumor-normal DNA was performed on 14 patients and tumor DNA and RNA was sequenced on additional 4 patients. Sequence analysis identified SNVs, indels, copy number events, fusions, alternate transcripts, breakpoints, TMB and MSI status. Clinically, actionable alterations were identified which could be targeted by FDA approved agents or clinical trials. Results: A total of 18 patients (1-17 y.o.) with low grade (n = 5) and high grade (n = 13) brain tumors were profiled. The cohort consisted of a spectrum of GBMs (45%), medulloblastomas (10%) astrocytomas (22%), and other brain tumors (23%). At least one targetable, driver alteration was identified in 83% of all patients, and 92% of high-grade patients had at least one targetable driver event. Targetable mutations were identified in histone and chromatin modifier genes like H3F3A in 3/18 cases (17%), SETD2, ARID1A, PBRM1 in 2/18 cases (11%), activation of PI3K/AKT/mTOR pathway genes in 6/18 cases (33%), DNA repair genes NBN, ATRX and BRCA2 in 3/18 cases (17%); BRAF V600E in 3 high-grade and a KIAA1549/BRAF fusion in a low-grade tumor, activation of cell cycle in 2/18 cases (11%), activation of FGFR pathway with FGFR1/TACC1 fusion and activating mutation in 2/18 cases (11%), activation of PDGFRA in 2/18 samples (11%), TP53 mutations in 4/18 cases (22%). A breakpoint translocation concurrent with LOH of PTCH1 locus was noted in a medulloblastoma patient. High TMB or MSI instability was not observed. Conclusions: Our results underline the importance of clinical sequencing in identifying targetable markers in high- risk brain tumors. Although limited by small sample size, our study highlights the need for ongoing clinical trials to integrate the genomic discoveries leading to better clinical outcomes.

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