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.

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 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.

Apparent diffusion coefficient values and non-homogeneity of diffusion in brain tumors in diffusion-weighted MRI

2019 ◽  
Vol 61 (2) ◽  
pp. 244-252
Author(s):  
Sedigheh Basirjafari ◽  
Masoud Poureisa ◽  
Babak Shahhoseini ◽  
Mohammad Zarei ◽  
Saeideh Aghayari Sheikh Neshin ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Standard Deviation ◽  
Brain Tumors ◽  
Region Of Interest ◽  
Low Grade ◽  
High Grade ◽  
Ki 67 ◽  
Apparent Diffusion ◽  
Adc Values ◽  
The Mean

Background The values that have been received from apparent diffusion coefficient (ADC) maps of diffusion-weighted magnetic resonance imaging (DW-MRI) might play a vital role in evaluating tumors and their grading scale. Purpose To investigate the predictive role of this heterogeneity in brain tumor pathologies and its correlation with Ki-67. Material and Methods A total of 124 patients with brain tumors underwent brain MRI with gadolinium injection. ADC and standard deviation of each lesion have been obtained from manual localization of the region of interest on the ADC map. A receiver operating characteristic analysis was conducted to determine the minimum cut-off values of the mean ADC and mean standard deviation of ADC maps having the highest sensitivity and specificity to differentiate high-grade and low-grade tumors. Results Mean ADC values in the region of interest were significantly lower for malignant tumors (grade IV and metastasis) than grade I brain tumors, while a higher mean standard deviation was observed. In a more detailed comparison of tumor groups, the mean standard deviation of the ADC for glioblastoma multiform was significantly higher than meningioma grade I ( P < 0.001) and metastasis was significantly higher than grade III and IV astrocytic tumors ( P = 0.004). The analysis of Ki-67 proliferation index and mean ADC values in gliomas showed a significant inverse correlation between the parameters (r = –0.0429, P < 0.001) and direct correlation between Ki-67 and mean standard deviation of the ADC (r = 0.551, P < 0.001). As an index for the ADC to differentiate high-grade and low-grade tumors, the cut-off values of 1.40*10−3 mm2/s for mean ADC and 45*10−3 mm2/s for mean standard deviation have the highest combination of sensitivity, specificity, and area under the curve. Conclusion The mean value and standard deviation of the ADC could be considered for differentiating between low-grade and high-grade brain tumors, as two available non-invasive methods.

scholarly journals Genetic Abnormalities, Clonal Evolution, and Cancer Stem Cells of Brain Tumors

2018 ◽  
Vol 6 (4) ◽  
pp. 85 ◽  
Author(s):  
Ugo Testa ◽  
Germana Castelli ◽  
Elvira Pelosi
Keyword(s):  
Brain Tumors ◽  
Clonal Evolution ◽  
Pediatric Brain Tumors ◽  
Genetic Alterations ◽  
World Health ◽  
Driver Mutations ◽  
Low Grade ◽  
High Grade ◽  
Genetic Profiling ◽  
Health Organization

Brain tumors are highly heterogeneous and have been classified by the World Health Organization in various histological and molecular subtypes. Gliomas have been classified as ranging from low-grade astrocytomas and oligodendrogliomas to high-grade astrocytomas or glioblastomas. These tumors are characterized by a peculiar pattern of genetic alterations. Pediatric high-grade gliomas are histologically indistinguishable from adult glioblastomas, but they are considered distinct from adult glioblastomas because they possess a different spectrum of driver mutations (genes encoding histones H3.3 and H3.1). Medulloblastomas, the most frequent pediatric brain tumors, are considered to be of embryonic derivation and are currently subdivided into distinct subgroups depending on histological features and genetic profiling. There is emerging evidence that brain tumors are maintained by a special neural or glial stem cell-like population that self-renews and gives rise to differentiated progeny. In many instances, the prognosis of the majority of brain tumors remains negative and there is hope that the new acquisition of information on the molecular and cellular bases of these tumors will be translated in the development of new, more active treatments.

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