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 ◽  
...  
1999 ◽  
Vol 173 (1) ◽  
pp. 119-125 ◽  
Author(s):  
J F Norfray ◽  
T Tomita ◽  
S E Byrd ◽  
B D Ross ◽  
P A Berger ◽  
...  

2020 ◽  
Vol 3 ◽  
Author(s):  
Eric Chen ◽  
Chang Ho ◽  
Benjamin Gray ◽  
Jason Parker ◽  
Emily Diller ◽  
...  

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. 


Author(s):  
Güleç Mert Doğan ◽  
Ahmet Sığırcı ◽  
Sevgi Taşolar ◽  
Aslınur Cengiz ◽  
Hilal Er Ulubaba ◽  
...  

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.


2020 ◽  
Author(s):  
Zezhong Ye ◽  
Komal Srinivasa ◽  
Joshua Lin ◽  
Jeffrey D. Viox ◽  
Chunyu Song ◽  
...  

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.


2006 ◽  
Vol 22 (11) ◽  
pp. 1435-1439 ◽  
Author(s):  
Peter Kan ◽  
James K. Liu ◽  
Gary Hedlund ◽  
Douglas L. Brockmeyer ◽  
Marion L. Walker ◽  
...  

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