Correlation of 3D Arterial Spin Labeling and Multi-Parametric Dynamic Susceptibility Contrast Perfusion MRI in Brain Tumors

Song

Computational and Mathematical Methods in Medicine

et al. 2022

The aim of this research was to analyze the application of fuzzy C-means (FCM) algorithm-based ARM-Linux-embedded system in magnetic resonance imaging (MRI) images for prediction of brain tumors. The optimized FCM (OFCM) algorithm was proposed based on kernel function, and the ARM-Linux-embedded imaging system was designed under ARM9 chip and Linux recorder, which were applied in MRI images of brain tumor patients. It was found that the sensitivity, specificity, and accuracy of the OFCM algorithm (90.46%, 88.97%, and 97.46%) were greater obviously than those of the deterministic C-means clustering algorithm (80.38%, 77.98%, and 85.24%) and the traditional FCM algorithm (83.26%, 79.56%, and 86.45%), and the difference was statistically substantial ( P < 0.05 ). The ME and running time of the OFCM algorithm decreased sharply in contrast to those of the deterministic C-means clustering algorithm and the traditional FCM algorithm ( P < 0.05 ). There were great differences in fraction anisotropy (FA) and mean diffusion (MD) of tumor parenchymal area, surrounding edema area, and normal white matter area ( P < 0.05 ). FA of stage III+IV was smaller than those of stage I and II ( P < 0.05 ), while the apparent diffusion coefficient (ADC) of stage III+IV was greater than that of stage I and II ( P < 0.05 ). In conclusion, the poor update data processing and low data clustering efficiency of FCM were solved by OFCM. Moreover, computational efficiency of ARM-Linux-embedded imaging system was improved, so as to better realize the prediction of brain tumor patients through ARM-Linux-embedded system based on adaptive FCM incremental clustering algorithm.

Section: Discussioncontrasting

confidence: 99%

Fuzzy C-Means Algorithm-Based ARM-Linux-Embedded System Combined with Magnetic Resonance Imaging for Progression Prediction of Brain Tumors

Song

Computational and Mathematical Methods in Medicine

et al. 2022

Magnetic Resonance in Med

“…The DSC perfusion acquisitions support the hypoperfusion highlighted through pCASL scans. ASL and DSC results are comparable in the non-US exposed hemisphere, in agreement with the literature 49 whereas this congruence is not valid in the hemisphere with BBB opening. A possible explanation for this is that the increase in surface permeability affects the acquisitions and the respective quantification models related to each method in distinct ways.…”

Section: Discussionsupporting

confidence: 85%

Evidence of cerebral hypoperfusion consecutive to ultrasound‐mediated blood‐brain barrier opening in rats

Labriji

Clauzel

Mestas

et al. 2023

Purpose This work aims to explore the effect of Blood Brain Barrier (BBB) opening using ultrasound combined with microbubbles injection on cerebral blood flow in rats. Methods Two groups of n = 5 rats were included in this study. The first group was used to investigate the impact of BBB opening on the Arterial Spin Labeling (ASL) signal, in particular on the arterial transit time (ATT). The second group was used to analyze the spatiotemporal evolution of the change in cerebral blood flow (CBF) over time following BBB opening and validate these results using DSC‐MRI. Results Using pCASL, a decrease in CBF of up to 29.6prefix±15.1%$$ 29.6\pm 15.1\% $$ was observed in the target hemisphere, associated with an increase in arterial transit time. The latter was estimated to be normal533prefix±normal121ms$$ 533\pm 12\mathrm{1ms} $$ in the BBB opening impacted regions against normal409prefix±normal93ms$$ 409\pm 93\mathrm{ms} $$ in the contralateral hemisphere. The spatio‐temporal analysis of CBF maps indicated a nonlocal hypoperfusion. DSC‐MRI measurements were consistent with the obtained results. Conclusion This study provided strong evidence that BBB opening using microbubble intravenous injection induces a transient hypoperfusion. A spatiotemporal analysis of the hypoperfusion changes allows to establish some points of similarity with the cortical spreading depression phenomenon.

“…These studies provide preliminary evidence that ASL can be used as a non-invasive alternative to DSC addressing the shortcoming of non-diffusible tracer (gadolinium) in DSC that leaks out of dysfunctional BBB and may lead to underestimation of the rTBF measurement [47]. In addition, there is scarce evidence on the prognostic role of each perfusion techniques [48–53], where rCBV measurements seem to provide the best sensitivity and specificity to predict tumor recurrence and survival time in gliomas patients [54].…”

Section: Discussionmentioning

confidence: 99%

The value of arterial spin labelling in adults glioma grading: systematic review and meta-analysis

et al. 2019

This study aimed to evaluate the diagnostic performance of arterial spin labelling (ASL) in grading of adult gliomas. Eighteen studies matched the inclusion criteria and were included after systematic searches through EMBASE and MEDLINE databases. The quality of the included studies was assessed utilizing Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). The quantitative values were extracted and a meta-analysis was subsequently based on a random-effect model with forest plot and joint sensitivity and specificity modelling. Hierarchical summary receiver operating characteristic (HROC) curve analysis was also conducted. The absolute tumour blood flow (TBF) values can differentiate high-grade gliomas (HGGs) from low-grade gliomas (LGGs) and grade II from grade IV tumours. However, it lacked the capacity to differentiate grade II from grade III tumours and grade III from grade IV tumours. In contrast, the relative TBF (rTBF) is effective in differentiating HGG from LGG and in glioma grading. The maximum rTBF (rTBFmax) demonstrated the best results in glioma grading. These results were also reflected in the sensitivity/specificity analysis in which the rTBFmax showed the highest discrimination performance in glioma grading. The estimated effect size for the rTBF was approximately similar between HGGs and LGGs, and grade II and grade III tumours, (–1.46 (–2.00, –0.91), p-value < 0.001), (–1.39 (–1.89, –0.89), p-value < 0.001), respectively; while it exhibited smaller effect size between grade III and grade IV (–1.05 (–1.82, –0.27)), p < 0.05). Sensitivity and specificity analysis replicate these results as well. This meta-analysis suggests that ASL is useful for glioma grading, especially when considering the rTBFmax parameter.