Perfusion-weighted techniques in MRI grading of pediatric cerebral tumors: efficiency of dynamic susceptibility contrast and arterial spin labeling

Comparison of Arterial Spin-Labeling and DSC Perfusion MR Imaging in Pediatric Brain Tumors: A Systematic Review and Meta-Analysis

BACKGROUND

Brain tumors are a leading cause of mortality in children. Accurate tumor grading is essential to plan treatment and for prognostication. Perfusion imaging has been shown to correlate well with tumor grade in adults, however there are fewer studies in pediatric patients. Moreover, there is no consensus regarding which MR perfusion technique demonstrates the highest accuracy in the latter population.

PURPOSE

We sought to compare the diagnostic test accuracy of DSC and arterial spin-labeling (ASL), in their ability to differentiate between low- and high-grade pediatric brain tumors at first presentation.

DATA SOURCES

Articles were retrieved from online electronic databases: MEDLINE (Ovid), Web of Science Core Collection, and Scopus.

STUDY SELECTION

Studies in pediatric patients with a treatment-naïve diagnosed brain tumor and imaging including either ASL or DSC or both, together with a histologic diagnosis were included. Studies involving adult patient or mixed age populations, studies with incomplete data, and those that used dynamic contrast-enhanced perfusion were excluded.

DATA ANALYSIS

The sensitivities and specificities obtained from each study were used to calculate the true-positive, true-negative, false-positive, and false-negative count. A case was defined as a histologically proved high-grade tumor. The random-effect model was used to merge statistics. Significance level was set at P < .05.

DATA SYNTHESIS

Forest plots showing pairs of sensitivity and specificity, with their 95% CIs, were constructed for each study. The bivariate model was applied to account for between-study variability. The summary receiver operating characteristics (SROC) plots were constructed from the obtained data sets. The area under the curve for the SROC of all studies was estimated to determine the overall diagnostic test accuracy of perfusion MRI, followed by a separate comparison of the SROC of ASL versus DSC studies.

LIMITATIONS

There was a small and heterogeneous sample size.

CONCLUSIONS

The diagnostic accuracy of ASL was found to be comparable and not inferior to DSC, thus its use in the diagnostic assessment of pediatric patients should continue to be supported.

Interictal EEG spikes increase perfusion in low-grade epilepsy-associated tumors: a pediatric arterial spin labeling study

PURPOSE

Arterial spin labeling (ASL), a noninvasive magnetic resonance (MRI) perfusion sequence, holds promise in the presurgical evaluation of pediatric lesional epilepsy patients, including those with low-grade epilepsy-associated tumors (LEATs). The interpretation of ASL-derived perfusion patterns, however, presents challenges. Our study aims to elucidate these perfusion changes in children with LEATs, exploring their correlations with clinical, electroencephalography (EEG), and anatomical MRI findings.

MATERIAL AND METHODS

Our cohort included 15 children with LEAT-associated focal lesional epilepsy who underwent single-delay pseudo-continuous ASL imaging; eight were imaged under sedation. We assessed perfusion images both qualitatively and quantitatively, focusing on LEAT-related perfusion changes, as indicated by the asymmetry index (AI) and regional cerebral blood flow (rCBF).

RESULTS

ASL revealed LEAT-related perfusion changes in all but two patients: 12 LEATs were hypoperfused and one was hyperperfused relative to the contralateral brain parenchyma (CBP). LEATs showed significantly lower perfusion compared to CBP (median: 38.7 vs. 59.1 mL/100 g/min for LEAT and CBP, respectively; p value = 0.004, Wilcoxon-Mann-Whitney), regardless of sedation. Notably, elevated AI and rCBF values correlated with interictal spikes on EEG (median: -0.008 and 0.84 vs -0.27 and 0.58, respectively), but not to other clinical, EEG, or MRI variables (p value = 0.036, Wilcoxon-Mann-Whitney).

CONCLUSIONS

By highlighting the connection between LEAT and brain perfusion, and by correlating perfusion characteristics and epileptogenicity, our research enhanced our understanding of pediatric epilepsy associated with LEATs. Also, by proving the robustness of these findings to sedation we confirmed the importance of adding ASL to epilepsy protocols to as a valuable tool to supplement anatomical imaging.

A Prospective Study of Arterial Spin Labelling in Paediatric Posterior Fossa Tumour Survivors: A Correlation with Neurocognitive Impairment

AIMS

Posterior fossa tumours (PFTs), which account for two-thirds of paediatric brain tumours, are successfully treated in about 70% of patients, but most survivors experience long-term cognitive impairment. We evaluated arterial spin labelling (ASL), a common, non-invasive magnetic resonance imaging (MRI) technique, as a biomarker of cognitive impairment in a paediatric PFT survivor population.

MATERIALS AND METHODS

Sixty participants were prospectively analysed. PFT survivors were at least 5 years post-treatment and had been treated as appropriate for their age and type of tumour. Group 1 had received radiotherapy and Group 2 had not. Group 3 were healthy controls matched to Group 1 for age, sex and handedness. All participants underwent cognitive assessment and multimodal MRI, including an ASL perfusion sequence. We used semi-quantitative ASL methods to assess differences in mean perfusion in the thalamus, caudate, putamen and hippocampus.

RESULTS

Statistically, no significant associations between cognitive data and radiation doses were identified. Compared with healthy controls, Group 1 patients had significantly lower overall mean perfusion values (20-30% lower, depending on the cerebral structure) and Group 2 had slightly lower mean perfusion values (5-10% lower). Perfusion values did not correlate with total prescribed irradiation doses nor with doses received by different cerebral structures. Episodic and semantic memory test scores were significantly lower in Group 1 and correlated with lower mean absolute perfusion values in the hippocampus (P < 0.04).

CONCLUSIONS

These preliminary results indicate that radiotherapy affects the perfusion of specific cerebral structures and identify perfusion as a potential biomarker of hippocampus-dependent memory deficit.

A multi-reader comparison of normal-appearing white matter normalization techniques for perfusion and diffusion MRI in brain tumors

PURPOSE

There remains no consensus normal-appearing white matter (NAWM) normalization method to compute normalized relative cerebral blood volume (nrCBV) and apparent diffusion coefficient (nADC) in brain tumors. This reader study explored nrCBV and nADC differences using different NAWM normalization methods.

METHODS

Thirty-five newly diagnosed glioma patients were studied. For each patient, two readers created four NAWM regions of interests: (1) a single plane in the centrum semiovale (CSOp), (2) 3 spheres in the centrum semiovale (CSOs), (3) a single plane in the slice of the tumor center (TUMp), and (4) 3 spheres in the slice of the tumor center (TUMs). Readers repeated NAWM segmentations 1 month later. Differences in nrCBV and nADC of the FLAIR hyperintense tumor, inter-/intra-reader variability, and time to segment NAWM were assessed. As a validation step, the diagnostic performance of each method for IDH-status prediction was evaluated.

RESULTS

Both readers obtained significantly different nrCBV (P < .001), nADC (P < .001), and time to segment NAWM (P < .001) between the four normalization methods. nrCBV and nADC were significantly different between CSO and TUM methods, but not between planar and spherical methods in the same NAWM region. Broadly, CSO methods were quicker than TUM methods, and spherical methods were quicker than planar methods. For all normalization techniques, inter-reader reproducibility and intra-reader repeatability were excellent (intraclass correlation coefficient > 0.9), and the IDH-status predictive performance remained similar.

CONCLUSION

The selected NAWM region significantly impacts nrCBV and nADC values. CSO methods, particularly CSOs, may be preferred because of time reduction, similar reader variability, and similar diagnostic performance compared to TUM methods.

Differentiation of pilocytic astrocytoma, medulloblastoma, and hemangioblastoma on diffusion-weighted and dynamic susceptibility contrast perfusion MRI

This study aimed to evaluate the diagnostic performance of dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging and apparent diffusion coefficient (ADC) for differentiating common posterior fossa tumors, pilocytic astrocytoma (PA), medulloblastoma (MB), and hemangioblastoma (HB). Between January 2016 and April 2022, we enrolled 23 (median age, 7 years [range, 2-26]; 12 female), 13 (10 years [1-24]; 3 female), and 12 (43 years [23-73]; 7 female) patients with PA, MB, and HB, respectively. Normalized relative cerebral blood volume and flow (nrCBV and nrCBF) and normalized mean ADC (nADCmean) were calculated from volume-of-interest and statistically compared. nADCmean was significantly higher in PA than in MB (PA: median, 2.2 [range, 1.59-2.65] vs MB: 0.93 [0.70-1.37], P < .001). nrCBF was significantly higher in HB than in PA and MB (PA: 1.10 [0.54-2.26] vs MB: 1.62 [0.93-3.16] vs HB: 7.83 [2.75-20.1], all P < .001). nrCBV was significantly different between all 3 tumor types (PA: 0.89 [0.34-2.28] vs MB: 1.69 [0.93-4.23] vs HB: 8.48 [4.59-16.3], P = .008 for PA vs MB; P < .001 for PA vs HB and MB vs HB). All tumors were successfully differentiated using an algorithmic approach with a threshold value of 4.58 for nrCBV and subsequent threshold value of 1.38 for nADCmean. DSC parameters and nADCmean were significantly different between PA, MB, and HB. An algorithmic approach combining nrCBV and nADCmean may be useful for differentiating these tumor types.

Arterial Spin Labeling Perfusion in Pediatric Brain Tumors: A Review of Techniques, Quality Control, and Quantification

Arterial spin labeling (ASL) is a magnetic resonance imaging (MRI) technique for measuring cerebral blood flow (CBF). This noninvasive technique has added a new dimension to the study of several pediatric tumors before, during, and after treatment, be it surgery, radiotherapy, or chemotherapy. However, ASL has three drawbacks, namely, a low signal-to-noise-ratio, a minimum acquisition time of 3 min, and limited spatial summarize current resolution. This technique requires quality control before ASL-CBF maps can be extracted and before any clinical investigations can be conducted. In this review, we describe ASL perfusion principles and techniques, summarize the most recent advances in CBF quantification, report technical advances in ASL (resting-state fMRI ASL, BOLD fMRI coupled with ASL), set out guidelines for ASL quality control, and describe studies related to ASL-CBF perfusion and qualitative and semi-quantitative ASL weighted-map quantification, in healthy children and those with pediatric brain tumors.

Predicting Survival in Patients with Brain Tumors: Current State-of-the-Art of AI Methods Applied to MRI

Given growing clinical needs, in recent years Artificial Intelligence (AI) techniques have increasingly been used to define the best approaches for survival assessment and prediction in patients with brain tumors. Advances in computational resources, and the collection of (mainly) public databases, have promoted this rapid development. This narrative review of the current state-of-the-art aimed to survey current applications of AI in predicting survival in patients with brain tumors, with a focus on Magnetic Resonance Imaging (MRI). An extensive search was performed on PubMed and Google Scholar using a Boolean research query based on MeSH terms and restricting the search to the period between 2012 and 2022. Fifty studies were selected, mainly based on Machine Learning (ML), Deep Learning (DL), radiomics-based methods, and methods that exploit traditional imaging techniques for survival assessment. In addition, we focused on two distinct tasks related to survival assessment: the first on the classification of subjects into survival classes (short and long-term or eventually short, mid and long-term) to stratify patients in distinct groups. The second focused on quantification, in days or months, of the individual survival interval. Our survey showed excellent state-of-the-art methods for the first, with accuracy up to ∼98%. The latter task appears to be the most challenging, but state-of-the-art techniques showed promising results, albeit with limitations, with C-Index up to ∼0.91. In conclusion, according to the specific task, the available computational methods perform differently, and the choice of the best one to use is non-univocal and dependent on many aspects. Unequivocally, the use of features derived from quantitative imaging has been shown to be advantageous for AI applications, including survival prediction. This evidence from the literature motivates further research in the field of AI-powered methods for survival prediction in patients with brain tumors, in particular, using the wealth of information provided by quantitative MRI techniques.

Dynamic susceptibility contrast and diffusion-weighted MRI in posterior fossa pilocytic astrocytoma and medulloblastoma

BACKGROUND AND PURPOSE

The utility of perfusion MRI in distinguishing between pilocytic astrocytoma (PA) and medulloblastoma (MB) is unclear. This study aimed to evaluate the diagnostic and prognostic performance of dynamic susceptibility contrast (DSC)-MRI parameters and apparent diffusion coefficient (ADC) values between PA and MB.

METHODS

Between January 2012 and August 2021, 49 (median, 7 years [range, 1-28 years]; 28 females) and 35 (median, 8 years [1-24 years]; 12 females) patients with pathologically confirmed PA and MB, respectively, were included. The normalized relative cerebral blood volume and flow (nrCBV and nrCBF) and mean and minimal normalized ADC (nADCmean and nADCmin) values were calculated using volume-of-interest analyses. Diagnostic performance and Pearson's correlation with progression-free survival were also evaluated.

RESULTS

The MB group showed a significantly higher nrCBV and nrCBF (nrCBV: 1.69 [0.93-4.23] vs. 0.95 [range, 0.37-2.28], p = .0032; nrCBF: 1.62 [0.93-3.16] vs. 1.07 [0.46-2.26], p = .0084) and significantly lower nADCmean and nADCmin (nADCmean: 0.97 [0.70-1.68] vs. 2.21 [1.44-2.80], p < .001; nADCmin: 0.50 [0.19-0.89] vs. 1.42 [0.89-2.20], p < .001) than the PA group. All parameters exhibited good diagnostic ability (accuracy >0.80) with nADCmin achieving the highest score (accuracy = 1). A moderate correlation was found between nADCmean and progression-free survival for MB (r = 0.44, p = .0084).

CONCLUSIONS

DSC-MRI parameters and ADC values were useful for distinguishing between PA and MB. A lower ADC indicated an unfavorable MB prognosis, but the DSC-MRI parameters did not correlate with progression-free survival in either group.

1.5 vs 3 Tesla Magnetic Resonance Imaging: A Review of Favorite Clinical Applications for Both Field Strengths-Part 2

ABSTRACT

The second part of this review deals with experiences in neuroradiological and pediatric examinations using modern magnetic resonance imaging systems with 1.5 T and 3 T, with special attention paid to experiences in pediatric cardiac imaging. In addition, whole-body examinations, which are widely used for diagnostic purposes in systemic diseases, are compared with respect to the image quality obtained in different body parts at both field strengths. A systematic overview of the technical differences at 1.5 T and 3 T has been presented in part 1 of this review, as well as several organ-based magnetic resonance imaging applications including musculoskeletal imaging, abdominal imaging, and prostate diagnostics.