Advanced MR Imaging in Pediatric Brain Tumors, Clinical Applications

Radiomics and artificial intelligence applications in pediatric brain tumors

BACKGROUND

The study of central nervous system (CNS) tumors is particularly relevant in the pediatric population because of their relatively high frequency in this demographic and the significant impact on disease- and treatment-related morbidity and mortality. While both morphological and non-morphological magnetic resonance imaging techniques can give important information concerning tumor characterization, grading, and patient prognosis, increasing evidence in recent years has highlighted the need for personalized treatment and the development of quantitative imaging parameters that can predict the nature of the lesion and its possible evolution. For this purpose, radiomics and the use of artificial intelligence software, aimed at obtaining valuable data from images beyond mere visual observation, are gaining increasing importance. This brief review illustrates the current state of the art of this new imaging approach and its contributions to understanding CNS tumors in children.

DATA SOURCES

We searched the PubMed, Scopus, and Web of Science databases using the following key search terms: ("radiomics" AND/OR "artificial intelligence") AND ("pediatric AND brain tumors"). Basic and clinical research literature related to the above key research terms, i.e., studies assessing the key factors, challenges, or problems of using radiomics and artificial intelligence in pediatric brain tumors management, was collected.

RESULTS

A total of 63 articles were included. The included ones were published between 2008 and 2024. Central nervous tumors are crucial in pediatrics due to their high frequency and impact on disease and treatment. MRI serves as the cornerstone of neuroimaging, providing cellular, vascular, and functional information in addition to morphological features for brain malignancies. Radiomics can provide a quantitative approach to medical imaging analysis, aimed at increasing the information obtainable from the pixels/voxel grey-level values and their interrelationships. The "radiomic workflow" involves a series of iterative steps for reproducible and consistent extraction of imaging data. These steps include image acquisition for tumor segmentation, feature extraction, and feature selection. Finally, the selected features, via training predictive model (CNN), are used to test the final model.

CONCLUSIONS

In the field of personalized medicine, the application of radiomics and artificial intelligence (AI) algorithms brings up new and significant possibilities. Neuroimaging yields enormous amounts of data that are significantly more than what can be gained from visual studies that radiologists can undertake on their own. Thus, new partnerships with other specialized experts, such as big data analysts and AI specialists, are desperately needed. We believe that radiomics and AI algorithms have the potential to move beyond their restricted use in research to clinical applications in the diagnosis, treatment, and follow-up of pediatric patients with brain tumors, despite the limitations set out.

[Pediatric posterior fossa tumors]

CLINICAL ISSUE

Tumors of the posterior fossa account for about 50-55% of brain tumors in childhood.

DIAGNOSTIC WORKUP

The most frequent tumor entities are medulloblastomas, pilocytic astrocytomas, ependymomas, diffuse midline gliomas and atypical teratoid-rhabdoid tumors. Neuroradiological differential diagnosis with magnetic resonance imaging (MRI) is of considerable importance for preoperative planning as well as planning of follow-up therapy.

PERFORMANCE

Most important findings for differential diagnosis of pediatric posterior fossa tumors are tumor location, patient age and the intratumoral apparent diffusion assessed by diffusion-weighted imaging.

ACHIEVEMENTS

Advanced MR techniques like MRI perfusion and MR spectroscopy can be helpful both in the initial differential diagnosis and in tumor surveillance, but exceptional characteristics of certain tumor entities should be kept in mind.

PRACTICAL RECOMMENDATIONS

Standard clinical MRI sequences including diffusion-weighted imaging are the main diagnostic tool in evaluating posterior fossa tumors in children. Advanced imaging methods can be helpful, but should never be interpreted separately from conventional MRI sequences.

Advanced intraoperative MRI in pediatric brain tumor surgery

Introduction: In the pediatric brain tumor surgery setting, intraoperative MRI (ioMRI) provides "real-time" imaging, allowing for evaluation of the extent of resection and detection of complications. The use of advanced MRI sequences could potentially provide additional physiological information that may aid in the preservation of healthy brain regions. This review aims to determine the added value of advanced imaging in ioMRI for pediatric brain tumor surgery compared to conventional imaging. Methods: Our systematic literature search identified relevant articles on PubMed using keywords associated with pediatrics, ioMRI, and brain tumors. The literature search was extended using the snowball technique to gather more information on advanced MRI techniques, their technical background, their use in adult ioMRI, and their use in routine pediatric brain tumor care. Results: The available literature was sparse and demonstrated that advanced sequences were used to reconstruct fibers to prevent damage to important structures, provide information on relative cerebral blood flow or abnormal metabolites, or to indicate the onset of hemorrhage or ischemic infarcts. The explorative literature search revealed developments within each advanced MRI field, such as multi-shell diffusion MRI, arterial spin labeling, and amide-proton transfer-weighted imaging, that have been studied in adult ioMRI but have not yet been applied in pediatrics. These techniques could have the potential to provide more accurate fiber tractography, information on intraoperative cerebral perfusion, and to match gadolinium-based T1w images without using a contrast agent. Conclusion: The potential added value of advanced MRI in the intraoperative setting for pediatric brain tumors is to prevent damage to important structures, to provide additional physiological or metabolic information, or to indicate the onset of postoperative changes. Current developments within various advanced ioMRI sequences are promising with regard to providing in-depth tissue information.

Prediction of H3 K27M-mutant in midline gliomas by magnetic resonance imaging: a systematic review and meta-analysis

PURPOSE

To summarize the predictive value of MRI for H3 K27M-mutant in midline gliomas using meta-analysis.

METHODS

Systematic electronic searches of the PubMed, Embase, ISI Web of Science, and Cochrane Library up to Jun 31, 2021, were conducted by two experienced neuroradiologists with the keywords of "MRI," "Glioma," and "H3 K27M." The hierarchical summary receiver-operating characteristic (HSROC) model was used to calculate the pooled sensitivity, specificity, positive likelihood ratio (LR +), negative likelihood ratio (LR -), and diagnostic odds ratio (DOR). Coupled forest plots were used to evaluate the heterogeneity of the included studies.

RESULTS

Of seven original studies with a total of 593 patients, 240 glioma patients were included, with 45.5-70.6% H3 K27M-mutant gliomas. Using MRI, a pooled sensitivity of 0.78 (95% CI, 0.66-0.87), specificity of 0.85 (95% CI, 0.76-0.91), LR + of 5.07 (95% CI, 3.19-8.08), LR - of 0.26 (95% CI, 0.16-0.42), and DOR of 19.80 (95% CI, 9.28-42.28) were achieved for H3 K27M-mutant prediction. Significant heterogeneity was observed among the studies in terms of sensitivity (Q = 16.83, df = 7, p = 0.02; I² = 58.40 [95% CI, 25.83-90.97]), LR - (Q = 16.61, df = 7, p = 0.02; I² = 57.87 [95% CI, 24.81-90.93]), and DOR (Q = 14.05, df = 7, p = 0.05; I² = 50.18 [95% CI, 10.06-90.31]).

CONCLUSIONS

This meta-analysis demonstrated a clinical value of MRI to predict H3 K27M-mutant in midline gliomas with a pooled sensitivity of 0.78 and specificity of 0.85.

MR Imaging of Pediatric Brain Tumors

Primary brain tumors are the most common solid neoplasms in children and a leading cause of mortality in this population. MRI plays a central role in the diagnosis, characterization, treatment planning, and disease surveillance of intracranial tumors. The purpose of this review is to provide an overview of imaging methodology, including conventional and advanced MRI techniques, and illustrate the MRI appearances of common pediatric brain tumors.

Diagnostic accuracy of qualitative MRI in 550 paediatric brain tumours: evaluating current practice in the computational era

BACKGROUND

To investigate the accuracy of qualitative reporting of conventional magnetic resonance imaging (MRI) in the classification of paediatric brain tumours.

METHODS

Preoperative MRI reports of 608 children prior to resection or biopsy of an intracranial lesion were retrospectively reviewed. A total of 550 children had complete radiological and histopathological notes, thereby reaching our inclusion criteria. Concordance between MRI report and final histopathological diagnosis was assessed using an established lexicon derived from the WHO 2016 classification of CNS tumours. Levels of agreement based on cellular origin, tumour type, and tumour grade were evaluated. Diagnostic accuracy, sensitivity, specificity, confidence intervals, and positive and negative predictive values were calculated.

RESULTS

Diagnostic accuracy differed significantly between tumour types and tumour grades. Sensitivities were highest for ependymomas and sellar, pituitary, pineal, and cranial and/or paraspinal nerve tumours (range 80.65-100%). Sensitivity was slightly lower for astrocytic gliomas, oligodendrogliomas, and choroid plexus, neuronal, mixed neuronal-glial, embryonal, and histiocytic tumours (range 63.33-79.59%). Low sensitivities were noted for meningiomas and mesenchymal non-meningothelial, melanocytic, and germ cell tumours (range 0-56.25%). The most correct tumour type predictions were made in the posterior fossa whilst the most incorrect predictions were made in the lobar regions, pineal/tectal plate area, and the supratentorial ventricles.

CONCLUSIONS

This is the largest published series investigating the predictive accuracy of MRI in paediatric brain tumours. We show that diagnostic accuracy varies greatly by tumour type and location. Looking forward, we should develop and leverage computational methods to improve accuracy in the tumour types and anatomical locations where qualitative diagnostic accuracy is lower.

Contrast Pediatric Brain Perfusion: Dynamic Susceptibility Contrast and Dynamic Contrast-Enhanced MR Imaging

Magnetic resonance (MR) perfusion is a robust imaging technique that assesses the passage of blood through the cerebral vascular network using a variety of techniques. The applications of MR perfusion have been expanded and is well suited to investigate cerebrovascular diseases and cerebral neoplastic processes in pediatric patients. Assessment of brain perfusion can augment the information obtained on conventional MR imaging and provides additional information on the biological and physiologic features of pediatric brain tumors. Similarly, MR perfusion can help guide the management of a variety of pediatric cerebrovascular diseases, including acute ischemic stroke and Moyamoya syndrome.

Evolution of surgical attitudes to paediatric thalamic tumours: the alder hey experience

PURPOSE

Attitudes to surgery for paediatric thalamic tumours have evolved due to improved preoperative imaging modalities and the advent of intraoperative MRI (iMRI) as well as enhanced understanding of tumour biology. We review the developments in our local practice over the last three decades with particular attention to the impact of iMRI.

METHODS

We identified all paediatric patients from a prospectively maintained neuro-oncology database who received surgery for a thalamic tumour (n = 30). All children were treated in a single UK tertiary paediatric neurosurgery centre between January 1991 and June 2020. Twenty patients underwent surgical resection, the remainder (10) undergoing biopsy only. Pre-operative surgical intent (biopsy versus debulking, near-total resection, or complete resection) as well as the use of iMRI were prospectively recorded. Complications recorded in clinical documentation between postoperative days 0 and 30 were retrospectively graded using a modified version of the Clavien Dindo scale. The extent of resection with respect to the pre-determined surgical aim was also recorded. Data on patient survival and disease progression status were obtained retrospectively.

RESULTS

In our series, there were 42 procedures (25 craniotomies, 17 biopsies) performed on 30 patients (17 male, with a median age of 8 at surgery). Of the 25 surgical resections performed, complete resection was achieved in 9 (36%), near-total resection in 10 (40%), and limited debulking in 6 (24%). The predetermined surgical aim was achieved or exceeded in 91.3% of cases. The proportion of craniotomies for which substantial resection was achieved, increased from 37.5 to 94.2% with use of iMRI (p = 0.014). Surgical morbidity was not associated with greater extent of surgical resection. High-grade histology is identified as the only independent significant factor influencing overall survival as calculated by Cox proportional hazards model (p = 0.006).

CONCLUSION

We note a significant change in the rate and extent of attempted resection of paediatric thalamic tumours that has developed over the last 3 decades. Use of iMRI is associated with a significant increase in substantial tumour resection surgeries. This is not associated with any significant level of surgical morbidity. Improvements in pre- and intra-operative imaging alongside better understanding of tumour biology facilitate patient selection and a surgically more aggressive approach in selected cases whilst maintaining safety and avoiding operative morbidity.

Clinical Review of Computed Tomography and MR Perfusion Imaging in Neuro-Oncology

Neuroimaging plays an essential role in the initial diagnosis and continued surveillance of intracranial neoplasms. The advent of perfusion techniques with computed tomography and MR imaging have proven useful in neuro-oncology, offering enhanced approaches for tumor grading, guiding stereotactic biopsies, and monitoring treatment efficacy. Perfusion imaging can help to identify treatment-related processes, such as radiation necrosis, pseudoprogression, and pseudoregression, and can help to inform treatment-related decision making. Perfusion imaging is useful to differentiate between tumor types and between tumor and nonneoplastic conditions. This article reviews the clinical relevance and implications of perfusion imaging in neuro-oncology and highlights promising perfusion biomarkers.

Effect Evaluation of Combined Application of Magnetic Resonance Diffusion Tensor Imaging and Brain Function Imaging in Radiation Therapy of Brain Tumours Involving Motor Pathways

This study is an attempt to find a way for functional imaging information to be applied clinically in radiation therapy. The basal nucleus is a collective term for a group of neural nucleus in the central nervous system that connects the pontine, brainstem, and cerebral cortex, including the caudate nucleus, the bean-shaped nucleus, the screen-shaped nucleus, and the amygdala. It is difficult to find the exact position of these neural nuclei on the computed tomography (CT) image or the T1 or T2 sequence of magnetic resonance. However, the development of neurosurgery has partially confirmed that these functional nuclei are involved in advanced cognitive functions such as memory, emotion, and learning. Neurosurgery has tried to avoid damaging these nucleus groups during surgery to improve the quality of life of patients, and there is currently no clear strategy for this in radiotherapy. Because CT and magnetic resonance spin echo (SE) sequences are difficult to find the anatomical location of the nucleus, it is difficult to have any strategy to protect these functions in radiotherapy planning. This article uses diffusion tensor imaging (DTI) images and fiber bundle tracking to obtain a more accurate anatomical position of the nerve nucleus on the image, and provides some available strategies for radiotherapy to protect patients’ brain function. The conclusion of this paper is that the combined application of DTI and functional magnetic resonance imaging (fMRI) can better observe the relationship among tumours, functional areas and white matter fibers, and guide the designation of radiotherapy plans.

The incidence of childhood cancer in Australia, 1983-2015, and projections to 2035

Objectives

To describe changes in childhood cancer incidence in Australia, 1983–2015, and to estimate projected incidence to 2035.

Design, setting

Population‐based study; analysis of Australian Childhood Cancer Registry data for the 20 547 children under 15 years of age diagnosed with cancer in Australia between 1983 and 2015.

Main outcome measures

Incidence rate changes during 1983–2015 were assessed by joinpoint regression, with rates age‐standardised to the 2001 Australian standard population. Incidence projections to 2035 were estimated by age‐period‐cohort modelling.

Results

The overall age‐standardised incidence rate of childhood cancer increased by 34% between 1983 and 2015, increasing by 1.2% (95% CI, +0.5% to +1.9%) per annum between 2005 and 2015. During 2011–2015, the mean annual number of children diagnosed with cancer in Australia was 770, an incidence rate of 174 cases (95% CI, 169–180 cases) per million children per year. The incidence of hepatoblastoma (annual percentage change [APC], +2.3%; 95% CI, +0.8% to +3.8%), Burkitt lymphoma (APC, +1.6%; 95% CI, +0.4% to +2.8%), osteosarcoma (APC, +1.1%; 95%, +0.0% to +2.3%), intracranial and intraspinal embryonal tumours (APC, +0.9%; 95% CI, +0.4% to +1.5%), and lymphoid leukaemia (APC, +0.5%; 95% CI, +0.2% to +0.8%) increased significantly across the period 1983–2015. The incidence rate of childhood melanoma fell sharply between 1996 and 2015 (APC, –7.7%; 95% CI, –10% to –4.8%). The overall annual cancer incidence rate is conservatively projected to rise to about 186 cases (95% CI, 175–197 cases) per million children by 2035 (1060 cases per year).

Conclusions

The incidence rates of several childhood cancer types steadily increased during 1983–2015. Although the reasons for these rises are largely unknown, our findings provide a foundation for health service planning for meeting the needs of children who will be diagnosed with cancer until 2035.

Role of diffusion weighted imaging for differentiating cerebral pilocytic astrocytoma and ganglioglioma BRAF V600E-mutant from wild type

PURPOSE

BRAF V600E mutation is a distinctive genomic alteration of pediatric low-grade gliomas with prognostic and therapeutic implications. The aim of this retrospective multicenter study was to analyze imaging features of BRAF V600E-mutant and wild-type cerebral pilocytic astrocytomas (PAs) and gangliogliomas (GGs), focusing on the role of diffusion weighted imaging (DWI).

METHODS

We retrospectively evaluated 56 pediatric patients with histologically proven, treatment-naïve PAs and GGs who underwent conventional MRI, DWI, and molecular analysis for BRAF V600E mutation. Twenty-three subjects presented BRAF V600E-mutant (12 PAs and 11 GGs) and 33 BRAF V600E wild-type (26 PAs and 7 GGs) tumors. Imaging studies were reviewed for dominant site, margin definition, hemorrhage, calcification, cystic components, contrast enhancement, and relative mean and minimum ADC values (rADCmean and rADCmin). Statistics included Fisher's exact test, Student t test, general linear model, and receiver operating characteristic (ROC) analysis.

RESULTS

PA and GG BRAF V600E-mutant had significantly lower rADCmean (p < 0.001) and rADCmin (p < 0.001) values than wild type, regardless of tumor histology and location. ROC analysis demonstrated similar performances between these parameters in predicting BRAF V600E status (rADCmean: AUC 0.831, p < 0.001; rADCmin: AUC 0.885, p < 0.001). No significant differences regarding additional imaging features emerged between BRAF V600E-mutant and wild-type lesions, with the exception of the number of tumors with cystic components, significantly higher in BRAF V600E-mutant PAs (p = 0.011) CONCLUSION: Assessment of the DWI characteristics of GGs and PAs may assist in predicting BRAF V600E status, suggesting a radiogenomic correlation and prompt molecular characterization of these tumors.

The correlation of fractional anisotropy parameters with Ki-67 index, and the clinical implication in grading of non-enhancing gliomas and neuronal-glial tumors

PURPOSE

To investigate the correlation between the FA parameters and Ki-67 labeling index, and their diagnostic performance in grading supratentorial non-enhancing gliomas and neuronal-glial tumors (GNGT).

METHODS

This institutional review board-approved, Health Insurance Portability and Accountability (HIPAA) compliant retrospective study enrolled 35 patients, including 19 with low grade GNGT and 16 with high grade GNGT. The mean FA, maximal FA and mean maximal FA values derived from diffusion tensor imaging were measured. The correlation between the FA parameters and the Ki-67 labeling index was assessed by Spearman rank test. The receiver operating characteristic curve analysis and multivariate logistic regression analysis were performed to detect the optimal imaging parameters in grading GNGT.

RESULTS

The three FA parameters of low grade GNGT were significantly lower than the high grade GNGT (p < 0.001). The mean FA, maximal FA and mean maximal FA had significant positive correlation with Ki-67 labeling index (p = 0.001, p < 0.001, p < 0.001 respectively). The maximal FA showed a higher sensitivity and specificity in grading of non-enhancing GNGT with specificity of 78.9%, sensitivity of 100.0%, respectively.

CONCLUSIONS

The FA parameters correlated with Ki-67 labeling index, and were useful surrogates in preoperative grading supratentorial non-enhancing GNGT.

Pediatric Brain Tumor Genetics: What Radiologists Need to Know

Brain tumors are the most common solid tumors in the pediatric population. Pediatric neuro-oncology has changed tremendously during the past decade owing to ongoing genomic advances. The diagnosis, prognosis, and treatment of pediatric brain tumors are now highly reliant on the genetic profile and histopathologic features of the tumor rather than the histopathologic features alone, which previously were the reference standard. The clinical information expected to be gleaned from radiologic interpretations also has evolved. Imaging is now expected to not only lead to a relevant short differential diagnosis but in certain instances also aid in predicting the specific tumor and subtype and possibly the prognosis. These processes fall under the umbrella of radiogenomics. Therefore, to continue to actively participate in patient care and/or radiogenomic research, it is important that radiologists have a basic understanding of the molecular mechanisms of common pediatric central nervous system tumors. The genetic features of pediatric low-grade gliomas, high-grade gliomas, medulloblastomas, and ependymomas are reviewed; differences between pediatric and adult gliomas are highlighted; and the critical oncogenic pathways of each tumor group are described. The role of the mitogen-activated protein kinase pathway in pediatric low-grade gliomas and of histone mutations as epigenetic regulators in pediatric high-grade gliomas is emphasized. In addition, the oncogenic drivers responsible for medulloblastoma, the classification of ependymomas, and the associated imaging correlations and clinical implications are discussed. ^©RSNA, 2018.

Advanced MR imaging and 18F-DOPA PET characteristics of H3K27M-mutant and wild-type pediatric diffuse midline gliomas

PURPOSE

The aim of this study was to investigate MRI-derived diffusion weighted imaging (DWI), ¹H-MR spectroscopy (¹H-MRS) and arterial spin labeling (ASL) perfusion imaging in comparison with ¹⁸F-dihydroxyphenylalanine (DOPA) PET with respect to diagnostic evaluation of pediatric diffuse midline gliomas (DMG) H3K27M-mutant and wild-type.

METHODS

We retrospectively analyzed 22 pediatric patients with DMG histologically proved and molecularly classified as H3K27M-mutant (12 subjects) and wild-type (10 subjects) who underwent DWI, ¹H-MRS, and ASL performed within 2 weeks of ¹⁸F-DOPA PET. DWI-derived relative minimum apparent diffusion coefficient (rADC min), ¹H-MRS data [choline/N-acetylaspartate (Cho/NAA), choline/creatine (Cho/Cr), and presence of lactate] and relative ASL-derived cerebral blood flow max (rCBF max) were compared with ¹⁸F-DOPA uptake Tumor/Normal tissue (T/N) and Tumor/Striatum (T/S) ratios, and correlated with histological and molecular features of DMG. Statistics included Pearson's chi-square and Mann-Whitney U tests, Spearman's rank correlation and receiver operating characteristic (ROC) analysis.

RESULTS

The highest degrees of correlation among different techniques were found between T/S, rADC min and Cho/NAA ratio (p < 0.01), and between rCBF max and rADC min (p < 0.01). Significant differences between histologically classified low- and high-grade DMG, independently of H3K27M-mutation, were found among all imaging techniques (p ≤ 0.02). Significant differences in terms of rCBF max, rADC min, Cho/NAA and ¹⁸F-DOPA uptake were also found between molecularly classified mutant and wild-type DMG (p ≤ 0.02), even though wild-type DMG included low-grade astrocytomas, not present among mutant DMG. When comparing only histologically defined high-grade mutant and wild-type DMG, only the ¹⁸F-DOPA PET data T/S demonstrated statistically significant differences independently of histology (p < 0.003). ROC analysis demonstrated that T/S ratio was the best parameter for differentiating mutant from wild-type DMG (AUC 0.94, p < 0.001).

CONCLUSIONS

Advanced MRI and ¹⁸F-DOPA PET characteristics of DMG depend on histological features; however, ¹⁸F-DOPA PET-T/S was the only parameter able to discriminate H3K27M-mutant from wild-type DMG independently of histology.

Advances in Neuro-Oncology Imaging Techniques

Background

Central nervous system (CNS) tumors are a rare but devastating malignancy, often robbing patients of the basic quality of life. Despite advances in our understanding of the CNS tumor disease processes, the prognosis for patients with CNS tumors remains poor. Better characterization and diagnostic and monitoring approaches are necessary to assist in diagnosis and treatment of CNS tumors. One important tool in the neuro-oncology armamentarium is the use of advanced imaging techniques.

Methods

We searched PubMed using the keywords neuro-oncology imaging, pseudoprogression, molecular imaging, and biomarkers. We limited our search to full-text English articles and identified other relevant articles from the reference lists of previously identified articles.

Results

Advances in imaging techniques have allowed investigators to explore various imaging modalities, from tumor characterization to differentiating pseudoprogression from tumor progression. Better imaging can result in better diagnostic approaches, greater and safer resection techniques, and improved monitoring of tumor progression.

Conclusion

This review highlights advances in neuro-oncology imaging techniques and their clinical utility in the treatment and management of primary brain tumors.

Grading and outcome prediction of pediatric diffuse astrocytic tumors with diffusion and arterial spin labeling perfusion MRI in comparison with 18F-DOPA PET

PURPOSE

The aim of this study was to investigate MRI-derived diffusion weighted imaging (DWI) and arterial spin labeling (ASL) perfusion imaging in comparison with ¹⁸F-dihydroxyphenylalanine (DOPA) PET with respect to diagnostic performance in tumor grading and outcome prediction in pediatric patients with diffuse astrocytic tumors (DAT).

METHODS

We retrospectively analyzed 26 children with histologically proven treatment naïve low and high grade DAT who underwent ASL and DWI performed within 2 weeks of ¹⁸F-DOPA PET. Relative ASL-derived cerebral blood flow max (rCBF max) and DWI-derived minimum apparent diffusion coefficient (rADC min) were compared with ¹⁸F-DOPA uptake tumor/normal tissue (T/N) and tumor/striatum (T/S) ratios, and correlated with World Health Organization (WHO) tumor grade and progression-free survival (PFS). Statistics included Pearson's chi-square and Mann-Whitney U tests, Spearman's rank correlation, receiver operating characteristic (ROC) analysis, discriminant function analysis (DFA), Kaplan-Meier survival curve, and Cox analysis.

RESULTS

A significant correlation was demonstrated between rCBF max, rADC min, and ¹⁸F-DOPA PET data (p < 0.001). Significant differences in terms of rCBF max, rADC min, and ¹⁸F-DOPA uptake were found between low- and high-grade DAT (p ≤ 0.001). ROC analysis and DFA demonstrated that T/S and T/N values were the best parameters for predicting tumor progression (AUC 0.93, p < 0.001). On univariate analysis, all diagnostic tools correlated with PFS (p ≤ 0.001); however, on multivariate analysis, only ¹⁸F-DOPA uptake remained significantly associated with outcome (p ≤ 0.03), while a trend emerged for rCBF max (p = 0.09) and rADC min (p = 0.08). The combination of MRI and PET data increased the predictive power for prognosticating tumor progression (AUC 0.97, p < 0.001).

CONCLUSIONS

DWI, ASL and ¹⁸F-DOPA PET provide useful complementary information for pediatric DAT grading. ¹⁸F-DOPA uptake better correlates with PFS prediction. Combining MRI and PET data provides the highest predictive power for prognosticating tumor progression suggesting a synergistic role of these diagnostic tools.