Arterial spin labelling and diffusion-weighted imaging in paediatric brain tumours

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.

Glioma grading using multiparametric MRI: head-to-head comparison among dynamic susceptibility contrast, dynamic contrast-enhancement, diffusion-weighted images, and MR spectroscopy

PURPOSE

To assess the diagnostic accuracy of dynamic susceptibility contrast, dynamic contrast-enhancement, MR spectroscopy (MRS), and diffusion-weighted imaging for differentiating high-grade (HGGs) from low-grade gliomas (LGGs).

METHODS

Seventy-two patients (16 LGGs, 56 HGGs) with pathologically confirmed gliomas were retrospectively included. From three-dimensionally segmented tumor, histogram analyses of relative cerebral blood volume (rCBV), volume transfer constant (K^trans), and apparent diffusion coefficient (ADC) were performed. Choline-to-creatinine ratio (Cho/Cr) was calculated using MRS. Logistic regression analyses were performed to differentiate HGGs (grade ≥ 3) from LGGs (grade ≤ 2). Areas under the receiver operating characteristics curves (AUC) were plotted. Subgroup analysis was performed between IDH-wildtype glioblastomas and IDH-mutant astrocytomas. Pairwise Spearman's correlation coefficients (ρ) were computed.

RESULTS

HGGs had higher 95th percentile rCBV, K^trans and Cho/Cr (P < 0.01) than LGGs. AUC of 95th percentiles of rCBV and K^trans were 0.79 (95% CI, 0.67-0.91) and 0.74 (95% CI, 0.59-0.88), respectively. AUC of 5th percentile of ADC was 0.63 (95% CI, 0.48-0.79), and that of Cho/Cr was 0.67 (95% CI, 0.52-0.81). IDH-wildtype glioblastomas and IDH-mutant astrocytomas showed significantly different 95th percentile rCBV (P = 0.04) and K^trans (P < 0.01), with K^trans showing the highest AUC (0.73, 95% CI 0.57-0.89) in IDH status prediction. Moderate correlations were observed between 95th percentile rCBV and K^trans (ρ = 0.47), Cho/Cr (ρ = 0.40), and 5th percentile ADC (ρ = -0.36) (all P < 0.01).

CONCLUSIONS

The 95th percentile rCBV may be most helpful in discriminating HGGs from LGGs. The 95th percentile K^trans may aid predicting IDH status of diffuse gliomas.

The therapeutic utility of combining dynamic contrast-enhanced magnetic resonance imaging with arterial spin labeling in the staging of nasopharyngeal carcinoma

BACKGROUND

To research the pathological and clinical staging uses of arterial spin labeling (ASL) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

MATERIALS AND METHODS

64 newly diagnosed nasopharyngeal carcinoma (NPC) patients were enrolled from December 2020 to January 2022, and 3.0 T MRI (Discovery 750W, GE Healthcare, USA) were used for ASL and DCE-MRI scans. The DCE-MRI and ASL raw data were processed post-acquisition on the GE image processing workstation (GE Healthcare, ADW 4.7, USA). The volume transfer constant (Ktrans), blood flow (BF), and accompanying pseudo-color images were generated automatically. Draw the region of interest (ROIs), and the Ktrans and BF values for each ROI were recorded separately. Based on pathological information and the most recent AJCC staging criteria, patients were divided into low T stage groups = T_1-2 and high T stage groups = T_3-4, low N stage groups = N_0-1 and high N stage groups = N_2-3, and low AJCC stage group = stage I-II and high AJCC stage group = stage III-IV. The association between the Ktrans_t and BF parameters and the T, N, and AJCC stages was compared using an independent sample t-test. Using a receiver operating characteristic (ROC) curve, the sensitivity, specificity, and AUC of Ktrans_t, BF_t, and their combined use in T and AJCC staging of NPC were investigated and assessed.

RESULT

The tumor-BF (BF_t) (t = - 4.905, P < 0.001) and tumor-Ktrans (Ktrans_t) (t = - 3.113, P = 0.003) in the high T stage group were significantly higher than those in the low T stage group. The Ktrans_t in the high N stage group was significantly higher than that in the low N stage group (t = - 2.071, P = 0.042). The BF_t (t = - 3.949, P < 0.001) and Ktrans_t (t = - 4.467, P < 0.001) in the high AJCC stage group were significantly higher than those in the low AJCC stage group. BF_t was moderately positively correlated with the T stage (r = 0.529, P < 0.001) and AJCC stage (r = 0.445, P < 0.001). Ktrans_t was moderately positively correlated with T staging (r = 0.368), N staging (r = 0.254), and AJCC staging (r = 0.411). There was also a positive correlation between BF and Ktrans in gross tumor volume (GTV) (r = 0.540, P < 0.001), parotid (r = 0.323, P < 0.009) and lateral pterygoid muscle (r = 0.445, P < 0.001). The sensitivity of the combined application of Ktrans_t and BF_t for AJCC staging increased from 76.5 and 78.4 to 86.3%, and the AUC value increased from 0.795 and 0.819 to 0.843, respectively.

CONCLUSION

Combining Ktrans and BF measures may make it possible to identify the clinical stages in NPC patients.

3D Amide Proton Transfer-Weighted Imaging for Grading Glioma and Correlating IDH Mutation Status: Added Value to 3D Pseudocontinuous Arterial Spin Labelling Perfusion

PURPOSE

The goal of this study was to evaluate the diagnostic performance of 3D amide proton transfer-weighted (3D-APTW) imaging and 3D pseudocontinuous arterial spin labelling (3D-pCASL) alone and in combination in grading gliomas (low-grade glioma (LGG) vs. high-grade glioma (HGG)) and correlating isocitrate dehydrogenase (IDH) mutation status.

PROCEDURES

Preoperatively, 81 patients with pathologically confirmed gliomas underwent 3.0-T magnetic resonance imaging (MRI) examinations. The APTW, relative APTW (rAPTW), cerebral blood flow (CBF), and relative CBF (rCBF) values were calculated to evaluate the solid components of the tumours. The MRI parameters were compared in the classification of gliomas by independent- and paired-samples t tests. A receiver operating characteristic (ROC) curve was constructed, and the area under the ROC curve (AUC) was calculated to assess the diagnostic performance of each parameter and the combination of the rAPTW and rCBF values.

RESULTS

Patients with HGG showed significantly higher APTW, rAPTW, CBF, and rCBF values than those with LGG (all p < 0.001). In the ROC curve analysis, the AUC of rAPTW was the highest at 0.90. By adding the rAPTW signal to the rCBF values, the diagnostic ability of the combined parameters improved from 0.90 to 0.96. The rAPTW value yielded the highest AUC (0.92) in correlating the IDH mutation status, and the diagnostic ability improved to 0.96 by adding it to the rCBF value.

CONCLUSION

3D-APTW imaging combined with 3D-pCASL imaging may be used to aid assessment of grading glioma and IDH mutation status.

Differentiation of true progression from treatment response in high-grade glioma treated with chemoradiation: a comparison study of 3D-APTW and 3D-PcASL imaging and DWI

PURPOSE

To assess and compare the diagnostic performance of 3D amide proton-transfer-weighted (3D-APTW) imaging, 3D pseudocontinuous arterial spin-labeling (3D-PcASL) imaging, and diffusion-weighted imaging in distinguishing true progression (TP) from treatment response (TR) in posttreatment malignant glioma patients.

MATERIALS AND METHODS

Forty-eight patients with suspected tumor recurrence were prospectively enrolled. Histological or longitudinal routine MRI follow-up over six months was assessed to confirm lesion type. The apparent diffusion coefficient (ADC), relative APTW_max (rAPTW), and relative CBF_max values (rCBF) were measured in lesions with enhancing regions on post-gadolinium T₁ -weighted MRI. MRI parameters between the TP and TR groups were compared using Student's t tests. In addition, a receiver operating characteristic (ROC) curve was constructed, and the area under the ROC curve (AUC) was calculated to assess the differentiation diagnostic performance of each parameter.

RESULTS

The TP group showed a significantly higher rAPTW and rCBF than the TR group; the AUCs of rAPTW and rCBF to distinguish between TP and TR were 0.911 (with sensitivity of 90.3% and specificity of 82.4%) and 0.852 (with sensitivity of 80.6% and specificity of 82.4%), respectively. By adding the rAPTW values to rCBF values, the diagnostic ability was improved from 0.852 to 0.951. ADC showed no significant differences between the TP and TR groups, with an AUC lower than 0.70.

CONCLUSION

Both 3D-PcASL and 3D-APTW imaging could distinguish TP from TR, and 3D-APTW had a better diagnostic performance. Combining the rAPTW values and rCBF values achieved a better diagnostic performance.

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.

Advanced Neuroimaging Approaches to Pediatric Brain Tumors

Simple Summary

After leukemias, brain tumors are the most common cancers in children, and early, accurate diagnosis is critical to improve patient outcomes. Beyond the conventional imaging methods of computed tomography (CT) and magnetic resonance imaging (MRI), advanced neuroimaging techniques capable of both structural and functional imaging are moving to the forefront to improve the early detection and differential diagnosis of tumors of the central nervous system. Here, we review recent developments in neuroimaging techniques for pediatric brain tumors.

Abstract

Central nervous system tumors are the most common pediatric solid tumors; they are also the most lethal. Unlike adults, childhood brain tumors are mostly primary in origin and differ in type, location and molecular signature. Tumor characteristics (incidence, location, and type) vary with age. Children present with a variety of symptoms, making early accurate diagnosis challenging. Neuroimaging is key in the initial diagnosis and monitoring of pediatric brain tumors. Conventional anatomic imaging approaches (computed tomography (CT) and magnetic resonance imaging (MRI)) are useful for tumor detection but have limited utility differentiating tumor types and grades. Advanced MRI techniques (diffusion-weighed imaging, diffusion tensor imaging, functional MRI, arterial spin labeling perfusion imaging, MR spectroscopy, and MR elastography) provide additional and improved structural and functional information. Combined with positron emission tomography (PET) and single-photon emission CT (SPECT), advanced techniques provide functional information on tumor metabolism and physiology through the use of radiotracer probes. Radiomics and radiogenomics offer promising insight into the prediction of tumor subtype, post-treatment response to treatment, and prognostication. In this paper, a brief review of pediatric brain cancers, by type, is provided with a comprehensive description of advanced imaging techniques including clinical applications that are currently utilized for the assessment and evaluation of pediatric brain tumors.

Dynamic susceptibility-contrast magnetic resonance imaging with contrast agent leakage correction aids in predicting grade in pediatric brain tumours: a multicenter study

BACKGROUND

Relative cerebral blood volume (rCBV) measured using dynamic susceptibility-contrast MRI can differentiate between low- and high-grade pediatric brain tumors. Multicenter studies are required for translation into clinical practice.

OBJECTIVE

We compared leakage-corrected dynamic susceptibility-contrast MRI perfusion parameters acquired at multiple centers in low- and high-grade pediatric brain tumors.

MATERIALS AND METHODS

Eighty-five pediatric patients underwent pre-treatment dynamic susceptibility-contrast MRI scans at four centers. MRI protocols were variable. We analyzed data using the Boxerman leakage-correction method producing pixel-by-pixel estimates of leakage-uncorrected (rCBVuncorr) and corrected (rCBVcorr) relative cerebral blood volume, and the leakage parameter, K2. Histological diagnoses were obtained. Tumors were classified by high-grade tumor. We compared whole-tumor median perfusion parameters between low- and high-grade tumors and across tumor types.

RESULTS

Forty tumors were classified as low grade, 45 as high grade. Mean whole-tumor median rCBVuncorr was higher in high-grade tumors than low-grade tumors (mean ± standard deviation [SD] = 2.37±2.61 vs. -0.14±5.55; P<0.01). Average median rCBV increased following leakage correction (2.54±1.63 vs. 1.68±1.36; P=0.010), remaining higher in high-grade tumors than low grade-tumors. Low-grade tumors, particularly pilocytic astrocytomas, showed T1-dominant leakage effects; high-grade tumors showed T2*-dominance (mean K2=0.017±0.049 vs. 0.002±0.017). Parameters varied with tumor type but not center. Median rCBVuncorr was higher (mean = 1.49 vs. 0.49; P=0.015) and K2 lower (mean = 0.005 vs. 0.016; P=0.013) in children who received a pre-bolus of contrast agent compared to those who did not. Leakage correction removed the difference.

CONCLUSION

Dynamic susceptibility-contrast MRI acquired at multiple centers helped distinguish between children's brain tumors. Relative cerebral blood volume was significantly higher in high-grade compared to low-grade tumors and differed among common tumor types. Vessel leakage correction is required to provide accurate rCBV, particularly in low-grade enhancing tumors.

Arterial Spin Labeling for Pediatric Central Nervous System Diseases: Techniques and Clinical Applications

Dynamic susceptibility contrast (DSC) and arterial spin labeling (ASL) are techniques used to evaluate brain perfusion using MRI. DSC requires dynamic image acquisition with a rapid administration of gadolinium-based contrast agent. In contrast, ASL obtains brain perfusion information using magnetically labeled blood water as an endogenous tracer. For the evaluation of brain perfusion in pediatric neurological diseases, ASL has a significant advantage compared to DSC, CT, and single-photon emission CT/positron emission tomography because of the lack of radiation exposure and contrast agent administration. However, in ASL, optimization of several parameters, including the type of labeling, image acquisition, background suppression, and postlabeling delay, is required, because they have a significant effect on the quantification of cerebral blood flow (CBF).In this article, we first review recent technical developments of ASL and age-dependent physiological characteristics in pediatric brain perfusion. We then review the clinical implementation of ASL in pediatric neurological diseases, including vascular diseases, brain tumors, acute encephalopathy with biphasic seizure and late reduced diffusion (AESD), and migraine. In moyamoya disease, ASL can be used for brain perfusion and vessel assessment in pre- and post-treatment. In arteriovenous malformations, ASL is sensitive to detect small degrees of shunt. Furthermore, in vascular diseases, the implementation of ASL-based time-resolved MR angiography is described. In neoplasms, ASL-derived CBF has a high diagnostic accuracy for differentiation between low- and high-grade pediatric brain tumors. In AESD and migraine, ASL may allow for accurate early diagnosis and provide pathophysiological information.

Cerebral Blood Flow of the Frontal Lobe in Untreated Children with Trigonocephaly versus Healthy Controls: An Arterial Spin Labeling Study

BACKGROUND

Craniofacial surgery is the standard treatment for children with moderate to severe trigonocephaly. The added value of surgery to release restriction of the frontal lobes is unproven, however. In this study, the authors aim to address the hypothesis that the frontal lobe perfusion is not restricted in trigonocephaly patients by investigating cerebral blood flow.

METHODS

Between 2018 and 2020, trigonocephaly patients for whom a surgical correction was considered underwent magnetic resonance imaging brain studies with arterial spin labeling to measure cerebral perfusion. The mean value of cerebral blood flow in the frontal lobe was calculated for each subject and compared to that of healthy controls.

RESULTS

Magnetic resonance imaging scans of 36 trigonocephaly patients (median age, 0.5 years; interquartile range, 0.3; 11 female patients) were included and compared to those of 16 controls (median age, 0.83 years; interquartile range, 0.56; 10 female patients). The mean cerebral blood flow values in the frontal lobe of the trigonocephaly patients (73.0 ml/100 g/min; SE, 2.97 ml/100 g/min) were not significantly different in comparison to control values (70.5 ml/100 g/min; SE, 4.45 ml/100 g/min; p = 0.65). The superior, middle, and inferior gyri of the frontal lobe showed no significant differences either.

CONCLUSIONS

The authors' findings suggest that the frontal lobes of trigonocephaly patients aged less than 18 months have a normal cerebral blood flow before surgery. In addition to the very low prevalence of papilledema or impaired skull growth previously reported, this finding further supports the authors' hypothesis that craniofacial surgery for trigonocephaly is rarely indicated for signs of raised intracranial pressure or restricted perfusion for patients younger than 18 months.

CLINICAL QUESTION/LEVEL OF EVIDENCE

Risk, II.

3D pCASL-perfusion in preoperative assessment of brain gliomas in large cohort of patients

The aim of the study was to evaluate the role of pseudocontinuous arterial spin labeling perfusion (pCASL-perfusion) in preoperative assessment of cerebral glioma grades. The study group consisted of 253 patients, aged 7-78 years with supratentorial gliomas (65 low-grade gliomas (LGG), 188 high-grade gliomas (HGG)). We used 3D pCASL-perfusion for each patient in order to calculate the tumor blood flow (TBF). We obtained maximal tumor blood flow (maxTBF) in small regions of interest (30 ± 10 mm²) and then normalized absolute maximum tumor blood flow (nTBF) to that of the contralateral normal-appearing white matter of the centrum semiovale. MaxTBF and nTBF values significantly differed between HGG and LGG groups (p < 0.001), as well as between patient groups separated by the grades (grade II vs. grade III) (p < 0.001). Moreover, we performed ROC-analysis which demonstrated high sensitivity and specificity in differentiating between HGG and LGG. We found significant differences for maxTBF and nTBF between grade III and IV gliomas, however, ROC-analysis showed low sensitivity and specificity. We did not observe a significant difference in TBF for astrocytomas and oligodendrogliomas. Our study demonstrates that 3D pCASL-perfusion as an effective diagnostic tool for preoperative differentiation of glioma grades.

The role of artificial intelligence in paediatric neuroradiology

Imaging plays a fundamental role in the managing childhood neurologic, neurosurgical and neuro-oncological disease. Employing multi-parametric MRI techniques, such as spectroscopy and diffusion- and perfusion-weighted imaging, to the radiophenotyping of neuroradiologic conditions is becoming increasingly prevalent, particularly with radiogenomic analyses correlating imaging characteristics with molecular biomarkers of disease. However, integration into routine clinical practice remains elusive. With modern multi-parametric MRI now providing additional data beyond anatomy, informing on histology, biology and physiology, such metric-rich information can present as information overload to the treating radiologist and, as such, information relevant to an individual case can become lost. Artificial intelligence techniques are capable of modelling the vast radiologic, biological and clinical datasets that accompany childhood neurologic disease, such that this information can become incorporated in upfront prognostic modelling systems, with artificial intelligence techniques providing a plausible approach to this solution. This review examines machine learning approaches than can be used to underpin such artificial intelligence applications, with exemplars for each machine learning approach from the world literature. Then, within the specific use case of paediatric neuro-oncology, we examine the potential future contribution for such artificial intelligence machine learning techniques to offer solutions for patient care in the form of decision support systems, potentially enabling personalised medicine within this domain of paediatric radiologic practice.

Advanced Magnetic Resonance Imaging in Pediatric Glioblastomas

The shortly upcoming 5th edition of the World Health Organization Classification of Tumors of the Central Nervous System is bringing extensive changes in the terminology of diffuse high-grade gliomas (DHGGs). Previously "glioblastoma," as a descriptive entity, could have been applied to classify some tumors from the family of pediatric or adult DHGGs. However, now the term "glioblastoma" has been divested and is no longer applied to tumors in the family of pediatric types of DHGGs. As an entity, glioblastoma remains, however, in the family of adult types of diffuse gliomas under the insignia of "glioblastoma, IDH-wildtype." Of note, glioblastomas still can be detected in children when glioblastoma, IDH-wildtype is found in this population, despite being much more common in adults. Despite the separation from the family of pediatric types of DHGGs, what was previously labeled as "pediatric glioblastomas" still remains with novel labels and as new entities. As a result of advances in molecular biology, most of the previously called "pediatric glioblastomas" are now classified in one of the four family members of pediatric types of DHGGs. In this review, the term glioblastoma is still apocryphally employed mainly due to its historical relevance and the paucity of recent literature dealing with the recently described new entities. Therefore, "glioblastoma" is used here as an umbrella term in the attempt to encompass multiple entities such as astrocytoma, IDH-mutant (grade 4); glioblastoma, IDH-wildtype; diffuse hemispheric glioma, H3 G34-mutant; diffuse pediatric-type high-grade glioma, H3-wildtype and IDH-wildtype; and high grade infant-type hemispheric glioma. Glioblastomas are highly aggressive neoplasms. They may arise anywhere in the developing central nervous system, including the spinal cord. Signs and symptoms are non-specific, typically of short duration, and usually derived from increased intracranial pressure or seizure. Localized symptoms may also occur. The standard of care of "pediatric glioblastomas" is not well-established, typically composed of surgery with maximal safe tumor resection. Subsequent chemoradiation is recommended if the patient is older than 3 years. If younger than 3 years, surgery is followed by chemotherapy. In general, "pediatric glioblastomas" also have a poor prognosis despite surgery and adjuvant therapy. Magnetic resonance imaging (MRI) is the imaging modality of choice for the evaluation of glioblastomas. In addition to the typical conventional MRI features, i.e., highly heterogeneous invasive masses with indistinct borders, mass effect on surrounding structures, and a variable degree of enhancement, the lesions may show restricted diffusion in the solid components, hemorrhage, and increased perfusion, reflecting increased vascularity and angiogenesis. In addition, magnetic resonance spectroscopy has proven helpful in pre- and postsurgical evaluation. Lastly, we will refer to new MRI techniques, which have already been applied in evaluating adult glioblastomas, with promising results, yet not widely utilized in children.

Noncontrast Pediatric Brain Perfusion: Arterial Spin Labeling and Intravoxel Incoherent Motion

Noncontrast magnetic resonance imaging techniques for measuring brain perfusion include arterial spin labeling (ASL) and intravoxel incoherent motion (IVIM). These techniques provide noninvasive and repeatable assessment of cerebral blood flow or cerebral blood volume without the need for intravenous contrast. This article discusses the technical aspects of ASL and IVIM with a focus on normal physiologic variations, technical parameters, and artifacts. Multiple pediatric clinical applications are presented, including tumors, stroke, vasculopathy, vascular malformations, epilepsy, migraine, trauma, and inflammation.

Combining multi-site magnetic resonance imaging with machine learning predicts survival in pediatric brain tumors

Brain tumors represent the highest cause of mortality in the pediatric oncological population. Diagnosis is commonly performed with magnetic resonance imaging. Survival biomarkers are challenging to identify due to the relatively low numbers of individual tumor types. 69 children with biopsy-confirmed brain tumors were recruited into this study. All participants had perfusion and diffusion weighted imaging performed at diagnosis. Imaging data were processed using conventional methods, and a Bayesian survival analysis performed. Unsupervised and supervised machine learning were performed with the survival features, to determine novel sub-groups related to survival. Sub-group analysis was undertaken to understand differences in imaging features. Survival analysis showed that a combination of diffusion and perfusion imaging were able to determine two novel sub-groups of brain tumors with different survival characteristics (p < 0.01), which were subsequently classified with high accuracy (98%) by a neural network. Analysis of high-grade tumors showed a marked difference in survival (p = 0.029) between the two clusters with high risk and low risk imaging features. This study has developed a novel model of survival for pediatric brain tumors. Tumor perfusion plays a key role in determining survival and should be considered as a high priority for future imaging protocols.

European Society for Paediatric Oncology (SIOPE) MRI guidelines for imaging patients with central nervous system tumours

INTRODUCTION

Standardisation of imaging acquisition is essential in facilitating multicentre studies related to childhood CNS tumours. It is important to ensure that the imaging protocol can be adopted by centres with varying imaging capabilities without compromising image quality.

MATERIALS AND METHOD

An imaging protocol has been developed by the Brain Tumour Imaging Working Group of the European Society for Paediatric Oncology (SIOPE) based on consensus among its members, which consists of neuroradiologists, imaging scientists and paediatric neuro-oncologists. This protocol has been developed to facilitate SIOPE led studies and regularly reviewed by the imaging working group.

RESULTS

The protocol consists of essential MRI sequences with imaging parameters for 1.5 and 3 Tesla MRI scanners and a set of optional sequences that can be used in appropriate clinical settings. The protocol also provides guidelines for early post-operative imaging and surveillance imaging. The complementary use of multimodal advanced MRI including diffusion tensor imaging (DTI), MR spectroscopy and perfusion imaging is encouraged, and optional guidance is provided in this publication.

CONCLUSION

The SIOPE brain tumour imaging protocol will enable consistent imaging across multiple centres involved in paediatric CNS tumour studies.

MRI biomarkers in neuro-oncology

The central role of MRI in neuro-oncology is undisputed. The technique is used, both in clinical practice and in clinical trials, to diagnose and monitor disease activity, support treatment decision-making, guide the use of focused treatments and determine response to treatment. Despite recent substantial advances in imaging technology and image analysis techniques, clinical MRI is still primarily used for the qualitative subjective interpretation of macrostructural features, as opposed to quantitative analyses that take into consideration multiple pathophysiological features. However, the field of quantitative imaging and imaging biomarker development is maturing. The European Imaging Biomarkers Alliance (EIBALL) and Quantitative Imaging Biomarkers Alliance (QIBA) are setting standards for biomarker development, validation and implementation, as well as promoting the use of quantitative imaging and imaging biomarkers by demonstrating their clinical value. In parallel, advanced imaging techniques are reaching the clinical arena, providing quantitative, commonly physiological imaging parameters that are driving the discovery, validation and implementation of quantitative imaging and imaging biomarkers in the clinical routine. Additionally, computational analysis techniques are increasingly being used in the research setting to convert medical images into objective high-dimensional data and define radiomic signatures of disease states. Here, I review the definition and current state of MRI biomarkers in neuro-oncology, and discuss the clinical potential of quantitative image analysis techniques.

Classification of paediatric brain tumours by diffusion weighted imaging and machine learning

To determine if apparent diffusion coefficients (ADC) can discriminate between posterior fossa brain tumours on a multicentre basis. A total of 124 paediatric patients with posterior fossa tumours (including 55 Medulloblastomas, 36 Pilocytic Astrocytomas and 26 Ependymomas) were scanned using diffusion weighted imaging across 12 different hospitals using a total of 18 different scanners. Apparent diffusion coefficient maps were produced and histogram data was extracted from tumour regions of interest. Total histograms and histogram metrics (mean, variance, skew, kurtosis and 10th, 20th and 50th quantiles) were used as data input for classifiers with accuracy determined by tenfold cross validation. Mean ADC values from the tumour regions of interest differed between tumour types, (ANOVA P < 0.001). A cut off value for mean ADC between Ependymomas and Medulloblastomas was found to be of 0.984 × 10⁻³ mm² s⁻¹ with sensitivity 80.8% and specificity 80.0%. Overall classification for the ADC histogram metrics were 85% using Naïve Bayes and 84% for Random Forest classifiers. The most commonly occurring posterior fossa paediatric brain tumours can be classified using Apparent Diffusion Coefficient histogram values to a high accuracy on a multicentre basis.

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

PURPOSE

Dynamic susceptibility contrast (DSC) and arterial spin labeling (ASL) perfusion MRI are applied in pediatric brain tumor grading, but their value for clinical daily practice remains unclear. We explored the ability of ASL and DSC to distinguish low- and high-grade lesions, in an unselected cohort of pediatric cerebral tumors.

METHODS

We retrospectively compared standard perfusion outcomes including blood volume, blood flow, and time parameters from DSC and ASL at 1.5T or 3T MRI scanners of 46 treatment-naive patients by drawing ROI via consensus by two neuroradiologists on the solid portions of every tumor. The discriminant abilities of perfusion parameters were evaluated by receiver operating characteristic (ROC) over the entire cohort and depending on the tumor location and the magnetic field.

RESULTS

ASL and DSC parameters showed overall low to moderate performances to distinguish low- and high-grade tumors (area under the curve: between 0.548 and 0.697). Discriminant abilities were better for tumors located supratentorially (AUC between 0.777 and 0.810) than infratentorially, where none of the metrics reached significance. We observed a better differentiation between low- and high-grade cancers at 3T than at 1.5-T. For infratentorial tumors, time parameters from DSC performed better than the commonly used metrics (AUC ≥ 0.8).

CONCLUSION

DSC and ASL show moderate abilities to distinguish low- and high-grade brain tumors in an unselected cohort. Absolute value of K2, TMAX, tMIP, and normalized value of TMAX of the DSC appear as an alternative to conventional parameters for infratentorial tumors. Three Tesla evaluation should be favored over 1.5-Tesla.

Advancements in Neuroimaging to Unravel Biological and Molecular Features of Brain Tumors

Simple Summary

Advanced neuroimaging is gaining increasing relevance for the characterization and the molecular profiling of brain tumor tissue. On one hand, for some tumor types, the most widespread advanced techniques, investigating diffusion and perfusion features, have been proven clinically feasible and rather robust for diagnosis and prognosis stratification. In addition, 2-hydroxyglutarate spectroscopy, for the first time, offers the possibility to directly measure a crucial molecular marker. On the other hand, numerous innovative approaches have been explored for a refined evaluation of tumor microenvironments, particularly assessing microstructural and microvascular properties, and the potential applications of these techniques are vast and still to be fully explored.

Abstract

In recent years, the clinical assessment of primary brain tumors has been increasingly dependent on advanced magnetic resonance imaging (MRI) techniques in order to infer tumor pathophysiological characteristics, such as hemodynamics, metabolism, and microstructure. Quantitative radiomic data extracted from advanced MRI have risen as potential in vivo noninvasive biomarkers for predicting tumor grades and molecular subtypes, opening the era of “molecular imaging” and radiogenomics. This review presents the most relevant advancements in quantitative neuroimaging of advanced MRI techniques, by means of radiomics analysis, applied to primary brain tumors, including lower-grade glioma and glioblastoma, with a special focus on peculiar oncologic entities of current interest. Novel findings from diffusion MRI (dMRI), perfusion-weighted imaging (PWI), and MR spectroscopy (MRS) are hereby sifted in order to evaluate the role of quantitative imaging in neuro-oncology as a tool for predicting molecular profiles, stratifying prognosis, and characterizing tumor tissue microenvironments. Furthermore, innovative technological approaches are briefly addressed, including artificial intelligence contributions and ultra-high-field imaging new techniques. Lastly, after providing an overview of the advancements, we illustrate current clinical applications and future perspectives.

Hybrid PET-MRI Imaging in Paediatric and TYA Brain Tumours: Clinical Applications and Challenges

(1) Background: Standard magnetic resonance imaging (MRI) remains the gold standard for brain tumour imaging in paediatric and teenage and young adult (TYA) patients. Combining positron emission tomography (PET) with MRI offers an opportunity to improve diagnostic accuracy. (2) Method: Our single-centre experience of ¹⁸F-fluorocholine (FCho) and ¹⁸fluoro-L-phenylalanine (FDOPA) PET–MRI in paediatric/TYA neuro-oncology patients is presented. (3) Results: Hybrid PET–MRI shows promise in the evaluation of gliomas and germ cell tumours in (i) assessing early treatment response and (ii) discriminating tumour from treatment-related changes. (4) Conclusions: Combined PET–MRI shows promise for improved diagnostic and therapeutic assessment in paediatric and TYA brain tumours.

Quantitative MRI demonstrates abnormalities of the third ventricle subventricular zone in neurofibromatosis type-1 and sporadic paediatric optic pathway glioma

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MRI provides supporting evidence of third ventricle subventricular involvement in OPG.

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Third ventricle subventricular zone ADC and CBF differs between NF1 and sporadic OPG.

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Third ventricle subventricular zone ADC correlates with vision in sporadic OPG.

Background

The subventricular zone of the third ventricle (TVZ) is a germinal stem cell niche, identified as the possible location of optic pathway glioma (OPG) cell origin. Paediatric OPGs are predominantly diagnosed as low-grade astrocytomas, which are either sporadic or are associated with neurofibromatosis type-1 (NF1). These tumours often cause a significant impairment to visual acuity (VA). Infiltrative/invasive tumour activity is associated with increased apparent diffusion coefficient (ADC) and cerebral blood flow (CBF). This study aimed to determine whether TVZ imaging features differed between sporadic-OPG, NF1-OPG and controls, and whether the ADC and CBF profile at the germinal stem cell niche (the TVZ) correlated with the primary outcome of VA.

Methods

ADC and CBF MRI data were acquired from 30 paediatric OPG patients (median age 6 years; range 8 months–17 years), along with VA measurements, during clinical surveillance of their tumour. Values for mean ADC and maximum CBF were measured at the TVZ, and normalized to normal-appearing grey matter. These values were compared between the two OPG groups and the healthy control subjects, and multivariate linear regression was used to test the linear association between these values and patient’s VA.

Results

In the TVZ, normalized mean ADC was higher in NF1-associated OPG patients (N = 15), compared to both sporadic OPG patients (N = 15; p = 0.010) and healthy controls (N = 14; p < 0.001). In the same region, normalized maximum CBF was higher in sporadic OPG patients compared to both NF1-OPG patients (p = 0.016) and healthy controls (p < 0.001). In sporadic OPG patients only, normalized mean ADC in the TVZ was significantly correlated with visual acuity (R² = 0.41, p = 0.019). No significant correlations were found between TVZ CBF and ADC values and visual acuity in the NF1-associated OPG patients.

Conclusion

Quantitative MRI detects TVZ abnormalities in both sporadic and NF1-OPG patients, and identifies TVZ features that differentiate the two. TVZ features may be useful MRI markers of interest in future predictive studies involving sporadic OPG.

Updates in Pediatric Malignant Gliomas

Malignant gliomas constitute a smaller portion of brain tumors in children compared with adults. Nevertheless, they can be devastating tumors with poor prognosis. Recent advances and improved understanding of the genetic and molecular characterization of pediatric brain tumors, including those of malignant gliomas, have led to the reclassification of many pediatric brain tumors and new entities have been defined. In this paper, we will present some of the more recent characterization and pertinent changes in pediatric high-grade gliomas, along with the conventional and advanced imaging features associated with these entities. Implications of the recent changes in pediatric malignant glioma classifications will also be discussed.

Combination of diffusion-weighted imaging and arterial spin labeling at 3.0 T for the clinical staging of nasopharyngeal carcinoma

PURPOSE

To probe the utility of diffusion-weighted imaging (DWI) and 3D arterial spin labeling (ASL) in assessing the clinical stage of nasopharyngeal carcinoma (NPC).

MATERIALS AND METHODS

This prospective study included sixty-five newly diagnosed NPC patients who underwent DWI and 3D ASL scans on a 3.0-T magnetic resonance imaging (MRI) system. The apparent diffusion coefficient (ADC) and the tumor blood flow (TBF) of NPC were measured. Tumors were classified as low or high T, N and American Joint Committee on Cancer (AJCC) stages. Student's t-test was used to evaluate the differences between tumors with low and high clinical stages. Pearson correlation analyses were performed to determine the correlation between MRI parameters and clinical stages. Receiver operating characteristic (ROC) curves were then used to evaluate diagnostic capability.

RESULTS

High T stage (T3/4) NPC showed significantly lower ADC_min (P = 0.000) and higher TBF_max (P = 0.003) and TBF_mean (P = 0.008) values than low T stage (T1/2) NPC. High N stage (N2/3) NPC showed significantly lower ADC_min values (P = 0.023) than low N stage (N0/1) NPC. High AJCC stage (III/IV) NPC showed significantly lower ADC_min (P = 0.000) and higher TBF_max (P = 0.005) and TBF_mean (P = 0.011) values than low AJCC stage (I/II) NPC. ADC_min values showed moderate negative correlations with T stage (r = -0.512, P = 0.000), N stage (r = -0.281, P = 0.023), and AJCC stage (r = -0.494, P = 0.000). TBF_max values showed moderate positive correlations with T stage (r = 0.369, P = 0.003) and AJCC stage (r = 0.346, P = 0.005). Compared with ADC_min and TBF_max alone, the combination of ADC_min and TBF_max improved the accuracy from 72.3% and 75.4% to 78.5%, respectively, for T staging, as well as from 72.3% and 69.2% to 83.1% for AJCC staging.

CONCLUSIONS

ADC_min and TBF_max values in patients with NPC could help evaluate clinical stages. ADC_min and TBF_max values combined could clearly improve the accuracy in the assessment of AJCC stage.

Distinguishing between paediatric brain tumour types using multi-parametric magnetic resonance imaging and machine learning: A multi-site study

The imaging and subsequent accurate diagnosis of paediatric brain tumours presents a radiological challenge, with magnetic resonance imaging playing a key role in providing tumour specific imaging information. Diffusion weighted and perfusion imaging are commonly used to aid the non-invasive diagnosis of children's brain tumours, but are usually evaluated by expert qualitative review. Quantitative studies are mainly single centre and single modality. The aim of this work was to combine multi-centre diffusion and perfusion imaging, with machine learning, to develop machine learning based classifiers to discriminate between three common paediatric tumour types. The results show that diffusion and perfusion weighted imaging of both the tumour and whole brain provide significant features which differ between tumour types, and that combining these features gives the optimal machine learning classifier with >80% predictive precision. This work represents a step forward to aid in the non-invasive diagnosis of paediatric brain tumours, using advanced clinical imaging.