A qualitative comparison of arterial spin labelling and dynamic susceptibility contrast MRI in 52 children with a range of neurological conditions

Metabolic imaging in recurrent gliomas: comparative performance of 18F-FDOPA, 18F-fluorocholine and 18F-FDG PET/CT

PURPOSE

The aim of this study was to directly evaluate glucose, amino-acid and membrane metabolism in tumor cells for diagnosis and prognostication of recurrent gliomas.

METHODS

Fifty-five patients (median age = 36 years; 33 men) with histologically proven gliomas and suspected recurrence were prospectively recruited and underwent 18F-FDG (Fluorodeoxyglucose), 18F-FDOPA (fluorodopa) and 18F-Fluorocholine-PET/CT. Images were evaluated by two physicians visually and quantitatively [lesion-SUVmax, tumor (T) to gray-matter (G) and metabolically-active tumor volumes (MTV)]. After median follow-up of 51.5 months, recurrence was diagnosed in 49 patients. Thirty-one patients died with a median survival of 14 months.

RESULTS

Diagnostic-accuracies for 18F-FDOPA, 18F-Fluorocholine,18F-FDG and contrast-enhanced-MRI were 92.7% (95% CI 82.7-97.1), 81.8% (69.7-89.8), 45.5% (33.0-58.5) and 44.7% (30.2-60.3), respectively. Among the 20 lesions, missed by MRI; 18F-FDOPA, 18F-Fluorocholine and 18F-FDG were able to detect 19, 14 and 4 lesions. Corresponding area-under-the-curves (T/G ratios) were 0.817 (0.615-1.000), 0.850 (0.736-0.963) and 0.814 (0.658-0.969), when differentiating recurrence from treatment-induced changes. In univariate-survival-analysis, 18F-FDOPA-T/G, visually detectable recurrence in 18F-FDG, 18F-FDOPA-MTV, cell-lineage and treatment-type were significant parameters. In Multivariate-Cox-regression analysis, 18F-FDOPA-MTV [HR = 1.009 (1.001-1.017); P  = 0.024 (~0.9% increase in hazard for every mL increase of MTV)] and cell-lineage [3.578 (1.447-8.846); P  = 0.006] remained significant. 18F-FDOPA-MTV cutoff <29.59 mL predicted survival higher than 2 years. At cutoff ≥29.59 mL, HR at 2 years was 2.759 (1.310-5.810).

CONCLUSION

18F-FDOPA-PET/CT can diagnose recurrence with high accuracy and MTV predicts survival. 18F-Fluorocholine is a good alternative. Higher 18F-FDG uptake is an adverse prognostic indicator.

Cerebral Hemodynamic and Metabolic Abnormalities in Neonatal Hypocalcemia: Findings from Advanced MRI

BACKGROUND AND PURPOSE

Neonatal hypocalcemia is the most common metabolic disorder, and whether asymptomatic disease should be treated with calcium supplements remains controversial. We aimed to quantify neonatal hypocalcemia's global CBF and cerebral metabolic rate of oxygen (CMRO2) using physiologic MR imaging and elucidate the pathophysiologic vulnerabilities of neonatal hypocalcemia.

MATERIALS AND METHODS

A total of 37 consecutive patients with neonatal hypocalcemia were enrolled. They were further divided into subgroups with and without structural MR imaging abnormalities, denoted as neonatal hypocalcemia-a (n = 24) and neonatal hypocalcemia-n (n = 13). Nineteen healthy neonates were enrolled as a control group. Brain physiologic parameters determined using phase-contrast MR imaging, T2-relaxation-under-spin-tagging MR imaging, and brain volume were compared between patients with neonatal hypocalcemia (their subgroups) and controls. Predictors for neonatal hypocalcemia-related brain injuries were identified using multivariate logistic regression analysis and expressed as ORs with 95% CIs.

RESULTS

Patients with neonatal hypocalcemia showed significantly lower CBF and CMRO2 compared with controls. Furthermore, the neonatal hypocalcemia-a subset (versus controls or neonatal hypocalcemia-n) had significantly lower CBF and CMRO2. There was no obvious difference in CBF and CMRO2 between the neonatal hypocalcemia-n subset and controls. CBF and CMRO2 were independently associated with neonatal hypocalcemia. The ORs were 0.80 (95% CI, 0.65-0.99) and 0.97 (95% CI, 0.89-1.05) for CBF and CMRO2, respectively.

CONCLUSIONS

Neonatal hypocalcemia with structural damage may exhibit lower hemodynamics and cerebral metabolism. CBF may be useful in assessing the need for calcium supplementation in asymptomatic neonatal hypocalcemia to prevent brain injury.

Applying machine learning classifiers to automate quality assessment of paediatric dynamic susceptibility contrast (DSC-) MRI data

OBJECTIVE

Investigate the performance of qualitative review (QR) for assessing dynamic susceptibility contrast (DSC-) MRI data quality in paediatric normal brain and develop an automated alternative to QR.

METHODS

1027 signal-time courses were assessed by Reviewer 1 using QR. 243 were additionally assessed by Reviewer 2 and % disagreements and Cohen's κ (κ) were calculated. The signal drop-to-noise ratio (SDNR), root mean square error (RMSE), full width half maximum (FWHM) and percentage signal recovery (PSR) were calculated for the 1027 signal-time courses. Data quality thresholds for each measure were determined using QR results. The measures and QR results trained machine learning classifiers. Sensitivity, specificity, precision, classification error and area under the curve from a receiver operating characteristic curve were calculated for each threshold and classifier.

RESULTS

Comparing reviewers gave 7% disagreements and κ = 0.83. Data quality thresholds of: 7.6 for SDNR; 0.019 for RMSE; 3 s and 19 s for FWHM; and 42.9 and 130.4% for PSR were produced. SDNR gave the best sensitivity, specificity, precision, classification error and area under the curve values of 0.86, 0.86, 0.93, 14.2% and 0.83. Random forest was the best machine learning classifier, giving sensitivity, specificity, precision, classification error and area under the curve of 0.94, 0.83, 0.93, 9.3% and 0.89.

CONCLUSION

The reviewers showed good agreement. Machine learning classifiers trained on signal-time course measures and QR can assess quality. Combining multiple measures reduces misclassification.

ADVANCES IN KNOWLEDGE

A new automated quality control method was developed, which trained machine learning classifiers using QR results.

Metabolic Imaging of Brain Tumor Recurrence

OBJECTIVE. Diagnosing brain tumor recurrence, especially with changes that occur after treatment, is a challenge. MRI has an exceptional structural resolution, which is important from the perspective of treatment planning. However, its reliability in diagnosing recurrence is relatively lower, when compared to metabolic imaging. The latter is more sensitive to the early changes associated with recurrence and relatively immune to confounding by treatment related changes. CONCLUSION. There is no one-stop shop for the diagnosis of recurrence in brain tumors. The sensitivity of metabolic imaging is not a substitute for the resolution of the MRI, making a multi-modal approach the only way forward.

Arterial Spin Labeling in Pediatric Neuroimaging

Perfusion imaging using arterial spin labeling noninvasively evaluates cerebral blood flow utilizing arterial blood water as endogenous tracer. It does not require the need of radiotracer or intravenous contrast and offers unique complimentary information in the imaging of pediatric brain. Common clinical applications include neonatal hypoxic ischemic encephalopathy, pediatric stroke and vascular malformations, epilepsy and brain tumors. Future applications may include evaluation of silent ischemia in sickle cell patients, monitor changes in intracranial pressure in hydrocephalus, provide additional insights in nonaccidental trauma and chronic traumatic brain injury (TBI) and in functional Magnetic resonance imaging (MRI). The purpose of this review article is to evaluate the technical considerations including pitfalls, physiological variations, clinical applications and future directions of arterial spin labeling imaging.

Cerebral blood flow in children with syndromic craniosynostosis: cohort arterial spin labeling studies

OBJECTIVE

In comparison with the general population, children with syndromic craniosynostosis (sCS) have abnormal cerebral venous anatomy and are more likely to develop intracranial hypertension. To date, little is known about the postnatal development change in cerebral blood flow (CBF) in sCS. The aim of this study was to determine CBF in patients with sCS, and compare findings with control subjects.

METHODS

A prospective cohort study of patients with sCS using MRI and arterial spin labeling (ASL) determined regional CBF patterns in comparison with a convenience sample of control subjects with identical MRI/ASL assessments in whom the imaging showed no cerebral/neurological pathology. Patients with SCS and control subjects were stratified into four age categories and compared using CBF measurements from four brain lobes, the cerebellum, supratentorial cortex, and white matter. In a subgroup of patients with sCS the authors also compared longitudinal pre- to postoperative CBF changes.

RESULTS

Seventy-six patients with sCS (35 female [46.1%] and 41 male [53.9%]), with a mean age of 4.5 years (range 0.2-19.2 years), were compared with 86 control subjects (38 female [44.2%] and 48 male [55.8%]), with a mean age of 6.4 years (range 0.1-17.8 years). Untreated sCS patients < 1 year old had lower CBF than control subjects. In older age categories, CBF normalized to values observed in controls. Graphical analyses of CBF by age showed that the normally expected peak in CBF during childhood, noted at 4 years of age in control subjects, occurred at 5-6 years of age in patients with sCS. Patients with longitudinal pre- to postoperative CBF measurements showed significant increases in CBF after surgery.

CONCLUSIONS

Untreated patients with sCS < 1 year old have lower CBF than control subjects. Following vault expansion, and with age, CBF in these patients normalizes to that of control subjects, but the usual physiological peak in CBF in childhood occurs later than expected.

Educational fMRI: From the Lab to the Classroom

Functional MRI (fMRI) findings hold many potential applications for education, and yet, the translation of fMRI findings to education has not flowed. Here, we address the types of fMRI that could better support applications of neuroscience to the classroom. This 'educational fMRI' comprises eight main challenges: (1) collecting artifact-free fMRI data in school-aged participants and in vulnerable young populations, (2) investigating heterogenous cohorts with wide variability in learning abilities and disabilities, (3) studying the brain under natural and ecological conditions, given that many practical topics of interest for education can be addressed only in ecological contexts, (4) depicting complex age-dependent associations of brain and behaviour with multi-modal imaging, (5) assessing changes in brain function related to developmental trajectories and instructional intervention with longitudinal designs, (6) providing system-level mechanistic explanations of brain function, so that useful individualized predictions about learning can be generated, (7) reporting negative findings, so that resources are not wasted on developing ineffective interventions, and (8) sharing data and creating large-scale longitudinal data repositories to ensure transparency and reproducibility of fMRI findings for education. These issues are of paramount importance to the development of optimal fMRI practices for educational applications.

Added value of arterial spin labeling magnetic resonance imaging in pediatric neuroradiology: pitfalls and applications

Arterial spin labeling is a noninvasive, non-gadolinium-dependent magnetic resonance imaging (MRI) technique to assess cerebral blood flow. It provides insight into both tissue metabolic activity and vascular supply. Because of its non-sensitivity toward blood-brain barrier leakage, arterial spin labeling is also more accurate in cerebral blood flow quantification than gadolinium-dependent methods. The aim of this pictorial essay is to promote the application of arterial spin labeling in pediatric neuroradiology. The authors provide information on artifacts and pitfalls as well as numerous fields of application based on pediatric cases.

Precision Medicine in Pediatric Neurooncology: A Review

Central nervous system tumors are the leading cause of cancer related death in children. Despite much progress in the field of pediatric neurooncology, modern combination treatment regimens often result in significant late effects, such as neurocognitive deficits, endocrine dysfunction, secondary malignancies, and a host of other chronic health problems. Precision medicine strategies applied to pediatric neurooncology target specific characteristics of individual patients' tumors to achieve maximal killing of neoplastic cells while minimizing unwanted adverse effects. Here, we review emerging trends and the current literature that have guided the development of new molecularly based classification schemas, promising diagnostic techniques, targeted therapies, and delivery platforms for the treatment of pediatric central nervous system tumors.