Radiological diagnosis of drop metastases from paediatric brain tumours using combination of 2D and 3D MRI sequences.

AIM: To evaluate spinal magnetic resonance imaging (MRI) examinations using a combination of two-dimensional (2D) and three-dimensional (3D) MRI sequences for diagnosis of drop metastases. MATERIALS AND METHODS: Fifty-five paediatric patients with primary brain tumours were evaluated for drop metastases at initial presentation using spinal MRI including sagittal 2D T1-weighted (W) contrast-enhanced (+C), axial 3D T1W+C volumetric interpolated breath-hold (VIBE), and sagittal 3D T2W SPACE (Sampling Perfection with Application optimised Contrasts using different flip angle Evolutions). RESULTS: The MRI false-negative rate was 4%, and cerebrospinal fluid (CSF) false-negative rate was 16% (p=0.07). The 3D T1W+C VIBE increased the number of drop metastases detected in 42% of patients. Drop metastases were more conspicuous in 25% of patients on 3D T2W SPACE. CONCLUSION: Spinal MRI examinations including 2D and 3D sequences demonstrate characteristics that may improve radiological diagnosis of drop metastases.

Contrast Leakage Patterns from Dynamic Susceptibility Contrast Perfusion MRI in the Grading of Primary Pediatric Brain Tumors.

BACKGROUND AND PURPOSE: The pattern of contrast leakage from DSC tissue signal intensity time curves have shown utility in distinguishing adult brain neoplasms, but has limited description in the literature for pediatric brain tumors. The purpose of this study is to evaluate the utility of grading pediatric brain tumors with this technique. MATERIALS AND METHODS: A retrospective review of tissue signal-intensity time curves from 63 pediatric brain tumors with preoperative DSC perfusion MR imaging was performed independently by 2 neuroradiologists. Tissue signal-intensity time curves were generated from ROIs placed in the highest perceived tumor relative CBV. The postbolus portion of the curve was independently classified as returning to baseline, continuing above baseline (T1-dominant contrast leakage), or failing to return to baseline (T2*-dominant contrast leakage). Interobserver agreement of curve classification was evaluated by using the Cohen κ. A consensus classification of curve type was obtained in discrepant cases, and the consensus classification was compared with tumor histology and World Health Organization grade. RESULTS: Tissue signal-intensity time curve classification concordance was 0.69 (95% CI, 0.54-0.84) overall and 0.79 (95% CI, 0.59-0.91) for a T1-dominant contrast leakage pattern. Twenty-five of 25 tumors with consensus T1-dominant contrast leakage were low-grade (positive predictive value, 1.0; 95% CI, 0.83-1.00). By comparison, tumors with consensus T2*-dominant contrast leakage or return to baseline were predominantly high-grade (10/15 and 15/23, respectively) with a high negative predictive value (1.0; 95% CI, 0.83-1.0). For pilomyxoid or pilocytic astrocytomas, a T1-dominant leak demonstrated high sensitivity (0.91; 95% CI, 0.70-0.98) and specificity (0.90, 95% CI, 0.75-0.97). CONCLUSIONS: There was good interobserver agreement in the classification of DSC perfusion tissue signal-intensity time curves for pediatric brain tumors, particularly for T1-dominant leakage. Among patients with pediatric brain tumors, a T1-dominant leakage pattern is highly specific for a low-grade tumor and demonstrates high sensitivity and specificity for pilocytic or pilomyxoid astrocytomas.

Diffusion imaging for tumor grading of supratentorial brain tumors in the first year of life.

BACKGROUND AND PURPOSE: Supratentorial tumors in the first year of life are typically large and heterogeneous at presentation, making differentiation of these CNS neoplasms on pre-operative imaging difficult. We hypothesize that the ADC value can reliably differentiate high- versus low-grade supratentorial tumors in this patient population. MATERIALS AND METHODS: A blinded review of ADC maps was performed on 19 patients with histologically proved supratentorial brain tumors diagnosed within the first year of life. Minimum ADC values obtained by region of interest from 2 neuroradiologists were averaged and compared with World Health Organization tumor grade. ADC values for the entire tumor were also obtained by use of a semi-automated histogram method and compared with World Health Organization tumor grade. Data were analyzed by use of Spearman ρ and Student t test, with a value of P < .05 considered statistically significant. RESULTS: For the manual ADC values, a significant negative correlation was found between the mean minimum ADC and tumor grade (P = .0016). A significant difference was found between the mean minimum ADC of the low-grade (1.14 × 10(-3) mm(2)/s ± 0.30) and high-grade tumors (0.64 × 10(-3) mm(2)/s ± 0.28) (P = .0018). Likewise, the semi-automated method demonstrated a significant negative correlation between the lowest 5th (P = .0002) and 10th (P = .0009) percentile individual tumor ADC values and tumor grade, a significant difference between the mean 5th and 10th percentile ADC values of the low-grade and high-grade groups (P = .0028), and a significant positive correlation with values obtained by manual region-of-interest placement (P < .000001). CONCLUSIONS: ADC maps can differentiate high- versus low-grade neoplasms for supratentorial tumors presenting in the first year of life, given the significant negative correlation between ADC values and tumor grade.