More articles from Functional
- Manganese-Enhanced MRI in Patients with Multiple Sclerosis
Mangafodipir is a manganese chelate that was clinically approved for MR imaging of liver lesions. The authors present a case series of 6 adults with multiple sclerosis who were scanned at baseline with gadolinium, then injected with mangafodipir, and followed at variable time points. Fourteen new lesions formed during or shortly before the study, of which 10 demonstrated manganese enhancement of varying intensity, timing, and spatial pattern. One gadolinium-enhancing extra-axial mass, presumably a meningioma, also demonstrated enhancement with manganese. Manganese enhancement was detected in lesions that formed in the days after mangafodipir injection, and this enhancement persisted for several weeks. They conclude that multiple sclerosis lesions were enhanced with a temporal and spatial profile distinct from that of gadolinium.
- Deep Learning for Pediatric Posterior Fossa Tumor Detection and Classification: A Multi-Institutional Study
This study cohort comprised 617 children (median age, 92 months; 56% males) from 5 pediatric institutions with posterior fossa tumors: diffuse midline glioma of the pons, medulloblastoma, pilocytic astrocytoma, and ependymoma. There were 199 controls. Tumor histology served as ground truth except for diffuse midline glioma of the pons, which was primarily diagnosed by MR imaging. A modified ResNeXt-50-32x4d architecture served as the backbone for a multitask classifier model, using T2-weighted MRI as input to detect the presence of tumor and predict tumor class. Model tumor detection accuracy exceeded an AUC of 0.99 and was similar to that of 4 radiologists. Model tumor classification accuracy was 92% with an F1 score of 0.80. The model was most accurate at predicting diffuse midline glioma of the pons, followed by pilocytic astrocytoma and medulloblastoma. Ependymoma prediction was the least accurate.
- Black Dipole or White Dipole: Using Susceptibility Phase Imaging to Differentiate Cerebral Microbleeds from Intracranial Calcifications
The authors evaluated the diagnostic accuracy of differentiating cerebral microbleeds and calcifications from phase patterns in axial locations in 31 consecutive patients undergoing both CT and MR imaging for acute infarction and exhibiting dark spots in gradient-echo magnitude images. Six patients had additional quantitative susceptibility mapping images. To determine their susceptibility, 2 radiologists separately investigated the phase patterns in the border and central sections. Among 190 gradient-echo dark spots, 62 calcifications and 128 cerebral microbleeds were detected from CT. Interobserver reliability was higher for the border phase patterns than for the central phase patterns. The sensitivity and specificity of the border phase patterns in identifying calcifications were higher than those of the central phase patterns, particularly for lesions >2.5 mm in diameter and quantitative susceptibility mapping of dark spots. They conclude that the border phase patterns were more accurate than the central phase patterns in differentiating calcifications and cerebral microbleeds and were as accurate as quantitative susceptibility mapping.