Comparison of computed tomography angiography versus cardiac catheterization for preoperative evaluation of major aortopulmonary collateral arteries in pulmonary atresia with ventricular septal defect

Introduction:

Pulmonary atresia with the ventricular septal defect is a rare congenital heart defect with high anatomic variability. The most important management question relates to the sources of pulmonary blood flow. The ability to differentiate between ductal dependence and major aortopulmonary collateral arteries is critical to achieving good outcomes and avoiding life-threatening hypoxia in the postneonatal period. Having accurate information about pulmonary arteries, major aortopulmonary collateral arteries, and sources of blood supply to each pulmonary segment is crucial for choosing the optimal surgical strategy. The purpose of this study is to compare computed tomography angiography (CTA) with cardiac catheterization for anatomic delineation of surgically relevant anatomy in pulmonary atresia with ventricular septal defect with major aortopulmonary collateral arteries.

Materials and Methods:

Retrospective review of all children with pulmonary atresia with ventricular septal defect with major aortopulmonary collateral arteries cared for at a large tertiary children's hospital who underwent cardiac catheterization with angiography and CTA close to each other without interval therapy. All studies were performed between 2007 and 2011.

Results:

There were 9 patients who met the inclusion criteria. Pulmonary artery anatomy (confluent vs. nonconfluent) was correctly identified in 9 patients by CTA and 8 patients by catheterization. There were no significant differences between CTA and catheterization in the identification of major aortopulmonary collateral arteries (mean = 3.4 collaterals/study via catheterization; mean = 3.1 collaterals/study via CTA; P = 0.67). CTA was superior to catheterization in the delineation of segmental pulmonary blood flow (P = 0.006).

Conclusion:

CTA and catheterization are equivalent in their ability to delineate pulmonary artery anatomy and major aortopulmonary collateral arteries.

Normalization enhances brain network features that predict individual intelligence in children with epilepsy

BACKGROUND AND PURPOSE

Architecture of the cerebral network has been shown to associate with IQ in children with epilepsy. However, subject-level prediction on this basis, a crucial step toward harnessing network analyses for the benefit of children with epilepsy, has yet to be achieved. We compared two network normalization strategies in terms of their ability to optimize subject-level inferences on the relationship between brain network architecture and brain function.

MATERIALS AND METHODS

Patients with epilepsy and resting state fMRI were retrospectively identified. Brain network nodes were defined by anatomic parcellation, first in patient space (nodes defined for each patient) and again in template space (same nodes for all patients). Whole-brain weighted graphs were constructed according to pair-wise correlation of BOLD-signal time courses between nodes. The following metrics were then calculated: clustering coefficient, transitivity, modularity, path length, and global efficiency. Metrics computed on graphs in patient space were normalized to the same metric computed on a random network of identical size. A machine learning algorithm was used to predict patient IQ given access to only the network metrics.

RESULTS

Twenty-seven patients (8-18 years) comprised the final study group. All brain networks demonstrated expected small world properties. Accounting for intrinsic population heterogeneity had a significant effect on prediction accuracy. Specifically, transformation of all patients into a common standard space as well as normalization of metrics to those computed on a random network both substantially outperformed the use of non-normalized metrics.

CONCLUSION

Normalization contributed significantly to accurate subject-level prediction of cognitive function in children with epilepsy. These findings support the potential for quantitative network approaches to contribute clinically meaningful information in children with neurological disorders.

Correction to: Comparative safety and efficacy of balloon use in air enema reduction for pediatric intussusception

The original version on this paper contained an error. The names of M. John Hicks and R. Paul Guillerman, though correctly appeared in the published version, are incorrectly displayed in indexing sites.

Relationship between heart rate and quiescent interval of the cardiac cycle in children using MRI

BACKGROUND

Imaging the heart in children comes with the challenge of constant cardiac motion. A prospective electrocardiography-triggered CT scan allows for scanning during a predetermined phase of the cardiac cycle with least motion. This technique requires knowing the optimal quiescent intervals of cardiac cycles in a pediatric population.

OBJECTIVE

To evaluate high-temporal-resolution cine MRI of the heart in children to determine the relationship of heart rate to the optimal quiescent interval within the cardiac cycle.

MATERIALS AND METHODS

We included a total of 225 consecutive patients ages 0-18 years who had high-temporal-resolution cine steady-state free-precession sequence performed as part of a magnetic resonance imaging (MRI) or magnetic resonance angiography study of the heart. We determined the location and duration of the quiescent interval in systole and diastole for heart rates ranging 40-178 beats per minute (bpm). We performed the Wilcoxon signed rank test to compare the duration of quiescent interval in systole and diastole for each heart rate group.

RESULTS

The duration of the quiescent interval at heart rates <80 bpm and >90 bpm was significantly longer in diastole and systole, respectively (P<.0001 for all ranges, except for 90-99 bpm [P=.02]). For heart rates 80-89 bpm, diastolic interval was longer than systolic interval, but the difference was not statistically significant (P=.06). We created a chart depicting optimal quiescent intervals across a range of heart rates that could be applied for prospective electrocardiography-triggered CT imaging of the heart.

CONCLUSION

The optimal quiescent interval at heart rates <80 bpm is in diastole and at heart rates ≥90 bpm is in systole. The period of quiescence at heart rates 80-89 bpm is uniformly short in systole and diastole.

Repeatability of graph theoretical metrics derived from resting-state functional networks in paediatric epilepsy patients

OBJECTIVE

To measure the repeatability of metrics that quantify brain network architecture derived from resting-state functional MRI in a cohort of paediatric patients with epilepsy.

METHODS

We identified patients with: (1) epilepsy; (2) brain MRI at 3 T; (3) two identical resting-state functional MRI acquisitions performed on the same day. Undirected, weighted networks were constructed based on the resting-state time series using a range of processing parameters including parcellation size and graph threshold. The following topological properties were calculated: degree, strength, characteristic path length, global efficiency, clustering coefficient, modularity and small worldness. Based on repeated measures, we then calculated: (1) Pearson correlation coefficient; (2) intraclass correlation coefficient; (3) root-mean-square coefficient of variation; (4) repeatability coefficient; and (5) 95% confidence limits for change.

RESULTS

26 patients were included (age range: 4-21 years). Correlation coefficients demonstrated a highly consistent relationship between repeated observations for all metrics, and the intraclass correlation coefficients were generally in the excellent range. Repeatability in the data set was not significantly influenced by parcellation size. However, trends towards decreased repeatability were observed at higher graph thresholds.

CONCLUSION

These findings demonstrate the reliability of network metrics in a cohort of paediatric patients with epilepsy. Advances in knowledge: Our results point to the potential for graph theoretical analyses of resting-state data to provide reliable markers of network architecture in children with epilepsy. At the level of an individual patient, change over time greater than the repeatability coefficient or 95% confidence limits for change is unlikely to be related to intrinsic variability of the method.

Modern American scurvy - experience with vitamin C deficiency at a large children's hospital

BACKGROUND

Until recently scurvy has been viewed in developed countries as a disease of the past. More recently there have been reports of case series of children with scurvy who have had a delayed diagnosis after an extensive diagnostic workup that included imaging. Most of these children have had underlying neurologic conditions such as autism.

OBJECTIVE

To review the medical records of children diagnosed with vitamin C (ascorbic acid) deficiency based on serum ascorbic acid levels at a large pediatric health care system, to determine imaging findings and utility of imaging in management, and to identify at-risk pediatric populations.

MATERIALS AND METHODS

We retrospectively identified cases of vitamin C deficiency in children tested for serum ascorbic acid levels during the last 5 years. We used the criteria of normal ascorbic acid >23 μmol/L and included children with ascorbic acid levels <23 μmol/L. We evaluated their clinical history, underlying medical condition, imaging studies obtained and imaging findings.

RESULTS

We identified 32 children with vitamin C deficiency. All of these children had underlying medical conditions, most commonly iron overload from multiple transfusions related to sickle cell anemia or thalassemia (20), neurologic disorders (4) and bone marrow transplant/chemotherapy (3). No cases of scurvy from dietary deficiency in otherwise normal children were identified. All except two children had multiple imaging studies, primarily related to their underlying conditions. Three of these children had extensive imaging workups related to diffuse musculoskeletal pain. Imaging findings included ill-defined sclerotic and lucent metaphyseal bands (mainly at the knee) on radiography and MRI studies that showed diffuse increased T2-weighted signal in the bilateral lower-extremity long-bone metaphyses, periosteal reaction and adjacent soft-tissue edema.

CONCLUSION

Vitamin C deficiency is not uncommon in large pediatric health care facilities, and it is frequently missed on clinical evaluation and diagnostic imaging. At-risk populations include those with iron overload, neurologic conditions and history of chemotherapy. Scurvy related to dietary deficiency in otherwise normal children was not encountered. When characteristic MRI findings are seen, particularly in children with a predisposing condition for vitamin C deficiency, scurvy should be considered and a serum ascorbic acid level checked to potentially confirm a diagnosis prior to further invasive tests.

Metrics of brain network architecture capture the impact of disease in children with epilepsy

BACKGROUND AND OBJECTIVE

Epilepsy is associated with alterations in the structural framework of the cerebral network. The aim of this study was to measure the potential of global metrics of network architecture derived from resting state functional MRI to capture the impact of epilepsy on the developing brain.

METHODS

Pediatric patients were retrospectively identified with: 1. Focal epilepsy; 2. Brain MRI at 3 Tesla, including resting state functional MRI; 3. Full scale IQ measured by a pediatric neuropsychologist. The cerebral cortex was parcellated into approximately 700 gray matter network nodes. The strength of a connection between two nodes was defined as the correlation between their resting BOLD signal time series. The following global network metrics were then calculated: clustering coefficient, transitivity, modularity, path length, and global efficiency. Epilepsy duration was used as an index for the cumulative impact of epilepsy on the brain.

RESULTS

45 patients met criteria (age: 4-19 years). After accounting for age of epilepsy onset, epilepsy duration was inversely related to IQ (p: 0.01). Epilepsy duration predicted by a machine learning algorithm on the basis of the five global network metrics was highly correlated with actual epilepsy duration (r: 0.95; p: 0.0001). Specifically, modularity and to a lesser extent path length and global efficiency were independently associated with epilepsy duration.

CONCLUSIONS

We observed that a machine learning algorithm accurately predicted epilepsy duration based on global metrics of network architecture derived from resting state fMRI. These findings suggest that network metrics have the potential to form the basis for statistical models that translate quantitative imaging data into patient-level markers of cognitive deterioration.

Brain Network Architecture and Global Intelligence in Children with Focal Epilepsy

BACKGROUND AND PURPOSE

The biologic basis for intelligence rests to a large degree on the capacity for efficient integration of information across the cerebral network. We aimed to measure the relationship between network architecture and intelligence in the pediatric, epileptic brain.

MATERIALS AND METHODS

Patients were retrospectively identified with the following: 1) focal epilepsy; 2) brain MR imaging at 3T, including resting-state functional MR imaging; and 3) full-scale intelligence quotient measured by a pediatric neuropsychologist. The cerebral cortex was parcellated into approximately 700 gray matter network "nodes." The strength of a connection between 2 nodes was defined by the correlation between their blood oxygen level-dependent time-series. We calculated the following topologic properties: clustering coefficient, transitivity, modularity, path length, and global efficiency. A machine learning algorithm was used to measure the independent contribution of each metric to the intelligence quotient after adjusting for all other metrics.

RESULTS

Thirty patients met the criteria (4-18 years of age); 20 patients required anesthesia during MR imaging. After we accounted for age and sex, clustering coefficient and path length were independently associated with full-scale intelligence quotient. Neither motion parameters nor general anesthesia was an important variable with regard to accurate intelligence quotient prediction by the machine learning algorithm. A longer history of epilepsy was associated with shorter path lengths (P = .008), consistent with reorganization of the network on the basis of seizures. Considering only patients receiving anesthesia during machine learning did not alter the patterns of network architecture contributing to global intelligence.

CONCLUSIONS

These findings support the physiologic relevance of imaging-based metrics of network architecture in the pathologic, developing brain.

The Arcuate Fasciculus and Language Development in a Cohort of Pediatric Patients with Malformations of Cortical Development

BACKGROUND AND PURPOSE

Patients with epilepsy and malformations of cortical development have a high prevalence of language deficits. The purpose of this study was to investigate whether the status of the arcuate fasciculus at diffusion tractography could provide a clinically meaningful marker of language function in patients with cortical malformations.

MATERIALS AND METHODS

Thirty-seven patients 3-18 years of age who had DTI performed at 3T and language evaluation by a pediatric neurologist were retrospectively identified. Twenty-two age-matched children without any neurologic, language, or MR imaging abnormalities who had identical DTI performed for an indication of headache were selected as a control cohort. The arcuate fasciculi were constructed and segmented by deterministic tractography for all subjects.

RESULTS

Twenty-one patients had intact language; 11 had mild-to-moderate and 5, profound language impairment. All patients with normal language and all control subjects had an identifiable left arcuate. The left arcuate was absent in 11 patients; all 11 were language-impaired. Failure to identify the left arcuate was strongly associated with some degree of language impairment (P < .001). Sensitivity, specificity, and positive predictive value for language dysfunction were 65%, 100%, and 100%, respectively. The absence of the arcuate bilaterally was associated with complete failure to develop oral language (P < .015).

CONCLUSIONS

Failure to identify the left arcuate fasciculus at diffusion tractography was a highly specific marker of language dysfunction in a cohort of pediatric patients with malformations of cortical development. Failure to identify the arcuate fasciculus on either side was associated with failure to develop oral language.