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Review |
1 Department of Radiology, Duke University Medical Center, Box 3808, Durham, NC
27710.
2 Departments of Radiology, Biomedical Engineering, and Medicine, Emory
University School of Medicine, Atlanta, GA.
Received October 3, 2008;
accepted after revision October 3, 2008.
Address correspondence to J. M. Provenzale.
Abstract
CONCLUSION. Many advanced imaging capabilities are being brought to bear to noninvasively monitor physiologic changes in the abnormal pediatric brain. Furthermore, novel forms of analysis that are evidence-based are being used to better understand how imaging studies are used and the impact they have on clinical decision making. The reader is encouraged to read these articles in their entirety in order to better understand the lines of inquiry contained in them.
Keywords: brain trauma • CT radiation dose • leukodystrophies • MR spectroscopy • neurofibromatosis • neuroradiology • outcomes research • pediatric imaging
For this review, six prominent pediatric neuroradiologists were contacted for suggestions of titles of articles that they think have been particularly important or influential over the past 5 years (the period of 2004-2008). From the titles provided by these experts, a spectrum of articles representing various important aspects of pediatric neuroradiology, as well as general radiology, were chosen for inclusion as representative of important topics (e.g., outcomes research and dose reduction in pediatric imaging) as well as advanced imaging techniques (e.g., diffusion tensor imaging and MR spectroscopy). These articles are summarized below.
Dose Reduction Strategy for Pediatric Head CT
In this study [1], the authors set out to determine the effect of tube current modulation on adult and pediatric neuroradiology CT protocols. Specifically, the authors quantitatively assessed the degree to which tube current modulation affected patient dose and image quality. Although both adult and pediatric CT protocols were examined, for the purposes of this review of the pediatric neuroradiology literature, solely the pediatric portion of the study is discussed.
The study examined patient dose and image quality under three CT conditions: first, a 16-MDCT scanner without using z-axis dose modulation; second, a 16-MDCT scanner using z-axis dose modulation; and, third, a 64-MDCT scanner using x-y-z-axis dose modulation. Dose modulation refers to a process whereby CT tube current is individually adjusted for each CT slice. Using z-axis modulation, the tube current for each CT slice can be manipulated to alter the CT dose (and the noise level) for each image. Thus, one can achieve an optimal balance between CT dose and image quality. The process of x-y-z-axis modulation is more complex and was developed after z-axis modulation. Using x-y-z-axis modulation, the CT dose can be altered not solely from one CT slice to another, but also within each CT slice, which allows one to optimize CT dose and image quality.
To set the lowest allowable dose level for an acceptable CT image, the investigators first determined maximal allowable noise levels for their 16-MDCT scanners using z-axis modulation and for their 64-MDCT scanners using x-y-z-axis modulation. These maximal allowable noise levels would provide the greatest reduction of radiation dose while still allowing the anatomic re solution needed for image interpretation. Thereafter, the investigators measured the dose reduction obtained by adoption of scanning parameters that provided the maxi mal allowable noise level.
For determination of the maximal allowable noise levels, all Neuroradiology faculty members reviewed CT images in which varying degrees of z-axis modulation had been per formed for the 16-MDCT scanner imaging protocol, which produced varying degrees of noise on images. The investigators initially set noise index levels at their lowest setting (i.e., higher end of the signal-to-noise ratios spectrum). Then z-axis modulation was per formed to allow the noise index for the 16-MDCT scanner protocol to be systematically increased until image quality was determined to be inadequate. A decision as to when this point was reached was determined by all faculty members in a consensus manner and the set of parameters that allowed the highest acceptable noise level was chosen. When a 64-MDCT scanner became available, x-y-z-axis modulation was performed for that scanner and the process was repeated for that scanner.
The investigators then compared dose decrease for each of the three imaging techniques. They examined three series of 100 consecutive patients each: one group imaged with a 16-MDCT scanner without dose modulation, another group imaged with a 16-MDCT scanner after z-axis dose modulation, and the third group imaged with a 64-MDCT scanner after the introduction of x-y-z-axis dose modulation. Radiation dose was measured using two dose indicators—that is, the volume CT dose index, which indicates the weighted CT dose index divided by the pitch, and the dose-length product, which represents the product of the volume CT dose index and the length of the scan in centimeters and provides an estimate of the total radiation burden. In addition, all scans were assessed for image quality by a single neuroradiologist who graded the scans for diagnostic acceptability.
The assessment of dose reduction in the pediatric CT protocol showed that both measures of dose were reduced by approximately 55-58% when dose modulation was used for the 16-MDCT scanner compared with the 16-MDCT scanner without dose modulation. When 64-MDCT scanning with x-y-z-axis modulation was compared with 16-MDCT with no dose modulation, a reduction of 53% in the volume CT dose index was seen, as well as a 26% reduction in the dose-length product. Image quality was found to be unaffected by dose modulation. Thus, the result of this study showed that issues of CT dose in pediatric imaging could be systematically addressed and could be resolved with an outcome that provided sizable reductions in CT dose while maintaining acceptable image quality.
Serial MRI of Hyperintense Foci in Neurofibromatosis Type 1
In this study, 12 patients with NF1 between the ages of 7 and 19 years underwent a total of 34 MR examinations. On average, each child underwent three MR examinations at time intervals of 2 years. Thereafter, hyperintense foci on T2-weighted images were manually delineated and the final outline of the hyperintense foci was made using an automated segmentation program. Hyperintense foci were assigned to one of the following seven regions: the striatal region (caudate, putamen, claustrum, and external capsule); the globus pallidus and internal capsule; the diencephalic region (thalamus, hypothalamus, and subthalamus); the medial cerebellar region (cerebellar vermis, deep cerebellar nuclei, and middle cerebellar peduncle); the ventral midbrain (cerebral peduncle) and ventral pons; the dorsal midbrain, pontine tegmentum, and medulla; and the white matter of lateral cerebellar hemispheres.
The analysis showed a total of 336 hyperintense foci were found in these locations. Approximately 65% were seen in the globus pallidus and internal capsule, 23% in the brainstem, and most of the remainder in the diencephalic region and cerebellum. In a few brain regions (i.e., the cerebellar region and supratentorial white matter), the number of hyperintense foci and the volume of affected tissue were at the highest level in patients who were in the 7- to 10-year-old age range and then decreased to lower levels thereafter. However, in most brain regions, the number of hyperintense foci and the volume of affected tissue decreased from a high in patients who were 7-10 years old to a low in patients who were 12-14 years old and then increased again in the late teenage years to levels comparable to those seen in the 7- to 10-year-old patients. The pattern of changes in the number of affected brain regions was similar to that of the number of lesions—that is, a high level in patients 7-10 years old and a high level again in the late teenage years, with a nadir in the intervening years.
In summary, this study depicted well the time course of the hyperintense foci characteristic of NF1 and shows that these lesions tend to regress during late childhood but become more predominant again in early adolescence. These findings can provide guidance for radiologists who are asked to interpret MRI studies in NF1 patients, especially when a comparison is made with prior imaging studies. A decrease in hyperintense foci may not be indicative of true disease remission if it is seen during late childhood. In addition, this study is informative to those interested in the cognitive aspects of NF1 because the results indicate that the number of hyperintense foci and the number of brain regions affected are highly variable over time. Thus, studies attempting to correlate cognitive measurements with the number of hyperintense foci must use MRI studies that are performed relatively close to the time of cognitive tests.
Outcomes Research-Based Analysis of the Use of Functional MRI Studies in Children
For this review, to highlight the benefits of outcomes research in pediatric neuropathology, an article was chosen that had the goal of assessing whether a relatively new imaging technique improved treatment out comes. In this study, investigators set out to prospectively determine the influence of preoperative brain activation studies (also referred to as "functional MRI" or "fMRI") in children with epilepsy [6]. The study was designed to assess the degree to which preoperative fMRI had an impact on the evaluation and treatment planning of seizure disorder patients about to undergo surgical therapy. In a previous study, the same authors had shown the cost-effectiveness of fMRI relative to the Wada test (i.e., assessment of language and memory soon after intracarotid infusion of sodium amobarbital via catheter angiography) for the evaluation of language lateralization [7]. A natural next study was to determine whether the use of preoperative fMRI changed patient management.
The authors enrolled 60 consecutive pediatric patients (mean age, 15.8 years) who were about to undergo surgical therapy for resection of a seizure focus. The clinical care team was provided with prospective questionnaires before presurgical fMRI testing. Members of the seizure team were asked to predict the anatomic location and the extent of areas of brain important to language and visual and motor function. In addition, team members were asked to indicate their level of confidence in their predictions. The team members were asked to outline the diagnostic and therapeutic plan, including whether Wada testing and direct intraoperative electrical mapping would likely be needed, as well as the details of the surgical plan.
After performance of fMRI, questionnaires were again provided to determine the effect of fMRI results on treatment planning. The study showed that the use of fMRI helped avoid further tests, including the invasive Wada test, in approximately 60% of patients. In addition, statistically significant increases in confidence levels regarding localization of motor and visual cortical function were also reported, and the seizure treatment team indicated that patient and family counseling were altered in approximately 60% of the cases. Furthermore, plans for intraoperative mapping were altered in 52% and surgical plans were revised in 42% of patients. A two-stage surgery with extraoperative direct electrical stimulation was revised to one-stage surgery in 8% of children. Finally, the extent of surgical resection was changed in 7% of children after fMRI showed eloquent brain cortex near the seizure focus.
This study serves as a good example of how radiologists can achieve the goals outlined by Thornbury [5] many years ago and understand how imaging tests are used by referring clinicians. One advantage of such an approach is that one better under stands the critical role that imaging tests and radiologists interpreting those tests play in the current medical environment. Importantly, such studies serve as a means for radiologists to show these facts to others outside the field of radiology, including those who determine levels of reimbursement for imaging studies.
Suspected Brain Trauma: Evidence-Based Decision Rules for Ordering CT
Palchak et al. [9] performed a prospective observational cohort study of children who presented to the pediatric emergency department at their institution after a history of nontrivial blunt head trauma during the period of July 1998 to September 2001. The patient population consisted of children with head injuries; however, children with trivial head trauma were excluded if the only abnormal finding was a scalp laceration or abrasion. The study population consisted of 2,043 children with head trauma, of whom 1,271 (62%) underwent CT. The CT scans were obtained at the discretion of the treating physicians and CT was performed in compliance with the guidelines at that institution. However, follow-up information was obtained on all children (even those who did not undergo CT) to determine whether a diagnosis of traumatic brain in jury had been missed.
The goal of the study was to derive clinical decision rules that would maximize the clinical efficiency of CT for brain imaging and provide high sensitivity for the diagnosis of traumatic brain injury and high negative predictive value for excluding children without traumatic brain injuries. Two outcome variables were defined at the beginning of the study: first, traumatic brain injury detected by CT; and, second, traumatic brain injury requiring acute intervention, which was defined as the need for a neurosurgical procedure, the need for anti epileptic medications for more than 1 week, the presence of persistent neurologic deficits, or the need for hospitalization for at least 2 nights.
Clinical findings were prospectively recorded and included history of loss of consciousness; the presence of amnesia, seizures, vomiting, current headache, or dizziness; clinical signs of skull fracture or scalp trauma; visual change; abnormal mental status; and focal neurologic deficits. The authors per formed univariate analyses for each of these clinical findings to determine the relative risk of traumatic brain injury on CT for each clinical feature and also the relative risk of traumatic brain injury requiring acute intervention. The relative risk refers to the ratio of probability of an event (e.g., traumatic brain injury on CT) when a condition (e.g., seizures) is present relative to the probability when the condition is absent. Finally, the authors devised decision trees for predicting children with traumatic brain injury on CT and for traumatic brain injury requiring acute intervention. For an algorithm such as the decision trees mentioned here, a high sensitivity (e.g., identification of children with traumatic brain injury on CT) and a high negative predictive value (i.e., prediction of children who do not have traumatic brain injury on CT) would be optimal. These decision trees used the clinical features that had the highest relative risk as decision points early in the algorithm.
A total of 98 children (7.7% of those who underwent head CT) had traumatic brain injuries on CT and 105 (5.1% of the 2,043 children enrolled in the study) had traumatic brain injuries requiring acute intervention. The study found that a number of factors would have predicted almost all children with CT evidence of head injury. In 99% of such children, one or more of the following features was always present: abnormal mental status; clinical signs of skull fracture; history of vomiting, scalp hematoma (in children < 2 years old), or headache. Furthermore, these clinical features would have identified 100% of children who required acute intervention, including at least 2 nights of hospitalization, or who had a neurologic deficit that required hospitalization, anticonvulsants for at least a week, or a neurosurgical procedure. On the other hand, the study also found that 304 of the 827 children (37%) who had none of these predictors underwent head CT. Of these 304 children, only one child was found to have a traumatic brain injury on head CT; application of the rule using these predictors would have eliminated 25% of CT scans obtained during this period. Furthermore, none of the 827 children without one of these predictors required acute intervention.
The univariate analysis to determine relative risk of traumatic brain injury on CT given the presence or absence of each clinical feature revealed relative risks ranging from 1.5 to 6.8. The features that had a relative risk at the high end of this range were abnormal mental status, focal neurologic deficit, and clinical signs of skull fracture. Headache and vomiting were at the low end of the range. A similar pattern was found on the univariate analysis to determine relative risk of traumatic brain injury requiring acute intervention. The decision tree for predicting children with traumatic brain injury on CT scans had a sensitivity of 98% and a negative predictive value of 99.6%. The decision trees used abnormal mental status and clinical signs of skull fracture, which had the highest relative risks in each univariate analysis, as decision points early in the algorithm. For the decision tree for predicting children with traumatic brain injury requiring acute intervention, the sensitivity and negative predictive value were both 100%. Thus, both decision trees would prove valuable as a means of screening children with possible traumatic brain injury.
For the general reader, the article by Palchak and colleagues [9] is a very good example of the benefits of the application of outcomes research to the field of radiology and of the use of decision-making rules to order radiologic tests. For the radiologist interested in outcomes research, the systematic approach shown here can serve as an example that could be applied to many other radiologic tests.
MR Spectroscopy for Evaluation of Children with Brain Trauma
The investigation found de creases in NAA levels and NAA/Cr and NAA/Cho ratios (although not statistically significant) in children with brain trauma compared with age-matched control subjects. This finding was in agreement with those of prior studies [11]. The authors interpreted the NAA data as an indication for neuronal and axonal injury in the frontoparietal lobe. Healthy control subjects performed better than children with traumatic brain injury on the various cognitive tests. Some of the correlations between MR spectroscopy data and cognitive testing approached, but did not reach, statistical significance. Decreases in NAA were most closely associated with intellectual function and arithmetic ability.
This study is of interest because it provides supportive evidence that advanced MR techniques and statistical analysis may provide predictive information, often in regions that appear normal on spin-echo sequences, that is not available from routine MRI. Subsequent studies by other investigators have substantiated the concept that MR spectroscopy shows abnormalities in normal-appearing brain regions adjacent to cortical contusions [12] and that MR spectroscopy data help predict neurologic outcome [13].
Advanced MRI of Neonatal Hypoxic-Ischemic injury
The study [14] was a prospective one in which 10 neonates born at term or near term underwent serial MRI. All infants except one were born after complicated deliveries and developed seizures soon after birth. The remaining infant showed signs of a jittery baby and was otherwise considered clinically normal. This infant was admitted to the study on the basis of the finding of an abnormally low arterial blood gas measurement but subsequently was determined to be healthy and discharged from the hospital. The first MR scan was always obtained in the first 48 hours of life; in most cases, a second scan was obtained within the first week of life. Eight infants underwent two MRI examinations and the remaining two infants underwent three. In addition to T1- and T2-weighted imaging, DWI and MR spectroscopy were performed during all MR examinations. On DWI studies, standard regions of interest for measurement of water diffusivity values were placed in a large number of predetermined areas rather than solely in areas thought to be abnormal. For MR spectroscopy assessments, a single-voxel technique was used and voxels were placed in deep gray matter regions and arterial watershed zones in white matter. Standard metabolites, including NAA (a measure of neuronal integrity), Cho (a marker of cell membrane turnover), lactate (indicative of anaerobic metabolism), and Cr, were measured, and peak ratios of lactate/Cho, lactate/NAA, and NAA/Cho were calculated for each voxel.
Conventional MRI techniques showed varying degrees of abnormality on the initial imaging examination in most patients. These findings were more common as well as more conspicuous in infants whose first imaging study was performed on day 2 of life (as opposed to day 1). All infants developed new areas or more extensive areas of hyperintense signal abnormality on T1-weighted images that were consistent with hypoxic-ischemic injury on the second MR scan compared with the first scan. These regions were typically seen either in the basal ganglia and thalamus or in a watershed territory distribution. By comparison, areas of abnormal signal intensity on T2-weighted images were relatively uncommon.
On DWI, restricted diffusion was seen on the initial imaging studies in all infants except the infant who was determined to be healthy and discharged from the hospital. However, in one infant, the region of restricted diffusion was very small and only mildly abnormal. Over the course of the study of most infants, the degree of restricted diffusion appeared to reach its peak at approximately 5 days after the insult. Furthermore, the appearance of abnormalities on DWI was dynamic, not solely from the perspective of changes in the degree of apparent diffusion coefficient (ADC) decrease over the first few days of life but also because new areas of restricted diffusion appeared after the initial MR examination. Specifically, during the first week of life, some areas with initially restricted diffusion (indicative of tissue damage) began to attain normal ADC values (i.e., so-called pseudo-normalization). Also, during the first week of life, regions that showed normal ADC values on day 1 or day 2 often developed restricted diffusion on subsequent imaging studies. Thus, the pattern of abnormalities on DWI differed depending on the day of life when the scan was obtained.
Findings on MR spectroscopy generally followed the temporal sequence seen for DWI abnormalities, with most marked abnormalities often seen on the second scan. For instance, when the initial scan was obtained on the first day of life and the second scan was obtained on either the second, third, or fourth day of life, the lactate/NAA ratio in the basal ganglia and thalamus always increased on the second scan. Similarly, in general the NAA/Cho ratio decreased and the Cr/NAA ratio increased in the injured region from the time of the first scan to that of the second scan. In the two patients who underwent three MR examinations, the NAA/Cho ratio had increased on the third scan in a pattern similar to the improvement in diffusion characteristics seen on DWI on the third scans.
Thus, in this study, a general pattern was seen for both DWI and MR spectroscopy abnormalities in most infants. The investigators indicated a number of limitations in this study, of which most are generic to MR studies in infants. These limitations include lack of precision in the determination of timing of neonatal hypoxic-ischemic injury and an inability to perform imaging on sick neonates at regular intervals. Nonetheless, despite these limitations, this study fulfilled its purpose of showing and further establishing the importance of DWI and MR spectroscopy in the evaluation of the neonate with a suspected hypoxic-ischemic event and in outlining the temporal course of changes that can be expected.
Diffusion Tensor Imaging Assessment of Brain Tumor Patients Treated with Irradiation
One recent study set out to prospectively evaluate whether changes in white matter anisotropy correlated with three clinical parameters: age at time of craniospinal irradiation, the radiation dose, and the time interval between irradiation and MRI [17]. The study evaluated 20 consecutive medulloblastoma survivors with a mean age of 11.0 years and compared histogram-derived mean white matter fractional anisotropy (FA) values in patients and those measured in age-matched control subjects. The authors used a template derived with statistical parametric mapping (SPM) software to segment brain tissue into white matter, gray matter, and CSF categories. Approximately 70% of the treatment survivors were found to have decreased mean FA values. The investigators found significant correlations between a decrease in the mean FA value and both age at the time of craniospinal irradiation and the radiation dose but not between the FA decrease and the time interval between irradiation and MRI. How ever, after multiple linear regression analyses, age at time of craniospinal irradiation was found to be the only independent variable that significantly affected FA decrease. The authors postulate that the small sample size may have been responsible for the lack of correlation of radiation dose and decrease in mean FA values.
In a subsequent study performed by the same investigators, decreases in mean FA values were found to be correlated with lower IQ scores after adjusting for age at treatment, radiation dose, and time interval from treatment [18]. Using a threshold of an IQ score of 85 for a below-average IQ score, the investigators found that a decrease in the mean FA of 3.3% was the best predictor for a below-average IQ score. Thus, a relatively small decrease in mean FA values appears to correlate with a rather substantial neurocognitive effect. This study, as the authors suggest, appears to validate measurement of FA values as a biomarker of radiation-induced neurotoxicity after craniospinal irradiation. Importantly, this article shows that MRI-derived findings that are not discernible by individual readers but are evident only using advanced computation methods can be strongly associated with the clinical effects of treatment.
One feature of the statistical techniques used in this study is worth noting because it sheds light on some limitations of the study. This investigation differed from many other diffusion tensor imaging studies by not using regions of interest to assess specific brain regions. Thus, an analysis of the entire white matter was made rather than interrogation of specific brain regions associated with various cognitive functions. In addition, as the authors indicate, the use of SPM segmentation would be expected to underestimate the degree of FA decrease as measured by region-of-interest analysis. Their rationale is as follows: Region-of-interest placements are typically within deep, compact white matter regions, which are known to be more vulnerable to radiation-induced effects. On the other hand, the SPM segmentation technique provides an assessment of the entire white matter, including peripheral regions that are less vulnerable to the effects of radiation. Thus, one ramification of the use of the SPM technique is that some patients with less marked decreases in FA will fail to be identified.
MR Spectroscopy-Based Model to Classify Children with Leukodystrophies
The study population consisted of 70 pediatric patients between the ages of 8 months and 17 years in whom MRI showed symmetric, predominantly white matter involvement and in whom clinical and laboratory tests needed to establish the diagnosis of hereditary leukoencephalopathy had been obtained. In 47 children, a definite diagnosis had been established previously. The diagnoses in these patients were characterized as fitting into one of the three following categories: a hypomyelinating disorder (various specific genetic alterations, n = 7), a disorder of rarefaction of white matter (leukoencephalopathy with vanishing white matter, MLC1 mutation, or respiratory chain complex defect mitochondrial disorders, n = 12), or a demyelinating disorder (Alexander's disease, adrenoleukody strophy, globoid cell leukodystrophy, or metachromatic leukodystrophy, n = 25). Three other patients had been diagnosed with Canavan's disease or L-2-OH glutaric aciduria. The remaining 23 children were undiagnosed and served as the subjects for testing of the model mentioned in the second hypothesis.
The MR spectroscopy protocol involved measurement of Cho, Cr, and NAA in six white matter regions. Then statistical analysis in the form of analysis of variance was performed for each of the six regions and again for the three groups of patients according to the classification scheme outlined earlier. This portion of the analysis showed that three metabolite ratios—Cho/NAA, Cho/Cr, and NAA/Cr—differed significantly between the demyelinating group and both the hypomyelination and the rarefaction groups. However, only the NAA/Cr ratio was significantly different between the rarefaction and hypomyelination groups.
Finally, a model intended to accurately separate patients into the three classification groups was constructed using a stepwise linear discriminant analysis. Within this model, the metabolite profile of the hypomyelinating disorders group was that in which Cho/NAA, Cho/Cr, and NAA/Cr ratios were similar to those of healthy children older than 2 years—that is, profiles with a large NAA signal intensity and near-equal Cho and Cr. The metabolite profile of the children with leukoencephalopathy classified as white matter rarefaction included decreased Cr and NAA in hyperintense white matter regions on T2-weighted imaging and unchanged Cho values so that the NAA/Cho ratio was approximately 1:1. Finally, the metabolic profile of the children with demyelinating diseases was that of elevated Cho (i.e., Cho/NAA > 1.5 and Cho/Cr > 1.4) and reduced NAA.
When this model was applied to the 44 children in whom a diagnosis had been established, the model correctly categorized 75% of children to one of the three classification groups listed earlier. In another 23 children, a definitive diagnosis had not yet been established, although a tentative diagnosis had been assigned. When the same model was applied to these 23 cases, 61% of the cases were correctly assigned to the proper classification group.
In conclusion, this study used MR spectroscopy data from patients with a known diagnosis of a specific white matter disorder to develop a model for assigning undiagnosed patients to one of three categories. The model generally performed very well with regard to both definitively diagnosed patients and those in whom a diagnosis had not yet been firmly established. This study serves as a model for use of a robust database and advanced statistical methods to develop computer models for classification of white matter disorders.
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Abstract
Introduction