Can ventricular 3D ultrasound of neonates with posthemorrhagic hydrocephalus inform on the need for a ventriculoperitoneal shunt?

OBJECTIVE: Some neonates born prematurely with intraventricular hemorrhage develop posthemorrhagic hydrocephalus and require lifelong treatment to divert the flow of CSF. Early prediction of the eventual need for a ventriculoperitoneal shunt (VPS) is difficult, and early discussions with families are based on statistics and the grade of hemorrhage. The authors hypothesize that change in ventricular volume during ventricular taps that is measured with repeated 3D ultrasound (3D US) imaging of the lateral ventricles could be used to assess the risk of the future requirement of a VPS. METHODS: A total of 92 neonates with intraventricular hemorrhage who were treated in the NICU were recruited between April 2012 and November 2019. Only patients who required ventricular taps (VTs) were included in this study, resulting in the analysis of 19 patients with a total of 61 VTs. Among them, 14 patients were treated with a VPS, and in 5 patients the hydrocephalus resolved spontaneously. Parameters studied were total ventricular volume measured with 3D US, ventricular volume change after VT, the ratio between volume reduction and tap amount, the difference between tap amount and volume reduction after tap, the average tap amount, the average number of days between taps, pre-tap head circumference, and reduction in head circumference after tap. RESULTS: Statistically significant differences were found in ventricular volume reduction after tap (p = 0.007), the ratio between volume reduction and tap amount (p = 0.03), the difference between tap amount and volume reduction after tap (p = 0.05), and the interval of days between taps (p = 0.0115). CONCLUSIONS: Measuring with 3D US before and after VT can be a useful tool for quantifying ventricular volume. The findings in this study showed that neonates who experience a large reduction of ventricular volume after VT are more likely to be treated with a shunt than are neonates who experience a small reduction.

Does ventricular volume affect the neurodevelopmental outcome in infants with intraventricular hemorrhage?

OBJECTIVE: The aim of this study is to investigate whether ventricular volume in posthemorrhagic ventricle dilatation impacts neurodevelopmental outcome. Infants were scanned with 3D cranial ultrasound in the first few months of life, and their neurodevelopmental outcome at 4, 8, 12, and 24 months corrected age (CA) was examined. METHODS: Forty-nine infants who suffered an intraventricular hemorrhage (IVH) were enrolled in the study. Subjects were scanned multiple times during their stay in the neonatal intensive care unit. Images were manually segmented to measure total volume of the lateral ventricles, and the highest volume was taken. Infants with a volume ≤ 20 cc were considered low-volume (n = 33), and infants with a volume ≥ 40 cc were considered high-volume (n = 12). Developmental outcome was assessed at 4, 8, and 12 months CA with the Alberta Infant Motor Scale (AIMS) and Infant Neurological International Battery (Infanib), and at 24 months CA with the Bayley Scales of Infant Development 3e (BSID III). RESULTS: Infants in the low-volume group had higher scores on the Infanib at 4 months CA, and on both the AIMS and Infanib at 8 and 12 months CA, even after controlling for gestational age, birth weight, and worst grade of IVH. We observed a trend where low-volume infants also scored higher on the cognitive and gross-motor subtests of the BSID III at 24 months CA. CONCLUSION: Our results show that ventricular volume affects neurodevelopmental outcome in infants with IVH. This finding could guide the timing of future interventions, as earlier intervention may decrease the likelihood of adverse neurodevelopmental outcome.

Quantitative 3-D head ultrasound measurements of ventricle volume to determine thresholds for preterm neonates requiring interventional therapies following posthemorrhagic ventricle dilatation.

Dilatation of the cerebral ventricles is a common condition in preterm neonates with intraventricular hemorrhage. This posthemorrhagic ventricle dilatation (PHVD) can lead to lifelong neurological impairment through ischemic injury due to increased intracranial pressure, and without treatment can lead to death. Two-dimensional ultrasound (US) through the fontanelles of the patients is serially acquired to monitor the progression of PHVD. These images are used in conjunction with clinical experience and physical exams to determine when interventional therapies such as needle aspiration of the built up cerebrospinal fluid (ventricle tap, VT) might be indicated for a patient; however, quantitative measurements of the ventricles size are often not performed. We describe the potential utility of the quantitative three-dimensional (3-D) US measurements of ventricle volumes (VVs) in 38 preterm neonates to monitor and manage PHVD. Specifically, we determined 3-D US VV thresholds for patients who received VT in comparison to patients with PHVD who resolve without intervention. In addition, since many patients who have an initial VT will receive subsequent interventions, we determined which PHVD patients will receive additional VT after the initial one has been performed.

Investigating the effects of cerebrospinal fluid removal on cerebral blood flow and oxidative metabolism in infants with post-hemorrhagic ventricular dilatation.

BackgroundPost-hemorrhagic ventricular dilatation (PHVD) is predictive of mortality and morbidity among very-low-birth-weight preterm infants. Impaired cerebral blood flow (CBF) due to elevated intracranial pressure (ICP) is believed to be a contributing factor.MethodsA hyperspectral near-infrared spectroscopy (NIRS) method of measuring CBF and the cerebral metabolic rate of oxygen (CMRO2) was used to investigate perfusion and metabolism changes in patients receiving a ventricular tap (VT) based on clinical management. To improve measurement accuracy, the spectral analysis was modified to account for compression of the cortical mantle caused by PHVD and the possible presence of blood breakdown products.ResultsFrom nine patients (27 VTs), a significant CBF increase was measured (15.6%) following VT (14.6±4.2 to 16.9±6.6 ml/100 g/min), but with no corresponding change in CMRO2 (1.02±0.41 ml O2/100 g/min). Post-VT CBF was in good agreement with a control group of 13 patients with patent ductus arteriosus but no major cerebral pathology (16.5±7.7 ml/100 g/min), whereas tissue oxygen saturation (StO2) was significantly lower (58.9±12.1% vs. 70.5±9.1% for controls).ConclusionCBF was impeded in PHVD infants requiring a clinical intervention, but the effect is not large enough to alter CMRO2.

Automatic segmentation approach to extracting neonatal cerebral ventricles from 3D ultrasound images.

Preterm neonates with a very low birth weight of less than 1,500 g are at increased risk for developing intraventricular hemorrhage (IVH). Progressive ventricle dilatation of IVH patients may cause increased intracranial pressure, leading to neurological damage, such as neurodevelopmental delay and cerebral palsy. The technique of 3D ultrasound (US) imaging has been used to quantitatively monitor the ventricular volume in IVH neonates, which may elucidate the ambiguity surrounding the timing of interventions in these patients as 2D clinical US imaging relies on linear measurement and visual estimation of ventricular dilation from a series of 2D slices. To translate 3D US imaging into the clinical setting, a fully automated segmentation algorithm is necessary to extract the ventricular system from 3D neonatal brain US images. In this paper, an automatic segmentation approach is proposed to delineate lateral ventricles of preterm neonates from 3D US images. The proposed segmentation approach makes use of phase congruency map, multi-atlas initialization technique, atlas selection strategy, and a multiphase geodesic level-sets (MGLS) evolution combined with a spatial shape prior derived from multiple pre-segmented atlases. Experimental results using 30 IVH patient images show that the proposed GPU-implemented approach is accurate in terms of the Dice similarity coefficient (DSC), the mean absolute surface distance (MAD), and maximum absolute surface distance (MAXD). To the best of our knowledge, this paper reports the first study on automatic segmentation of the ventricular system of premature neonatal brains from 3D US images.

Longitudinal Analysis of Pre-Term Neonatal Cerebral Ventricles From 3D Ultrasound Images Using Spatial-Temporal Deformable Registration.

Preterm neonates with a very low birth weight of less than 1,500 grams are at increased risk for developing intraventricular hemorrhage (IVH), which is a major cause of brain injury in preterm neonates. Quantitative measurements of ventricular dilatation or shrinkage play an important role in monitoring patients and evaluating treatment options. 3D ultrasound (US) has been developed to monitor ventricle volume as a biomarker for ventricular changes. However, ventricle volume as a global indicator does not allow for precise analysis of local ventricular changes, which could be linked to specific neurological problems often seen in the patient population later in life. In this work, a 3D+t spatial-temporal deformable registration approachis proposed, which is applied to the analysis of the detailed local changes of preterm IVH neonatal ventricles from 3D US images. In particular, a novel sequential convex/dual optimization algorithm is introduced to extract the optimal 3D+t spatial-temporal deformable field, which simultaneously optimizes the sequence of 3D deformation fieldswhile enjoying both efficiencyand simplicity in numerics. The developed registration technique was evaluated by comparing two manually extracted ventricle surfaces from the baseline and the registered follow-up images using the metrics of Dice similarity coefficient (DSC), mean absolute surface distance (MAD), and maximum absolute surface distance (MAXD). The performed experiments using 14 patients with 5 time-point images per patient show that the proposed 3D+t registration approach accurately recovered the longitudinal deformation of ventricle surfaces from 3D US images. The proposed approach may be potentially used to analyse the change pattern of cerebral ventricles of IVH patients, their response to different treatment options, and to elucidate the deficiencies that a patient could have later in life. To the best of our knowledge, this paper reports the first study on the longitudinalanalysis of neonatal ventricular system from 3D US images.

Preterm neonatal lateral ventricle volume from three-dimensional ultrasound is not strongly correlated to two-dimensional ultrasound measurements.

The aim of this study is to compare longitudinal two-dimensional (2-D) and three-dimensional (3-D) ultrasound (US) estimates of ventricle size in preterm neonates with posthemorrhagic ventricular dilatation (PHVD) using quantitative measurements of the lateral ventricles. Cranial 2-D US and 3-D US images were acquired from neonatal patients with diagnosed PHVD within 10 min of each other one to two times per week and analyzed offline. Ventricle index, anterior horn width, third ventricle width, and thalamo-occipital distance were measured on the 2-D images and ventricle volume (VV) was measured from 3-D US images. Changes in the measurements between successive image sets were also recorded. No strong correlations were found between VV and 2-D US measurements ([Formula: see text] between 0.69 and 0.36). Additionally, weak correlations were found between changes in 2-D US measurements and 3-D US VV ([Formula: see text] between 0.13 and 0.02). A trend was found between increasing 2-D US measurements and 3-D US-based VV, but this was not the case when comparing changes between 3-D US VV and 2-D US measurements. If 3-D US-based VV provides a more accurate estimate of ventricle size than 2-D US measurements, moderate-weak correlations with 3-D US suggest that monitoring preterm patients with PHVD using 2-D US measurements alone might not accurately represent whether the ventricles are progressively dilating. A volumetric measure (3-D US or MRI) could be used instead to more accurately represent changes.

In Vivo Validation of a 3-D Ultrasound System for Imaging the Lateral Ventricles of Neonates.

Intra-ventricular hemorrhage, with the resultant cerebral ventricle dilation, is a common cause of brain injury in preterm neonates. Clinically, monitoring is performed using 2-D ultrasound (US); however, its clinical utility in dilation is limited because it cannot provide accurate measurements of irregular volumes such as those of the ventricles, and this might delay treatment until the patient's condition deteriorates severely. We have developed a 3-D US system to image the lateral ventricles of neonates within the confines of incubators. We describe an in vivo ventricle volume validation study in two parts: (i) comparisons between ventricle volumes derived from 3-D US and magnetic resonance images obtained within 24 h; and (ii) the difference between 3-D US ventricle volumes before and after clinically necessary interventions (ventricle taps), which remove cerebral spinal fluid. Magnetic resonance imaging ventricle volumes were found to be 13% greater than 3-D US ventricle volumes; however, we observed high correlations (R(2) = 0.99) when comparing the two modalities. Differences in ventricle volume pre- and post-intervention compared with the reported volume of cerebrospinal fluid removed also were highly correlated (R(2) = 0.93); the slope was not found to be statistically significantly different from 1 (p < 0.05), and the y-intercept was not found to be statistically different from 0 (p < 0.05). Comparison between 3-D US images can detect the volume change after neonatal intra-ventricular hemorrhage. This could be used to determine which patients will have progressive ventricle dilation and allow for more timely surgical interventions. However, 3-D US ventricle volumes should not be directly compared with magnetic resonance imaging ventricle volumes.

A framework for quantification and visualization of segmentation accuracy and variability in 3D lateral ventricle ultrasound images of preterm neonates.

PURPOSE: Intraventricular hemorrhage (IVH) is a major cause of brain injury in preterm neonates. Three dimensional ultrasound (US) imaging systems have been developed to visualize 3D anatomical structure of preterm neonatal intracranial ventricular system with IVH and ventricular dilation. To allow quantitative analysis, the ventricle system is required to be segmented accurately and efficiently from 3D US images. Although semiautomatic segmentation algorithms have been developed, local segmentation accuracy and variability associated with these algorithms should be evaluated statistically before they can be applied in clinical settings. This work proposes a statistical framework to quantify the local accuracy and variability and performs statistical tests to identify locations where the semiautomatically segmented surfaces are significantly different from manually segmented surfaces. METHODS: Three dimensional lateral ventricle US images of preterm neonates were each segmented six times manually and using a semiautomated segmentation algorithm. The local difference between manually and algorithmically segmented surfaces as well as the segmentation variability for each method was computed and superimposed on the ventricular surface of each subject. To summarize the segmentation performance for a whole group of subjects, the subject-specific local difference and standard deviation maps were registered onto a 3D template ventricular surface using a nonrigid registration algorithm. Pointwise, intersubject average accuracy and pooled variability for the whole group of subjects can be computed and visualized on the template surface, providing a summary of performance of the segmentation algorithm for the whole group of ventricles with highly variable geometry. In addition to pointwise statistical analysis performed on the template surface, statistical conclusion regarding the accuracy of the segmentation algorithm was made for subregions and the whole ventricle with the spatial correlation of pointwise accuracy taken into account. RESULTS: Ten 3D US images were involved in this study. Pointwise local difference, ΔS, its absolute value |ΔS| as well as the standard deviations of the manual and algorithm segmentations were computed and superimposed on the each ventricle surface. Regions with lower segmentation accuracy and higher segmentation variability can be identified from these maps, and the localized information was applied to improve the accuracy of the algorithm. Intersubject average ΔS and |ΔS| as well as pooled standard deviations was computed on the template surface. Intersubject average ΔS and |ΔS| indicated that the algorithm underestimated regions in the neighborhood of the tips of anterior, inferior, and posterior horns. Intersubject pooled standard deviations indicated that manual segmentation had a higher segmentation variability than algorithm segmentation over the whole ventricle. Statistical analysis on the template surface showed that there was significant difference between algorithm and manual methods for segmenting the right lateral ventricle but not for the left lateral ventricle. CONCLUSIONS: A framework was proposed for evaluating, visualizing, and summarizing the local accuracy and variability of a segmentation algorithm. This framework can be used for improving the accuracy of segmentation algorithms, as well as providing useful feedback to improve the manual segmentation performance. More importantly, this framework can be applied for longitudinal monitoring of local ventricular changes of neonates with IVH.

Development of a combined broadband near-infrared and diffusion correlation system for monitoring cerebral blood flow and oxidative metabolism in preterm infants.

Neonatal neuromonitoring is a major clinical focus of near-infrared spectroscopy (NIRS) and there is an increasing interest in measuring cerebral blood flow (CBF) and oxidative metabolism (CMRO2) in addition to the classic tissue oxygenation saturation (StO2). The purpose of this study was to assess the ability of broadband NIRS combined with diffusion correlation spectroscopy (DCS) to measured changes in StO2, CBF and CMRO2 in preterm infants undergoing pharmaceutical treatment of patent ductus arteriosus. CBF was measured by both DCS and contrast-enhanced NIRS for comparison. No significant difference in the treatment-induced CBF decrease was found between DCS (27.9 ± 2.2%) and NIRS (26.5 ± 4.3%). A reduction in StO2 (70.5 ± 2.4% to 63.7 ± 2.9%) was measured by broadband NIRS, reflecting the increase in oxygen extraction required to maintain CMRO2. This study demonstrates the applicability of broadband NIRS combined with DCS for neuromonitoring in this patient population.

3D MR ventricle segmentation in pre-term infants with post-hemorrhagic ventricle dilatation (PHVD) using multi-phase geodesic level-sets.

Intraventricular hemorrhage (IVH) or bleed within the cerebral ventricles is a common condition among very low birth weight pre-term neonates. The prognosis for these patients is worsened should they develop progressive ventricular dilatation, i.e., post-hemorrhagic ventricle dilatation (PHVD), which occurs in 10-30% of IVH patients. Accurate measurement of ventricular volume would be valuable information and could be used to predict PHVD and determine whether that specific patient with ventricular dilatation requires treatment. While the monitoring of PHVD in infants is typically done by repeated transfontanell 2D ultrasound (US) and not MRI, once the patient's fontanels have closed around 12-18months of life, the follow-up patient scans are done by MRI. Manual segmentation of ventricles from MR images is still seen as a gold standard. However, it is extremely time- and labor-consuming, and it also has observer variability. This paper proposes an accurate multiphase geodesic level-set segmentation algorithm for the extraction of the cerebral ventricle system of pre-term PHVD neonates from 3D T1 weighted MR images. The proposed segmentation algorithm makes use of multi-region segmentation technique associated with spatial priors built from a multi-atlas registration scheme. The leave-one-out cross validation with 19 patients with mild enlargement of ventricles and 7 hydrocephalus patients shows that the proposed method is accurate, suggesting that the proposed approach could be potentially used for volumetric and morphological analysis of the ventricle system of IVH neonatal brains in clinical practice.

User-guided segmentation of preterm neonate ventricular system from 3-D ultrasound images using convex optimization.

A three-dimensional (3-D) ultrasound (US) system has been developed to monitor the intracranial ventricular system of preterm neonates with intraventricular hemorrhage (IVH) and the resultant dilation of the ventricles (ventriculomegaly). To measure ventricular volume from 3-D US images, a semi-automatic convex optimization-based approach is proposed for segmentation of the cerebral ventricular system in preterm neonates with IVH from 3-D US images. The proposed semi-automatic segmentation method makes use of the convex optimization technique supervised by user-initialized information. Experiments using 58 patient 3-D US images reveal that our proposed approach yielded a mean Dice similarity coefficient of 78.2% compared with the surfaces that were manually contoured, suggesting good agreement between these two segmentations. Additional metrics, the mean absolute distance of 0.65 mm and the maximum absolute distance of 3.2 mm, indicated small distance errors for a voxel spacing of 0.22 × 0.22 × 0.22 mm(3). The Pearson correlation coefficient (r = 0.97, p < 0.001) indicated a significant correlation of algorithm-generated ventricular system volume (VSV) with the manually generated VSV. The calculated minimal detectable difference in ventricular volume change indicated that the proposed segmentation approach with 3-D US images is capable of detecting a VSV difference of 6.5 cm(3) with 95% confidence, suggesting that this approach might be used for monitoring IVH patients' ventricular changes using 3-D US imaging. The mean segmentation times of the graphics processing unit (GPU)- and central processing unit-implemented algorithms were 50 ± 2 and 205 ± 5 s for one 3-D US image, respectively, in addition to 120 ± 10 s for initialization, less than the approximately 35 min required by manual segmentation. In addition, repeatability experiments indicated that the intra-observer variability ranges from 6.5% to 7.5%, and the inter-observer variability is 8.5% in terms of the coefficient of variation of the Dice similarity coefficient. The intra-class correlation coefficient for ventricular system volume measurements for each independent observer ranged from 0.988 to 0.996 and was 0.945 for three different observers. The coefficient of variation and intra-class correlation coefficient revealed that the intra- and inter-observer variability of the proposed approach introduced by the user initialization was small, indicating good reproducibility, independent of different users.

Lateral ventricle segmentation of 3D pre-term neonates US using convex optimization.

Intraventricular hemorrhage (IVH) is a common disease among preterm infants with an occurrence of 12-20% in those born at less than 35 weeks gestational age. Neonates at risk of IVH are monitored by conventional 2D ultrasound (US) for hemorrhage and potential ventricular dilation. Compared to 2D US relying on linear measurements from a single slice and visually estimates to determine ventricular dilation, 3D US can provide volumetric ventricle measurements, more sensitive to longitudinal changes in ventricular volume. In this work, we propose a global optimization-based surface evolution approach to the segmentation of the lateral ventricles in preterm neonates with IVH. The proposed segmentation approach makes use of convex optimization technique in combination with a subject-specific shape model. We show that the introduced challenging combinatorial optimization problem can be solved globally by means of convex relaxation. In this regard, we propose a coupled continuous max-flow model, which derives a new and efficient dual based algorithm, that can be implemented on GPUs to achieve a high-performance in numerics. Experiments demonstrate the advantages of our approach in both accuracy and efficiency. To the best of our knowledge, this paper reports the first study on semi-automatic segmentation of lateral ventricles in neonates with IVH from 3D US images.