The premature brain embodies an underdeveloped vascular system, which can lead to poor cerebral blood flow (CBF), impaired metabolism, and subsequent brain injury. NNeMo (Neonatal NeuroMonitor) is an in-house built brain monitor that provides continuous and simultaneous measurements of CBF, tissue saturation (StO2), and metabolism. Nine premature infants were monitored for 6 h on day 1 and 3 of life. An oscillatory signal was observed in CBF and StO2 which diminished by day 3; metabolic response was not impacted by minor fluctuations in perfusion. Hemodynamic neuromonitoring could aid in predicting the onset of cerebral hemorrhaging or gauging brain injury severity.
In comparison to two-dimensional (2D) ultrasound (US), three-dimensional (3D) US imaging is a more sensitive alternative for monitoring the size and shape of neonatal cerebral lateral ventricles. It can be used when following posthemorrhagic ventricular dilatation, after intraventricular hemorrhaging (IVH), which is bleeding inside the lateral ventricles of the brain in preterm infants. Tracking ventricular dilatation is important in neonates as it can cause increased intracranial pressure, leading to neurological damage. However, manually segmenting 3D US images is time-consuming and tedious due to poor image contrast and the complex shape of cerebral ventricles. In this paper, we describe an automated segmentation method based on the U-Net model for the segmentation of 3D US images that may contain one or both ventricle(s). We trained and tested two models, a 3D U-Net and slice-based 2D U-Net, on a total of 193 3D US images (105 one ventricle and 88 two ventricle images). To mitigate the class imbalance of the object vs. background, we augmented the images through rotation and translation. As a benchmark comparison, we also trained a U-Net++ model and compared the results with the original U-Net. When all the images were used in a single U-Net model, the 3D U-Net and 2D U-Net yielded a Dice similarity coefficient (DSC) of 0.67±0.16 and 0.76±0.09 respectively. When two 2D U-Net models were trained separately, they yielded a DSC of 0.82±0.09 and 0.74±0.07 for one ventricle and two ventricle images, respectively. Compared to the best previous fully automated method, the proposed 2D U-Net method reported a comparable DSC when using all images but an increased DSC of 0.05 when using only one ventricle image.
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.
Dilatation of the cerebral ventricles is a common condition in preterm neonates with intraventricular hemorrhage (IVH). Post Hemorrhagic Ventricular Dilatation (PHVD) can lead to lifelong neurological impairment caused by ischemic injury due to increased intracranial pressure, and without treatment can lead to death. Previously, we have developed and validated a 3D ultrasound (US) system to monitor the progression of ventricle volumes (VV) in IVH patients; however, many patients with severe PHVD have ventricles so large they cannot be imaged within a single 3D US image. This limits the utility of atlas based segmentation algorithms required to measure VV as parts of the ventricles are in separate 3D US images, and thus, an already challenging segmentation becomes increasingly difficult to solve. Without a more automated segmentation, the clinical utility of 3D US ventricle volumes cannot be fully realized due to the large number of images and patients required to validate the technique in a clinical trials. Here, we describe the initial results of an automated ‘stitching’ algorithm used to register and combine multiple 3D US images of the ventricles of patients with PHVD. Our registration results show that we were able to register these images with an average target registration error (TRE) of 4.25±1.95 mm.
A complication of intraventricular hemorrhage among preterm neonates is post-hemorrhagic ventricle dilation (PHVD), which is associated with a greater risk of life-long neurological disability. Clinical evidence, including suppressed EEG patterns, suggests that cerebral perfusion and oxygenation is impaired in these patients, likely due to elevated intracranial pressure (ICP). Cerebral blood flow (CBF) and the cerebral metabolic rate of oxygen (CMRO2) can be quantified by dynamic contrast-enhanced NIRS; however, PHVD poses a unique challenge to NIRS since the cerebral mantle can be compressed to 1 cm or less. The objectives of this work were to develop a finite-slab model for the analysis of NIRS spectra, incorporating depth measurements from ultrasound images, and to assess the magnitude of error when using the standard semi-infinite model. CBF, tissue saturation (StO2) and CMRO2 were measured in 9 patients receiving ventricle taps to reduce ICP. Monte Carlo simulations indicated that errors in StO2 could be greater than 20% if the cerebral mantle was reduced to 1 cm. Using the finite-slab model, basal CBF and CMRO2 in the PHVD patients were not significantly different from a control group of preterm infants (14.6 ± 4.2 ml/100 g/min and 1.0 ± 0.4 ml O2/100 g/min), but StO2 was significantly lower (PDA 70.5 ± 9%, PHVD 58.9 ± 12%). Additionally, ventricle tapping improved CBF by 15.6 ± 22%. This work indicates that applying NIRS to PHVD patients is prone to error; however, this issue can be overcome with the appropriate model and using readily available ultrasound images.
Most debilitating neurological disorders can have anatomical origins. Yet unlike other body organs, the anatomy alone cannot easily provide an understanding of brain functionality. In fact, addressing the challenge of linking structural and functional connectivity remains in the frontiers of neuroscience. Aggregating multimodal neuroimaging datasets may be critical for developing theories that span brain functionality, global neuroanatomy and internal microstructures. Functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) are main such techniques that are employed to investigate the brain under normal and pathological conditions. FMRI records blood oxygenation level of the grey matter (GM), whereas DTI is able to reveal the underlying structure of the white matter (WM). Brain global activity is assumed to be an integration of GM functional hubs and WM neural pathways that serve to connect them. In this study we developed and evaluated a two-phase algorithm. This algorithm is employed in a 3D interactive connectivity visualization framework and helps to accelerate clustering of virtual neural pathways. In this paper, we will detail an algorithm that makes use of an index-based membership array formed for a whole brain tractography file and corresponding parcellated brain atlas. Next, we demonstrate efficiency of the algorithm by measuring required times for extracting a variety of fiber clusters, which are chosen in such a way to resemble all sizes probable output data files that algorithm will generate. The proposed algorithm facilitates real-time visual inspection of neuroimaging data to further the discovery in structure-function relationship of the brain networks.
KEYWORDS: 3D image processing, 3D metrology, Image segmentation, Ultrasonography, 3D acquisition, Magnetic resonance imaging, Transducers, 3D imaging standards, Standards development, Imaging systems
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 (R2 between 0.69 and 0.36). Additionally, weak correlations were found between changes in 2-D US measurements and 3-D US VV (R2 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.
Dilation of the cerebral ventricles is a common condition in preterm neonates with intraventricular hemorrhage (IVH). This post hemorrhagic ventricle dilation (PHVD) can lead to lifelong neurological impairment through ischemic injury due to increased intracranial pressure and without treatment, can lead to death.
Clinically, 2D ultrasound (US) through the fontanelles ('soft spots') of the patients are serially acquired to monitor the progression of the ventricle dilation. These images are used to determine when interventional therapies such as needle aspiration of the built up cerebrospinal fluid (CSF) ('ventricle tap', VT) might be indicated for a patient; however, quantitative measurements of the growth of the ventricles are often not performed. There is no consensus on when a neonate with PHVD should have an intervention and often interventions are performed after the potential for brain damage is quite high.
Previously we have developed and validated a 3D US system to monitor the progression of ventricle volumes (VV) in IVH patients.
We will describe the potential utility of quantitative 2D and 3D US to monitor and manage PHVD in neonates. Specifically, we will look to determine image-based measurement thresholds for patients who will require VT in comparison to patients with PHVD who resolve without intervention. Additionally, since many patients who have an initial VT will require subsequent interventions, we look at the potential for US to determine which PHVD patients will require additional VT after the initial one has been performed.
Intraventricular hemorrhage (IVH) or bleed within the brain is a common condition among pre-term infants that occurs in very low birth weight preterm neonates. The prognosis is further worsened by the development of progressive ventricular dilatation, i.e., post-hemorrhagic ventricle dilation (PHVD), which occurs in 10-30% of IVH patients. In practice, predicting PHVD accurately and determining if that specific patient with ventricular dilatation requires the ability to measure accurately ventricular volume. While monitoring of PHVD in infants is typically done by repeated US and not MRI, once the patient has been treated, the follow-up over the lifetime of the patient is done by MRI. While manual segmentation is still seen as a gold standard, it is extremely time consuming, and therefore not feasible in a clinical context, and it also has a large inter- and intra-observer variability. This paper proposes a segmentation algorithm to extract the cerebral ventricles from 3D T1- weighted MR images of pre-term infants with PHVD. The proposed segmentation algorithm makes use of the convex optimization technique combined with the learned priors of image intensities and label probabilistic map, which is built from a multi-atlas registration scheme. The leave-one-out cross validation using 7 PHVD patient T1 weighted MR images showed that the proposed method yielded a mean DSC of 89.7% ± 4.2%, a MAD of 2.6 ± 1.1 mm, a MAXD of 17.8 ± 6.2 mm, and a VD of 11.6% ± 5.9%, suggesting a good agreement with manual segmentations.
One of the major non-congenital cause of neurological impairment among neonates born very preterm is intraventricular hemorrhage (IVH) - bleeding within the lateral ventricles. Most IVH patients will have a transient period of ventricle dilation that resolves spontaneously. However, those patients most at risk of long-term impairment are those who have progressive ventricle dilation as this causes macrocephaly, an abnormally enlarged head, then later causes increases intracranial pressure (ICP). 2D ultrasound (US) images through the fontanelles of the patients are serially acquired to monitor the progression of the ventricle dilation. These images are used to determine when interventional therapies such as needle aspiration of the built up CSF might be indicated for a patient. Initial therapies usually begin during the third week of life. Such interventions have been shown to decrease morbidity and mortality in IVH patients; however, this comes with risks of further hemorrhage or infection; therefore only patients requiring it should be treated. Previously we have developed and validated a 3D US system to monitor the progression of ventricle volumes (VV) in IVH patients. This system has been validated using phantoms and a small set of patient images. The aim of this work is to determine the ability of 3D US generated VV to categorize patients into those who will require interventional therapies, and those who will have spontaneous resolution. Patients with higher risks could therefore be monitored better, by re-allocating some of the resources as the low risks infants would need less monitoring.
KEYWORDS: 3D image processing, Image segmentation, Ultrasonography, 3D metrology, Brain, 3D acquisition, Traumatic brain injury, Brain mapping, 3D image reconstruction, 3D applications
Intraventricular hemorrhage (IVH) is a major cause of brain injury in preterm neonates. Quantitative measurement of ventricular dilation or shrinkage is important for monitoring patients and in evaluation of treatment options. 3D ultrasound (US) has been used to monitor the ventricle volume as a biomarker for ventricular dilation. However, volumetric quantification does not provide information as to where dilation occurs. The location where dilation occurs may be related to specific neurological problems later in life. For example, posterior horn enlargement, with thinning of the corpus callosum and parietal white matter fibres, could be linked to poor visuo-spatial abilities seen in hydrocephalic children. In this work, we report on the development and application of a method used to analyze local surface change of the ventricles of preterm neonates with IVH from 3D US images. The technique is evaluated using manual segmentations from 3D US images acquired in two imaging sessions. The surfaces from baseline and follow-up were registered and then matched on a point-by-point basis. The distance between each pair of corresponding points served as an estimate of local surface change of the brain ventricle at each vertex. The measurements of local surface change were then superimposed on the ventricle surface to produce the 3D local surface change map that provide information on the spatio-temporal dilation pattern of brain ventricles following IVH. This tool can be used to monitor responses to different treatment options, and may provide important information for elucidating the deficiencies a patient will have later in life.
Dilation of the cerebral ventricles is a common condition in preterm neonates with intraventricular hemorrhage (IVH). This post hemorrhagic ventricle dilation (PHVD) can lead to lifelong neurological impairment through ischemic injury due to increased intracranial pressure (ICP). Interventions, such as ventricular tapping to remove cerebrospinal fluid (CSF), are used to prevent injury, but determining the optimal time for treatment is difficult as clinical signs of increased ICP lack sensitivity. There is a growing interest in using near-infrared spectroscopy (NIRS) because of its ability to monitor cerebral oxygen saturation (StO2) at the bedside. However, the accuracy of NIRS may be affected by signal contamination from enlarged ventricles, especially if there are blood breakdown products (bbp) in CSF following IVH. To investigate this, serial NIR spectra from the head and from CSF samples were acquired over a month from seven IVH patients undergoing treatment for PHVD. Over time, the visual appearance of the CSF samples progressed from dark brown (“tea color”) to clear yellow, reflecting the reduction in bbp concentration as confirmed by the stronger absorption around 760 nm at the earlier time points. All CSF samples contained strong absorption at 960 nm due to water. More importantly the same trend in these absorption features was observed in the in vivo spectra, and Monte Carlo simulations confirmed the potential for signal contamination from enlarged ventricles. These findings highlight the challenges of accurately measuring StO2 in this patient population and the necessity of using a hyperspectral NIRS system to resolve the additional chromophores.
Endoscopic and laparoscopic surgeries are used for many minimally invasive procedures but limit the visual and haptic feedback available to the surgeon. This can make vessel sparing procedures particularly challenging to perform. Previous approaches have focused on hardware intensive intraoperative imaging or augmented reality systems that are difficult to integrate into the operating room. This paper presents a simple approach in which motion is visually enhanced in the endoscopic video to reveal pulsating arteries. This is accomplished by amplifying subtle, periodic changes in intensity coinciding with the patient’s pulse. This method is then applied to two procedures to illustrate its potential. The first, endoscopic third ventriculostomy, is a neurosurgical procedure where the floor of the third ventricle must be fenestrated without injury to the basilar artery. The second, nerve-sparing robotic prostatectomy, involves removing the prostate while limiting damage to the neurovascular bundles. In both procedures, motion magnification can enhance subtle pulsation in these structures to aid in identifying and avoiding them.
KEYWORDS: 3D image processing, Magnetic resonance imaging, 3D metrology, Image segmentation, Imaging systems, Transducers, 3D acquisition, In vivo imaging, Brain, Image acquisition
Dilated lateral ventricles in neonates can be due to many different causes, such as brain loss, or congenital malformation; however, the main cause is hydrocephalus, which is the accumulation of fluid within the ventricular system. Hydrocephalus can raise intracranial pressure resulting in secondary brain damage, and up to 25% of patients with severely enlarged ventricles have epilepsy in later life. Ventricle enlargement is clinically monitored using 2D US through the fontanels. The sensitivity of 2D US to dilation is poor because it cannot provide accurate measurements of irregular volumes such as the ventricles, so most clinical evaluations are of a qualitative nature. We developed a 3D US system to image the cerebral ventricles of neonates within the confines of incubators that can be easily translated to more open environments. Ventricle volumes can be segmented from these images giving a quantitative volumetric measurement of ventricle enlargement without moving the patient into an imaging facility. In this paper, we report on in vivo validation studies: 1) comparing 3D US ventricle volumes before and after clinically necessary interventions removing CSF, and 2) comparing 3D US ventricle volumes to those from MRI. Post-intervention ventricle volumes were less than pre-intervention measurements for all patients and all interventions. We found high correlations (R = 0.97) between the difference in ventricle volume and the reported removed CSF with the slope not significantly different than 1 (p < 0.05). Comparisons between ventricle volumes from 3D US and MR images taken 4 (±3.8) days of each other did not show significant difference (p=0.44) between 3D US and MRI through paired t-test.
KEYWORDS: 3D image processing, Ultrasonography, 3D metrology, 3D modeling, Transducers, Imaging systems, Medical research, Health sciences, 3D scanning, Neodymium
Clinical intracranial ultrasound (US) is performed as a standard of care on neonates at risk of intraventricular hemorrhaging (IVH) and is also used after a diagnosis to monitor for potential ventricular dilation. However, it is difficult to estimate the volume of ventricles with 2D US due to their irregular shape. We developed a 3D US system to be used as an adjunct to a clinical system to investigate volumetric changes in the ventricles of neonates with IVH. Our system has been found have an error of within 1% of actual distance measurements in all three directions and volume measurements of manually segmented volumes from phantoms were not statistically significantly different from the actual values (p>0.3). Interobserver volume measurements of the lateral ventricles in a patient with grade III IVH found no significant differences between measurements. There is the potential to use this system in IVH patients to monitor the progression of ventriculomegaly over time.
The importance of presenting medical images in an intuitive and usable manner during a procedure is essential.
However, most medical visualization interfaces, particularly those designed for minimally-invasive surgery, suffer
from a number of issues as a consequence of disregarding the human perceptual, cognitive, and motor system's
limitations. This matter is even more prominent when human visual system is overlooked during the design cycle.
One example is the visualization of the neuro-vascular structures in MR angiography (MRA) images. This study
investigates perceptual performance in the usability of a display to visualize blood vessels in MRA volumes
using a contour enhancement technique. Our results show that when contours are enhanced, our participants,
in general, can perform faster with higher level of accuracy when judging the connectivity of different vessels.
One clinical outcome of such perceptual enhancement is improvement of spatial reasoning needed for planning
complex neuro-vascular operations such as treating Arteriovenous Malformations (AVMs). The success of an
AVM intervention greatly depends on fully understanding the anatomy of vascular structures. However, poor
visualization of pre-operative MRA images makes the planning of such a treatment quite challenging.
Surgical resection of epileptic foci is a typical treatment for drug-resistant epilepsy, however, accurate preoperative
localization is challenging and often requires invasive sub-dural or intra-cranial electrode placement.
The presence of cellular abnormalities in the resected tissue can be used to validate the effectiveness of multispectralMagnetic
Resonance Imaging (MRI) in pre-operative foci localization and surgical planning. If successful,
these techniques can lead to improved surgical outcomes and less invasive procedures. Towards this goal, a
novel pipeline is presented here for post-operative imaging of temporal lobe specimens involving MRI and digital
histology, and present and evaluate methods for bringing these images into spatial correspondence. The sparsely-sectioned
histology images of resected tissue represents a challenge for 3D reconstruction which we address
with a combined 3D and 2D rigid registration algorithm that alternates between slice-based and volume-based
registration with the ex-vivo MRI. We also evaluate four methods for non-rigid within-plane registration using
both images and fiducials, with the top performing method resulting in a target registration error of 0.87 mm.
This work allows for the spatially-local comparison of histology with post-operative MRI and paves the way for
eventual registration with pre-operative MRI images.
Endoscopic third ventriculostomy is a minimally invasive surgical technique to treat hydrocephalus; a condition
where patients suffer from excessive amounts of cerebrospinal fluid (CSF) in the ventricular system of their
brain. This technique involves using a monocular endoscope to locate the third ventricle, where a hole can be
made to drain excessive fluid. Since a monocular endoscope provides only a 2D view, it is difficult to make this
perforation due to the lack of monocular cues and depth perception. In a previous study, we had investigated
the use of a stereo-endoscope to allow neurosurgeons to locate and avoid hazardous areas on the surface of the
third ventricle. In this paper, we extend our previous study by developing a new methodology to evaluate the
targeting performance in piercing the hole in the membrane. We consider the accuracy of this surgical task and
derive an index of performance for a task which does not have a well-defined position or width of target. Our
performance metric is sensitive and can distinguish between experts and novices. We make use of this metric to
demonstrate an objective learning curve on this task for each subject.
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