3T magnetic resonance imaging testing of externally programmable shunt valves

Zabramski, Joseph M.; Preul, Mark C.; Debbins, Josef P.; McCusker, Daniel J.

doi:10.4103/2152-7806.99171

Cited by 14 publications

(8 citation statements)

References 9 publications

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“…In addition, our data compares favorably with reported data relating to shunt failure with 40% of children requiring intervention for shunt failure within the first 2 years after placement [ 37 ]. This is congruent with published results from previous studies whereby it has been demonstrated that the type of shunt valve used has no effect on shunt failure rates [ 13 , 38 ], with consensus guidelines not favoring any particular shunt valve type [ 18 , 39 ].…”

Section: Discussionsupporting

confidence: 91%

Programmable Shunt Valves for Pediatric Hydrocephalus: 22-Year Experience from a Singapore Children’s Hospital

Tey

Low

et al. 2021

Brain Sciences

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(1) Background: pediatric hydrocephalus is a challenging condition. Programmable shunt valves (PSV) have been increasingly used. This study is undertaken to firstly, to objectively evaluate the efficacy of PSV as a treatment modality for pediatric hydrocephalus; and next, review its associated patient outcomes at our institution. Secondary objectives include the assessment of our indications for PSV, and corroboration of our results with published literature. (2) Methods: this is an ethics-approved, retrospective study. Variables of interest include age, gender, hydrocephalus etiology, shunt failure rates and incidence of adjustments made per PSV. Data including shunt failure, implant survival, and utility comparisons between PSV types are subjected to statistical analyses. (3) Results: in this case, 51 patients with PSV are identified for this study, with 32 index and 19 revision shunts. There are 3 cases of shunt failure (6%). The mean number of adjustments per PSV is 1.82 times and the mean number of adjustments made per PSV is significantly lower for MEDTRONIC™ Strata PSVs compared with others (p = 0.031). Next, PSV patients that are adjusted more frequently include cases of shunt revisions, PSVs inserted due to CSF over-drainage and tumor-related hydrocephalus. (4) Conclusion: we describe our institutional experience of PSV use in pediatric hydrocephalus and its advantages in a subset of patients whose opening pressures are uncertain and evolving.

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Section: Discussionsupporting

confidence: 91%

Programmable Shunt Valves for Pediatric Hydrocephalus: 22-Year Experience from a Singapore Children’s Hospital

Tey

Low

et al. 2021

Brain Sciences

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“…Shunt technology for hydrocephalus has grown rapidly, and adjustable shunt valves are now common. 7,11,13,16 Furthermore, the development of shunt valves with locking systems that eliminate the risk of unintentional valve pressure changes during MRI enables easy follow-up examination after shunt implantation.…”

Section: Discussionmentioning

confidence: 99%

“…4 However, susceptibility artifacts are more prominent on echoplanar imaging-based diffusion imaging and time-offlight MRA based on gradient echo sequences than they are on sequences obtaining an echo that use a 180° pulse, such as T1WI, T2WI, and FLAIR. 6,11,13,16 This means that patients with a shunt valve potentially pose a difficulty for evaluation of the aforementioned critical diseases. In fact, Singleton et al 12 reported a case in which a shunt valve artifact concealed the development of an underlying meningioma, highlighting the difficulty of detailed examination by MRI.…”

Section: Figmentioning

confidence: 99%

“…Some studies have reported comparisons of artifacts induced by programmable shunt valves, but most have mainly performed ex vivo assessments. 8,10,11,16 Moreover, many studies have calculated volumes or gross areas of artifacts. From the clinical perspective, the most important information is the extent of brain structure concealed by artifacts and the ease of changing image results by changing pressure settings.…”

Section: Figmentioning

confidence: 99%

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Setting pressure can change the size and shape of MRI artifacts caused by adjustable shunt valves: a study of the 4 newest models

Uchida¹,

Amano²,

Nakatogawa³

et al. 2019

Journal of Neurosurgery

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OBJECTIVEAdjustable shunt valves that have been developed for the management of hydrocephalus all rely on intrinsically magnetic components, and artifacts with these valves on MRI are thus inevitable. The authors have previously reported that the shapes of shunt artifacts differ under different valve pressures with the proGAV 2.0 valve. In the present study the authors compared the size and shape of artifacts at different pressure settings with 4 new-model shunt valves.METHODSThe authors attached 4 new models of MRI-resistant shunt valve to the temporal scalp of a healthy volunteer: the proGAV 2.0; Codman Certas Plus; Polaris; and Strata MR. They set 3 different scales of pressures for each valve, depending on magnet orientation to the body axis. Artifacts were evaluated and compared among all valves on a 3.0-T GE scanner and 2 valves were also evaluated on a Philips scanner and a Siemens scanner. In-plane artifact sizes were evaluated as the maximum distance of the artifact from the expected scalp.RESULTSThe sizes and shapes of artifacts changed depending on valve pressure for all valves on the 3 different MRI scanners. Artifacts were less prominent on spin echo sequences than on gradient echo sequences. For diffusion-weighted imaging and time-of-flight MR angiography, the authors matched image numbers within the same sequence and compared appearances of artifacts. For all valves, the number of images affected by artifacts and the image number showing the largest artifact differed among valve settings.CONCLUSIONSArtifacts of all adjustable shunt valves showed gross changes corresponding to pressure setting. Not only the maximum distance of artifacts but also the shape changed significantly. The authors suggest that changing pressure settings offers one of the easiest ways to minimize artifacts on MRI.

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“…Correct identification of CFS-SVs is essential for verifying the compatibility with the MRI machine and to monitor for potential setting changes due to the MR magnetic field 4 – 8 . In fact, exposing patients with some programmable CSF-SVs to MR imaging procedures poses a significant risk of unintentional changes in shunt settings, even if such devices are not MR incompatible 9 – 12 . Lavinio et al .…”

Section: Introductionmentioning

confidence: 99%

MRI Compatibility: Automatic Brain Shunt Valve Recognition using Feature Engineering and Deep Convolutional Neural Networks

Giancardo

Arevalo

Tenreiro

et al. 2018

Sci Rep

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The aim of this study is to evaluate whether we could develop a machine learning method to distinguish models of cerebrospinal fluid shunt valves (CSF-SVs) from their appearance in clinical X-rays. This is an essential component of an automatic MRI safety system based on X-ray imaging. To this end, a retrospective observational study using 416 skull X-rays from unique subjects retrieved from a clinical PACS system was performed. Each image included a CSF-SV representing the most common brands of programmable shunt valves currently used in US which were split into five different classes. We compared four machine learning pipelines: two based on engineered image features (Local Binary Patterns and Histogram of Oriented Gradients) and two based on features learned by a deep convolutional neural network architecture. Performance is evaluated using accuracy, precision, recall and f1-score. Confidence intervals are computed with non-parametric bootstrap procedures. Our best performing method identified the valve type correctly 96% [CI 94–98%] of the time (CI: confidence intervals, precision 0.96, recall 0.96, f1-score 0.96), tested using a stratified cross-validation approach to avoid chances of overfitting. The machine learning pipelines based on deep convolutional neural networks showed significantly better performance than the ones based on engineered image features (mean accuracy 95–96% vs. 56–64%). This study shows the feasibility of automatically distinguishing CSF-SVs using clinical X-rays and deep convolutional neural networks. This finding is the first step towards an automatic MRI safety system for implantable devices which could decrease the number of patients that experience denials or delays of their MRI examinations.

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3T magnetic resonance imaging testing of externally programmable shunt valves

Cited by 14 publications

References 9 publications

Programmable Shunt Valves for Pediatric Hydrocephalus: 22-Year Experience from a Singapore Children’s Hospital

Programmable Shunt Valves for Pediatric Hydrocephalus: 22-Year Experience from a Singapore Children’s Hospital

Setting pressure can change the size and shape of MRI artifacts caused by adjustable shunt valves: a study of the 4 newest models

MRI Compatibility: Automatic Brain Shunt Valve Recognition using Feature Engineering and Deep Convolutional Neural Networks

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