Performing MRI on patients with MRI-conditional and non-conditional cardiac implantable electronic devices: an update for radiologists

Cunqueiro, Alain; Lipton, Michael L.; Dym, R. Joshua; Jain, Vineet R.; Sterman, Jonathan; Scheinfeld, Meir H.

doi:10.1016/j.crad.2019.07.006

Cited by 12 publications

(9 citation statements)

References 16 publications

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“…In standard MRI study protocols, before an MRI study can be scheduled, a radiologist must verify the patient has an MRI-conditional system with no contraindications (such as abandoned or fractured leads) and then a cardiologist must provide an order that the device be programmed to an MRI-conditional mode. 8 If the appropriateness of the MRI study request for the patient is met, the device will be interrogated by personnel with device expertise prior to the MRI, an MRI scan will be performed by an MRI technologist with a clinician monitoring the patient’s heart rate throughout, and the device will be interrogated again by electrophysiology personnel after the MRI. 8 This division of responsibilities and tasks between multiple individuals complicates the MRI procedure.…”

Section: Discussionmentioning

confidence: 99%

“… 8 If the appropriateness of the MRI study request for the patient is met, the device will be interrogated by personnel with device expertise prior to the MRI, an MRI scan will be performed by an MRI technologist with a clinician monitoring the patient’s heart rate throughout, and the device will be interrogated again by electrophysiology personnel after the MRI. 8 This division of responsibilities and tasks between multiple individuals complicates the MRI procedure.…”

Section: Discussionmentioning

confidence: 99%

“…Despite a growing list of MRI-conditional medical devices, barriers such as lack of training of medical personnel and logistical difficulties still exist. 7 , 8 , 9 Further advancements have been developed to reduce the burden of programming MRI-conditional devices into and out of an MRI safe mode. The MRI AutoDetect is one of these advancements.…”

Section: Introductionmentioning

confidence: 99%

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Utilization and programming of an automatic MRI recognition feature for cardiac rhythm management devices

Mullane¹,

Michaelis²,

Henrikson³

et al. 2021

Heart Rhythm O2

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Background Cardiac implantable electronic devices (CIED)—ie, pacemakers, implantable cardioverter-defibrillators, and cardiac resynchronization therapy devices—have recently been designed to allow for patients to safely undergo magnetic resonance imaging (MRI) when specific programming is implemented. MRI AutoDetect is a feature that automatically switches CIED’s programming into and out of an MR safe mode when exposed to an MRI environment. Objective The purpose was to analyze de-identified daily remote transmission data to characterize the utilization of the MRI AutoDetect feature. Methods Home Monitoring transmission data collected from MRI AutoDetect–capable devices were retrospectively analyzed to determine the workflow and usage in patients experiencing an MRI using the MRI AutoDetect feature. Results Among 48,756 capable systems, 2197 devices underwent an MRI using the MRI AutoDetect feature. In these 2197 devices, the MRI AutoDetect feature was used a total of 2806 times with an average MRI exposure of 40.83 minutes. The majority (88.9%) of MRI exposures occurred on the same day as the MRI AutoDetect programming. A same day post-MRI exposure follow-up device interrogation was performed 8.6% of the time. A device-related complaint occurred within 30 days of the MRI exposure in 0.25% of MRI exposures using MRI AutoDetect but with no adverse clinical outcome. Conclusion As a result of automation in device programming, the MRI AutoDetect feature eliminated post-MRI device reprogramming in 91.4% of MRI exposures and, while less frequent, allowed for pre-MRI interrogations prior to the day of the MRI exposure—reducing resource utilization and creating workflow flexibility.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Utilization and programming of an automatic MRI recognition feature for cardiac rhythm management devices

Mullane¹,

Michaelis²,

Henrikson³

et al. 2021

Heart Rhythm O2

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“…This information may be obtained from the documents available with the patients. If no such records exist, there are a few radiological markers which may help in the identification of MRI conditional system 130 . Industry or FDA published lists of MRI‐conditional components may be useful to be present in the evaluation room where these patients are evaluated 131 .…”

Section: Proposed Protocols In Literature For Mri In Patients With Nomentioning

confidence: 99%

“…There have been several recent publications suggesting different safety protocols for carrying out an MRI in patients with CIED 11,12,94,123,130,131,134–136 . The overall idea of the protocol is as summarized in Figure 3.…”

Section: Proposed Protocols In Literature For Mri In Patients With Nomentioning

confidence: 99%

MRI in patients with cardiac implantable electronic devices: A comprehensive review

Deshpande

Kella

Padmanabhan

2021

Pacing Clinical Electrophis

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Magnetic resonance imaging (MRI) has become a commonly used non‐ionizing radiation dependent imaging modality which has an excellent spatial resolution with the capability to provide physiological information. Cardiac implantable electronic devices (CIEDs) are used in modern cardiology with a frequency of 1:50 over 75 years of age and nearly one in three people in this population required MRI during their lifetime. Changes in the CIED structure, electronics, and algorithms paired with changes in the protocol design of MRI have created a relatively safe environment for performing MRI in patients with CIED. Despite their documentation in literature and a guideline document from a professional society, significant skepticism exists in doing MRI in patients with CIEDs. We intend to give an overview of interactions between MRI and CIEDs, including the evidence available in this regard and conclude with the suggestion of a protocol for safely carrying out an MRI in patients with CIEDs.

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Neural Network Detection of Pacemakers for MRI Safety

2022

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Flagging the presence of cardiac devices such as pacemakers before an MRI scan is essential to allow appropriate safety checks. We assess the accuracy with which a machine learning model can classify the presence or absence of a pacemaker on pre-existing chest radiographs. A total of 7973 chest radiographs were collected, 3996 with pacemakers visible and 3977 without. Images were identified from information available on the radiology information system (RIS) and correlated with report text. Manual review of images by two board certified radiologists was performed to ensure correct labeling. The data set was divided into training, validation, and a hold-back test set. The data were used to retrain a pre-trained image classification neural network. Final model performance was assessed on the test set. Accuracy of 99.67% on the test set was achieved. Re-testing the final model on the full training and validation data revealed a few additional misclassified examples which are further analyzed. Neural network image classification could be used to screen for the presence of cardiac devices, in addition to current safety processes, providing notification of device presence in advance of safety questionnaires. Computational power to run the model is low. Further work on misclassified examples could improve accuracy on edge cases. The focus of many healthcare applications of computer vision techniques has been for diagnosis and guiding management. This work illustrates an application of computer vision image classification to enhance current processes and improve patient safety.

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Performing MRI on patients with MRI-conditional and non-conditional cardiac implantable electronic devices: an update for radiologists

Cited by 12 publications

References 16 publications

Utilization and programming of an automatic MRI recognition feature for cardiac rhythm management devices

Utilization and programming of an automatic MRI recognition feature for cardiac rhythm management devices

MRI in patients with cardiac implantable electronic devices: A comprehensive review

Neural Network Detection of Pacemakers for MRI Safety

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