Singular Novel <i>Technology</i> With Varied <i>Techniques</i> For Implementation

Friedman, Paul A.; Asirvatham, Samuel J.; Prystowsky, Eric N.

doi:10.1111/jce.13104

Cited by 2 publications

(1 citation statement)

References 4 publications

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“…4); the resulting four combined categories (per safety level) underwent accuracy assessment. • Simultaneous visualization of fixation helix and distal battery chevron 53,54 (and)…”

Section: Evaluation and Support Of The Evolving Llied Model For Devic...mentioning

confidence: 99%

Pre-deployment assessment of an AI model to assist radiologists in chest X-ray detection and identification of lead-less implanted electronic devices for pre-MRI safety screening: realized implementation needs and proposed operational solutions

et al. 2022

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Purpose: Chest X-ray (CXR) use in pre-MRI safety screening, such as for lead-less implanted electronic device (LLIED) recognition, is common. To assist CXR interpretation, we "predeployed" an artificial intelligence (AI) model to assess (1) accuracies in LLIED-type (and consequently safety-level) identification, (2) safety implications of LLIED nondetections or misidentifications, (3) infrastructural or workflow requirements, and (4) demands related to model adaptation to real-world conditions.Approach: A two-tier cascading methodology for LLIED detection/localization and identification on a frontal CXR was applied to evaluate the performance of the original nine-class AI model. With the unexpected early appearance of LLIED types during simulated real-world trialing, retraining of a newer 12-class version preceded retrialing. A zero footprint (ZF) graphical user interface (GUI)/viewer with DICOM-based output was developed for inference-result display and adjudication, supporting end-user engagement and model continuous learning and/or modernization.Results: During model testing or trialing using both the nine-class and 12-class models, robust detection/localization was consistently 100%, with mAP 0.99 from fivefold cross-validation. Safety-level categorization was high during both testing (AUC ≥ 0.98 and ≥0.99, respectively) and trialing (accuracy 98% and 97%, respectively). LLIED-type identifications by the two models during testing (1) were 98.9% and 99.5% overall correct and (2) consistently showed AUC ≥ 0.92 (1.00 for 8/9 and 9/12 LLIED-types, respectively). Pre-deployment trialing of both models demonstrated overall type-identification accuracies of 94.5% and 95%, respectively. Of the small number of misidentifications, none involved MRI-stringently conditional or MRIunsafe types of LLIEDs. Optimized ZF GUI/viewer operations led to greater user-friendliness for radiologist engagement.Conclusions: Our LLIED-related AI methodology supports (1) 100% detection sensitivity, (2) high identification (including MRI-safety) accuracy, and (3) future model deployment with facilitated inference-result display and adjudication for ongoing model adaptation to future realworld experiences.

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“…4); the resulting four combined categories (per safety level) underwent accuracy assessment. • Simultaneous visualization of fixation helix and distal battery chevron 53,54 (and)…”

Section: Evaluation and Support Of The Evolving Llied Model For Devic...mentioning

confidence: 99%

Pre-deployment assessment of an AI model to assist radiologists in chest X-ray detection and identification of lead-less implanted electronic devices for pre-MRI safety screening: realized implementation needs and proposed operational solutions

et al. 2022

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Percutaneous access to the heart: Nontraditional approaches for the electrophysiologist

Asirvatham¹

2018

Cardiovasc electrophysiol

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Singular Novel Technology With Varied Techniques For Implementation

Cited by 2 publications

References 4 publications

Pre-deployment assessment of an AI model to assist radiologists in chest X-ray detection and identification of lead-less implanted electronic devices for pre-MRI safety screening: realized implementation needs and proposed operational solutions

Pre-deployment assessment of an AI model to assist radiologists in chest X-ray detection and identification of lead-less implanted electronic devices for pre-MRI safety screening: realized implementation needs and proposed operational solutions

Percutaneous access to the heart: Nontraditional approaches for the electrophysiologist

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