Automatic Detection of Coil Position in the Chest X-ray Images for Assessing the Risks of Lead Extraction Procedures

Yingliang Ma, Vishal S Mehta, C. Aldo Rinaldi, Pengpeng Hu, Steven Niederer, Reza Razavi

Research output: Chapter in Book/Report/Conference proceedingConference proceedingpeer-review

1 Citation (Scopus)

Abstract

The lead extraction procedures are for the patients who already have pacemaker implanted and leads need to be replaced. The procedure is a high-risk procedure and it could lead to major complications or even procedure-related death. Recently, an Electra Registry Outcome Score (EROS) was designed to create a risk assessment tool using the data about personal health records and an accuracy of 0.70 was achieved. In this paper, we hypothesized that a coil inside the superior vena cava (SVC) is a very important risk factor. By integrating it into the risk assessment model, the accuracy can be further improved. Therefore, an automatic detection method was developed to localize the positions of coils in the X-ray images. It was based on a U-Net convolutional network. To determine the coil position relative to the SVC position inside the chest X-ray image, the heart region was first detected by using a modified VGG16 model. Then, the bounding box of the SVC can be estimated based on the heart anatomy. Finally, a XGBoost classifier was trained on the data about personal health records and the risk factor about the coil position. An accuracy of 0.85 was achieved.
Original languageEnglish
Title of host publicationFunctional Imaging and Modeling of the Heart
Subtitle of host publication12th International Conference, FIMH 2023, Proceedings
EditorsOlivier Bernard, Patrick Clarysse, Nicolas Duchateau, Jacques Ohayon, Magalie Viallon
PublisherSpringer
Pages310-319
Number of pages10
ISBN (Electronic)978-3-031-35302-4
ISBN (Print)978-3-031-35301-7
DOIs
Publication statusE-pub ahead of print - 16 Jun 2023
Event12th International Conference On Functional Imaging And Modeling Of The Heart - Lyon, France
Duration: 19 Jun 202322 Jun 2023
https://fimh2023.sciencesconf.org/

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume13958
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th International Conference On Functional Imaging And Modeling Of The Heart
Abbreviated titleFIMH2023
Country/TerritoryFrance
CityLyon
Period19/06/2322/06/23
Internet address

Keywords

  • deep learning
  • wire detection
  • risk assessment

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