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. 2019 Jan 24;19(3):470.
doi: 10.3390/s19030470.

Vital Sign Monitoring and Cardiac Triggering at 1.5 Tesla: A Practical Solution by an MR-Ballistocardiography Fiber-Optic Sensor

Jan Nedoma  1 , Marcel Fajkus  2 , Radek Martinek  3 , Homer Nazeran  4
Affiliations

Vital Sign Monitoring and Cardiac Triggering at 1.5 Tesla: A Practical Solution by an MR-Ballistocardiography Fiber-Optic Sensor

Jan Nedoma et al. Sensors (Basel). .

Abstract

This article presents a solution for continuous monitoring of both respiratory rate (RR) and heart rate (HR) inside Magnetic Resonance Imaging (MRI) environments by a novel ballistocardiography (BCG) fiber-optic sensor. We designed and created a sensor based on the Fiber Bragg Grating (FBG) probe encapsulated inside fiberglass (fiberglass is a composite material made up of glass fiber, fabric, and cured synthetic resin). Due to this, the encapsulation sensor is characterized by very small dimensions (30 × 10 × 0.8 mm) and low weight (2 g). We present original results of real MRI measurements (conventionally most used 1.5 T MR scanner) involving ten volunteers (six men and four women) by performing conventional electrocardiography (ECG) to measure the HR and using a Pneumatic Respiratory Transducer (PRT) for RR monitoring. The acquired sensor data were compared against real measurements using the objective Bland⁻Altman method, and the functionality of the sensor was validated (95.36% of the sensed values were within the ±1.96 SD range for the RR determination and 95.13% of the values were within the ±1.96 SD range for the HR determination) by this means. The accuracy of this sensor was further characterized by a relative error below 5% (4.64% for RR and 4.87% for HR measurements). The tests carried out in an MRI environment demonstrated that the presence of the FBG sensor in the MRI scanner does not affect the quality of this imaging modality. The results also confirmed the possibility of using the sensor for cardiac triggering at 1.5 T (for synchronization and gating of cardiovascular magnetic resonance) and for cardiac triggering when a Diffusion Weighted Imaging (DWI) is used.

Keywords: MRI-compatible; ballistocardiography (BCG); cardiac triggering; fiber bragg grating (FBG); fiberglass; heart rate (HR); respiratory rate (RR).

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
ECG signal in various types of magnetic fields (0 T, 1.5 T and 3 T).
Figure 2
Figure 2
Blog diagram of the FBG structure.
Figure 3
Figure 3
A prototype of created and designed measuring sensor.
Figure 4
Figure 4
A reflection spectrum of the Bragg grating before and after encapsulation.
Figure 5
Figure 5
The dependence of Bragg wavelength on the temperature during the temperature loading in the temperature box.
Figure 6
Figure 6
Sample recordings of electrocardiogram (ECG) and Ballistocardiography (BCG) signals.
Figure 7
Figure 7
Signal processing from the FBG sensor to determine respiratory and heart rate [44].
Figure 8
Figure 8
Positioning of the FBG sensor on the human body and the experimental setup.
Figure 9
Figure 9
(a) a schematic location of the FBG sensor on the human body; (b) a photo taken during a real measurement (test subject M1).
Figure 10
Figure 10
A sample recording of breathing activity using the FBG and the reference device: (a) M1 volunteer, and (b) F1 volunteer.
Figure 11
Figure 11
The full-time course of breathing activity over the conducted MRI examinations: (a) volunteer M1, and (b) volunteer F1.
Figure 12
Figure 12
Reproducibility of RR determination capabilities of our FBG sensor (based on comparison with Pneumatic Respiratory Transducer-based RR calculations) using the Bland–Altman method for the data acquired from: (a) volunteer M1, and (b) volunteer F1.
Figure 13
Figure 13
Ten-second long sample recordings of the heart activity; (a) M1 volunteer, and (b) F1 volunteer.
Figure 14
Figure 14
The full-time course of cardiac activity over the conducted MRI examinations: (a) volunteer M1, and (b) volunteer F1.
Figure 15
Figure 15
Reproducibility of HR determination capabilities of our FBG sensor (based on comparison with ECG-based HR calculations) using the Bland–Altman analysis method and data acquired from: (a) volunteer M1, and (b) volunteer F1.
Figure 16
Figure 16
A sample MRI image (axial view) showing where the FBG sensor was positioned: A GE T2-weighted image (400 × 400 pixels).
Figure 17
Figure 17
(a) An example of ECG signal interference in DWI MRI sequences, (b) An example of a signal obtained from the FBG sensor before and after filtering.
Figure 18
Figure 18
Example of analyzed R–J interval.
See this image and copyright information in PMC

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