Quantification of blood flow in the fetus with cardiovascular magnetic resonance imaging using Doppler ultrasound gating: validation against metric optimized gating

The Regional Ethical Review Board approved the study, which was performed according to the Helsinki declaration. Pregnant women with singleton pregnancies were recruited at Skane University Hospital, Lund, Sweden. Participants provided written informed consent before participating.

A prototype CMR-compatible DUS device (Northh Medical GmbH, Hamburg, Germany) was used for external cardiac gating as previously described by Kording et al. [1, 15]. The device assessed flow through the beating fetal heart and converted the Doppler signal into square wave trigger signals transferred to the CMR scanner using an auxiliary coaxial cable. The DUS transducer was placed on the maternal abdomen over the fetal thorax and fastened using an elastic belt. Accurate placement for good signal quality was achieved by testing different positions for the DUS transducer until a consistent Doppler waveform of fetal cardiac blood flow was found. In particular cases, palpation of the fetus was used to simplify the process. The DUS signal can be occasionally lost during imaging due to fetal movement or during maternal deep inhalation or exhalation for breath holds. From previous experience, it often returns spontaneously within approximately 1 min. If the DUS signal was lost and did not return, the position of the transducer was adjusted accordingly in the current study. A consistent Doppler waveform of fetal cardiac blood flow was verified before acquisition of flow data.

For the MOG method, flow data were acquired using a simulated heart rate with a constant RR interval of 525 ms in order to oversample the fetal cardiac cycle as proposed in the original description of MOG for fetal CMR [13]. Image reconstruction was performed offline using the MOG-Public Software 2.7 (https://​github.​com/​MetricOptimizedG​ating/​MOG-Public). In short, the MOG algorithm was applied to the oversampled phase-contrast raw data, taking approximately 10 min per slice. Data were then transferred back to the CMR scanner for reconstruction of standard DICOM images for analysis. The current study used the initial MOG algorithm that assumes a constant fetal heart rate for the first and second halves of data acquisition. Although a more recent MOG implementation accounting for beat-to-beat variation now exists, it requires time-consuming post-processing and is in our experience less important for flow measurements than cardiac cine imaging (unpublished data).

CMR was performed using a 1.5 T scanner (Aera, Siemens, Erlangen, Germany) with a combination of an 18-channel phased-array coil and a spine receiver coil. Data were acquired in the left decubitus position to avoid compression of the maternal inferior caval vein and potential impact on cardiovascular physiology during CMR. All CMR acquisitions were performed within a maximum limit for specific absorption rate of 2 W/kg and with limited noise levels.

Sagittal, coronal and transversal balanced steady-state free precession (bSSFP) images were acquired to localize the fetal descending aorta and the umbilical vein. Additional scout images were acquired if necessary to certify that the phase-contrast flow acquisitions were positioned perpendicular to the respective vessel. Phase-contrast quantitative flow data were acquired in the fetal descending aorta at the level of the diaphragm and in the fetal intra-abdominal umbilical vein (Fig. 1). In six fetuses, DUS-gated flow was acquired six to 12 times in both the fetal descending aorta and the umbilical vein, respectively, without repositioning the pregnant woman, to assess repeatability of DUS-gated flow measurements. Three of these six fetuses were included only to test the repeatability of the DUS-gated flow and no corresponding MOG flow images were acquired. A 2D segmented gradient recalled echo phase-contrast sequence was used during shallow maternal free breathing to limit acquisition time and reduce the likelihood of fetal movement during image acquisition. Parameters were the same for all subjects, with the exception of DUS acquisition time (TE/TR 2.76/5.03 ms, flip angle 20°, VENC 150 cm/s, in-plane resolution 1.41 × 1.41 mm, slice thickness 5 mm, acquired temporal resolution 30.18 ms, reconstructed temporal resolution 14.7 ms). Acquisition time for DUS was median 22 s (range 19–31 s) and for MOG 26 s in all acquisitions.

Images acquired by DUS gating and images reconstructed using MOG were analyzed in Segment v2.2 (Medviso AB, Lund, Sweden) [17]. Vessel delineations were performed using the same static ROI throughout the cardiac cycle or using a time-resolved ROI adjusted to the vessel contour in each time frame. Static ROI:s of different sizes were used to determine the impact of ROI size on measured flow. A circular ROI fitted to the vessel contour in the time frame with the largest vessel area was used as reference. Additional circular ROI:s were placed at the same ROI center with diameters 50, 75, 125 and 150% of that of the original 100% ROI. Flow volumes were obtained for each ROI size and expressed as percentage of the flow volume of the original 100% ROI.

Four observers at two centers (observer 1, DS, and 2, EH, in Lund; observer 3, CKM, and 4, LS, in Toronto) manually delineated the fetal descending aorta and the umbilical vein using both time-resolved and static delineations. Data are presented based on delineations by observer 1, if not otherwise stated. For time-resolved delineations an ROI was drawn around the vessel lumen in all time frames of the cardiac cycle and adapted to vessel diameter over time. For static delineations, the largest vessel area was used to determine the static ROI size and the ROI copied to all time frames of the cardiac cycle. All observers were blinded to each others’ delineations and to subject information. Observer 1 delineated all vessels twice to assess intraobserver variability. Flow assessment was generally performed without background correction. Agreement of measurements without and with linear background correction was assessed for time-resolved measurements and the impact of ROI size on flow measurements was assessed both without and with linear background correction.

All statistical analyses were performed using GraphPad (Prism v8.0.2, La Jolla, California, USA). Data in text are presented as mean ± standard deviation (SD) or median (range) as appropriate. Bias and variability were assessed as the mean difference of measurements ± SD. Coefficient of variation (CoV) was calculated as SD divided by the mean of differences and expressed as percentage. Bland-Altman analysis was performed to determine bias and 95% limits of agreement (LoA, i.e. bias ±1.96SD, which is presented in Bland-Altman graphs) for flow without and with linear background correction, time-resolved versus static delineations, intra- and interobserver agreement and agreement between DUS and MOG methods.

Descending aortic flow was 726 (348–1130) ml/min by DUS and 708 (440–1170) ml/min by MOG and umbilical venous flow was 366 (150–782) ml/min by DUS and 404 (147–697) ml/min by MOG. Figure 3 shows flow volumes by DUS and MOG and relative flow differences between methods versus gestational age. Bias±SD for flow measurements without versus with linear background correction was for descending aortic flow − 17 ± 42 ml/min (− 3 ± 6%) by DUS and − 17 ± 43 ml/min (− 3 ± 6%) by MOG, respectively, and for umbilical venous flow 33 ± 41 ml/min (8 ± 12%) by DUS and 43 ± 42 ml/min (14 ± 17%) by MOG, respectively.

Flow volumes obtained using the DUS and MOG methods showed a low bias, although with wide limits of agreement. For time-resolved delineations, bias and variability between the DUS and MOG methods for descending aortic flow and umbilical venous flow were − 45 ± 122 ml/min (− 6 ± 15%) and 19 ± 136 ml/min (2 ± 24%) (Fig. 4). For static delineations, bias and variability between the DUS and MOG methods for descending aortic flow and umbilical venous flow were − 23 ± 112 ml/min (− 2 ± 14%) and 9 ± 103 ml/min (0 ± 23%) (Fig. 4). Aliasing was present in one fetus in aortic flow data after but not before MOG reconstruction, thus not visible at acquisition. This aliased flow data set could not be unwrapped. In the same fetus aliasing was present also in the DUS-gated aortic flow data, but this flow data set could be successfully unwrapped.

Flow data from fetuses in whom DUS-gated phase-contrast images were acquired repeatedly in the fetal descending aorta and abdominal umbilical vein are shown in Fig. 5 and in Table 2. Repeated flow acquisitions by DUS gating in the same fetus showed similar flow volumes. In one subject (subject 2) one repeated umbilical venous flow was acquired at a registered fetal heart rate of 80 beats per minute. This value is far below normal and most likely represents a poor DUS signal with missed heart beat detection rather than the true fetal heart rate.

Data from flow measurements performed using varying ROI sizes are shown in Fig. 6. For flow measurements both without and with linear background correction, increase in ROI size to greater than vessel diameter caused flow volume overestimation and decrease in ROI size to smaller than vessel diameter caused flow volume underestimation. The underestimation was however relatively greater than the overestimation caused by increased ROI size.

Time-resolved versus static vessel delineations showed low bias and narrow limits of agreement (Fig. 7). Time-resolved versus static delineations showed a bias and variability for descending aortic flow of 33 ± 39 ml/min (4 ± 6%) using the DUS method and 56 ± 55 ml/min (7 ± 7%) using the MOG method, and for umbilical venous flow 11 ± 84 ml/min (2 ± 15%) using the DUS method and 1 ± 44 ml/min (0 ± 10%) using the MOG method.

For time-resolved delineations, intraobserver variability for DUS and MOG methods were for descending aortic flow 19 ± 54 ml/min (2 ± 7%) and 32 ± 55 ml/min (4 ± 6%), respectively, and for umbilical venous flow − 10 ± 73 ml/min (− 3 ± 13%) and − 2 ± 26 ml/min (− 1 ± 8%), respectively (Fig. 8). For static delineations, intraobserver variability for DUS and MOG methods were for descending aortic flow − 15 ± 96 ml/min (− 2 ± 13%) and 17 ± 59 ml/min (2 ± 9%), respectively, and for umbilical venous flow − 31 ± 62 ml/min (− 5 ± 11%) and 25 ± 67 ml/min (8 ± 17%), respectively (Fig. 8).

Interobserver variability was low between three of four observers. Interobserver variability was low in center one and between center one and one observer from center two whereas the second observer from center two measured systematically lower flow volumes. Interobserver variability between all observers is reported in Table 3 (time-resolved delineations) and Table 4 (static delineations). For time-resolved delineations, interobserver variability within centers is shown in Fig. 9.

The number of repeated scans required for flow images in subjects where both DUS and MOG acquisitions were successful were for the descending aorta 1 (1–3) by DUS and 1 (1–3) by MOG and for the umbilical vein 1 (1–3) by DUS and 1 (1–2) by MOG. The scan time is similar for both DUS and MOG, as the same sequences are used for image acquisition. The DUS device typically takes less than 5 min to position and may in some cases need repositioning as described in Methods/Gating methods. For each MOG flow image, applying the MOG algorithm offline took approximately 10 min (i.e. 20 min per fetus if only one acquisition for each vessel was performed). After applying the offline MOG algorithm, data need to be transferred back to the scanner for image reconstruction. In our hospital the scanner is available for this after regular working hours. In total, reconstructed MOG flow images for analysis thus take considerably longer to acquire. Moreover, a static vessel delineation typically takes about 20 s to perform. A time-resolved vessel delineation on the other hand consists of about 30 static delineations and takes about 5 min to perform.

This study included mainly third trimester fetuses. The current results may therefore not apply to smaller fetuses in whom fetal movement may have larger impact on stability of DUS signal and image acquisition. In addition, flow measurements in smaller fetuses may be unreliable as current standard methods are at their limit of spatial resolution versus vessel size. Development of high-resolution CMR sequences for fetal application however shows promising results. Moreover, all images were acquired in maternal free breathing and the possible effects of maternal breathing movement on quantification of fetal flow volumes was not investigated. However, as both DUS and MOG data were acquired under similar conditions, it is unlikely that the shallow maternal breathing had impact on the comparison in the current study. Finally, a direct comparison of trigger signals between the DUS and MOG methods was not possible as the DUS gating signal could not be recorded simultaneously with the MOG data acquisition and the post-processed MOG gating signal was not available for further analysis offline.