This study assessed a new methodology with a straightened model generated from the four-dimensional cardiac computed tomography sequence to obtain the desired measurements for valve sizing in the application of transcatheter pulmonary valve replacement.
The measurements of the right ventricle (RV) and pulmonary artery (PA), for selecting the optimal prosthesis size for transcatheter pulmonary valve replacement (TPVR), vary considerably. Three-dimensional (3D) computed tomography (CT) imaging for device size prediction is insufficient to assess the displacement of the right ventricular outflow tract (RVOT) and PA, which could increase the risk of stent misplacement and paravalvular leak. The aim of this study is to provide a dynamic model to visualize and quantify the anatomy of the RVOT to PA over the entire cardiac cycle by four-dimensional (4D) cardiac CT reconstruction to obtain an accurate quantitative evaluation of the required valve size. In this pilot study, cardiac CT from sheep J was chosen to illustrate the procedures. 3D cardiac CT was imported into 3D reconstruction software to build a 4D sequence which was divided into eleven frames over the cardiac cycle to visualize the deformation of the heart. Diameter, cross-sectional area, and circumference of five imaging planes at the main PA, sinotubular junction, sinus, basal plane of the pulmonary valve (BPV), and RVOT were measured at each frame in 4D straightened models prior to valve implantation to predict the valve size. Meanwhile, dynamic changes in the RV volume were also measured to evaluate right ventricular ejection fraction (RVEF). 3D measurements at the end of the diastole were obtained for comparison with the 4D measurements. In sheep J, 4D CT measurements from the straightened model resulted in the same choice of valve size for TPVR (30 mm) as 3D measurements. The RVEF of sheep J from pre-CT was 62.1 %. In contrast with 3D CT, the straightened 4D reconstruction model not only enabled accurate prediction for valve size selection for TPVR but also provided an ideal virtual reality, thus presenting a promising method for TPVR and the innovation of TPVR devices.
Dysfunction of the right ventricular outflow tract (RVOT) and pulmonary valve abnormalities are two of the most frequent consequences of severe congenital heart disease, for example, patients with repaired tetralogy of Fallot (TOF), certain types of double outlet right ventricle (DORV), and transposition of the great arteries1,2,3. The majority of these patients face multiple operations throughout their lives and along with advancing age, the risks of complexity and comorbidities increase. These patients may benefit from transcatheter pulmonary valve replacement (TPVR) as a minimally invasive treatment4. To date, there has been a steady growth in the number of patients undergoing TPVR and several thousands of these procedures have been performed worldwide. Compared with traditional open-heart surgery, TPVR requires a more accurate anatomical measurement of the xenograft or homograft from the right ventricle (RV) to pulmonary artery (PA), as well as the repair of pulmonary and RVOT stenosis via transannular patch, by computed tomography angiography (CTA) prior to intervention and to ensure that the patients are free from stent fracture and paravalvular leak (PVL)5,6.
A prospective, multicenter study demonstrated that a multidetector CT annular sizing algorithm played an important role in selecting the appropriate valve size, which could decrease the degree of paravalvular regurgitation7. In recent years, quantitative analysis has been more and more applied in clinical medicine. Quantitative analysis has enormous potential to enable objective and correct interpretation of clinical imaging and to verify that patients are free of stent fracture and paravalvular leak, which can enhance patient-specific therapy and treatment response evaluation. In previous clinical practice, it was feasible to reconstruct CT imaging from three planes (sagittal, coronal, and axial) with two-dimensional (2D) CT to obtain a visualization model8. Contrast-enhanced electrocardiogram (ECG)-gated CT has become more important in the evaluation of RVOT/PA 3D morphology and function, as well as in the identification of patients with a suitable RVOT implantation site that is capable of maintaining TPVR stability throughout the cardiac cycle9,10.
However, in the contemporary standard clinical and preclinical settings, the acquired 4D CT data are usually translated into 3D planes for manual quantification and visual evaluation which cannot show 3D/4D dynamic information11. Furthermore, even with 3D information, the measurements obtained from multiplanar reconstruction (MPR) have various limitations, such as poor quality of visualization and lack of dynamic deformation due to the different directions of blood flow in the right heart12. Measurements are time-consuming to gather and prone to mistakes, as 2D alignment and sectioning can be imprecise, resulting in misinterpretation and distensibility. Currently, there is no consensus on which measurement of RVOT-PA could reliably provide accurate information about the indications and valve sizing for TPVR in patients with dysfunctional RVOT and/or pulmonary valve disease.
In this study, the method for measuring RVOT-PA using a straightened right heart model via a 4D cardiac CT sequence is provided to determine how best to characterize the 3D deformations of RVOT-PA throughout the cardiac cycle. The spatio-temporal correlation imaging was completed by including the temporal dimension and, therefore, were able to measure variations in RVOT-PA magnitude. Additionally, the deformation of the straightened models could positively impact TPVR valve sizing and procedural planning.
All cardiac CT data were obtained from GrOwnValve preclinical trials with the approval of the legal and ethical committee of the Regional Office for Health and Social Affairs, Berlin (LAGeSo). All animals received humane care in compliance with the guidelines of the European and German Societies of Laboratory Animal Science (FELASA, GV-SOLAS). In this study, the Pre-CT from sheep J was chosen to illustrate the procedures.
1. Perform 3D cardiac CT in sheep
2. Open-source 3D reconstruction software application settings and extension installments
3. Load cardiac CT data into 3D slicer from the DICOM files
4. Create 4D beating heart volume and beating right heart volume
5. Create straightened models from the 4D sequence
NOTE: It is highly recommended to build each 10% of the cardiac cycle frame in a single 3D slicer folder, otherwise there will be too many data trees aligned in the DATA module, making it inefficient to create the straightened models. To get the single 3D slicer folder of each 10% frame, it needs to load the 4D sequence several times, choose every frame and save them in a single folder.
6. Export the figures and STL files
7. Perform five planar measurements
8. 3D multiplanar reconstruction (MPR) measurements and right ventricular volume measurement from the 3D sequence (the best-reconstructed phase at the end of diastole)
NOTE: In this study, the sheep J Pre-CT was chosen to illustrate the MPR measurement procedures.
9. Calculation for stented heart valve selection
NOTE: In this section, the measurements of the sinotubular junction were used to illustrate the procedure.
In sheep J, the 4D total heart and right heart models were successfully generated from the 4D cardiac CT sequence which showed the deformation throughout the entire cardiac cycle. For better visualization, the whole deformation of the beating heart and right heart is exhibited in every direction in Figure 3 – Figure 4 and in Video 1 – Video 2.
The straightened right heart models were obtained following the mask volume in each 10% of the segmentation to illustrate the deformations of the right heart in a straightened model in sheep J Pre-CT (Figure 5).
Five planes were added in the desired locations to perform the measurements as shown in Figure 2A, as well as the MPR measurements in 3D reconstruction software and not the conventional method of cropping the 4D volume in sheep J Pre-CT shown in Figure 2B. The changes in cross-sectional area, perimeter, and circumference were obtained in different phases of the cardiac cycle to generate the tendency diagrams as shown in Figure 6. Original data from 4D CT measurements and 3D CT measurements are shown in Supplementary file 1. In sheep J, 4D CT measurements from the straightened model resulted in the same choice of valve size for TPVR (30 mm) as the MPR measurements from the end-diastolic series, with the advantages of remarkable virtual reality and reliable results. There were significant differences in the measured cross-sectional area (RVOT: 3.42 cm2 in 4D versus 4.28 cm2 in 2D, BPV: 2.96 cm2 in 4D versus 3.92 cm2 in 2D), and circumference (RVOT: 76.1 mm in 4D versus 87.06 mm in 2D, BPV: 67.65 mm in 4D versus 75.73 mm in 2D) in RVOT and the basal plane of the pulmonary valve. The right ventricular ejection fraction of sheep J from the pre-CT was 62.1%.
Figure 1. User interface in 3- dimensional reconstruction software. Toolbar, data tree, and other functional menus of the 3- dimensional reconstruction software are shown for operating the program. Please click here to view a larger version of this figure.
Figure 2. Five planes in the straightened model for measurement and multiplanar reconstruction measurements in the 3-dimensional sequence (end-diastolic phase). (A) Plane a: main pulmonary artery, 20 mm offset from plane b; plane b: sinotubular junction; plane c: sinus of the pulmonary valve; plane d: bottom of pulmonary valve; plane e: in the right ventricular outflow tract, 10 mm offset from plane d. (B) MPR measurements in the 3D sequence of the end-diastolic phase at five planes: 10 mm offset from the bottom of the pulmonary valve, bottom of the pulmonary valve, sinus of the pulmonary valve, sinotubular junction, and main pulmonary artery (20 mm offset from sinotubular junction). Please click here to view a larger version of this figure.
Figure 3. 4-dimensional heart deformations throughout the cardiac cycle. Total heart deformations of sheep J pre-computed tomography shows the shape changes from 0% to 100% of the cardiac cycle. Please click here to view a larger version of this figure.
Figure 4. 4- dimensional right heart deformation throughout the cardiac cycle. Right heart deformations of sheep J pre- computed tomography shows the shape changes from 0% to 100% of the cardiac cycle. Please click here to view a larger version of this figure.
Figure 5. Straightened right heart deformation of the sheep J pre- computed tomography throughout the cardiac cycle. Straightened right heart deformations of sheep J pre- computed tomography shows the shape changes from 0% to 100% of the cardiac cycle. Please click here to view a larger version of this figure.
Figure 6. Changes in circumference, average diameter, cross-sectional area, and right ventricular volume throughout the cardiac cycle. (A) Changes in circumference during the cardiac cycle at the five planes. (B) Changes in average diameter (calculated using formula 1 in step 9.1) during the cardiac cycle at the five planes. (C) Changes in the cross-sectional area during the cardiac cycle at the five planes. (D) Change in right ventricular volume during the cardiac cycle. Please click here to view a larger version of this figure.
Video 1. 4- dimensional total heart deformation. Throughout the cardiac cycle, the 4-dimensional entire heart reconstruction can be visualized in every direction. Please click here to download this Video.
Video 2. 4- dimensional right heart deformation. The beating heart (superior vena cava, right atrium, right ventricle, and pulmonary artery) can be visualized in every direction throughout the entire cardiac cycle. Please click here to download this Video.
Supplementary file 1. The table presents the original data from 4D CT measurements and 3D CT measurements generated by following the protocol described including the parameters from the pulmonary artery, right ventricular volume, and the measurements of the aorta from sheep J pre- computed tomography. Please click here to download this File.
To date, this is the first study to illustrate a patient-specific measurement of the morphology and dynamic parameters of RVOT-PA with a straightened cardiac model generated from a 4D CT sequence, which can be applied to predict the optimal valve size for TPVR. This methodology wasillustrated using sheep J Pre-CT imaging to obtain the dynamic deformations, right ventricular volumes, right ventricular function, and magnitude of RVOT/PA change from the RVOT to the pulmonary trunk in five planes at every 10% reconstruction of the cardiac cycle. Compared with 3D imaging, the straightened models not only predicted the same valve size as the MPR measurements from the end-diastolic 3D images but also allowed for a more intuitive model to extract the desired information about the right heart. According to the findings of a previous study13, the proposed method allows for a better understanding of in vivo loading conditions in patients with dysfunctional RVOT and/or pulmonary valve disease, as well as the development of new TPVR devices that are morphologically adapted to the different RVOT anatomies of patients requiring TPVR and may exhibit improved mechanical performance in the long run. However, the current methodology of quantitative measurement for a pre-interventional evaluation of TPVR is based on MPR measurements in the 3D sequence, which could result in unexpected errors during evaluations based on the anatomical curve of the RVOT and PA. Furthermore, detailed information can be lost in the 3D models generated from the 4D sequence in terms of the heart's overall movement14.
In this study, a 4D beating heart model was created to observe and visualize the heart's total deformation throughout the cardiac cycle by using a mask for the 4D volume of the segmentation in 3D reconstruction software and not the conventional method of cropping the 4D volume in sheep J. This method can provide an accurate and efficient way of building a 4D model as a 3D reconstruction from a 3D sequence to visualize the heart and select the valve size. Furthermore, the same method was used to reconstruct the right heart model as a dynamic model from the segmentations in each 10% of the cardiac cycle segmented using the Grow From Seeds effect in 3D reconstruction software. The 4D right heart model can visualize the entire anatomical morphology throughout the RR interval, based on which cardiologists can develop a patient-specific strategy for TPVR. In addition, the 3D straightened right heart models obtained from the 4D sequence in each 10% of the cardiac cycle can furnish a precise, morphological, and functional quantification of the right heart, especially in the five planes applied for the stented heart valve selection. Prior to creating the straightened models, a manual and exact 3D segmentation of the right heart from each 10% cardiac cycle is required. When doing right heart segmentations, after the volume from one frame has been masked, the 3D segmentation in the current frame will emerge automatically by using the Scissor function for the undesirable structures. In order to retain the whole volume of RVOT, a tiny piece of the left coronary artery must be kept in the segmentations. To create a straightened model, it is pivotal to add a centerline into the original right heart model to ensure the quality of the straightened model and decrease the computational load. The straightened right heart model accurately reflected all the correlations of the cardiac anatomy, including perimeters, circumferences, and cross-sectional areas, allowing a subsequent extraction of morphological information and direct measurements in a holistic fashion. In this study, the measurements from the 4D straightened model resulted in the same choice of valve size (30 mm in diameter) as the 3D measurements in MPR, but with the advantages of remarkable virtual reality and reliable results in sheep J. It also enables the collection of data on right ventricular volumes during the whole cardiac cycle, which can be then applied to calculate the right ventricular ejection fraction.
Previous clinical studies have shown significant differences in the measured cross-sectional areas of RVOTPA between static and dynamic section planes secondary to large 3D displacements and rotations15. In sheep J Pre-CT, the significant differences in measured cross-sectional areas and circumferences in the RVOT plane and basal plane of the pulmonary valve were also observed in the RVOT: 3.42 cm2 in 4D versus 4.28 cm2 in 3D, BPV: 2.96 cm2 in 4D versus 3.92 cm2 in 3D, and RVOT circumferences: 76.1 mm in 4D versus 87.06 mm in 3D, BPV: 67.65 mm in 4D versus 75.73 mm in 3D. To obtain data for the measurements, the five dynamic planes were applied instead of fixed planes; here, the sinotubular plane and the basal plane of the pulmonary valve were chosen as the lines of reference. These five planes included all the space that can be utilized to deploy the stented heart valve. The RVOT plane exhibited the largest deformation throughout the cardiac cycle in the five planes, highlighting the need for a versatile TPVR device that enables adaptability to various anatomies and retains the designed geometry of the stented heart valve for long-term durability without fracture and migration. The nitinol stent with shape memory is a promising candidate for mounting a tri-leaflet valve for future TPVR. For the clinical application, especially for the patients who have had transannular patch repair or TPVR, it would need more efforts to reconstruct the anatomy as there are artifacts from the adhesion between the pericardium and myocardium, stent, and the deformed anatomy. It needs higher resolution CT data, well-developed reconstruction software, and abundant experience of CT analysis to translate this method for clinical use. But this method can be used for large animal trials as well as for the peri-operative evaluation for patients with Tetralogy of Fallot, isolated pulmonic stenosis who haven't had any open-heart surgeries or interventional therapies.
The described method for the 4D straightened model can enable accurate and visual identification and calculation of all segments of the heart from the RVOT to PA, which can help not only cardiologists to obtain a precise pre-interventional evaluation, but also cardiac engineers to innovate novel TPVR devices for future applications.
The main limitation of the methodology for the 4D straightened model measurement in this study is that the data were obtained from only one sheep pre-CT without a large sample population. Additionally, post-implantation CT imaging was not performed to follow up on the valve size and structural changes in the right heart. Lastly, for the patients who have had transannular patch repair or TPVR, it is more difficult to reconstruct the anatomy as there are artifacts from the adhesion between the pericardium and myocardium, stent, and the deformed anatomy.
Conclusion
In contrast with 3D CT, the straightened 4D reconstruction model not only enabled an accurate prediction of valve size selection for TPVR, but also provided ideal virtual reality in sheep J, and therefore will be a promising method for TPVR and the innovation of TPVR devices.
The authors have nothing to disclose.
Xiaolin Sun and Yimeng Hao contributed equally to this manuscript and share first authorship. Heartfelt appreciation is extended to all who contributed to this work, both past and present members. This work was supported by grants from the German Federal Ministry for Economic Affairs and Energy, EXIST – Transfer of Research (03EFIBE103). Xiaolin Sun and Yimeng Hao are supported by the China Scholarship Council (Xiaolin Sun- CSC: 201908080063, Yimeng Hao-CSC: 202008450028).
Adobe Illustrator | Adobe | Adobe Illustrator 2021 | Graphics software |
Butorphanol | Richter Pharma AG | Vnr531943 | 0.4mg/kg |
Fentanyl | Janssen-Cilag Pharma GmbH | DE/H/1047/001-002 | 0.01mg/kg |
Glycopyrroniumbromid | Accord Healthcare B.V | PZN11649123 | 0.011mg/kg |
GraphPad Prism | GraphPad Software Inc. | Version 9.0 | Versatile statistics software |
Imeron 400 MCT | Bracco Imaging | PZN00229978 | 2.0–2.5 ml/kg |
Ketamine | Actavis Group PTC EHF | ART.-Nr. 799-762 | 2–5 mg/kg/h |
Midazolam | Hameln pharma plus GMBH | MIDAZ50100 | 0.4mg/kg |
Multislice Somatom Definition Flash | Siemens AG | A91CT-01892-03C2-7600 | Cardiac CT Scanner |
Propofol | B. Braun Melsungen AG | PZN 11164495 | 20mg/ml, 1–2.5 mg/kg |
Propofol | B. Braun Melsungen AG | PZN 11164443 | 10mg/ml, 2.5–8.0 mg/kg/h |
Safety IV Catheter with Injection port | B. Braun Melsungen AG | LOT: 20D03G8346 | 18 G Catheter with Injection port |
3D Slicer | Slicer | Slicer 4.13.0-2021-08-13 | Software: 3D Slicer image computing platform |