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3D Geometry of the Aortic Valve: The Future of Aortic Valve Repair or Just Another Measurement?
Author’s Accepted Manuscript 3D Geometry of the AV: The Future of AV Repair or Just Another Measurement? M. Megan Chacon, Nicholas W. Markin, Sasha K. Shillcutt www.elsevier.com/locate/buildenv
PII: DOI: Reference:
S1053-0770(17)30364-6 http://dx.doi.org/10.1053/j.jvca.2017.04.009 YJCAN4091
To appear in: Journal of Cardiothoracic and Vascular Anesthesia Cite this article as: M. Megan Chacon, Nicholas W. Markin and Sasha K. Shillcutt, 3D Geometry of the AV: The Future of AV Repair or Just Another Measurement?, Journal of Cardiothoracic and Vascular Anesthesia, http://dx.doi.org/10.1053/j.jvca.2017.04.009 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
1 3D Geometry of the AV: The Future of AV Repair or Just Another Measurement? Corresponding Author: M. Megan Chacon, MD Assistant Professor University of Nebraska Medical Center Omaha, Nebraska 68198-4455 [email protected] Nicholas W. Markin, MD, FASE Assistant Professor University of Nebraska Medical Center Omaha, Nebraska 68198-4455 Sasha K. Shillcutt, MD, MS, FASE Associate Professor University of Nebraska Medical Center Omaha, Nebraska 68198-4455 Conflicts of interest: Dr. M. Megan Chacon and Dr. Nicholas Markin have no conflicts to disclose. Dr. Sasha Shillcutt is a consultant for e-echocardiography.
EDITORIAL Traditional surgical management of aortic valve insufficiency has been largely limited to aortic valve replacement or composite valve and root replacement.[1] Aortic valve repair has known advantages over aortic valve replacement though aortic replacement is far more common. Long-term complications of prosthetic valve implantation include thromboembolism, endocarditis, and dysfunction requiring reoperation. Mechanical valve implantation requires the patient to take lifelong anticoagulation therapy. As surgical techniques in aortic valve repair continue to evolve, there is a need to improve our understanding of patient-specific aortic valve anatomy. Understanding the structure of the aortic valve apparatus and the mechanism of
2
aortic insufficiency (AI) is required to determine if a patient is a candidate for aortic valve repair. As the classification of mitral valve disease by Carpentier [2] was largely responsible for further advances in techniques for mitral valve repair, the development of a functional classification system for AI has helped to guide aortic valve repair strategy and may predict post-repair outcome.[3] The aortic valve structure includes both the aortic valve annulus and the valve cusps. The interaction between the annulus and the cusps is the main determinant of valve function. When considering the structure of the aortic valve apparatus, knowledge of the anatomy of the surrounding structures is crucial. The functional aortic annulus (FAA) is comprised of three distinct components: the aortic valve annulus and cusps, the sinuotubular junction (STJ), and the ventriculo-aortic junction.[4] El Khoury and colleagues developed a functional classification system for aortic root and aortic valve abnormalities.[5] This was a large step toward successful aortic valve repair as it provides cardiologists, cardiac surgeons, and cardiac anesthesiologists with a common language to communicate the etiology and pathology of aortic valve disease.[3] The mechanism of AI is important for successful surgical repair techniques. The aortic valve annulus is not a single structure, but includes both the ventriculo-aortic and the sino-tubular junction. AI results from either diseased aortic valve leaflets, or from an enlarged aortic root, preventing correct apposition of the leaflets.[6] Common leaflet pathologies causing AI include senile calcifications, bicuspid valves, infective endocarditis, and rheumatic disease. Causes of AI due to aortic pathology include idiopathic aortic root dilation, collagen vascular disease, and aortic dissection. El Khoury and colleagues described a repair-oriented classification of AI.[3, 5] Type 1 AI is associated with normal leaflet motion. Therefore, the regurgitation is due to
3
dilation of the STJ, ascending aorta, sinuses of Valsalva, or the ventriculo-aortic junction (type 1a-1c). Repair of these types of lesions includes STJ remodeling by graft, aortic valve sparing aortic root repair, or sub-commissural annuloplasty. Type 1d is due to cusp perforation without abnormality of the aortic annulus, typically repaired by autologous or bovine pericardial patch. Type II AI is due to excessive cusp tissue, such as leaflet prolapse. Type III AI is due to leaflet restriction, such as the restriction that occurs from degenerative or calcified leaflets. Types II and III AI may be repaired by prolapse repair techniques or decalcification. Restrictive leaflet pathology due to fibrosis or calcification and the need for partial cusp replacement are predictors for recurrent AI after repair.[3, 7] Two-dimensional transesophageal echocardiography (TEE) examination allows description of the aortic valve leaflets and commissures. Characteristics such as redundancy, restriction, cusp height, mobility, fusion, alignment, and thickness of the valve are well described using TEE. Measurements of the left ventricular outflow tract (LVOT), aortic valve annulus, aortic root, STJ, and ascending aorta can be reliably performed.[6] AI severity is visually assessed using color flow Doppler and spectral Doppler. Central and eccentric jets suggest different pathologies of AI. Semi-quantitative measures such as ratio of regurgitant jet width to LVOT width are evaluated in all patients due to its simplicity, assessed in the midesophageal aortic valve long axis view. Quantification of severity is done by vena contract or effective regurgitant orifice area calculation. Pulse wave Doppler (PWD) can evaluate diastolic reversal in the descending aorta. Continuous wave Doppler (CWD) in the deep transgastric long axis view allows calculation of pressure half time, although this finding should serve as complementary data for AV assessment as it is influenced by chamber compliance and pressures.[6]
4
3D technology has vastly improved successful mitral valve repair techniques. Similarly, a 3D representation and understanding of the functional aortic valve may do the same for advancing techniques in aortic valve repair. In this issue, Khamooshian and colleagues propose an innovative and feasible technique using 3D technology to create a patient-specific model of the aortic valve apparatus. Advanced 3D tools to quantify the geometry of the aortic root are promising, and may be valuable to better predicting graft size and determining the extent of need for leaflet remodeling in patients that qualify for valve-sparing aortic root repair.[8] Individualized models that can predict success or calculate ideal leaflet length for the valve is key to providing more opportunities for repair. This suggests that 2D imaging alone may not be sufficient to allow for the needed level of sophistication imaging. Just as the understanding of cardiac structure and function improved with the transition from m-mode imaging to 2D framed based echocardiography, the addition of 3D echocardiography has improved understanding of structure and anatomic relationships when compared to 2D imaging alone.[9]
The evolution of echocardiography has brought real-time machine learning algorithm based measurements to the echocardiographer. The user can obtain a single 3D acquisition and the software will take a series of complex three-dimension measurements of the valve and report these parameters within a short period of time, on the order of one to two minutes, as described in this issue by Khammooshian. This advancement brings forward questions of validity and applicability much in the same way that the introduction of 3D echocardiography did in decades past.[10] The question is then posed, is this type of advancement distinctly different that other past advancements? If the computerized measurements are faster and just as accurate as an expert echocardiographer’s measurements, is this not the natural evolution of
5
this technology? The authors of the ASE position paper from 2007 regarding 3D echocardiography remark that “As with any emerging technology, the enthusiasm to embrace a new technique must be tempered by a critical appraisal of the evidence supporting its use.”[10] We believe that this too is the case regarding fully automated software to measure and model the aortic valve.
Critical appraisal is an important next step in the evaluation of this technology and findings its utility in the clinical area. Prior studies comparing the accuracy of semi-automated borderdetection tracking software demonstrates relatively high levels of correlation with cardiac CT and MR measurements.[11-13] Shibayama et. al. showed on head-to-head comparison that semi-automated measurements are most similar to cardiac MR and fully automated measures less similar.[11] Other groups also show the semi-automated processes have good correlation in various measurement scenarios such as virtual basal ring measurements for TAVR.[13] If the machine learning algorithm has not yet become as accurate as the semi-automated process, that is only an indication that further training of the machine learning algorithm may be needed. Therefore, at this time it is not clear how to answer the question whether fully automated machine learning algorithms can and should replace human measurement. When the human measurement and the machine learning algorithm measurement (which is based on overlaying models of the valve created from thousands of prior valve evaluations) differ from each other, who is right or who performs the tie-breaker?
In this month’s Journal, Khamooshian and colleagues investigate the ability of one software to measure the aortic annulus and the adjacent anatomic structures in a feasibility study. The
6
authors demonstrate both the ability of the software to measure and track dynamic changes to the size of the aortic valve and the ability of the software to quickly measure and perform 3D modeling. As discussed in the accompanied article, aortic anatomy is complex and no single 2D image can fully represent the complexity of the valve. This modeling software performs the measurements quickly. If further studies can demonstrate optimal anatomy and important anatomical and structural relationships unique to functional and durable valves and their repairs, this technology may allow for improved valve repair. Further studies comparing these automated measurements and models to time-intensive human-derived measurements and models must be the next step in this critical appraisal. The feasibility study presented here should inspire future work on the assessment of accuracy and reliability of these systems to give the clinician the correct information.
As echocardiographers transitioned from M-mode to 2D, and certainly from 2D to 3D, skills were lost that were no longer needed in the age of new technology. M-mode interpretation gave way to 2D imaging and better understanding of cardiac function. 2D evaluation of the mitral valve through systematic evaluation of the leaflets in multiple planes has been replaced by many with 3D representations leading to a better appreciation of complex anatomy. We may find that future echocardiographers are less troubled with measurements and objective data point acquisition such as left ventricular ejection fraction and stroke volume. The future burden of echocardiography may involve the more difficult aspects of what to do with the information once you have it and how to base clinical decisions on that information to guide intraoperative patient care.
7
REFERENCES 1.
Boodhwani, M. and G. El Khoury, Aortic valve repair: indications and outcomes. Curr Cardiol Rep, 2014. 16(6): p. 490.
2.
Carpentier, A., Cardiac valve surgery--the "French correction". J Thorac Cardiovasc Surg, 1983. 86(3): p. 323-37.
3.
Boodhwani, M., et al., Repair-oriented classification of aortic insufficiency: impact on surgical techniques and clinical outcomes. J Thorac Cardiovasc Surg, 2009. 137(2): p. 286-94.
4.
Underwood, M.J., et al., The aortic root: structure, function, and surgical reconstruction. Heart, 2000. 83(4): p. 376-80.
5.
El Khoury, G., et al., Functional classification of aortic root/valve abnormalities and their correlation with etiologies and surgical procedures. Curr Opin Cardiol, 2005. 20(2): p. 115-21.
6.
Lancellotti, P., et al., European Association of Echocardiography recommendations for the assessment of valvular regurgitation. Part 1: aortic and pulmonary regurgitation (native valve disease). Eur J Echocardiogr, 2010. 11(3): p. 223-44.
7.
Schneider, U., et al., Two decades of experience with root remodeling and valve repair for bicuspid aortic valves. J Thorac Cardiovasc Surg, 2017. 153(4): p. S65-S71.
8.
Muraru, D., et al., Assessment of aortic valve complex by three-dimensional echocardiography: a framework for its effective application in clinical practice. Eur Heart J Cardiovasc Imaging, 2012. 13(7): p. 541-55.
8
9.
Shiota, T., 3D echocardiography: the present and the future. J Cardiol, 2008. 52(3): p. 169-85.
10.
Hung, J., et al., 3D echocardiography: a review of the current status and future directions. J Am Soc Echocardiogr, 2007. 20(3): p. 213-33.
11.
Shibayama, K., et al., Evaluation of automated measurement of left ventricular volume by novel real-time 3-dimensional echocardiographic system: Validation with cardiac magnetic resonance imaging and 2-dimensional echocardiography. J Cardiol, 2013. 61(4): p. 281-8.
12.
Heo, R., et al., Automated quantification of left atrial size using three-beat averaging real-time three dimensional Echocardiography in patients with atrial fibrillation. Cardiovasc Ultrasound, 2015. 13: p. 38.
13.
Mediratta, A., et al., 3D echocardiographic analysis of aortic annulus for transcatheter aortic valve replacement using novel aortic valve quantification software: Comparison with computed tomography. Echocardiography, 2017.
PII: DOI: Reference:
S1053-0770(17)30364-6 http://dx.doi.org/10.1053/j.jvca.2017.04.009 YJCAN4091
To appear in: Journal of Cardiothoracic and Vascular Anesthesia Cite this article as: M. Megan Chacon, Nicholas W. Markin and Sasha K. Shillcutt, 3D Geometry of the AV: The Future of AV Repair or Just Another Measurement?, Journal of Cardiothoracic and Vascular Anesthesia, http://dx.doi.org/10.1053/j.jvca.2017.04.009 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
1 3D Geometry of the AV: The Future of AV Repair or Just Another Measurement? Corresponding Author: M. Megan Chacon, MD Assistant Professor University of Nebraska Medical Center Omaha, Nebraska 68198-4455 [email protected] Nicholas W. Markin, MD, FASE Assistant Professor University of Nebraska Medical Center Omaha, Nebraska 68198-4455 Sasha K. Shillcutt, MD, MS, FASE Associate Professor University of Nebraska Medical Center Omaha, Nebraska 68198-4455 Conflicts of interest: Dr. M. Megan Chacon and Dr. Nicholas Markin have no conflicts to disclose. Dr. Sasha Shillcutt is a consultant for e-echocardiography.
EDITORIAL Traditional surgical management of aortic valve insufficiency has been largely limited to aortic valve replacement or composite valve and root replacement.[1] Aortic valve repair has known advantages over aortic valve replacement though aortic replacement is far more common. Long-term complications of prosthetic valve implantation include thromboembolism, endocarditis, and dysfunction requiring reoperation. Mechanical valve implantation requires the patient to take lifelong anticoagulation therapy. As surgical techniques in aortic valve repair continue to evolve, there is a need to improve our understanding of patient-specific aortic valve anatomy. Understanding the structure of the aortic valve apparatus and the mechanism of
2
aortic insufficiency (AI) is required to determine if a patient is a candidate for aortic valve repair. As the classification of mitral valve disease by Carpentier [2] was largely responsible for further advances in techniques for mitral valve repair, the development of a functional classification system for AI has helped to guide aortic valve repair strategy and may predict post-repair outcome.[3] The aortic valve structure includes both the aortic valve annulus and the valve cusps. The interaction between the annulus and the cusps is the main determinant of valve function. When considering the structure of the aortic valve apparatus, knowledge of the anatomy of the surrounding structures is crucial. The functional aortic annulus (FAA) is comprised of three distinct components: the aortic valve annulus and cusps, the sinuotubular junction (STJ), and the ventriculo-aortic junction.[4] El Khoury and colleagues developed a functional classification system for aortic root and aortic valve abnormalities.[5] This was a large step toward successful aortic valve repair as it provides cardiologists, cardiac surgeons, and cardiac anesthesiologists with a common language to communicate the etiology and pathology of aortic valve disease.[3] The mechanism of AI is important for successful surgical repair techniques. The aortic valve annulus is not a single structure, but includes both the ventriculo-aortic and the sino-tubular junction. AI results from either diseased aortic valve leaflets, or from an enlarged aortic root, preventing correct apposition of the leaflets.[6] Common leaflet pathologies causing AI include senile calcifications, bicuspid valves, infective endocarditis, and rheumatic disease. Causes of AI due to aortic pathology include idiopathic aortic root dilation, collagen vascular disease, and aortic dissection. El Khoury and colleagues described a repair-oriented classification of AI.[3, 5] Type 1 AI is associated with normal leaflet motion. Therefore, the regurgitation is due to
3
dilation of the STJ, ascending aorta, sinuses of Valsalva, or the ventriculo-aortic junction (type 1a-1c). Repair of these types of lesions includes STJ remodeling by graft, aortic valve sparing aortic root repair, or sub-commissural annuloplasty. Type 1d is due to cusp perforation without abnormality of the aortic annulus, typically repaired by autologous or bovine pericardial patch. Type II AI is due to excessive cusp tissue, such as leaflet prolapse. Type III AI is due to leaflet restriction, such as the restriction that occurs from degenerative or calcified leaflets. Types II and III AI may be repaired by prolapse repair techniques or decalcification. Restrictive leaflet pathology due to fibrosis or calcification and the need for partial cusp replacement are predictors for recurrent AI after repair.[3, 7] Two-dimensional transesophageal echocardiography (TEE) examination allows description of the aortic valve leaflets and commissures. Characteristics such as redundancy, restriction, cusp height, mobility, fusion, alignment, and thickness of the valve are well described using TEE. Measurements of the left ventricular outflow tract (LVOT), aortic valve annulus, aortic root, STJ, and ascending aorta can be reliably performed.[6] AI severity is visually assessed using color flow Doppler and spectral Doppler. Central and eccentric jets suggest different pathologies of AI. Semi-quantitative measures such as ratio of regurgitant jet width to LVOT width are evaluated in all patients due to its simplicity, assessed in the midesophageal aortic valve long axis view. Quantification of severity is done by vena contract or effective regurgitant orifice area calculation. Pulse wave Doppler (PWD) can evaluate diastolic reversal in the descending aorta. Continuous wave Doppler (CWD) in the deep transgastric long axis view allows calculation of pressure half time, although this finding should serve as complementary data for AV assessment as it is influenced by chamber compliance and pressures.[6]
4
3D technology has vastly improved successful mitral valve repair techniques. Similarly, a 3D representation and understanding of the functional aortic valve may do the same for advancing techniques in aortic valve repair. In this issue, Khamooshian and colleagues propose an innovative and feasible technique using 3D technology to create a patient-specific model of the aortic valve apparatus. Advanced 3D tools to quantify the geometry of the aortic root are promising, and may be valuable to better predicting graft size and determining the extent of need for leaflet remodeling in patients that qualify for valve-sparing aortic root repair.[8] Individualized models that can predict success or calculate ideal leaflet length for the valve is key to providing more opportunities for repair. This suggests that 2D imaging alone may not be sufficient to allow for the needed level of sophistication imaging. Just as the understanding of cardiac structure and function improved with the transition from m-mode imaging to 2D framed based echocardiography, the addition of 3D echocardiography has improved understanding of structure and anatomic relationships when compared to 2D imaging alone.[9]
The evolution of echocardiography has brought real-time machine learning algorithm based measurements to the echocardiographer. The user can obtain a single 3D acquisition and the software will take a series of complex three-dimension measurements of the valve and report these parameters within a short period of time, on the order of one to two minutes, as described in this issue by Khammooshian. This advancement brings forward questions of validity and applicability much in the same way that the introduction of 3D echocardiography did in decades past.[10] The question is then posed, is this type of advancement distinctly different that other past advancements? If the computerized measurements are faster and just as accurate as an expert echocardiographer’s measurements, is this not the natural evolution of
5
this technology? The authors of the ASE position paper from 2007 regarding 3D echocardiography remark that “As with any emerging technology, the enthusiasm to embrace a new technique must be tempered by a critical appraisal of the evidence supporting its use.”[10] We believe that this too is the case regarding fully automated software to measure and model the aortic valve.
Critical appraisal is an important next step in the evaluation of this technology and findings its utility in the clinical area. Prior studies comparing the accuracy of semi-automated borderdetection tracking software demonstrates relatively high levels of correlation with cardiac CT and MR measurements.[11-13] Shibayama et. al. showed on head-to-head comparison that semi-automated measurements are most similar to cardiac MR and fully automated measures less similar.[11] Other groups also show the semi-automated processes have good correlation in various measurement scenarios such as virtual basal ring measurements for TAVR.[13] If the machine learning algorithm has not yet become as accurate as the semi-automated process, that is only an indication that further training of the machine learning algorithm may be needed. Therefore, at this time it is not clear how to answer the question whether fully automated machine learning algorithms can and should replace human measurement. When the human measurement and the machine learning algorithm measurement (which is based on overlaying models of the valve created from thousands of prior valve evaluations) differ from each other, who is right or who performs the tie-breaker?
In this month’s Journal, Khamooshian and colleagues investigate the ability of one software to measure the aortic annulus and the adjacent anatomic structures in a feasibility study. The
6
authors demonstrate both the ability of the software to measure and track dynamic changes to the size of the aortic valve and the ability of the software to quickly measure and perform 3D modeling. As discussed in the accompanied article, aortic anatomy is complex and no single 2D image can fully represent the complexity of the valve. This modeling software performs the measurements quickly. If further studies can demonstrate optimal anatomy and important anatomical and structural relationships unique to functional and durable valves and their repairs, this technology may allow for improved valve repair. Further studies comparing these automated measurements and models to time-intensive human-derived measurements and models must be the next step in this critical appraisal. The feasibility study presented here should inspire future work on the assessment of accuracy and reliability of these systems to give the clinician the correct information.
As echocardiographers transitioned from M-mode to 2D, and certainly from 2D to 3D, skills were lost that were no longer needed in the age of new technology. M-mode interpretation gave way to 2D imaging and better understanding of cardiac function. 2D evaluation of the mitral valve through systematic evaluation of the leaflets in multiple planes has been replaced by many with 3D representations leading to a better appreciation of complex anatomy. We may find that future echocardiographers are less troubled with measurements and objective data point acquisition such as left ventricular ejection fraction and stroke volume. The future burden of echocardiography may involve the more difficult aspects of what to do with the information once you have it and how to base clinical decisions on that information to guide intraoperative patient care.
7
REFERENCES 1.
Boodhwani, M. and G. El Khoury, Aortic valve repair: indications and outcomes. Curr Cardiol Rep, 2014. 16(6): p. 490.
2.
Carpentier, A., Cardiac valve surgery--the "French correction". J Thorac Cardiovasc Surg, 1983. 86(3): p. 323-37.
3.
Boodhwani, M., et al., Repair-oriented classification of aortic insufficiency: impact on surgical techniques and clinical outcomes. J Thorac Cardiovasc Surg, 2009. 137(2): p. 286-94.
4.
Underwood, M.J., et al., The aortic root: structure, function, and surgical reconstruction. Heart, 2000. 83(4): p. 376-80.
5.
El Khoury, G., et al., Functional classification of aortic root/valve abnormalities and their correlation with etiologies and surgical procedures. Curr Opin Cardiol, 2005. 20(2): p. 115-21.
6.
Lancellotti, P., et al., European Association of Echocardiography recommendations for the assessment of valvular regurgitation. Part 1: aortic and pulmonary regurgitation (native valve disease). Eur J Echocardiogr, 2010. 11(3): p. 223-44.
7.
Schneider, U., et al., Two decades of experience with root remodeling and valve repair for bicuspid aortic valves. J Thorac Cardiovasc Surg, 2017. 153(4): p. S65-S71.
8.
Muraru, D., et al., Assessment of aortic valve complex by three-dimensional echocardiography: a framework for its effective application in clinical practice. Eur Heart J Cardiovasc Imaging, 2012. 13(7): p. 541-55.
8
9.
Shiota, T., 3D echocardiography: the present and the future. J Cardiol, 2008. 52(3): p. 169-85.
10.
Hung, J., et al., 3D echocardiography: a review of the current status and future directions. J Am Soc Echocardiogr, 2007. 20(3): p. 213-33.
11.
Shibayama, K., et al., Evaluation of automated measurement of left ventricular volume by novel real-time 3-dimensional echocardiographic system: Validation with cardiac magnetic resonance imaging and 2-dimensional echocardiography. J Cardiol, 2013. 61(4): p. 281-8.
12.
Heo, R., et al., Automated quantification of left atrial size using three-beat averaging real-time three dimensional Echocardiography in patients with atrial fibrillation. Cardiovasc Ultrasound, 2015. 13: p. 38.
13.
Mediratta, A., et al., 3D echocardiographic analysis of aortic annulus for transcatheter aortic valve replacement using novel aortic valve quantification software: Comparison with computed tomography. Echocardiography, 2017.