Maria Gusseva , Nikhil Thatte , Daniel A. Castellanos , Peter E. Hammer , Sunil J. Ghelani , Ryan Callahan , Tarique Hussain , Radomír Chabiniok
{"title":"生物力学模型结合压力-体积环分析帮助复杂先天性心脏病患者的手术计划","authors":"Maria Gusseva , Nikhil Thatte , Daniel A. Castellanos , Peter E. Hammer , Sunil J. Ghelani , Ryan Callahan , Tarique Hussain , Radomír Chabiniok","doi":"10.1016/j.media.2024.103441","DOIUrl":null,"url":null,"abstract":"<div><div>Patients with congenitally corrected transposition of the great arteries (ccTGA) can be treated with a double switch operation (DSO) to restore the normal anatomical connection of the left ventricle (LV) to the systemic circulation and the right ventricle (RV) to the pulmonary circulation. The subpulmonary LV progressively deconditions over time due to its connection to the low pressure pulmonary circulation and needs to be retrained using a surgical pulmonary artery band (PAB) for 6–12 months prior to the DSO. The subsequent clinical follow-up, consisting of invasive cardiac pressure and non-invasive imaging data, evaluates LV preparedness for the DSO. Evaluation using standard clinical techniques has led to unacceptable LV failure rates of ∼15 % after DSO. We propose a computational modeling framework to (1) reconstruct LV and RV pressure-volume (PV) loops from non-simultaneously acquired imaging and pressure data and gather model-derived mechanical indicators of ventricular function; and (2) perform <em>in silico</em> DSO to predict the functional response of the LV when connected to the high-pressure systemic circulation.</div><div>Clinical datasets of six patients with ccTGA after PAB, consisting of cardiac magnetic resonance imaging (MRI) and right and left heart catheterization, were used to build patient-specific models of LV and RV – <span><math><msubsup><mi>M</mi><mrow><mtext>baseline</mtext></mrow><mtext>LV</mtext></msubsup></math></span> and <span><math><msubsup><mi>M</mi><mrow><mtext>baseline</mtext></mrow><mtext>RV</mtext></msubsup></math></span>. For <em>in silico</em> DSO the models of <span><math><msubsup><mi>M</mi><mrow><mtext>baseline</mtext></mrow><mtext>LV</mtext></msubsup></math></span> and <span><math><msubsup><mi>M</mi><mrow><mtext>baseline</mtext></mrow><mtext>RV</mtext></msubsup></math></span> were used while imposing the afterload of systemic and pulmonary circulations, respectively. Model-derived contractility and Pressure-Volume Area (PVA) – i.e., the sum of stroke work and potential energy – were computed for both ventricles at baseline and after <em>in silico</em> DSO.</div><div><em>In silico</em> DSO suggests that three patients would require a substantial augmentation of LV contractility between 54 % and 80 % and an increase in PVA between 38 % and 79 % with respect to the baseline values to accommodate the increased afterload of the systemic circulation. On the contrary, the baseline functional state of the remaining three patients is predicted to be adequate to sustain cardiac output after the DSO.</div><div>This work demonstrates the vast variation of LV function among patients with ccTGA and emphasizes the importance of a biventricular approach to assess patients’ readiness for DSO. Model-derived predictions have the potential to provide additional insights into planning of complex surgical interventions.</div></div>","PeriodicalId":18328,"journal":{"name":"Medical image analysis","volume":"101 ","pages":"Article 103441"},"PeriodicalIF":10.7000,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Biomechanical modeling combined with pressure-volume loop analysis to aid surgical planning in patients with complex congenital heart disease\",\"authors\":\"Maria Gusseva , Nikhil Thatte , Daniel A. Castellanos , Peter E. Hammer , Sunil J. Ghelani , Ryan Callahan , Tarique Hussain , Radomír Chabiniok\",\"doi\":\"10.1016/j.media.2024.103441\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Patients with congenitally corrected transposition of the great arteries (ccTGA) can be treated with a double switch operation (DSO) to restore the normal anatomical connection of the left ventricle (LV) to the systemic circulation and the right ventricle (RV) to the pulmonary circulation. The subpulmonary LV progressively deconditions over time due to its connection to the low pressure pulmonary circulation and needs to be retrained using a surgical pulmonary artery band (PAB) for 6–12 months prior to the DSO. The subsequent clinical follow-up, consisting of invasive cardiac pressure and non-invasive imaging data, evaluates LV preparedness for the DSO. Evaluation using standard clinical techniques has led to unacceptable LV failure rates of ∼15 % after DSO. We propose a computational modeling framework to (1) reconstruct LV and RV pressure-volume (PV) loops from non-simultaneously acquired imaging and pressure data and gather model-derived mechanical indicators of ventricular function; and (2) perform <em>in silico</em> DSO to predict the functional response of the LV when connected to the high-pressure systemic circulation.</div><div>Clinical datasets of six patients with ccTGA after PAB, consisting of cardiac magnetic resonance imaging (MRI) and right and left heart catheterization, were used to build patient-specific models of LV and RV – <span><math><msubsup><mi>M</mi><mrow><mtext>baseline</mtext></mrow><mtext>LV</mtext></msubsup></math></span> and <span><math><msubsup><mi>M</mi><mrow><mtext>baseline</mtext></mrow><mtext>RV</mtext></msubsup></math></span>. For <em>in silico</em> DSO the models of <span><math><msubsup><mi>M</mi><mrow><mtext>baseline</mtext></mrow><mtext>LV</mtext></msubsup></math></span> and <span><math><msubsup><mi>M</mi><mrow><mtext>baseline</mtext></mrow><mtext>RV</mtext></msubsup></math></span> were used while imposing the afterload of systemic and pulmonary circulations, respectively. Model-derived contractility and Pressure-Volume Area (PVA) – i.e., the sum of stroke work and potential energy – were computed for both ventricles at baseline and after <em>in silico</em> DSO.</div><div><em>In silico</em> DSO suggests that three patients would require a substantial augmentation of LV contractility between 54 % and 80 % and an increase in PVA between 38 % and 79 % with respect to the baseline values to accommodate the increased afterload of the systemic circulation. On the contrary, the baseline functional state of the remaining three patients is predicted to be adequate to sustain cardiac output after the DSO.</div><div>This work demonstrates the vast variation of LV function among patients with ccTGA and emphasizes the importance of a biventricular approach to assess patients’ readiness for DSO. Model-derived predictions have the potential to provide additional insights into planning of complex surgical interventions.</div></div>\",\"PeriodicalId\":18328,\"journal\":{\"name\":\"Medical image analysis\",\"volume\":\"101 \",\"pages\":\"Article 103441\"},\"PeriodicalIF\":10.7000,\"publicationDate\":\"2024-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Medical image analysis\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1361841524003669\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical image analysis","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1361841524003669","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Biomechanical modeling combined with pressure-volume loop analysis to aid surgical planning in patients with complex congenital heart disease
Patients with congenitally corrected transposition of the great arteries (ccTGA) can be treated with a double switch operation (DSO) to restore the normal anatomical connection of the left ventricle (LV) to the systemic circulation and the right ventricle (RV) to the pulmonary circulation. The subpulmonary LV progressively deconditions over time due to its connection to the low pressure pulmonary circulation and needs to be retrained using a surgical pulmonary artery band (PAB) for 6–12 months prior to the DSO. The subsequent clinical follow-up, consisting of invasive cardiac pressure and non-invasive imaging data, evaluates LV preparedness for the DSO. Evaluation using standard clinical techniques has led to unacceptable LV failure rates of ∼15 % after DSO. We propose a computational modeling framework to (1) reconstruct LV and RV pressure-volume (PV) loops from non-simultaneously acquired imaging and pressure data and gather model-derived mechanical indicators of ventricular function; and (2) perform in silico DSO to predict the functional response of the LV when connected to the high-pressure systemic circulation.
Clinical datasets of six patients with ccTGA after PAB, consisting of cardiac magnetic resonance imaging (MRI) and right and left heart catheterization, were used to build patient-specific models of LV and RV – and . For in silico DSO the models of and were used while imposing the afterload of systemic and pulmonary circulations, respectively. Model-derived contractility and Pressure-Volume Area (PVA) – i.e., the sum of stroke work and potential energy – were computed for both ventricles at baseline and after in silico DSO.
In silico DSO suggests that three patients would require a substantial augmentation of LV contractility between 54 % and 80 % and an increase in PVA between 38 % and 79 % with respect to the baseline values to accommodate the increased afterload of the systemic circulation. On the contrary, the baseline functional state of the remaining three patients is predicted to be adequate to sustain cardiac output after the DSO.
This work demonstrates the vast variation of LV function among patients with ccTGA and emphasizes the importance of a biventricular approach to assess patients’ readiness for DSO. Model-derived predictions have the potential to provide additional insights into planning of complex surgical interventions.
期刊介绍:
Medical Image Analysis serves as a platform for sharing new research findings in the realm of medical and biological image analysis, with a focus on applications of computer vision, virtual reality, and robotics to biomedical imaging challenges. The journal prioritizes the publication of high-quality, original papers contributing to the fundamental science of processing, analyzing, and utilizing medical and biological images. It welcomes approaches utilizing biomedical image datasets across all spatial scales, from molecular/cellular imaging to tissue/organ imaging.