Relationship of Cardiac MRI-Derived Pulmonary Arterial Stiffness Markers and Invasive Hemodynamic

Relationship of Cardiac MRI-Derived Pulmonary Arterial Stiffness Markers and Invasive Hemodynamic | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Relationship of Cardiac MRI-Derived Pulmonary Arterial Stiffness Markers and Invasive Hemodynamic Ipek Buber, Paul Heerdt, Inderjit Singh, Joseph Phillip, Cihan Ilyas Sevgican, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7228327/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Pulmonary arterial stiffness (PAS) is a noninvasive imaging biomarker associated with disease severity in pulmonary hypertension (PH). This study aimed to evaluate PAS using cardiac magnetic resonance (CMR) imaging and investigate its relationship with hemodynamic parameters from right heart catheterization (RHC) across PH subgroups. Methods In this retrospective study, 44 patients with PH who underwent both RHC and CMR were classified into pre-capillary (precapPH), post-capillary (postcapPH), and combined pre- and post-capillary (combPH) PH groups based on guideline-defined criteria. PAS was assessed by CMR-derived pulse wave velocity (PWV) and relative area change (RAC) of the main pulmonary artery. RHC measurements included mPAP, PVR, and right ventricular pressures and mixed venous saturation. Results PWV was significantly higher in combPH (4.49 ± 1.32 m/s) compared to precapPH (3.40 ± 0.98 m/s, p = 0.04). RAC was significantly lower in combPH (0.18 ± 0.11) than in postcapPH (0.28 ± 0.09), p = X.XX) and precapPH (0.18 ± 0.07, p = 0.01). PWV correlated with mPAP ( r = 0.34, p = 0.022), RAP (r = 0.39, p = 0.008), and RVEDVi (r = 0.34, p = 0.022), while RAC showed a negative correlation with PVR ( r = − 0.36, p = 0.01). Distinct RV adaptation patterns were observed among subgroups, with combPH patients exhibiting the most impaired hemodynamics. Conclusion CMR-derived PAS indices correlate with invasive hemodynamic markers and differ among PH subtypes. PWV and RAC may serve as useful noninvasive markers for assessing pulmonary vascular burden and differentiating disease severity in PH. Larger prospective studies are needed to validate their clinical utility. Pulmonary Hypertension Pulmonary Arterial Stiffness Pulse Wave Velocity Phase-contrast Figures Figure 1 Figure 2 Figure 3 Introduction Pulmonary hypertension (PH) is a heterogeneous condition characterized by an increase in mean pulmonary artery pressure (mPAP > 20 mmHg). It is classified into three hemodynamic subgroups based on pulmonary arterial wedge pressure (PAWP) and pulmonary vascular resistance (PVR), which are measured via right heart catheterization (RHC). These subgroups are pre-capillary PH (precapPH), post-capillary PH (postcapPH), and combined pre- and post-capillary PH (combPH) [ 1 , 2 ]. Pulmonary arterial stiffness (PAS) has become an important marker for the early detection of PH and an indicator of disease severity[ 3 ]. Over the past two decades, studies have utilized a combination of invasive RHC and noninvasive cardiac magnetic resonance (CMR)-derived indices to assess PAS, offering valuable insights into its diagnostic and prognostic utility in both PH patients and controls[ 4 – 6 ]. Among the various CMR biomarkers for PAS evaluation, pulse wave velocity (PWV) and relative area change (RAC) of the main pulmonary artery (PA) are considered the most robust and reliable methods[ 7 ]. For instance, a study involving patients with idiopathic pulmonary arterial hypertension (PAH) and healthy subjects demonstrated that noninvasive RAC evaluation serves as a sensitive marker for early increases in PVR and predicts adverse outcomes[ 8 ]. In addition, Ghio et al. found that reduced pulmonary arterial compliance, which indicates increased right ventricular (RV) afterload and progressive RV dysfunction, remains lower in combPH patients compared to precapPH patients[ 9 ]. Despite these findings, there are limited data on the relationship between PAS metrics and RHC-derived hemodynamic indices, as well as the differences across hemodynamic subgroups, highlighting a need for further research. The aim of this study is to evaluate PAS using CMR imaging and to examine its relationship with hemodynamic parameters obtained from RHC, as well as the differences among PH subgroups. This will contribute towards the goal of increasing the role of CMR in risk management of these subjects, who must be followed carefully, but cannot received unlimited RHCs. Materials and Methods Patient Selection Inclusion criteria A total of 60 consecutive patients who underwent RHC at our institution (between 2019 and 2025) for suspected PH, and who had a recent cardiac MRI (performed within 1 week to 1 month after catheterization) were included in this retrospective study. PrecapPH consisted of patients with idiopathic PAH and connective tissue disease associated with PAH, while postcapPH consisted of patients with PH due to heart failure with preserved ejection fraction (HFpEF) and combPH consisted of patients in both cases. The classification of groups was based on current guideline definitions (precapPH was defined as mPAP > 20 mmHg, PVR > 2 (wood unit) WU and PAWP 20 mmHg, PVR 15 mmHg and combPH defines as mPAP > 20 mmHg, PVR > 2 WU and PAWP > 15 mmHg)[ 2 ]. Exclusion criteria Patients who had already received targeted therapy were excluded from the study (N = 6). Patients with insufficient CMR image quality that hindered accurate calculation of area and flow measurements were excluded (N = 16). To reduce bias from this exclusion, PA image quality was evaluated by two observers, who independently identified non-diagnostic PA area or flow curves, blinded to patient status. Any disagreements were resolved by discussion until a consensus was reached. Ultimately, data from 44 patients were analyzed. Right Heart Catheterization RHC was conducted with the patient in a supine position, using either a 6.0 or 7.5F Swan-Ganz catheter (Edwards Life Sciences, Irvine, CA, USA) inserted percutaneously into the internal jugular vein under fluoroscopic and ultrasound guidance. Right atrial (RA), RV, PA, and PAWP, along with oxygen saturations from the superior vena cava, RA, and PA, were measured. All pressures were recorded at the end of passive exhalation, and when significant respirophasic fluctuations were noted in the hemodynamic tracings, an electronic average was used. A zero reference was established at the mid-thoracic level. Cardiac output (CO) was measured using the thermodilution method. PVR was calculated as (mPAP – PAWP)/CO and expressed in WU. Stroke volume (SV) was determined by dividing by heart rate, and both CO and SV were indexed to body surface area to calculate cardiac index (CI) and SV index (SVi)[ 10 – 14 ] Cardiac MRI Measurement of volumes and functions All imaging was performed on a 1.5T Siemens scanner (Aera). Left ventricular and RV parameters including end-diastolic volume (EDV), end-systolic volume (ESV), SV, and ejection fraction (EF) were derived using balanced steady-state free precession (bSSFP) images obtained from contiguous short-axis slices spanning the base to the apex. A single reader assessed both LV and RV parameters using Circle Cardiovascular Imaging software (Circle Cardiovascular Imaging Inc., Calgary, Alberta, Canada) in line with CMR postprocessing guidelines[ 15 ]. Endocardial and epicardial contours were outlined at end-diastole (largest blood volume phase) and end-systole (smallest blood volume phase). The trabeculations and papillary muscles were included in the volumetric calculations. PA Flow, Area, and Pulse Wave Velocity Measurements PA area, flow, and PWV measurements were obtained using breath-held through-plane 2D phase-contrast (VENC = 150 cm/s), with typical scan parameters of TR/TE/flip angle = 4.6ms/2.4ms/20°, 192x192 matrix, FOV 360 mm, 2.3x2.3mm 2 in-plane resolution (prior to zero-filling), slice thickness 6mm, true temporal resolution 37ms, bandwidth 449 Hz/pixel. Images were acquired in a standard PA view; Fig. 1A shows the PA area (A) and flow (Q) measured over the cardiac cycle from a phase-contrast acquisition. Segment v3.2 R8836 software was used for the post-processing of the PA MRI data. The PA contours were traced semi-automatically, with manual adjustments made as needed for each phase. The maximum (Amax) and minimum (Amin) cross-sectional areas of the PA were measured in systolic and diastolic images, respectively (Fig. 1A). The through-plane flows in the PA throughout the cardiac cycle were measured in Segment, after 1st -order background phase correction. The RAC was derived as the ratio of the area change to the maximum area (RAC = (Amax − Amin)/Amax), with smaller changes indicating stiffer vessels. PWV was assessed as described by Cain et al. using the ratio of the slope of the flow vs. time curve (ΔQ/Δt) to the slope of the area vs. time curve (Δ Area/Δt) –the ΔQ/ΔA method [ 7 ]. These slopes were obtained in the early systolic phase of the area or flow-time curve (Fig. 1B, C). Statistical Analysis Continuous variables were expressed as mean ± standard deviation (SD) and range, while categorical variables were presented as counts and percentages. The normality of data distribution was assessed using the Shapiro–Wilk test. Comparisons between the three PH subgroups were performed using one-way analysis of variance (ANOVA) for normally distributed variables. For parameters showing significant overall differences, post hoc pairwise comparisons were conducted using Tukey’s test to identify intergroup differences. Correlations between CMR-derived stiffness indices PWV and RAC and hemodynamic and functional parameters were evaluated using Pearson’s correlation coefficient. A p -value of less than 0.05 was considered statistically significant. All analyses were performed using IBM SPSS Statistics, version 14. Results Table 1 showed that demographic and CMR findings of groups. The combPH group exhibited the highest PWV (4.49 ± 1.32 m/s) which was significantly greater than that of the precapPH group (3.40 ± 0.98 m/s, p = 0.04) (figure 2a). In contrast, RAC was significantly lower in the combPH group (0.18 ± 0.11mm) compared to the postcapPH group (0.28 ± 0.09) and precapPH group (0.18 ± 0.07, p = 0.010) (figure 2b). The postcapPH group also had the highest right ventricular ejection fraction (RVEF) (57.80 ± 8.16%, p = 0.007), and the lowest RVESV and RVESV index, measured at (67.70 ± 41.07 mL, p = 0.024) and (34.63 ± 17.02 mL/m², p = 0.012), respectively. Correlation analysis revealed that (table 2) PWV was positively correlated with mPAP (r = 0.34, p = 0.022) (figure 3a), right atrial pressure (RAP) (r = 0.39, p = 0.008), and right ventricular end-diastolic volume index (RVEDVi) (r = 0.34, p = 0.022). RAC was significantly negatively correlated with PVR (r = –0.36, p = 0.010) (figure 3b), and positively correlated with PA oxygen saturation (r = 0.30, p = 0.04). Table 3 shows RHC findings of groups. The combPH group demonstrated the most impaired hemodynamic profile. This group exhibited significantly higher RAP (16.42 ± 6.92 mmHg), right ventricular systolic pressure (RVSP) (78.92 ± 18.31 mmHg), right ventricular end-diastolic pressure (RVEDP) (20.58 ± 6.42 mmHg) and mPAP (51.92 ± 11.08 mmHg) compared to both the precap and postcapPH groups ( p < 0.001 for all). More favorable hemodynamic profiles were observed in the postcapPH group. This subgroup demonstrated the highest oxygen saturations , including superior vena cava (67.00 ± 4.18%) , right atrium (69.90 ± 3.73%) , and PA (69.30 ± 3.30%) saturations, all significantly greater than those in the combPH group ( p ≤ 0.003). The lowest PVR was also noted in the postcapPH group (1.80 ± 1.21 WU), compared to precapPH (6.56 ± 3.50 WU) and combPH (8.28 ± 4.69 WU) ( p < 0.001) as expected. Additionally, CI (by RHC) was significantly different among groups, with the postcapPH group showing the highest CI (2.95 ± 0.85 L/min/m²) and the combPH group the lowest (2.10 ± 0.89 L/min/m², p = 0.038). Similarly, SVI was significantly lower in the combPH group (31.64 ± 16.87 mL/m²) compared to both precapPH (35.80 ± 11.04 mL/m²) and postcapPH (48.57 ± 11.17 mL/m², p = 0.011). The PAWP was significantly elevated in the postcapPH (22.00 ± 7.57 mmHg) and combPH (21.08 ± 4.93 mmHg) groups, compared to precapPH (9.45 ± 3.52 mmHg, p < 0.001), consistent with the defining hemodynamic criteria for post-capillary involvement. Discussion This study explored the associations between PAS, RV functional metrics assessed by CMR imaging, and hemodynamic parameters obtained from RHC in patients with PH. Our findings demonstrated that PWV was significantly and positively correlated with mPAP, whereas RAC showed a significant negative correlation with PVR. Additionally, PWV was significantly higher in patients with combPH compared to those with precapPH. Importantly, RAC was significantly lower in the combPH group than in the other subgroup. Prior studies have not directly compared CMR-derived PAS parameters across different hemodynamic subgroups of PH. Some existing research using related indices—such as pulmonary arterial compliance—found no significant differences between patients with PAH and chronic thromboembolic PH, both of which exhibit precapillary features[ 16 ]. Another study involving combPH patients reported that pulmonary pulse transit time, another potential marker of vascular stiffness, was significantly worse in the combPH group and may be useful for identifying this subgroup [ 17 ]. Consistent with these findings, our study demonstrated that combPH patients exhibited significantly higher PWV and lower RAC, indicating greater vascular stiffness compared to the other subgroups. Notably, PWV showed a moderate positive correlation with mPAP, aligning with previous studies that linked PWV to early pulmonary vascular disease and elevated pressures, particularly in conditions such as COPD [ 18 ].Given its reproducibility with CMR and its sensitivity to vascular changes, PWV and RAC may serve not only as a marker to differentiate PH phenotypes but also as a noninvasive indicator of disease severity and vascular remodeling, especially in patients with combPH. RAC is one of the most widely reported and easily calculated CMR-derived markers for assessing PAS [ 19 ]. It provides a simplified measure of PA stiffness that is largely independent of pulse pressure, although it is not considered the gold standard compared to PWV. Previous studies demonstrated a relationship between RAC and PVR, which was found to be predictive of adverse outcomes [ 6 , 8 ]. In line with previous studies, our analysis found a significant correlation between RAC and PVR, and a trend toward association with mPAP (p = 0.052). The postcapPH group, which had the lowest PVR among all subgroups, also exhibited the highest RAC values. These findings may suggest that RAC could serve as a useful non-invasive parameter related to pulmonary vascular load. Although increased PAS is known to contribute to RV dysfunction by increasing afterload [ 5 ], our study did not demonstrate a direct correlation between PAS indices and RVEF, although RVEDVi did show a significant association. This finding suggests that PWV may serve as an independent predictor of disease severity in PH, rather than merely reflecting RV functional impairment. The lack of a direct relationship between PAS and RVEF likely reflects the multifactorial nature of RV adaptation in PH, which is influenced by vascular stiffness, intrinsic myocardial contractility, RV– PA coupling, and elevated left-sided filling pressures[ 19 ]. In our cohort, the combPH group—characterized by the most impaired PAS and the highest hemodynamic burden, including elevated PVR, RAP, and RVEDP—also exhibited the most pronounced RV dysfunction. In contrast, the postcapPH group, which demonstrated lower PVR and more compliant pulmonary vasculature (i.e., lower PWV), showed preserved RVEF and smaller RV volumes, suggesting more favorable RV adaptation in the context of isolated postcapillary pressure elevation[ 20 ]. These findings support the concept that PAS is a unique and independent predictor of PH severity. While not directly correlated with RVEF, increased PAS likely contributes to the overall afterload burden that drives maladaptive RV remodeling over time [ 21 ]. Limitations This study has several limitations. First, the relatively small sample size within PH subgroups may limit the generalizability of our findings. Larger, multicenter studies including a broader spectrum of PH phenotypes are needed to validate and expand upon these results. Second, the lack of long-term follow-up data precludes assessment of the prognostic value of CMR-derived PAS parameters. Finally, MR imaging and right heart catheterization were not performed on the same day in all patients, which may have introduced temporal variability in hemodynamic status. The method for measuring PWV by CMR requires accurate evaluation of PA flow and area. The PA area measurement is challenging due to cardiac motion of the PA and lack of conspicuity of the PA in very early systole. Conclusion In this study, the associations between CMR-derived markers of PAS and invasive hemodynamic parameters in patients with PH were evaluated. PWV was found to be positively correlated with mPAP and was the highest in the combPH group. RAC demonstrated a significant inverse correlation with PVR and was lowest in the same subgroup. These findings suggest that non-invasive CMR-based stiffness indices may be useful in reflecting pulmonary vascular burden and differentiating disease severity among PH phenotypes. Further validation through larger, prospective studies is warranted to establish their clinical and prognostic value. Abbreviations PH Pulmonary Hypertension PAS Pulmonary Arterial Stiffness CMR Cardiac Magnetic Resonance RHC Right Heart Catheterization precapPH Pre-capillary Pulmonary Hypertension postcapPH Post-capillary Pulmonary Hypertension combPH Combined Pre- and Post-capillary Pulmonary Hypertension PWV Pulse Wave Velocity RAC Relative Area Change mPAP Mean Pulmonary Artery Pressure PVR Pulmonary Vascular Resistance RA Right Atrium RV Right Ventricle RVEDVi Right Ventricular End-Diastolic Volume Index RVEDP Right Ventricular End-Diastolic Pressure RVSP Right Ventricular Systolic Pressure RVEF Right Ventricular Ejection Fraction LV Left Ventricle PA Pulmonary Artery PAWP Pulmonary Artery Wedge Pressure CO Cardiac Output SV Stroke Volume CI Cardiac Index SVi Stroke Volume Index EDV End-Diastolic Volume ESV End-Systolic Volume bSSFP Balanced Steady-State Free Precession VENC Velocity Encoding (in phase contrast MRI) TR/TE Repetition Time / Echo Time FOV Field of View WU Wood Units EF Ejection Fraction Declarations Acknowledgments. Ipek Buber was supported by TUBITAK 2219 at Yale University Disclosures (none directly related) Edwards Lifesciences – consulting Cardiage LLC – consulting Emka Medical – equity interest Authors’ contributions IB and DCP designed the study and wrote the main manuscript. CIS performed statistical analysis of the data. JP, IS, PH collected data and interpretation the study. JX and JL studied with deep learning program. All authors critically revised and approved the final version of the manuscript. All authors read and approved of the final manuscript. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Funding No funding Ethics approval and consent to participate. All participants provided written consent before entering the study. The study was approved by Yale University Institutional Review Board according to the Declaration of Helsinki, as exempt chart review study; IRB number for data collection is 2000024783. Consent for publication Not applicable. Competing interests All authors declare that they have no competing interests. Conflict of interest The authors declare no conflict of interest. References Kovacs G, Bartolome S, Denton CP, Gatzoulis MA, Gu S, Khanna D, et al. Definition, classification and diagnosis of pulmonary hypertension. Eur Respir J. 2024 Oct 31;64(4):2401324. doi: 10.1183/13993003.01324-2024. PMID: 39209475; PMCID: PMC11533989. Humbert M, Kovacs G, Hoeper MM, Badagliacca R, Berger RMF, Brida M,et al., 2022 ESC/ERS Guidelines for the diagnosis and treatment of pulmonary hypertension. Eur Heart J, 2022. 43 (38): p. 3618-3731. 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Ibe T, Wada H, Sakakura K, Ugata Y, Maki H, Yamamoto K,et al., Combined pre- and post-capillary pulmonary hypertension: The clinical implications for patients with heart failure. PLoS One, 2021. 16 (3): p. e0247987. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7228327","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":504509828,"identity":"1cc7fa93-3f6b-4552-a16a-e8151201af7f","order_by":0,"name":"Ipek Buber","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIiWNgGAWjYBACNgYGZgbGBoYEIH2AgaEAJJZAtBY2IDYgQgsDQguPAXFa+KSbDxsw7jicxy995pvEDwMbBn72HAP8DpM5lpzAeOZwsWRf7jbJHoM0BsmeNwS0SOQYH2BsO5y44QzvNgkeg8MMBjcI2SKR/xmsZf8ZnmeSfwz+M9gT1pLDnAC2hYeHTZrH4ACDgQRhvxgbJJ5JL5Y4w2ZsLWOQzCNx5lkBXi3ys5sfS3zcYZ3H38P88OabCjs5/vbkDXi1MEgwwCOCBcTmwa8cpgUKmD8QVj4KRsEoGAUjEQAAARtBnJDlG6sAAAAASUVORK5CYII=","orcid":"","institution":"Yale University","correspondingAuthor":true,"prefix":"","firstName":"Ipek","middleName":"","lastName":"Buber","suffix":""},{"id":504509829,"identity":"bd877451-9db8-4b12-992e-c3f943050e77","order_by":1,"name":"Paul Heerdt","email":"","orcid":"","institution":"Yale University","correspondingAuthor":false,"prefix":"","firstName":"Paul","middleName":"","lastName":"Heerdt","suffix":""},{"id":504509830,"identity":"0706d241-0dac-434c-84a5-7168952d21b8","order_by":2,"name":"Inderjit Singh","email":"","orcid":"","institution":"Yale University","correspondingAuthor":false,"prefix":"","firstName":"Inderjit","middleName":"","lastName":"Singh","suffix":""},{"id":504509831,"identity":"efa74b1f-9dea-455e-a308-20e35ed304fa","order_by":3,"name":"Joseph Phillip","email":"","orcid":"","institution":"Yale University","correspondingAuthor":false,"prefix":"","firstName":"Joseph","middleName":"","lastName":"Phillip","suffix":""},{"id":504509832,"identity":"87c91c79-4b25-49c4-b3a1-a8eef27f7b2a","order_by":4,"name":"Cihan Ilyas Sevgican","email":"","orcid":"","institution":"private health hospital","correspondingAuthor":false,"prefix":"","firstName":"Cihan","middleName":"Ilyas","lastName":"Sevgican","suffix":""},{"id":504509833,"identity":"cca1d7e5-b3ec-4283-b8a9-0f017de69cdb","order_by":5,"name":"Jérôme Lamy","email":"","orcid":"","institution":"Université Paris Cité","correspondingAuthor":false,"prefix":"","firstName":"Jérôme","middleName":"","lastName":"Lamy","suffix":""},{"id":504509834,"identity":"ffe5c0c3-4e1f-4151-9325-46b8070da256","order_by":6,"name":"Jie Xiang","email":"","orcid":"","institution":"Yale University","correspondingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Xiang","suffix":""},{"id":504509835,"identity":"538634dd-6b29-4735-b496-8ccc02bf85dd","order_by":7,"name":"Dana C. Peters","email":"","orcid":"","institution":"Yale University","correspondingAuthor":false,"prefix":"","firstName":"Dana","middleName":"C.","lastName":"Peters","suffix":""}],"badges":[],"createdAt":"2025-07-27 21:23:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7228327/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7228327/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89979462,"identity":"a4e57584-eb7a-4c39-85d9-ab22a7d2806f","added_by":"auto","created_at":"2025-08-27 06:18:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":343255,"visible":true,"origin":"","legend":"\u003cp\u003eA: Examples of PA phase-contrast images and measurements. A: PA area (A) and flow (Q) were measured over the cardiac cycle using magnitude and phase images respectively.\u003c/p\u003e\n\u003cp\u003eFigure 1B: PA flow and area changes, measured during the cardiac cycle. Plot of flow vs. Area during early systole (see region of indicated by red dots at the slope) yields a slope which measures PWV in this subject without PH was measured to be 1.4 m/s in a subject without PH.\u003c/p\u003e\n\u003cp\u003eFigure 1C: PWV in a 65-year-old female with idiopathic pulmonary arterial hypertension, here measured to be 6.3 m/s.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7228327/v1/072a603bdaf6b4e45efb69a0.png"},{"id":89979459,"identity":"779c2bed-dfc9-4d2a-82df-0c071a02711b","added_by":"auto","created_at":"2025-08-27 06:18:27","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":71357,"visible":true,"origin":"","legend":"\u003cp\u003eDifferences of Pulse Wave Velocity (a) and Relative Area Change (b)across PH subgroups\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7228327/v1/d47e94e743227bb75c55055c.jpg"},{"id":89979460,"identity":"5436431f-3475-4c45-a3d4-c71b06260398","added_by":"auto","created_at":"2025-08-27 06:18:27","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":59769,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation Plot of Pulse Wave Velocity and mean Pulmonary Arterial Pressure (a), Relative Area Change and Pulmonary Vascular Resistance (b).\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7228327/v1/1795ffa68de44ca84656a3e5.jpg"},{"id":90171012,"identity":"548fefde-122d-4cb5-a0b4-612d66ce0ad3","added_by":"auto","created_at":"2025-08-29 11:17:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1256741,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7228327/v1/5fec0768-b890-4806-9eaa-c8ef96f7e39a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Relationship of Cardiac MRI-Derived Pulmonary Arterial Stiffness Markers and Invasive Hemodynamic","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePulmonary hypertension (PH) is a heterogeneous condition characterized by an increase in mean pulmonary artery pressure (mPAP\u0026thinsp;\u0026gt;\u0026thinsp;20 mmHg). It is classified into three hemodynamic subgroups based on pulmonary arterial wedge pressure (PAWP) and pulmonary vascular resistance (PVR), which are measured via right heart catheterization (RHC). These subgroups are pre-capillary PH (precapPH), post-capillary PH (postcapPH), and combined pre- and post-capillary PH (combPH) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePulmonary arterial stiffness (PAS) has become an important marker for the early detection of PH and an indicator of disease severity[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Over the past two decades, studies have utilized a combination of invasive RHC and noninvasive cardiac magnetic resonance (CMR)-derived indices to assess PAS, offering valuable insights into its diagnostic and prognostic utility in both PH patients and controls[\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Among the various CMR biomarkers for PAS evaluation, pulse wave velocity (PWV) and relative area change (RAC) of the main pulmonary artery (PA) are considered the most robust and reliable methods[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFor instance, a study involving patients with idiopathic pulmonary arterial hypertension (PAH) and healthy subjects demonstrated that noninvasive RAC evaluation serves as a sensitive marker for early increases in PVR and predicts adverse outcomes[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In addition, Ghio et al. found that reduced pulmonary arterial compliance, which indicates increased right ventricular (RV) afterload and progressive RV dysfunction, remains lower in combPH patients compared to precapPH patients[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Despite these findings, there are limited data on the relationship between PAS metrics and RHC-derived hemodynamic indices, as well as the differences across hemodynamic subgroups, highlighting a need for further research.\u003c/p\u003e\u003cp\u003eThe aim of this study is to evaluate PAS using CMR imaging and to examine its relationship with hemodynamic parameters obtained from RHC, as well as the differences among PH subgroups. This will contribute towards the goal of increasing the role of CMR in risk management of these subjects, who must be followed carefully, but cannot received unlimited RHCs.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cb\u003ePatient Selection\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eInclusion criteria\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA total of 60 consecutive patients who underwent RHC at our institution (between 2019 and 2025) for suspected PH, and who had a recent cardiac MRI (performed within 1 week to 1 month after catheterization) were included in this retrospective study. PrecapPH consisted of patients with idiopathic PAH and connective tissue disease associated with PAH, while postcapPH consisted of patients with PH due to heart failure with preserved ejection fraction (HFpEF) and combPH consisted of patients in both cases. The classification of groups was based on current guideline definitions (precapPH was defined as mPAP\u0026thinsp;\u0026gt;\u0026thinsp;20 mmHg, PVR\u0026thinsp;\u0026gt;\u0026thinsp;2 (wood unit) WU and PAWP\u0026thinsp;\u0026lt;\u0026thinsp;15 mmHg and postcapPH was defined as mPAP\u0026thinsp;\u0026gt;\u0026thinsp;20 mmHg, PVR\u0026thinsp;\u0026lt;\u0026thinsp;2 WU and PAWP\u0026thinsp;\u0026gt;\u0026thinsp;15 mmHg and combPH defines as mPAP\u0026thinsp;\u0026gt;\u0026thinsp;20 mmHg, PVR\u0026thinsp;\u0026gt;\u0026thinsp;2 WU and PAWP\u0026thinsp;\u0026gt;\u0026thinsp;15 mmHg)[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eExclusion criteria\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePatients who had already received targeted therapy were excluded from the study (N\u0026thinsp;=\u0026thinsp;6). Patients with insufficient CMR image quality that hindered accurate calculation of area and flow measurements were excluded (N\u0026thinsp;=\u0026thinsp;16). To reduce bias from this exclusion, PA image quality was evaluated by two observers, who independently identified non-diagnostic PA area or flow curves, blinded to patient status. Any disagreements were resolved by discussion until a consensus was reached. Ultimately, data from 44 patients were analyzed.\u003c/p\u003e\u003cp\u003e\u003cb\u003eRight Heart Catheterization\u003c/b\u003e\u003c/p\u003e\u003cp\u003eRHC was conducted with the patient in a supine position, using either a 6.0 or 7.5F Swan-Ganz catheter (Edwards Life Sciences, Irvine, CA, USA) inserted percutaneously into the internal jugular vein under fluoroscopic and ultrasound guidance. Right atrial (RA), RV, PA, and PAWP, along with oxygen saturations from the superior vena cava, RA, and PA, were measured. All pressures were recorded at the end of passive exhalation, and when significant respirophasic fluctuations were noted in the hemodynamic tracings, an electronic average was used. A zero reference was established at the mid-thoracic level. Cardiac output (CO) was measured using the thermodilution method. PVR was calculated as (mPAP \u0026ndash; PAWP)/CO and expressed in WU. Stroke volume (SV) was determined by dividing by heart rate, and both CO and SV were indexed to body surface area to calculate cardiac index (CI) and SV index (SVi)[\u003cspan additionalcitationids=\"CR11 CR12 CR13\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/p\u003e\u003cp\u003e\u003cb\u003eCardiac MRI\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eMeasurement of volumes and functions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAll imaging was performed on a 1.5T Siemens scanner (Aera). Left ventricular and RV parameters including end-diastolic volume (EDV), end-systolic volume (ESV), SV, and ejection fraction (EF) were derived using balanced steady-state free precession (bSSFP) images obtained from contiguous short-axis slices spanning the base to the apex.\u003c/p\u003e\u003cp\u003eA single reader assessed both LV and RV parameters using Circle Cardiovascular Imaging software (Circle Cardiovascular Imaging Inc., Calgary, Alberta, Canada) in line with CMR postprocessing guidelines[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Endocardial and epicardial contours were outlined at end-diastole (largest blood volume phase) and end-systole (smallest blood volume phase). The trabeculations and papillary muscles were included in the volumetric calculations.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePA Flow, Area, and Pulse Wave Velocity Measurements\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePA area, flow, and PWV measurements were obtained using breath-held through-plane 2D phase-contrast (VENC\u0026thinsp;=\u0026thinsp;150 cm/s), with typical scan parameters of TR/TE/flip angle\u0026thinsp;=\u0026thinsp;4.6ms/2.4ms/20\u0026deg;, 192x192 matrix, FOV 360 mm, 2.3x2.3mm\u003csup\u003e2\u003c/sup\u003e in-plane resolution (prior to zero-filling), slice thickness 6mm, true temporal resolution 37ms, bandwidth 449 Hz/pixel. Images were acquired in a standard PA view; Fig.\u0026nbsp;1A shows the PA area (A) and flow (Q) measured over the cardiac cycle from a phase-contrast acquisition.\u003c/p\u003e\u003cp\u003eSegment v3.2 R8836 software was used for the post-processing of the PA MRI data. The PA contours were traced semi-automatically, with manual adjustments made as needed for each phase. The maximum (Amax) and minimum (Amin) cross-sectional areas of the PA were measured in systolic and diastolic images, respectively (Fig.\u0026nbsp;1A). The through-plane flows in the PA throughout the cardiac cycle were measured in Segment, after 1st -order background phase correction.\u003c/p\u003e\u003cp\u003eThe RAC was derived as the ratio of the area change to the maximum area (RAC = (Amax\u0026thinsp;\u0026minus;\u0026thinsp;Amin)/Amax), with smaller changes indicating stiffer vessels.\u003c/p\u003e\u003cp\u003ePWV was assessed as described by Cain et al. using the ratio of the slope of the flow vs. time curve (ΔQ/Δt) to the slope of the area vs. time curve (Δ Area/Δt) \u0026ndash;the ΔQ/ΔA method [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These slopes were obtained in the early systolic phase of the area or flow-time curve (Fig.\u0026nbsp;1B, C).\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eContinuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) and range, while categorical variables were presented as counts and percentages. The normality of data distribution was assessed using the Shapiro\u0026ndash;Wilk test. Comparisons between the three PH subgroups were performed using one-way analysis of variance (ANOVA) for normally distributed variables. For parameters showing significant overall differences, post hoc pairwise comparisons were conducted using Tukey\u0026rsquo;s test to identify intergroup differences.\u003c/p\u003e\u003cp\u003eCorrelations between CMR-derived stiffness indices PWV and RAC and hemodynamic and functional parameters were evaluated using Pearson\u0026rsquo;s correlation coefficient. A \u003cem\u003ep\u003c/em\u003e-value of less than 0.05 was considered statistically significant. All analyses were performed using IBM SPSS Statistics, version 14.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eTable 1 showed that demographic and CMR findings of groups. The combPH group exhibited the highest PWV (4.49 \u0026plusmn; 1.32 m/s) which was significantly greater than that of the precapPH group (3.40 \u0026plusmn; 0.98 m/s, \u003cem\u003ep\u003c/em\u003e = 0.04) (figure 2a). In contrast, RAC was significantly lower in the combPH group (0.18 \u0026plusmn; 0.11mm) compared to the postcapPH group (0.28 \u0026plusmn; 0.09) and precapPH group (0.18 \u0026plusmn; 0.07, \u003cem\u003ep\u003c/em\u003e = 0.010) (figure 2b). The postcapPH group also had the highest right ventricular ejection fraction (RVEF) (57.80 \u0026plusmn; 8.16%, p\u0026nbsp;= 0.007), and the lowest RVESV and RVESV index, measured at (67.70 \u0026plusmn; 41.07 mL, \u003cem\u003ep\u003c/em\u003e = 0.024) and (34.63 \u0026plusmn; 17.02 mL/m\u0026sup2;, \u003cem\u003ep\u003c/em\u003e = 0.012), respectively.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCorrelation analysis revealed that (table 2) PWV was positively correlated with mPAP (r = 0.34, \u003cem\u003ep\u003c/em\u003e = 0.022) (figure 3a), right atrial pressure (RAP) (r = 0.39, \u003cem\u003ep\u003c/em\u003e = 0.008), and right ventricular end-diastolic volume index (RVEDVi) (r = 0.34, \u003cem\u003ep\u003c/em\u003e = 0.022). RAC was significantly negatively correlated with PVR (r = \u0026ndash;0.36, \u003cem\u003ep\u003c/em\u003e= 0.010) (figure 3b), and positively correlated with PA oxygen saturation (r = 0.30, \u003cem\u003ep\u003c/em\u003e = 0.04).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3 shows RHC findings of groups. The \u003cstrong\u003ecombPH\u0026nbsp;\u003c/strong\u003egroup demonstrated the most impaired hemodynamic profile. This group exhibited significantly higher \u003cstrong\u003eRAP\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e(16.42 \u0026plusmn; 6.92 mmHg),\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eright ventricular systolic pressure (RVSP)\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e(78.92 \u0026plusmn; 18.31 mmHg),\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eright ventricular end-diastolic pressure (RVEDP)\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e(20.58 \u0026plusmn; 6.42 mmHg) and mPAP (51.92 \u0026plusmn; 11.08 mmHg) compared to both the \u003cstrong\u003eprecap\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eand \u003cstrong\u003epostcapPH\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003egroups (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001 for all).\u003c/p\u003e\n\u003cp\u003eMore favorable hemodynamic profiles were observed in the \u003cstrong\u003epostcapPH\u0026nbsp;\u003c/strong\u003egroup. This subgroup demonstrated the\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ehighest oxygen saturations\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003eincluding \u003cstrong\u003esuperior vena cava (67.00 \u0026plusmn; 4.18%)\u003c/strong\u003e\u003cstrong\u003e,\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eright atrium (69.90 \u0026plusmn; 3.73%)\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003eand\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ePA (69.30 \u0026plusmn; 3.30%)\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003esaturations, all significantly greater than those in the combPH group (\u003cem\u003ep\u003c/em\u003e \u0026le; 0.003). The \u003cstrong\u003elowest PVR\u003c/strong\u003e was also noted in the postcapPH group (1.80 \u0026plusmn; 1.21 WU), compared to precapPH (6.56 \u0026plusmn; 3.50 WU) and combPH (8.28 \u0026plusmn; 4.69 WU) (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001) as expected.\u003c/p\u003e\n\u003cp\u003eAdditionally, CI (by RHC) was significantly different among groups, with the postcapPH group showing the highest CI (2.95 \u0026plusmn; 0.85 L/min/m\u0026sup2;) and the combPH group the lowest (2.10 \u0026plusmn; 0.89 L/min/m\u0026sup2;, \u003cem\u003ep\u003c/em\u003e = 0.038). Similarly, \u003cstrong\u003eSVI\u003c/strong\u003e was significantly \u003cstrong\u003elower in the combPH group\u003c/strong\u003e (31.64 \u0026plusmn; 16.87 mL/m\u0026sup2;) compared to both precapPH (35.80 \u0026plusmn; 11.04 mL/m\u0026sup2;) and postcapPH (48.57 \u0026plusmn; 11.17 mL/m\u0026sup2;, \u003cem\u003ep\u003c/em\u003e = 0.011). The PAWP\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ewas significantly elevated in the postcapPH (22.00 \u0026plusmn; 7.57 mmHg) and combPH (21.08 \u0026plusmn; 4.93 mmHg) groups, compared to precapPH (9.45 \u0026plusmn; 3.52 mmHg, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), consistent with the defining hemodynamic criteria for post-capillary involvement.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e This study explored the associations between PAS, RV functional metrics assessed by CMR imaging, and hemodynamic parameters obtained from RHC in patients with PH. Our findings demonstrated that PWV was significantly and positively correlated with mPAP, whereas RAC showed a significant negative correlation with PVR. Additionally, PWV was significantly higher in patients with combPH compared to those with precapPH. Importantly, RAC was significantly lower in the combPH group than in the other subgroup.\u003c/p\u003e\u003cp\u003ePrior studies have not directly compared CMR-derived PAS parameters across different hemodynamic subgroups of PH. Some existing research using related indices\u0026mdash;such as pulmonary arterial compliance\u0026mdash;found no significant differences between patients with PAH and chronic thromboembolic PH, both of which exhibit precapillary features[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Another study involving combPH patients reported that pulmonary pulse transit time, another potential marker of vascular stiffness, was significantly worse in the combPH group and may be useful for identifying this subgroup [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Consistent with these findings, our study demonstrated that combPH patients exhibited significantly higher PWV and lower RAC, indicating greater vascular stiffness compared to the other subgroups. Notably, PWV showed a moderate positive correlation with mPAP, aligning with previous studies that linked PWV to early pulmonary vascular disease and elevated pressures, particularly in conditions such as COPD [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].Given its reproducibility with CMR and its sensitivity to vascular changes, PWV and RAC may serve not only as a marker to differentiate PH phenotypes but also as a noninvasive indicator of disease severity and vascular remodeling, especially in patients with combPH.\u003c/p\u003e\u003cp\u003eRAC is one of the most widely reported and easily calculated CMR-derived markers for assessing PAS [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. It provides a simplified measure of PA stiffness that is largely independent of pulse pressure, although it is not considered the gold standard compared to PWV. Previous studies demonstrated a relationship between RAC and PVR, which was found to be predictive of adverse outcomes [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In line with previous studies, our analysis found a significant correlation between RAC and PVR, and a trend toward association with mPAP (p\u0026thinsp;=\u0026thinsp;0.052). The postcapPH group, which had the lowest PVR among all subgroups, also exhibited the highest RAC values. These findings may suggest that RAC could serve as a useful non-invasive parameter related to pulmonary vascular load.\u003c/p\u003e\u003cp\u003eAlthough increased PAS is known to contribute to RV dysfunction by increasing afterload [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], our study did not demonstrate a direct correlation between PAS indices and RVEF, although RVEDVi did show a significant association. This finding suggests that PWV may serve as an independent predictor of disease severity in PH, rather than merely reflecting RV functional impairment.\u003c/p\u003e\u003cp\u003eThe lack of a direct relationship between PAS and RVEF likely reflects the multifactorial nature of RV adaptation in PH, which is influenced by vascular stiffness, intrinsic myocardial contractility, RV\u0026ndash; PA coupling, and elevated left-sided filling pressures[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In our cohort, the combPH group\u0026mdash;characterized by the most impaired PAS and the highest hemodynamic burden, including elevated PVR, RAP, and RVEDP\u0026mdash;also exhibited the most pronounced RV dysfunction. In contrast, the postcapPH group, which demonstrated lower PVR and more compliant pulmonary vasculature (i.e., lower PWV), showed preserved RVEF and smaller RV volumes, suggesting more favorable RV adaptation in the context of isolated postcapillary pressure elevation[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThese findings support the concept that PAS is a unique and independent predictor of PH severity. While not directly correlated with RVEF, increased PAS likely contributes to the overall afterload burden that drives maladaptive RV remodeling over time [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eLimitations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study has several limitations. First, the relatively small sample size within PH subgroups may limit the generalizability of our findings. Larger, multicenter studies including a broader spectrum of PH phenotypes are needed to validate and expand upon these results. Second, the lack of long-term follow-up data precludes assessment of the prognostic value of CMR-derived PAS parameters. Finally, MR imaging and right heart catheterization were not performed on the same day in all patients, which may have introduced temporal variability in hemodynamic status. The method for measuring PWV by CMR requires accurate evaluation of PA flow and area. The PA area measurement is challenging due to cardiac motion of the PA and lack of conspicuity of the PA in very early systole.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this study, the associations between CMR-derived markers of PAS and invasive hemodynamic parameters in patients with PH were evaluated. PWV was found to be positively correlated with mPAP and was the highest in the combPH group. RAC demonstrated a significant inverse correlation with PVR and was lowest in the same subgroup. These findings suggest that non-invasive CMR-based stiffness indices may be useful in reflecting pulmonary vascular burden and differentiating disease severity among PH phenotypes. Further validation through larger, prospective studies is warranted to establish their clinical and prognostic value.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePulmonary Hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePAS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePulmonary Arterial Stiffness\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCMR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCardiac Magnetic Resonance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eRHC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRight Heart Catheterization\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eprecapPH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePre-capillary Pulmonary Hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003epostcapPH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePost-capillary Pulmonary Hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ecombPH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCombined Pre- and Post-capillary Pulmonary Hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePWV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePulse Wave Velocity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eRAC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRelative Area Change\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003emPAP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean Pulmonary Artery Pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePVR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePulmonary Vascular Resistance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eRA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRight Atrium\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eRV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRight Ventricle\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eRVEDVi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRight Ventricular End-Diastolic Volume Index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eRVEDP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRight Ventricular End-Diastolic Pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eRVSP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRight Ventricular Systolic Pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eRVEF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRight Ventricular Ejection Fraction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eLV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLeft Ventricle\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePulmonary Artery\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePAWP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePulmonary Artery Wedge Pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCO\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCardiac Output\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eStroke Volume\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCardiac Index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSVi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eStroke Volume Index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eEDV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEnd-Diastolic Volume\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eESV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEnd-Systolic Volume\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ebSSFP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eBalanced Steady-State Free Precession\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVENC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eVelocity Encoding (in phase contrast MRI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTR/TE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRepetition Time / Echo Time\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eFOV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eField of View\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eWU\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eWood Units\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eEF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEjection Fraction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIpek Buber was supported by TUBITAK 2219 at Yale University\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosures (none directly related)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEdwards Lifesciences – consulting\u003c/p\u003e\n\u003cp\u003eCardiage LLC – consulting\u003c/p\u003e\n\u003cp\u003eEmka Medical – equity interest\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIB and DCP designed the study and wrote the main manuscript. CIS performed statistical analysis of the data. JP, IS, PH collected data and interpretation the study. JX and JL studied with deep learning program. All authors critically revised and approved the final version of the manuscript. All authors read and approved of the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants provided written consent before entering the study. The study was approved by Yale University Institutional Review Board according to the Declaration of Helsinki, as exempt chart review study; IRB number for data collection is 2000024783.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKovacs G, Bartolome S, Denton CP, Gatzoulis MA, Gu S, Khanna D, et al. Definition, classification and diagnosis of pulmonary hypertension. 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J Appl Physiol (1985), 2021. \u003cstrong\u003e131\u003c/strong\u003e(1): p. 424-433.\u003c/li\u003e\n\u003cli\u003eJoseph P, Savarimuthu S, Zhao J, Yan X, Oakland HT, Cullinan M, et al., Noninvasive determinants of pulmonary hypertension in interstitial lung disease. Pulm Circ, 2023. \u003cstrong\u003e13\u003c/strong\u003e(1): p. e12197.\u003c/li\u003e\n\u003cli\u003eSchulz-Menger J, Bluemke DA, Bremerich J, Flamm SD, Fogel MA, Friedrich MG, Kim RJ, et al., Standardized image interpretation and post-processing in cardiovascular magnetic resonance - 2020 update : Society for Cardiovascular Magnetic Resonance (SCMR): Board of Trustees Task Force on Standardized Post-Processing. J Cardiovasc Magn Reson, 2020. \u003cstrong\u003e22\u003c/strong\u003e(1): p. 19.\u003c/li\u003e\n\u003cli\u003eMcCormick A, Krishnan A, Badesch D, Benza RL, Bull TM, De Marco T,et al., Pulmonary artery compliance in different forms of pulmonary hypertension. Heart, 2023. \u003cstrong\u003e109\u003c/strong\u003e(14): p. 1098-1105.\u003c/li\u003e\n\u003cli\u003eGong C, Guo X, Wan K, Chen C, Chen X, Guo J, et al., Corrected MRI Pulmonary Transit Time for Identification of Combined Precapillary and Postcapillary Pulmonary Hypertension in Patients With Left Heart Disease. J Magn Reson Imaging, 2023. \u003cstrong\u003e57\u003c/strong\u003e(5): p. 1518-1528.\u003c/li\u003e\n\u003cli\u003eAgoston-Coldea L, Lupu S, Mocan T. Pulmonary Artery Stiffness by Cardiac Magnetic Resonance Imaging Predicts Major Adverse Cardiovascular Events in patients with Chronic Obstructive Pulmonary Disease. Sci Rep, 2018. \u003cstrong\u003e8\u003c/strong\u003e(1): p. 14447.\u003c/li\u003e\n\u003cli\u003eBrittain EL, Thenappan T, Huston JH, Agrawal V, Lai YC, Dixon D, et al., Elucidating the Clinical Implications and Pathophysiology of Pulmonary Hypertension in Heart Failure With Preserved Ejection Fraction: A Call to Action: A Science Advisory From the American Heart Association. Circulation, 2022. \u003cstrong\u003e146\u003c/strong\u003e(7): p. e73-e88.\u003c/li\u003e\n\u003cli\u003evan Wezenbeek J, Kianzad A, van de Bovenkamp A, Wessels J, Mouratoglou SA, Braams NJ, et al., Right Ventricular and Right Atrial Function Are Less Compromised in Pulmonary Hypertension Secondary to Heart Failure With Preserved Ejection Fraction: A Comparison With Pulmonary Arterial Hypertension With Similar Pressure Overload. Circ Heart Fail, 2022. \u003cstrong\u003e15\u003c/strong\u003e(2): p. e008726.\u003c/li\u003e\n\u003cli\u003eIbe T, Wada H, Sakakura K, Ugata Y, Maki H, Yamamoto K,et al., Combined pre- and post-capillary pulmonary hypertension: The clinical implications for patients with heart failure. PLoS One, 2021. \u003cstrong\u003e16\u003c/strong\u003e(3): p. e0247987.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Pulmonary Hypertension, Pulmonary Arterial Stiffness, Pulse Wave Velocity, Phase-contrast","lastPublishedDoi":"10.21203/rs.3.rs-7228327/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7228327/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003ePulmonary arterial stiffness (PAS) is a noninvasive imaging biomarker associated with disease severity in pulmonary hypertension (PH). This study aimed to evaluate PAS using cardiac magnetic resonance (CMR) imaging and investigate its relationship with hemodynamic parameters from right heart catheterization (RHC) across PH subgroups.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003e In this retrospective study, 44 patients with PH who underwent both RHC and CMR were classified into pre-capillary (precapPH), post-capillary (postcapPH), and combined pre- and post-capillary (combPH) PH groups based on guideline-defined criteria. PAS was assessed by CMR-derived pulse wave velocity (PWV) and relative area change (RAC) of the main pulmonary artery. RHC measurements included mPAP, PVR, and right ventricular pressures and mixed venous saturation.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003ePWV was significantly higher in combPH (4.49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32 m/s) compared to precapPH (3.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98 m/s, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04). RAC was significantly lower in combPH (0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11) than in postcapPH (0.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09), p\u0026thinsp;=\u0026thinsp;X.XX) and precapPH (0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01). PWV correlated with mPAP (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.34, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.022), RAP (r\u0026thinsp;=\u0026thinsp;0.39, p\u0026thinsp;=\u0026thinsp;0.008), and RVEDVi (r\u0026thinsp;=\u0026thinsp;0.34, p\u0026thinsp;=\u0026thinsp;0.022), while RAC showed a negative correlation with PVR (\u003cem\u003er\u003c/em\u003e = \u0026minus;\u0026thinsp;0.36, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01). Distinct RV adaptation patterns were observed among subgroups, with combPH patients exhibiting the most impaired hemodynamics.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eCMR-derived PAS indices correlate with invasive hemodynamic markers and differ among PH subtypes. PWV and RAC may serve as useful noninvasive markers for assessing pulmonary vascular burden and differentiating disease severity in PH. Larger prospective studies are needed to validate their clinical utility.\u003c/p\u003e","manuscriptTitle":"Relationship of Cardiac MRI-Derived Pulmonary Arterial Stiffness Markers and Invasive Hemodynamic","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-27 06:18:23","doi":"10.21203/rs.3.rs-7228327/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"20836d87-e6b1-4566-825b-90be535124f7","owner":[],"postedDate":"August 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-29T11:09:02+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-27 06:18:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7228327","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7228327","identity":"rs-7228327","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}