Myocardial Pyruvate Metabolism Before and After CABG in Three-Vessel Disease Using Hyperpolarized Carbon-13 MRI

Myocardial Pyruvate Metabolism Before and After CABG in Three-Vessel Disease Using Hyperpolarized Carbon-13 MRI | 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 Article Myocardial Pyruvate Metabolism Before and After CABG in Three-Vessel Disease Using Hyperpolarized Carbon-13 MRI Gaurav Sharma, Jaidip Jagtap, Sung-Han Lin, Jae Mo Park, Crystal Harrison, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9570351/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Hyperpolarized [1-¹³C]pyruvate MRI provides real-time, radiation-free insight into myocardial pyruvate metabolism and mitochondrial oxidative capacity, yet its utility in patients with severe multivessel coronary artery disease before and after surgical revascularization remains unknown. Here we show, in the first prospective study applying this technique to three-vessel disease, that serial imaging is feasible and safe with no serious adverse events in 22 injections. Healthy myocardium displayed a bicarbonate-to-total hyperpolarized carbon product ratio of 0.66 ± 0.13, indicating that the majority of pyruvate undergoes oxidation. Patients exhibited significantly lower ratios in the inferolateral segment (P = 0.03) with reciprocal increases in lactate, and global ratios correlated with left ventricular ejection fraction (r = 0.695, P = 0.006). Post-revascularization changes were heterogeneous across individuals. These findings establish hyperpolarized 13C MRI as a powerful tool for noninvasive assessment of myocardial metabolism in multivessel coronary artery disease and support its potential for longitudinal therapeutic monitoring. Health sciences/Biomarkers/Diagnostic markers Health sciences/Cardiology/Cardiovascular biology/Cardiovascular diseases/Vascular diseases/Coronary artery disease and stable angina/Ischaemia Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 INTRODUCTION Coronary artery bypass grafting (CABG) remains the standard of care for patients with severe multivessel coronary artery disease (CAD), particularly those with left main or three-vessel involvement accompanied by reduced left ventricular function 1,2 . The success of surgical revascularization depends critically on the presence of viable myocardium capable of functional recovery following restoration of blood flow 3,4 . Current methods for assessing ischemic burden or myocardial viability include dobutamine echocardiography, myocardial perfusion imaging, delayed enhancement cardiac magnetic resonance imaging (MRI), and 18 F-fluorodeoxyglucose positron emission tomography, which evaluates glucose metabolic activity 3,5-8 . Although these modalities provide complementary information, they assess metabolic status indirectly or require ionizing radiation which limits serial studies. Hyperpolarized 13 C MRI is an emerging noninvasive method that provides unprecedented real-time metabolic insight into mitochondrial function in human patients, entirely free of ionizing radiation. 9-12 Intravenous injection of hyperpolarized [1- 13 C]pyruvate enables real-time visualization of myocardial pyruvate metabolism, where flux through pyruvate dehydrogenase (PDH) to bicarbonate reflects mitochondrial oxidative capacity, and conversion via lactate dehydrogenase (LDH) to lactate, indicates redox state and overall carbohydrate metabolism. 13,14 In ischemic myocardium, reduced oxygen delivery impairs mitochondrial oxidative phosphorylation, diminishing fatty acid oxidation and PDH-mediated pyruvate oxidation while increasing reliance on anaerobic glycolysis. These metabolic shifts may precede structural changes detectable by conventional imaging. Detecting PDH flux, a unique feature of mitochondrial function, may better identify patients likely to benefit from revascularization. The ability to assess apparent PDH activity using HP [1- 13 C]pyruvate MRI therefore offers a unique window into myocardial metabolic status that may inform ischemia and viability assessment and improve therapeutic decision-making. The objectives of this study were threefold: to characterize myocardial pyruvate metabolism using HP [1- 13 C]pyruvate MRI in patients with three-vessel coronary artery disease compared with healthy controls; to evaluate regional metabolic alterations corresponding to coronary artery territories; and to assess metabolic changes following coronary artery bypass grafting. The findings establish feasibility for this metabolic imaging approach in the longitudinal evaluation of patients undergoing surgical revascularization and provide preliminary evidence for its potential role in assessing myocardial metabolism in real-time to guide management of ischemic heart disease. RESULTS Study Population Characteristics Baseline characteristics of the study population are presented in Table 1. Healthy controls (n=9) were younger (36 ± 4 versus 64 ± 12 years, p<0.001), more likely female (66.7% versus 0%), and had lower body mass index (24.2 ± 1.0 versus 29.1 ± 1.2 kg/m², p<0.01) compared with CAD patients (n=5). By design, healthy controls had no cardiovascular comorbidities, whereas CAD patients demonstrated a high burden of traditional cardiovascular risk factors including hypertension (80%), hyperlipidemia (60%), former tobacco use (60%), and diabetes or prediabetes (40%). Two patients (40%) had obstructive sleep apnea and two (40%) had a history of malignancy. All CAD patients had angiographically confirmed three-vessel coronary artery disease with significant stenoses requiring elective surgical revascularization (Supplementary Table 2 and Supplementary Methods). Pre-CABG imaging was performed 14 ± 9 days before surgery, and post-CABG imaging occurred 120 ± 23 days following the procedure. Safety and Feasibility of Hyperpolarized 13 C MRI All 22 hyperpolarized [1-¹³C]pyruvate injections (10 healthy + 6 pre-CABG + 6 post-CABG) were completed without serious adverse events. No subjects experienced clinically significant hemodynamic perturbations, arrhythmias, allergic reactions, or injection site reactions during the study or during the 2-hour follow up. Side effects were limited to mild lip flushing or a metallic taste immediately following injection, resolving within seconds. One healthy volunteer (H7) and one CAD patient (Pre-CABG5) were excluded from analysis due to technical failures, yielding a per-protocol technical success rate of 87.5% (14/16 acquisitions). Quality control parameters for all successful acquisitions were within predefined acceptable ranges (Figure 2B), including temperature (28.0 ± 2.6°C), pH (7.75 ± 0.19), pyruvate concentration (245 ± 11 mM), polarization signal (4500 ± 1483 a.u.), time from dissolution to injection (48 ± 8 seconds), and residual radical concentration (1.61 ± 1.60 μM, all within optimal range). In selected subjects, a second HP [1- 13 C]pyruvate injection was performed at a different imaging axis (long-axis versus short-axis) within the same session. Corresponding short-axis and long-axis metabolite maps confirmed consistent spatial localization of pyruvate, bicarbonate, and lactate signals across the 17-segment model (Supplementary Figure 3). Regional Metabolic Assessment: Healthy Controls Versus Pre-CABG Representative dynamic image series from a healthy volunteer (Figure 2C, upper rows) and a pre-CABG patient (Figure 2E) capture the metabolic bolus transit and its characteristic differences between normal and ischemic myocardium. Extended temporal resolution of this transit is detailed in Supplementary Figure 4. The high-signal pyruvate bolus is first visualized in the left ventricular cavity (reflecting the 25-second delay in data acquisition after injection), while signal appearance in the right ventricular cavity is observed subsequently during recirculation. Representative normalized dynamic curves demonstrate robust oxidative metabolic activity in a healthy volunteer (Figure 2D), characterized by a dominant bicarbonate peak (AUC Bic = 13.54 a.u.). Conversely, the pre-CABG patient (Figure 2F) exhibits suppressed bicarbonate production (AUC Bic = 5.93 a.u.) and a flattened, delayed metabolic conversion profile compared to the sharp, early peak observed in the healthy control (Figure 2D), despite an identical injection protocol. Representative Bic/THCP ratio maps for each individual subject are shown in Figure 3A-B. In healthy controls, Bic/THCP ratios were relatively uniform across all six mid-ventricular myocardial segments (mean of all signal from the LV myocardium, 0.66 ± 0.13; Figure 5A), indicating homogeneous PDH-mediated metabolic activity. In contrast, pre-CABG patients demonstrated marked regional metabolic heterogeneity with reduced Bic/THCP ratios (mean global ratio 0.51 ± 0.18; Figure 5A), most notably in the inferolateral territories (p=0.03). Although all patients had 3-vessel CAD, this cohort had a high prevalence of severe circumflex and right CAD (Supplementary Table 2). Segment-by-segment comparison revealed significantly reduced bicarbonate production in the inferolateral segment (AHA segment 11) of pre-CABG patients compared with healthy controls (p=0.03; Figure 3H), corresponding to the circumflex or right coronary artery territory. Representative angiographic images (Figure 3C) illustrate the lesion distribution in one patient. Other segments showed non-significant trends toward reduced Bic/THCP ratios in the pre-CABG group, including the inferior segment (p=0.06; Figure 3G). Because Bic/THCP and Lac/THCP sum to 1 by definition, reduced Bic/THCP necessarily corresponds to elevated Lac/THCP at both the global and voxel level. The spatial distribution of Lac/THCP across individual voxels (Supplementary Figure 5) provides a complementary view of regional metabolic heterogeneity, with higher values in territories corresponding to stenotic vessels. As expected from the Bic/THCP results, the inferolateral segment (segment 11) showed significantly elevated Lac/THCP in pre-CABG patients versus healthy controls (p=0.03; Supplementary Figure 5G). Anatomical overlay of individual metabolite maps onto proton images confirmed accurate cardiac localization of the hyperpolarized ¹³C signal and illustrated the regional differences in bicarbonate distribution between healthy and ischemic myocardium (Supplementary Figure 7). Mid-ventricular polar maps (Figure 5A and 5B) summarize the AHA 17-segment distribution of Bic/THCP ratios and Lac/THCP ratios across all three groups. These maps highlight the regional metabolic impairment concentrated in the inferolateral and inferior segments of pre-CABG patients, contrasting with the relatively uniform metabolic pattern observed in healthy controls. Ventricular Function Pre-CABG patients exhibited localized regional metabolic impairments against a background of otherwise intact global oxidative activity, as shown in Figure 3A-3I. Across the combined cohort of healthy controls and pre-CABG patients, mean global Bic/THCP ratio correlated significantly with left ventricular ejection fraction (Spearman r=0.695, p=0.006; Figure 3L), demonstrating that impaired PDH-mediated pyruvate oxidation is significantly associated with reduced systolic function. Functional assessment confirmed that left ventricular ejection fraction (LVEF) was significantly lower in pre-CABG patients compared with healthy controls (43.0 ± 10.5% versus 60.2 ± 7.8%; p=0.02; Figure 3K). Pre-CABG patients demonstrated reduced systolic function with wall motion abnormalities, consistent with their underlying three-vessel disease. All patients were clinically stable and on guideline-directed medical therapy at the time of imaging. Heart rate did not differ significantly between groups (p=0.55; Figure 3J), nor did left ventricular stroke volume (p=1.00; Figure 3M) or cardiac output (p=1.00; Figure 3N). Right ventricular ejection fraction (p=0.61; Figure 3O) and right ventricular cardiac output (p=0.80; Figure 3P) were also comparable between groups. Following CABG, there was no difference in ejection fraction compared with pre-CABG values (43.0 ± 10.5% pre-CABG versus 44.8 ± 10.2% post-CABG; p=0.44; Figure 4J), Other hemodynamic parameters including heart rate, stroke volume, and cardiac output remained stable following surgery (Figure 4I, 4L-O). Metabolic Changes Following CABG Paired pre-CABG and post-CABG Bic/THCP ratio maps for all five patients are presented in Figure 4A–B. Visual inspection of individual patient maps revealed heterogeneous responses to surgical revascularization. Notably, Post-CABG3 demonstrated a marked decrease in Bic/THCP ratios compared with Pre-CABG3, while Post-CABG6 showed improvement relative to Pre-CABG6, illustrating the inter-patient variability inherent to this small cohort. In aggregate, the mean global Bic/THCP ratio did not change significantly following CABG (pre-CABG: 0.51 ± 0.18 versus post-CABG: 0.42 ± 0.34; mean δ: −0.09 ± 0.27; Figure 5A). Regional quantitative comparisons demonstrated no statistically significant changes in any individual segment (Figure 4C–H), including the inferolateral segment (p=1.00; Figure 4G). However, Bic/THCP ratios (Figure 5A) revealed trends toward improvement in specific segments, with mean normalized ratios increasing from 0.49 ± 0.18 (pre-CABG) to 0.57 ± 0.32 (post-CABG; mean δ: +0.09 ± 0.27). Corresponding Lac/THCP ratio maps in CAD patients showed reciprocal trends to the Bic/THCP ratio, with heterogeneous responses in lactate production observed in previously ischemic territories following revascularization (Supplementary Figure 6). While this study was not primarily designed to determine kinetic rate constants, we explored the feasibility of mapping apparent kinetic rate constants with spatial distributions mapping the conversion of pyruvate conversion (Supplementary Figures 8-10). Spatial distributions of k PB (pyruvate-to-bicarbonate; Supplementary Figure 8) revealed heterogeneous post-CABG changes, while k PL (pyruvate-to-lactate; Supplementary Figure 9) remained relatively stable following revascularization, suggesting that metabolic recovery, where present, primarily involves restoration of oxidative capacity rather than cytosolic redox state. Corresponding polar maps are shown in Supplementary Figure 10. A trend toward a positive correlation between mean global Bic/THCP ratio and LV ejection fraction was observed in the pre- and post-CABG cohort (Spearman r = 0.575, p = 0.082; Figure 4K), consistent with the strong relationship observed in the combined healthy and pre-CABG analysis, though it did not reach statistical significance in this smaller paired group. Circulating Metabolic Substrates Results from serum metabolite analysis are shown in Figures 6A–D. As anticipated, triglyceride levels were significantly elevated in pre-CABG patients compared with healthy controls (p=0.011; Figure 6B). Serum pyruvate, prior to the HP exam, was increased following CABG, perhaps indicating diet or medications changes (p=0.002; Figure 6C). Insulin levels showed a non-significant trend toward reduction following CABG (Figure 6A), while non-esterified fatty acid levels remained stable across all groups (Figure 6D). Medication changes following CABG were documented (Figure 6E). All five CAD patients received lipid-lowering agents and antiplatelet therapy at both time-points. Diuretic use increased from one to five patients post-CABG, likely due to post-operative fluid management protocols, while SGLT2 inhibitors were initiated in two patients. Calcium channel blocker use decreased from four to two patients, and nitrate use decreased from four to one patient following revascularization. DISCUSSION This is the first report of imaging the products of HP [1- 13 C]pyruvate in patients with documented three-vessel coronary artery disease before and after surgical revascularization. This study demonstrates the feasibility and safety of HP [1- 13 C]pyruvate MRI for serial evaluation of mitochondrial function in the heart of patients with severe coronary artery disease and abnormal ventricular function. The principal findings include: high Bic/THCP in healthy myocardium, a correlation between global metabolic activity and ventricular function across all subjects, and a variable metabolic response following CABG. In selected subjects there were regional reductions in PDH-mediated bicarbonate production in territories corresponding to severe coronary stenoses. These observations establish a foundation for larger studies examining the role of 13 C metabolic imaging in assessment of patients with ischemic heart disease. Earlier spectroscopy studies of pyruvate metabolism in human myocardium found that only a small fraction of the injected pyruvate was oxidized in mitochondria and the majority was reduced to lactate. Bic/THCP ranged from 0.07 to 0.23 in healthy subjects or in otherwise-healthy women prior to therapy for breast cancer 10 15 . The current finding that Bic/THCP was much higher (0.66 in healthy myocardium and 0.51 even in patients with severe coronary artery disease), indicates that in stable subjects the majority of injected pyruvate undergoes oxidative metabolism. This difference between current results and earlier reports is due to acquisition of HP[1- 13 C]lactate signal from the blood pool in the right and left ventricular cavities in spectroscopy studies, thus reducing the ratio Bic/(Bic+Lac). The current results demonstrate that 13 C imaging is essential for exams in patients. Under conditions of persistent oxygen limitation, the myocardium becomes more reduced, leading to inactivation of the PDH complex and impaired decarboxylation of pyruvate. Metabolism of pyruvate and other carbohydrates shifts to lactate production because of the high NADH/NAD + in ischemic muscle. Overall glucose metabolism shifts to anaerobic glycolysis. In the current study, all patients had angiographically significant three vessel CAD and all subjects were clinically stable at the time of the exam without complaints of angina and presumably without ischemia. However, in this population, the reduction in bicarbonate production observed in the inferolateral segment (AHA segment 11, p=0.03) correlated with the angiographic severity of individual stenoses in the right coronary artery or the circumflex system, perhaps indicating subclinical ischemia. When all subjects, healthy and pre-CABG patients were grouped, there was a correlation (r=0.695, p=0.006) between PDH-mediated oxidative capacity (Bic/THCP ratio) and LVEF. As suggested, this effect could be due to subclinical ischemia. However, PDH flux is very sensitive to competing substrates. Increased oxidation of long-chain fatty acids or ketones may substantially suppress PDH flux even in normal myocardium 13,14 , and it is conceivable that some drug therapies such as beta adrenergic blockers may impact PDH flux. The possibility that systemic changes in oxidizable substrate concentrations must be considered is supported by the findings of small differences in the concentrations of triglycerides, fatty acids and other substrates in subsets. Thus, although the current results are consistent with an effect of severe CAD on both left ventricular function and pyruvate oxidation, further work on the effects of competing substrates and drug effects is essential to determine if reduced pyruvate oxidation indicates subclinical and perhaps reversible ischemia. The metabolic response to surgical revascularization observed in this study was heterogeneous across patients and segments. While the normalized Bic/THCP ratio showed a numerical increase from 0.49 ± 0.18 to 0.57 ± 0.32 (δ: +0.09 ± 0.27; Figure 5B), the unnormalized global ratio exhibited a slight decrease (0.51 ± 0.18 to 0.42 ± 0.34; δ: −0.09 ± 0.27; Figure 5A), and individual segment comparisons did not reach statistical significance (Figure 4C–H). This discordance likely reflects the substantial inter-patient variability inherent to a five-patient cohort, where individual outliers (such as Post-CABG3, who demonstrated markedly reduced metabolic activity) can disproportionately influence group-level statistics. The wide standard deviations observed in δ values across all segments (Figure 5A–B and Supplementary Figure 10) underscore this challenge. Despite the absence of statistically significant paired changes, the direction of metabolic recovery in several individual patients aligns with the expected physiological response to restored coronary blood flow, namely improved oxygen delivery and reactivation of mitochondrial oxidative phosphorylation. Serial perfusion-metabolism studies using PET have demonstrated that recovery of glucose metabolism may precede or parallel functional improvement following revascularization 16 , and the 120-day post-CABG time point in the present study may capture a period of ongoing metabolic remodeling where resting oxidative metabolic activity has not yet fully normalized. Current clinical practice for myocardial viability assessment relies primarily on delayed enhancement cardiac MRI and 18 F-FDG PET 6 . Delayed enhancement imaging identifies irreversible scar based on gadolinium kinetics but cannot directly assess metabolic activity in non-enhanced segments. Monitoring carbohydrate metabolism using [ 18 F]fluoro-deoxyglucose is thought to be the most sensitive method for identifying heart muscle that will recover after revascularization 6,17 . However, a clear benefit for FDG PET-assisted care was not demonstrated in one study 18 , suggesting that alternative methods may provide additional information. Surprisingly, the impact of bypass surgery on myocardial carbohydrate metabolism has not been extensively evaluated. Glucose metabolism may be reduced by CABG, consistent with results in some of the current patients 19,20 . Hyperpolarized [1- 13 C]pyruvate MRI offers several potential advantages for myocardial metabolic assessment. The technique directly visualizes metabolic conversion rather than static tracer accumulation, providing mechanistic information about PDH activity that underlies cellular energy production. The absence of ionizing radiation permits serial imaging to monitor therapeutic response. Furthermore, integration with anatomical proton MRI within a single examination enables comprehensive characterization of structure, function, and metabolism. Future studies directly comparing HP [1- 13 C]pyruvate MRI with established stress test and viability methods are warranted to define the incremental value of metabolic imaging. The small sample size limits statistical power and precludes definitive conclusions regarding metabolic differences and treatment effects. The substantial age and sex differences between healthy controls and CAD patients represent potential confounders. Although patients were clinically stable at the time of the study, there was no independent assessment of possible ischemia at the time of the exam. Further, the hemodynamic significance of each lesion was not assessed by invasive methods, so even moderately significant stenosis could have been associated with downstream ischemia. The lack of direct comparison with established viability methods ( 18 F-FDG PET, delayed enhancement MRI) prevents assessment of incremental diagnostic value. The findings of this study have several potential clinical implications that warrant validation in appropriately powered cohorts. First, pre-operative metabolic imaging with HP [1-¹³C]pyruvate MRI may inform patient selection for surgical revascularization by identifying ischemic myocardium. The significant correlation between Bic/THCP ratio and LVEF observed in this study (r=0.695, p=0.006) suggests that metabolic imaging provides complementary prognostic information that could enhance existing decision-making frameworks in low ejection fraction patients. Second, serial metabolic imaging may enable non-invasive monitoring of therapeutic response, not only to revascularization but also to emerging metabolic modulators 21-23 . Third, integration of metabolic imaging with first-pass perfusion assessment within a single MRI examination may enable characterization of perfusion-metabolism mismatch analogous to PET-based approaches, potentially identifying hibernating myocardium with greater specificity and without the logistical burden of coordinating two separate imaging modalities. Finally, the current study demonstrated the feasibility of collecting kinetic rate constant data from all myocardial segments. Such data have been used in earlier studies to calculate the apparent rate constants for pyruvate conversion to bicarbonate or lactate. The current pulse sequence with a delay of 25 seconds prior to data acquisition is not suitable for the earlier mathematical models, but it would be a simple matter to collect appropriate data. Development of alternative hyperpolarized substrates, such as [2- 13 C]pyruvate for Krebs cycle assessment or [ 13 C]acetoacetate for ketone bodies may provide additional metabolic dimensions relevant to ischemic heart disease 24,25 . This study demonstrates the feasibility and safety of HP [1- 13 C]pyruvate MRI for assessing myocardial pyruvate metabolism in patients with three-vessel coronary artery disease before and after CABG. Regional metabolic impairment corresponding to coronary territories and significant correlations with ventricular function support the potential of this technique as a non-invasive metabolic biomarker. These findings establish a foundation for larger validation studies examining the role of metabolic imaging in myocardial viability assessment and therapeutic monitoring. METHODS Study Design and Population This prospective, single-center study enrolled participants between June 2023 and July 2025 at UT Southwestern Medical Center (Figure 1). The study protocol was approved by the institutional review board (IRB No. STU-2020-0953, investigational new drug application no. 133229, NCT06047028), and all participants provided written informed consent. The study population comprised two cohorts: healthy volunteers without cardiovascular disease or risk factors, and patients with angiographically confirmed three-vessel coronary artery disease scheduled for elective CABG. The detailed enrollment criteria are available in Supplementary Methods. Briefly, the inclusion criteria for healthy volunteers included age 18-80 years, absence of cardiovascular disease or major cardiovascular risk factors (hypertension, diabetes mellitus, hyperlipidemia, tobacco use), body mass index less than 30 kg/m 2 , and no contraindications to MRI. Inclusion criteria for the CAD cohort included age 18 years or older, angiographically documented three-vessel CAD with planned CABG, and clinical stability allowing pre-operative imaging. Exclusion criteria for both groups included estimated glomerular filtration rate less than 60 mL/min/1.73m 2 , contraindications to MRI, pregnancy or lactation, and inability to provide informed consent. Of 16 enrolled subjects, 10 were healthy volunteers and 6 were CAD patients. One healthy volunteer and one CAD patient were excluded due to technical acquisition failures, yielding final cohorts of 9 healthy controls and 5 CAD patients for analysis. CAD patients underwent imaging at two time points: pre-CABG (14 ± 9 days before surgery) and post-CABG (120 ± 23 days after surgery). Hyperpolarized [1- 13 C]Pyruvate Preparation and Quality Control Clinical-grade [1- 13 C]pyruvic acid (Isotec, Sigma-Aldrich) was polarized using a SPINlab clinical polarizer (GE Healthcare, Waukesha, WI, USA) according to previously validated protocols 26,27 . Briefly, 1.47 g of neat pyruvic acid containing 15 mM trityl radical (AH111501, GE Healthcare) and 1 mM gadolinium chelate was placed in the polarization chamber and subjected to microwave irradiation at 3.35 T and 0.85 K. Following polarization (3.70 ± 0.62 hours), the sample was rapidly dissolved in superheated sterile water and neutralized to physiological pH. Rigorous quality control parameters were verified before injection, consistent with investigational new drug requirements (Supplementary Figure 1). Quality control metrics included: temperature, pH, pyruvate concentration, signal from SPINlab, time from dissolution to injection, and residual radical concentration. Injections were administered as a 0.4 mL/kg bolus (0.1 mmol/kg) over 20 seconds into an antecubital vein, followed by a 25 mL saline flush (Figure 2). MRI Protocol All imaging was performed on a 3T clinical MRI scanner (750w Discovery, GE Healthcare, Waukesha, WI) equipped with a custom-built two-loop 13 C Helmholtz surface coil (PulseTeq Limited; Chobham, Surrey, UK) for 13 C imaging and the body coil for 1 H localization. Subjects underwent a standardized glucose load (48 g oral glucose) approximately 30 minutes before imaging to stimulate insulin secretion and enhance myocardial glucose uptake and PDH activity. Following glucose loading, subjects were positioned in the scanner for anatomical reference imaging. Proton imaging included: balanced steady-state free precession cine imaging in standard cardiac views (short-axis stack, 2-chamber, 3-chamber, 4-chamber and long-axis stack) for volumetric analysis. The protocol used a field of view of 400 × 400 mm² with a spatial resolution of 2.08 × 2.08 mm² and slice thickness of 8 mm. Key sequence parameters included a flip angle of 50°, echo time (TE) of 1.2 ms, repetition time (TR) of 3.4 ms, and acquisition of 30 cardiac phases. Following completion of proton imaging, HP [1- 13 C]pyruvate was injected, and 13 C imaging commenced ~ 25 seconds post-injection to target the left ventricular bolus arrival. Hyperpolarized 13 C imaging employed a slice-selective spectral-spatial excitation pulse with metabolite-specific flip angles (pyruvate 10°, lactate 90°, bicarbonate 90°) to optimize signal while preserving hyperpolarization. Dynamic acquisition parameters included: field of view (FOV): 400 × 400 mm², matrix 40 x 40, data acquisition every R-R interval at end-diastole, in-plane resolution 10 mm x 10 mm, slice thickness 30 mm, and temporal resolution of 1 cardiac cycle over 60 seconds of acquisition. Electrocardiographic gating was employed to minimize cardiac motion artifacts. All subjects received at least one HP [1- 13 C]pyruvate injection for short-axis (SAX) cardiac imaging, with select subjects receiving an additional HP [1- 13 C]pyruvate injection for long-axis (LAX) imaging within the same session. All procedures for hyperpolarized pyruvate production and injection, 1 H MRI acquisition, 13 C MRI acquisition, and subject monitoring were conducted in accordance with previously published studies and consensus statement 26-28 . Image Analysis and Metabolic Quantification Proton cine images were analyzed using commercial software (QMass, Medis Medical Imaging Systems) for quantification of left ventricular volumes, ejection fraction, and wall motion. Hyperpolarized 13 C data were processed using MATLAB (R2025b; MathWorks, Natick, MA) based HP- 13 CMRAnalyst (custom software; Supplementary Figure 2) incorporating established methodologies 29 . Segmental analysis followed the American Heart Association 17-segment model 30 . Data were analyzed in segments 7 to 12. Metabolic ratios were calculated for each myocardial segment. Total hyperpolarized carbon-13 product (THCP) was defined as the sum of hyperpolarized [1- 13 C]lactate and [ 13 C]bicarbonate signals. Primary metabolic metrics included: bicarbonate-to-THCP ratio (Bic/THCP), reflecting PDH-mediated pyruvate-to-bicarbonate conversion; lactate-to-THCP ratio (Lac/THCP), reflecting lactate dehydrogenase activity; and total metabolic activity (sum of bicarbonate and lactate signals within the myocardium). While these experiments were not designed to calculate kinetic rate constants, apparent kinetic rate constants were estimated using a simplified two-site exchange model 31,32 . This approach eliminates the need for arterial input function modeling by using the measured pyruvate signal directly as the driving function. Model fitting was performed on a voxel-wise basis using nonlinear least-squares optimization, with constraints applied to ensure physiologically plausible solutions. Additional methodological details, assumptions, and validation analyses are provided in the Supplementary Material. Laboratory Assessments Fasting blood samples were obtained before each imaging session for metabolic substrate analysis. Measurements included serum glucose, insulin, triglycerides, non-esterified fatty acids (NEFA), and pyruvic acid. Comprehensive metabolic panels and complete blood counts were performed to ensure eligibility and safety (Supplementary Table 1). Statistical Analysis Continuous variables are presented as mean ± standard deviation or median (interquartile range) as appropriate. Categorical variables are presented as counts and percentages. Comparisons between healthy controls and pre-CABG patients employed the Mann-Whitney U test for continuous variables and Fisher exact test for categorical variables, given the small sample sizes. Paired comparisons between pre-CABG and post-CABG measurements used the Wilcoxon signed-rank test. Correlations between metabolic parameters and ventricular function were assessed using Spearman rank correlation. Regional metabolic differences across coronary territories were evaluated using analysis of variance with post-hoc Tukey correction. A two-sided p-value≤0.05 was considered statistically significant. Given the exploratory nature of this study, analyses were focused on effect size estimation and physiological plausibility. No formal correction for multiple comparisons was applied to avoid Type II errors in this pilot cohort; results should be interpreted as hypothesis-generating. Statistical analyses were performed using R Statistical Software (v4.5.2; R Core Team, 2025) and GraphPad Prism (v10, GraphPad Software). Declarations ACKNOWLEDGMENTS The authors thank the research nursing staff and MRI technologists at the Advanced Imaging Research Center and Clinical Trials Office at Cardiovascular and Thoracic Surgery for their expert assistance with study conduct. The authors also thank the patients and healthy volunteers who participated in this research. ETHICS STATEMENT This study was conducted in accordance with the Declaration of Helsinki. The protocol was approved by the Institutional Review Board of UT Southwestern Medical Center (IRB No. STU-2020-0953) under IND No. 133229. The study is registered at ClinicalTrials.gov (NCT06047028). All participants provided written informed consent prior to enrollment. DATA AVAILABILITY De-identified individual participant data and the custom MATLAB-based analysis software (HP- 13 CMRAnalyst) are available from the corresponding authors upon reasonable request, subject to institutional data sharing agreements and applicable privacy regulations. AUTHOR CONTRIBUTIONS Author Contributions G.S., C.R.M. and M.E.J. conceived and designed the study. G.S., S.H.L., J.M.P., C.E.H., J.L., S.S.M., and C.R.M. performed experiments and acquired data. G.S. and J.M.J. analyzed the data. G.S., C.R.M., M.P., and M.E.J. interpreted the results. G.S. drafted the manuscript with input from all authors. All authors critically revised the manuscript for important intellectual content and approved the final version submitted for publication. FUNDING STATEMENT This work was supported by the American Heart Association (23SCEFIA1154964, 24IPA1272385, 24TPA1297929) and the National Institutes of Health (S10OD018468, S10RR029119, P41EB015908, R01HL170039). COMPETING INTERESTS The authors declare that they have no competing financial or non-financial interests. References Virani, S. S. et al. 2023 AHA/ACC/ACCP/ASPC/NLA/PCNA Guideline for the Management of Patients With Chronic Coronary Disease: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines. Circulation 148 , e9–e119 (2023). https://doi.org/10.1161/CIR.0000000000001168 Lawton, J. S. et al. 2021 ACC/AHA/SCAI Guideline for Coronary Artery Revascularization: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation 145 , e18–e114 (2022). https://doi.org/10.1161/CIR.0000000000001038 Ryan, M. et al. Myocardial viability testing: all STICHed up, or about to be REVIVED? Eur Heart J 43 , 118–126 (2022). https://doi.org/10.1093/eurheartj/ehab729 Velazquez, E. J. et al. Coronary-Artery Bypass Surgery in Patients with Ischemic Cardiomyopathy. 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Hyperpolarized 13C Metabolic MRI of the Human Heart: Initial Experience. Circ Res 119 , 1177–1182 (2016). https://doi.org/10.1161/CIRCRESAHA.116.309769 Rider, O. J. et al. Noninvasive In Vivo Assessment of Cardiac Metabolism in the Healthy and Diabetic Human Heart Using Hyperpolarized (13)C MRI. Circ Res 126 , 725–736 (2020). https://doi.org/10.1161/CIRCRESAHA.119.316260 Apps, A. et al. Proof-of-Principle Demonstration of Direct Metabolic Imaging Following Myocardial Infarction Using Hyperpolarized 13C CMR. JACC Cardiovasc Imaging 14 , 1285–1288 (2021). https://doi.org/10.1016/j.jcmg.2020.12.023 Larson, P. E. Z. et al. Regional quantification of cardiac metabolism with hyperpolarized [1-13C]-pyruvate CMR evaluated in an oral glucose challenge. Journal of Cardiovascular Magnetic Resonance 25 , 77 (2023). https://doi.org/https://doi.org/10.1186/s12968-023-00972-7 Merritt, M. E. et al. Hyperpolarized 13C allows a direct measure of flux through a single enzyme-catalyzed step by NMR. 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Curr Probl Cardiol 32 , 375–410 (2007). https://doi.org/10.1016/j.cpcardiol.2007.04.001 Beanlands, R. S. et al. F-18-fluorodeoxyglucose positron emission tomography imaging-assisted management of patients with severe left ventricular dysfunction and suspected coronary disease: a randomized, controlled trial (PARR-2). J Am Coll Cardiol 50 , 2002–2012 (2007). https://doi.org/10.1016/j.jacc.2007.09.006 Maes, A. et al. Regional myocardial blood flow, glucose utilization and contractile function before and after revascularization and ultrastructural findings in patients with chronic coronary artery disease. Eur J Nucl Med 22 , 1299–1305 (1995). https://doi.org/10.1007/BF00801617 Tamaki, N. et al. Relation of change in wall motion and glucose metabolism after coronary artery bypass grafting--assessment with positron emission tomography. Jpn Circ J 55 , 923–929 (1991). https://doi.org/10.1253/jcj.55.923 Fragasso, G. et al. Effects of metabolic modulation by trimetazidine on left ventricular function and phosphocreatine/adenosine triphosphate ratio in patients with heart failure. Eur Heart J 27 , 942–948 (2006). https://doi.org/10.1093/eurheartj/ehi816 Morrow, D. A. et al. Effects of Ranolazine on Recurrent Cardiovascular Events in Patients With Non–ST-Elevation Acute Coronary SyndromesThe MERLIN-TIMI 36 Randomized Trial. JAMA 297 , 1775–1783 (2007). https://doi.org/10.1001/jama.297.16.1775 Santos-Gallego, C. G. et al. Empagliflozin Ameliorates Adverse Left Ventricular Remodeling in Nondiabetic Heart Failure by Enhancing Myocardial Energetics. J Am Coll Cardiol 73 , 1931–1944 (2019). https://doi.org/10.1016/j.jacc.2019.01.056 Schroeder, M. A. et al. Real-time assessment of Krebs cycle metabolism using hyperpolarized 13C magnetic resonance spectroscopy. FASEB J 23 , 2529–2538 (2009). https://doi.org/10.1096/fj.09-129171 Sharma, G. et al. Co-Polarized [1-13C]Pyruvate and [1,3-13C2]Acetoacetate Provide a Simultaneous View of Cytosolic and Mitochondrial Redox in a Single Experiment. ACS Sensors 6 , 3967–3977 (2021). https://doi.org/10.1021/acssensors.1c01225 Punwani, S. et al. Consensus recommendations for hyperpolarized [1-13C]pyruvate MRI multi-center human studies. Magnetic Resonance in Medicine 94 , 1386–1400 (2025). https://doi.org/https://doi.org/10.1002/mrm.30570 Ma, J. et al. Cardiac T2 * measurement of hyperpolarized (13) C metabolites using metabolite-selective multi-echo spiral imaging. Magn Reson Med 86 , 1494–1504 (2021). https://doi.org/10.1002/mrm.28796 Reed, G. D. et al. Characterization and compensation of f0 inhomogeneity artifact in spiral hyperpolarized (13) C imaging of the human heart. Magn Reson Med 86 , 157–166 (2021). https://doi.org/10.1002/mrm.28691 Sharma, G., Jagtap, J., Peltz, M., Malloy, C. & Jessen, M. Abstract 4365204: HP-13CMRAnalyst: A MATLAB Application for Dynamic Cardiac Metabolic Imaging Analysis Using Hyperpolarized Carbon-13 MRI. Circulation 152 , A4365204–A4365204 (2025). https://doi.org/10.1161/circ.152.suppl_3.4365204 Cerqueira, M. D. et al. Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart. A statement for healthcare professionals from the Cardiac Imaging Committee of the Council on Clinical Cardiology of the American Heart Association. Circulation 105 , 539–542 (2002). https://doi.org/10.1161/hc0402.102975 Khegai, O. et al. Apparent rate constant mapping using hyperpolarized [1-(13)C]pyruvate. NMR Biomed 27 , 1256–1265 (2014). https://doi.org/10.1002/nbm.3174 Zierhut, M. L. et al. Kinetic modeling of hyperpolarized 13C1-pyruvate metabolism in normal rats and TRAMP mice. J Magn Reson 202 , 85–92 (2010). https://doi.org/10.1016/j.jmr.2009.10.003 Table Table 1. Baseline Demographics and Clinical Characteristics. Comparison of demographic data, comorbidities, and anthropometric measurements between Healthy Controls (n=9) and patients with Three-Vessel Coronary Artery Disease (CAD, n=5). Values are presented as mean ± standard deviation or count (percentage). BMI = body mass index; CABG = coronary artery bypass grafting; COPD = chronic obstructive pulmonary disease. * p < 0.05 vs CAD Patients. Additional Declarations There is NO Competing Interest. Supplementary Files NatureCVRManuscriptSupplementaryMaterialFinal04282026.pdf SUPPLEMENTARY MATERIALS The supplementary materials PDF file include: Supplementary Table 1. Baseline Laboratory Parameters Supplementary Table 2. Clinical Course of the CAD patients Supplementary Figure 1. Study Workflow and Quality Control Process Supplementary Figure 2. Metabolism and HP-13CMRAnalyst Software Interface Supplementary Figure 3. Reproducibility Assessment Supplementary Figure 4. Pyruvate metabolism in Healthy vs Pre-CABG subjects Supplementary Figure 5. Lactate/THCP Ratio Maps in Healthy vs Pre-CABG subjects Supplementary Figure 6. Lactate/THCP Ratio Maps in Pre-CABG vs Post-CABG Supplementary Figure 7. Anatomical Overlay of Metabolite Maps in Healthy vs Pre-CABG Supplementary Figure 8. Apparent kPB Rate Constant Maps Supplementary Figure 9. Apparent kPL Rate Constant Maps Supplementary Figure 10. kPL Rate Constant Polar Maps Supplementary Materials and Methods. Enrollment Criteria, Postoperative Metabolic Changes and Clinical Course of CAD subjects, Detailed Kinetic Analysis Protocol Cite Share Download PDF Status: Under Review 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. 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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-9570351","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":638566254,"identity":"8210c544-311e-423c-8acd-7ec71c7cccd5","order_by":0,"name":"Gaurav 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Center","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"Jessen","suffix":""}],"badges":[],"createdAt":"2026-04-29 23:50:40","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9570351/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9570351/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109179800,"identity":"109bda0a-33a7-43d6-af74-0fa67d93de78","added_by":"auto","created_at":"2026-05-13 10:05:48","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":489945,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStudy Flow Diagram. \u003c/strong\u003eSixteen subjects were enrolled between June 2023 and July 2025, comprising 10 healthy volunteers and 6 patients with three-vessel coronary artery disease (CAD). One subject from each cohort was excluded due to technical acquisition failures, yielding final cohorts of 9 healthy controls and 5 CAD patients. CAD patients underwent hyperpolarized (HP) \u003csup\u003e13\u003c/sup\u003eC MRI at two time points: before coronary artery bypass grafting (CABG) (14 ± 9 days pre-surgery) and after CABG (120 ± 23 days post-surgery). \u003csup\u003e1\u003c/sup\u003eH = proton.\u003c/p\u003e","description":"","filename":"image1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9570351/v1/2830d553c964b61e52c341c1.jpg"},{"id":109179798,"identity":"af44b1a0-2ee7-45fd-bf7d-1298fdc8b1d5","added_by":"auto","created_at":"2026-05-13 10:05:47","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1119952,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHyperpolarized \u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e13\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eC MRI Protocol and Quality Control. (A) \u003c/strong\u003eImaging protocol timeline. Subjects underwent oral glucose loading (approximately 30 minutes) followed by positioning and cine imaging (20 minutes). Hyperpolarized [1-\u003csup\u003e13\u003c/sup\u003eC]pyruvate was injected intravenously with electrocardiogram (ECG)-gated \u003csup\u003e13\u003c/sup\u003eC imaging commencing approximately 25 seconds post-injection\u003cstrong\u003e. (B)\u003c/strong\u003e Quality control parameters for all acquisitions demonstrating consistent polarization performance across temperature, pH, pyruvate concentration, signal intensity, dissolution-to-injection delay time, and residual radical concentration. No severe arrhythmia events were observed across all 22 injections (0/22 in 10 healthy, 6 pre-CABG and 6 Post-CABG scans). \u003cstrong\u003e(C–D) \u003c/strong\u003eRepresentative Healthy Volunteer:\u003cstrong\u003e (C) \u003c/strong\u003eWhole-heart dynamic spectral images showing metabolite distribution. (\u003cstrong\u003eD) \u003c/strong\u003eTime-resolved metabolite signal intensity curves extracted specifically from the myocardium (normalized to maximum pyruvate signal), demonstrating high PDH mediated oxidative activity (AUC\u003csub\u003eBic\u003c/sub\u003e=13.54).\u003cstrong\u003e (E–F)\u003c/strong\u003e Representative Pre-CABG Patient: \u003cstrong\u003e(E) \u003c/strong\u003eWhole-heart dynamic spectral images.\u003cstrong\u003e (F) \u003c/strong\u003eCorresponding myocardial signal curves (normalized to maximum pyruvate) in myocardium, revealing blunted oxidative metabolism (AUC\u003csub\u003eBic\u003c/sub\u003e=5.93). AUC = area under the curve; Bic = bicarbonate; Lac = lactate; Pyr = pyruvate.\u003c/p\u003e","description":"","filename":"image2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9570351/v1/83e8ad621adb0a43a31dc1bf.jpg"},{"id":109179796,"identity":"eb5003d7-bf9b-448f-8837-ba90dc556bd0","added_by":"auto","created_at":"2026-05-13 10:05:47","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1040841,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRegional Bicarbonate-to-Total Hyperpolarized Carbon Product (Bic/THCP) Ratio Maps. (A) \u003c/strong\u003eBic/THCP ratio map overlays on anatomic image for all healthy controls (H1-H10, excluding H7) demonstrating relatively uniform metabolic activity across myocardial segments. \u003cstrong\u003e(B) \u003c/strong\u003eBic/THCP ratio maps for pre-CABG patients (Pre-CABG1-Pre-CABG6, excluding Pre-CABG5) showing regional metabolic heterogeneity with reduced bicarbonate production in specific territories. \u003cstrong\u003e(C) \u003c/strong\u003eRepresentative coronary angiography demonstrating stenoses in right coronary artery (RCA), left circumflex (obtuse marginal (OM)), and left anterior descending (LAD) territories.\u003cstrong\u003e (D-I) \u003c/strong\u003eQuantitative comparison of regional Bic/THCP ratios across varying segments (Anterior, Anteroseptal, Inferoseptal, Inferior, Inferolateral, Anterolateral). \u003cstrong\u003e(J-P) \u003c/strong\u003eGlobal hemodynamic and functional metrics comparing healthy controls and pre-CABG patients. Bic/THCP ratios were significantly lower in the inferolateral segment in pre-CABG patients compared with healthy controls (p=0.03).\u003c/p\u003e","description":"","filename":"image3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9570351/v1/a66aff83d2a1ff7d91466bb5.jpg"},{"id":109205402,"identity":"9bf7dc8c-06fe-45c7-825d-f0b674ecc510","added_by":"auto","created_at":"2026-05-13 15:04:36","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1086103,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePre-CABG Versus Post-CABG Bic/THCP Ratio Comparison. (A) \u003c/strong\u003eBic/THCP ratio map overlays on anatomic image for pre-CABG patients.\u003cstrong\u003e (B) \u003c/strong\u003eCorresponding post-CABG maps for the same patients.\u003cstrong\u003e (C-H) \u003c/strong\u003eRegional quantitative comparisons of Bic/THCP ratios before and after surgery. \u003cstrong\u003e(I-O)\u003c/strong\u003e Changes in global hemodynamic parameters following revascularization: Heart Rate \u003cstrong\u003e(I)\u003c/strong\u003e, LV Ejection Fraction \u003cstrong\u003e(J)\u003c/strong\u003e, Bic/THCP ratio versus LV EF correlation in the pre- and post-CABG cohort \u003cstrong\u003e(K)\u003c/strong\u003e, LV Stroke Volume \u003cstrong\u003e(L)\u003c/strong\u003e, LV Cardiac Output \u003cstrong\u003e(M)\u003c/strong\u003e, RV Ejection Fraction \u003cstrong\u003e(N)\u003c/strong\u003e, and RV Cardiac Output \u003cstrong\u003e(O).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9570351/v1/03185fcda9e7914f0fcc03d0.jpg"},{"id":109206006,"identity":"b5cbe4bf-7b00-4fb7-9a29-0924faa11728","added_by":"auto","created_at":"2026-05-13 15:10:29","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":373638,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePolar Maps of Regional Metabolic Parameters. (A) \u003c/strong\u003eMean Bicarbonate-to-Total Hyperpolarized Carbon Product (Bic/THCP) ratio maps for Healthy controls, Pre-CABG, and Post-CABG patients, including quantitative difference (Δ\u003csub\u003ePost - Pre\u003c/sub\u003e). \u003cstrong\u003e(B) \u003c/strong\u003eMean Lactate-to-THCP (Lac/THCP) ratio maps.\u003cstrong\u003e \u003c/strong\u003eNote the regional metabolic impairment (reduced Bic/THCP) localized to the inferolateral territory (AHA segment 11) in the Pre-CABG cohort.\u003c/p\u003e","description":"","filename":"image5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9570351/v1/278111de520f3660afbd4770.jpg"},{"id":109205994,"identity":"e490d615-8b24-4086-ba3d-98ba6a63049f","added_by":"auto","created_at":"2026-05-13 15:10:17","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":499670,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCirculating Metabolic Substrates Before and After CABG. \u003c/strong\u003e(A–D) Serum levels for (A) Insulin, (B) Triglycerides, (C) Pyruvic Acid, and (D) Nonesterified Fatty Acids (NEFA) across Healthy controls and CAD patients (Pre- and Post-CABG). The yellow shaded region in each plot indicates the established normal reference range for the respective substrate.\u003cstrong\u003e \u003c/strong\u003e(E) Distribution of patient medications within the CAD cohort, comparing the number of patients on specific therapies before (dark red) and after (light red) CABG.\u003c/p\u003e","description":"","filename":"image6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9570351/v1/9a2fe5f56745aa0590ff3b38.jpg"},{"id":109207999,"identity":"7533b52b-0d99-4d62-b1bf-f5197910f083","added_by":"auto","created_at":"2026-05-13 15:22:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4997213,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9570351/v1/a3c94452-4bd7-4f43-9d5d-02bb963d1ac3.pdf"},{"id":109205367,"identity":"74dc9e21-667a-475d-8d4f-ba75e0eeaeca","added_by":"auto","created_at":"2026-05-13 15:04:26","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2645219,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSUPPLEMENTARY MATERIALS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe supplementary materials PDF file include:\u003c/p\u003e\n\u003cp\u003eSupplementary Table 1. Baseline Laboratory Parameters\u003c/p\u003e\n\u003cp\u003eSupplementary Table 2. Clinical Course of the CAD patients\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 1. Study Workflow and Quality Control Process\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 2. Metabolism and HP-13CMRAnalyst Software Interface\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 3. Reproducibility Assessment\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 4. Pyruvate metabolism in Healthy vs Pre-CABG subjects\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 5. Lactate/THCP Ratio Maps in Healthy vs Pre-CABG subjects\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 6. Lactate/THCP Ratio Maps in Pre-CABG vs Post-CABG\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 7. Anatomical Overlay of Metabolite Maps in Healthy vs Pre-CABG\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 8. Apparent \u003cem\u003ekPB\u003c/em\u003e Rate Constant Maps\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 9. Apparent \u003cem\u003ekPL\u003c/em\u003e Rate Constant Maps\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 10. \u003cem\u003ekPL\u003c/em\u003e Rate Constant Polar Maps\u003c/p\u003e\n\u003cp\u003eSupplementary Materials and Methods. Enrollment Criteria, Postoperative Metabolic Changes and Clinical Course of CAD subjects, Detailed Kinetic Analysis Protocol\u003c/p\u003e","description":"","filename":"NatureCVRManuscriptSupplementaryMaterialFinal04282026.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9570351/v1/74b15f919e36f6728ec87842.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Myocardial Pyruvate Metabolism Before and After CABG in Three-Vessel Disease Using Hyperpolarized Carbon-13 MRI","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eCoronary artery bypass grafting (CABG) remains the standard of care for patients with severe multivessel coronary artery disease (CAD), particularly those with left main or three-vessel involvement accompanied by reduced left ventricular function\u003csup\u003e1,2\u003c/sup\u003e.\u0026nbsp;The success of surgical revascularization depends critically on the presence of viable myocardium capable of functional recovery following restoration of blood flow\u0026nbsp;\u003csup\u003e3,4\u003c/sup\u003e.\u0026nbsp;Current methods for assessing ischemic burden or myocardial viability include dobutamine echocardiography, myocardial perfusion imaging, delayed enhancement cardiac magnetic resonance imaging (MRI), and \u003csup\u003e18\u003c/sup\u003eF-fluorodeoxyglucose positron emission tomography, which evaluates glucose metabolic activity\u003csup\u003e3,5-8\u003c/sup\u003e. Although these modalities provide complementary information, they assess metabolic status indirectly or require ionizing radiation which limits serial studies.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHyperpolarized \u003csup\u003e13\u003c/sup\u003eC MRI is an emerging noninvasive method that provides unprecedented real-time metabolic insight into mitochondrial function in human patients, entirely free of ionizing radiation.\u003csup\u003e9-12\u003c/sup\u003e Intravenous injection of hyperpolarized [1-\u003csup\u003e13\u003c/sup\u003eC]pyruvate enables real-time visualization of myocardial pyruvate metabolism, where flux through pyruvate dehydrogenase (PDH) to bicarbonate reflects mitochondrial oxidative capacity, and conversion via lactate dehydrogenase (LDH) to lactate, indicates redox state and overall carbohydrate metabolism.\u003csup\u003e13,14\u003c/sup\u003e In ischemic myocardium, reduced oxygen delivery impairs mitochondrial oxidative phosphorylation, diminishing fatty acid oxidation and PDH-mediated pyruvate oxidation while increasing reliance on anaerobic glycolysis. These metabolic shifts may precede structural changes detectable by conventional imaging. Detecting PDH flux, a unique feature of mitochondrial function, may better identify patients likely to benefit from revascularization. The ability to assess apparent PDH activity using HP [1-\u003csup\u003e13\u003c/sup\u003eC]pyruvate MRI therefore offers a unique window into myocardial metabolic status that may inform ischemia and viability assessment and improve therapeutic decision-making.\u003c/p\u003e\n\u003cp\u003eThe objectives of this study were threefold: to characterize myocardial pyruvate metabolism using HP [1-\u003csup\u003e13\u003c/sup\u003eC]pyruvate MRI in patients with three-vessel coronary artery disease compared with healthy controls; to evaluate regional metabolic alterations corresponding to coronary artery territories; and to assess metabolic changes following coronary artery bypass grafting. The findings establish feasibility for this metabolic imaging approach in the longitudinal evaluation of patients undergoing surgical revascularization and provide preliminary evidence for its potential role in assessing myocardial metabolism in real-time to guide management of ischemic heart disease.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cstrong\u003eStudy Population Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBaseline characteristics of the study population are presented in Table 1. Healthy controls (n=9) were younger (36 ± 4 versus 64 ± 12 years, p\u0026lt;0.001), more likely female (66.7% versus 0%), and had lower body mass index (24.2 ± 1.0 versus 29.1 ± 1.2 kg/m², p\u0026lt;0.01) compared with CAD patients (n=5). By design, healthy controls had no cardiovascular comorbidities, whereas CAD patients demonstrated a high burden of traditional cardiovascular risk factors including hypertension (80%), hyperlipidemia (60%), former tobacco use (60%), and diabetes or prediabetes (40%). Two patients (40%) had obstructive sleep apnea and two (40%) had a history of malignancy. All CAD patients had angiographically confirmed three-vessel coronary artery disease with significant stenoses requiring elective surgical revascularization (Supplementary Table 2 and Supplementary Methods). Pre-CABG imaging was performed 14 ± 9 days before surgery, and post-CABG imaging occurred 120 ± 23 days following the procedure.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eSafety and Feasibility of Hyperpolarized \u003csup\u003e13\u003c/sup\u003eC MRI\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eAll 22 hyperpolarized [1-¹³C]pyruvate injections (10 healthy + 6 pre-CABG + 6 post-CABG) were completed without serious adverse events. No subjects experienced clinically significant hemodynamic perturbations, arrhythmias, allergic reactions, or injection site reactions during the study or during the 2-hour follow up. Side effects were limited to mild lip flushing or a metallic taste immediately following injection, resolving within seconds. One healthy volunteer (H7) and one CAD patient (Pre-CABG5) were excluded from analysis due to technical failures, yielding a per-protocol technical success rate of 87.5% (14/16 acquisitions). Quality control parameters for all successful acquisitions were within predefined acceptable ranges (Figure 2B), including temperature (28.0 ± 2.6°C), pH (7.75 ± 0.19), pyruvate concentration (245 ± 11 mM), polarization signal (4500 ± 1483 a.u.), time from dissolution to injection (48 ± 8 seconds), and residual radical concentration (1.61 ± 1.60 μM, all within optimal range). In selected subjects, a second HP [1-\u003csup\u003e13\u003c/sup\u003eC]pyruvate injection was performed at a different imaging axis (long-axis versus short-axis) within the same session.\u0026nbsp;Corresponding short-axis and long-axis metabolite maps confirmed consistent spatial localization of pyruvate, bicarbonate, and lactate signals across the 17-segment model (Supplementary Figure 3).\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eRegional Metabolic Assessment: Healthy Controls Versus Pre-CABG\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eRepresentative dynamic image series from a healthy volunteer (Figure 2C, upper rows) and a pre-CABG patient (Figure 2E) capture the metabolic bolus transit and its characteristic differences between normal and ischemic myocardium. Extended temporal resolution of this transit is detailed in Supplementary Figure 4. The high-signal pyruvate bolus is first visualized in the left ventricular cavity (reflecting the 25-second delay in data acquisition after injection), while signal appearance in the right ventricular cavity is observed subsequently during recirculation. Representative normalized dynamic curves demonstrate robust oxidative metabolic activity in a healthy volunteer (Figure 2D), characterized by a dominant bicarbonate peak (AUC\u003csub\u003eBic\u003c/sub\u003e= 13.54 a.u.). Conversely, the pre-CABG patient (Figure 2F) exhibits suppressed bicarbonate production (AUC\u003csub\u003eBic\u003c/sub\u003e = 5.93 a.u.) and a flattened, delayed metabolic conversion profile compared to the sharp, early peak observed in the healthy control (Figure 2D), despite an identical injection protocol. Representative Bic/THCP ratio maps for each individual subject are shown in Figure 3A-B.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn healthy controls, Bic/THCP ratios were relatively uniform across all six mid-ventricular myocardial segments (mean of all signal from the LV myocardium, 0.66 ± 0.13; Figure 5A), indicating homogeneous PDH-mediated metabolic activity. In contrast, pre-CABG patients demonstrated marked regional metabolic heterogeneity with reduced Bic/THCP ratios (mean global ratio 0.51 ± 0.18; Figure 5A), most notably in the inferolateral territories (p=0.03). Although all patients had 3-vessel CAD, this cohort had a high prevalence of severe circumflex and right CAD (Supplementary Table 2). Segment-by-segment comparison revealed significantly reduced bicarbonate production in the inferolateral segment (AHA segment 11) of pre-CABG patients compared with healthy controls (p=0.03; Figure 3H), corresponding to the circumflex or right coronary artery territory. Representative angiographic images (Figure 3C) illustrate the lesion distribution in one patient. Other segments showed non-significant trends toward reduced Bic/THCP ratios in the pre-CABG group, including the inferior segment (p=0.06; Figure 3G). Because Bic/THCP and Lac/THCP sum to 1 by definition, reduced Bic/THCP necessarily corresponds to elevated Lac/THCP at both the global and voxel level. The spatial distribution of Lac/THCP across individual voxels (Supplementary Figure 5) provides a complementary view of regional metabolic heterogeneity, with higher values in territories corresponding to stenotic vessels. As expected from the Bic/THCP results, the inferolateral segment (segment 11) showed significantly elevated Lac/THCP in pre-CABG patients versus healthy controls (p=0.03; Supplementary Figure 5G). Anatomical overlay of individual metabolite maps onto proton images confirmed accurate cardiac localization of the hyperpolarized ¹³C signal and illustrated the regional differences in bicarbonate distribution between healthy and ischemic myocardium (Supplementary Figure 7). Mid-ventricular polar maps (Figure 5A and 5B) summarize the AHA 17-segment distribution of Bic/THCP ratios and Lac/THCP ratios across all three groups. These maps highlight the regional metabolic impairment concentrated in the inferolateral and inferior segments of pre-CABG patients, contrasting with the relatively uniform metabolic pattern observed in healthy controls.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eVentricular Function\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003ePre-CABG patients exhibited localized regional metabolic impairments against a background of otherwise intact global oxidative activity, as shown in Figure 3A-3I. Across the combined cohort of healthy controls and pre-CABG patients, mean global Bic/THCP ratio correlated significantly with left ventricular ejection fraction (Spearman r=0.695, p=0.006; Figure 3L), demonstrating that impaired PDH-mediated pyruvate oxidation is significantly associated with reduced systolic function. Functional assessment confirmed that left ventricular ejection fraction (LVEF) was significantly lower in pre-CABG patients compared with healthy controls (43.0 ± 10.5% versus 60.2 ± 7.8%; p=0.02; Figure 3K). Pre-CABG patients demonstrated reduced systolic function with wall motion abnormalities, consistent with their underlying three-vessel disease. All patients were clinically stable and on guideline-directed medical therapy at the time of imaging. Heart rate did not differ significantly between groups (p=0.55; Figure 3J), nor did left ventricular stroke volume (p=1.00; Figure 3M) or cardiac output (p=1.00; Figure 3N). Right ventricular ejection fraction (p=0.61; Figure 3O) and right ventricular cardiac output (p=0.80; Figure 3P) were also comparable between groups. Following CABG, there was no difference in ejection fraction compared with pre-CABG values (43.0 ± 10.5% pre-CABG versus 44.8 ± 10.2% post-CABG; p=0.44; Figure 4J), Other hemodynamic parameters including heart rate, stroke volume, and cardiac output remained stable following surgery (Figure 4I, 4L-O).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eMetabolic Changes Following CABG\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePaired pre-CABG and post-CABG Bic/THCP ratio maps for all five patients are presented in Figure 4A–B. Visual inspection of individual patient maps revealed heterogeneous responses to surgical revascularization. Notably, Post-CABG3 demonstrated a marked decrease in Bic/THCP ratios compared with Pre-CABG3, while Post-CABG6 showed improvement relative to Pre-CABG6, illustrating the inter-patient variability inherent to this small cohort. In aggregate, the mean global Bic/THCP ratio did not change significantly following CABG (pre-CABG: 0.51 ± 0.18 versus post-CABG: 0.42 ± 0.34; mean δ: −0.09 ± 0.27; Figure 5A). Regional quantitative comparisons demonstrated no statistically significant changes in any individual segment (Figure 4C–H), including the inferolateral segment (p=1.00; Figure 4G). However, Bic/THCP ratios (Figure 5A) revealed trends toward improvement in specific segments, with mean normalized ratios increasing from 0.49 ± 0.18 (pre-CABG) to 0.57 ± 0.32 (post-CABG; mean δ: +0.09 ± 0.27).\u003c/p\u003e\n\u003cp\u003eCorresponding Lac/THCP ratio maps in CAD patients showed reciprocal trends to the Bic/THCP ratio, with heterogeneous responses in lactate production observed in previously ischemic territories following revascularization (Supplementary Figure 6). \u0026nbsp; While this study was not primarily designed to determine kinetic rate constants, we explored the feasibility of mapping apparent kinetic rate constants with spatial distributions mapping the conversion of pyruvate conversion (Supplementary Figures 8-10). Spatial distributions of \u003cem\u003ek\u003csub\u003ePB\u003c/sub\u003e\u003c/em\u003e (pyruvate-to-bicarbonate; Supplementary Figure 8) revealed heterogeneous post-CABG changes, while \u003cem\u003ek\u003csub\u003ePL\u003c/sub\u003e\u0026nbsp;\u003c/em\u003e(pyruvate-to-lactate; Supplementary Figure 9) remained relatively stable following revascularization, suggesting that metabolic recovery, where present, primarily involves restoration of oxidative capacity rather than cytosolic redox state. Corresponding polar maps are shown in Supplementary Figure 10. A trend toward a positive correlation between mean global Bic/THCP ratio and LV ejection fraction was observed in the pre- and post-CABG cohort (Spearman r = 0.575, p = 0.082; Figure 4K), consistent with the strong relationship observed in the combined healthy and pre-CABG analysis, though it did not reach statistical significance in this smaller paired group.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eCirculating Metabolic Substrates\u0026nbsp;\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eResults from serum metabolite analysis are shown in Figures 6A–D. As anticipated, triglyceride levels were significantly elevated in pre-CABG patients compared with healthy controls (p=0.011; Figure 6B). Serum pyruvate, prior to the HP exam, was increased following CABG, perhaps indicating diet or medications changes (p=0.002; Figure 6C). Insulin levels showed a non-significant trend toward reduction following CABG (Figure 6A), while non-esterified fatty acid levels remained stable across all groups (Figure 6D). Medication changes following CABG were documented (Figure 6E). All five CAD patients received lipid-lowering agents and antiplatelet therapy at both time-points. Diuretic use increased from one to five patients post-CABG, likely due to post-operative fluid management protocols, while SGLT2 inhibitors were initiated in two patients. Calcium channel blocker use decreased from four to two patients, and nitrate use decreased from four to one patient following revascularization.\u0026nbsp;\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis is the first report of imaging the products of HP [1-\u003csup\u003e13\u003c/sup\u003eC]pyruvate in patients with documented three-vessel coronary artery disease before and after surgical revascularization. This study demonstrates the feasibility and safety of HP [1-\u003csup\u003e13\u003c/sup\u003eC]pyruvate MRI for serial evaluation of mitochondrial function in the heart of patients with severe coronary artery disease and abnormal ventricular function. The principal findings include: high Bic/THCP in healthy myocardium, a correlation between global metabolic activity and ventricular function across all subjects, and a variable metabolic response following CABG. \u0026nbsp;In selected subjects there were regional reductions in PDH-mediated bicarbonate production in territories corresponding to severe coronary stenoses. These observations establish a foundation for larger studies examining the role of \u003csup\u003e13\u003c/sup\u003eC metabolic imaging in assessment of patients with ischemic heart disease.\u003c/p\u003e\n\u003cp\u003eEarlier spectroscopy studies of pyruvate metabolism in human myocardium found that only a small fraction of the injected pyruvate was oxidized in mitochondria and the majority was reduced to lactate. Bic/THCP ranged from 0.07 to 0.23 in healthy subjects or in otherwise-healthy women prior to therapy for breast cancer\u003csup\u003e10\u003c/sup\u003e \u003csup\u003e15\u003c/sup\u003e. The current finding that Bic/THCP was much higher (0.66 in healthy myocardium and 0.51 even in patients with severe coronary artery disease), indicates that in stable subjects the majority of injected pyruvate undergoes oxidative metabolism. This difference between current results and earlier reports is due to acquisition of HP[1-\u003csup\u003e13\u003c/sup\u003eC]lactate signal from the blood pool in the right and left ventricular cavities in spectroscopy studies, thus reducing the ratio Bic/(Bic+Lac). The current results demonstrate that \u003csup\u003e13\u003c/sup\u003eC imaging is essential for exams in patients. Under conditions of persistent oxygen limitation, the myocardium becomes more reduced, leading to inactivation of the PDH complex and impaired decarboxylation of pyruvate. Metabolism of pyruvate and other carbohydrates shifts to lactate production because of the high NADH/NAD\u003csup\u003e+\u003c/sup\u003e in ischemic muscle. \u0026nbsp; Overall glucose metabolism shifts to anaerobic glycolysis. \u0026nbsp;In the current study, all patients had angiographically significant three vessel CAD and all subjects were clinically stable at the time of the exam without complaints of angina and presumably without ischemia. However, in this population, the reduction in bicarbonate production observed in the inferolateral segment (AHA segment 11, p=0.03) correlated with the angiographic severity of individual stenoses in the right coronary artery or the circumflex system, perhaps indicating subclinical ischemia.\u003c/p\u003e\n\u003cp\u003eWhen all subjects, healthy and pre-CABG patients were grouped, there was a correlation (r=0.695, p=0.006) between PDH-mediated oxidative capacity (Bic/THCP ratio) and LVEF. As suggested, this effect could be due to subclinical ischemia. However, PDH flux is very sensitive to competing substrates. \u0026nbsp;Increased oxidation of long-chain fatty acids or ketones may substantially suppress PDH flux even in normal myocardium\u003csup\u003e13,14\u003c/sup\u003e, and it is conceivable that some drug therapies such as beta adrenergic blockers may impact PDH flux. The possibility that systemic changes in oxidizable substrate concentrations must be considered is supported by the findings of small differences in the concentrations of triglycerides, fatty acids and other substrates in subsets. \u0026nbsp;Thus, although the current results are consistent with an effect of severe CAD on both left ventricular function and pyruvate oxidation, further work on the effects of competing substrates and drug effects is essential to determine if reduced pyruvate oxidation indicates subclinical and perhaps reversible ischemia.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe metabolic response to surgical revascularization observed in this study was heterogeneous across patients and segments. While the normalized Bic/THCP ratio showed a numerical increase from 0.49 ± 0.18 to 0.57 ± 0.32 (δ: +0.09 ± 0.27; Figure 5B), the unnormalized global ratio exhibited a slight decrease (0.51 ± 0.18 to 0.42 ± 0.34; δ: −0.09 ± 0.27; Figure 5A), and individual segment comparisons did not reach statistical significance (Figure 4C–H). This discordance likely reflects the substantial inter-patient variability inherent to a five-patient cohort, where individual outliers (such as Post-CABG3, who demonstrated markedly reduced metabolic activity) can disproportionately influence group-level statistics. The wide standard deviations observed in δ values across all segments (Figure 5A–B and Supplementary Figure 10) underscore this challenge. Despite the absence of statistically significant paired changes, the direction of metabolic recovery in several individual patients aligns with the expected physiological response to restored coronary blood flow, namely improved oxygen delivery and reactivation of mitochondrial oxidative phosphorylation. Serial perfusion-metabolism studies using PET have demonstrated that recovery of glucose metabolism may precede or parallel functional improvement following revascularization\u003csup\u003e16\u003c/sup\u003e, and the 120-day post-CABG time point in the present study may capture a period of ongoing metabolic remodeling where resting oxidative metabolic activity has not yet fully normalized.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCurrent clinical practice for myocardial viability assessment relies primarily on delayed enhancement cardiac MRI and \u003csup\u003e18\u003c/sup\u003eF-FDG PET\u003csup\u003e6\u003c/sup\u003e. Delayed enhancement imaging identifies irreversible scar based on gadolinium kinetics but cannot directly assess metabolic activity in non-enhanced segments.\u0026nbsp;Monitoring carbohydrate metabolism using [\u003csup\u003e18\u003c/sup\u003eF]fluoro-deoxyglucose is thought to be the most sensitive method for identifying heart muscle that will recover after revascularization\u003csup\u003e6,17\u003c/sup\u003e. However, a clear benefit for FDG PET-assisted care was not demonstrated in one study\u003csup\u003e18\u003c/sup\u003e, suggesting that alternative methods may provide additional information.\u0026nbsp; \u0026nbsp;Surprisingly, the impact of bypass surgery on myocardial carbohydrate metabolism has not been extensively evaluated. \u0026nbsp;Glucose metabolism may be reduced by CABG, consistent with results in some of the current patients\u0026nbsp;\u003csup\u003e19,20\u003c/sup\u003e. Hyperpolarized [1-\u003csup\u003e13\u003c/sup\u003eC]pyruvate MRI offers several potential advantages for myocardial metabolic assessment. The technique directly visualizes metabolic conversion rather than static tracer accumulation, providing mechanistic information about PDH activity that underlies cellular energy production. The absence of ionizing radiation permits serial imaging to monitor therapeutic response. Furthermore, integration with anatomical proton MRI within a single examination enables comprehensive characterization of structure, function, and metabolism.\u0026nbsp; Future studies directly comparing HP [1-\u003csup\u003e13\u003c/sup\u003eC]pyruvate MRI with established stress test and viability methods are warranted to define the incremental value of metabolic imaging.\u003c/p\u003e\n\u003cp\u003eThe small sample size limits statistical power and precludes definitive conclusions regarding metabolic differences and treatment effects. The substantial age and sex differences between healthy controls and CAD patients represent potential confounders. Although patients were clinically stable at the time of the study, there was no independent assessment of possible ischemia at the time of the exam. Further, the hemodynamic significance of each lesion was not assessed by invasive methods, so even moderately significant stenosis could have been associated with downstream ischemia. \u0026nbsp;The lack of direct comparison with established viability methods (\u003csup\u003e18\u003c/sup\u003eF-FDG PET, delayed enhancement MRI) prevents assessment of incremental diagnostic value.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe findings of this study have several potential clinical implications that warrant validation in appropriately powered cohorts. First, pre-operative metabolic imaging with HP [1-¹³C]pyruvate MRI may inform patient selection for surgical revascularization by identifying ischemic myocardium. The significant correlation between Bic/THCP ratio and LVEF observed in this study (r=0.695, p=0.006) suggests that metabolic imaging provides complementary prognostic information that could enhance existing decision-making frameworks in low ejection fraction patients. Second, serial metabolic imaging may enable non-invasive monitoring of therapeutic response, not only to revascularization but also to emerging metabolic modulators \u003csup\u003e21-23\u003c/sup\u003e. \u0026nbsp;Third, integration of metabolic imaging with first-pass perfusion assessment within a single MRI examination may enable characterization of perfusion-metabolism mismatch analogous to PET-based approaches, potentially identifying hibernating myocardium with greater specificity and without the logistical burden of coordinating two separate imaging modalities. Finally, the current study demonstrated the feasibility of collecting kinetic rate constant data from all myocardial segments. Such data have been used in earlier studies to calculate the apparent rate constants for pyruvate conversion to bicarbonate or lactate. The current pulse sequence with a delay of 25 seconds prior to data acquisition is not suitable for the earlier mathematical models, but it would be a simple matter to collect appropriate data. Development of alternative hyperpolarized substrates, such as [2-\u003csup\u003e13\u003c/sup\u003eC]pyruvate for Krebs cycle assessment or [\u003csup\u003e13\u003c/sup\u003eC]acetoacetate for ketone bodies may provide additional metabolic dimensions relevant to ischemic heart disease \u003csup\u003e24,25\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThis study demonstrates the feasibility and safety of HP [1-\u003csup\u003e13\u003c/sup\u003eC]pyruvate MRI for assessing myocardial pyruvate metabolism in patients with three-vessel coronary artery disease before and after CABG. Regional metabolic impairment corresponding to coronary territories and significant correlations with ventricular function support the potential of this technique as a non-invasive metabolic biomarker. These findings establish a foundation for larger validation studies examining the role of metabolic imaging in myocardial viability assessment and therapeutic monitoring.\u003c/p\u003e"},{"header":"METHODS","content":"\u003ch2\u003e\u003cstrong\u003eStudy Design and Population\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThis prospective, single-center study enrolled participants between June 2023 and July 2025 at UT Southwestern Medical Center (Figure 1). The study protocol was approved by the institutional review board (IRB No. STU-2020-0953, investigational new drug application no. 133229, NCT06047028), and all participants provided written informed consent. The study population comprised two cohorts: healthy volunteers without cardiovascular disease or risk factors, and patients with angiographically confirmed three-vessel coronary artery disease scheduled for elective CABG.\u003c/p\u003e\n\u003cp\u003eThe detailed enrollment criteria are available in Supplementary Methods. Briefly, the inclusion criteria for healthy volunteers included age 18-80 years, absence of cardiovascular disease or major cardiovascular risk factors (hypertension, diabetes mellitus, hyperlipidemia, tobacco use), body mass index less than 30 kg/m\u003csup\u003e2\u003c/sup\u003e, and no contraindications to MRI. Inclusion criteria for the CAD cohort included age 18 years or older, angiographically documented three-vessel CAD with planned CABG, and clinical stability allowing pre-operative imaging. Exclusion criteria for both groups included estimated glomerular filtration rate less than 60 mL/min/1.73m\u003csup\u003e2\u003c/sup\u003e, contraindications to MRI, pregnancy or lactation, and inability to provide informed consent. Of 16 enrolled subjects, 10 were healthy volunteers and 6 were CAD patients. One healthy volunteer and one CAD patient were excluded due to technical acquisition failures, yielding final cohorts of 9 healthy controls and 5 CAD patients for analysis. CAD patients underwent imaging at two time points: pre-CABG (14 ± 9 days before surgery) and post-CABG (120 ± 23 days after surgery).\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eHyperpolarized [1-\u003csup\u003e13\u003c/sup\u003eC]Pyruvate Preparation and Quality Control\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eClinical-grade [1-\u003csup\u003e13\u003c/sup\u003eC]pyruvic acid (Isotec, Sigma-Aldrich) was polarized using a SPINlab clinical polarizer (GE Healthcare, Waukesha, WI, USA) according to previously validated protocols\u003csup\u003e26,27\u003c/sup\u003e. Briefly, 1.47 g of neat pyruvic acid containing 15 mM trityl radical (AH111501, GE Healthcare) and 1 mM gadolinium chelate was placed in the polarization chamber and subjected to microwave irradiation at 3.35 T and 0.85 K. Following polarization (3.70 ± 0.62 hours), the sample was rapidly dissolved in superheated sterile water and neutralized to physiological pH. Rigorous quality control parameters were verified before injection, consistent with investigational new drug requirements (Supplementary Figure 1). Quality control metrics included: temperature, pH, pyruvate concentration, signal from SPINlab, time from dissolution to injection, and residual radical concentration. Injections were administered as a 0.4 mL/kg bolus (0.1 mmol/kg) over 20 seconds into an antecubital vein, followed by a 25 mL saline flush (Figure 2).\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eMRI Protocol\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eAll imaging was performed on a 3T clinical MRI scanner (750w Discovery, GE Healthcare, Waukesha, WI) equipped with a custom-built two-loop \u003csup\u003e13\u003c/sup\u003eC Helmholtz surface coil (PulseTeq Limited; Chobham, Surrey, UK) for \u003csup\u003e13\u003c/sup\u003eC imaging and the body coil for \u003csup\u003e1\u003c/sup\u003eH localization. Subjects underwent a standardized glucose load (48 g oral glucose) approximately 30 minutes before imaging to stimulate insulin secretion and enhance myocardial glucose uptake and PDH activity. Following glucose loading, subjects were positioned in the scanner for anatomical reference imaging. Proton imaging included: balanced steady-state free precession cine imaging in standard cardiac views (short-axis stack, 2-chamber, 3-chamber, 4-chamber and long-axis stack) for volumetric analysis. The protocol used a field of view of 400 × 400 mm² with a spatial resolution of 2.08 × 2.08 mm² and slice thickness of 8 mm. Key sequence parameters included a flip angle of 50°, echo time (TE) of 1.2 ms, repetition time (TR) of 3.4 ms, and acquisition of 30 cardiac phases. Following completion of proton imaging, HP [1-\u003csup\u003e13\u003c/sup\u003eC]pyruvate was injected, and \u003csup\u003e13\u003c/sup\u003eC imaging commenced ~ 25 seconds post-injection to target the left ventricular bolus arrival.\u003c/p\u003e\n\u003cp\u003eHyperpolarized \u003csup\u003e13\u003c/sup\u003eC imaging employed a slice-selective spectral-spatial excitation pulse with metabolite-specific flip angles (pyruvate 10°, lactate 90°, bicarbonate 90°) to optimize signal while preserving hyperpolarization. Dynamic acquisition parameters included: field of view (FOV): 400 × 400 mm², matrix 40 x 40, data acquisition every R-R interval at end-diastole, in-plane resolution 10 mm x 10 mm, slice thickness 30 mm, and temporal resolution of 1 cardiac cycle over 60 seconds of acquisition. Electrocardiographic gating was employed to minimize cardiac motion artifacts. All subjects received at least one HP [1-\u003csup\u003e13\u003c/sup\u003eC]pyruvate injection for short-axis (SAX) cardiac imaging, with select subjects receiving an additional HP [1-\u003csup\u003e13\u003c/sup\u003eC]pyruvate injection for long-axis (LAX) imaging within the same session. All procedures for hyperpolarized pyruvate production and injection, \u003csup\u003e1\u003c/sup\u003eH MRI acquisition, \u003csup\u003e13\u003c/sup\u003eC MRI acquisition, and subject monitoring were conducted in accordance with previously published studies and consensus statement\u003csup\u003e26-28\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImage Analysis and Metabolic Quantification\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eProton cine images were analyzed using commercial software (QMass, Medis Medical Imaging Systems) for quantification of left ventricular volumes, ejection fraction, and wall motion. Hyperpolarized \u003csup\u003e13\u003c/sup\u003eC data were processed using MATLAB (R2025b; MathWorks, Natick, MA) based \u003cem\u003eHP-\u003csup\u003e13\u003c/sup\u003eCMRAnalyst\u003c/em\u003e (custom software; Supplementary Figure 2) incorporating established methodologies\u003csup\u003e29\u003c/sup\u003e. Segmental analysis followed the American Heart Association 17-segment model \u003csup\u003e30\u003c/sup\u003e. Data were analyzed in segments 7 to 12. \u0026nbsp;Metabolic ratios were calculated for each myocardial segment. Total hyperpolarized carbon-13 product (THCP) was defined as the sum of hyperpolarized [1-\u003csup\u003e13\u003c/sup\u003eC]lactate and [\u003csup\u003e13\u003c/sup\u003eC]bicarbonate signals. Primary metabolic metrics included: bicarbonate-to-THCP ratio (Bic/THCP), reflecting PDH-mediated pyruvate-to-bicarbonate conversion; lactate-to-THCP ratio (Lac/THCP), reflecting lactate dehydrogenase activity; and total metabolic activity (sum of bicarbonate and lactate signals within the myocardium). While these experiments were not designed to calculate kinetic rate constants, apparent kinetic rate constants were estimated using a simplified two-site exchange model \u003csup\u003e31,32\u003c/sup\u003e. This approach eliminates the need for arterial input function modeling by using the measured pyruvate signal directly as the driving function. Model fitting was performed on a voxel-wise basis using nonlinear least-squares optimization, with constraints applied to ensure physiologically plausible solutions. Additional methodological details, assumptions, and validation analyses are provided in the Supplementary Material.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eLaboratory Assessments\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eFasting blood samples were obtained before each imaging session for metabolic substrate analysis. Measurements included serum glucose, insulin, triglycerides, non-esterified fatty acids (NEFA), and pyruvic acid. Comprehensive metabolic panels and complete blood counts were performed to ensure eligibility and safety (Supplementary Table 1).\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eContinuous variables are presented as mean ± standard deviation or median (interquartile range) as appropriate. Categorical variables are presented as counts and percentages. Comparisons between healthy controls and pre-CABG patients employed the Mann-Whitney U test for continuous variables and Fisher exact test for categorical variables, given the small sample sizes. Paired comparisons between pre-CABG and post-CABG measurements used the Wilcoxon signed-rank test. Correlations between metabolic parameters and ventricular function were assessed using Spearman rank correlation. Regional metabolic differences across coronary territories were evaluated using analysis of variance with post-hoc Tukey correction. A two-sided p-value≤0.05 was considered statistically significant. Given the exploratory nature of this study, analyses were focused on effect size estimation and physiological plausibility. No formal correction for multiple comparisons was applied to avoid Type II errors in this pilot cohort; results should be interpreted as hypothesis-generating. Statistical analyses were performed using R Statistical Software (v4.5.2; R Core Team, 2025) and GraphPad Prism (v10, GraphPad Software).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the research nursing staff and MRI technologists at the Advanced Imaging Research Center and Clinical Trials Office at Cardiovascular and Thoracic Surgery for their expert assistance with study conduct. The authors also thank the patients and healthy volunteers who participated in this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eETHICS STATEMENT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the Declaration of Helsinki. The protocol was approved by the Institutional Review Board of UT Southwestern Medical Center (IRB No. STU-2020-0953) under IND No. 133229. The study is registered at ClinicalTrials.gov (NCT06047028). All participants provided written informed consent prior to enrollment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDATA AVAILABILITY\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDe-identified individual participant data and the custom MATLAB-based analysis software (HP-\u003csup\u003e13\u003c/sup\u003eCMRAnalyst) are available from the corresponding authors upon reasonable request, subject to institutional data sharing agreements and applicable privacy regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAUTHOR CONTRIBUTIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthor Contributions G.S., C.R.M. and M.E.J. conceived and designed the study. G.S., S.H.L., J.M.P., C.E.H., J.L., S.S.M., and C.R.M. performed experiments and acquired data. G.S. and J.M.J. analyzed the data. G.S., C.R.M., M.P., and M.E.J. interpreted the results. G.S. drafted the manuscript with input from all authors. All authors critically revised the manuscript for important intellectual content and approved the final version submitted for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFUNDING STATEMENT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the American Heart Association (23SCEFIA1154964, 24IPA1272385, 24TPA1297929) and the National Institutes of Health (S10OD018468, S10RR029119, P41EB015908, R01HL170039).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCOMPETING INTERESTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing financial or non-financial interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eVirani, S. 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L.\u003cem\u003e et al.\u003c/em\u003e Kinetic modeling of hyperpolarized 13C1-pyruvate metabolism in normal rats and TRAMP mice. \u003cem\u003eJ Magn Reson\u003c/em\u003e \u003cstrong\u003e202\u003c/strong\u003e, 85\u0026ndash;92 (2010). https://doi.org/10.1016/j.jmr.2009.10.003\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Baseline Demographics and Clinical Characteristics.\u003c/strong\u003e Comparison of demographic data, comorbidities, and anthropometric measurements between Healthy Controls (n=9) and patients with Three-Vessel Coronary Artery Disease (CAD, n=5). Values are presented as mean \u0026plusmn; standard deviation or count (percentage). BMI = body mass index; CABG = coronary artery bypass grafting; COPD = chronic obstructive pulmonary disease. * p \u0026lt; 0.05 vs CAD Patients.\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\" 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Here we show, in the first prospective study applying this technique to three-vessel disease, that serial imaging is feasible and safe with no serious adverse events in 22 injections. Healthy myocardium displayed a bicarbonate-to-total hyperpolarized carbon product ratio of 0.66 ± 0.13, indicating that the majority of pyruvate undergoes oxidation. Patients exhibited significantly lower ratios in the inferolateral segment (P = 0.03) with reciprocal increases in lactate, and global ratios correlated with left ventricular ejection fraction (r = 0.695, P = 0.006). Post-revascularization changes were heterogeneous across individuals. These findings establish hyperpolarized 13C MRI as a powerful tool for noninvasive assessment of myocardial metabolism in multivessel coronary artery disease and support its potential for longitudinal therapeutic monitoring.","manuscriptTitle":"Myocardial Pyruvate Metabolism Before and After CABG in Three-Vessel Disease Using Hyperpolarized Carbon-13 MRI","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-13 10:05:38","doi":"10.21203/rs.3.rs-9570351/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-cardiovascular-research","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"natcardiovascres","sideBox":"Learn more about [Nature Cardiovascular Research](https://www.nature.com/natcardiovascres/)","snPcode":"","submissionUrl":"https://mts-natcardiovascres.nature.com/cgi-bin/main.plex","title":"Nature Cardiovascular Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Research","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"ce16e475-8bd9-4b2c-9310-6d843c8962b5","owner":[],"postedDate":"May 13th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewersInvited","content":"3","date":"2026-05-11T21:56:25+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-29T23:49:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"Nature Cardiovascular Research","date":"2026-04-29T23:49:23+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":67962207,"name":"Health sciences/Biomarkers/Diagnostic markers"},{"id":67962208,"name":"Health sciences/Cardiology/Cardiovascular biology/Cardiovascular diseases/Vascular diseases/Coronary artery disease and stable angina/Ischaemia"}],"tags":[],"updatedAt":"2026-05-13T10:05:41+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-13 10:05:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9570351","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9570351","identity":"rs-9570351","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}