Sage Journals: Discover world-class research

Abstract

While severe vasculopathic manifestations of systemic sclerosis (SSc) are well-recognized, characterization of subclinical progressive vasculopathy contributing to cardiac involvement remains an unmet clinical need. This review highlights the evolving understanding of SSc heart involvement (SHI), including current standard clinical cardiac evaluation methods, prevalence of various cardiac manifestations of SHI, and advances at the forefront of precision medicine. Informed by this growing body of literature, we describe the development of a novel interdisciplinary cardio-rheumatology clinic at the Vanderbilt University Medical Center. Utilizing advances in imaging techniques and systemic retrieval and analysis of complex data sets, our dedicated cardio-rheumatology clinic offers opportunities for therapeutic advances and personalized medicine through mechanistic disease phenotyping in SSc. Nailfold capillaroscopy, thermography, and hand ultrasound with Doppler are acquired to characterize small vessel vasculopathy, while echocardiogram, ambulatory cardiac rhythm monitoring, cardiac magnetic resonance imaging, and cardiac positron emission tomography/computed tomography are utilized to characterize cardiac disease. By correlating vasculopathy imaging with cardiac manifestations, our cardio-rheumatology clinic aims to identify patients with SSc who would benefit from additional cardiac investigation even in the absence of cardiac symptomatology. This interdisciplinary collaboration may allow earlier detection of primary SHI, which is a common cause of death in SSc patients, resulting from both morpho-functional and electrical cardiac abnormalities. Our shared model of care and robust data acquisition facilitate clinical investigation by utilizing technological advances in data management. Using deep learning and pattern recognition, artificial intelligence (AI) offers opportunities to integrate data from imaging and monitoring techniques outlined in this report to provide quantifiable markers of disease progression and treatment efficacy. Given the potential for extensive AI data processing but the low prevalence of SSc, developing a multicenter cloud-based image sharing platform would accelerate clinical investigation in the field. Ultimately, we aim to tailor therapeutic decisions and risk mitigation strategies to improve SSc patient outcomes.

Keywords

cardiac cardio-rheumatology imaging magnetic resonance imaging systemic sclerosis

Introduction

Precision medicine offers the promise of therapeutic advances through mechanistic disease phenotyping that allows the healthcare provider to prescribe the correct therapy with an individualized approach. Systemic sclerosis (SSc, scleroderma) is a multi-organ disease characterized by variably progressive vasculopathy with resultant fibrosis due to heterogeneous exogenous exposures and endogenous factors.¹ While severe vasculopathic manifestations such as digital ulcers, pulmonary arterial hypertension, gastric antral vascular ectasia, and scleroderma renal crisis are well-recognized, characterization of any progressive vasculopathy contributing to primary SSc heart involvement (SHI), especially in patients with overlapping skeletal myositis, is an unmet need.² Primary SHI is a common cause of death due to morpho-functional and electrical cardiac abnormalities.³

The study of rare diseases benefits from well-phenotyped subjects with linked patient-reported outcomes and biospecimens. International collaborative efforts like the Scleroderma Clinical Trials Consortium have developed outcome measures for use in clinical practice and research that capture multisystem damage and activity.^4,5 Rare disease registries, such as the Collaborative National Quality and Efficacy Registry, have standardized data collection at point-of-care visits to centers of excellence, which provide investigators with critical disease natural history and treatment data.⁶ Multidisciplinary clinics further enhance the ability for management and care advancement.⁷ Clinical programs with co-localized gastroenterologists, pulmonologists, cardiologists, and rheumatologists can address barriers to access and delivery of care in ways that traditional, dispersed outpatient clinics cannot.⁸

Advances in imaging techniques and the systematic retrieval, collection, management, and analysis of very large and complex sets of structured and unstructured data offer opportunities in combined subspecialty clinics to develop personalized treatment strategies for individual patients as they attend the clinic.^9
–11 The goal of developing automated clinical decision tools to facilitate objective and standardized assessment regardless of observer experience is of particular interest in cardiac and vascular imaging.¹² In this report, we discuss the design of a cardio-rheumatology clinic with the potential of incorporating vasculopathy imaging as an opportunity for precision medicine for SSc.

The cardio-rheumatology clinic: At the forefront of precision medicine

The field of cardio-rheumatology has recently emerged as a subspecialty focusing on the impact of inflammation on the cardiovascular system.¹³ It is acknowledged that substantial gaps remain in the management of cardiovascular disease and risk in patients with systemic rheumatic diseases.¹⁴ Integrated cardio-rheumatology clinics enhance collaboration between the specialties of rheumatology and cardiology, with responsibility for the management of cardiovascular health shared between rheumatologists and cardiologists. A shared model of care has been proposed as a strategy to optimize care and implement individualized management and risk management plans in an area of ongoing clinical uncertainty.^14,15

At the Vanderbilt University Medical Center, SSc patients are offered care at an integrated cardio-rheumatology clinic where a cardiologist and rheumatologist provide a same-day, coordinated assessment (Figure 1). The goal of the care visit is a comprehensive cardiovascular health assessment and education for lifestyle modification in the context of quantification of systemic vasculopathy, inflammation, and fibrosis. Our dedicated cardio-rheumatology clinic offers logistical advantages in the coordination of care, as well as an opportunity for thorough, structured data collection. In our specialty cardio-rheumatology clinic, we aim to better understand how noninvasive cardiac and vascular imaging can be used to inform the assessment of cardiac disease in SSc. Many patients with SSc remain asymptomatic while having a progressive cardiac disease process, hypothesized to be the result of chronic microvascular injury.¹⁶ Thus, establishing a correlation between vascular imaging and characterization of SSc-vasculopathy and developing cardiac disease may assist in the early detection of SHI and facilitate timely cardiology referrals and assessment in patients without symptoms or standard indications for further cardiac testing.

Figure 1.

Cardio-rheumatology clinic structure.

The clinical variables collected during the cardiology visit include the primary cardiac diagnosis and symptoms, cardiovascular risk factors, physical examination findings, laboratory studies, and electrocardiogram (ECG). Cardiac biomarkers of particular interest are B-type natriuretic peptide (BNP) and troponin, in addition to a lipid panel including lipoprotein A for risk stratification. An ECG is performed as an initial screening test for conduction system abnormalities, including arrhythmias, conduction delay, low voltage or delayed R-wave progression, or pathologic Q-waves indicating prior infarct. A transthoracic echocardiogram (TTE) is obtained for evaluation of cardiac structure and function as well as an estimate of pulmonary arterial pressure (Table 1). Cardiac testing is prescribed as clinically appropriate for each patient, and follow-up is scheduled on a case-by-case basis; for example, one patient might need shorter interval follow-up with their rheumatologist and longer follow-up with their cardiologist, or vice versa. For the success of this system, it is imperative to have a channel of open and timely communication between providers.

Table 1.

Summary of clinical variables collected during the cardiology visit.

Medical history
• Primary cardiac diagnosis
• Concomitant autoimmune disease
• Patient’s characteristics of scleroderma (if applicable)
• Cardiovascular risk factors

Physical examination findings

Laboratory studies
• In addition to standard labs, ESR, CRP, Troponin T (or Troponin I), CK, BNP (or ntBNP), Lipoprotein (a)

Imaging
• Electrocardiogram
• Echocardiogram
• Nailfold video capillaroscopy
• CMR
• PET/CT^a
• SPECT^a

Interventions
• Cardiac rhythm monitoring^a
• Endomyocardial biopsy^a

Physician outcome assessment

In select cases and when clinically indicated.

BNP, B-type natriuretic peptide; CK, Creative Kinase; CMR, cardiac magnetic resonance; CRP, C-Reactive protein; CT, computed tomography; ESR, Erythrocyte sedimentation rate; PET, positron emission tomography; SPECT, single-photon emission computed tomography.

Standardized note templates and imaging platforms that allow data extraction and de-identified data sharing are critical aspects of this combined cardio-rheumatology clinic for future multicenter and international collaboration. The development of the REDCap Clinical Data Interoperability Services module provides seamless data exchange between the REDCap research electronic data capture and the electronic health record, improving accuracy and efficiency.¹⁷ The goal is to systematically retrieve, collect, manage, and analyze sets of routinely collected clinical variables, such as vital signs, examination findings, laboratory results, ECGs, and cardiac imaging, which are components of many national and international SSc registries.⁹

Our cardio-rheumatology clinic was inaugurated in November 2024, after almost 1 year of coordination and implementation. In its initial phase, the clinic opened to referral primarily of SSc patients; with the support of a referral algorithm created by our clinical team, it is now open to patients with systemic inflammatory disease who are at an inherently high risk for cardiovascular disease or have established cardiac disease. We have evaluated approximately 35 patients with concomitant cardiac imaging, including cardiac magnetic resonance (CMR) when clinically indicated.

The coordinated clinical evaluation is tailored to the individual needs of the patient based on symptoms, cardiac risk score, or the presence of cardiac abnormalities found incidentally.

Given the rarity of SSc, it is important to establish longitudinal clinical cohorts on a multi-institutional and international level to appropriately follow patients’ clinical course.¹⁸ The ability to automatically extract data from clinical consultations provides an opportunity to enroll all consented subjects at their point of care visit, minimizing missing data and facilitating robust cardiac phenotyping of patients with SSc on a large scale. Data are needed to better understand how to integrate the information provided by the detailed assessments of cardiac structure, function, rhythm, and biomarkers of SSc vasculopathy with clinical assessments to tailor therapeutic decisions and risk mitigation strategies to improve SSc patient outcomes. A multi-center cloud-based imaging repository, paired with clinical data, can help to longitudinally quantify and standardize the assessment of SHI and inform the development of data-driven prognostic and treatment algorithms to improve patient outcomes.

Current standard cardiac evaluation

Individuals with SSc can have cardiac disease due to the direct effects of SSc itself, namely SHI, which can manifest as myocardial, pericardial, valvular, and coronary microvascular disease or abnormalities of the conduction system.¹⁸ Secondary cardiac complications can arise from other disease manifestations such as interstitial lung disease, pulmonary vascular disease or renal disease. In addition, SSc can accelerate cardiac complications of other coexisting conditions such as systemic hypertension, diabetes, sleep disorders, and obesity.¹⁹

While autopsy studies demonstrate cardiac involvement in up to 80% of SSc patients, low ejection fraction (EF) is only found in approximately 5% of patients with SSc, suggesting that traditional echocardiographic mechanisms of assessment are of lesser value in predicting the burden of SSc-related myocardial disease.¹⁸ However, TTE often remains an initial screening investigation for patients with SSc due to the ease of obtaining the study and the noninvasive nature of the test. The routine acquisition of serial TTE in SSc can identify important structural and functional cardiac abnormalities. Abnormalities of left ventricle (LV) filling pressures, which precede the onset of LV remodeling, occur at a much higher rate in patients with SSc as compared to individuals without SSc.²⁰ Accordingly, studies have shown that heart failure with preserved ejection fraction is more common in patients with SSc.²¹ Advances, such as speckle-tracking echocardiography, increase sensitivity in detecting sub-clinical cardiac involvement.¹³ Even subtle echocardiographic changes in both systolic and diastolic function in patients with SSc are of both prognostic and functional importance.^22,23

In a prospective study of 570 patients in France with SSc, LV hypertrophy was found in 22.6% of patients, while LV diastolic dysfunction was found in 17.7% of patients.²⁴ In a US-based study of patients with SSc and their age- and sex-matched controls, LV hypertrophy was more common in patients with SSc, and of the patients with SSc who underwent single-photon emission computed tomography (CT), 60% demonstrated reversible LV perfusion defects, as early as age 40.²⁵ Thus, while echocardiography may not detect early signs of myocardial dysfunction in patients with SSc, it can still detect many structural and functional changes that are more prevalent in SSc than in the general population. Real-time assessment of longitudinal, well-structured echocardiogram data is an advantage of a cardio-rheumatology clinic because it allows investigation of the prognostic implications of abnormal findings and correlation with clinical rheumatologic assessment. The appropriate balance of management of underlying autoimmune disease with the management of cardiovascular risk profile and appropriate implementation of cardioprotective therapies is facilitated by assessment in a fully integrated cardio-rheumatology clinic.¹³

Arrhythmias and palpitations are common cardiac complaints in patients with SSc. There is a higher rate of rhythm disorders observed in patients with SSc, and an over twofold increased risk of conduction system disease is observed.²⁶ Risk of sudden cardiac death in patients with SSc is thought to be 10-fold higher than in the general population.²⁷ Cardiac event monitors (CEM), Holter monitors, mobile cardiac telemetry (MCT), and loop recorders are utilized for the diagnosis of intermittent symptoms and to assess for overall arrhythmic disease burden. CEM requires patient activation, allowing for interrogation of rhythm immediately prior to and immediately after symptom onset. MCT does not require patient activation, with the device automatically activating upon detection of an arrhythmia. By contrast, Holter monitors continuously record the patient’s ECG without requiring any patient or device-mediated activation and are usually utilized for a shorter duration, such as 24–48 h. Loop recorders are subcutaneously implanted devices that allow for continuous monitoring similar to a Holter, but can be utilized for longer durations, even indefinitely. A cardiac loop recorder can provide insights into SSc-associated arrhythmia pathogenesis.²⁸ Selection of ambulatory cardiac monitoring device is highly individualized and dependent on the frequency and quality of reported symptoms, as well as patient compliance.

CMR is the gold standard noninvasive investigation for the assessment of cardiac structure and function and is an ideal modality for the early detection of indolent autoimmune disease through myocardial tissue characterization.^29,30 A high prevalence of diffuse myocardial fibrosis has been detected in SSc patients even in the absence of cardiac symptoms or abnormalities of cardiac function.^28,31 Up to half of the patients in a cross-sectional study of 19 SSc patients without overt cardiovascular disease and normal EF by TTE had identifiable late gadolinium enhancement (LGE), suggesting myocardial scar or fibrosis, as well as higher T1 and extracellular volume fraction (ECV) on CMR compared to controls, correlated with disease activity scores.³² As such, the European Association of Cardiovascular Imaging recommends a baseline CMR for any patient with SSc and suspected cardiac involvement.²⁹ However, the clinical implications of subtle cardiac abnormalities in the absence of cardiac symptoms are unclear. A prospective study of 74 SSc patients without known cardiovascular disease found no association between LGE and cardiovascular outcomes, but expanded ECV was associated with more frequent cardiovascular events and worse outcomes.³³ Another prospective study of 150 SSc patients, including both symptomatic and asymptomatic patients, found that abnormal T2 signal and burden of LGE independently predicted ventricular arrhythmias.³⁴ The role of follow-up CMR imaging is emerging, with expert opinion suggesting that repeat CMR is indicated when there are clear symptomatic changes, to evaluate the efficacy of immunomodulatory and cardioprotective treatments, or if extracardiac manifestations of SSc are unresponsive to treatment.²⁹ Some clinicians argue that CMR should be considered even more broadly when considering a change in treatment, such as the addition of biologics with possible cardiotoxicity, or when there is discordance between clinical and laboratory findings.³⁵

Recent studies have examined resting and stress myocardial perfusion and myocardial blood flow (MBF) reserve via CMR compared to quantitative myocardial perfusion obtained by positron emission tomography (PET)/CT imaging, the gold standard for noninvasive MBF quantification.^36,37 Myocardial perfusion via CMR can be assessed visually, semi-quantitatively, or quantitatively with novel post-processing software. The MBF reserve by CMR is derived from velocity-encoded flow in the coronary sinus, quantified at rest and during hyperemic vasodilation. The most recent analyses conclude that quantitative perfusion CMR correlates weakly with MBF quantification by PET/CT or invasive quantification; however, it is reliable in detecting anatomically severe coronary artery disease (CAD).³⁷ In addition, a large body of literature has demonstrated high performance of perfusion CMR for diagnostic and prognostic value in coronary microvascular dysfunction.³⁸ CMR has high utility for chamber size quantification and function, assessment of myocardial fibrosis, inflammation, edema, diagnosis, and interval evaluation of myocarditis, pericarditis, tissue viability, and quantification of scar burden, and coronary flow reserve assessment. The potential for myocardial tissue characterization is extremely valuable in studying cardiac vasculopathy, inflammation, and fibrosis (Figure 2). Quantitative myocardial perfusion PET/CT imaging provides robust cardiac evaluation, including quantitative assessments of regional myocardial perfusion, LV volumes and EF, calcified atherosclerotic burden, MBF, and myocardial flow reserve (MFR). In combination, these values are highly accurate in the diagnosis and risk stratification of patients with suspected or known CAD. PET MBF quantification can reliably identify coronary microvascular dysfunction.³⁹ Normal stress MBF and MFR have a high negative predictive value, reliably excluding high-risk CAD. Conversely, a severely reduced MFR (<1.5) identifies patients at high clinical risk for adverse events due to obstructive CAD, microvascular dysfunction, or a combination of both.⁴⁰

Figure 2.

Myocardial tissue characterization.

While 18F-fluoro-deoxy-glucose (FDG) PET/CT can assess myocarditis by detecting underlying inflammation as increased myocardial FDG uptake, CMR remains the preferred imaging modality for diagnosing myocarditis.⁴¹ FDG PET findings can enhance the diagnostic capabilities of CMR by increasing its sensitivity for detecting mild or borderline myocarditis and boosting its specificity for chronic myocarditis. In most centers, CMR and PET/CT occur in different imaging sites at different times; however, initial data from retrospective and case-based observational studies indicate that simultaneous cardiac FDG PET/MR offers complementary and additional value in the assessment of myocarditis, compared to using PET/CT or CMR alone.⁴²

Paired vasculopathy imaging and cardiac data

Advances in automated interpretation of imaging provide further opportunities for the detection of novel biomarkers. It is unclear which parameters of SSc cardiac disease should garner the most clinical attention, as no robust longitudinal studies are tracking subclinical cardiac disease and its attendant impacts on health outcomes in patients with SSc. Objective microvascular imaging tools such as musculoskeletal ultrasound, infrared thermography (IRT), and nailfold capillaroscopy have the potential to capture data correlated to self-report assessment of Raynaud’s phenomenon (RP) as well as cardiovascular manifestations.

Musculoskeletal ultrasound allows for the comprehensive evaluation of the spectrum of hand pathology in SSc. In addition to identifying abnormalities in the joint, tendons, and nerves, ultrasound can elucidate the vascular pathology that drives hand impairment, such as RP, digital ulcers, and calcinosis. Ulnar artery occlusion and finger pulp blood flow are two suggested imaging biomarkers for vasculopathy. Ulnar artery occlusion is associated with a history of fingertip ulcers, telangiectasias, and a late capillaroscopic pattern.⁴³ In addition, ulnar artery occlusion is associated with calcinosis; calcium deposition thought to be driven by ischemic insults, even in the absence of digital ulcers.⁴⁴ Severe reduction in finger pulp blood flow is associated with digital ulcers and ulnar artery occlusion in SSc patients.⁴⁴ There is an observed association between the burden of peripheral arterial disease and heart failure in SSc,⁴⁵ suggesting quantification of the burden of peripheral vasculopathy may have a role in predicting future significant SHI as part of a multi-modal assessment of heart involvement in SSc.

Clinical thermography, consisting primarily of IRT, which captures variations in surface temperature due to thermal emissions from the body, is a noninvasive and non-contact technique that is also suitable for SSc hand assessments.⁴⁶ IRT generates maps of blood flow by detecting the infrared emissions of the metabolic heat conducted by circulating blood. Detectable changes in peripheral blood perfusion are an early sequel of SSc vasculopathy, with the hands being ideal measurement sites. Clinical IRT of the hands has been demonstrated to help predict the development of digital ulcers.⁴⁷

Nailfold video capillaroscopy (NVC) is a noninvasive tool for examining the microcirculation and changes in capillaroscopic abnormalities during follow-up. NVC findings in patients with SSc include several characteristic microvascular abnormalities, collectively referred to as the “scleroderma pattern (SD-pattern).” These findings are typically categorized into three progressive stages: early, active, and late scleroderma patterns.⁴⁸ Findings include (Figure 3): (a) Giant capillaries: Enlarged capillary loops, often one of the earliest detectable abnormalities in SSc. (b) Microhemorrhages: Small areas of bleeding within the nailfold capillaries, resulting from the collapse of giant capillaries. (c) Avascular areas: Regions where capillaries are absent, indicating significant capillary loss. (d) Neo-angiogenesis: Formation of new, often irregular, and ramified capillaries, occurring in response to tissue hypoxia and capillary loss.

Figure 3.

Nailfold video capillaroscopy. (a) Giant capillaries; enlarged capillary loops that are often one of the earliest detectable abnormalities in SSc. (b) Microhemorrhages resulting from the collapse of giant capillaries. (c) Avascular areas: capillaries are absent, indicating significant capillary loss. (d) Neoangiogenesis. Formation of new capillaries in response to tissue hypoxia and capillary loss.

The severity of skin, lung, heart, and peripheral vascular involvement increases progressively from the early to the late NVC patterns. Patients with the late pattern, that is, lower capillary density and changes showing significant capillary loss, are at a significantly higher risk of having active disease, digital ulcers, and moderate to severe skin, heart, and lung involvement.^49
–51 Thus, NVC serves as a valuable tool for assessing disease severity and allows for the quantification of microvascular disease that can be correlated with other organ involvements. NVC abnormalities have been linked with impaired coronary microcirculation⁵² and SSc-associated cardiomyopathy⁵³ as well as pulmonary vascular disease.⁵⁴

Specialized imaging

SSc patients have been shown to have profound attenuation in exercise capacity.⁵⁵ Though frequently linked to cardiopulmonary abnormalities,⁵⁶ exercise capacity is often impaired in SSc patients without central hemodynamic impairments,^57,58 and in small muscle mass exercise, a paradigm which is not cardiopulmonary limited.⁵⁹ These findings indicate local blood flow and inherent alterations in muscle metabolism and function are likely to play an important role in exercise intolerance in this patient group. Several novel methodologies may provide critical insight into these essential questions, facilitating targeted therapies for patients with SSc.

Magnetic resonance spectroscopy (MRS) is a powerful, noninvasive technique for measuring muscle metabolism in vivo during exercise. Phosphorus (31P) MRS can be used to provide insights into different aspects of muscle metabolism.^60,61 31P-MRS enables direct measurement of high-energy phosphate metabolites such as phosphocreatine and adenosine triphosphate (ATP), as well as the assessment of mitochondrial function during exercise and recovery.⁶² To perform MRS for muscle metabolism, a high-field MRI scanner with specialized coils is utilized to acquire localized spectra from specific muscle groups.⁶⁰ The subject may be asked to perform small-muscle mass exercises during the scan to study dynamic changes in muscle metabolism. By analyzing the resulting spectra, various metabolites and parameters such as ATP synthesis rates, proton efflux, and buffer capacity can be quantified to provide a comprehensive assessment of muscle energetics and metabolism.^61,63 Utilization of this technique could provide insightful information related to skeletal muscle metabolism and mitochondrial function in SSc patients and should be prioritized to better elucidate the mechanisms of exercise intolerance.

While attenuated bulk limb blood flow during exercise utilizing duplex ultrasonography has been documented, there is a dearth of evidence on regional and microvascular blood flow dynamics in SSc patients. Delivery of oxygen and nutrients and removal of metabolic byproducts and carbon dioxide are exclusively done in the microvascular regions of the muscle. Arterial spin labeling (ASL) MRI is a noninvasive technique that effectively measures specific muscle perfusion without needing contrast agents. A pulsed or pseudo-continuous ASL sequence is typically employed to use ASL for muscle perfusion measurements.⁶⁴ The process involves magnetically labeling arterial blood water proximal to the muscle of interest and then allowing time for this labeled blood to perfuse the tissue before image acquisition.⁶⁵ Multiple labeled and control images are collected and averaged to improve the signal-to-noise ratio. The difference between labeled and control images provides a measure of perfusion, quantified in units of mL/min/100 g of tissue.⁶⁶ Future studies coupling these methodologies would provide incredible insight into the perfusion to muscle metabolism matching in exercising skeletal muscle, giving us greater insight into the precise areas of dysfunction that lead to exercise intolerance in SSc patients, directing us to new therapeutic targets in SSc patients.

Artificial intelligence

Artificial intelligence (AI) offers significant opportunities to improve the evaluation of patients with SSc and cardiac involvement by integrating data from a wide range of advanced imaging and monitoring techniques. AI-driven models can analyze complex datasets from echocardiograms, nailfold capillaroscopy, thermography, CMR, PET scans, and ambulatory cardiac rhythm monitoring to detect early signs of cardiac complications, such as myocardial fibrosis, microvascular dysfunction, arrhythmias, and pulmonary arterial hypertension, which are common concerns in SSc. A recent study examining the efficiency and scalability of CMR interpretation investigated the screening and diagnosis of cardiovascular disease using AI-enabled CMR, in which they developed and validated computerized CMR interpretation for screening and diagnosis of 11 types of cardiovascular disease in 9719 patients. Their findings are promising (area under the curve of 0.988% ± 0.3% and 0.991% ± 0.0%, respectively) and demonstrate the high potential of this model for improving cardiovascular disease screening and diagnosis.⁶⁷

By utilizing deep learning and pattern recognition, AI can identify subtle capillary abnormalities from nailfold capillaroscopy,⁶⁸ and potentially, quantify myocardial strain in echocardiograms, or detect perfusion deficits in PET or MRI scans to provide detailed, quantifiable markers of disease progression. Thermographic imaging, ultrasound, and ambulatory rhythm monitoring offer real-time assessments of tissue perfusion, vascular integrity, and arrhythmias, which AI could analyze longitudinally to monitor disease evolution and treatment efficacy.

In addition, an AI-based model could serve as a centralized platform for data collection, compiling imaging results, cardiac rhythm data, and clinical metrics across diverse patient populations. Such a platform would facilitate large-scale data gathering, enabling researchers to refine diagnostic criteria, establish predictive markers, and develop personalized management strategies for patients with SSc. Centralized repositories for image storage and analysis may enhance multi-center collaborations, which are requisite to understanding rare conditions. Digital Imaging and Communications in Medicine (DICOM) format is an international standard for archiving, exchanging, and viewing medical images. DICOM images can easily be transferred within and between institutions in both identified (containing protected health information) and de-identified versions. Furthermore, the availability of large-scale storage, particularly in Health Insurance Portability and Accountability Act-compliant cloud-based repositories, facilitates both rapid depositing of images and long-term storage. The Vanderbilt Heart Imaging Core Lab provides a platform by which investigators within and outside of Vanderbilt can transfer imaging studies at any time via cloud-based approaches. These images can then be analyzed centrally, using standardized methods, by assessors masked to clinical data. This approach may be particularly relevant for rare disorders where standardized imaging protocols and analysis may help enhance phenotypic signal across patients while minimizing “noise” that can occur due to variability across clinical centers.

Conclusion

Interdisciplinary collaboration and shared models of care have been developed to better manage patients with complex medical conditions.¹⁴ Advanced imaging with novel methods of data acquisition, storage, sharing, and analysis offers new opportunities to study rare but important disease manifestations such as SHI. International, interdisciplinary collaboration is an opportunity to develop new evidence-based strategies of investigation, risk stratification, and treatments for SHI.

Footnotes

Acknowledgements

None.

Declarations

ORCID iD

Tania Ruiz Maya

References

Komura

Yanaba

Bouaziz

, et al. Perspective to precision medicine in scleroderma. Front Immunol 2023; 14: 1298665.

Bruni

Ross

. Cardiac involvement in systemic sclerosis: getting to the heart of the matter. Best Pract Res Clin Rheumatol 2021; 35: 101668.

Bruni

Buch

Furst

, et al. Primary systemic sclerosis heart involvement: a systematic literature review and preliminary data-driven, consensus-based WSF/HFA definition. J Scleroderma Relat Disord 2022; 7: 24–32.

Ross

Hansen

Proudman

, et al.; Australian Scleroderma Interest Group (ASIG), Canadian Scleroderma Research Group (CSRG), the Scleroderma Clinical Trials Consortium Activity Index Working Group. Development and initial validation of the novel scleroderma clinical trials consortium activity index. Arthritis Rheumatol 2024; 76: 1635–1644.

Ferdowsi

Huq

Stevens

, et al. Development and validation of the Scleroderma Clinical Trials Consortium Damage Index (SCTC-DI): a novel instrument to quantify organ damage in systemic sclerosis. Ann Rheum Dis 2019; 78: 807–816.

Shanmugam

Frech

Steen

, et al. Collaborative National Quality and Efficacy Registry (CONQUER) for Scleroderma: outcomes from a multicenter US-based systemic sclerosis registry. Clin Rheumatol 2020; 39: 93–102.

Farina

Benanti

De Luca

, et al. The role of the multidisciplinary health care team in the management of patients with systemic sclerosis. J Multidiscip Healthc 2022; 15: 815–824.

Allred

Frech

McComber

, et al. Chronic multiorgan rare disease: the role of the nurse practitioner as a leader of the healthcare team. J Med Pract Manage 2017; 32: 413–416.

Radic

Frech

. Big data in systemic sclerosis: Great potential for the future. J Scleroderma Relat Disord 2020; 5: 172–177.

10.

Smith

Herrick

Ingegnoli

, et al. Standardisation of nailfold capillaroscopy for the assessment of patients with Raynaud’s phenomenon and systemic sclerosis. Autoimmun Rev 2020; 19: 102458.

11.

Frech

. Imaging techniques for assessment of vascular involvement in systemic sclerosis. Curr Opin Rheumatol 2022; 34: 311–318.

12.

Duff

Scarsbrook

Ravikumar

, et al. An automated method for artifical intelligence assisted diagnosis of active aortitis using radiomic analysis of FDG PET-CT images. Biomolecules 2023; 13: 343.

13.

Weber

Garshick

Liao

, et al. Sore, hot, and at risk: the emerging specialty of cardio-rheumatology. J Am Heart Assoc 2023; 12: e027846.

14.

Eder

Harvey

. Cardio-rheumatology: it’s time to collaborate. Nat Rev Rheumatol 2022; 18: 247–248.

15.

Mohammed

Shukla

Fisher

, et al. Initial survey of UK rheumatologists to inform a national cardio-rheumatology strategy. Rheumatology (Oxford) 2024; 64(3): 1541–1542.

16.

Allanore

Meune

. Primary myocardial involvement in systemic sclerosis: evidence for a microvascular origin. Clin Exp Rheumatol 2010; 28: S48–S53.

17.

Cheng

Duda

Taylor

, et al. REDCap on FHIR: clinical data interoperability services. J Biomed Inform 2021; 121: 103871.

18.

Ross

Prior

Proudman

, et al. Defining primary systemic sclerosis heart involvement: a scoping literature review. Semin Arthritis Rheum 2019; 48: 874–887.

19.

Rangarajan

Matiasz

Freed

. Cardiac complications of systemic sclerosis and management: recent progress. Curr Opin Rheumatol 2017; 29: 574–584.

20.

Yan

Luo

Nie

, et al. Association between systemic sclerosis and left ventricle dysfunction: findings from observational studies. Heliyon 2023; 9: e14110.

21.

Fontes Oliveira

Rei

Oliveira

, et al. Prevalence and prognostic significance of heart failure with preserved ejection fraction in systemic sclerosis. Future Cardiol 2022; 18: 17–25.

22.

Ross

Patel

Stevens

, et al. The clinical implications of left ventricular diastolic dysfunction in systemic sclerosis. Clin Exp Rheumatol 2022; 40: 1986–1992.

23.

Fairley

Hansen

Proudman

, et al. Prognostic and functional importance of both overt and subclinical left ventricular systolic dysfunction in systemic sclerosis. Semin Arthritis Rheum 2024; 66: 152443.

24.

De Groote

Gressin

Hachulla

, et al. Evaluation of cardiac abnormalities by Doppler echocardiography in a large nationwide multicentric cohort of patients with systemic sclerosis. Ann Rheum Dis 2008; 67: 31–36.

25.

Papagoras

Achenbach

Tsifetaki

, et al. Heart involvement in systemic sclerosis: a combined echocardiographic and scintigraphic study. Clin Rheumatol 2014; 33: 1105–1111.

26.

Radwan

Kurmann

Sandhu

, et al. Systemic sclerosis portends increased risk of conduction and rhythm abnormalities at diagnosis and during disease course: a US population-based cohort. J Scleroderma Relat Disord 2021; 6: 277–285.

27.

Fairley

Ross

Quinlivan

, et al. Sudden cardiac death, arrhythmias and abnormal electrocardiography in systemic sclerosis: a systematic review and meta-analysis. Semin Arthritis Rheum 2023; 62: 152229.

28.

Bissell

Dumitru

Erhayiem

, et al. Incidental significant arrhythmia in scleroderma associates with cardiac magnetic resonance measure of fibrosis and hs-TnI and NT-proBNP. Rheumatology (Oxford) 2019; 58: 1221–1226.

29.

Mavrogeni

Pepe

Nijveldt

, et al. Cardiovascular magnetic resonance in autoimmune rheumatic diseases: a clinical consensus document by the European Association of Cardiovascular Imaging. Eur Heart J Cardiovasc Imaging 2022; 23: e308–e322.

30.

Mavrogeni

Kitas

Dimitroulas

, et al. Cardiovascular magnetic resonance in rheumatology: current status and recommendations for use. Int J Cardiol 2016; 217: 135–148.

31.

Ross

Costello

Brown

, et al. Myocardial fibrosis and arrhythmic burden in systemic sclerosis. Rheumatology (Oxford) 2022; 61: 4497–4502.

32.

Ntusi

Piechnik

Francis

, et al. Subclinical myocardial inflammation and diffuse fibrosis are common in systemic sclerosis—a clinical study using myocardial T1-mapping and extracellular volume quantification. J Cardiovasc Magn Reson 2014; 16: 21.

33.

Dumitru

Bissell

Erhayiem

, et al. Cardiovascular outcomes in systemic sclerosis with abnormal cardiovascular MRI and serum cardiac biomarkers. RMD Open 2021; 7: e001689.

34.

Mavrogeni

Gargani

Pepe

, et al. Cardiac magnetic resonance predicts ventricular arrhythmias in scleroderma: the Scleroderma Arrhythmia Clinical Utility Study (SAnCtUS). Rheumatology (Oxford) 2020; 59: 1938–1948.

35.

Vallianou

Geladari

Panagopoulos

, et al. Cardiac MRI in autoimmune diseases: where are we now? Curr Cardiol Rev 2021; 17: e160721190002.

36.

Pons-Llado

Kellman

. State-of-the-art of myocardial perfusion by CMR: a practical view. Rev Cardiovasc Med 2022; 23: 325.

37.

Rasmussen

Murphy

Milidonis

, et al. Myocardial blood flow by magnetic resonance in patients with suspected coronary stenosis: comparison to PET and invasive physiology. Circ Cardiovasc Imaging 2024; 17: e016635.

38.

Zhou

Sin

Yan

, et al. Qualitative and quantitative stress perfusion cardiac magnetic resonance in clinical practice: a comprehensive review. Diagnostics (Basel) 2023; 13: 524.

39.

Schindler

Fearon

Pelletier-Galarneau , et al. Myocardial perfusion PET for the detection and reporting of coronary microvascular dysfunction: a JACC: Cardiovascular Imaging Expert Panel Statement. JACC Cardiovasc Imaging 2023; 16: 536–548.

40.

Di Carli

. PET perfusion and flow assessment: tomorrows’ technology today. Semin Nucl Med 2020; 50: 227–237.

41.

Martens

Cooper

Tang

WHW

. Diagnostic approach for suspected acute myocarditis: considerations for standardization and broadening clinical spectrum. J Am Heart Assoc 2023; 12: e031454.

42.

Chen

Jeudy

. Assessment of myocarditis: cardiac MR, PET/CT, or PET/MR? Curr Cardiol Rep 2019; 21: 76.

43.

Lescoat

Yelnik

Coiffier

, et al. Ulnar artery occlusion and severity markers of vasculopathy in systemic sclerosis: a multicenter cross-sectional study. Arthritis Rheumatol 2019; 71: 983–990.

44.

Fairchild

Chung

Sharpless

, et al. Ultrasound detection of calcinosis and association with ulnar artery occlusion in patients with systemic sclerosis. Arthritis Care Res (Hoboken) 2021; 73: 1332–1337.

45.

Hsieh

Chen

Chou

, et al. Association between systemic sclerosis and peripheral arterial disease: a nationwide observation retrospective claim records cohort study in Taiwan. BMJ Open 2021; 11: e048149.

46.

Miziolek

Lis-Swiety

Skrzypek-Salamon

, et al. Correlation between the infrared thermogram and microvascular abnormalities of the nailfold in patients with systemic sclerosis. Postepy Dermatol Alergol 2021; 38: 115–122.

47.

Pauling

Shipley

Harris

, et al. Use of infrared thermography as an endpoint in therapeutic trials of Raynaud’s phenomenon and systemic sclerosis. Clin Exp Rheumatol 2012; 30: S103–S115.

48.

Boulon

Aiouaz

Blaise

, et al. Correlation between capillaroscopic classifications and severity in systemic sclerosis: results from SCLEROCAP study at inclusion. Clin Exp Rheumatol 2019; 37(Suppl. 119): 63–68.

49.

Caramaschi

Canestrini

Martinelli

, et al. Scleroderma patients nailfold videocapillaroscopic patterns are associated with disease subset and disease severity. Rheumatology (Oxford) 2007; 46: 1566–1569.

50.

Sulli

Paolino

Pizzorni

, et al. Progression of nailfold capillaroscopic patterns and correlation with organ involvement in systemic sclerosis: a 12 year study. Rheumatology (Oxford) 2020; 59: 1051–1058.

51.

Smith

Riccieri

Pizzorni

, et al. Nailfold capillaroscopy for prediction of novel future severe organ involvement in systemic sclerosis. J Rheumatol 2013; 40: 2023–2028.

52.

Zanatta

Famoso

Boscain

, et al. Nailfold avascular score and coronary microvascular dysfunction in systemic sclerosis: a newsworthy association. Autoimmun Rev 2019; 18: 177–183.

53.

Bissell

L-A

Md Yusof

Buch

. Primary myocardial disease in scleroderma-a comprehensive review of the literature to inform the UK Systemic Sclerosis Study Group cardiac working group. Rheumatology (Oxford) 2017; 56: 882–895.

54.

Minopoulou

Theodorakopoulou

Boutou

, et al. Nailfold capillaroscopy in systemic sclerosis patients with and without pulmonary arterial hypertension: a systematic review and meta-analysis. J Clin Med 2021; 10: 1528.

55.

Blom-Bulow

Jonson

Bauer

. Factors limiting exercise performance in progressive systemic sclerosis. Semin Arthritis Rheum 1983; 13: 174–181.

56.

Kovacs

Maier

Aberer

, et al. Borderline pulmonary arterial pressure is associated with decreased exercise capacity in scleroderma. Am J Respir Crit Care Med 2009; 180: 881–886.

57.

Pons-Estel

Alarcon

Scofield

, et al. Understanding the epidemiology and progression of systemic lupus erythematosus. Semin Arthritis Rheum 2010; 39: 257–268.

58.

Ross

Costello

Lindqvist

, et al. Disease specific determinants of cardiopulmonary fitness in systemic sclerosis. Semin Arthritis Rheum 2023; 58: 152137.

59.

Adams

Reich

Uhlemann

, et al. Molecular effects of exercise training in patients with cardiovascular disease: focus on skeletal muscle, endothelium, and myocardium. Am J Physiol Heart Circ Physiol 2017; 313: H72–H88.

60.

Klepochova

Valkovic

Hochwartner

, et al. Differences in muscle metabolism between triathletes and normally active volunteers investigated using multinuclear magnetic resonance spectroscopy at 7T. Front Physiol 2018; 9: 300.

61.

Hwang

Choi

. Use of in vivo magnetic resonance spectroscopy for studying metabolic diseases. Exp Mol Med 2015; 47: e139.

62.

Piil

Jorgensen

Egelund

, et al. Effects of aging and exercise training on leg hemodynamics and oxidative metabolism in the transition from rest to steady-state exercise: role of cGMP signaling. Am J Physiol Regul Integr Comp Physiol 2018; 315: R274–R283.

63.

Fiedler

Schmid

Goluch

, et al. Skeletal muscle ATP synthesis and cellular H(+) handling measured by localized (31)P-MRS during exercise and recovery. Sci Rep 2016; 6: 32037.

64.

Englund

Rodgers

Langham

, et al. Measurement of skeletal muscle perfusion dynamics with pseudo-continuous arterial spin labeling (pCASL): assessment of relative labeling efficiency at rest and during hyperemia, and comparison to pulsed arterial spin labeling (PASL). J Magn Reson Imaging 2016; 44: 929–939.

65.

Pollak

Meyer

Epstein

, et al. Arterial spin labeling MR imaging reproducibly measures peak-exercise calf muscle perfusion: a study in patients with peripheral arterial disease and healthy volunteers. JACC Cardiovasc Imaging 2012; 5: 1224–1230.

66.

Qin

Alsop

Bolar

, et al. Velocity-selective arterial spin labeling perfusion MRI: a review of the state of the art and recommendations for clinical implementation. Magn Reson Med 2022; 88: 1528–1547.

67.

Wang

Yang

Wen

, et al. Screening and diagnosis of cardiovascular disease using artificial intelligence-enabled cardiac magnetic resonance imaging. Nat Med 2024; 30: 1471–1480.

68.

Ozturk

Laclau

Boulon

, et al. Analysis of nailfold capillaroscopy images with artificial intelligence: Data from literature and performance of machine learning and deep learning from images acquired in the SCLEROCAP study. Microvasc Res 2025; 157: 104753.

Cardio-rheumatology: integrated care and the opportunities for personalized medicine

Abstract

Keywords

Introduction

The cardio-rheumatology clinic: At the forefront of precision medicine

Current standard cardiac evaluation

Paired vasculopathy imaging and cardiac data

Specialized imaging

Artificial intelligence

Conclusion

Footnotes

Acknowledgements

Declarations

ORCID iD

References