Role of cardiac MRI in the diagnosis of immune checkpoint inhibitor-associated myocarditis

Base-to-apex Gradient Pattern Assessed by Cardiovascular Magnetic Resonance in Takotsubo Cardiomyopathy

OBJECTIVES

The purpose of this study was to investigate the base-to-apex gradient strain pattern as a noncontrast cardiovascular magnetic resonance (CMR) parameter in patients with Takotsubo cardiomyopathy (TTC) and determine whether this pattern may help discriminate TTC from patients with anterior myocardial infarction (AMI).

MATERIALS AND METHODS

A total of 80 patients were included in the analysis: 30 patients with apical ballooning TTC and 50 patients with AMI. Global and regional ventricular function, including longitudinal (LS), circumferential (CS), and radial strain (RS), were assessed using CMR. The base-to-apex LS, RS, and CS gradients, defined as the peak gradient difference between averaged basal and apical strain, were calculated.

RESULTS

The base-to-apex RS gradient was impaired in TTC patients compared with the AMI group (14.04 ± 15.50 vs. -0.43 ± 11.59, P =0.001). Conversely, there were no significant differences in the base-to-apex LS and CS gradients between the AMI group and TTC patients (0.14 ± 2.71 vs. -1.5 ± 3.69, P =0.054: -0.99 ± 6.49 vs. ±1.4 ± 5.43, P =0.47, respectively). Beyond the presence and extension of LGE, base-to-apex RS gradient was the only independent discriminator between TTC and AMI (OR 1.28; 95% CI 1.08, 1.52, P =0.006) in multivariate logistic regression analysis.

CONCLUSION

The findings of this study suggest that the pattern of regional myocardial strain impairment could serve as an additional noncontrast CMR tool to refine the diagnosis of TTC. A pronounced base-to-apex RS gradient may be a specific left ventricle strain pattern of TTC.

Cardiovascular adverse events associated with immune checkpoint inhibitors: a meta-analysis

Objective

To evaluate the cardiovascular safety of anticancer drug immune checkpoint inhibitors (ICIs) used in patients with malignant tumors.

Methods

Four clinical research databases that have been completed since their establishment were searched, and the odds ratios and 95% confidence intervals of each indicator were statistically calculated.

Results

62 randomized controlled trial and controlled trials were included. In single drug treatment ICIs group, the overall risk of cardio cerebral Vascular disease at all levels was higher than that in the placebo/chemotherapy group. Especially in all grades of Myocarditis and above grade 3 compared with normal controls, except for pericardial lesions, other indicators have no obvious side effects.

Conclusion

Single drug use of an anti-tumor ICIs may increase cardiovascular side effects risk in cancer patients, so we need to strengthen monitoring, identification and management, and timely intervention to manage ICI induced adverse events.

Cine-cardiac magnetic resonance to distinguish between ischemic and non-ischemic cardiomyopathies: a machine learning approach

OBJECTIVE

This work aimed to derive a machine learning (ML) model for the differentiation between ischemic cardiomyopathy (ICM) and non-ischemic cardiomyopathy (NICM) on non-contrast cardiovascular magnetic resonance (CMR).

METHODS

This retrospective study evaluated CMR scans of 107 consecutive patients (49 ICM, 58 NICM), including atrial and ventricular strain parameters. We used these data to compare an explainable tree-based gradient boosting additive model with four traditional ML models for the differentiation of ICM and NICM. The models were trained and internally validated with repeated cross-validation according to discrimination and calibration. Furthermore, we examined important variables for distinguishing between ICM and NICM.

RESULTS

A total of 107 patients and 38 variables were available for the analysis. Of those, 49 were ICM (34 males, mean age 60 ± 9 years) and 58 patients were NICM (38 males, mean age 56 ± 19 years). After 10 repetitions of the tenfold cross-validation, the proposed model achieved the highest area under curve (0.82, 95% CI [0.47-1.00]) and lowest Brier score (0.19, 95% CI [0.13-0.27]), showing competitive diagnostic accuracy and calibration. At the Youden's index, sensitivity was 0.72 (95% CI [0.68-0.76]), the highest of all. Analysis of predictions revealed that both atrial and ventricular strain CMR parameters were important for the identification of ICM patients.

CONCLUSION

The current study demonstrated that using a ML model, multi chamber myocardial strain, and function on non-contrast CMR parameters enables the discrimination between ICM and NICM with competitive diagnostic accuracy.

CLINICAL RELEVANCE STATEMENT

A machine learning model based on non-contrast cardiovascular magnetic resonance parameters may discriminate between ischemic and non-ischemic cardiomyopathy enabling wider access to cardiovascular magnetic resonance examinations with lower costs and faster imaging acquisition.

KEY POINTS

• The exponential growth in cardiovascular magnetic resonance examinations may require faster and more cost-effective protocols. • Artificial intelligence models can be utilized to distinguish between ischemic and non-ischemic etiologies. • Machine learning using non-contrast CMR parameters can effectively distinguish between ischemic and non-ischemic cardiomyopathies.

Effect of late gadolinium enhancement on left atrial impairment in myocarditis patients

OBJECTIVE

The aims of our study were to investigate the effect of the extent and location of late gadolinium enhancement (LGE) on the left atrium (LA) function in patients with acute myocarditis (AM) using cardiovascular magnetic resonance (CMR).

METHOD

This retrospective study performed CMR scans in 113 consecutive patients (89 males, 24 females; mean age 45.8 ± 17.3 years) with AM that met the updated Lake Louise criteria. Reservoir, conduit, and booster LA functions were analyzed by CMR feature tracking using dedicated software. Besides LA strain measurements, myocardial scar location and extent were assigned and quantified by LGE imaging.

RESULTS

AM patients with septal LGE had impaired reservoir, conduit, and conduit strain rate function in comparison with AM patients with non-septal LGE (p = 0.001, for all). In fully adjusted multivariable linear regression, reservoir and conduit were significantly associated with left ventricle (LV) LGE location (β coefficient = 8.205, p = 0.007; β coefficient = 5.185, p = 0.026; respectively). In addition, LA parameters decreased according to the increase in the extent of LV fibrosis (LGE ≤ 10%; LGE 11-19%; LGE ≥ 20%). After adjustment in multivariable linear regression, the association with LV LGE extent was no longer statistically significant.

CONCLUSION

In patients with acute myocarditis, LA function abnormalities are significantly associated with LV LGE location, but not with LGE extent. Septal LGE is paralleled by a deterioration of LA reservoir and conduit function.

CLINICAL RELEVANCE STATEMENT

Left atrium dysfunction is associated with the presence of late gadolinium enhancement in the left ventricle septum and can be useful in the clinical prognostication of patients with acute myocarditis, allowing individually tailored treatment.

KEY POINTS

• Myocardial fibrosis is related to atrial impairment. • The location of myocardial fibrosis is the main determinant of atrial dysfunction in myocarditis patients. • The quantification of atrial mechanisms may provide more in-depth insight into myocarditis pathophysiology.

Cardiac Fibrosis Automated Diagnosis Based on FibrosisNet Network Using CMR Ischemic Cardiomyopathy

Ischemic heart condition is one of the most prevalent causes of death that can be treated more effectively and lead to fewer fatalities if identified early. Heart muscle fibrosis affects the diastolic and systolic function of the heart and is linked to unfavorable cardiovascular outcomes. Cardiac magnetic resonance (CMR) scarring, a risk factor for ischemic heart disease, may be accurately identified by magnetic resonance imaging (MRI) to recognize fibrosis. In the past few decades, numerous methods based on MRI have been employed to identify and categorize cardiac fibrosis. Because they increase the therapeutic advantages and the likelihood that patients will survive, developing these approaches is essential and has significant medical benefits. A brand-new method that uses MRI has been suggested to help with diagnosing. Advances in deep learning (DL) networks contribute to the early and accurate diagnosis of heart muscle fibrosis. This study introduces a new deep network known as FibrosisNet, which detects and classifies fibrosis if it is present. It includes some of 17 various series layers to achieve the fibrosis detection target. The introduced classification system is trained and evaluated for the best performance results. In addition, deep transfer-learning models are applied to the different famous convolution neural networks to find fibrosis detection architectures. The FibrosisNet architecture achieves an accuracy of 96.05%, a sensitivity of 97.56%, and an F1-Score of 96.54%. The experimental results show that FibrosisNet has numerous benefits and produces higher results than current state-of-the-art methods and other advanced CNN approaches.

Pulmonary transit time as a marker of diastolic dysfunction in Takotsubo syndrome

AIM

To evaluate the pulmonary transit time (PTT) and its derived parameters using cardiac magnetic resonance imaging (CMRI) as markers of diastolic dysfunction in Takotsubo syndrome (TS) and its relationship with transthoracic echocardiography and CMRI parameters.

MATERIALS AND METHODS

Twenty-two patients with TS, who exhibited diastolic dysfunction as assessed by transthoracic echocardiography, were enrolled retrospectively and the PTT, pulmonary transit time index (PTTI), and pulmonary blood volume index (PBVI) were evaluated using first-pass CMRI. PTT was calculated as the number of cardiac cycles required for a bolus of contrast agent to move from the right ventricle (RV) to the left ventricle (LV), whereas PTTI represents the PTT interval corrected for the heart rate. Finally, PBVI was calculated as the product of PTTI, and RV stroke volume indexed for body surface area. Normal references of PTT, PTTI, and PBVI were evaluated in a cohort of 20 age- and sex-matched healthy controls.

RESULTS

Compared with healthy subjects, TS patients showed significantly higher PTT, PTTI, and PBVI (p=0.0001, p=0.0001, and p=0.002, respectively). Using multivariable logistic regression, PBVI provided the best differentiation between TS and controls (AUC 0.84). PBVI was significantly associated with the index of diastolic dysfunction and left atrial strain parameters. In addition, PBVI demonstrated a significant correlation with global T2 mapping (r=0,520, p=0,019).

CONCLUSION

PTT and the derived parameters, as assessed using first-pass CMRI, are potential tools for assessing LV diastolic dysfunction in patients with TS.

Sex-based differences in late gadolinium enhancement among patients with acute myocarditis

OBJECTIVE

The aims of our study were to investigate the sex differences in late gadolinium enhancement (LGE) using cardiovascular magnetic resonance (CMR) in a single-centre cohort of consecutive patients with acute myocarditis (AM).

METHOD

This retrospective study performed CMR scans in 135 consecutive patients with AM that met the Lake Louise criteria. On CMR, LV ventricular strain functions were performed on conventional cine SSFP sequences. Besides myocardial strain measurements, myocardial scar location, extension, and size were assigned and quantified by LGE imaging.

RESULTS

There was no difference in age (age 42.51 ± 19.64 years vs 40.92 ± 19.94 years; p = 0.74) and cardiovascular risk profile between women and men. Despite similar comorbidities, women were more like to present with dyspnea (p = 0.001). Women demonstrated higher prevalence of septal LGE (p = 0.004) and increased global circumferential strain parameters (p = 0.008) in comparison with men. In multivariate analysis, female sex remained an independent determinant of septal LGE (β coefficient = -0.520, p = 0.001).

CONCLUSION

This is the first study reporting sex differences in LGE localization in AM. Women have more septal LGE involvement independent of age, cardiovascular risk factors, and CMR parameters. These findings further emphasize the sex-based differences in cardiovascular diseases.

Cardiovascular Effects of Immune Checkpoint Inhibitors: More Than Just Myocarditis

PURPOSE OF REVIEW

Immune checkpoint inhibitors have reshaped the treatment of cancer, but they are characterized by peculiar toxicity consisting of immune-related adverse events that may potentially affect any organ or system. In this review, we summarize data on clinical presentation, diagnosis, pathogenesis, and management of the main immune-related cardiovascular toxicities of immune checkpoint inhibitors.

RECENT FINDINGS

The most relevant immune-related cardiovascular toxicity is myocarditis, but other non-negligible reported events include non-inflammatory heart failure, conduction abnormalities, pericardial disease, and vasculitis. More recently, growing evidence suggests a role for immune checkpoint inhibitors in accelerating atherosclerosis and promoting plaque inflammation, thus leading to myocardial infarction. Immune checkpoint inhibitors are associated with several forms of cardiovascular toxicity; thus, an accurate cardiovascular baseline evaluation and periodical monitoring are required. Furthermore, the optimization of cardiovascular risk factors before, during, and after treatment may contribute to mitigating both short-term and long-term cardiovascular toxicity of these drugs.

Artificial Intelligence Applications in Cardiovascular Magnetic Resonance Imaging: Are We on the Path to Avoiding the Administration of Contrast Media?

In recent years, cardiovascular imaging examinations have experienced exponential growth due to technological innovation, and this trend is consistent with the most recent chest pain guidelines. Contrast media have a crucial role in cardiovascular magnetic resonance (CMR) imaging, allowing for more precise characterization of different cardiovascular diseases. However, contrast media have contraindications and side effects that limit their clinical application in determinant patients. The application of artificial intelligence (AI)-based techniques to CMR imaging has led to the development of non-contrast models. These AI models utilize non-contrast imaging data, either independently or in combination with clinical and demographic data, as input to generate diagnostic or prognostic algorithms. In this review, we provide an overview of the main concepts pertaining to AI, review the existing literature on non-contrast AI models in CMR, and finally, discuss the strengths and limitations of these AI models and their possible future development.

Automated diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging using deep learning models: A review

In recent years, cardiovascular diseases (CVDs) have become one of the leading causes of mortality globally. At early stages, CVDs appear with minor symptoms and progressively get worse. The majority of people experience symptoms such as exhaustion, shortness of breath, ankle swelling, fluid retention, and other symptoms when starting CVD. Coronary artery disease (CAD), arrhythmia, cardiomyopathy, congenital heart defect (CHD), mitral regurgitation, and angina are the most common CVDs. Clinical methods such as blood tests, electrocardiography (ECG) signals, and medical imaging are the most effective methods used for the detection of CVDs. Among the diagnostic methods, cardiac magnetic resonance imaging (CMRI) is increasingly used to diagnose, monitor the disease, plan treatment and predict CVDs. Coupled with all the advantages of CMR data, CVDs diagnosis is challenging for physicians as each scan has many slices of data, and the contrast of it might be low. To address these issues, deep learning (DL) techniques have been employed in the diagnosis of CVDs using CMR data, and much research is currently being conducted in this field. This review provides an overview of the studies performed in CVDs detection using CMR images and DL techniques. The introduction section examined CVDs types, diagnostic methods, and the most important medical imaging techniques. The following presents research to detect CVDs using CMR images and the most significant DL methods. Another section discussed the challenges in diagnosing CVDs from CMRI data. Next, the discussion section discusses the results of this review, and future work in CVDs diagnosis from CMR images and DL techniques are outlined. Finally, the most important findings of this study are presented in the conclusion section.

Early evaluation of severe immune checkpoint inhibitor-associated myocarditis: a real-world clinical practice

PURPOSE

Immune checkpoint inhibitor (ICI)-associated myocarditis is a rare but severe complication for patients treated with immunotherapy. This study aims to explore the predictive significance of patients' clinical features and examination results for the severity of ICI-associated myocarditis.

METHODS

Data from a real-world cohort of 81 cancer patients who developed ICI-associated myocarditis after immunotherapy were retrospectively analyzed. The development of myocarditis of Common Terminology Criteria for Adverse Events (CTCAE) grades 3-5 and/or the major adverse cardiovascular event (MACE) was set as endpoints. Logistic regression was used to evaluate the predictive value of each factor.

RESULTS

CTCAE grades 3-5 and MACE developed in 43/81 (53.1%) and 28/81 (34.6%) cases, respectively. The likelihood of CTCAE grades 3-5 and MACE increased with the accumulation of organs affected by the ICI-associated adverse events and initial clinical symptoms. Concurrent systematic therapies during ICI treatment did not raise the risk of myocarditis severity, while prior chemotherapy did. Besides classical serum cardiac markers, a higher neutrophil ratio was also related to poorer cardiac outcomes, whereas higher lymphocyte and monocyte ratios were predictors of favorable cardiac outcomes. The CD4+ T cell ratio and CD4/CD8 ratio were negatively related to CTCAE grades 3-5. Several cardiovascular magnetic resonance parameters were associated with myocarditis severity, whereas the predictive value of echocardiography and electrocardiogram was weak.

CONCLUSION

This study comprehensively evaluated the prognostic value of patients' clinical characteristics and examination results and identified several predictors of severe ICI-associated myocarditis, which will facilitate early detection of severe ICI-associated myocarditis in patients receiving immunotherapy.

Exploring the EVolution in PrognOstic CapabiLity of MUltisequence Cardiac MagneTIc ResOnance in PatieNts Affected by Takotsubo Cardiomyopathy Based on Machine Learning Analysis: Design and Rationale of the EVOLUTION Study

PURPOSE

Takotsubo cardiomyopathy (TTC) is a transient but severe acute myocardial dysfunction with a wide range of outcomes from favorable to life-threatening. The current risk stratification scores of TTC patients do not include cardiac magnetic resonance (CMR) parameters. To date, it is still unknown whether and how clinical, trans-thoracic echocardiography (TTE), and CMR data can be integrated to improve risk stratification.

METHODS

EVOLUTION (Exploring the eVolution in prognOstic capabiLity of mUlti-sequence cardiac magneTIc resOnance in patieNts affected by Takotsubo cardiomyopathy) is a multicenter, international registry of TTC patients who will undergo a clinical, TTE, and CMR evaluation. Clinical data including demographics, risk factors, comorbidities, laboratory values, ECG, and results from TTE and CMR analysis will be collected, and each patient will be followed-up for in-hospital and long-term outcomes. Clinical outcome measures during hospitalization will include cardiovascular death, pulmonary edema, arrhythmias, stroke, or transient ischemic attack.Clinical long-term outcome measures will include cardiovascular death, pulmonary edema, heart failure, arrhythmias, sudden cardiac death, and major adverse cardiac and cerebrovascular events defined as a composite endpoint of death from any cause, myocardial infarction, recurrence of TTC, transient ischemic attack, and stroke. We will develop a comprehensive clinical and imaging score that predicts TTC outcomes and test the value of machine learning models, incorporating clinical and imaging parameters to predict prognosis.

CONCLUSIONS

The main goal of the study is to develop a comprehensive clinical and imaging score, that includes TTE and CMR data, in a large cohort of TTC patients for risk stratification and outcome prediction as a basis for possible changes in patient management.

Epicardial fat volume assessed with cardiac magnetic resonance imaging in patients with Takotsubo cardiomyopathy

PURPOSE

The aims of our study were to investigate with cardiovascular magnetic resonance (CMR) the role of Epicardial Fat Volume (EFV) and distribution in patients with Takotsubo cardiomyopathy (TTC). Moreover, we explored EFV in patients with TTC and related this to comorbidities, cardiac biomarkers, and cardiac function.

METHODS

This retrospective study performed CMR scans in 30 consecutive TTC patients and 20 healthy controls. The absolute amount of EFV was quantified in consecutive short-axis cine stacks through the modified Simpson's rule. In addition, the left atrio-ventricular groove (LV) and right ventricle (RV) Epicardial Fat Thickness (EFT) were measured as well. Besides epicardial fat, LV myocardial strain parameters and T2 mapping measurements were obtained.

RESULTS

TTC patients and controls were of comparable age, sex, and body mass index. Compared to healthy controls, patients with TTC demonstrated a significantly increased EFV, epicardial fat mass, and EFV indexed for body 7surface area (p = 0.005; p = 0.003; p = 0.008; respectively). In a multiple regression model including age, sex, BMI, atrial fibrillation, and dyslipidemia, TTC remained an independent association with EFV (p = 0.008). Global T2 mapping and Global longitudinal strain in patients with TTC were correlated with EFV (r = 0.63, p = 0.001, and r = 0.44, p = 0.02, respectively).

CONCLUSION

Patients with TTC have increased EFV compared to healthy controls, despite a similar body mass index. The amount of epicardial fat was associated with CMR markers of myocardial inflammation and subclinical contractile dysfunction.

Machine learning approach in diagnosing Takotsubo cardiomyopathy: The role of the combined evaluation of atrial and ventricular strain, and parametric mapping

BACKGROUND

Cardiac magnetic resonance (CMR) with late gadolinium enhancement (LGE) is a key diagnostic tool in the differential diagnosis between non-ischemic cause of cardiac chest pain. Some patients are not eligible for a gadolinium contrast-enhanced CMR; in this scenario, the diagnosis remains challenging without invasive examination. Our purpose was to derive a machine learning model integrating some non-contrast CMR parameters and demographic factors to identify Takotsubo cardiomyopathy (TTC) in subjects with cardiac chest pain.

MATERIAL AND METHODS

Three groups of patients were retrospectively studied: TTC, acute myocarditis, and healthy controls. Global and regional left ventricular longitudinal, circumferential, and radial strain (RS) analysis included were assessed. Reservoir, conduit, and booster bi-atrial functions were evaluated by tissue-tracking. Parametric mapping values were also assessed in all the patients. Five different tree-based ensemble learning algorithms were tested concerning their ability in recognizing TTC in a fully cross-validated framework.

RESULTS

The CMR-based machine learning (ML) ensemble model, by using the Extremely Randomized Trees algorithm with Elastic Net feature selection, showed a sensitivity of 92% (95% CI 78-100), specificity of 86% (95% CI 80-92) and area under the ROC of 0.94 (95% CI 0.90-0.99) in diagnosing TTC. Among non-contrast CMR parameters, the Shapley additive explanations analysis revealed that left atrial (LA) strain and strain rate were the top imaging markers in identifying TTC patients.

CONCLUSIONS

Our study demonstrated that using a tree-based ensemble learning algorithm on non-contrast CMR parameters and demographic factors enables the identification of subjects with TTC with good diagnostic accuracy.

TRANSLATIONAL OUTLOOK

Our results suggest that non-contrast CMR features can be implemented in a ML model to accurately identify TTC subjects. This model could be a valuable tool for aiding in the diagnosis of subjects with a contraindication to the contrast media. Furthermore, the left atrial conduit strain and strain rate were imaging markers that had a strong impact on TTC identification. Further prospective and longitudinal studies are needed to validate these findings and assess predictive performance in different cohorts, such as those with different ethnicities, and social backgrounds and undergoing different treatments.

Neuromuscular and cardiac adverse events associated with immune checkpoint inhibitors: pooled analysis of individual cases from multiple institutions and literature

BACKGROUND

Immune checkpoint inhibitors (ICIs) have revolutionized the management of multiple tumors, due to improved efficacy, quality of life, and safety. While most immune-related adverse events (irAEs) are mild and easily managed, in rare cases such events may be life-threatening, especially those affecting the neuromuscular and cardiac system. The management of neuromuscular/cardiac irAEs is not clear due to the lack of consistent data. Therefore, we carried out a pooled analysis of collected cases from selected Italian centers and individual data from published case reports and case series, in order to improve our understanding of these irAEs.

PATIENTS AND METHODS

We collected retrospective data from patients treated in six Italian centers with ICIs (programmed cell death protein 1 or programmed death-ligand 1 and/or cytotoxic T-lymphocyte antigen 4 inhibitor) for any solid tumor who experienced neuromuscular and/or cardiovascular toxicity. Then, we carried out a search of case reports and series of neuromuscular/cardiac irAEs from ICIs with any solid tumor.

RESULTS

This analysis includes cases from Italian institutions (n = 18) and the case reports identified in our systematic literature search (n = 120), for a total of 138 patients. Among these patients, 50 (36.2%) had complete resolution of their neuromuscular/cardiac irAEs, in 21 (15.2%) cases there was a clinical improvement with mild sequelae, and 53 (38.4%) patients died as a result of the irAEs. Factors significantly associated with worse outcomes were early irAE onset, within the first two cycles of ICI (Fisher P < 0.0001), clinical manifestation of both myositis and myocarditis when compared with patients who developed only myositis or myocarditis (chi-square P = 0.0045), and the development of arrhythmia (Fisher P = 0.0070).

CONCLUSIONS

To the best of our knowledge, this is the largest collection of individual cases of immune-related myocarditis/myositis. Early irAE onset, concurrent development of myositis and myocarditis, as well as occurrence of arrhythmias are associated with worse outcomes and should encourage an aggressive immunomodulatory treatment.

Incidence of adverse cardiovascular events associated with immune checkpoint inhibitors and risk factors for left ventricular dysfunction: A single-center prospective clinical study

Background

The incidence of immune checkpoint inhibitors (ICI)-related adverse cardiovascular events (ACEs) may be underestimated, and there are few reports on the incidence and risk factors of ICI-induced left ventricular dysfunction (LVD).

Objectives

This study aimed to investigate the incidence of ACEs caused by ICI, in particular to analyze the incidence and risk factors of LV systolic and diastolic dysfunction.

Materials and methods

A prospective clinical study was performed on patients who received ICI in our hospital from November 2020 to October 2021. They received regular cardiovascular examinations, including echocardiography, ECG, cTnT, and NT-proBNP, etc. The incidence of various ACEs was counted, and the risk factors of LVD were analyzed.

Results

A total of 106 cancer patients treated with ICI were recruited. During the follow-up, 41 patients (38.68%) developed various ECG abnormalities, 39 patients (36.79%) developed LVDD, 9 patients (8.49%) developed CTRCD, and 2 patients (1.89%) developed new pericardial effusion. The patients with elevated cTnT, CK-MB, and NT-proBNP were 10 (9.43%), 8 (7.55%), and 8 (7.5%), respectively. Thirteen of the 52 patients with LVD had hypertension, while 4 of the 54 patients without LVD had hypertension (OR = 4.17, 95% CI: 1.26-13.78; P = 0.019). The baseline LVEF and LVFS of patients with LVD were 61.54 ± 4.15% and 33.78 ± 2.73%, while those of the control group were 64.16 ± 3.68% and 34.95 ± 2.84, respectively (P = 0.003 and P = 0.048). Compared with patients without LVD, patients with LVD had lower e' (6.99 ± 1.33 cm/s vs. 7.64 ± 1.39 cm/s, P = 0.029) and higher E to e' ratio (11.89 ± 3.15 cm/s vs. 10.43 ± 2.52, P = 0.024). Multiple regression analysis showed that a history of hypertension (HR = 26.52, 95% CI: 2.479-283.667, P = 0.007) and lower baseline e' (HR = 0.04, 95% CI: 0.003-0.709, P = 0.028) were risk factors for developing LVD.

Conclusion

Patients treated with ICI may develop multiple ACEs, including acute myocarditis, pericarditis, ECG abnormalities, and elevated cardiac biomarkers. ICI may lead to a high incidence of LVD, and echocardiography is helpful for early detection of LVD. Patients with hypertension or poor LV systolic or diastolic function at baseline were predictors of LVD after ICI treatment.

Cardiovascular Magnetic Resonance Imaging Patterns in Rare Cardiovascular Diseases

Rare cardiovascular diseases (RCDs) have low incidence but major clinical impact. RCDs' classification includes Class I-systemic circulation, Class II-pulmonary circulation, Class III-cardiomyopathies, Class IV-congenital cardiovascular diseases (CVD), Class V-cardiac tumors and CVD in malignancy, Class VI-cardiac arrhythmogenic disorders, Class VII-CVD in pregnancy, Class VIII-unclassified rare CVD. Cardiovascular Magnetic Resonance (CMR) is useful in the diagnosis/management of RCDs, as it performs angiography, function, perfusion, and tissue characterization in the same examination. Edema expressed as a high signal in STIRT2 or increased T2 mapping is common in acute/active inflammatory states. Diffuse subendocardial fibrosis, expressed as diffuse late gadolinium enhancement (LGE), is characteristic of microvascular disease as in systemic sclerosis, small vessel vasculitis, cardiac amyloidosis, and metabolic disorders. Replacement fibrosis, expressed as LGE, in the inferolateral wall of the left ventricle (LV) is typical of neuromuscular disorders. Patchy LGE with concurrent edema is typical of myocarditis, irrespective of the cause. Cardiac hypertrophy is characteristic in hypertrophic cardiomyopathy (HCM), cardiac amyloidosis (CA) and Anderson-Fabry Disease (AFD), but LGE is located in the IVS, subendocardium and lateral wall in HCM, CA and AFD, respectively. Native T1 mapping is increased in HCM and CA and reduced in AFD. Magnetic resonance angiography provides information on aortopathies, such as Marfan, Turner syndrome and Takayasu vasculitis. LGE in the right ventricle is the typical finding of ARVC, but it may involve LV, leading to the diagnosis of arrhythmogenic cardiomyopathy. Tissue changes in RCDs may be detected only through parametric imaging indices.