Defining echocardiographic predictors of outcome in cardiac amyloidosis by subtype.

BACKGROUND: Current echocardiographic risk factors for prognosis in cardiac amyloidosis (CA) do not distinguish between the two main subtypes: transthyretin cardiomyopathy (TTR) and immunoglobulin light chain cardiomyopathy (AL), each of which require distinct diagnostic and therapeutic approaches. Additionally, only traditional parameters have been studied with little data on advanced techniques. Accordingly, we sought to determine whether differences exist in 2D transthoracic echocardiography (2DE) predictors of survival between the CA subtypes using a comprehensive approach. METHODS: 220 patients (72±12 years) with confirmed CA (AL=89, TTR=131) who underwent 2DE at the time of CA diagnosis were enrolled. Left ventricular (LV) dimensions, indexed mass (LVMi), global longitudinal strain (LVGLS), apical-sparing ratio (LVASR), diastology, right ventricular (RV) size and function indices including tricuspid annular systolic excursion (TAPSE), RV free-wall (RVFWS) and global (RVGLS) strain, indexed left (LA) and right atrial volumes (LAVi and RAVi), LA strain (reservoir and booster) and RV systolic pressure (RVSP) were measured. A propensity-score weighted stepwise variable selection Cox proportional hazards model derived from NYHA class and renal impairment status at diagnosis was used to determine the associations between 2DE parameters and mortality specific to CA subtype over a median follow-up of 36-months. RESULTS: After adjusting for age, atrial fibrillation and treatment, parameters associated with survival were RVFWS (p=0.003, HR 1.15, 95% CI[1.053,1.245]) and RVSP (p=0.03, HR 1.03, 95% CI[1.004,1.063]) in AL and LVASR (p=0.007, HR 6.68, 95% CI[1.75,25.492]) and RAVi (p=0.049, HR 1.03, 95% CI[1.000,1.052]) in TTR. CONCLUSIONS: Echocardiographic prognosticators for survival are specific to cardiac amyloid subtype. These results potentially provide information critical for clinical decision-making and follow-up in these patients.

Managing Implanted Cardiac Electronic Devices in Patients With Severe Tricuspid Regurgitation: JACC State-of-the-Art Review.

Orthotopic transcatheter tricuspid valve replacement (TTVR) devices have been shown to be highly effective in reducing tricuspid regurgitation (TR), and interest in this therapy is growing with the recent commercial approval of the first orthotopic TTVR. Recent TTVR studies report preexisting cardiac implantable electronic device (CIED) transvalvular leads in ∼35% of patients, with entrapment during valve implantation. Concerns have been raised regarding the safety of entrapping leads and counterbalanced against the risks of transvenous lead extraction (TLE) when indicated. This Heart Valve Collaboratory consensus document attempts to define the patient population with CIED lead-associated or lead-induced TR, describe the risks of lead entrapment during TTVR, delineate the risks and benefits of TLE in this setting, and develop a management algorithm for patients considered for TTVR. An electrophysiologist experienced in CIED management should be part of the multidisciplinary heart team and involved in shared decision making.

Normative Values of Echocardiographic Chamber Size and Function in Older Healthy Adults: The Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: Echocardiographic (2-dimensional echocardiography) thresholds indicating disease or impaired functional status compared with normal physiological aging in individuals aged ≥65 years are not clearly defined. In the present study, we sought to establish standard values for 2-dimensional echocardiography parameters related to chamber size and function in older adults without cardiopulmonary or cardiometabolic conditions. METHODS: In this cross-sectional study of 3032 individuals who underwent 2-dimensional echocardiography at exam 6 in the MESA (Multi-Ethnic Study of Atherosclerosis), 608 participants fulfilled our inclusion criteria of healthy aging, with normative values defined as the mean ± 1.96 standard deviation and compared across sex and race and ethnicity. Functional status measures included NT-proBNP (N-terminal pro-B-type natriuretic peptide), 6-minute walk distance, and Kansas City Cardiomyopathy Questionnaire. Prognostic performance using MESA cutoffs was compared with established guideline cutoffs using time-to-event analysis. RESULTS: The normative aging cohort (69.5±7.0 years, 46.2% male, 47.5% White) had lower NT-proBNP, higher 6-minute walk distance, and higher (better) Kansas City Cardiomyopathy Questionnaire summary values. Women had significantly smaller chamber sizes and better biventricular systolic function. White participants had the largest chamber dimensions, whereas Chinese participants had the smallest, even after adjustment for body size. Current guidelines identified 81.6% of healthy older adults in MESA as having cardiac abnormalities. CONCLUSIONS: Among a large, diverse group of healthy older adults, we found significant differences in cardiac structure and function by sex and race/ethnicity, which may signal sex-specific cardiac remodeling with advancing age. It is crucial for existing guidelines to consider the observed and clinically significant differences in cardiac structure and function associated with healthy aging. Our study highlights that existing guidelines, which grade abnormalities in echocardiographic cardiac chamber size and function based on younger individuals, may not adequately address the anticipated changes associated with normal aging.

Echocardiographic Detection of Regional Wall Motion Abnormalities Using Artificial Intelligence Compared to Human Readers.

BACKGROUND: Although regional wall motion abnormality (RWMA) detection is foundational to transthoracic echocardiography, current methods are prone to interobserver variability. We aimed to develop a deep learning (DL) model for RWMA assessment and compare it to expert and novice readers. METHODS: We used 15,746 transthoracic echocardiography studies-including 25,529 apical videos-which were split into training, validation, and test datasets. A convolutional neural network was trained and validated using apical 2-, 3-, and 4-chamber videos to predict the presence of RWMA in 7 regions defined by coronary perfusion territories, using the ground truth derived from clinical transthoracic echocardiography reports. Within the test cohort, DL model accuracy was compared to 6 expert and 3 novice readers using F1 score evaluation, with the ground truth of RWMA defined by expert readers. Significance between the DL model and novices was assessed using the permutation test. RESULTS: Within the test cohort, the DL model accurately identified any RWMA with an area under the curve of 0.96 (0.92-0.98). The mean F1 scores of the experts and the DL model were numerically similar for 6 of 7 regions: anterior (86 vs 84), anterolateral (80 vs 74), inferolateral (83 vs 87), inferoseptal (86 vs 86), apical (88 vs 87), inferior (79 vs 81), and any RWMA (90 vs 94), respectively, while in the anteroseptal region, the F1 score of the DL model was lower than the experts (75 vs 89). Using F1 scores, the DL model outperformed both novices 1 (P = .002) and 2 (P = .02) for the detection of any RWMA. CONCLUSIONS: Deep learning provides accurate detection of RWMA, which was comparable to experts and outperformed a majority of novices. Deep learning may improve the efficiency of RWMA assessment and serve as a teaching tool for novices.

Optimización de la interpretación de ecocardiogramas con la utilización de Machine Learning en el estudio WASE / Optimizing Echocardiograms Interpretation with the Application of Machine Learning in the WASE Study

RESUMEN Introducción: El número creciente de estudios ecocardiográficos y la necesidad de cumplir rigurosamente con las recomendaciones de guías internacionales de cuantificación, ha llevado a que los cardiólogos deban realizar tareas sumamente extensas y repetitivas, como parte de la interpretación y análisis de cantidades de información cada vez más abrumadoras. Novedosas técnicas de machine learning (ML), diseñadas para reconocer imágenes y realizar mediciones en las vistas adecuadas, están siendo cada vez más utilizadas para responder a esta necesidad evidente de automatización de procesos. Objetivos: Nuestro objetivo fue evaluar un modelo alternativo de interpretación y análisis de estudios ecocardiográficos, basado fundamentalmente en la utilización de software de ML, capaz de identificar y clasificar vistas y realizar mediciones estandarizadas de forma automática. Material y métodos: Se utilizaron imágenes obtenidas en 2000 sujetos normales, libres de enfermedad, de los cuales 1800 fueron utilizados para desarrollar los algoritmos de ML y 200 para su validación posterior. Primero, una red neuronal convolucional fue desarrollada para reconocer 18 vistas ecocardiográficas estándar y clasificarlas de acuerdo con 8 grupos (stacks) temáticos. Los resultados de la identificación automática fueron comparados con la clasificación realizada por expertos. Luego, algoritmos de ML fueron desarrollados para medir automáticamente 16 parámetros de eco Doppler de evaluación clínica habitual, los cuales fueron comparados con las mediciones realizadas por un lector experto. Finalmente, comparamos el tiempo necesario para completar el análisis de un estudio ecocardiográfico con la utilización de métodos manuales convencionales, con el tiempo necesario con el empleo del modelo que incorpora ML en la clasificación de imágenes y mediciones ecocardiográficas iniciales. La variabilidad inter e intraobservador también fue analizada. Resultados: La clasificación automática de vistas fue posible en menos de 1 segundo por estudio, con una precisión de 90 % en imágenes 2D y de 94 % en imágenes Doppler. La agrupación de imágenes en stacks tuvo una precisión de 91 %, y fue posible completar dichos grupos con las imágenes necesarias en 99% de los casos. La concordancia con expertos fue excelente, con diferencias similares a las observadas entre dos lectores humanos. La incorporación de ML en la clasificación y medición de imágenes ecocardiográficas redujo un 41 % el tiempo de análisis y demostró menor variabilidad que la metodología de interpretación convencional. Conclusión: La incorporación de técnicas de ML puede mejorar significativamente la reproducibilidad y eficiencia de las interpretaciones y mediciones ecocardiográficas. La implementación de este tipo de tecnologías en la práctica clínica podría resultar en reducción de costos y aumento en la satisfacción del personal médico.

ABSTRACT Background: The growing number of echocardiographic tests and the need for strict adherence to international quantification guidelines have forced cardiologists to perform highly extended and repetitive tasks when interpreting and analyzing increasingly overwhelming amounts of data. Novel machine learning (ML) techniques, designed to identify images and perform measurements at relevant visits, are becoming more common to meet this obvious need for process automation. Objectives: Our objective was to evaluate an alternative model for the interpretation and analysis of echocardiographic tests mostly based on the use of ML software in order to identify and classify views and perform standardized measurements automatically. Methods: Images came from 2000 healthy subjects, 1800 of whom were used to develop ML algorithms and 200 for subsequent validation. First, a convolutional neural network was developed in order to identify 18 standard echocardiographic views and classify them based on 8 thematic groups (stacks). The results of automatic identification were compared to classification by experts. Later, ML algorithms were developed to automatically measure 16 Doppler scan parameters for regular clinical evaluation, which were compared to measurements by an expert reader. Finally, we compared the time required to complete the analysis of an echocardiographic test using conventional manual methods with the time needed when using the ML model to classify images and perform initial echocardiographic measurements. Inter- and intra-observer variability was also analyzed. Results: Automatic view classification was possible in less than 1 second per test, with a 90% accuracy for 2D images and a 94% accuracy for Doppler scan images. Stacking images had a 91% accuracy, and it was possible to complete the groups with any necessary images in 99% of cases. Expert agreement was outstanding, with discrepancies similar to those found between two human readers. Applying ML to echocardiographic imaging classification and measurement reduced time of analysis by 41% and showed lower variability than conventional reading methods. Conclusion: Application of ML techniques may significantly improve reproducibility and efficiency of echocardiographic interpretations and measurements. Using this type of technologies in clinical practice may lead to reduced costs and increased medical staff satisfaction.

Limitations of apical sparing pattern in cardiac amyloidosis: a multicentre echocardiographic study.

AIMS: Although impaired left ventricular (LV) global longitudinal strain (GLS) with apical sparing is a feature of cardiac amyloidosis (CA), its diagnostic accuracy has varied across studies. We aimed to determine the ability of apical sparing ratio (ASR) and most common echocardiographic parameters to differentiate patients with confirmed CA from those with clinical and/or echocardiographic suspicion of CA but with this diagnosis ruled out. METHODS AND RESULTS: We identified 544 patients with confirmed CA and 200 controls (CTRLs) as defined above (CTRL patients). Measurements from transthoracic echocardiograms were performed using artificial intelligence software (Us2.AI, Singapore) and audited by an experienced echocardiographer. Receiver operating characteristic curve analysis was used to evaluate the diagnostic performance and optimal cut-offs for the differentiation of CA patients from CTRL patients. Additionally, a group of 174 healthy subjects (healthy CTRL) was included to provide insight on how patients and healthy CTRLs differed echocardiographically. LV GLS was more impaired (-13.9 ± 4.6% vs. -15.9 ± 2.7%, P < 0.0005), and ASR was higher (2.4 ± 1.2 vs. 1.7 ± 0.9, P < 0.0005) in the CA group vs. CTRL patients. Relative wall thickness and ASR were the most accurate parameters for differentiating CA from CTRL patients [area under the curve (AUC): 0.77 and 0.74, respectively]. However, even with the optimal cut-off of 1.67, ASR was only 72% sensitive and 66% specific for CA, indicating the presence of apical sparing in 32% of CTRL patients and even in 6% healthy subjects. CONCLUSION: Apical sparing did not prove to be a CA-specific biomarker for accurate identification of CA, when compared with clinically similar CTRLs with no CA.

Prevalence of valvular heart disease in cardiac amyloidosis and impact on survival.

BACKGROUND: Limited data exists on the prognostic impact of valvular heart disease in cardiac amyloidosis (CA). We therefore sought to define the prevalence of valvular disease in patients with CA and assess the effects of significant valve disease on survival. METHODS: This multi-center retrospective cohort study included consecutive patients with confirmed transthyretin (TTR) or light chain (AL) amyloidosis. Echocardiographic data closest to the date of amyloid diagnosis was reviewed, and severity was graded according to ASE guidelines. Kaplan-Meier survival analysis was performed to compare survival between patients with moderate or greater valve disease against those with mild or less disease. RESULTS: We included 345 patients (median age 76 years; 73 % men; 110 AL, 235TTR). The median survival for the total patient cohort with cardiac amyloidosis was 2.92 years, with 30 % of patients surviving at five years after their diagnosis. Median survival comparing AL vs ATTR was 2.58 years vs 2.82 years (p = 0.67) The most common valvular abnormalities in the total cohort were mitral (62 %) and tricuspid (66 %).regurgitation There was a statistically significant difference in median survival between patients with no or mild MR compared to those with moderate or severe MR (2.92 years vs 3.35 years, p = 0.0047) (Fig. 5). There was a statistically significant difference in median survival in patients with no or mild TR compared to those with moderate or severe TR (3.35 years vs 2.3 years, p = 0.015). CONCLUSION: Our study demonstrates a significant prevalence of mitral and tricuspid regurgitation in CA, with patients with moderate to severe MR and TR having a poorer prognosis.

Right Ventricular Thrombus on Echocardiography.

Right ventricular thrombi (RVTs) have been almost exclusively studied in patients with pulmonary embolism (PE). The implications of an isolated RVT, a finding typically encountered on transthoracic echocardiography (TTE), are lacking. In this study, we sought to identify the echocardiographic and clinical features associated with the presence of RVTs. Between 1998 and 2023, 138 patients with RVT documented on TTE were retrospectively identified. Demographic data, presence of intracardiac devices, hypercoagulable conditions, history of deep vein thrombosis (DVT), PE, and/or left ventricular thrombus were abstracted from electronic chart review. Measurements of right and left ventricular size, and function were performed on TTE. Of the total population of patients with RVT, <1/2 had intracardiac devices, 29% had a documented hypercoagulable state (e.g., cancer or a clotting disorder). Most patients had dilated (77%) and dysfunctional (72%) right ventricles. Approximately 50% of RVTs were discovered in nonstandard imaging planes, suggesting that the presence of RVT is likely underestimated in clinical practice. Of those evaluated for PE, 80% had PE. Of those evaluated for DVT, 53% had DVT. In conclusion, further investigations are warranted to better guide when to investigate the right ventricle for RVTs on TTE and the impact of RVTs on patient outcomes.

Three-dimensional echocardiographic evaluation of longitudinal and non-longitudinal components of right ventricular contraction: results from the World Alliance of Societies of Echocardiography study.

AIMS: Right ventricular (RV) functional assessment is mainly limited to its longitudinal contraction. Dedicated three-dimensional echocardiography (3DE) software enabled the separate assessment of the non-longitudinal components of RV ejection fraction (EF). The aims of this study were (i) to establish normal values for RV 3D-derived longitudinal, radial, and anteroposterior EF (LEF, REF, and AEF, respectively) and their relative contributions to global RVEF, (ii) to calculate 3D RV strain normal values, and (iii) to determine sex-, age-, and race-related differences in these parameters in a large group of normal subjects (WASE study). METHODS AND RESULTS: 3DE RV wide-angle datasets from 1043 prospectively enrolled healthy adult subjects were analysed to generate a 3D mesh model of the RV cavity (TomTec). Dedicated software (ReVISION) was used to analyse RV motion along the three main anatomical planes. The EF values corresponding to each plane were identified as LEF, REF, and AEF. Relative contributions were determined by dividing each EF component by the global RVEF. RV strain analysis included longitudinal, circumferential, and global area strains (GLS, GCS, and GAS, respectively). Results were categorized by sex, age (18-40, 41-65, and >65 years), and race. Absolute REF, AEF, LEF, and global RVEF were higher in women than in men (P < 0.001). With aging, both sexes exhibited a decline in all components of longitudinal shortening (P < 0.001), which was partially compensated in elderly women by an increase in radial contraction. Black subjects showed lower RVEF and GAS values compared with white and Asian subjects of the same sex (P < 0.001), and black men showed significantly higher RV radial but lower longitudinal contributions to global RVEF compared with Asian and white men. CONCLUSION: 3DE evaluation of the non-longitudinal components of RV contraction provides additional information regarding RV physiology, including sex-, age-, and race-related differences in RV contraction patterns that may prove useful in disease states involving the right ventricle.

Normative Values of Echocardiographic Chamber Size and Function in Older Healthy Adults: The Multi-Ethnic Study of Atherosclerosis.

Background: Echocardiographic (2DE) thresholds indicating disease or impaired functional status compared to normal physiologic aging in individuals ≥ 65 years are not clearly defined. In the present study, we sought to establish standard values for 2DE parameters related to chamber size and function in older adults without cardiopulmonary or cardiometabolic conditions. Methods: In this cross-sectional study of 3032 individuals who underwent 2DE at Exam 6 in the Multi-Ethnic Study of Atherosclerosis (MESA), 608 participants fulfilled our inclusion criteria, with normative values defined as the mean value ± 1.96 standard deviations and compared across sex and race/ethnicity. Functional status measures included NT-proBNP, 6-minute walk distance [6MWD], and Kansas City Cardiomyopathy Questionnaire [KCCQ]. Prognostic performance using MESA cutoffs was compared to established guideline cutoffs using time-to-event analysis. Results: Participants meeting our inclusion criteria (69.5 ± 7.0 years, 46.2% male, 47.5% White) had lower NT-proBNP, higher 6MWD, and higher (better) KCCQ summary values. Women had significantly smaller chamber sizes and better biventricular systolic function. White participants had the largest chamber dimensions, while Chinese participants had the smallest, even after adjustment for body size. Current guidelines identified 81.6% of healthy older adults in MESA as having cardiac abnormalities. Conclusions: Among a large, diverse group of healthy older adults, we found significant differences in cardiac structure and function across sexes and races/ethnicities, which may signal sex-specific cardiac remodeling with advancing age. It is crucial for existing guidelines to consider the observed and clinically significant differences in cardiac structure and function associated with healthy aging. Our study highlights that existing guidelines, which grade abnormalities in echocardiographic cardiac chamber size and function based on younger individuals, may not adequately address the anticipated changes associated with normal aging.

Deep learning assisted measurement of echocardiographic left heart parameters: improvement in interobserver variability and workflow efficiency.

Machine learning techniques designed to recognize views and perform measurements are increasingly used to address the need for automation of the interpretation of echocardiographic images. The current study was designed to determine whether a recently developed and validated deep learning (DL) algorithm for automated measurements of echocardiographic parameters of left heart chamber size and function can improve the reproducibility and shorten the analysis time, compared to the conventional methodology. The DL algorithm trained to identify standard views and provide automated measurements of 20 standard parameters, was applied to images obtained in 12 randomly selected echocardiographic studies. The resultant measurements were reviewed and revised as necessary by 10 independent expert readers. The same readers also performed conventional manual measurements, which were averaged and used as the reference standard for the DL-assisted approach with and without the manual revisions. Inter-reader variability was quantified using coefficients of variation, which together with analysis times, were compared between the conventional reads and the DL-assisted approach. The fully automated DL measurements showed good agreement with the reference technique: Bland-Altman biases 0-14% of the measured values. Manual revisions resulted in only minor improvement in accuracy: biases 0-11%. This DL-assisted approach resulted in a 43% decrease in analysis time and less inter-reader variability than the conventional methodology: 2-3 times smaller coefficients of variation. In conclusion, DL-assisted approach to analysis of echocardiographic images can provide accurate left heart measurements with the added benefits of improved reproducibility and time savings, compared to conventional methodology.

Anomalous right coronary artery from the main pulmonary artery (ARCAPA): Incidental finding in an asymptomatic septuagenarian.

Anomalous right coronary artery (RCA) from the main pulmonary artery (ARCAPA) is a rare finding. Clinical presentations range from asymptomatic to sudden death. We present the case of ARCAPA in a septuagenarian initially suspected on a screening chest computed tomography (CT) and later confirmed on cardiac CT. A summary of important points related to this entity is also discussed.

Cardiovascular computed tomography for the detection of quadricuspid aortic valve: A case report.

Aortic regurgitation (AR) represents a significant cause of morbidity and mortality. Due to its low cost and widespread availability, echocardiography remains the frontline for aortic valve (AV) assessment. However, poor sonographic windows may limit the assessment of valve morphology with this technique. Cardiovascular computed tomography (CCT) is increasingly utilized prior to structural AV interventions. Due to its excellent spatial resolution, CCT provides exceptional characterization of aortic leaflets. Accordingly, we present a case of a quadricuspid valve diagnosed by CCT. Here, CCT led to a new diagnosis of quadricuspid valve, highlighting the potential for CCT for the characterization of aortic leaflet morphology. CCT may be particularly useful in patients with contraindications to transesophageal echocardiography or those undergoing structural or robotic interventions.

Preservation of Circumferential and Radial Left Ventricular Function as a Mitigating Mechanism for Impaired Longitudinal Strain in Early Cardiac Amyloidosis.

BACKGROUND: In patients with cardiac amyloidosis (CA), left ventricular ejection fraction (LVEF) is frequently preserved, despite commonly reduced global longitudinal strain (GLS). We hypothesized that nonlongitudinal contraction may initially serve as a mitigating mechanism to maintain cardiac output and studied the relationship between global circumferential (GCS) and radial (GRS) strain with LVEF and extracellular volume (ECV), a marker of amyloid burden. METHODS: Patients with CA who underwent cardiac magnetic resonance (CMR; n = 140, 70.7 ± 11.5 years, 66% male) or echocardiography (n = 67, 71 ± 13 years, 66% male) and normal controls (CMR, n = 20; echocardiography, n = 45) were retrospectively identified, and GCS, GLS, and GRS were quantified using feature-tracking CMR or speckle-tracking echocardiography and compared between CA patients with preserved and reduced LVEF (CAHFpEF, CAHFrEF) and controls. The prevalence of impaired strain (magnitudes <2.5th percentile of the controls) was compared between CAHFpEF and CAHFrEF and between ECV quartiles. RESULTS: While echocardiography-derived GLS was impaired in both CAHFpEF (-13.4% ± 3.1%, P < .003) and CAHFrEF (-9.1% ± 3.2%, P < .003), compared with controls (-20.8% ± 2.4%), GCS was more impaired in CAHFrEF compared with both controls (-15.6% ± 5.0% vs -32.3% ± 3.3%, P < .003) and CAHFpEF (-30.4% ± 5.7%, P < .003) and did not differ between CAHFpEF and controls (P = .24). The prevalence of abnormal CMR-derived GCS (P < .0001) and GRS (P < .0001) but not GLS (P = .054) varied significantly across ECV quartiles. CONCLUSIONS: Among CA patients with preserved LVEF, preserved GCS and GRS, despite near-universally impaired GLS, may be explained by an initial predominantly subendocardial involvement, where mostly longitudinal fibers are located. If confirmed in future studies, these findings may facilitate identification of patients with early stages of CA, when treatments may be most effective.

How Often Does Apical Sparing of Longitudinal Strain Indicate the Presence of Cardiac Amyloidosis?

Echocardiographic diagnosis of cardiac amyloidosis (CA) is frequently suggested by the presence of a left ventricular (LV) apical sparing pattern (ASP) on longitudinal strain (LS) assessment, the so-called "cherry on top" pattern, defined by strain magnitude preserved exclusively at the apex. However, it is unclear how frequently this strain pattern truly represents CA. This study aimed to evaluate the predictive value of ASP in the diagnosis of CA. We retrospectively identified consecutive adult patients who had the following studies performed within an 18-month period: (1) transthoracic echocardiogram and (2) either (a) cardiac magnetic resonance imaging, (b) Technetium-Pyrophosphate (PYP) imaging, or (c) endomyocardial biopsy. LS was retrospectively measured in the apical 4-, 3-, and 2-chamber views in patients who had adequate noncontrast images (n = 466). An apical sparing ratio (ASR) was calculated as (average apical strain)/[(average basal strain) + (average midventricular strain)]. Patients with ASR ≥1 were evaluated for the presence/absence of CA, using established criteria. Basic LV parameters were also measured. A total of 33 patients (7.1%) had ASP. Nine of these patients (27%) had "confirmed" CA, 2 (6.1%) "highly probable" CA, 1 (3.0%) "possible" CA, and 21 (64%) no evidence of CA. When comparing patients with and without confirmed CA, there were no significant differences in ASR, average global LS, ejection fraction, or LV mass. Patients with confirmed CA were older (76 ± 9 vs 59 ± 18 years, p = 0.01) and had thicker posterior wall (15 ± 3 vs 11 ± 3 mm, p = 0.004) with a trend toward thicker septal wall (15 ± 2 vs 12 ± 4 mm, p = 0.05). In conclusion, the presence of ASP on LS represents confirmed or highly probable CA in only 1/3 of patients and is more likely to indicate true CA in older patients with increased LV wall thickness. Although a larger, prospective study is needed to confirm these findings, 1/3 should be considered as a large diagnostic yield that justifies further testing, given the poor outcomes associated with CA diagnosis.

Multimodality Imaging of Right Heart Function: JACC Scientific Statement.

Right ventricular (RV) size and function assessed by multimodality imaging are associated with outcomes in a variety of cardiovascular diseases. Understanding RV anatomy and physiology is essential in appreciating the strengths and weaknesses of current imaging methods and gives these measurements greater context. The adaptation of the right ventricle to different types and severity of stress, particularly over time, is specific to the cardiovascular disease process. Multimodality imaging parameters, which determine outcomes, reflect the ability to image the initial and longitudinal RV response to stress. This paper will review the standard and novel imaging methods for assessing RV function and the impact of these parameters on outcomes in specific disease states.