Philip N. Hawkins

BACKGROUND: Diagnosing cardiac amyloidosis (CA) on echocardiography can be challenging due to the imaging overlap between CA and more prevalent causes of a hypertrophic phenotype. This study sought to (1) evaluate the performance of artificial-intelligence (AI) derived measurements incorporated into the established multiparametric echocardiographic scoring system to detect CA; (2) develop and validate an AI-based deep-learning model for video-based detection of CA on echocardiography. METHODS: The study population comprised 5776 patients (CA, 2756; controls, 3020). The training data set included patients from the UK National Amyloidosis Center and Taiwan MacKay Memorial Hospital (CA, 2241; controls, 2130). External test data sets were obtained from the US Duke University Health System (CA, 334; left ventricular hypertrophy controls, 668) and Japan National Cerebral and Cardiovascular Center (CA, 181; left ventricular hypertrophy controls, 222). RESULTS: The multiparametric echocardiographic score computed using AI-derived measurements achieved an accuracy of 79.5% (sensitivity, 75.4%; specificity, 81.5%) in the United States cohort and 79.7% (sensitivity, 81.6%; specificity, 78.1%) in the Japan cohort. The deep-learning model demonstrated accuracies of 96.2% (sensitivity, 96.8%; specificity, 95.7%) and 95.8% (sensitivity, 97.3%; specificity, 94.3%) in the internal validation and internal test sets, respectively. External validation of the deep-learning model showed accuracies of 87.5% (sensitivity, 86.6%; specificity, 87.9%) in the United States and 88.4% (sensitivity, 92.3%; specificity, 85.3%) in the Japanese cohort. Subgroup analysis demonstrated that the deep-learning model showed robust discrimination of CA from other hypertrophic phenocopies: CA versus hypertension (area under the curve [AUC], 0.92 [95% CI, 0.91–0.94]), CA versus hypertrophic cardiomyopathy (AUC, 0.91 [95% CI, 0.87–0.94]), CA versus aortic stenosis (AUC, 0.93 [95% CI, 0.90–0.95]), CA versus chronic kidney disease (AUC, 0.93 [95% CI, 0.91–0.95]). The deep-learning model was able to classify a greater proportion of patients compared with the AI-derived multiparametric echocardiographic score and achieved superior diagnostic accuracy (AUC, 0.93 [95% CI, 0.91–0.95] versus AUC, 0.88 [95% CI, 0.85–0.90]; P <0.001). CONCLUSIONS: Both the multiparametric echocardiographic score computed from AI-derived measurements and the fully automated deep-learning model can accurately identify patients with CA in globally diverse cohorts, with the deep-learning model providing superior performance.

Transthyretin amyloid cardiomyopathy (ATTR-CM) is a progressive disorder marked by amyloid deposition in the heart, ultimately impairing cardiac function. Recent treatment advances have paralleled an evolving understanding of ATTR-CM pathophysiology. One emerging hypothesis suggests that an imbalance between in vivo amyloid production and natural clearance may drive disease progression, a conceptual framework that still requires validation. Transthyretin (TTR) stabilizers, such as tafamidis and acoramidis, mitigate amyloid formation by promoting the native tetrameric conformation of circulating TTR, thereby slowing functional decline and prolonging survival. Similarly, TTR gene silencers inhibit hepatic TTR synthesis, and gene-editing therapy with nexiguran ziclumeran offers an additional strategy to reduce amyloid production. However, these approaches do not enhance the body’s limited capacity to clear existing amyloid deposits, underscoring the need for novel agents that accelerate amyloid removal. Promisingly, monoclonal antibodies targeting TTR amyloid are under development, with early clinical trials suggesting that this passive immunotherapy may reverse disease progression and improve heart function. Ultimately, optimal management of ATTR-CM will require further elucidation of the complex interplay between amyloid formation, its structural and functional impacts, its clearance mechanisms, and the potential for myocardial reverse remodelling.

Background and Aims: Cardiovascular magnetic resonance (CMR) and extracellular volume (ECV) mapping can measure amyloid burden in vivo. This study sought to assess the natural history of transthyretin amyloid cardiomyopathy (ATTR-CM) in terms of amyloid deposition burden (ECV) over time, changes in cardiac amyloid load following treatment with patisiran, and the association between change in ECV and mortality. Methods: All 189 patients (untreated = 119, patisiran = 70) underwent assessment with CMR at baseline, 160 patients (untreated = 94, patisiran = 66) had a 1-year follow-up CMR and 75 patients (untreated = 42, patisiran = 33) had a 2-year follow-up CMR, of whom 36 patients (untreated = 17, patisiran = 29) had follow-up CMR at both timepoints. CMR response was graded by change in ECV: progression (≥5% increase), stable (<5% change) and regression (≥5% decrease). Results: In untreated patients, 36% progressed at 1 year which significantly increased to 62% at 2 years. Mean increase in ECV of 4.1% (after 1 year) and 6.8% (after 2 years) was observed and associated with significant worsening in biomarkers and structural parameters. No significant difference in mean ECV was observed following treatment with patisiran at both timepoints. Stable ECV was observed in 88% of patients (after 1 year) and 100% of patients (after 2 years). Structural parameters remained stable following treatment. ECV progression after 1 year was independently associated with mortality after adjusting for known predictors (hazard ratio 2.021; 95% confidence interval 1.081–3.781; P = .028). Conclusions: CMR with ECV mapping can track changes in cardiac amyloid burden and treatment response in ATTR-CM, with changes in ECV being independently associated with outcomes.

BACKGROUND: The extent of myocardial bone tracer uptake with technetium pyrophosphate, hydroxymethylene diphosphonate, and 3,3-diphosphono-1,2-propanodicarboxylate in transthyretin amyloid cardiomyopathy (ATTR-CM) might reflect cardiac amyloid burden and be associated with outcome. METHODS: Consecutive patients with ATTR-CM who underwent diagnostic bone tracer scintigraphy with acquisition of whole-body planar and cardiac single-photon emission computed tomography (SPECT) images from the National Amyloidosis Centre and 4 Italian centers were included. Cardiac uptake was defined according to the Perugini classification: 0=absent cardiac uptake; 1=mild uptake less than bone; 2=moderate uptake equal to bone; and 3=high uptake greater than bone. Extent of right ventricular (RV) uptake was defined as focal (basal segment of the RV free wall only) or diffuse (extending beyond basal segment) on the basis of SPECT imaging. The primary outcome was all-cause mortality. RESULTS: Among 1422 patients with ATTR-CM, RV uptake accompanying left ventricular uptake was identified by SPECT imaging in 100% of cases at diagnosis. Median follow-up in the whole cohort was 34 months (interquartile range, 21 to 50 months), and 494 patients died. By Kaplan-Meier analysis, diffuse RV uptake on SPECT imaging (n=936) was associated with higher all-cause mortality compared with focal (n=486) RV uptake (77.9% versus 22.1%; P P =0.27 in grade 2 versus grade 3). On multivariable analysis, after adjustment for age at diagnosis (hazard ratio [HR], 1.03 [95% CI, 1.02–1.04]; P TTR variant (HR, 1.42 [95% CI, 1.20–1.81]; P =0.004), National Amyloidosis Centre stage (each category, P P =0.043), E/e’ (HR, 1.02 [95% CI, 1.007–1.03]; P =0.004), right atrial area index (HR, 1.05 [95% CI, 1.02–1.08]; P =0.001), and left ventricular global longitudinal strain (HR, 1.06 [95% CI, 1.03–1.09]; P P P P =0.02, respectively). CONCLUSIONS: Diffuse RV uptake of bone tracer on SPECT imaging is associated with poor outcomes in patients with ATTR-CM and is an independent prognostic marker at diagnosis.

Background: Transthyretin cardiac amyloidosis (ATTR‐CA) is a progressive and ultimately fatal cardiomyopathy. Biomarkers reflecting multiorgan dysfunction are of increasing importance in patients with heart failure; however, their significance in ATTR‐CA remains largely unknown. The aims of this study were to characterize the multifaceted nature of ATTR‐CA using blood biomarkers and assess the association between blood biomarkers and prognosis. Methods and Results: This is a retrospective cohort study of 2566 consecutive patients diagnosed with ATTR‐CA between 2007 and 2023. Anemia (39%), high urea (52%), hyperbilirubinemia (18%), increased alkaline phosphatase (16%), increased CRP (C‐reactive protein; 27%), and increased troponin (98.2%) were common findings in the overall population, whereas hyponatremia (6%) and hypoalbuminemia (2%) were less common. These abnormalities were most common in patients with p.(V142I) hereditary ATTR‐CA, and became more prevalent as the severity of cardiac disease increased. Multivariable Cox regression analysis demonstrated that anemia (hazard ratio [HR], 1.19 [95% CI, 1.04–1.37]; P =0.01), high urea (HR, 1.23 [95% CI, 1.04–1.45]; P =0.01), hyperbilirubinemia (HR, 1.32 [95% CI, 1.13–1.57; P =0.001), increased alkaline phosphatase (HR, 1.20 [95% CI, 1.01–1.42; P =0.04), hyponatremia (HR, 1.65 [95% CI, 1.28–2.11]; P 56 ng/L (HR, 1.72 [95% CI, 1.46–2.03]; P P =0.003) and in a subgroup of the overall population with a left ventricular ejection fraction ≤40% (HR, 1.39 [95% CI, 1.08–1.81]; P =0.01). Conclusions: Cardiac and noncardiac biomarker abnormalities were common and reflect the complex and multifaceted nature of ATTR‐CA, with a wide range of biomarkers remaining independently associated with mortality. Clinical trials are needed to investigate whether biomarker abnormalities represent modifiable risk factors that if specifically targeted could improve outcomes.

Transthyretin cardiac amyloidosis (ATTR-CA) has been traditionally considered a rare and inexorably fatal condition. ATTR-CA now is an increasingly recognised cause of heart failure and mortality worldwide with effective pharmacological treatments. Advances in non-invasive diagnosis, coupled with the development of effective treatments, have transformed the diagnosis of ATTR-CA, which is now possible without recourse to endomyocardial biopsy in around 70% of cases. Many patients are now diagnosed at an earlier stage. Echocardiography and cardiac magnetic resonance have enabled identification of patients with possible ATTR-CA and more accurate prognostic stratification. Therapies able to slow or halt ATTR-CA progression and increase survival are now available and there is also evidence that patients may benefit from specific conventional heart failure medications. A wide horizon of possibilities is unfolding and awaits discovery.

BACKGROUND: Apo AI amyloidosis (AApoAI) and Apo AIV amyloidosis (AApoAIV) are rare but increasingly recognized causes of cardiac amyloidosis (CA). We sought to define the cardiac phenotype in AApoAI and AApoAIV using multimodality imaging. METHODS: We identified all patients with AApoAI and AApoAIV assessed at our center between 2000 and 2021, and 2 cohorts of patients with immunoglobulin light-chain amyloidosis (AL) and transthyretin amyloidosis matched for age, sex, and cardiac involvement. RESULTS: Forty-five patients had AApoAI, 13 (29%) of whom had cardiac involvement, 32 (71%) renal involvement, 28 (62%) splenic involvement, 27 (60%) hepatic involvement, and 7 (16%) laryngeal involvement. AApoAI-CA commonly presented with heart failure (n=8, 62%) or dysphonia (n=7, 54%). The Arg173Pro variant universally caused cardiac and laryngeal involvement (n=7, 100%). AApoAI-CA was associated with right-sided involvement, with a thicker right ventricular free wall (8.6±1.9 versus 6.3±1.3 mm versus 7.7±1.2 mm, P =0.004), greater incidence of tricuspid stenosis (4 [31%] versus 0 [0%] versus 0 [0%], P =0.012) and tricuspid regurgitation (6 [46%] versus 1 [8%] versus 2 [15%], P =0.048) than AL-CA and transthyretin CA. Twenty-one patients had AApoAIV, and cardiac involvement was more common than in AApoAI (15 [71%] versus 13 [29%], P =0.001). AApoAIV-CA most commonly presented with heart failure (n=12, 80%), and a lower median estimated glomerular filtration rate than AL-CA and transthyretin CA (36 mL/[min·1.73 m²] versus 65 mL/[min·1.73 m²] versus 63 mL/[min·1.73 m²], P P =0.003), whereas cardiac uptake on bone scintigraphy was less common in AApoAIV-CA than AApoAI-CA (all grade 1) (14% versus 82%, P 172 and >30 months, respectively), and a lower risk of mortality than matched patients with AL-amyloidosis (AL versus AApoAI: hazard ratio, 4.54 [95% CI, 2.02–10.14]; P P =0.013). CONCLUSIONS: Dysphonia, multisystem involvement, or right-sided cardiac disease should raise suspicion of AApoAI-CA. AApoAIV-CA presents most commonly with heart failure and always displays classical CA imaging features, mimicking common forms of CA. Both AApoAI and AApoAIV are associated with a good prognosis and a lower risk of mortality than matched patients with AL-amyloidosis.