Reference Ranges, Diagnostic and Prognostic Utility of Native T1 Mapping and Extracellular Volume for Cardiac Amyloidosis: A Meta‐Analysis

Atlas of Regional Left Ventricular Scar in Nonischemic Cardiomyopathies: Substrates and Etiologies

Most acquired and inherited cardiomyopathies are characterized by regional left ventricular involvement and nonischemic myocardial scars, often with a disease-specific pattern. Irrespective of the etiology and pathophysiological mechanisms, myocardial disorders are invariably associated with cardiac fibrosis, which contributes to dysfunction and electrical instability. Accordingly, cardiac magnetic resonance plays a central role in the diagnostic work-up and prognostic risk stratification of cardiomyopathies, particularly with the increasing correlation between genetic background and specific disease phenotype. Starting from pattern and distribution of myocardial fibrosis at cardiac magnetic resonance, we provide a practical regional atlas of nonischemic myocardial scar to guide the diagnostic approach to nonischemic cardiomyopathies.

Role of endogenous T1ρ and its dispersion imaging in differential diagnosis of cardiac amyloidosis

BACKGROUND

Cardiovascular magnetic resonance (CMR) has demonstrated excellent performance in the diagnosis of cardiac amyloidosis (CA). However, misdiagnosis occasionally occurs because the morphological and functional features of CA are non-specific. This study was performed to determine the value of non-contrast CMR T1ρ in the diagnosis of CA.

METHODS

This prospective study included 45 patients with CA, 30 patients with hypertrophic cardiomyopathy (HCM), and 10 healthy controls (HCs). All participants underwent cine (whole heart), T1ρ mapping, pre- and post-contrast T1 mapping imaging (three slices), and late gadolinium enhancement using a 3T whole-body magnetic resonance imaging system. All participants underwent T1ρ at two spin-locking frequencies: 0 and 298 Hz. Extracellular volume (ECV) maps were obtained using pre- and post-contrast T1 maps. The myocardial T1ρ dispersion map, termed myocardial dispersion index (MDI), was also calculated. All parameters were measured in the left ventricular myocardial wall. Participants in the HC group were scanned twice on different days to assess the reproducibility of T1ρ measurements.

RESULTS

Excellent reproducibility was observed upon evaluation of the coefficient of variation between two scans (T1ρ [298 Hz]: 3.1%; T1ρ [0 Hz], 2.5%). The ECV (HC: 27.4 ± 2.8% vs HCM: 32.6 ± 5.8% vs CA: 46 ± 8.9%; p < 0.0001), T1ρ [0 Hz] (HC: 35.8 ± 1.7 ms vs HCM: 40.0 ± 4.5 ms vs CA: 51.4 ± 4.4 ms; p < 0.0001) and T1ρ [298 Hz] (HC: 41.9 ± 1.6 ms vs HCM: 48.8 ± 6.2 ms vs CA: 54.4 ± 5.2 ms; p < 0.0001) progressively increased from the HC group to the HCM group, and then the CA group. The MDI progressively decreased from the HCM group to the HC group, and then the CA group (HCM: 8.8 ± 2.8 ms vs HC: 6.1 ± 0.9 ms vs CA: 3.4 ± 2.1 ms; p < 0.0001). For differential diagnosis, the combination of MDI and T1ρ [298 Hz] showed the greatest sensitivity (98.3%) and specificity (95.5%) between CA and HCM, compared with the native T1 and ECV.

CONCLUSION

The T1ρ and MDI approaches can be used as non-contrast CMR imaging biomarkers to improve the differential diagnosis of patients with CA.

Native skeletal muscle T1-time on cardiac magnetic resonance: A predictor of outcome in patients with heart failure with preserved ejection fraction

BACKGROUND

Heart failure with preserved ejection fraction (HFpEF) is associated with heart failure (HF) hospitalizations and death. Previous studies have shown that altered muscle composition is associated with higher risk of adverse outcome in HFpEF patients.

AIM

The purpose of our study was to investigate the association between skeletal muscle composition, as measured by skeletal muscle T1-times on cardiac magnetic resonance (CMR) imaging, and adverse outcome.

METHODS

We measured skeletal muscle T1-times of the back muscles on standard CMR images in a prospective cohort of HFpEF patients. Cox regression models were used to test the association of skeletal muscle T1-times and adverse outcome defined as hospitalization for HF and/or cardiovascular death.

RESULTS

We included 101 patients (mean age 72±7 years, 71 % female) in our study. The median skeletal muscle T1-times were 842 ms (IQR 806-881 ms). In univariate analysis high muscle T1-time was associated with adverse outcome (HR=1.96 [95 % CI, 1.31-2.94] per every 100 ms increase; p=.001). After adjustment for age, sex, body mass index, left- and right ventricular ejection fraction, N-terminal pro-brain natriuretic peptide and myocardial native T1-times, native skeletal muscle T1-time remained an independent predictor for adverse outcome (HR=1.94 [95 % CI, 1.24-3.03] per every 100 ms increase; p=.004).

CONCLUSION

In patients with HFpEF, high skeletal muscle T1-times on standard CMR scans are associated with higher rates of HF hospitalizations and cardiovascular death.

CONDENSED ABSTRACT

Skeletal muscle abnormalities are common in patients with heart failure with preserved ejection fraction (HFpEF). The present study evaluates skeletal muscle composition, as quantified by native skeletal muscle T1-times of the back muscles on standard cardiac magnetic resonance imaging, and assessed the association with adverse outcome, defined as hospitalization for heart failure and/or cardiovascular death. In a prospective cohort of 101 patients with HFpEF, we found that high native skeletal muscle T1-times are associated with an increased risk for adverse outcome. These findings suggest that native skeletal muscle T1-time may serve as marker for improved risk prediction.

Pericardial Disease in Cardiac Amyloidosis: A Comprehensive Review

In patients with cardiac amyloidosis, pericardial involvement is common, with up to half of patients presenting with pericardial effusions. The pathophysiological mechanisms of pericardial pathology in cardiac amyloidosis include chronic elevations in right-sided filling pressures, myocardial and pericardial inflammation due to cytotoxic effects of amyloid deposits, and renal involvement with subsequent uremia and hypoalbuminemia. The pericardial effusions are typically small; however, several cases of life-threatening cardiac tamponade with hemorrhagic effusions have been described as a presenting clinical scenario. Constrictive pericarditis can also occur due to amyloidosis and its identification presents a clinical challenge in patients with cardiac amyloidosis who concurrently manifest signs of restrictive cardiomyopathy. Multimodality imaging, including echocardiography, cardiac computed tomography, and cardiac magnetic resonance imaging, is useful in the evaluation and management of this patient population. The recognition of pericardial effusion is important in the risk stratification of patients with cardiac amyloidosis as its presence confers a poor prognosis. However, specific treatment aimed at the effusions themselves is seldom indicated. Cardiac tamponade and constrictive pericarditis may necessitate pericardiocentesis and pericardiectomy, respectively.

Multi-parametric non-contrast cardiac magnetic resonance for the differentiation between cardiac amyloidosis and hypertrophic cardiomyopathy

AIM

To evaluate the ability of fast strain-encoded (SENC) cardiac magnetic resonance (CMR) derived myocardial strain and native T1 mapping to discriminate between hypertrophic cardiomyopathy (HCM) and cardiac amyloidosis.

METHODS

Ninety nine patients (57 with hypertrophic cardiomyopathy and 42 with cardiac amyloidosis) were systematically analysed. LV-ejection fraction, LV-mass index, septal wall thickness and native T1 mapping values were assessed. In addition, global circumferential and longitudinal strain and segmental circumferential and longitudinal strain in basal, mid-ventricular, and apical segments were calculated. A ratio was built by dividing native T1 values by basal segmental strain (T1-to-basal segmental strain ratio).

RESULTS

Myocardial strain was equally distributed in apical and basal segments in HCM patients, whereas an apical sparing with less impaired apical strain was noticed in cardiac amyloidosis (apical-to-basal-ratio of 1.01 ± 0.23 versus 1.20 ± 0.28, p < 0.001). T1 values were significantly higher in amyloidosis compared to HCM patients (1170.7 ± 66.4 ms versus 1078.3 ± 57.4ms, p < 0.001). The T1-to-basal segmental strain ratio exhibited high accuracy for the differentiation between the two clinical entities (Sensitivity = 85%, Specificity = 77%, AUC = 0.90, 95% CI = 0.81-0.95, p < 0.001). Multivariable analysis showed that age and the T1-to-basal-strain-ratio were the most robust factors for the differentiation between HCM and cardiac amyloidosis.

CONCLUSION

The T1-to-basal-segmental strain ratio, combining information from segmental circumferential and longitudinal strain and native T1 mapping aids the differentiation between HCM and cardiac amyloidosis with high accuracy and within a fast CMR protocol, obviating the need for contrast agent administration.

Imaging cardiac hypertrophy in hypertrophic cardiomyopathy and its differential diagnosis

PURPOSE OF REVIEW

The aim of this study was to review imaging of myocardial hypertrophy in hypertrophic cardiomyopathy (HCM) and its phenocopies. The introduction of cardiac myosin inhibitors in HCM has emphasized the need for careful evaluation of the underlying cause of myocardial hypertrophy.

RECENT FINDINGS

Advances in imaging of myocardial hypertrophy have focused on improving precision, diagnosis, and predicting prognosis. From improved assessment of myocardial mass and function, to assessing myocardial fibrosis without the use of gadolinium, imaging continues to be the primary tool in understanding myocardial hypertrophy and its downstream effects. Advances in differentiating athlete's heart from HCM are noted, and the increasing rate of diagnosis in cardiac amyloidosis using noninvasive approaches is especially highlighted due to the implications on treatment approach. Finally, recent data on Fabry disease are shared as well as differentiating other phenocopies from HCM.

SUMMARY

Imaging hypertrophy in HCM and ruling out other phenocopies is central to the care of patients with HCM. This space will continue to rapidly evolve, as disease-modifying therapies are under investigation and being advanced to the clinic.

Cardiac MRI-derived Extracellular Volume Fraction versus Myocardium-to-Lumen R1 Ratio at Postcontrast T1 Mapping for Detecting Cardiac Amyloidosis

Purpose

To evaluate the diagnostic performance of myocardium-to-lumen R1 (1/T1) ratio on postcontrast T1 maps for the detection of cardiac amyloidosis in a large patient sample.

Materials and Methods

This retrospective study included consecutive patients who underwent MRI-derived extracellular volume fraction (MRI ECV) analysis between March 2017 and July 2021 because of known or suspected heart failure or cardiomyopathy. Pre- and postcontrast T1 maps were generated using the modified Look-Locker inversion recovery sequence. Diagnostic performances of MRI ECV and myocardium-to-lumen R1 ratio on postcontrast T1 maps (a simplified index not requiring a native T1 map and hematocrit level data) for detecting cardiac amyloidosis were evaluated using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity.

Results

Of 352 patients (mean age, 63 years ± 16 [SD]; 235 men), 136 had cardiac amyloidosis. MRI ECV showed 89.0% (121 of 136; 95% CI: 82%, 94%) sensitivity and 98.6% (213 of 216; 95% CI: 96%, 100%) specificity for helping detect cardiac amyloidosis (cutoff value of 40% [AUC, 0.99 {95% CI: 0.97, 1.00}; P < .001]). Postcontrast myocardium-to-lumen R1 ratio showed 92.6% (126 of 136; 95% CI: 89%, 96%) sensitivity and 93.1% (201 of 216; 95% CI: 89%, 96%) specificity (cutoff value of 0.84 [AUC, 0.98 {95% CI: 0.95, 0.99}; P < .001]). There was no evidence of a difference in AUCs for each parameter (P = .10).

Conclusion

Postcontrast myocardium-to-lumen R1 ratio showed excellent diagnostic performance comparable to that of MRI ECV in the detection of cardiac amyloidosis.Keywords: MR Imaging, Cardiac, Heart, Cardiomyopathies Supplemental material is available for this article. © RSNA, 2023.

CT Extracellular Volume Fraction versus Myocardium-to-Lumen Signal Ratio for Cardiac Amyloidosis

Background Large studies on the diagnostic performance of CT-derived myocardial extracellular volume fraction (ECV) for detecting cardiac amyloidosis are lacking. A simple and practical index as a surrogate for CT ECV would be clinically useful. Purpose To compare the diagnostic performances between CT-derived myocardial ECV and myocardium-to-lumen signal ratio for the detection of cardiac amyloidosis in a large patient sample. Materials and Methods This retrospective study included patients who underwent CT ECV analysis because of suspected heart failure or cardiomyopathy between January 2018 and July 2021. CT ECV was quantified using routine pre-transcatheter aortic valve replacement planning cardiac CT, pre-atrial fibrillation ablation planning cardiac CT, or coronary CT angiography with the addition of unenhanced and delayed phase cardiac CT scans. The diagnostic performances of CT ECV and myocardium-to-lumen signal ratio in delayed phase cardiac CT (a simplified index not requiring unenhanced CT and hematocrit) for detecting cardiac amyloidosis were evaluated using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. Results Of 552 patients (mean age, 69 years ± 14 [SD]; 295 men), 41 had cardiac amyloidosis. The sensitivity of CT ECV for amyloidosis was 90% (37 of 41 patients [95% CI: 77, 97]), with a specificity of 92% (472 of 511 patients [95% CI: 90, 95]) and optimal ECV cutoff value of 37% (AUC, 0.97 [95% CI: 0.96, 0.99]). The sensitivity of myocardium-to-lumen signal ratio was 88% (36 of 41 patients [95% CI: 74, 96]), with a specificity of 92% (469 of 511 patients [95% CI: 89, 94]) and optimal myocardium-to-lumen signal ratio cutoff value of 0.87 (AUC, 0.96 [95% CI: 0.94, 0.97]; P = .27 for comparison with ECV). Conclusion CT-derived myocardial extracellular volume fraction and myocardium-to-lumen signal ratio showed comparable and excellent diagnostic performance in detecting cardiac amyloidosis in a large patient sample. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Williams in this issue.

Deep Learning to Classify AL versus ATTR Cardiac Amyloidosis MR Images

The aim of this work was to compare the classification of cardiac MR-images of AL versus ATTR amyloidosis by neural networks and by experienced human readers. Cine-MR images and late gadolinium enhancement (LGE) images of 120 patients were studied (70 AL and 50 TTR). A VGG16 convolutional neural network (CNN) was trained with a 5-fold cross validation process, taking care to strictly distribute images of a given patient in either the training group or the test group. The analysis was performed at the patient level by averaging the predictions obtained for each image. The classification accuracy obtained between AL and ATTR amyloidosis was 0.750 for cine-CNN, 0.611 for Gado-CNN and between 0.617 and 0.675 for human readers. The corresponding AUC of the ROC curve was 0.839 for cine-CNN, 0.679 for gado-CNN (p < 0.004 vs. cine) and 0.714 for the best human reader (p < 0.007 vs. cine). Logistic regression with cine-CNN and gado-CNN, as well as analysis focused on the specific orientation plane, did not change the overall results. We conclude that cine-CNN leads to significantly better discrimination between AL and ATTR amyloidosis as compared to gado-CNN or human readers, but with lower performance than reported in studies where visual diagnosis is easy, and is currently suboptimal for clinical practice.

Non-LGE Cardiac Magnetic Resonance Imaging in Patients with Cardiac Amyloidosis

Cardiac involvement is the leading cause of death in patients with cardiac amyloidosis. Early recognition is crucial as it can significantly change the course of the disease. Until now, the imaging modality of choice for diagnosing cardiac amyloidosis has been cardiac magnetic resonance imaging (CMR) with late gadolinium enhancement (LGE). LGE-CMR in patients with cardiac amyloidosis reveals characteristic LGE patterns that lead to a diagnosis while also correlating well with disease prognosis. However, LGE-CMR has numerous drawbacks that the newer CMR modality, T1 mapping, aims to improve. T1 mapping can be further subdivided into native T1 mapping, which does not require the use of contrast, and ECV measurement, which requires the use of contrast. Numerous T1 mapping techniques have been developed, each one with its own advantages and disadvantages when it comes to procedure difficulty and image quality. A literature review to identify relevant published articles was performed by two authors. This review aimed to present the value of T1 mapping in diagnosing cardiac amyloidosis, quantifying the amyloid burden, and evaluating the prognosis of patients with amyloidosis with cardiac involvement.

Feasibility of 68Ga-Labeled Fibroblast Activation Protein Inhibitor PET/CT in Light-Chain Cardiac Amyloidosis

BACKGROUND

Systemic amyloid light chain (AL) amyloidosis is the most common type of amyloidosis, leading to cardiomyocyte necrosis and interstitial fibrosis. Gallium-68-labeled fibroblast activation protein inhibitor 04 (⁶⁸Ga-FAPI-04) has recently been introduced for imaging fibroblast activation in cardiac diseases. To date, cardiac fibroblast and cardiac amyloidosis (CA) phenotype activities have not been mapped.

OBJECTIVES

The aim of this study was to evaluate the feasibility of ⁶⁸Ga-FAPI-04 positron emission tomography (PET)/computed tomography (CT) in assessing AL CA.

METHODS

Thirty consecutive patients (mean age: 59.1 ± 7.7 years; 20 men, 10 women) with biopsy-proven AL amyloidosis were enrolled prospectively (including 27 with AL CA and 3 without AL CA). All patients underwent ⁶⁸Ga-FAPI-04 PET/CT (107.4 ± 26.5 MBq). Global standardized uptake values and left ventricular (LV) molecular volume were calculated in correlation to echocardiography (n = 30), cardiac magnetic resonance (n = 18), and clinical biomarkers. Subsequently, the patients were categorized as having patchy (PET-patchy), extensive (PET-extensive), and negative (PET-negative) patterns.

RESULTS

Of all patients, 80% (24 of 30) showed increased LV uptake (PET-patchy [n = 4] vs PET-extensive [n = 20]), whereas 6 patients did not show visible myocardial uptake. Standardized uptake value ratio and LV molecular volume were significantly higher in the PET-extensive than the PET-patchy group (2.79 mL ± 1.22 mL vs 1.53 mL ± 0.66 mL [P = 0.045] and 198.3 mL ± 59.97 mL vs 127.8 mL ± 25.82 [P = 0.005], respectively). Additionally, ⁶⁸Ga-FAPI-04 uptake was significantly correlated with clinical biomarkers (Mayo stage and N-terminal pro-brain natriuretic peptide), interventricular septal thickness, left ventricular ejection fraction (LVEF), LV end-systolic volume, extracellular volume, and LV global strain (P < 0.05).

CONCLUSIONS

⁶⁸Ga-FAPI-04 PET/CT is feasible in detecting myocardial fibroblast activation in patients with AL CA in correlation with myocardial remodeling. It might provide complementary information on cardiac molecular characterization and staging of disease.

Beyond Sarcomeric Hypertrophic Cardiomyopathy: How to Diagnose and Manage Phenocopies

PURPOSE OF REVIEW

We describe the most common phenocopies of hypertrophic cardiomyopathy, their pathogenesis, and clinical presentation highlighting similarities and differences. We also suggest a step-by-step diagnostic work-up that can guide in differential diagnosis and management.

RECENT FINDINGS

In the last years, a wider application of genetic testing and the advances in cardiac imaging have significantly changed the diagnostic approach to HCM phenocopies. Different prognosis and management, with an increasing availability of disease-specific therapies, make differential diagnosis mandatory. The HCM phenotype can be the cardiac manifestation of different inherited and acquired disorders presenting different etiology, prognosis, and treatment. Differential diagnosis requires a cardiomyopathic mindset allowing to recognize red flags throughout the diagnostic work-up starting from clinical and family history and ending with advanced imaging and genetic testing. Different prognosis and management, with an increasing availability of disease-specific therapies make differential diagnosis mandatory.

Deep Learning Supplants Visual Analysis by Experienced Operators for the Diagnosis of Cardiac Amyloidosis by Cine-CMR

Background: Diagnosing cardiac amyloidosis (CA) from cine-CMR (cardiac magnetic resonance) alone is not reliable. In this study, we tested if a convolutional neural network (CNN) could outperform the visual diagnosis of experienced operators. Method: 119 patients with cardiac amyloidosis and 122 patients with left ventricular hypertrophy (LVH) of other origins were retrospectively selected. Diastolic and systolic cine-CMR images were preprocessed and labeled. A dual-input visual geometry group (VGG ) model was used for binary image classification. All images belonging to the same patient were distributed in the same set. Accuracy and area under the curve (AUC) were calculated per frame and per patient from a 40% held-out test set. Results were compared to a visual analysis assessed by three experienced operators. Results: frame-based comparisons between humans and a CNN provided an accuracy of 0.605 vs. 0.746 (p < 0.0008) and an AUC of 0.630 vs. 0.824 (p < 0.0001). Patient-based comparisons provided an accuracy of 0.660 vs. 0.825 (p < 0.008) and an AUC of 0.727 vs. 0.895 (p < 0.002). Conclusion: based on cine-CMR images alone, a CNN is able to discriminate cardiac amyloidosis from LVH of other origins better than experienced human operators (15 to 20 points more in absolute value for accuracy and AUC), demonstrating a unique capability to identify what the eyes cannot see through classical radiological analysis.

Diagnostic Work-Up of Cardiac Amyloidosis Using Cardiovascular Imaging: Current Standards and Practical Algorithms

Among non-ischemic cardiomyopathies, cardiac amyloidosis is one of the most common, being caused by extracellular depositions of amyloid fibrils in the myocardium. Two main forms of cardiac amyloidosis are known so far, including 1) light-chain (AL) amyloidosis caused by monoclonal production of light-chains, and 2) transthyretin (ATTR) amyloidosis, caused by dissociation of the transthyretin tetramer into monomers. Both AL and ATTR amyloidosis are progressive diseases with median survival from diagnosis of less than 6 months and 3 to 5 years, respectively, if untreated. In this regard, death occurs in most patients due to cardiac causes, mainly congestive heart failure, which can be prevented due to the presence of effective, life-saving treatment regimens. Therefore, early diagnosis of cardiac amyloidosis is crucial more than ever. However, diagnosis of cardiac amyloidosis may be challenging due to variable clinical manifestations and the perceived rarity of the disease. In this regard, clinical and laboratory reg flags are available, which may help clinicians to raise suspicion of cardiac amyloidosis. In addition, advances in cardiovascular imaging have already revealed a higher prevalence of cardiac amyloidosis in specific populations, so that the diagnosis especially of ATTR amyloidosis has experienced a >30-fold increase during the past ten years. The goal of our review article is to summarize these findings and provide a practical approach for clinicians on how to use cardiovascular imaging techniques, such as echocardiography, cardiac magnetic resonance, bone scintigraphy and, if required, organ biopsy within predefined diagnostic algorithms for the diagnostic work-up of patients with suspected cardiac amyloidosis. In addition, two clinical cases and practical tips are provided in this context.

Diagnostic performance of CMR, SPECT, and PET imaging for the detection of cardiac amyloidosis: a meta-analysis

Background

Noninvasive myocardial imaging modalities, such as cardiac magnetic resonance (CMR), single photon emission computed tomography (SPECT), and Positron emission tomography (PET), are well-established and extensively used to detect cardiac amyloid (CA). The purpose of this study is to directly compare CMR, SPECT, and PET scans in the diagnosis of CA, and to provide evidence for further scientific research and clinical decision-making.

Methods

PubMed, Embase, and Cochrane Library were searched. Studies used CMR, SPECT and/or PET for the diagnosis of CA were included. Pooled sensitivity, specificity, positive and negative likelihood ratio (LR), diagnostic odds ratio (DOR), their respective 95% confidence intervals (CIs) and the area under the summary receiver operating characteristic (SROC) curve (AUC) were calculated. Quality assessment of included studies was conducted.

Results

A total of 31 articles were identified for inclusion in this meta-analysis. The pooled sensitivities of CMR, SPECT and PET were 0.84, 0.98 and 0.78, respectively. Their respective overall specificities were 0.87, 0.92 and 0.95. Subgroup analysis demonstrated that ^99mTc-HMDP manifested the highest sensitivity (0.99). ^99mTc-PYP had the highest specificity (0.95). The AUC values of ^99mTc-DPD, ^99mTc-PYP, ^99mTc-HMDP were 0.89, 0.99, and 0.99, respectively. PET scan with ¹¹C-PIB demonstrated a pooled sensitivity of 0.91 and specificity of 0.97 with an AUC value of 0.98.

Conclusion

Our meta-analysis reveals that SEPCT scans present better diagnostic performance for the identification of CA as compared with other two modalities.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-021-02292-z.

Progress and Research Priorities in Imaging Genomics for Heart and Lung Disease: Summary of an NHLBI Workshop

Imaging genomics is a rapidly evolving field that combines state-of-the-art bioimaging with genomic information to resolve phenotypic heterogeneity associated with genomic variation, improve risk prediction, discover prevention approaches, and enable precision diagnosis and treatment. Contemporary bioimaging methods provide exceptional resolution generating discrete and quantitative high-dimensional phenotypes for genomics investigation. Despite substantial progress in combining high-dimensional bioimaging and genomic data, methods for imaging genomics are evolving. Recognizing the potential impact of imaging genomics on the study of heart and lung disease, the National Heart, Lung, and Blood Institute convened a workshop to review cutting-edge approaches and methodologies in imaging genomics studies, and to establish research priorities for future investigation. This report summarizes the presentations and discussions at the workshop. In particular, we highlight the need for increased availability of imaging genomics data in diverse populations, dedicated focus on less common conditions, and centralization of efforts around specific disease areas.

Diagnostic Value of Extracellular Volume Quantification and Myocardial Perfusion Analysis at CT in Cardiac Amyloidosis

Background CT can provide information regarding myocardial perfusion and expansion of the extracellular space, which is relevant to patients with cardiac amyloidosis (CA). Purpose To evaluate the role of CT in the diagnosis and prognosis of CA. Materials and Methods In this prospective study (Commission National de l'Informatique et des Libertés registration no. 1431858), participants with CA, participants with nonamyloid cardiac hypertrophy (NACH), and participants without hypertrophy were included between April 2017 and December 2018. The confirmed diagnosis of CA was determined according to established criteria (ie, proven with positive bone scintigraphy or endomyocardial biopsy). All participants were imaged with dynamic CT perfusion imaging at whole-heart cardiac CT. Extracellular volume measured at CT and myocardial perfusion parameters calculated on CT perfusion maps were compared among different participant groups. Differences between continuous data were tested using the unpaired t test, Mann-Whitney rank-sum test, or the Kruskal-Wallis test. Results A total of 84 participants with CA, 43 participants with NACH, and 33 participants without hypertrophy were included. Participants with CA exhibited a higher value of extracellular volume measured at CT (mean, 54.7% ± 9.7 [standard deviation]) than participants with NACH (mean, 34.6% ± 9.1; P < .001) and participants without hypertrophy (mean, 35.9% ± 9.9; P = .001). Mean myocardial blood volume and mean myocardial blood flow were lower in participants with CA (mean myocardial blood volume: 4.05 mL/100 g of myocardium ± 0.80; mean myocardial blood flow: 73.2 mL/100 g of myocardium per minute ± 25.7) compared to participants with NACH (mean myocardial blood volume: 5.38 mL/100 g of myocardium ± 1.20, P < .001; mean myocardial blood flow: 89.6 mL/100 g of myocardium per minute ± 31.3, P = .007) and participants without hypertrophy (mean myocardial blood volume: 5.68 mL/100 g of myocardium ± 1.05; mean myocardial blood flow: 106.3 mL/100 g of myocardium per minute ± 29.8; P < .001 for both). Extracellular volume measured at CT (hazard ratio >0.56 vs ≤0.56 = 4.2 [95% CI: 1.4, 11.8]), mean slope (hazard ratio ≤3.0 sec^-1 vs >3.0 sec^-1 = 0.2 [95% CI: 0.1, 0.8]), and time to peak (hazard ratio >20 seconds vs ≤20 seconds = 11.6 [95% CI: 1.3, 101.6]) were predictive of mortality in participants with CA. Conclusion Participants with cardiac amyloidosis exhibited an increase in extracellular volume at CT and abnormal CT perfusion parameters. Extracellular volume and several perfusion parameters were predictive of mortality. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Zimmerman in this issue.