Dataset Information

Diagnostic performance of imaging investigations in detecting and differentiating cardiac amyloidosis: a systematic review and meta-analysis.

ABSTRACT:

Aims

The study aims to systematically assess the diagnostic performance of cardiac magnetic resonance (CMR) and nuclear scintigraphy (index tests) for the diagnosis and differentiation of subtypes of cardiac amyloidosis.

Methods and results

MEDLINE and Embase electronic databases were searched for studies evaluating the diagnostic performance of CMR or nuclear scintigraphy in detecting cardiac amyloidosis and subsequently in differentiating transthyretin amyloidosis (ATTR) from immunoglobulin light-chain (AL) amyloidosis. In this meta-analysis, histopathological examination of tissue from endomyocardial biopsy (EMB) or extra-cardiac organs were reference standards. Pooled sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio were calculated, and a random effects meta-analysis was used to estimate diagnostic odds ratios. Methodological quality was assessed using a validated instrument. Of the 2947 studies identified, 27 met the criteria for inclusion. Sensitivity and specificity of CMR in diagnosing cardiac amyloidosis was 85.7% and 92.0% against EMB reference and 78.9% and 93.9% with any organ histology reference. Corresponding sensitivity and specificity of nuclear scintigraphy was 88.4% and 87.2% against EMB reference and 82.0% and 98.8% with histology from any organ. CMR was unable to reliably differentiate ATTR from AL amyloidosis (sensitivity 28.1-99.0% and specificity 11.0-60.0%). Sensitivity and specificity of nuclear scintigraphy in the differentiation of ATTR from AL amyloidosis ranged from 90.9% to 91.5% and from 88.6% to 97.1%. Pooled negative likelihood ratio and positive likelihood ratio for scintigraphy in this setting were 0.1 and 8, with EMB reference standard. Study quality assessed by QUADAS-2 was generally poor with evidence of bias.

Conclusions

Cardiac magnetic resonance is a useful test for diagnosing cardiac amyloidosis but is not reliable in further classifying the disease. Nuclear scintigraphy offers strong diagnostic performance in both the detection of cardiac amyloidosis and differentiating ATTR from AL amyloidosis. Our findings support the use of both imaging modalities in a non-invasive diagnostic algorithm that also tests for the presence of monoclonal protein.

SUBMITTER: Brownrigg J

PROVIDER: S-EPMC6816075 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Publications

Diagnostic performance of imaging investigations in detecting and differentiating cardiac amyloidosis: a systematic review and meta-analysis.

Brownrigg Jack J Lorenzini Massimiliano M Lumley Matthew M Elliott Perry P

ESC heart failure 20190905 5

<h4>Aims</h4>The study aims to systematically assess the diagnostic performance of cardiac magnetic resonance (CMR) and nuclear scintigraphy (index tests) for the diagnosis and differentiation of subtypes of cardiac amyloidosis.<h4>Methods and results</h4>MEDLINE and Embase electronic databases were searched for studies evaluating the diagnostic performance of CMR or nuclear scintigraphy in detecting cardiac amyloidosis and subsequently in differentiating transthyretin amyloidosis (ATTR) from im ...[more]

PMID: 31487121

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Project description:BackgroundCardiac masses are rare, but lead to high risk of stroke and death. Because of the different treatment methods, it is significant for clinicians to differentiate the nature of masses. Cardiac magnetic resonance (CMR) imaging has high intrinsic soft-tissue contrast and high spatial and temporal resolution and can provide evidence for differential diagnosis of cardiac masses. However, there is no evidence-based conclusion as to its accuracy. Therefore, the purpose of our study is to perform a systematic review on this issue and provide useful information for clinical diagnosis and treatment.MethodsWe will perform a systematic search in EMBASE, Cochrane Library, PubMed and Web of Science for diagnostic studies using CMR to detect cardiac masses from inception to October, 2019. Two authors will independently screen titles and abstracts for relevance, review full texts for inclusion and conduct detail data extraction. The methodological quality will be assessed using the QUADAS-2 tool. If pooling is possible, we will use bivariate model for diagnostic meta-analysis to estimate summary sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of CMR, as well as different sequences of CMR. Estimates of sensitivity and specificity from each study will be plotted in summary receive operating curve space and forest plots will be constructed for visual examination of variation in test accuracy. If enough studies are available, we will conduct sensitivity analysis and subgroup analysis.ResultsThe results of this systematic review and meta-analysis will be published in a peer-reviewed journal.ConclusionTo our knowledge, this will be the first systematic review on the accuracy of CMR in the differential diagnosis of cardiac masses. This study will provide evidence and data to form a comprehensive understanding of the clinical value of CMR for cardiac masses patients.Ethics and disseminationEthics approval and patient consent are not required, as this study is a systematic review.Prospero registration numberCRD42019137800.

Project description:BACKGROUND:Several methods for tumor delineation are used in literature on breast diffusion weighted imaging (DWI) to measure the apparent diffusion coefficient (ADC). However, in the process of reaching consensus on breast DWI scanning protocol, image analysis and interpretation, still no standardized optimal breast tumor tissue selection (BTTS) method exists. Therefore, the purpose of this study is to assess the impact of BTTS methods on ADC in the discrimination of benign from malignant breast lesions in DWI in terms of sensitivity, specificity and area under the curve (AUC). METHODS AND FINDINGS:In this systematic review and meta-analysis, adhering to the PRISMA statement, 61 studies, with 65 study subsets, in females with benign or malignant primary breast lesions (6291 lesions) were assessed. Studies on DWI, quantified by ADC, scanned on 1.5 and 3.0 Tesla and using b-values 0/50 and ≥ 800 s/mm2 were included. PubMed and EMBASE were searched for studies up to 23-10-2019 (n = 2897). Data were pooled based on four BTTS methods (by definition of measured region of interest, ROI): BTTS1: whole breast tumor tissue selection, BTTS2: subtracted whole breast tumor tissue selection, BTTS3: circular breast tumor tissue selection and BTTS4: lowest diffusion breast tumor tissue selection. BTTS methods 2 and 3 excluded necrotic, cystic and hemorrhagic areas. Pooled sensitivity, specificity and AUC of the BTTS methods were calculated. Heterogeneity was explored using the inconsistency index (I2) and considering covariables: field strength, lowest b-value, image of BTTS selection, pre-or post-contrast DWI, slice thickness and ADC threshold. Pooled sensitivity, specificity and AUC were: 0.82 (0.72-0.89), 0.79 (0.65-0.89), 0.88 (0.85-0.90) for BTTS1; 0.91 (0.89-0.93), 0.84 (0.80-0.87), 0.94 (0.91-0.96) for BTTS2; 0.89 (0.86-0.92), 0.90 (0.85-0.93), 0.95 (0.93-0.96) for BTTS3 and 0.90 (0.86-0.93), 0.84 (0.81-0.87), 0.86 (0.82-0.88) for BTTS4, respectively. Significant heterogeneity was found between studies (I2 = 95). CONCLUSIONS:None of the breast tissue selection (BTTS) methodologies outperformed in differentiating benign from malignant breast lesions. The high heterogeneity of ADC data acquisition demands further standardization, such as DWI acquisition parameters and tumor tissue selection to substantially increase the reliability of DWI of the breast.

Dataset Information

Diagnostic performance of imaging investigations in detecting and differentiating cardiac amyloidosis: a systematic review and meta-analysis.

Aims

Methods and results

Conclusions

Publications

Diagnostic performance of imaging investigations in detecting and differentiating cardiac amyloidosis: a systematic review and meta-analysis.

Similar Datasets

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