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1.
Radiol Clin North Am ; 58(3): 503-516, 2020 May.
Artigo em Inglês | MEDLINE | ID: mdl-32276700

RESUMO

Because of a recent increase in survival rates and life expectancy of patients with congenital heart disease (CHD), radiologists are facing new challenges when imaging the peculiar anatomy of individuals with repaired CHD. Cardiac computed tomography and magnetic resonance are paramount noninvasive imaging tools that are useful in assessing patients with repaired CHD, and both techniques are increasingly performed in centers where CHD is not the main specialization. This review provides general radiologists with insight into the main issues of imaging patients with repaired CHD, and the most common findings and complications of each individual pathology and its repair.


Assuntos
Cardiopatias Congênitas/diagnóstico por imagem , Cardiopatias Congênitas/cirurgia , Imagem por Ressonância Magnética/métodos , Tomografia Computadorizada por Raios X/métodos , Adolescente , Adulto , Humanos , Adulto Jovem
3.
J Thorac Imaging ; 35 Suppl 1: S49-S57, 2020 May.
Artigo em Inglês | MEDLINE | ID: mdl-32168163

RESUMO

PURPOSE: The purpose of this study was to evaluate the accuracy of a novel fully automated deep learning (DL) algorithm implementing a recurrent neural network (RNN) with long short-term memory (LSTM) for the detection of coronary artery calcium (CAC) from coronary computed tomography angiography (CCTA) data. MATERIALS AND METHODS: Under an IRB waiver and in HIPAA compliance, a total of 194 patients who had undergone CCTA were retrospectively included. Two observers independently evaluated the image quality and recorded the presence of CAC in the right (RCA), the combination of left main and left anterior descending (LM-LAD), and left circumflex (LCx) coronary arteries. Noncontrast CACS scans were allowed to be used in cases of uncertainty. Heart and coronary artery centerline detection and labeling were automatically performed. Presence of CAC was assessed by a RNN-LSTM. The algorithm's overall and per-vessel sensitivity, specificity, and diagnostic accuracy were calculated. RESULTS: CAC was absent in 84 and present in 110 patients. As regards CCTA, the median subjective image quality, signal-to-noise ratio, and contrast-to-noise ratio were 3.0, 13.0, and 11.4. A total of 565 vessels were evaluated. On a per-vessel basis, the algorithm achieved a sensitivity, specificity, and diagnostic accuracy of 93.1% (confidence interval [CI], 84.3%-96.7%), 82.76% (CI, 74.6%-89.4%), and 86.7% (CI, 76.8%-87.9%), respectively, for the RCA, 93.1% (CI, 86.4%-97.7%), 95.5% (CI, 88.77%-98.75%), and 94.2% (CI. 90.2%-94.6%), respectively, for the LM-LAD, and 89.9% (CI, 80.2%-95.8%), 90.0% (CI, 83.2%-94.7%), and 89.9% (CI, 85.0%-94.1%), respectively, for the LCx. The overall sensitivity, specificity, and diagnostic accuracy were 92.1% (CI, 92.1%-95.2%), 88.9% (CI. 84.9%-92.1%), and 90.3% (CI, 88.0%-90.0%), respectively. When accounting for image quality, the algorithm achieved a sensitivity, specificity, and diagnostic accuracy of 76.2%, 87.5%, and 82.2%, respectively, for poor-quality data sets and 93.3%, 89.2% and 90.9%, respectively, when data sets rated adequate or higher were combined. CONCLUSION: The proposed RNN-LSTM demonstrated high diagnostic accuracy for the detection of CAC from CCTA.

4.
J Thorac Imaging ; 35 Suppl 1: S58-S65, 2020 May.
Artigo em Inglês | MEDLINE | ID: mdl-32195886

RESUMO

During the latest years, artificial intelligence, and especially machine learning (ML), have experienced a growth in popularity due to their versatility and potential in solving complex problems. In fact, ML allows the efficient handling of big volumes of data, allowing to tackle issues that were unfeasible before, especially with deep learning, which utilizes multilayered neural networks. Cardiac computed tomography (CT) is also experiencing a rise in examination numbers, and ML might help handle the increasing derived information. Moreover, cardiac CT presents some fields wherein ML may be pivotal, such as coronary calcium scoring, CT angiography, and perfusion. In particular, the main applications of ML involve image preprocessing and postprocessing, and the development of risk assessment models based on imaging findings. Concerning image preprocessing, ML can help improve image quality by optimizing acquisition protocols or removing artifacts that may hinder image analysis and interpretation. ML in image postprocessing might help perform automatic segmentations and shorten examination processing times, also providing tools for tissue characterization, especially concerning plaques. The development of risk assessment models from ML using data from cardiac CT could aid in the stratification of patients who undergo cardiac CT in different risk classes and better tailor their treatment to individual conditions. While ML is a powerful tool with great potential, applications in the field of cardiac CT are still expanding, and not yet routinely available in clinical practice due to the need for extensive validation. Nevertheless, ML is expected to have a big impact on cardiac CT in the near future.

5.
J Thorac Imaging ; 2020 Mar 20.
Artigo em Inglês | MEDLINE | ID: mdl-32205821

RESUMO

OBJECTIVES: Computed tomography (CT) myocardial perfusion imaging (CT-MPI) with hyperemia induced by regadenoson was evaluated for the detection of myocardial ischemia, safety, relative radiation exposure, and patient experience compared with single-photon emission computed tomography (SPECT) imaging. MATERIALS AND METHODS: Twenty-four patients (66.5 y, 29% male) who had undergone clinically indicated SPECT imaging and provided written informed consent were included in this phase II, IRB-approved, and FDA-approved clinical trial. All patients underwent coronary CT angiography and CT-MPI with hyperemia induced by the intravenous administration of regadenoson (0.4 mg/5 mL). Patient experience and findings on CT-MPI images were compared to SPECT imaging. RESULTS: Patient experience and safety were similar between CT-MPI and SPECT procedures and no serious adverse events due to the administration of regadenoson occurred. SPECT resulted in a higher number of mild adverse events than CT-MPI. Patient radiation exposure was similar during the combined coronary computed tomography angiography and CT-MPI (4.4 [2.7] mSv) and SPECT imaging (5.6 [1.7] mSv) (P-value 0.401) procedures. Using SPECT as the reference standard, CT-MPI analysis showed a sensitivity of 58.3% (95% confidence interval [CI]: 27.7-84.8), a specificity of 100% (95% CI: 73.5-100), and an accuracy of 79.1% (95% CI: 57.9-92.87). Low apparent sensitivity occurred when the SPECT defects were small and highly suspicious for artifacts. CONCLUSIONS: This study demonstrated that CT-MPI is safe, well tolerated, and can be performed with comparable radiation exposure to SPECT. CT-MPI has the benefit of providing both complete anatomic coronary evaluation and assessment of myocardial perfusion.

6.
Radiology ; 295(2): 326-327, 2020 May.
Artigo em Inglês | MEDLINE | ID: mdl-32159451
7.
J Nucl Cardiol ; 2020 Feb 05.
Artigo em Inglês | MEDLINE | ID: mdl-32026327

RESUMO

BACKGROUND: Coronary physiology assessments have been shown by multiple trials to add clinical value in detecting significant coronary artery disease and predicting cardiovascular outcomes. Fractional flow reserve (FFR) obtained during invasive coronary angiography (ICA) has become the new reference standard for hemodynamic significance detection. Absolute myocardial blood flow (MBF) quantification by means of dynamic positron emission tomography (dPET) has high diagnostic and prognostic values. FFR is an invasive measure and as such cannot be applied broadly, while MBF quantification is commonly performed on standard vascular territories intermixing normal flow from normal regions with abnormal flow from abnormal regions and consequently limiting its diagnostic power. OBJECTIVE: The aim of this study is to provide physicians with reliable software tools for the non-invasive assessment of lesion-specific physiological significance for the entire coronary tree by combining PET-derived absolute flow data and coronary computed tomography angiography (CTA)-derived anatomy and coronary centerlines. METHODS: The dynamic PET/CTA myocardial blood flow assessment with fused imagery (DEMYSTIFY) study is an observational prospective clinical study to develop algorithms and software tools to fuse coronary anatomy data obtained from CTA with dPET data to non-invasively measure absolute MBF, myocardial flow reserve, and relative flow reserve across specific coronary lesions. Patients (N = 108) will be collected from 4 institutions (Emory University Hospital, USA; Chonnam National University Hospital, South Korea; Samsung Medical Center, South Korea; Seoul National University Hospital, South Korea). These results will be compared to those obtained invasively in the catheterization laboratory and to a relatively novel non-invasive technique to estimate FFR based on CTA and computational fluid dynamics. CONCLUSIONS: Success of these developments should lead to the following benefits: (1) eliminate unnecessary invasive coronary angiography in patients with no significant lesions, (2) avoid stenting physiologically insignificant lesions, (3) guide percutaneous coronary interventions process to the location of significant lesions, (4) provide a flow-color-coded 3D roadmap of the entire coronary tree to guide bypass surgery, and (5) use less radiation and lower the cost from unnecessary procedures. TRIAL REGISTRY: The DEMYSTIFY study has been registered on ClinicalTrials.gov with registration number NCT04221594.

8.
J Thorac Imaging ; 35(3): 198-203, 2020 May.
Artigo em Inglês | MEDLINE | ID: mdl-32032251

RESUMO

PURPOSE: The purpose of this study was to evaluate the utilization of invasive and noninvasive tests and compare cost in patients presenting with chest pain to the emergency department (ED) who underwent either triple-rule-out computed tomography angiography (TRO-CTA) or standard of care. MATERIALS AND METHODS: We performed a retrospective single-center analysis of 2156 ED patients who presented with acute chest pain with a negative initial troponin and electrocardiogram for myocardial injury. Patient cohorts matched by patient characteristics who had undergone TRO-CTA as a primary imaging test (n=1139) or standard of care without initial CTA imaging (n=1017) were included in the study. ED visits, utilization of tests, and costs during the initial episode of hospital care were compared. RESULTS: No significant differences in the diagnosis of coronary artery disease, pulmonary embolism, or aortic dissection were observed. Median ED waiting time (4.5 vs. 7.0 h, P<0.001), median total length of hospital stay (5.0 vs. 32.0 h, P<0.001), hospital admission rate (12.6% vs. 54.2%, P<0.001), and ED return rate to our hospital within 30 days (3.5% vs. 14.6%, P<0.001) were significantly lower in the TRO-CTA group. Moreover, reduced rates of additional testing and invasive coronary angiography (4.9% vs. 22.7%, P<0.001), and ultimately lower total cost per patient (11,783$ vs. 19,073$, P<0.001) were observed in the TRO-CTA group. CONCLUSIONS: TRO-CTA as an initial imaging test in ED patients presenting with acute chest pain was associated with shorter ED and hospital length of stay, fewer return visits within 30 days, and ultimately lower ED and hospitalization costs.

9.
J Thorac Imaging ; 35 Suppl 1: S3-S10, 2020 May.
Artigo em Inglês | MEDLINE | ID: mdl-32073539

RESUMO

The field of artificial intelligence (AI) is currently experiencing a period of extensive growth in a wide variety of fields, medicine not being the exception. The base of AI is mathematics and computer science, and the current fame of AI in industry and research stands on 3 pillars: big data, high performance computing infrastructure, and algorithms. In the current digital era, increased storage capabilities and data collection systems, lead to a massive influx of data for AI algorithm. The size and quality of data are 2 major factors influencing performance of AI applications. However, it is highly dependent on the type of task at hand and algorithm chosen to perform this task. AI may potentially automate several tedious tasks in radiology, particularly in cardiothoracic imaging, by pre-readings for the detection of abnormalities, accurate quantifications, for example, oncologic volume lesion tracking and cardiac volume and image optimization. Although AI-based applications offer great opportunity to improve radiology workflow, several challenges need to be addressed starting from image standardization, sophisticated algorithm development, and large-scale evaluation. Integration of AI into the clinical workflow also needs to address legal barriers related to security and protection of patient-sensitive data and liability before AI will reach its full potential in cardiothoracic imaging.

11.
Atherosclerosis ; 294: 25-32, 2020 02.
Artigo em Inglês | MEDLINE | ID: mdl-31945615

RESUMO

BACKGROUND AND AIMS: Artificial intelligence (AI) is increasing its role in diagnosis of patients with suspicious coronary artery disease. The aim of this manuscript is to develop a deep convolutional neural network (CNN) to classify coronary computed tomography angiography (CCTA) in the correct Coronary Artery Disease Reporting and Data System (CAD-RADS) category. METHODS: Two hundred eighty eight patients who underwent clinically indicated CCTA were included in this single-center retrospective study. The CCTAs were stratified by CAD-RADS scores by expert readers and considered as reference standard. A deep CNN was designed and tested on the CCTA dataset and compared to on-site reading. The deep CNN analyzed the diagnostic accuracy of the following three Models based on CAD-RADS classification: Model A (CAD-RADS 0 vs CAD-RADS 1-2 vs CAD-RADS 3,4,5), Model 1 (CAD-RADS 0 vs CAD-RADS>0), Model 2 (CAD-RADS 0-2 vs CAD-RADS 3-5). Time of analysis for both physicians and CNN were recorded. RESULTS: Model A showed a sensitivity, specificity, negative predictive value, positive predictive value and accuracy of 47%, 74%, 77%, 46% and 60%, respectively. Model 1 showed a sensitivity, specificity, negative predictive value, positive predictive value and accuracy of 66%, 91%, 92%, 63%, 86%, respectively. Conversely, Model 2 demonstrated the following sensitivity, specificity, negative predictive value, positive predictive value and accuracy: 82%, 58%, 74%, 69%, 71%, respectively. Time of analysis was significantly lower using CNN as compared to on-site reading (530.5 ± 179.1 vs 104.3 ± 1.4 sec, p=0.01) CONCLUSIONS: Deep CNN yielded accurate automated classification of patients with CAD-RADS.

12.
Am J Cardiol ; 124(9): 1340-1348, 2019 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-31481177

RESUMO

This study investigated the impact of coronary CT angiography (cCTA)-derived plaque markers and machine-learning-based CT-derived fractional flow reserve (CT-FFR) to identify adverse cardiac outcome. Data of 82 patients (60 ± 11 years, 62% men) who underwent cCTA and invasive coronary angiography (ICA) were analyzed in this single-center retrospective, institutional review board-approved, HIPAA-compliant study. Follow-up was performed to record major adverse cardiac events (MACE). Plaque quantification of lesions responsible for MACE and control lesions was retrospectively performed semiautomatically from cCTA together with machine-learning based CT-FFR. The discriminatory value of plaque markers and CT-FFR to predict MACE was evaluated. After a median follow-up of 18.5 months (interquartile range 11.5 to 26.6 months), MACE was observed in 18 patients (21%). In a multivariate analysis the following markers were predictors of MACE (odds ratio [OR]): lesion length (OR 1.16, p = 0.018), low-attenuation plaque (<30 HU) (OR 4.59, p = 0.003), Napkin ring sign (OR 2.71, p = 0.034), stenosis ≥50% (OR 3.83, p 0.042), and CT-FFR ≤0.80 (OR 7.78, p = 0.001). Receiver operating characteristics analysis including stenosis ≥50%, plaque markers and CT-FFR ≤0.80 (Area under the curve 0.94) showed incremental discriminatory power over stenosis ≥50% alone (Area under the curve 0.60, p <0.0001) for the prediction of MACE. cCTA-derived plaque markers and machine-learning CT-FFR demonstrate predictive value to identify MACE. In conclusion, combining plaque markers with machine-learning CT-FFR shows incremental discriminatory power over cCTA stenosis grading alone.

13.
Eur J Radiol ; 119: 108657, 2019 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-31521876

RESUMO

PURPOSE: This study investigated the impact of gender differences on the diagnostic performance of machine-learning based coronary CT angiography (cCTA)-derived fractional flow reserve (CT-FFRML) for the detection of lesion-specific ischemia. METHOD: Five centers enrolled 351 patients (73.5% male) with 525 vessels in the MACHINE (Machine leArning Based CT angiograpHy derIved FFR: a Multi-ceNtEr) registry. CT-FFRML and invasive FFR ≤ 0.80 were considered hemodynamically significant, whereas cCTA luminal stenosis ≥50% was considered obstructive. The diagnostic performance to assess lesion-specific ischemia in both men and women was assessed on a per-vessel basis. RESULTS: In total, 398 vessels in men and 127 vessels in women were included. Compared to invasive FFR, CT-FFRML reached a sensitivity, specificity, positive predictive value, and negative predictive value of 78% (95%CI 72-84), 79% (95%CI 73-84), 75% (95%CI 69-79), and 82% (95%CI: 76-86) in men vs. 75% (95%CI 58-88), 81 (95%CI 72-89), 61% (95%CI 50-72) and 89% (95%CI 82-94) in women, respectively. CT-FFRML showed no statistically significant difference in the area under the receiver-operating characteristic curve (AUC) in men vs. women (AUC: 0.83 [95%CI 0.79-0.87] vs. 0.83 [95%CI 0.75-0.89], p = 0.89). CT-FFRML was not superior to cCTA alone [AUC: 0.83 (95%CI: 0.75-0.89) vs. 0.74 (95%CI: 0.65-0.81), p = 0.12] in women, but showed a statistically significant improvement in men [0.83 (95%CI: 0.79-0.87) vs. 0.76 (95%CI: 0.71-0.80), p = 0.007]. CONCLUSIONS: Machine-learning based CT-FFR performs equally in men and women with superior diagnostic performance over cCTA alone for the detection of lesion-specific ischemia.


Assuntos
Angiografia por Tomografia Computadorizada/normas , Estenose Coronária/diagnóstico por imagem , Isquemia Miocárdica/diagnóstico por imagem , Angiografia por Tomografia Computadorizada/métodos , Angiografia Coronária/métodos , Angiografia Coronária/normas , Estenose Coronária/fisiopatologia , Métodos Epidemiológicos , Feminino , Reserva Fracionada de Fluxo Miocárdico/fisiologia , Hemodinâmica/fisiologia , Humanos , Aprendizado de Máquina , Masculino , Pessoa de Meia-Idade , Isquemia Miocárdica/fisiopatologia , Fatores Sexuais , Tomografia Computadorizada Espiral/métodos , Tomografia Computadorizada Espiral/normas
14.
Radiology ; 293(2): 260-271, 2019 11.
Artigo em Inglês | MEDLINE | ID: mdl-31502938

RESUMO

In this article, the authors discuss the technical background and summarize the current body of literature regarding virtual monoenergetic (VM) images derived from dual-energy CT data, which can be reconstructed between 40 and 200 keV. Substantially improved iodine attenuation at lower kiloelectron volt levels and reduced beam-hardening artifacts at higher kiloelectron volt levels have been demonstrated from all major manufacturers of dual-energy CT units. Improved contrast attenuation with VM imaging at lower kiloelectron volt levels enables better delineation and diagnostic accuracy in the detection of various vascular or oncologic abnormalities. Low-kiloelectron-volt VM imaging may be useful for salvaging CT studies with suboptimal contrast material delivery or providing additional information on the arterial vasculature obtained from venous phase acquisitions. For patients with renal impairment, substantial reductions in the use of iodinated contrast material can be achieved by using lower-energy VM imaging. The authors recommend routine reconstruction of VM images at 50 keV when using dual-energy CT to exploit the increased contrast properties. For reduction of beam-hardening artifacts, VM imaging at 120 keV is useful for the initial assessment.

15.
Artigo em Inglês | MEDLINE | ID: mdl-31422141

RESUMO

OBJECTIVES: This study was conducted to investigate the influence of coronary artery calcium (CAC) score on the diagnostic performance of machine-learning-based coronary computed tomography (CT) angiography (cCTA)-derived fractional flow reserve (CT-FFR). BACKGROUND: CT-FFR is used reliably to detect lesion-specific ischemia. Novel CT-FFR algorithms using machine-learning artificial intelligence techniques perform fast and require less complex computational fluid dynamics. Yet, influence of CAC score on diagnostic performance of the machine-learning approach has not been investigated. METHODS: Four hundred eighty-two vessels from 314 patients (62.3 ± 9.3 years, 77% male) who underwent cCTA followed by invasive FFR were investigated from the MACHINE (Machine Learning based CT Angiography derived FFR: a Multi-center Registry) registry data. CAC scores were quantified using the Agatston convention. The diagnostic performance of CT-FFR to detect lesion-specific ischemia was assessed across all Agatston score categories (CAC 0, >0 to <100, 100 to <400, and ≥400) on a per-vessel level with invasive FFR as the reference standard. RESULTS: The diagnostic accuracy of CT-FFR versus invasive FFR was superior to cCTA alone on a per-vessel level (78% vs. 60%) and per patient level (83% vs. 73%) across all Agatston score categories. No statistically significant differences in the diagnostic accuracy, sensitivity, or specificity of CT-FFR were observed across the categories. CT-FFR showed good discriminatory power in vessels with high Agatston scores (CAC ≥ 400) and high performance in low-to-intermediate Agatston scores (CAC >0 to <400) with a statistically significant difference in the area under the receiver-operating characteristic curve (AUC) (AUC: 0.71 [95% confidence interval (CI): 0.57-0.85] vs. 0.85 [95% CI: 0.82-0.89], p = 0.04). CT-FFR showed superior diagnostic value over cCTA in vessels with high Agatston scores (CAC ≥ 400: AUC 0.71 vs. 0.55, p = 0.04) and low-to-intermediate Agatston scores (CAC >0 to <400: AUC 0.86 vs. 0.63, p < 0.001). CONCLUSIONS: Machine-learning-based CT-FFR showed superior diagnostic performance over cCTA alone in CAC with a significant difference in the performance of CT-FFR as calcium burden/Agatston calcium score increased. (Machine Learning Based CT Angiography Derived FFR: a Multicenter, Registry [MACHINE] NCT02805621).

16.
Circ Cardiovasc Imaging ; 12(7): e008754, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-31303028

RESUMO

BACKGROUND: Maternal pregnancy complications, particularly preeclampsia and gestational diabetes mellitus, are described to increase the risk for subsequent coronary artery disease (CAD). In addition, black women are at higher risk for CAD. The objective of this study was to compare the prevalence and extent of CAD as detected by coronary computed tomographic angiography (CCTA) in black women with and without a history of prior pregnancy complications. METHODS: We retrospectively evaluated patient characteristics and CCTA findings in groups of black women with a prior history of preterm delivery (n=154), preeclampsia (n=137), or gestational diabetes mellitus (n=148), and a matched control group of black women who gave birth without such complications (n=445). Univariate and multivariate analyses were performed to assess risk factors of CAD. RESULTS: All groups with prior pregnancy complications showed higher rates of any (≥20% luminal narrowing) and obstructive (≥50% luminal narrowing) CAD (preterm delivery: 29.2% and 9.1%; preeclampsia: 29.2% and 7.3%; and gestational diabetes mellitus: 47.3% and 15.5%) compared with control women (23.8% and 5.4%). After accounting for confounding factors at multivariate analysis, gestational diabetes mellitus remained a strong risk factor of any (odds ratio, 3.26; 95% CI, 2.03-5.22; P<0.001) and obstructive CAD (odds ratio, 3.00; 95% CI, 1.55-5.80; P<0.001) on CCTA. CONCLUSIONS: Black women with a history of pregnancy complications, particularly gestational diabetes mellitus, have a higher prevalence of CAD on CCTA while only a history of gestational diabetes mellitus was independently associated with any and obstructive CAD on CCTA.

17.
J Cardiovasc Comput Tomogr ; 13(5): 274-280, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31029649

RESUMO

In the last decade, technical advances in the field of medical imaging significantly improved and broadened the application of coronary CT angiography (CCTA) for the non-invasive assessment of coronary artery disease. Recently, similar breakthroughs are happening in the post-processing, analysis and interpretation of radiological images. Technologies such as radiomics allow to extract significantly more information from scans than what human visual assessment is capable of. This allows the precision phenotyping of diseases based on medical images. The increased amount of information can then be analyzed using novel data analytic techniques such as machine learning (ML) and deep learning (DL), which utilize the power of big data to build predictive models, which seek to mimic human intelligence, artificially. Thanks to big data availability and increased computational power, these novel analytic methods are outperforming conventional statistical techniques. In this current overview we describe the basics of radiomics, ML and DL, highlighting similarities, differences, limitations and potential pitfalls of these techniques. In addition, we provide a brief overview of recently published results on the applications of the aforementioned techniques for the non-invasive assessment of coronary atherosclerosis using CCTA.


Assuntos
Angiografia por Tomografia Computadorizada , Angiografia Coronária/métodos , Doença da Artéria Coronariana/diagnóstico por imagem , Vasos Coronários/diagnóstico por imagem , Aprendizado Profundo , Placa Aterosclerótica , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Doença da Artéria Coronariana/terapia , Humanos , Valor Preditivo dos Testes , Prognóstico , Reprodutibilidade dos Testes , Índice de Gravidade de Doença
18.
Magn Reson Imaging Clin N Am ; 27(2): 243-262, 2019 May.
Artigo em Inglês | MEDLINE | ID: mdl-30910096

RESUMO

Prevalence of patients with congenital heart disease (CHD) is rapidly increasing due to continuous advancements in diagnostic techniques and medical or surgical treatment approaches. Along with cardiac computed tomography angiography, cardiac magnetic resonance (CMR) serves as a fundamental imaging modality for pre-surgical planning in patients with CHD, as CMR allows for the evaluation of cardiac and great vessel anatomy, biventricular function, flow dynamics, and tissue characterization. This information is essential for risk-assessment and optimal timing of surgical interventions. This article discusses the current role of pediatric cardiac MR imaging as a practical preoperative assessment tool in the pediatric population.


Assuntos
Cardiopatias Congênitas/diagnóstico por imagem , Imagem por Ressonância Magnética/métodos , Cuidados Pré-Operatórios/métodos , Adolescente , Criança , Pré-Escolar , Feminino , Coração/diagnóstico por imagem , Humanos , Lactente , Masculino
19.
BMC Cardiovasc Disord ; 19(1): 39, 2019 02 11.
Artigo em Inglês | MEDLINE | ID: mdl-30744612

RESUMO

BACKGROUND: The heterogeneity of risk in patients with diabetes mellitus (DM) is acknowledged in new guidelines promulgating different treatment recommendations for diabetics at low cardiac risk. We performed a retrospective longitudinal follow-up study to evaluate coronary plaque progression and its impact on cardiac events in asymptomatic diabetic patients. METHODS: Data of 197 asymptomatic patients (63.1 ± 17 years, 60% males) with DM and suspected coronary artery disease (CAD) who underwent clinically indicated dual-source cardiac computed tomography (CT) were retrospectively analyzed. Patients with DM received standard of care treatment. Patients were classified into two groups based on CT coronary artery calcium scores (CACS): A, CACS> 10; B, CACS≤10. Progression of coronary plaque burden in both groups was evaluated and compared by baseline and follow-up coronary CT angiography (CCTA) using semi-automated plaque analysis and quantification software. Follow-up data were retrospectively gathered from medical records and endpoints of cardiac events were recorded via prospective phone-calls. The impacts of plaque composition and progression on cardiac events were specifically assessed. RESULTS: Patients with CACS> 10 showed an increase in dense coronary calcium volume, while patients with CACS≤10 had a more pronounced increase in the volume of low-attenuation "lipid-rich" plaque components between CCTA acquisitions. The composite endpoint occurred in 20 patients (10.2%) after a median follow-up period of 41.8 months. Furthermore, at follow-up CCTA, the presence of CACS> 10 (adjusted odds ratio, 0.701; 95% CI, 0.612-0.836), increase of dense calcium volume (OR, 0.860 95% CI, 0.771-0.960), and lipid volume (OR, 1.013; 95% CI, 1.007-1.020) were all independent predictors of cardiac events. CONCLUSION: Asymptomatic patients with DM experienced plaque progression as well as progression to "overt or silent CAD". The relative increase in plaque volume was associated with subsequent cardiac events, and the coronary calcification seemed to be inversely related to the outcome in asymptomatic diabetic patients.


Assuntos
Angiografia por Tomografia Computadorizada , Angiografia Coronária/métodos , Doença da Artéria Coronariana/diagnóstico por imagem , Diabetes Mellitus , Placa Aterosclerótica , Calcificação Vascular/diagnóstico por imagem , Idoso , Idoso de 80 Anos ou mais , Doenças Assintomáticas , China/epidemiologia , Doença da Artéria Coronariana/epidemiologia , Diabetes Mellitus/diagnóstico , Diabetes Mellitus/epidemiologia , Progressão da Doença , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Valor Preditivo dos Testes , Prognóstico , Estudos Retrospectivos , Medição de Risco , Fatores de Risco , Fatores de Tempo , Calcificação Vascular/epidemiologia
20.
Eur J Radiol ; 112: 136-143, 2019 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-30777202

RESUMO

BACKGROUND: The aim of this study was to assess the potential of rest-stress DECT iodine quantification to discriminate between normal, ischemic, and infarcted myocardium. METHODS: Patients who underwent rest-stress DECT on a 2nd generation dual-source system and cardiac magnetic resonance (CMR) were retrospectively included from a prospective study cohort. CMR was performed to identify ischemic and infarcted myocardium and categorize patients into ischemic, infarcted, and control groups. Controls were analyzed on a per-slice and per-segment basis. Regions of interest (ROIs) were placed in ischemic and infarcted areas based on CMR. Additionally, ROIs were placed in the septal area to assess normal and remote myocardium. RESULTS: We included 42 patients: 10 ischemic, 17 infarcted, and 15 controls. Iodine concentrations showed no significant between segments in controls. Iodine concentrations for normal myocardium increased significantly from rest to stress (median 3.7 mg/mL (interquartile range 3.5-3.9) vs. 4.5 mg/mL (4.3-4.9)) (p < 0.001). Iodine concentrations in diseased myocardium were significantly lower than in normal myocardium; 1.3 mg/mL (0.9-1.8) and 0.6 mg/mL (0.4-0.8) at rest and stress in ischemic myocardium, and 0.3 mg/mL (0.3-0.5) and 0.5 mg/mL (0.5-0.7) at rest and stress in infarcted myocardium (p < 0.005 and p < 0.001). At rest only, iodine concentrations were significantly lower in infarcted vs. ischemic myocardium (p < 0.001). The optimal threshold for differentiating diseased from normal myocardium was 2.5 mg/mL and 2.1 mg/mL for rest and stress (AUC 1.00). To discriminate ischemic from infarcted myocardium, the optimal threshold was 1.0 mg/ml (AUC 0.944) at rest. CONCLUSION: DECT iodine concentration from rest-stress imaging can potentially differentiate between normal, ischemic, and infarcted myocardium.


Assuntos
Meios de Contraste/farmacocinética , Iodo/farmacocinética , Isquemia Miocárdica/diagnóstico , Idoso , Estudos de Casos e Controles , Teste de Esforço/métodos , Feminino , Coração/fisiologia , Humanos , Angiografia por Ressonância Magnética/métodos , Masculino , Pessoa de Meia-Idade , Infarto do Miocárdio/diagnóstico , Imagem de Perfusão do Miocárdio/métodos , Miocárdio/química , Estudos Prospectivos , Descanso , Estudos Retrospectivos , Tomografia Computadorizada por Raios X/métodos
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