RESUMO
Supplemental material is available for this article. See also the article by Lenkinski and Rofsky in this issue. See also the article by McKee et al in this issue.
Assuntos
Gases de Efeito Estufa , Imageamento por Ressonância Magnética , Humanos , Imageamento por Ressonância Magnética/métodos , Imageamento por Ressonância Magnética/economiaRESUMO
Left ventricular (LV) diastolic dysfunction (DD) is an initially asymptomatic condition that can progress to heart failure, either with preserved or reduced ejection fraction. As such, DD is a growing public health problem. Impaired relaxation, the first stage of DD, is associated with altered LV filling. With progression, reducing LV compliance leads to restrictive cardiomyopathy. While cardiac magnetic resonance (CMR) imaging is the reference for LV systolic function assessment, transthoracic echocardiography (TTE) with Doppler flow measurements remains the standard for diastolic function assessment. Rather than simply replicating TTE measurements, CMR should complement and further advance TTE findings. We provide herein a step-by-step review of CMR findings in DD as well as imaging features which may help identify the underlying cause.
Assuntos
Diástole , Imageamento por Ressonância Magnética , Disfunção Ventricular Esquerda , Humanos , Disfunção Ventricular Esquerda/diagnóstico por imagem , Disfunção Ventricular Esquerda/fisiopatologia , Imageamento por Ressonância Magnética/métodos , Ecocardiografia/métodosAssuntos
Inteligência Artificial , Angiografia por Tomografia Computadorizada , Angiografia Coronária , Substituição da Valva Aórtica Transcateter , Humanos , Substituição da Valva Aórtica Transcateter/métodos , Angiografia por Tomografia Computadorizada/métodos , Angiografia Coronária/métodos , FótonsAssuntos
Adenocarcinoma , Internato e Residência , Neoplasias Pancreáticas , Humanos , Neoplasias Pancreáticas/diagnóstico por imagem , Neoplasias Pancreáticas/cirurgia , Adenocarcinoma/diagnóstico por imagem , Adenocarcinoma/cirurgia , Internato e Residência/métodos , Tomografia Computadorizada por Raios X/métodos , Feminino , Masculino , Idoso , Radiologia/educaçãoRESUMO
PURPOSE: The purpose of this study was to propose a deep learning-based approach to detect pulmonary embolism and quantify its severity using the Qanadli score and the right-to-left ventricle diameter (RV/LV) ratio on three-dimensional (3D) computed tomography pulmonary angiography (CTPA) examinations with limited annotations. MATERIALS AND METHODS: Using a database of 3D CTPA examinations of 1268 patients with image-level annotations, and two other public datasets of CTPA examinations from 91 (CAD-PE) and 35 (FUME-PE) patients with pixel-level annotations, a pipeline consisting of: (i), detecting blood clots; (ii), performing PE-positive versus negative classification; (iii), estimating the Qanadli score; and (iv), predicting RV/LV diameter ratio was followed. The method was evaluated on a test set including 378 patients. The performance of PE classification and severity quantification was quantitatively assessed using an area under the curve (AUC) analysis for PE classification and a coefficient of determination (R²) for the Qanadli score and the RV/LV diameter ratio. RESULTS: Quantitative evaluation led to an overall AUC of 0.870 (95% confidence interval [CI]: 0.850-0.900) for PE classification task on the training set and an AUC of 0.852 (95% CI: 0.810-0.890) on the test set. Regression analysis yielded R² value of 0.717 (95% CI: 0.668-0.760) and of 0.723 (95% CI: 0.668-0.766) for the Qanadli score and the RV/LV diameter ratio estimation, respectively on the test set. CONCLUSION: This study shows the feasibility of utilizing AI-based assistance tools in detecting blood clots and estimating PE severity scores with 3D CTPA examinations. This is achieved by leveraging blood clots and cardiac segmentations. Further studies are needed to assess the effectiveness of these tools in clinical practice.