Assessment of the relationship between regional wall motion abnormality score revealed by parametric imaging and the extent of LGE with CMR.

The aim of this study was to assess the relationship between left ventricular (LV) regional myocardial wall motion abnormality (WMA), revealed by visual interpretation of cardiac magnetic resonance (CMR) cine images together with the computed wall motion parametric image, and the transmural scar extent, as assessed by Late gadolinium Enhancement (LGE), in 40 patients. Each cine CMR short-axis loop was processed to compute a parametric image where each pixel represents the amplitude of the Hilbert transform of videointensity over time. Two expert radiologists blindly interpreted the cine CMR images in combination with the corresponding parametric image to assign a WMA score for each of the 16 myocardial sectors in which the LV myocardium was subdivided. Such score was compared per sector to the level of transmural scar extent obtained by LGE images. A total of 592 myocardial segments were analyzed. A significant decrease in regional wall motion was observed in sectors with LGE transmural hyperenhancement > 75% of tissue, as well as a correlation between parametric image amplitude and peak radial and circumferential strain, computed by feature tracking. The results showed a reduction in prediction error Lambda of WMA from LGE of 65%, and of LGE from WMA of 63%. In particular, the estimated probability of correct prediction of WMA from LGE was 76%, while that of LGE from WMA was 75%. The interpretation of myocardial viability by LGE images combined with the WMA information, derived from cine CMR and parametric images, could improve the clinical decision making process.

A Multi-Agent Deep Reinforcement Learning Approach for Enhancement of COVID-19 CT Image Segmentation.

Currently, most mask extraction techniques are based on convolutional neural networks (CNNs). However, there are still numerous problems that mask extraction techniques need to solve. Thus, the most advanced methods to deploy artificial intelligence (AI) techniques are necessary. The use of cooperative agents in mask extraction increases the efficiency of automatic image segmentation. Hence, we introduce a new mask extraction method that is based on multi-agent deep reinforcement learning (DRL) to minimize the long-term manual mask extraction and to enhance medical image segmentation frameworks. A DRL-based method is introduced to deal with mask extraction issues. This new method utilizes a modified version of the Deep Q-Network to enable the mask detector to select masks from the image studied. Based on COVID-19 computed tomography (CT) images, we used DRL mask extraction-based techniques to extract visual features of COVID-19 infected areas and provide an accurate clinical diagnosis while optimizing the pathogenic diagnostic test and saving time. We collected CT images of different cases (normal chest CT, pneumonia, typical viral cases, and cases of COVID-19). Experimental validation achieved a precision of 97.12% with a Dice of 80.81%, a sensitivity of 79.97%, a specificity of 99.48%, a precision of 85.21%, an F1 score of 83.01%, a structural metric of 84.38%, and a mean absolute error of 0.86%. Additionally, the results of the visual segmentation clearly reflected the ground truth. The results reveal the proof of principle for using DRL to extract CT masks for an effective diagnosis of COVID-19.

SARS-CoV-2 diagnosis using medical imaging techniques and artificial intelligence: A review.

OBJECTIVE: SARS-CoV-2 is a worldwide health emergency with unrecognized clinical features. This paper aims to review the most recent medical imaging techniques used for the diagnosis of SARS-CoV-2 and their potential contributions to attenuate the pandemic. Recent researches, including artificial intelligence tools, will be described. METHODS: We review the main clinical features of SARS-CoV-2 revealed by different medical imaging techniques. First, we present the clinical findings of each technique. Then, we describe several artificial intelligence approaches introduced for the SARS-CoV-2 diagnosis. RESULTS: CT is the most accurate diagnostic modality of SARS-CoV-2. Additionally, ground-glass opacities and consolidation are the most common signs of SARS-CoV-2 in CT images. However, other findings such as reticular pattern, and crazy paving could be observed. We also found that pleural effusion and pneumothorax features are less common in SARS-CoV-2. According to the literature, the B lines artifacts and pleural line irregularities are the common signs of SARS-CoV-2 in ultrasound images. We have also stated the different studies, focusing on artificial intelligence tools, to evaluate the SARS-CoV-2 severity. We found that most of the reported works based on deep learning focused on the detection of SARS-CoV-2 from medical images while the challenge for the radiologists is how to differentiate between SARS-CoV-2 and other viral infections with the same clinical features. CONCLUSION: The identification of SARS-CoV-2 manifestations on medical images is a key step in radiological workflow for the diagnosis of the virus and could be useful for researchers working on computer-aided diagnosis of pulmonary infections.

Partial congenital absence of the pericardium: a case report

Abstract The complete or the partial absence of pericardium is a rare congenital malformation for which the patients are commonly asymptomatic and the diagnosis is incidental. The absence of the left side of the pericardium is the most common anomaly that is reported in the literature while the complete absence of pericardium or the absence of the right side of the pericardium are uncommon and their criteria are still unrecognized given their rare occurrence in clinical practice. This paper aims to report a case of 19-year-old male with the congenital partial absence of both sides of the pericardium and to highlight the symptoms and the different cardiac imaging modalities used to confirm the diagnosis of this defect.

Partial Congenital Absence of The Pericardium: A Case Report.

The complete or the partial absence of pericardium is a rare congenital malformation for which the patients are commonly asymptomatic and the diagnosis is incidental. The absence of the left side of the pericardium is the most common anomaly that is reported in the literature while the complete absence of pericardium or the absence of the right side of the pericardium are uncommon and their criteria are still unrecognized given their rare occurrence in clinical practice. This paper aims to report a case of 19-year-old male with the congenital partial absence of both sides of the pericardium and to highlight the symptoms and the different cardiac imaging modalities used to confirm the diagnosis of this defect.

Comparison Between 3D Echocardiography and Cardiac Magnetic Resonance Imaging (CMRI) in the Measurement of Left Ventricular Volumes and Ejection Fraction.

BACKGROUND: Echocardiography and Cardiac Magnetic Resonance Imaging (CMRI) are two noninvasive techniques for the evaluation of cardiac function for patients with coronary artery diseases. Although echocardiography is the commonly used technique in clinical practice for the assessment of cardiac function, the measurement of LV volumes and left ventricular ejection fraction (LVEF) by the use of this technique is still influenced by several factors inherent to the protocol acquisition, which may affect the accuracy of echocardiography in the measurement of global LV parameters. OBJECTIVE: The aim of this study is to compare the end systolic volume (ESV), the end diastolic volume (EDV), and the LVEF values obtained with three dimensional echocardiography (3D echo) with those obtained by CMRI (3 Tesla) in order to estimate the accuracy of 3D echo in the assessment of cardiac function. METHODS: 20 subjects, (9 controls, 6 with myocardial infarction, and 5 with myocarditis) with age varying from 18 to 58, underwent 3D echo and CMRI. LV volumes and LVEF were computed from CMRI using a stack of cine MRI images in a short axis view. The same parameters were calculated using the 3D echo. A linear regression analysis and Bland Altman diagrams were performed to evaluate the correlation and the degree of agreement between the measurements obtained by the two methods. RESULTS: The obtained results show a strong correlation between the 3D echo and CMR in the measurement of functional parameters (r = 0.96 for LVEF values, r = 0.99 for ESV and r= 0.98 for EDV, p < 0.01 for all) with a little lower values of LV volumes and higher values of LVEF by 3D echo compared to CMRI. According to statistical analysis, there is a slight discrepancy between the measurements obtained by the two methods. CONCLUSION: 3D echo represents an accurate noninvasive tool for the assessment of cardiac function. However, other studies should be conducted on a larger population including some complicated diagnostic cases.

The Role of Phase Image in the Detection of Myocardial Dyskinesia by Magnetic Resonance Imaging (MRI).

BACKGROUND: The assessment of cardiac wall motion abnormalities plays an important role in the evaluation of many cardiovascular diseases and the prediction of functional recovery. Most of the methods dedicated to identifying the location of wall motion abnormalities have been restricted to study hypokinesia while an accurate way to assess dyskinesia is still needed in Cardiac Magnetic Resonance Imaging (CMRI). OBJECTIVE: The aim of this study is to propose a phase image based on the analytic signal able to assess the extent of the myocardial dyskinetic segments in Cardiac Magnetic Resonance Imaging (CMRI). MATERIALS: 22 subjects were retrospectively enrolled in this study (age 46 ± 11): 15 presenting an aneurysm and 7 control subjects with normal wall motion. For each patient, three standard views (short axis view, 2 chamber and 4 chamber views) were acquired using 3 Tesla Siemens Avanto MRI scanner and a segmented True FISP sequence. All the cine MRI images were analyzed by two experimented observers who were blinded to the diagnostic results. RESULTS: The outcomes of this study show that using the proposed phase image in MRI clinical routine can increase the accuracy of the detection of myocardial dyskinetic segments from 77.23 % to 86.38 %, the sensitivity from 67.48 % to 78.86 % as well the specificity from 80.92 % to 89.23 % compared to the standard method based on cine MRI interpretation. CONCLUSION: The phase image is a promising tool in CMRI for the assessment of dyskinetic segments and the degree of myocardial asynchronism.

Left ventricular MRI wall motion assessment by monogenic signal amplitude image computation.

BACKGROUND: Cardiac Magnetic Resonance Imaging (MRI) is the commonly used technique for the assessment of left ventricular (LV) function. Apart manually or semi-automatically contouring LV boundaries for quantification of By visual interpretation of cine images, assessment of regional wall motion is performed by visual interpretation of cine images, thus relying on an experience-dependent and subjective modality. OBJECTIVE: The aim of this work is to describe a novel algorithm based on the computation of the monogenic amplitude image to be utilized in conjunction with conventional cine-MRI visualization to assess LV motion abnormalities and to validate it against gold standard expert visual interpretation. METHODS: The proposed method uses a recent image processing tool called "monogenic signal" to decompose the MR images into features, which are relevant for motion estimation. Wall motion abnormalities are quantified locally by measuring the temporal variations of the monogenic signal amplitude. The new method was validated by two non-expert radiologists using a wall motion scoring without and with the computed image, and compared against the expert interpretation. The proposed approach was tested on a population of 40 patients, including 8 subjects with normal ventricular function and 32 pathological cases (20 with myocardial infarction, 9 with myocarditis, and 3 with dilated cardiomyopathy). RESULTS: The results show that, for both radiologists, sensitivity, specificity and accuracy of cine-MRI alone were similar and around 59%, 77%, and 71%, respectively. Adding the proposed amplitude image while visualizing the cine MRI images significantly increased both sensitivity, specificity and accuracy up to 75%, 89%, and 84%, respectively. CONCLUSION: Accuracy of wall motion interpretation adding amplitude image to conventional visualization was proven feasible and superior to standard image interpretation on the considered population, in inexperienced observers. Adding the amplitude images as a diagnostic tool in clinical routine is likely to improve the detection of myocardial segments presenting a cardiac dysfunction.

Parametric Imaging for the Assessment of Cardiac Motion: A Review.

The assessment of wall motion abnormalities such as hypokinesia or dyskinesia and the identification of their extent as well as their degree of severity allow an accurate evaluation of several ischemic heart diseases and an early diagnosis of heart failure. These dysfunctions are usually revealed by a drop of contraction indicating a regional hypokinesia or a total absence of the wall motion in case of akinesia. The discrimination between these contraction abnormalities plays also a significant role in the therapeutic decision through the differentiation between the infarcted zones, which have lost their contractile function, and the stunned areas that still retain viable myocardial tissues. The lack of a reliable method for the evaluation of wall motion abnormalities in cardiac imaging presents a major limitation for a regional assessment of the left ventricular function. In the past years, several techniques were proposed as additional tools for the local detection of wall motion deformation. Among these approaches, the parametric imaging is likely to represent a promising technique for the analysis of a local contractile function. The aim of this paper is to review the most recent techniques of parametric imaging computation developed in cardiac imaging and their potential contributions in clinical practice.

Interpretation of cardiac wall motion from cine-MRI combined with parametric imaging based on the Hilbert transform.

OBJECT: The aim of this study was to test and validate the clinical impact of parametric amplitude images obtained using the Hilbert transform on the regional interpretation of cardiac wall motion abnormalities from cine-MR images by non-expert radiologists compared with expert consensus. MATERIALS AND METHODS: Cine-MRI short-axis images obtained in 20 patients (10 with myocardial infarction, 5 with myocarditis and 5 with normal function) were processed to compute a parametric amplitude image for each using the Hilbert transform. Two expert radiologists blindly reviewed the cine-MR images to define a gold standard for wall motion interpretation for each left ventricular sector. Two non-expert radiologists reviewed and graded the same images without and in combination with parametric images. Grades assigned to each segment in the two separate sessions were compared with the gold standard. RESULTS: According to expert interpretation, 264/320 (82.5%) segments were classified as normal and 56/320 (17.5%) were considered abnormal. The accuracy of the non-expert radiologists' grades compared to the gold standard was significantly improved by adding parametric images (from 87.2 to 94.6%) together with sensitivity (from 64.29 to 84.4%) and specificity (from 92 to 96.9%), also resulting in reduced interobserver variability (from 12.8 to 5.6%). CONCLUSION: The use of parametric amplitude images based on the Hilbert transform in conjunction with cine-MRI was shown to be a promising technique for improvement of the detection of left ventricular wall motion abnormalities in less expert radiologists.