722 research outputs found

    Should the host reaction to anisakiasis influence the treatment? Different clinical presentations in two cases

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    Gastrointestinal anisakiasis is a parasitic infection occurring in people that consume raw or inadequately cooked fish or squid. It is frequently characterized by severe epigastric pain, nausea and vom iting caused by the penetration of the larvae into the gastric wall. Acute gastric anisakiasis with severe chest discomfort is rarely report ed in Italy. On the other hand, gastro-allergic anisakiasis with rash, urticaria and isolated angioedema or anaphylaxis is a clinical entity that has been described only recently. Also, if patients usually develop symptoms within 12 hours after raw seafood ingestion, not always endoscopic exploration can promptly identify the Anisakis larvae. Moreover, some authors consider the prevailing allergic reaction as a natural and effective defense against the parasitic attack. We report two cases of peculiar manifestations of anisakiasis in both acute and chronic forms (severe chest discomfort and anaphylactoid reaction)

    Automated Scar Segmentation from CMR-LGE Images Using a Deep Learning Approach

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    Aim. The presence of myocardial scar is a strong predictor of ventricular remodeling, cardiac dysfunction and mortality. Our aim was to assess quantitatively the presence of scar tissue from cardiac-magnetic-resonance (CMR) with late-Gadolinium-enhancement (LGE) images using a deep-learning (DL) approach. Methods. Scar segmentation was performed automatically with a DL approach based on ENet, a deep fully-convolutional neural network (FCNN). We investigated three different ENet configurations. The first configuration (C1) exploited ENet to retrieve directly scar segmentation from the CMR-LGE images. The second (C2) and third (C3) configurations performed scar segmentation in the myocardial region, which was previously obtained in a manual or automatic way with a state-of-the-art DL method, respectively. Results. When tested on 250 CMR-LGE images from 30 patients, the best-performing configuration (C2) achieved 97% median accuracy (inter-quartile (IQR) range = 4%) and 71% median Dice similarity coefficient (IQR = 32%). Conclusions. DL approaches using ENet are promising in automatically segmenting scars in CMR-LGE images, achieving higher performance when limiting the search area to the manually-defined myocardial region

    A Novel Approach Based on Spatio-temporal Features and Random Forest for Scar Detection Using Cine Cardiac Magnetic Resonance Images

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    Aim. To identify the presence of scar tissue in the left ventricle from Gadolinium (Gd)-free magnetic resonance cine sequences using a learning-based approach relying on spatio-temporal features. Methods. The spatial and temporal features were extracted using local binary patterns from (i) cine end-diastolic frame and (ii) two parametric images of amplitude and phase wall motion, respectively, and classified with Random Forest. Results. When tested on 328 cine sequences from 40 patients, a recall of 70% was achieved, improving significantly the classification resulting from spatial and temporal features processed separately. Conclusions. The proposed approach showed promising results, paving the way for scar identification from Gd-free images

    Atrial and Ventricular Strain Imaging Using CMR in the Prediction of Ventricular Arrhythmia in Patients with Myocarditis

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    (1) Objective: Myocarditis can be associated with ventricular arrhythmia (VA), individual non-invasive risk stratification through cardiovascular magnetic resonance (CMR) is of great clinical significance. Our study aimed to explore whether left atrial (LA) and left ventricle (LV) myocardial strain serve as independent predictors of VA in patients with myocarditis. (2) Methods: This retrospective study evaluated CMR scans in 141 consecutive patients diagnosed with myocarditis based on the updated Lake Louise criteria (29 females, mean age 41 ± 20). The primary endpoint was VA; this encompassed ventricular fibrillation, sustained ventricular tachycardia, nonsustained ventricular tachycardia, and frequent premature ventricular complexes. LA and LV strain function were performed on conventional cine SSFP sequences. (3) Results: After a median follow-up time of 23 months (interquartile range (18–30)), 17 patients with acute myocarditis reached the primary endpoint. In the multivariable Cox regression analysis, LA reservoir (hazard ratio [HR] and 95% confidence interval [CI]: 0.93 [0.87–0.99], p = 0.02), LA booster (0.87 95% CI [0.76–0.99], p = 0.04), LV global longitudinal (1.26 95% CI [1.02–1.55], p = 0.03), circumferential (1.37 95% CI [1.08–1.73], p = 0.008), and radial strain (0.89 95% CI [0.80–0.98], p = 0.01) were all independent determinants of VA. Patients with LV global circumferential strain &gt; −13.3% exhibited worse event-free survival compared to those with values ≀ −13.3% (p &lt; 0.0001). (4) Conclusions: LA and LV strain mechanism on CMR are independently associated with VA events in patients with myocarditis, independent to LV ejection fraction, and late gadolinium enhancement location. Incorporating myocardial strain parameters into the management of myocarditis may improve risk stratification.</p

    Effect of late gadolinium enhancement on left atrial impairment in myocarditis patients

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    ObjectiveThe aims of our study were to investigate the effect of the extent and location of late gadolinium enhancement (LGE) on the left atrium (LA) function in patients with acute myocarditis (AM) using cardiovascular magnetic resonance (CMR).MethodThis retrospective study performed CMR scans in 113 consecutive patients (89 males, 24 females; mean age 45.8 &amp; PLUSMN; 17.3 years) with AM that met the updated Lake Louise criteria. Reservoir, conduit, and booster LA functions were analyzed by CMR feature tracking using dedicated software. Besides LA strain measurements, myocardial scar location and extent were assigned and quantified by LGE imaging.ResultsAM patients with septal LGE had impaired reservoir, conduit, and conduit strain rate function in comparison with AM patients with non-septal LGE (p = 0.001, for all). In fully adjusted multivariable linear regression, reservoir and conduit were significantly associated with left ventricle (LV) LGE location (&amp; beta; coefficient = 8.205, p = 0.007; &amp; beta; coefficient = 5.185, p = 0.026; respectively). In addition, LA parameters decreased according to the increase in the extent of LV fibrosis (LGE &amp; LE; 10%; LGE 11-19%; LGE &amp; GE; 20%). After adjustment in multivariable linear regression, the association with LV LGE extent was no longer statistically significant.ConclusionIn patients with acute myocarditis, LA function abnormalities are significantly associated with LV LGE location, but not with LGE extent. Septal LGE is paralleled by a deterioration of LA reservoir and conduit function.Clinical relevance statementLeft atrium dysfunction is associated with the presence of late gadolinium enhancement in the left ventricle septum and can be useful in the clinical prognostication of patients with acute myocarditis, allowing individually tailored treatment.Key Points &amp; BULL; Myocardial fibrosis is related to atrial impairment.&amp; BULL; The location of myocardial fibrosis is the main determinant of atrial dysfunction in myocarditis patients.&amp; BULL; The quantification of atrial mechanisms may provide more in-depth insight into myocarditis pathophysiology.Key Points &amp; BULL; Myocardial fibrosis is related to atrial impairment.&amp; BULL; The location of myocardial fibrosis is the main determinant of atrial dysfunction in myocarditis patients.&amp; BULL; The quantification of atrial mechanisms may provide more in-depth insight into myocarditis pathophysiology.Key Points &amp; BULL; Myocardial fibrosis is related to atrial impairment.&amp; BULL; The location of myocardial fibrosis is the main determinant of atrial dysfunction in myocarditis patients.&amp; BULL; The quantification of atrial mechanisms may provide more in-depth insight into myocarditis pathophysiology

    Rationale and design of the dual-energy computed tomography for ischemia determination compared to &#8220;gold standard&#8221; non-invasive and invasive techniques (DECIDE-Gold) : a multicenter international efficacy diagnostic study of rest-stress dual-energy computed tomography angiography with perfusion

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    Background: Dual-energy CT (DECT) has potential to improve myocardial perfusion for physiologic assessment of coronary artery disease (CAD). Diagnostic performance of rest-stress DECT perfusion (DECTP) is unknown. Objective: DECIDE-Gold is a prospective multicenter study to evaluate the accuracy of DECT to detect hemodynamic (HD) significant CAD, as compared to fractional flow reserve (FFR) as a reference standard. Methods: Eligible participants are subjects with symptoms of CAD referred for invasive coronary angiography (ICA). Participants will undergo DECTP, which will be performed by pharmacological stress, and participants will subsequently proceed to ICA and FFR. HD-significant CAD will be defined as FFR\ua0 64\ua00.80. In those undergoing myocardial stress imaging (MPI) by positron emission tomography (PET), single photon emission computed tomography (SPECT) or cardiac magnetic resonance (CMR) imaging, ischemia will be graded by % ischemic myocardium. Blinded core laboratory interpretation will be performed for CCTA, DECTP, MPI, ICA, and FFR. Results: Primary endpoint is accuracy of DECTP to detect 651 HD-significant stenosis at the subject level when compared to FFR. Secondary and tertiary endpoints are accuracies of combinations of DECTP at the subject and vessel levels compared to FFR and MPI. Conclusion: DECIDE-Gold will determine the performance of DECTP for diagnosing ischemia

    A token-mixer architecture for CAD-RADS classification of coronary stenosis on multiplanar reconstruction CT images

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    Background and objective: In patients with suspected Coronary Artery Disease (CAD), the severity of stenosis needs to be assessed for precise clinical management. An automatic deep learning-based algorithm to classify coronary stenosis lesions according to the Coronary Artery Disease Reporting and Data System (CAD-RADS) in multiplanar reconstruction images acquired with Coronary Computed Tomography Angiography (CCTA) is proposed. Methods: In this retrospective study, 288 patients with suspected CAD who underwent CCTA scans were included. To model long-range semantic information, which is needed to identify and classify stenosis with challenging appearance, we adopted a token-mixer architecture (ConvMixer), which can learn structural relationship over the whole coronary artery. ConvMixer consists of a patch embedding layer followed by repeated convolutional blocks to enable the algorithm to learn long-range dependences between pixels. To visually assess ConvMixer performance, Gradient-Weighted Class Activation Mapping (Grad-CAM) analysis was used. Results: Experimental results using 5-fold cross-validation showed that our ConvMixer can classify significant coronary artery stenosis (i.e., stenosis with luminal narrowing ≄50%) with accuracy and sensitivity of 87% and 90%, respectively. For CAD-RADS 0 vs. 1–2 vs. 3–4 vs. 5 classification, ConvMixer achieved accuracy and sensitivity of 72% and 75%, respectively. Additional experiments showed that ConvMixer achieved a better trade-off between performance and complexity compared to pyramid-shaped convolutional neural networks. Conclusions: Our algorithm might provide clinicians with decision support, potentially reducing the interobserver variability for coronary artery stenosis evaluation
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