The international journal of cardiovascular imaging最新文献

The term acute aortic syndrome (AAS) refers to a range of different entities, including dissection, intramural haematoma and penetrating atherosclerotic ulcer. Patients with chronic renal disease and particularly those with dominant polycystic kidney disease are susceptible to this pathology, given the underlying renal arteriopathy and hypertension. Imaging plays a crucial role in diagnosing, grading and guiding management of these patients, with computed tomography angiography (CTA) being on the frontline. Albeit of overlapping of imaging findings between these conditions, specific imaging characteristics help discriminate and guide treatment. Given the nephrotoxic contrast agent involved, tailored CTA protocols or alternative imaging modalities such as MRI or US are necessary in this patient population. This review article discusses the main imaging findings of entities found in the spectrum of AAS, as well as the appropriate use and protocol of imaging modalities, focusing on the appropriate use of nephrotoxic contrast agents, the preservation of renal function and maintenance of optimal diagnostic accuracy.

Background: Intracardiac echocardiography (ICE) appears to be a potential alternative for percutaneous left atrial appendage occlusion (LAAO) to transesophageal echocardiography (TEE). Thus, a meta-analysis was performed comparing ICE vs. TEE for LAAO guidance.

Methods: A comprehensive literature search was performed using MEDLINE, Scopus and Web of Science electronic databases from their inception to November 2023.

Results: 18 studies (124,230 patients) were included. Technical success was higher in ICE- compared to TEE-guidance (OR: 1.36, 95% CI 1.14 to 1.63, p = 0.006) and fewer devices employed (SMD: -0.22, 95% CI -0.43 to -0.01, p = 0.04, I2 = 62%). ICE guidance related with more pericardial effusion/tamponade and iatrogenic residual shunts (logRR: 0.62, 95% CI 0.36 to 0.89, p < 0.001 and RR: 1.53, 95% CI 1.12 to 2.09, p = 0.02, I2 = 1%, respectively). More vascular complications were noted in ICE group (logRR: 0.45, 95% CI 0.11 to 0.78, p = 0.009).

Conclusion: ICE-guided imaging is an effective alternative to TEE in LAAO, as it shows better efficacy than TEE, considering technical success. However, the higher rates of adverse events should be carefully considered.

Background: Pulmonary stenosis (PS) is common in congenital heart disease and an integral finding in Tetralogy of Fallot (TOF). Pulmonary regurgitation (PR) is more commonly found following surgery in repaired TOF. We aimed to evaluate the haemodynamic effects of PS and PR on cardiac physiology in a porcine model using cardiac magnetic resonance-based feature tracking (CMR-FT) deformation imaging.

Methods: CMR-FT was performed in 14 pigs before and 10-12 weeks after surgery. Surgery included either pulmonary artery banding to simulate PS (n = 7), or an incision to the pulmonary valve to simulate PR (n = 7). CMR-FT assessment included left and right ventricular global longitudinal (LV/RV GLS) and LV circumferential (GCS) strain and strain rates (SR) as well as left and right atrial reservoir/conduit/booster pump (LA/RA Es, Ee, Ea) strain and SR.

Results: RV GLS was significantly reduced following PS compared to PR induction (PS -7.51 vs. PR -23.84, p < 0.001). RV GLS improved after induction of PR (before - 20.50 vs. after - 23.84, p = 0.018) as opposed to PS (before - 11.73 vs. after - 7.51, p = 0.128). Similarly, RA Es (PS 14.22 vs. PR 27.34, p = 0.017) and Ee (PS 8.65 vs. PR 20.51, p = 0.004) were decreased in PS compared to PR with detrimental impact of PS (Es before 23.20 vs. after 14.22, p = 0.018, Ee before 15.04 vs. after 8.65, p = 0.028) but not PR (Es before 31.65 vs. after 27.34, p = 0.176, Ee before 20.63 vs. after 20.51, p = 0.499).

Conclusions: In a porcine model of RV pressure vs. volume overload, increased after- but not preload shows detrimental impact on RV and RA physiology.

The purpose of this study was to explore the impact of papillary muscle (PPM) infarction on left atrial and ventricular strain parameters in patients with non-anterior ST-segment elevation myocardial infarction (NA-STEMI) using cardiovascular magnetic resonance (CMR). This retrospective study performed CMR scans on 88 consecutive patients with NA-STEMI (68 males, 65 ± 10.05 years). Among them, 30 demonstrated PPM infarction (25 males, 67.12 ± 9.49 years), defined as late gadolinium enhancement (LGE) in a papillary muscle head in two contiguous LGE CMR slices, and confirmed on the long-axis LGE CMR slices. Atrial and ventricular strain were analyzed by CMR feature tracking with dedicated post-processing software. Patients with PPM infarction were older (p = 0.001), with lower left ventricular ejection fraction (p = 0.040), higher indexed left ventricular end-diastolic volume (p = 0.020), and end-systolic volume (p = 0.044) compared to patients without LGE in the papillary muscle. Additionally, patients with PPM infarction showed impaired reservoir strain, booster strain, global longitudinal strain (GLS), and higher LGE extent compared to NA-STEMI patients without PPM involvement (p = 0.001, p = 0.004, p = 0.001, and p = 0.003, respectively). In multivariable analysis, GLS, global radial strain, reservoir strain, and booster strain parameters were the only independent determinants of PPM infarction (p = 0.001, p = 0.041, p = 0.002, and p = 0.027, respectively). The presence of PPM infarction assessed by CMR is independently linked to atrial and ventricular strain impairment in patients with NA-STEMI.

Computed tomography (CT)-derived Epicardial Adipose Tissue (EAT) is linked to cardiovascular disease outcomes. However, its role in patients undergoing Transcatheter Aortic Valve Replacement (TAVR) and the interplay with aortic stenosis (AS) cardiac damage (CD) remains unexplored. We aim to investigate the relationship between EAT characteristics, AS CD, and all-cause mortality. We retrospectively included consecutive patients who underwent CT-TAVR followed by TAVR. EAT volume and density were estimated using a deep-learning platform and CD was assessed using echocardiography. Patients were classified according to low/high EAT volume and density. All-cause mortality at 4 years was compared using Kaplan-Meier and Cox regression analyses. A total of 666 patients (median age 81 [74-86] years; 54% female) were included. After a median follow-up of 1.28 (IQR 0.53-2.57) years, 11.7% (n = 77) of patients died. The EAT volume (p = 0.017) decreased, and density increased (p < 0.001) with worsening AS CD. Patients with low EAT volume (< 49cm³) and high density (≥-86 HU) had higher all-cause mortality (log-rank p = 0.02 and p = 0.01, respectively), even when adjusted for age, sex, and clinical characteristics (HR 1.71, p = 0.02 and HR 1.73, p = 0.03, respectively). When CD was added to the model, low EAT volume (HR 1.67 p = 0.03) and CD stages 3 and 4 (HR 3.14, p = 0.03) remained associated with all-cause mortality. In patients with AS undergoing TAVR, CT-derived low EAT volume, and high density were independently associated with increased 4-year mortality and worse CD stage. Only EAT volume remained associated when adjusted for CD.

This study aimed to evaluate the efficacy of the single-energy metal artifact reduction (SEMAR) algorithm in reducing metal artifacts and enhancing image quality in contrast-enhanced computed tomography (CT) for patients undergoing endovascular aneurysm repair (EVAR) with coil embolization. Thirty-eight patients (mean age 81.0 ± 6 years; 31 men, 7 women) who underwent contrast-enhanced CT following EVAR and internal iliac artery coil embolization between September 2022 and May 2023 were retrospectively analyzed. The Artifact Index (AI) quantified metallic artifacts from internal iliac artery aneurysm coils in CT images, calculated from the standard deviation of the artifact-containing region relative to a reference region. CT values of the external iliac artery at the same slice were also evaluated and compared. Two radiologists independently performed qualitative assessments of SEMAR and non-SEMAR images. SEMAR significantly reduced metal artifacts, decreasing the AI from 171.9 ± 74.5 HU to 35.8 ± 16.9 HU (p < 0.001). The mean CT values of the external iliac artery were similar for SEMAR (259.4 ± 63.7 HU) and non-SEMAR (257.1 ± 63.6 HU, indicating no significant difference. Qualitative assessment scores improved significantly with SEMAR (from 1.0 ± 0.0 to 2.5 ± 0.5; p < 0.001), enhancing visualization of internal iliac artery aneurysms. Interobserver agreement was high (κ = 0.83). The SEMAR algorithm effectively reduces metal artifacts in contrast-enhanced CT, significantly enhancing image quality without altering adjacent artery CT values. These improvements enhance the image quality of post-operative assessments in patients undergoing EVAR with coil embolization.

Anderson-Fabry disease (AFD) is a X-linked lysosomal storage disorder that can result in cardiac dysfunction including left ventricular hypertrophy (LVH) and conduction abnormalities (Frontiers in cardiovascular medicine vol. 10) [1]. The manifestations of AFD in women may be isolated to one organ and occur late in life due to the random inactivation of the X chromosome. This non-classic presentation may make reaching a diagnosis more difficult. In our case, a 63-year-old woman with family history of AFD presenting with chest pain underwent echocardiography which showed LVH. Cardiac magnetic resonance (CMR) was performed confirming LVH as well as identifying extensive late gadolinium enhancement. T1 values were normal. Despite normal T1 values and female sex, a diagnosis of cardiac involvement of AFD should still be considered and was confirmed with genetic testing.

Coronary artery calcification (CAC) is a key marker of coronary artery disease (CAD) but is often underreported in cancer patients undergoing non-gated CT or PET/CT scans. Traditional CAC assessment requires gated CT scans, leading to increased radiation exposure and the need for specialized personnel. This study aims to develop an artificial intelligence (AI) method to automatically detect CAC from non-gated, freely-breathing, low-dose CT images obtained from positron emission tomography/computed tomography scans. A retrospective analysis of 677 PET/CT scans from a medical center was conducted. The dataset was divided into training (88%) and testing (12%) sets. The DLA-3D model was employed for high-resolution representation learning of cardiac CT images. Data preprocessing techniques were applied to normalize and augment the images. Performance was assessed using the area under the curve (AUC), accuracy, sensitivity, specificity and p-values. The AI model achieved an average AUC of 0.85 on the training set and 0.80 on the testing set. The model demonstrated expert-level performance with a specificity of 0.79, a sensitivity of 0.67, and an overall accuracy of 0.73 for the test group. In real-world scenarios, the model yielded a specificity of 0.8, sensitivity of 0.6, and an accuracy of 0.76. Comparison with human experts showed comparable performance. This study developed an AI method utilizing DLA-3D for automated CAC detection in non-gated PET/CT images. Findings indicate reliable CAC detection in routine PET/CT scans, potentially enhancing both cancer diagnosis and cardiovascular risk assessment. The DLA-3D model shows promise in aiding non-specialist physicians and may contribute to improved cardiovascular risk assessment in oncological imaging, encouraging additional CAC interpretation.