Diagnostic and Interventional Imaging最新文献

Purpose

The purpose of this study was to investigate the prognostic value of left atrioventricular coupling index (LACI) assessed by cardiac computed tomography (CT), to predict cardiovascular death in consecutive patients referred for cardiac CT with coronary analysis.

Materials and methods

Between 2010 and 2020, we conducted a single-centre study with all consecutive patients without known cardiovascular disease referred for cardiac CT. LACI was defined as the ratio of left atrial to left ventricle end-diastolic volumes. The primary outcome was cardiovascular death. Cox regressions were used to evaluate the association between LACI and primary outcome after adjustment for traditional risk factors and cardiac CT angiography findings.

Results

In 1,444 patients (mean age, 70 ± 12 [standard deviation] years; 43% men), 67 (4.3%) patients experienced cardiovascular death after a median follow-up of 6.8 (Q1, Q3: 5.9, 9.1) years. After adjustment, LACI was positively associated with the occurrence of cardiovascular death (adjusted hazard ratio [HR], 1.07 [95% CI: 1.05–1.09] per 1% increment; P < 0.001), and all-cause death (adjusted HR, 1.05 [95% CI: 1.03–1.07] per 1% increment; P <0.001). After adjustment, a LACI ≥ 25% showed the best improvement in model discrimination and reclassification for predicting cardiovascular death above traditional risk factors and cardiac CT findings (C-statistic improvement: 0.27; Nnet reclassification improvement = 0.826; Integrative discrimination index =0.209, all P < 0.001; likelihood-ratio-test, P < 0.001).

Conclusion

LACI measured by cardiac CT is independently associated with cardiovascular death and all-cause death in patients without known cardiovascular disease referred for cardiac CT, with an incremental prognostic value over traditional risk factors and cardiac CT findings.

Purpose

The invasive British Cardiovascular Intervention Society Jeopardy Score (iBCIS-JS) is a simple angiographic scoring system, enabling quantification of the extent of jeopardized myocardium related to clinically significant coronary artery disease (CAD). The purpose of this study was to develop and validate the coronary CT angiography-based BCIS-JS (CT-BCIS-JS) against the iBCIS-JS in patients with suspected or stable CAD.

Materials and methods

Patients who underwent coronary CT angiography followed by invasive coronary angiography, within 90 days were retrospectively included. CT-BCIS-JS and iBCIS-JS were calculated, with a score ≥ 6 indicating extensive CAD. Correlation between the CT-BCIS-JS and iBCIS-JS was searched for using Spearman's coefficient, and agreement with weighted Kappa (κ) analyses.

Results

A total of 122 patients were included. There were 102 men and 20 women with a median age of 62 years (Q1, Q3: 54, 68; age range: 19–83 years). No differences in median CT-BCIS-JS (4; Q1, Q3: 0, 8) and median iBCIS-JS (4; Q1, Q3: 0, 8) were found (P = 0.18). Extensive CAD was identified in 53 (43.4%) and 52 (42.6%) patients using CT-BCIS-JS and iBCIS-JS, respectively (P = 0.88). CT-based and iBCIS-JS showed excellent correlation (r = 0.98; P < 0.001) and almost perfect agreement (κ = 0.93; 95% confidence interval: 0.90–0.97). Agreement for identification of an iBCIS-JS ≥ 6 was almost perfect (κ = 0.94; 95 % confidence interval: 0.87–0.99).

Conclusion

The CT-BCIS-JS represents a feasible, and accurate method for quantification of CAD, with capabilities not different from those of iBCIS-JS. It enables simple, non-invasive identification of patients with anatomically extensive CAD.

Purpose

The purpose of this in vivo animal study was to compare the acute histological effects on the arterial vessel wall of free-flow vs. blocked-flow embolization with metacryloxysulfolane-n‑butyl cyanoacrylate (MS-NBCA) in several concentrations.

Materials and methods

A total of 42 rabbit renal arteries were embolized using MS-NBCA mixed with ethiodized oil. The MS-NBCA concentration was 12.5%, 25%, or 50%. All mixtures were injected under both free-flow and blocked-flow conditions. The rabbits were euthanised 30 min after arterial embolization. Arterial-lumen distension, intimal inflammation and necrosis, peri‑arterial edema, and distality of MS-NBCA penetration were assessed histologically. Multivariable regression analyses were performed using a manual backward procedure, with linear, ordinal and logistic regression to search for factors associated with these outcomes

Results

Marked or severe dilatation was observed in 36 out of 42 arteries (86%) and marked or transmural intimal arteritis in all 42 arteries (42/42; 100%). Lumen dilatation caused focal vessel-wall flattening, which resulted in intimal necrosis. Multifocal necrosis extending from the intima to the media occurred in 23 out of 42 kidneys (55%) and peri‑arterial edema with multifocal vascular leakage in 19 out of 42 kidneys (45%). At multivariable analysis, blocked-flow MS-NBCA injection was associated with greater severity of vessel-wall lesions, including intimal arteritis (P = 0.003) and intimal necrosis (P = 0.014), compared to free-flow injection. Blocked-flow injection was also associated with peri‑arterial edema (P = 0.008) and greater distality of MS-NBCA penetration (P = 0.001).

Conclusion

Blocked-flow MS-NBCA injection during renal artery embolization is significantly associated with more acute arterial-wall damage and greater distality of glue penetration compared to free-flow injection in a rabbit model. These preliminary findings may have clinical implications, as blocked-flow injection is routinely used to treat specific vascular diseases or malformations in human.

Purpose

The purpose of this study was to evaluate the percentage of coronary angiography that can be securely avoided by the interpretation of coronary arteries on pre transcatheter aortic valve implantation CT (TAVI-CT), using CT images obtained with deep-learning reconstruction and motion correction algorithms.

Material and method

All consecutive patients who underwent TAVI-CT and coronary angiography, from December 2021 to July 2022 were screened for inclusion in the study. Patients who had previous coronary artery revascularization or who did not undergo TAVI were excluded. All TAVI-CT examinations were obtained using deep-learning reconstruction and motion correction algorithms. On TAVI-CT examinations, quality and stenosis of coronary artery were analyzed retrospectively. When insufficient image quality and/or when diagnosis or doubt of one significant coronary artery stenosis, patients were considered as having possible coronary artery stenosis. The results of coronary angiography were used as the standard of reference for significant CAS.

Results

A total of 206 patients (92 men; mean age, 80.6 years) were included; of these 27/206 (13%) had significant coronary artery stenosis on coronary angiography and were referred for potential revascularization. Sensitivity, specificity, negative predictive value, positive predictive value, and accuracy of TAVI-CT to identify patients requiring coronary artery revascularization was 100% (95% confidence interval [CI]: 87.2–100%), 100% (95% CI: 96.3–100%), 54% (95% CI: 46.6–61.6), 25% (95% CI: 17.0–34.0%) and 60% (95% CI: 53.1–66.9%) respectively. Intra- and inter observer variability was substantial agreement for quality and decision to recommend coronary angiography. Mean reading time was 2 ± 1.2 (standard deviation) min (range: 1–5 min). Overall, TAVI-CT could potentially rule out indication for revascularization for 97 patients (47%).

Conclusion

Analysis of coronary artery on TAVI-CT using deep-learning reconstruction and motion correction algorithms can potentially safely avoid coronary angiography in 47% of patients.

Purpose

The purpose of this study was to assess the diagnostic capabilities of cardiac magnetic resonance (CMR) T2* mapping in detecting incidental hepatic and cardiac iron overload.

Materials and methods

Patients with various clinical indications for CMR examination were consecutively included at a single center from January 2019 to April 2023. All patients underwent T2* mapping at 1.5 T in a single mid-ventricular short-axis as part of a comprehensive routine CMR protocol. T2* measurements were performed of the heart (using a region-of-interest in the interventricular septum) and the liver, categorized according to the severity of iron overload. The degree of cardiac iron overload was categorized as mild (15 ms < T2* < 20 ms), moderate (10 ms < T2* < 15 ms) and severe (T2* < 10 ms). The degree of hepatic iron overload was categorized as mild (4 ms < T2* < 8 ms), moderate (2 ms < T2* < 4 ms), severe (T2* < 2 ms). Image quality and inter-reader agreement were assessed using intraclass correlation coefficient (ICC).

Results

CMR examinations from 614 patients (374 men, 240 women) with a mean age of 50 ± 18 (standard deviation) years were fully evaluable. A total of 24/614 patients (3.9%) demonstrated incidental hepatic iron overload; of these, 22/614 patients (3.6%) had mild hepatic iron overload, and 2/614 patients (0.3%) had moderate hepatic iron overload. Seven out of 614 patients (1.1%) had incidental cardiac iron overload; of these, 5/614 patients (0.8%) had mild iron overload, 1/614 patients (0.2%) had moderate iron overload, and 1/614 patients (0.2%) had severe iron overload. Good to excellent inter-reader agreement was observed for the assessment of T2* values (ICC, 0.90 for heart [95% confidence interval: 0.88–0.91]; ICC, 0.91 for liver [95% confidence interval: 0.89–0.92]).

Conclusion

Analysis of standard CMR T2* maps detects incidental cardiac and hepatic iron overload in 1.1% and 3.9% of patients, respectively, which may have implications for further patient management. Therefore, despite an overall low number of incidental abnormal findings, T2* imaging may be included in a standardized comprehensive CMR protocol.

Recent advances in artificial intelligence (AI) for cardiac computed tomography (CT) have shown great potential in enhancing diagnosis and prognosis prediction in patients with cardiovascular disease. Deep learning, a type of machine learning, has revolutionized radiology by enabling automatic feature extraction and learning from large datasets, particularly in image-based applications. Thus, AI-driven techniques have enabled a faster analysis of cardiac CT examinations than when they are analyzed by humans, while maintaining reproducibility. However, further research and validation are required to fully assess the diagnostic performance, radiation dose-reduction capabilities, and clinical correctness of these AI-driven techniques in cardiac CT. This review article presents recent advances of AI in the field of cardiac CT, including deep-learning-based image reconstruction, coronary artery motion correction, automatic calcium scoring, automatic epicardial fat measurement, coronary artery stenosis diagnosis, fractional flow reserve prediction, and prognosis prediction, analyzes current limitations of these techniques and discusses future challenges.

Purpose

The purpose of this study was to compare the performance of three magnetic resonance imaging (MRI) reading methods in the follow-up of patients with multiple sclerosis (MS).

Materials and methods

This retrospective study included patients with MS who underwent two brain follow-up MRI examinations with three-dimensional fluid-attenuated inversion recovery (FLAIR) sequences between September 2016 and December 2019. Two neuroradiology residents independently reviewed FLAIR images using three post-processing methods including conventional reading (CR), co-registration fusion (CF), and co-registration subtraction with color-coding (CS), while being blinded to all data but FLAIR images. The presence and number of new, growing, or shrinking lesions were compared between reading methods. The reading time, reading confidence, and inter- and intra-observer agreements were also assessed. An expert neuroradiologist established the standard of reference. Statistical analyses were corrected for multiple testing.

Results

A total of 198 patients with MS were included. There were 130 women and 68 men, with a mean age of 41 ± 12 (standard deviation) years (age range: 21–79 years). Using CS and CF, more patients were detected with new lesions compared to CR (93/198 [47%] and 79/198 [40%] vs. 54/198 [27%], respectively; P < 0.01). The median number of new hyperintense FLAIR lesions detected was significantly greater using CS and CF compared to CR (2 [Q1, Q3: 0, 6] and 1 [Q1, Q3: 0, 3] vs. 0 [Q1, Q3: 0, 1], respectively; P < 0.001). The mean reading time was significantly shorter using CS and CF compared to CR (P < 0.001), with higher confidence in readings and higher inter- and intra-observer agreements.

Conclusion

Post-processing tools such as CS and CF substantially improve the accuracy of follow-up MRI examinations in patients with MS while reducing reading time and increasing readers' confidence and reproducibility.

Purpose

The purpose of this study was to compare a new free-breathing compressed sensing cine (FB-CS) cardiac magnetic resonance imaging (CMR) to the standard reference multi-breath-hold segmented cine (BH-SEG) CMR in an unselected population.

Materials and methods

From January to April 2021, 52 consecutive adult patients who underwent both conventional BH-SEG CMR and new FB-CS CMR with fully automated respiratory motion correction were retrospectively enrolled. There were 29 men and 23 women with a mean age of 57.7 ± 18.9 (standard deviation [SD]) years (age range: 19.0–90.0 years) and a mean cardiac rate of 74.6 ± 17.9 (SD) bpm. For each patient, short-axis stacks were acquired with similar parameters providing a spatial resolution of 1.8 × 1.8 × 8.0 mm³ and 25 cardiac frames. Acquisition and reconstruction times, image quality (Likert scale from 1 to 4), left and right ventricular volumes and ejection fractions, left ventricular mass, and global circumferential strain were assessed for each sequence.

Results

FB-CS CMR acquisition time was significantly shorter (123.8 ± 28.4 [SD] s vs. 267.2 ± 39.3 [SD] s for BH-SEG CMR; P < 0.0001) at the penalty of a longer reconstruction time (271.4 ± 68.7 [SD] s vs. 9.9 ± 2.1 [SD] s for BH-SEG CMR; P < 0.0001). In patients without arrhythmia or dyspnea, FB-CS CMR provided subjective image quality that was not different from that of BH-SEG CMR (P = 0.13). FB-CS CMR improved image quality in patients with arrhythmia (n = 18; P = 0.002) or dyspnea (n = 7; P = 0.02), and the edge sharpness was improved at end-systole and end-diastole (P = 0.0001). No differences were observed between the two techniques in ventricular volumes and ejection fractions, left ventricular mass or global circumferential strain in patients in sinus rhythm or with cardiac arrhythmia.

Conclusion

This new FB-CS CMR addresses respiratory motion and arrhythmia-related artifacts without compromising the reliability of ventricular functional assessment.