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Objective: After transcatheter aortic valve replacement, the mean transvalvular pressure gradient indicates the effectiveness of the therapy. The objective is to develop artificial intelligence to predict the post-transcatheter aortic valve replacement aortic valve pressure gradient and aortic valve area from preprocedural echocardiography and computed tomography data. Methods: A retrospective study was conducted on patients who underwent transcatheter aortic valve replacement due to aortic valve stenosis. A total of 1091 patients were analyzed for pressure gradient predictions (mean age 76.8 ± 9.2 years, 57.8% male), and 1063 patients were analyzed for aortic valve area predictions (mean age 76.7 ± 9.3 years, 57.2% male). An artificial intelligence learning model was trained (training: n = 663 patients, validation: n = 206 patients) and tested (testing: n = 222 patients) to predict pressure gradient, and a separate artificial intelligence learning model was trained (training: n = 640 patients, validation: n = 218 patients) and tested (testing: n = 205 patients) for predicting aortic valve area. Results: The mean absolute error for pressure gradient and aortic valve area predictions was 3.0 mm Hg and 0.45 cm2, respectively. Valve sheath size, body surface area, and age were determined to be the top 3 predictors for pressure gradient, and valve sheath size, left ventricular ejection fraction, and aortic annulus mean diameter were identified to be the top 3 predictors of post-transcatheter aortic valve replacement aortic valve area. A training dataset size of more than 500 patients demonstrated good robustness of the artificial intelligence models for pressure gradient and aortic valve area. Conclusions: The artificial intelligence-based algorithm has demonstrated potential in predicting post-transcatheter aortic valve replacement transvalvular pressure gradient predictions for patients with aortic valve stenosis. Further studies are necessary to differentiate pressure gradient between valve types.
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BACKGROUND: Ferumoxytol is becoming more widely used as an off-label blood-pool contrast agent for MR angiography (MRA) and four-dimensional (4D) flow imaging in pediatric cardiovascular disease. Brand and generic versions of ferumoxytol are available with no information on relative efficacy as a contrast agent and safety profiles. OBJECTIVE: This study evaluates patient safety and image quality of comparable dosages of generic ferumoxytol (GF) versus brand ferumoxytol (BF) with the following hypotheses: (1) Reducing the contrast dosage from 3 to 2 mg/kg will not affect imaging quality and diagnostic accuracy of MRA and four-dimensional 4D flow. (2) GF and BF have similar image quality. (3) GF and BF have similar patient safety profiles. MATERIALS AND METHODS: In an IRB-approved retrospective study, changes in vitals/clinical status between baseline, during infusion, and 30 min post-infusion were analyzed in 3 groups: group 1 (3 mg/kg BF, 216 patients, age: 19.29 ± 11.71 years ranging from 2 months to 62 years), group 2 (2 mg/kg BF, 47 patients, age: 15.35 ± 8.56 years ranging from 10 days to 41 years), and group 3 (2 mg/kg GF, 127 patients, age: 17.16 ± 12.18 years ranging from 6 days to 58 years). Both pediatric and adult patients with congenital heart disease (CHD) indications were included within the study. Adverse reactions were classified as mild, moderate, or severe. Quantitative analysis of MR image quality was performed with signal-to-noise ratio (SNR) on MRA and velocity-to-noise ratio (VNR) on 4D flow. Qualitative grading of imaging features was performed by 2 experienced observers. Two-way analysis of variance (ANOVA) and chi-square tests were used for comparison with a P value of ≤ 0.05 used for significance. RESULTS: No statistical difference was found in clinical status and vital signs (P>0.05). No severe reactions were reported. 7.9% of GF patients experienced an adverse reaction compared to 2.3% with 3 mg/kg BF and 8.4% with 2 mg/kg BF. There was no statistical difference in SNR between the 3 groups (P>0.05). For 4D flow, 2 mg/kg GF demonstrated an increase in VNR compared to 2 mg/kg BF (P = 0.005). The qualitative scores for MRA and 4D flow were high (≥ 3) across all 3 groups. CONCLUSIONS: No significant difference was identified between 2 mg/kg GF and BF in terms of safety profile and image quality. Given the small sample size of this study, further studies are required to confirm these results.