From Compressed-Sensing to Deep Learning MR: Comparative Biventricular Cardiac Function Analysis in a Patient Cohort.
J Magn Reson Imaging
; 59(4): 1231-1241, 2024 Apr.
Article
en En
| MEDLINE
| ID: mdl-37435633
ABSTRACT
BACKGROUND:
Conventional segmented, retrospectively gated cine (Conv-cine) is challenged in patients with breath-hold difficulties. Compressed sensing (CS) has shown values in cine imaging but generally requires long reconstruction time. Recent artificial intelligence (AI) has demonstrated potential in fast cine imaging.PURPOSE:
To compare CS-cine and AI-cine with Conv-cine in quantitative biventricular functions, image quality, and reconstruction time. STUDY TYPE Prospective human studies.SUBJECTS:
70 patients (age, 39 ± 15 years, 54.3% male). FIELD STRENGTH/SEQUENCE 3T; balanced steady state free precession gradient echo sequences. ASSESSMENT Biventricular functional parameters of CS-, AI-, and Conv-cine were measured by two radiologists independently and compared. The scan and reconstruction time were recorded. Subjective scores of image quality were compared by three radiologists. STATISTICAL TESTS Paired t-test and two related-samples Wilcoxon sign test were used to compare biventricular functional parameters between CS-, AI-, and Conv-cine. Intraclass correlation coefficient (ICC), Bland-Altman analysis, and Kendall's W method were applied to evaluate agreement of biventricular functional parameters and image quality of these three sequences. A P-value <0.05 was considered statistically significant, and standardized mean difference (SMD) < 0. 100 was considered no significant difference.RESULTS:
Compared to Conv-cine, no statistically significant differences were identified in CS- and AI-cine function results (all P > 0.05), except for very small differences in left ventricle end-diastole volumes of 2.5 mL (SMD = 0.082) and 4.1 mL (SMD = 0.096), respectively. Bland-Altman scatter plots revealed that biventricular function results were mostly distributed within the 95% confidence interval. All parameters had acceptable to excellent interobserver agreements (ICC 0.748-0.989). Compared with Conv-cine (84 ± 13 sec), both CS (14 ± 2 sec) and AI (15 ± 2 sec) techniques reduced scan time. Compared with CS-cine (304 ± 17 sec), AI-cine (24 ± 4 sec) reduced reconstruction time. CS-cine demonstrated significantly lower quality scores than Conv-cine, while AI-cine demonstrated similar scores (P = 0.634).CONCLUSION:
CS- and AI-cine can achieve whole-heart cardiac cine imaging in a single breath-hold. Both CS- and AI-cine have the potential to supplement the gold standard Conv-cine in studying biventricular functions and benefit patients having difficulties with breath-holds. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY STAGE 1.Palabras clave
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Aprendizaje Profundo
/
Ventrículos Cardíacos
Tipo de estudio:
Prognostic_studies
Límite:
Adult
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
J Magn Reson Imaging
Asunto de la revista:
DIAGNOSTICO POR IMAGEM
Año:
2024
Tipo del documento:
Article
País de afiliación:
China