Five-minute knee MRI: An AI-based super resolution reconstruction approach for compressed sensing. A validation study on healthy volunteers.
Eur J Radiol
; 175: 111418, 2024 Jun.
Article
en En
| MEDLINE
| ID: mdl-38490130
ABSTRACT
PURPOSE:
To investigate the potential of combining Compressed Sensing (CS) and a newly developed AI-based super resolution reconstruction prototype consisting of a series of convolutional neural networks (CNN) for a complete five-minute 2D knee MRI protocol.METHODS:
In this prospective study, 20 volunteers were examined using a 3T-MRI-scanner (Ingenia Elitionâ¯X,â¯Philips). Similar to clinical practice, the protocol consists of a fat-saturated 2D-proton-density-sequence in coronal, sagittal and transversal orientation as well as a sagittal T1-weighted sequence. The sequences were acquired with two different resolutions (standard and low resolution) and the raw data reconstructed with two different reconstruction algorithms a conventional Compressed SENSE (CS) and a new CNN-based algorithm for denoising and subsequently to interpolate and therewith increase the sharpness of the image (CS-SuperRes). Subjective image quality was evaluated by two blinded radiologists reviewing 8 criteria on a 5-point Likert scale and signal-to-noise ratio calculated as an objective parameter.RESULTS:
The protocol reconstructed with CS-SuperRes received higher ratings than the time-equivalent CS reconstructions, statistically significant especially for low resolution acquisitions (e.g., overall image impression 4.3⯱â¯0.4 vs. 3.4⯱â¯0.4, pâ¯<â¯0.05). CS-SuperRes reconstructions for the low resolution acquisition were comparable to traditional CS reconstructions with standard resolution for all parameters, achieving a scan time reduction from 1101â¯min to 446â¯min (57â¯%) for the complete protocol (e.g. overall image impression 4.3⯱â¯0.4 vs. 4.0⯱â¯0.5, pâ¯<â¯0.05).CONCLUSION:
The newly-developed AI-based reconstruction algorithm CS-SuperRes allows to reduce scan time by 57% while maintaining unchanged image quality compared to the conventional CS reconstruction.Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Algoritmos
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Imagen por Resonancia Magnética
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Voluntarios Sanos
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Articulación de la Rodilla
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:
Eur J Radiol
Año:
2024
Tipo del documento:
Article