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Deep learning-based acceleration of Compressed Sense MR imaging of the ankle.
Foreman, Sarah C; Neumann, Jan; Han, Jessie; Harrasser, Norbert; Weiss, Kilian; Peeters, Johannes M; Karampinos, Dimitrios C; Makowski, Marcus R; Gersing, Alexandra S; Woertler, Klaus.
Afiliação
  • Foreman SC; Department of Radiology, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany. sarah.foreman@tum.de.
  • Neumann J; Department of Radiology, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany.
  • Han J; Department of Radiology, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany.
  • Harrasser N; Department of Orthopaedic Surgery, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany.
  • Weiss K; Philips GmbH, Röntgenstrasse 22, 22335, Hamburg, Germany.
  • Peeters JM; Philips Healthcare, Veenpluis 4-6, Building QR-0.113, 5684, Best, PC, Netherlands.
  • Karampinos DC; Department of Radiology, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany.
  • Makowski MR; Department of Radiology, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany.
  • Gersing AS; Department of Radiology, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany.
  • Woertler K; Department of Neuroradiology, University Hospital Munich (LMU), Marchioninistrasse 15, 81377, Munich, Germany.
Eur Radiol ; 32(12): 8376-8385, 2022 Dec.
Article em En | MEDLINE | ID: mdl-35751695
ABSTRACT

OBJECTIVES:

To evaluate a compressed sensing artificial intelligence framework (CSAI) to accelerate MRI acquisition of the ankle.

METHODS:

Thirty patients were scanned at 3T. Axial T2-w, coronal T1-w, and coronal/sagittal intermediate-w scans with fat saturation were acquired using compressed sensing only (1244 min, CS), CSAI with an acceleration factor of 4.6-5.3 (645 min, CSAI2x), and CSAI with an acceleration factor of 6.9-7.7 (446 min, CSAI3x). Moreover, a high-resolution axial T2-w scan was obtained using CSAI with a similar scan duration compared to CS. Depiction and presence of abnormalities were graded. Signal-to-noise and contrast-to-noise were calculated. Wilcoxon signed-rank test and Cohen's kappa were used to compare CSAI with CS sequences.

RESULTS:

The correlation was perfect between CS and CSAI2x (κ = 1.0) and excellent for CS and CSAI3x (κ = 0.86-1.0). No significant differences were found for the depiction of structures between CS and CSAI2x and the same abnormalities were detected in both protocols. For CSAI3x the depiction was graded lower (p ≤ 0.001), though most abnormalities were also detected. For CSAI2x contrast-to-noise fluid/muscle was higher compared to CS (p ≤ 0.05), while no differences were found for other tissues. Signal-to-noise and contrast-to-noise were higher for CSAI3x compared to CS (p ≤ 0.05). The high - resolution axial T2-w sequence specifically improved the depiction of tendons and the tibial nerve (p ≤ 0.005).

CONCLUSIONS:

Acquisition times can be reduced by 47% using CSAI compared to CS without decreasing diagnostic image quality. Reducing acquisition times by 63% is feasible but should be reserved for specific patients. The depiction of specific structures is improved using a high-resolution axial T2-w CSAI scan. KEY POINTS • Prospective study showed that CSAI enables reduction in acquisition times by 47% without decreasing diagnostic image quality. • Reducing acquisition times by 63% still produces images with an acceptable diagnostic accuracy but should be reserved for specific patients. • CSAI may be implemented to scan at a higher resolution compared to standard CS images without increasing acquisition times.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Artefatos / Aprendizado Profundo Tipo de estudo: Guideline / Observational_studies Limite: Humans Idioma: En Revista: Eur Radiol Assunto da revista: RADIOLOGIA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Alemanha

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Artefatos / Aprendizado Profundo Tipo de estudo: Guideline / Observational_studies Limite: Humans Idioma: En Revista: Eur Radiol Assunto da revista: RADIOLOGIA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Alemanha