Journal of medical imaging (Bellingham, Wash.) · 2025
Application of thin-slice and accelerated T1-weighted GRE sequences in 1.5T abdominal magnetic resonance imaging using deep learning image reconstruction.
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Joos Natalie S, Afat Saif, Nickel Marcel Dominik, Weiland Elisabeth, Herrmann Judith, Ursprung Stephan, Almansour Haidara, Lingg Andreas, Werner Sebastian, Haase Bianca, Nikolaou Konstantin, Gassenmaier Sebastian
Аннотация
PURPOSE: Deep-learning (DL)-based image reconstruction (DLR) is a key technique for reducing acquisition time (TA) and increasing morphologic resolution in abdominal magnetic resonance imaging (MRI). We aim to compare the performance of a standard ( VIBE Std ) gradient echo (GRE) sequence with Dixon fat separation versus an accelerated ultra-fast ( VIBE UF ) and high-resolution ( VIBE HR ) T1-weighted GRE sequence with Dixon fat separation and DLR.
APPROACH: A total of 50 patients with an abdominal 1.5T MRI, with a mean age of 59 ± 11 years, were prospectively included from January to July 2023. Each examination protocol included VIBE Std , VIBE UF , and VIBE HR . Both DL sequences use more aggressive parallel imaging and partial Fourier sampling to reduce TA (slice thickness VIBE Std and VIBE UF 3 mm, VIBE HR 2 mm). Evaluation of each contrast-enhanced datasets for noise, artifacts, sharpness/contrast, overall image quality, and diagnostic confidence was performed independently by four radiologists using a Likert scale of 1 to 5 (5 = best).
RESULTS: VIBE UF significantly reduced TA (mean 7.3 s versus 15.0 s ( VIBE Std ) and 14.5 s ( VIBE HR ); p < 0.001 ). Both DL sequences provided significantly better sharpness/contrast for all organs compared with VIBE Std (median 5 versus 4; p < 0.001 ). VIBE UF showed less noise than VIBE Std (median 5 versus 4; p < 0.001 ), but VIBE Std was less artifact-affected than both DL sequences (median 5 versus 4; p < 0.001 ). Overall image quality was superior in both DL sequences compared with VIBE Std (median 5 versus 4; p < 0.001 ). Diagnostic confidence and lesion detectability were not significantly different ( p > 0.05 ).
CONCLUSION: DL-based image reconstruction significantly improves overall image quality for VIBE UF and VIBE HR , with VIBE UF reducing TA by ∼ 50 % .
APPROACH: A total of 50 patients with an abdominal 1.5T MRI, with a mean age of 59 ± 11 years, were prospectively included from January to July 2023. Each examination protocol included VIBE Std , VIBE UF , and VIBE HR . Both DL sequences use more aggressive parallel imaging and partial Fourier sampling to reduce TA (slice thickness VIBE Std and VIBE UF 3 mm, VIBE HR 2 mm). Evaluation of each contrast-enhanced datasets for noise, artifacts, sharpness/contrast, overall image quality, and diagnostic confidence was performed independently by four radiologists using a Likert scale of 1 to 5 (5 = best).
RESULTS: VIBE UF significantly reduced TA (mean 7.3 s versus 15.0 s ( VIBE Std ) and 14.5 s ( VIBE HR ); p < 0.001 ). Both DL sequences provided significantly better sharpness/contrast for all organs compared with VIBE Std (median 5 versus 4; p < 0.001 ). VIBE UF showed less noise than VIBE Std (median 5 versus 4; p < 0.001 ), but VIBE Std was less artifact-affected than both DL sequences (median 5 versus 4; p < 0.001 ). Overall image quality was superior in both DL sequences compared with VIBE Std (median 5 versus 4; p < 0.001 ). Diagnostic confidence and lesion detectability were not significantly different ( p > 0.05 ).
CONCLUSION: DL-based image reconstruction significantly improves overall image quality for VIBE UF and VIBE HR , with VIBE UF reducing TA by ∼ 50 % .