Objectives To evaluate the utility of a deep learning (DL)-based image enhancement for improving the image quality and diagnostic performance of 3D contrast-enhanced T1-weighted black blood (BB) MR imaging for brain metastases. Materials and methods This retrospective study included 126 patients with and 121 patients without brain metastasis who underwent 3-T MRI examinations. Commercially available DL-based MR image enhancement software was utilized for image post-processing. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of enhancing lesions were measured. For qualitative assessment and diagnostic performance evaluation, two radiologists graded the overall image quality, noise, and artifacts of each image and the conspicuity of visible lesions. The Wilcoxon signed-rank test and regression analyses with generalized estimating equations (GEEs) were used for statistical analysis. Results For MR images that were not previously processed using other DL-based methods, SNR and CNR were higher in the DL-enhanced images than in the standard images (438.3 vs. 661.1, p < 0.01; 173.9 vs. 223.5, p < 0.01). Overall image quality and noise were improved in the DL images (p < 0.01, average score-5 proportion 38% vs. 65%; p < 0.01, 43% vs. 74%), whereas artifacts did not significantly differ (p ≥ 0.07). Sensitivity was increased after post-processing from 79 to 86% (p = 0.02), especially for lesions smaller than 5 mm (69 to 78%, p = 0.03), and changes in specificity (p = 0.24) and average false-positive (FP) count (p = 0.18) were not significant. Conclusion DL image enhancement improves the image quality and diagnostic performance of 3D contrast-enhanced T1-weighted BB MR imaging for the detection of small brain metastases. Key Points <Emphasis Type="BoldItalic">Question</Emphasis> Can deep learning (DL)-based image enhancement improve the image quality and diagnostic performance of 3D contrast-enhanced T1-weighted black blood (BB) MR imaging for brain metastases? <Emphasis Type="BoldItalic">Findings</Emphasis> DL-based image enhancement improved image quality of thin slice BB MR images and sensitivity for brain metastasis, particularly for lesions smaller than 5 mm. <Emphasis Type="BoldItalic">Clinical relevance</Emphasis> DL-based image enhancement on BB images may assist in the accurate diagnosis of brain metastasis by achieving better sensitivity while maintaining comparable specificity. Graphical Abstract

Deep learning-based image enhancement for improved black blood imaging in brain metastasis

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2025年8月8日

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Gaeun Oh,
Seungyoon Paik,
Sang Won Jo,
Hye Jeong Choi,
Roh-Eul Yoo,
Seung Hong Choi

摘要

Objectives

To evaluate the utility of a deep learning (DL)-based image enhancement for improving the image quality and diagnostic performance of 3D contrast-enhanced T1-weighted black blood (BB) MR imaging for brain metastases.

Materials and methods

This retrospective study included 126 patients with and 121 patients without brain metastasis who underwent 3-T MRI examinations. Commercially available DL-based MR image enhancement software was utilized for image post-processing. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of enhancing lesions were measured. For qualitative assessment and diagnostic performance evaluation, two radiologists graded the overall image quality, noise, and artifacts of each image and the conspicuity of visible lesions. The Wilcoxon signed-rank test and regression analyses with generalized estimating equations (GEEs) were used for statistical analysis.

Results

For MR images that were not previously processed using other DL-based methods, SNR and CNR were higher in the DL-enhanced images than in the standard images (438.3 vs. 661.1, p < 0.01; 173.9 vs. 223.5, p < 0.01). Overall image quality and noise were improved in the DL images (p < 0.01, average score-5 proportion 38% vs. 65%; p < 0.01, 43% vs. 74%), whereas artifacts did not significantly differ (p ≥ 0.07). Sensitivity was increased after post-processing from 79 to 86% (p = 0.02), especially for lesions smaller than 5 mm (69 to 78%, p = 0.03), and changes in specificity (p = 0.24) and average false-positive (FP) count (p = 0.18) were not significant.

Conclusion

DL image enhancement improves the image quality and diagnostic performance of 3D contrast-enhanced T1-weighted BB MR imaging for the detection of small brain metastases.

Key Points

Question Can deep learning (DL)-based image enhancement improve the image quality and diagnostic performance of 3D contrast-enhanced T1-weighted black blood (BB) MR imaging for brain metastases?

Findings DL-based image enhancement improved image quality of thin slice BB MR images and sensitivity for brain metastasis, particularly for lesions smaller than 5 mm.

Clinical relevance DL-based image enhancement on BB images may assist in the accurate diagnosis of brain metastasis by achieving better sensitivity while maintaining comparable specificity.

Graphical Abstract