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Thin-Slice Prostate MRI Enabled by Deep Learning Image Reconstruction.

Sebastian Gassenmaier¹, Verena Warm², Dominik Nickel³

¹Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Hoppe-Seyler-Strasse 3, 72076 Tuebingen, Germany.

|February 11, 2023

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Deep learning accelerated thin-slice MRI (T2_DLR) enhances prostate cancer diagnostics by improving image quality and lesion detection without increasing scan time. This advanced technique offers superior sharpness and overall image quality compared to conventional MRI (T2_S).

Area of Science:

Radiology
Medical Imaging
Oncology

Background:

Thin-slice prostate MRI can improve cancer diagnostics.
Prolonged acquisition time is a limitation of thin-slice MRI.
Deep learning acceleration offers a potential solution to reduce scan times.

Purpose of the Study:

To evaluate the impact of a thin-slice deep learning accelerated T2-weighted (T2_DLR) sequence on prostate MRI.
To compare T2_DLR with conventional T2-weighted TSE imaging (T2_S) regarding image quality and diagnostic performance.
To assess the effect of T2_DLR on acquisition time.

Main Methods:

A prospective study included 30 patients undergoing prostate MRI.
Conventional T2_S (3 mm slices) was acquired, followed by thin-slice T2_DLR (2 mm slices).

Keywords:

MRI deep learning image reconstruction prostate thin-slice

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Radiologists assessed image sharpness, lesion detectability, artifacts, overall quality, and diagnostic confidence using a Likert scale.

Main Results:

T2_DLR demonstrated superior sharpness and lesion detectability compared to T2_S (median 4 vs. 3, p < 0.001).
Overall image quality was significantly better with T2_DLR (median 4 vs. 3, p < 0.001).
Despite slightly longer acquisition time (4:37 min vs. 4:12 min), both readers preferred T2_DLR in 29 cases.

Conclusions:

Thin-slice T2_DLR significantly improves prostate MRI image quality and lesion detection.
This deep learning accelerated sequence achieves these improvements without a significant increase in acquisition time.
T2_DLR represents a promising advancement for prostate cancer diagnostics.