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High-resolution prostate diffusion MRI using eddy current-nulled convex optimized diffusion encoding and random matrix theory-based denoising

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Abstract

Objective

To develop and evaluate a technique combining eddy current-nulled convex optimized diffusion encoding (ENCODE) with random matrix theory (RMT)-based denoising to accelerate and improve the apparent signal-to-noise ratio (aSNR) and apparent diffusion coefficient (ADC) mapping in high-resolution prostate diffusion-weighted MRI (DWI).

Materials and methods

Eleven subjects with clinical suspicion of prostate cancer were scanned at 3T with high-resolution (HR) (in-plane: 1.0 × 1.0 mm2) ENCODE and standard-resolution (1.6 × 2.2 mm2) bipolar DWI sequences (both had 7 repetitions for averaging, acquisition time [TA] of 5 min 50 s). HR-ENCODE was retrospectively analyzed using three repetitions (accelerated effective TA of 2 min 30 s). The RMT-based denoising pipeline utilized complex DWI signals and Marchenko–Pastur distribution-based principal component analysis to remove additive Gaussian noise in images from multiple coils, b-values, diffusion encoding directions, and repetitions. HR-ENCODE with RMT-based denoising (HR-ENCODE-RMT) was compared with HR-ENCODE in terms of aSNR in prostate peripheral zone (PZ) and transition zone (TZ). Precision and accuracy of ADC were evaluated by the coefficient of variation (CoV) between repeated measurements and mean difference (MD) compared to the bipolar ADC reference, respectively. Differences were compared using two-sided Wilcoxon signed-rank tests (P < 0.05 considered significant).

Results

HR-ENCODE-RMT yielded 62% and 56% higher median aSNR than HR-ENCODE (b = 800 s/mm2) in PZ and TZ, respectively (P < 0.001). HR-ENCODE-RMT achieved 63% and 70% lower ADC-CoV than HR-ENCODE in PZ and TZ, respectively (P < 0.001). HR-ENCODE-RMT ADC and bipolar ADC had low MD of 22.7 × 10–6 mm2/s in PZ and low MD of 90.5 × 10–6 mm2/s in TZ.

Conclusions

HR-ENCODE-RMT can shorten the acquisition time and improve the aSNR of high-resolution prostate DWI and achieve accurate and precise ADC measurements in the prostate.

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Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

The authors thank Nashla Barroso, Dr. Preeti Ahuja , study coordinators, and clinicians at UCLA for assisting subject recruitment. The authors thank Mayssam Wehbe, Nicholas Haid, Francine Cobla, Lalageh Arzooian, and Kelly O’Connor at UCLA for their assistance with data acquisition. The authors also thank Fadil Ali, Sevgi Gokce Kafali, and other members in the UCLA Magnetic Resonance Research Labs for helpful discussions.

Funding

This work was supported in part by the National Cancer Institute under award number R01CA248506, the Jonsson Comprehensive Cancer Center at UCLA, and the Integrated Diagnostics Program in the Departments of Radiological Sciences and Pathology of the David Geffen School of Medicine at UCLA. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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Authors and Affiliations

  1. Department of Radiological Sciences, University of California Los Angeles, 300 UCLA Medical Plaza, Suite B119, Los Angeles, CA, 90095, USA

    Zhaohuan Zhang, Elif Aygun, Shu-Fu Shih, Steven S. Raman, Kyunghyun Sung & Holden H. Wu

  2. Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, USA

    Zhaohuan Zhang, Elif Aygun, Shu-Fu Shih, Kyunghyun Sung & Holden H. Wu

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  1. Zhaohuan Zhang
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Contributions

ZZ: study conception and design, acquisition of data, analysis and interpretation of data, drafting of manuscript, critical revision; EA: analysis and interpretation of data, critical revision; SS: study conception and design, critical revision, drafting of manuscript; SR: study conception and design, critical revision; KS: study conception and design, critical revision; HW: study conception and design, drafting of manuscript, critical revision.

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Correspondence to Holden H. Wu.

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Zhang, Z., Aygun, E., Shih, SF. et al. High-resolution prostate diffusion MRI using eddy current-nulled convex optimized diffusion encoding and random matrix theory-based denoising. Magn Reson Mater Phy (2024). https://doi.org/10.1007/s10334-024-01147-w

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