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Magnetic Resonance Materials in Physics, Biology and Medicine

13.02.2024 | Research Article

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

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

Erschienen in: Magnetic Resonance Materials in Physics, Biology and Medicine

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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.

Nur mit Berechtigung zugänglich

Goh V (2023) Tumor physiology and clinically significant prostate cancer detection. Radiol Soc North Am. 306:200–201

Boesen L, Chabanova E, Løgager V, Balslev I, Thomsen HS (2015) Apparent diffusion coefficient ratio correlates significantly with prostate cancer Gleason score at final pathology. J Magn Reson Imaging 42(2):446–453PubMedCrossRef

Tavakoli AA, Hielscher T, Badura P, Görtz M, Kuder TA, Gnirs R, Schwab C, Hohenfellner M, Schlemmer H-P, Bonekamp D (2023) Contribution of dynamic contrast-enhanced and diffusion MRI to PI-RADS for detecting clinically significant prostate cancer. Radiology 306(1):186–199PubMedCrossRef

Fütterer JJ (2016) High-resolution diffusion-weighted imaging increases prostate cancer visibility? EBioMedicine 7:12PubMedPubMedCentralCrossRef

Medved M, Soylu-Boy FN, Karademir I, Sethi I, Yousuf A, Karczmar GS, Oto A (2014) High-resolution diffusion-weighted imaging of the prostate. Am J Roentgenol 203(1):85–90CrossRef

Nguyen C, Sharif-Afshar AR, Fan Z, Xie Y, Wilson S, Bi X, Payor L, Saouaf R, Kim H, Li D (2016) 3 D high-resolution diffusion-weighted MRI at 3 T: Preliminary application in prostate cancer patients undergoing active surveillance protocol for low-risk prostate cancer. Magn Reson Med 75(2):616–626PubMedCrossRef

Reischauer C, Wilm BJ, Froehlich JM, Gutzeit A, Prikler L, Gablinger R, Boesiger P, Wentz K-U (2011) High-resolution diffusion tensor imaging of prostate cancer using a reduced FOV technique. Eur J Radiol 80(2):e34–e41PubMedCrossRef

Sharif-Afshar A-R, Nguyen C, Feng TS, Payor L, Fan Z, Saouaf R, Li D, Kim HL (2016) Prospective pilot trial to evaluate a high resolution diffusion-weighted MRI in prostate cancer patients. EBioMedicine 7:80–84PubMedPubMedCentralCrossRef

Bourne R, Panagiotaki E (2016) Limitations and prospects for diffusion-weighted MRI of the prostate. Diagnostics 6(2):21PubMedPubMedCentralCrossRef

10.

Langer DL, van der Kwast TH, Evans AJ, Sun L, Yaffe MJ, Trachtenberg J, Haider MA (2008) Intermixed normal tissue within prostate cancer: effect on MR imaging measurements of apparent diffusion coefficient and T2—sparse versus dense cancers. Radiology 249(3):900–908PubMedCrossRef

11.

Wu W, Miller KL (2017) Image formation in diffusion MRI: a review of recent technical developments. J Magn Reson Imaging 46(3):646–662PubMedPubMedCentralCrossRef

12.

Lee G, Oto A, Giurcanu M (2022) Prostate MRI: is endorectal coil necessary?—a review. Life 12(4):569PubMedPubMedCentralCrossRefADS

13.

Ullrich T, Kohli M, Ohliger M, Magudia K, Arora S, Barrett T, Bittencourt L, Margolis D, Schimmöller L, Turkbey B (2020) Quality Comparison of 3 Tesla multiparametric MRI of the prostate using a flexible surface receiver coil versus conventional surface coil plus endorectal coil setup. Abdominal Radiology 45:4260–4270PubMedCrossRef

14.

Jambor I (2017) Optimization of prostate MRI acquisition and post-processing protocol: a pictorial review with access to acquisition protocols. Acta Radiologica Open 6(12):2058460117745574PubMedPubMedCentralCrossRef

15.

Aliotta E, Moulin K, Ennis DB (2018) Eddy current–nulled convex optimized diffusion encoding (EN-CODE) for distortion-free diffusion tensor imaging with short echo times. Magn Reson Med 79(2):663–672PubMedCrossRef

16.

Aliotta E, Wu HH, Ennis DB (2017) Convex optimized diffusion encoding (CODE) gradient waveforms for minimum echo time and bulk motion–compensated diffusion-weighted MRI. Magn Reson Med 77(2):717–729PubMedCrossRef

17.

Zhang Z, Moulin K, Aliotta E, Shakeri S, Afshari Mirak S, Hosseiny M, Raman S, Ennis DB, Wu HH (2020) Prostate diffusion MRI with minimal echo time using eddy current nulled convex optimized diffusion encoding. J Magn Reson Imaging 51(5):1526–1539PubMedCrossRef

18.

Kyriazi S, Blackledge M, Collins DJ, Desouza NM (2010) Optimising diffusion-weighted imaging in the abdomen and pelvis: comparison of image quality between monopolar and bipolar single-shot spin-echo echo-planar sequences. Eur Radiol 20:2422–2431PubMedCrossRef

19.

Reese TG, Heid O, Weisskoff R, Wedeen V (2003) Reduction of eddy-current-induced distortion in diffusion MRI using a twice-refocused spin echo. Magn Reson Med 49(1):177–182PubMedCrossRef

20.

Attenberger UI, Rathmann N, Sertdemir M, Riffel P, Weidner A, Kannengiesser S, Morelli JN, Schoenberg SO, Hausmann D (2016) Small field-of-view single-shot EPI-DWI of the prostate: evaluation of spatially-tailored two-dimensional radiofrequency excitation pulses. Z Med Phys 26(2):168–176PubMedCrossRef

21.

Marchenko VA, Pastur LA (1967) Distribution of eigenvalues for some sets of random matrices. Matematicheskii Sbornik 114(4):507–536

22.

Veraart J, Novikov DS, Christiaens D, Ades-Aron B, Sijbers J, Fieremans E (2016) Denoising of diffusion MRI using random matrix theory. Neuroimage 142:394–406PubMedCrossRef

23.

Gavish M, Donoho DL (2017) Optimal shrinkage of singular values. IEEE Trans Inf Theory 63(4):2137–2152MathSciNetCrossRef

24.

Lemberskiy G, Mazaheri Y, Vargas HA, Otazo R, Fieremans E, Novikov DS. Reducing scan time of routine prostate diffusion-weighted imaging using random matrix theory reconstruction. Processings of the 28th Annual Meeting of ISMRM. 2020

25.

Johnson DC, Raman SS, Mirak SA, Kwan L, Bajgiran AM, Hsu W, Maehara CK, Ahuja P, Faiena I, Pooli A (2019) Detection of individual prostate cancer foci via multiparametric magnetic resonance imaging. Eur Urol 75(5):712–720PubMedCrossRef

26.

Wilm BJ, Svensson J, Henning A, Pruessmann KP, Boesiger P, Kollias SS (2007) Reduced field-of-view MRI using outer volume suppression for spinal cord diffusion imaging. Magn Reson Med 57(3):625–630PubMedCrossRef

27.

Padhani AR, Liu G, Mu-Koh D, Chenevert TL, Thoeny HC, Takahara T, Dzik-Jurasz A, Ross BD, Van Cauteren M, Collins D (2009) Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia 11(2):102–125PubMedPubMedCentralCrossRef

28.

Cordero-Grande L, Christiaens D, Hutter J, Price AN, Hajnal JV (2019) Complex diffusion-weighted image estimation via matrix recovery under general noise models. Neuroimage 200:391–404PubMedCrossRef

29.

Lemberskiy G, Baete S, Veraart J, Shepherd TM, Fieremans E, Novikov DS Achieving sub-mm clinical diffusion MRI resolution by removing noise during reconstruction using random matrix theory. In: Processings of the 27th Annual Meeting of ISMRM. 2019.

30.

Moeller S, Pisharady PK, Ramanna S, Lenglet C, Wu X, Dowdle L, Yacoub E, Uğurbil K, Akçakaya M (2021) NOise Reduction with DIstribution Corrected (NORDIC) PCA in dMRI with complex-valued parameter-free locally low-rank processing. Neuroimage 226:117539PubMedCrossRef

31.

Gudbjartsson H, Patz S (1995) The Rician distribution of noisy MRI data. Magn Reson Med 34(6):910–914PubMedPubMedCentralCrossRef

32.

Hutter J, Christiaens DJ, Schneider T, Cordero-Grande L, Slator PJ, Deprez M, Price AN, Tournier J-D, Rutherford M, Hajnal JV (2018) Slice-level diffusion encoding for motion and distortion correction. Med Image Anal 48:214–229PubMedPubMedCentralCrossRef

33.

Powell E, Schneider T, Battiston M, Grussu F, Toosy A, Clayden JD, Wheeler-Kingshott CAG (2022) SENSE EPI reconstruction with 2D phase error correction and channel-wise noise removal. Magn Reson Med 88(5):2157–2166PubMedPubMedCentralCrossRef

34.

Pruessmann KP, Weiger M, Börnert P, Boesiger P (2001) Advances in sensitivity encoding with arbitrary k-space trajectories. Magn Reson Med 46(4):638–651PubMedCrossRef

35.

Heid O. Robust EPI phase correction. Processings of the 5th Annual Meeting of ISMRM. 1997.

36.

Haldar JP, Liu Y, Liao C, Fan Q, Setsompop K (2020) Fast submillimeter diffusion MRI using gSlider-SMS and SNR-enhancing joint reconstruction. Magn Reson Med 84(2):762–776PubMedPubMedCentralCrossRef

37.

Breuer FA, Kannengiesser SA, Blaimer M, Seiberlich N, Jakob PM, Griswold MA (2009) General formulation for quantitative G-factor calculation in GRAPPA reconstructions. Magn Reson Med 62(3):739–746PubMedCrossRef

38.

Walsh DO, Gmitro AF, Marcellin MW (2000) Adaptive reconstruction of phased array MR imagery. Magn Reson Med 43(5):682–690PubMedCrossRef

39.

Dietrich O, Raya JG, Reeder SB, Reiser MF, Schoenberg SO (2007) Measurement of signal-to-noise ratios in MR images: influence of multichannel coils, parallel imaging, and reconstruction filters. J Magn Reson Imaging 26(2):375–385PubMedCrossRef

40.

Baltzer P, Mann RM, Iima M, Sigmund EE, Clauser P, Gilbert FJ, Martincich L, Partridge SC, Patterson A, Pinker K (2020) Diffusion-weighted imaging of the breast—a consensus and mission statement from the EUSOBI International Breast Diffusion-Weighted Imaging working group. Eur Radiol 30:1436–1450PubMedCrossRef

41.

Irfanoglu MO, Sarlls J, Nayak A, Pierpaoli C (2019) Evaluating corrections for eddy-currents and other EPI distortions in diffusion MRI: methodology and a dataset for benchmarking. Magn Reson Med 81(4):2774–2787PubMedCrossRef

42.

Zhang Q, Coolen BF, Versluis MJ, Strijkers GJ, Nederveen AJ (2017) Diffusion-prepared stimulated-echo turbo spin echo (DPsti-TSE): an eddy current-insensitive sequence for three-dimensional high-resolution and undistorted diffusion-weighted imaging. NMR Biomed 30(7):e3719CrossRef

43.

Ades-Aron B, Veraart J, Kochunov P, McGuire S, Sherman P, Kellner E, Novikov DS, Fieremans E (2018) Evaluation of the accuracy and precision of the diffusion parameter EStImation with Gibbs and NoisE removal pipeline. Neuroimage 183:532–543PubMedCrossRef

44.

Ramos-Llordén G, Vegas-Sánchez-Ferrero G, Liao C, Westin CF, Setsompop K, Rathi Y (2021) SNR-enhanced diffusion MRI with structure-preserving low-rank denoising in reproducing kernel Hilbert spaces. Magn Reson Med 86(3):1614–1632PubMedPubMedCentralCrossRef

45.

Bourne R, Liang S, Panagiotaki E, Bongers A, Sved P, Watson G (2017) Measurement and modeling of diffusion time dependence of apparent diffusion coefficient and fractional anisotropy in prostate tissue ex vivo. NMR Biomed 30(10):e3751CrossRef

46.

Lemberskiy G, Fieremans E, Veraart J, Deng F-M, Rosenkrantz AB, Novikov DS (2018) Characterization of prostate microstructure using water diffusion and NMR relaxation. Front phys 6:91PubMedPubMedCentralCrossRef

47.

Lemberskiy G, Rosenkrantz AB, Veraart J, Taneja SS, Novikov DS, Fieremans E (2017) Time-dependent diffusion in prostate cancer. Invest Radiol 52(7):405–411PubMedCrossRef

48.

Zhang Z, Wu HH, Priester A, Magyar C, Afshari Mirak S, Shakeri S, Mohammadian Bajgiran A, Hosseiny M, Azadikhah A, Sung K (2020) Prostate microstructure in prostate cancer using 3-T MRI with diffusion-relaxation correlation spectrum imaging: validation with whole-mount digital histopathology. Radiology 296(2):348–355PubMedCrossRef

49.

Chatterjee A, Watson G, Myint E, Sved P, McEntee M, Bourne R (2015) Changes in epithelium, stroma, and lumen space correlate more strongly with Gleason pattern and are stronger predictors of prostate ADC changes than cellularity metrics. Radiology 277(3):751–762PubMedCrossRef

50.

Purysko AS, Baroni RH, Giganti F, Costa D, Renard-Penna R, Kim CK, Raman SS (2021) PI-RADS version 2.1: a critical review, from the AJR special series on radiology reporting and data systems. Am J Roentgenol. 216(1):20–32CrossRef

51.

Kaye EA, Aherne EA, Duzgol C, Häggström I, Kobler E, Mazaheri Y, Fung MM, Zhang Z, Otazo R, Vargas HA (2020) Accelerating prostate diffusion-weighted MRI using a guided denoising convolutional neural network: retrospective feasibility study. Radiol Artif Intell 2(5):200007CrossRef

52.

Chan CC, Haldar JP (2021) Local perturbation responses and checkerboard tests: characterization tools for nonlinear MRI methods. Magn Reson Med 86(4):1873–1887PubMedPubMedCentralCrossRef

53.

Fernandes FF, Olesen JL, Jespersen SN, Shemesh N (2023) MP-PCA denoising of fMRI time-series data can lead to artificial activation “spreading.” Neuroimage 273:120118PubMedCrossRef

54.

Shih S-F, Zhang Z, Tasdelen B, Yagiz E, Cui SX, Zhong X, Nayak KS, Wu HH. Multi-coil multi-contrast random matrix theory-based denoising for liver fat and R2* quantification at 0.55T. Processings of the 31st Annual Meeting of ISMRM. 2023.

55.

Holdsworth SJ, Skare S, Newbould RD, Guzmann R, Blevins NH, Bammer R (2008) Readout-segmented EPI for rapid high resolution diffusion imaging at 3T. Eur J Radiol 65(1):36–46PubMedCrossRef

Titel: High-resolution prostate diffusion MRI using eddy current-nulled convex optimized diffusion encoding and random matrix theory-based denoising
verfasst von: Zhaohuan Zhang
Elif Aygun
Shu-Fu Shih
Steven S. Raman
Kyunghyun Sung
Holden H. Wu
Publikationsdatum: 13.02.2024
Verlag: Springer International Publishing
Erschienen in: Magnetic Resonance Materials in Physics, Biology and Medicine
Print ISSN: 0968-5243
Elektronische ISSN: 1352-8661
DOI: https://doi.org/10.1007/s10334-024-01147-w

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

Abstract

Objective

Materials and methods

Results

Conclusions

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Die Highlights vom Kongress des American College of Cardiology 2024

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Abstract

Objective

Materials and methods

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Conclusions

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Neu im Fachgebiet Radiologie

„Übersichtlicher Wegweiser“: Lauterbachs umstrittener Klinik-Atlas ist online

Klinikreform soll zehntausende Menschenleben retten

Darf man die Behandlung eines Neonazis ablehnen?

Ein Drittel der jungen Ärztinnen und Ärzte erwägt abzuwandern

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