nach oben

Erschienen in:

07.09.2023 | Diagnostic Neuroradiology

Feasibility study of super-resolution deep learning-based reconstruction using k-space data in brain diffusion-weighted images

verfasst von: Kensei Matsuo, Takeshi Nakaura, Kosuke Morita, Hiroyuki Uetani, Yasunori Nagayama, Masafumi Kidoh, Masamichi Hokamura, Yuichi Yamashita, Kensuke Shinoda, Mitsuharu Ueda, Akitake Mukasa, Toshinori Hirai

Erschienen in: Neuroradiology | Ausgabe 11/2023

Einloggen, um Zugang zu erhalten

Abstract

Purpose

The purpose of this study is to evaluate the influence of super-resolution deep learning-based reconstruction (SR-DLR), which utilizes k-space data, on the quality of images and the quantitation of the apparent diffusion coefficient (ADC) for diffusion-weighted images (DWI) in brain magnetic resonance imaging (MRI).

Methods

A retrospective analysis was performed on 34 patients who had undergone DWI using a 3 T MRI system with SR-DLR reconstruction based on k-space data in August 2022. DWI was reconstructed with SR-DLR (Matrix = 684 × 684) and without SR-DLR (Matrix = 228 × 228). Measurements were made of the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) in white matter (WM) and grey matter (GM), and the full width at half maximum (FWHM) of the septum pellucidum. Two radiologists assessed image noise, contrast, artifacts, blur, and the overall quality of three image types using a four-point scale. Quantitative and qualitative scores between images with and without SR-DLR were compared using the Wilcoxon signed-rank test.

Results

Images with SR-DLR showed significantly higher SNRs and CNRs than those without SR-DLR (p < 0.001). No statistically significant variances were found in the apparent diffusion coefficients (ADCs) in WM and GM between images with and without SR-DLR (ADC in WM, p = 0.945; ADC in GM, p = 0.235). Moreover, the FWHM without SR-DLR was notably lower compared to that with SR-DLR (p < 0.001).

Conclusion

SR-DLR has the potential to augment the quality of DWI in DL MRI scans without significantly impacting ADC quantitation.

Kono K, Inoue Y, Nakayama K, Shakudo M, Morino M, Ohata K et al (2001) The role of diffusion-weighted imaging in patients with brain tumors. AJNR Am J Neuroradiol 22(6):1081–1088PubMedPubMedCentral

Okorie CK, Ogbole GI, Owolabi MO, Ogun O, Adeyinka A, Ogunniyi A (2015) Role of diffusion-weighted imaging in acute stroke management using low-field magnetic resonance imaging in resource-limited settings. West Afr J Radiol 22(2):61–66CrossRefPubMedPubMedCentral

Butts K, Riederer SJ, Ehman RL, Thompson RM, Jack CR (1994) Interleaved echo planar imaging on a standard MRI system. Magn Reson Med 31(1):67–72CrossRefPubMed

Porter DA, Heidemann RM (2009) High resolution diffusion-weighted imaging using readout-segmented echo-planar imaging, parallel imaging and a two-dimensional navigator-based reacquisition. Magn Reson Med 62(2):468–475CrossRefPubMed

Morelli J, Porter D, Ai F, Gerdes C, Saettele M, Feiweier T et al (2013) Clinical evaluation of single-shot and readout-segmented diffusion-weighted imaging in stroke patients at 3 T. Acta Radiol 54(3):299–306CrossRefPubMed

Wang Y, Ma X, Zhang Z, Dai E, Jeong HK, Xie B et al (2018) A comparison of readout segmented EPI and interleaved EPI in high-resolution diffusion weighted imaging. Magn Reson Imaging 1(47):39–47CrossRef

Kidoh M, Shinoda K, Kitajima M, Isogawa K, Nambu M, Uetani H et al (2020) Deep learning based noise reduction for brain MR imaging: tests on phantoms and healthy volunteers. Magn Reson Med Sci 19(3):195–206CrossRefPubMed

Uetani H, Nakaura T, Nakaura T, Kitajima M, Morita K, Haraoka Kentaro et al (2022) Hybrid deep-learning-based denoising method for compressed sensing in pituitary MRI: comparison with the conventional wavelet-based denoising method. Eur Radiol 32(7):4527–453CrossRefPubMed

Uetani H, Nakaura T, Kitajima M, Yuichi Y, Hamasaki T, Tateishi M et al (2021) A preliminary study of deep learning-based reconstruction specialized for denoising in high-frequency domain: usefulness in high-resolution three-dimensional magnetic resonance cisternography of the cerebellopontine angle. Neuroradiology 63(1):63–71CrossRefPubMed

10.

Higaki T, Nakamura Y, Tatsugami F, Nakaura T, Awai K (2019) Improvement of image quality at CT and MRI using deep learning. Jpn J Radiol 37(1):73–80CrossRefPubMed

11.

Yasaka K, Akai H, Sugawara H, Tajima T, Akahane M, Yoshioka N et al (2022) Impact of deep learning reconstruction on intracranial 1.5 T magnetic resonance angiography. Jpn J Radiol 40(5):476–83CrossRefPubMed

12.

Chaudhari AS, Fang Z, Kogan F, Wood JP, Stevens KJ, Gibbons EK et al (2018) Super-resolution musculoskeletal MRI using deep learning. Magn Reson Med 80(5):2139–2154CrossRefPubMedPubMedCentral

13.

Chaudhari AS, Stevens KJ, Wood JP, Chakraborty Amit K, Chakraborty A, Chakraborty Amit et al (2020) Utility of deep learning super-resolution in the context of osteoarthritis MRI biomarkers. J Magn Reson Imaging. 51(3):768–79CrossRefPubMed

14.

Pham CH, Tor-Díez C, Meunier H, Bednarek N, Fablet R et al (2019) Multiscale brain MRI super-resolution using deep 3D convolutional networks. Comput Med Imaging Graph 77:101647CrossRefPubMed

15.

Du YP, Parker DL, Davis WL, Cao G (1994) Reduction of partial-volume artifacts with zero-filled interpolation in three-dimensional MR angiography. J Magn Reson Imaging 4(5):733–741CrossRefPubMed

16.

Bernstein MA, Fain SB, Riederer SJ (2001) Effect of windowing and zero-filled reconstruction of MRI data on spatial resolution and acquisition strategy. J Magn Reson Imaging 14(3):270–280CrossRefPubMed

17.

Kutsuna H, Uematsu S, Shinoda K (2023) High resolution MR reconstruction with functionally separate neural networks. ISMRM. No. 2922

18.

Basser PJ, Mattiello J, LeBihan D (1994) Estimation of the effective self-diffusion tensor from the NMR spin echo. J Magn Reson B 103(3):247–254CrossRefPubMed

19.

Yoshida M, Nakaura T, Inoue T, Tanoue S, Takada S, Utsunomiya D et al (2018) Magnetic resonance cholangiopancreatography with GRASE sequence at 3.0T: does it improve image quality and acquisition time as compared with 3D TSE? Eur Radiol 28(6):2436–43CrossRefPubMed

20.

Chen Z, Pawar K, Ekanayake M, Pain C, Zhong S, Egan GF (2022) Deep learning for image enhancement and correction in magnetic resonance imaging—state-of-the-art and challenges. J Digit Imaging 36(1):204–230CrossRefPubMedPubMedCentral

21.

Zhao M, Wei Y, Wong KKL (2022) A generative adversarial network technique for high-quality super-resolution reconstruction of cardiac magnetic resonance images. Magn Reson Imaging 1(85):153–160CrossRef

22.

Chun J, Chun J, Zhang H, Gach HM, Olberg S, Mazur TR et al (2019) MRI super-resolution reconstruction for MRI-guided adaptive radiotherapy using cascaded deep learning: in the presence of limited training data and unknown translation model. Med Phys 46(9):4148–4164CrossRefPubMed

23.

Gibbs JW (1898) Fourier’s Series. Nature 59(1522):200–200CrossRef

Titel: Feasibility study of super-resolution deep learning-based reconstruction using k-space data in brain diffusion-weighted images
verfasst von: Kensei Matsuo
Takeshi Nakaura
Kosuke Morita
Hiroyuki Uetani
Yasunori Nagayama
Masafumi Kidoh
Masamichi Hokamura
Yuichi Yamashita
Kensuke Shinoda
Mitsuharu Ueda
Akitake Mukasa
Toshinori Hirai
Publikationsdatum: 07.09.2023
Verlag: Springer Berlin Heidelberg
Erschienen in: Neuroradiology / Ausgabe 11/2023
Print ISSN: 0028-3940
Elektronische ISSN: 1432-1920
DOI: https://doi.org/10.1007/s00234-023-03212-y

Leitlinien kompakt für die Neurologie

Mit medbee Pocketcards sicher entscheiden.

^{Seit 2022 gehört die medbee GmbH zum Springer Medizin Verlag}

Kostenlos registrieren

Neu im Fachgebiet Neurologie

Nicht Creutzfeldt Jakob, sondern Abführtee-Vergiftung

29.05.2024 Hyponatriämie Nachrichten

Eine ältere Frau trinkt regelmäßig Sennesblättertee gegen ihre Verstopfung. Der scheint plötzlich gut zu wirken. Auf Durchfall und Erbrechen folgt allerdings eine Hyponatriämie. Nach deren Korrektur kommt es plötzlich zu progredienten Kognitions- und Verhaltensstörungen.

Schutz der Synapsen bei Alzheimer

29.05.2024 Morbus Alzheimer Nachrichten

Mit einem Neurotrophin-Rezeptor-Modulator lässt sich möglicherweise eine bestehende Alzheimerdemenz etwas abschwächen: Erste Phase-2-Daten deuten auf einen verbesserten Synapsenschutz.

Sozialer Aufstieg verringert Demenzgefahr

24.05.2024 Demenz Nachrichten

Ein hohes soziales Niveau ist mit die beste Versicherung gegen eine Demenz. Noch geringer ist das Demenzrisiko für Menschen, die sozial aufsteigen: Sie gewinnen fast zwei demenzfreie Lebensjahre. Umgekehrt steigt die Demenzgefahr beim sozialen Abstieg.

Hirnblutung unter DOAK und VKA ähnlich bedrohlich

17.05.2024 Direkte orale Antikoagulanzien Nachrichten

Kommt es zu einer nichttraumatischen Hirnblutung, spielt es keine große Rolle, ob die Betroffenen zuvor direkt wirksame orale Antikoagulanzien oder Marcumar bekommen haben: Die Prognose ist ähnlich schlecht.

Update Neurologie

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.

Newsletter bestellen

Live-Webinar "Urologie und Sexualmedizin in der Praxis"

Springer Medizin

Abstract

Purpose

Methods

Results

Conclusion

Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten

Weitere Artikel der Ausgabe 11/2023

Comparison of diffusion weighted imaging b0 with T2*-weighted gradient echo or susceptibility weighted imaging for intracranial hemorrhage detection after reperfusion therapy for ischemic stroke

Ghost twisting of the dual-layer flow-diverting stent

Correction to: Cortical high‑flow sign on arterial spin labeling: a novel biomarker for IDH‑mutation and 1p/19q‑codeletion status in diffuse gliomas without intense contrast enhancement

Impact of cannabis use on brain metabolism using 31P and 1H magnetic resonance spectroscopy

White matter microstructural disruption in minimal hepatic encephalopathy: a neurite orientation dispersion and density imaging (NODDI) study

European Society of Neuroradiology (ESNR)