Deep learning-based image reconstruction for the multi-arterial phase images: improvement of the image quality to assess the small hypervascular hepatic tumor on gadoxetic acid-enhanced liver MRI.

التفاصيل البيبلوغرافية
العنوان:	Deep learning-based image reconstruction for the multi-arterial phase images: improvement of the image quality to assess the small hypervascular hepatic tumor on gadoxetic acid-enhanced liver MRI.
المؤلفون:	Yun SM; Department of Radiology, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Korea., Hong SB; Department of Radiology, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Korea. cinematiclife7@hanmail.net.; Department of Radiology and Research Institute of Radiology, Pusan National University Hospital, Pusan National University School of Medicine, 179 Gudeok-ro, Seo-gu, Busan, 49241, Korea. cinematiclife7@hanmail.net., Lee NK; Department of Radiology, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Korea., Kim S; Department of Radiology, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Korea., Ji YH; Department of Radiology, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Korea., Seo HI; Department of Surgery, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Korea., Park YM; Department of Surgery, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Korea., Noh BG; Department of Surgery, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Korea., Nickel MD; Siemens Healthcare GmbH, Erlangen, Germany.
المصدر:	Abdominal radiology (New York) [Abdom Radiol (NY)] 2024 Jun; Vol. 49 (6), pp. 1861-1869. Date of Electronic Publication: 2024 Mar 21.
نوع المنشور:	Journal Article
اللغة:	English
بيانات الدورية:	Publisher: Springer Country of Publication: United States NLM ID: 101674571 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2366-0058 (Electronic) NLM ISO Abbreviation: Abdom Radiol (NY) Subsets: MEDLINE
أسماء مطبوعة:	Original Publication: [New York] : Springer, [2016]-
مواضيع طبية MeSH:	Gadolinium DTPA* , Liver Neoplasms/diagnostic imaging , Contrast Media , Deep Learning* , Magnetic Resonance Imaging*/methods, Humans ; Female ; Male ; Middle Aged ; Retrospective Studies ; Aged ; Adult ; Image Enhancement/methods ; Image Interpretation, Computer-Assisted/methods ; Liver/diagnostic imaging ; Signal-To-Noise Ratio
مستخلص:	Purpose: To evaluated the impact of a deep learning (DL)-based image reconstruction on multi-arterial-phase magnetic resonance imaging (MA-MRI) for small hypervascular hepatic masses in patients who underwent gadoxetic acid-enhanced liver MRI. Methods: We retrospectively enrolled 55 adult patients (aged ≥ 18 years) with small hepatic hypervascular mass (≤ 3 cm) between December 2022 and February 2023. All patients underwent MA-MRI, subsequently reconstructed with a DL-based application. Qualitative assessment with Linkert scale including motion artifact (MA), liver edge (LE), hepatic vessel clarity (HVC) and image quality (IQ) was performed. Quantitative image analysis including signal to noise ratio (SNR), contrast to noise ratio (CNR) and noise was performed. Results: On both arterial phases (APs), all qualitative parameters were significantly improved after DL-based image reconstruction. (LE on 1st AP, 1.22 vs 1.61; LE on 2nd AP, 1.21 vs 1.65; HVC on 1st AP, 1.24 vs 1.39; HVC on 2nd AP, 1.24 vs 1.44; IQ on 1st AP, 1.17 vs 1.45; IQ on 2nd AP, 1.17 vs 1.47, all p values < 0.05). The SNR, CNR and noise were significantly improved after DL-based image reconstruction. (SNR on AP1, 279.08 vs 176.14; SNR on AP2, 334.34 vs 199.24; CNR on AP1, 106.09 vs 64.14; CNR on AP2, 129.66 vs 73.73; noise on AP1, 1.51 vs 2.33; noise on AP2, 1.45 vs 2.28, all p values < 0.05). Conclusions: Gadoxetic acid-enhanced MA-MRI with DL-based image reconstruction improved the qualitative and quantitative parameters. Despite the short acquisition time, high-quality MA-MRI is now achievable. (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)
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فهرسة مساهمة:	Keywords: Deep-learning image reconstruction; Gadoxetic acid; Liver; Magnetic resonance imaging; Multi-arterial-phase magnetic resonance imaging
المشرفين على المادة:	0 (gadolinium ethoxybenzyl DTPA) K2I13DR72L (Gadolinium DTPA) 0 (Contrast Media)
تواريخ الأحداث:	Date Created: 20240321 Date Completed: 20240628 Latest Revision: 20240628
رمز التحديث:	20240628
DOI:	10.1007/s00261-024-04236-5
PMID:	38512517
قاعدة البيانات:	MEDLINE

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تدمد:	2366-0058
DOI:	10.1007/s00261-024-04236-5