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Ultrafast Brain MRI with Deep Learning Reconstruction for Suspected Acute Ischemic Stroke.
Altmann, Sebastian; Grauhan, Nils F; Brockstedt, Lavinia; Kondova, Mariya; Schmidtmann, Irene; Paul, Roman; Clifford, Bryan; Feiweier, Thorsten; Hosseini, Zahra; Uphaus, Timo; Groppa, Sergiu; Brockmann, Marc A; Othman, Ahmed E.
Affiliation
  • Altmann S; From the Department of Neuroradiology (S.A., N.F.G., L.B., M.K., M.A.B., A.E.O.), Institute of Medical Biostatistics, Epidemiology and Informatics (I.S., R.P.), and Department of Neurology (T.U., S.G.), University Medical Center Mainz, Johannes Gutenberg University, Langenbeckstr 1, 55131 Mainz, Ger
  • Grauhan NF; From the Department of Neuroradiology (S.A., N.F.G., L.B., M.K., M.A.B., A.E.O.), Institute of Medical Biostatistics, Epidemiology and Informatics (I.S., R.P.), and Department of Neurology (T.U., S.G.), University Medical Center Mainz, Johannes Gutenberg University, Langenbeckstr 1, 55131 Mainz, Ger
  • Brockstedt L; From the Department of Neuroradiology (S.A., N.F.G., L.B., M.K., M.A.B., A.E.O.), Institute of Medical Biostatistics, Epidemiology and Informatics (I.S., R.P.), and Department of Neurology (T.U., S.G.), University Medical Center Mainz, Johannes Gutenberg University, Langenbeckstr 1, 55131 Mainz, Ger
  • Kondova M; From the Department of Neuroradiology (S.A., N.F.G., L.B., M.K., M.A.B., A.E.O.), Institute of Medical Biostatistics, Epidemiology and Informatics (I.S., R.P.), and Department of Neurology (T.U., S.G.), University Medical Center Mainz, Johannes Gutenberg University, Langenbeckstr 1, 55131 Mainz, Ger
  • Schmidtmann I; From the Department of Neuroradiology (S.A., N.F.G., L.B., M.K., M.A.B., A.E.O.), Institute of Medical Biostatistics, Epidemiology and Informatics (I.S., R.P.), and Department of Neurology (T.U., S.G.), University Medical Center Mainz, Johannes Gutenberg University, Langenbeckstr 1, 55131 Mainz, Ger
  • Paul R; From the Department of Neuroradiology (S.A., N.F.G., L.B., M.K., M.A.B., A.E.O.), Institute of Medical Biostatistics, Epidemiology and Informatics (I.S., R.P.), and Department of Neurology (T.U., S.G.), University Medical Center Mainz, Johannes Gutenberg University, Langenbeckstr 1, 55131 Mainz, Ger
  • Clifford B; From the Department of Neuroradiology (S.A., N.F.G., L.B., M.K., M.A.B., A.E.O.), Institute of Medical Biostatistics, Epidemiology and Informatics (I.S., R.P.), and Department of Neurology (T.U., S.G.), University Medical Center Mainz, Johannes Gutenberg University, Langenbeckstr 1, 55131 Mainz, Ger
  • Feiweier T; From the Department of Neuroradiology (S.A., N.F.G., L.B., M.K., M.A.B., A.E.O.), Institute of Medical Biostatistics, Epidemiology and Informatics (I.S., R.P.), and Department of Neurology (T.U., S.G.), University Medical Center Mainz, Johannes Gutenberg University, Langenbeckstr 1, 55131 Mainz, Ger
  • Hosseini Z; From the Department of Neuroradiology (S.A., N.F.G., L.B., M.K., M.A.B., A.E.O.), Institute of Medical Biostatistics, Epidemiology and Informatics (I.S., R.P.), and Department of Neurology (T.U., S.G.), University Medical Center Mainz, Johannes Gutenberg University, Langenbeckstr 1, 55131 Mainz, Ger
  • Uphaus T; From the Department of Neuroradiology (S.A., N.F.G., L.B., M.K., M.A.B., A.E.O.), Institute of Medical Biostatistics, Epidemiology and Informatics (I.S., R.P.), and Department of Neurology (T.U., S.G.), University Medical Center Mainz, Johannes Gutenberg University, Langenbeckstr 1, 55131 Mainz, Ger
  • Groppa S; From the Department of Neuroradiology (S.A., N.F.G., L.B., M.K., M.A.B., A.E.O.), Institute of Medical Biostatistics, Epidemiology and Informatics (I.S., R.P.), and Department of Neurology (T.U., S.G.), University Medical Center Mainz, Johannes Gutenberg University, Langenbeckstr 1, 55131 Mainz, Ger
  • Brockmann MA; From the Department of Neuroradiology (S.A., N.F.G., L.B., M.K., M.A.B., A.E.O.), Institute of Medical Biostatistics, Epidemiology and Informatics (I.S., R.P.), and Department of Neurology (T.U., S.G.), University Medical Center Mainz, Johannes Gutenberg University, Langenbeckstr 1, 55131 Mainz, Ger
  • Othman AE; From the Department of Neuroradiology (S.A., N.F.G., L.B., M.K., M.A.B., A.E.O.), Institute of Medical Biostatistics, Epidemiology and Informatics (I.S., R.P.), and Department of Neurology (T.U., S.G.), University Medical Center Mainz, Johannes Gutenberg University, Langenbeckstr 1, 55131 Mainz, Ger
Radiology ; 310(2): e231938, 2024 02.
Article in En | MEDLINE | ID: mdl-38376403
ABSTRACT
Background Deep learning (DL)-accelerated MRI can substantially reduce examination times. However, studies prospectively evaluating the diagnostic performance of DL-accelerated MRI reconstructions in acute suspected stroke are lacking. Purpose To investigate the interchangeability of DL-accelerated MRI with conventional MRI in patients with suspected acute ischemic stroke at 1.5 T. Materials and Methods In this prospective study, 211 participants with suspected acute stroke underwent clinically indicated MRI at 1.5 T between June 2022 and March 2023. For each participant, conventional MRI (including T1-weighted, T2-weighted, T2*-weighted, T2 fluid-attenuated inversion-recovery, and diffusion-weighted imaging; 14 minutes 18 seconds) and DL-accelerated MRI (same sequences; 3 minutes 4 seconds) were performed. The primary end point was the interchangeability between conventional and DL-accelerated MRI for acute ischemic infarction detection. Secondary end points were interchangeability regarding the affected vascular territory and clinically relevant secondary findings (eg, microbleeds, neoplasm). Three readers evaluated the overall occurrence of acute ischemic stroke, affected vascular territory, clinically relevant secondary findings, overall image quality, and diagnostic confidence. For acute ischemic lesions, size and signal intensities were assessed. The margin for interchangeability was chosen as 5%. For interrater agreement analysis and interrater reliability analysis, multirater Fleiss κ and the intraclass correlation coefficient, respectively, was determined. Results The study sample consisted of 211 participants (mean age, 65 years ± 16 [SD]); 123 male and 88 female). Acute ischemic stroke was confirmed in 79 participants. Interchangeability was demonstrated for all primary and secondary end points. No individual equivalence indexes (IEIs) exceeded the interchangeability margin of 5% (IEI, -0.002 [90% CI -0.007, 0.004]). Almost perfect interrater agreement was observed (P > .91). DL-accelerated MRI provided higher overall image quality (P < .001) and diagnostic confidence (P < .001). The signal properties of acute ischemic infarctions were similar in both techniques and demonstrated good to excellent interrater reliability (intraclass correlation coefficient, ≥0.8). Conclusion Despite being four times faster, DL-accelerated brain MRI was interchangeable with conventional MRI for acute ischemic lesion detection. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Haller in this issue.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Stroke / Deep Learning / Ischemic Stroke Limits: Aged / Female / Humans / Male Language: En Journal: Radiology Year: 2024 Document type: Article Country of publication: Estados Unidos

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Stroke / Deep Learning / Ischemic Stroke Limits: Aged / Female / Humans / Male Language: En Journal: Radiology Year: 2024 Document type: Article Country of publication: Estados Unidos