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Altmann S, Grauhan NF, Brockstedt L, Kondova M, Schmidtmann I, Paul R, Clifford B, Feiweier T, Hosseini Z, Uphaus T, Groppa S, Brockmann MA, Othman AE. Ultrafast Brain MRI with Deep Learning Reconstruction for Suspected Acute Ischemic Stroke. Radiology 2024; 310:e231938. [PMID: 38376403 DOI: 10.1148/radiol.231938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
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.
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Affiliation(s)
- Sebastian Altmann
- 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, Germany; Siemens Medical Solutions USA, Boston, Mass (B.C.); and Siemens Healthcare, Erlangen, Germany (T.F., Z.H.)
| | - Nils F Grauhan
- 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, Germany; Siemens Medical Solutions USA, Boston, Mass (B.C.); and Siemens Healthcare, Erlangen, Germany (T.F., Z.H.)
| | - Lavinia Brockstedt
- 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, Germany; Siemens Medical Solutions USA, Boston, Mass (B.C.); and Siemens Healthcare, Erlangen, Germany (T.F., Z.H.)
| | - Mariya Kondova
- 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, Germany; Siemens Medical Solutions USA, Boston, Mass (B.C.); and Siemens Healthcare, Erlangen, Germany (T.F., Z.H.)
| | - Irene Schmidtmann
- 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, Germany; Siemens Medical Solutions USA, Boston, Mass (B.C.); and Siemens Healthcare, Erlangen, Germany (T.F., Z.H.)
| | - Roman Paul
- 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, Germany; Siemens Medical Solutions USA, Boston, Mass (B.C.); and Siemens Healthcare, Erlangen, Germany (T.F., Z.H.)
| | - Bryan Clifford
- 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, Germany; Siemens Medical Solutions USA, Boston, Mass (B.C.); and Siemens Healthcare, Erlangen, Germany (T.F., Z.H.)
| | - Thorsten Feiweier
- 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, Germany; Siemens Medical Solutions USA, Boston, Mass (B.C.); and Siemens Healthcare, Erlangen, Germany (T.F., Z.H.)
| | - Zahra Hosseini
- 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, Germany; Siemens Medical Solutions USA, Boston, Mass (B.C.); and Siemens Healthcare, Erlangen, Germany (T.F., Z.H.)
| | - Timo Uphaus
- 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, Germany; Siemens Medical Solutions USA, Boston, Mass (B.C.); and Siemens Healthcare, Erlangen, Germany (T.F., Z.H.)
| | - Sergiu Groppa
- 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, Germany; Siemens Medical Solutions USA, Boston, Mass (B.C.); and Siemens Healthcare, Erlangen, Germany (T.F., Z.H.)
| | - Marc A Brockmann
- 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, Germany; Siemens Medical Solutions USA, Boston, Mass (B.C.); and Siemens Healthcare, Erlangen, Germany (T.F., Z.H.)
| | - Ahmed E Othman
- 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, Germany; Siemens Medical Solutions USA, Boston, Mass (B.C.); and Siemens Healthcare, Erlangen, Germany (T.F., Z.H.)
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Ding XB, Wang XX, Xia DH, Liu H, Tian HY, Fu Y, Chen YK, Qin C, Wang JQ, Xiang Z, Zhang ZX, Cao QC, Wang W, Li JY, Wu E, Tang BS, Ma MM, Teng JF, Wang XJ. Impaired meningeal lymphatic drainage in patients with idiopathic Parkinson's disease. Nat Med 2021; 27:411-418. [PMID: 33462448 DOI: 10.1038/s41591-020-01198-1] [Citation(s) in RCA: 168] [Impact Index Per Article: 56.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Accepted: 12/01/2020] [Indexed: 01/29/2023]
Abstract
Animal studies implicate meningeal lymphatic dysfunction in the pathogenesis of neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease (PD). However, there is no direct evidence in humans to support this role1-5. In this study, we used dynamic contrast-enhanced magnetic resonance imaging to assess meningeal lymphatic flow in cognitively normal controls and patients with idiopathic PD (iPD) or atypical Parkinsonian (AP) disorders. We found that patients with iPD exhibited significantly reduced flow through the meningeal lymphatic vessels (mLVs) along the superior sagittal sinus and sigmoid sinus, as well as a notable delay in deep cervical lymph node perfusion, compared to patients with AP. There was no significant difference in the size (cross-sectional area) of mLVs in patients with iPD or AP versus controls. In mice injected with α-synuclein (α-syn) preformed fibrils, we showed that the emergence of α-syn pathology was followed by delayed meningeal lymphatic drainage, loss of tight junctions among meningeal lymphatic endothelial cells and increased inflammation of the meninges. Finally, blocking flow through the mLVs in mice treated with α-syn preformed fibrils increased α-syn pathology and exacerbated motor and memory deficits. These results suggest that meningeal lymphatic drainage dysfunction aggravates α-syn pathology and contributes to the progression of PD.
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Affiliation(s)
- Xue-Bing Ding
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Institute of Parkinson and Movement Disorder, Zhengzhou University, Zhengzhou, China
| | - Xin-Xin Wang
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Institute of Parkinson and Movement Disorder, Zhengzhou University, Zhengzhou, China
| | - Dan-Hao Xia
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Institute of Parkinson and Movement Disorder, Zhengzhou University, Zhengzhou, China
| | - Han Liu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Institute of Parkinson and Movement Disorder, Zhengzhou University, Zhengzhou, China
| | - Hai-Yan Tian
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Institute of Parkinson and Movement Disorder, Zhengzhou University, Zhengzhou, China
| | - Yu Fu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Institute of Parkinson and Movement Disorder, Zhengzhou University, Zhengzhou, China
| | - Yong-Kang Chen
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Institute of Parkinson and Movement Disorder, Zhengzhou University, Zhengzhou, China
| | - Chi Qin
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Institute of Parkinson and Movement Disorder, Zhengzhou University, Zhengzhou, China
| | - Jiu-Qi Wang
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Institute of Parkinson and Movement Disorder, Zhengzhou University, Zhengzhou, China
| | - Zhi Xiang
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Institute of Parkinson and Movement Disorder, Zhengzhou University, Zhengzhou, China
| | - Zhong-Xian Zhang
- National Centre for International Research in Cell and Gene Therapy, Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Qin-Chen Cao
- Department of Radiation Therapy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Wei Wang
- Henan Medical Association, Zhengzhou, China
| | - Jia-Yi Li
- Neural Plasticity and Repair Unit, Wallenberg Neuroscience Center, Department of Experimental Medical Science, Lund University, Lund, Sweden.,Institute of Health Sciences, China Medical University, Shenyang, China
| | - Erxi Wu
- Neuroscience Institute and Department of Neurosurgery, Baylor Scott & White Health, Temple, TX, USA.,Texas A & M University Colleges of Medicine and Pharmacy, College Station, TX, USA.,Livestrong Cancer Institutes and Department of Oncology, Dell Medical School, the University of Texas at Austin, Austin, TX, USA
| | - Bei-Sha Tang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Ming-Ming Ma
- Department of Neurology, Affiliated People's Hospital of Zhengzhou University, Henan Provincial People's Hospital, Zhengzhou, China.
| | - Jun-Fang Teng
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China. .,Institute of Parkinson and Movement Disorder, Zhengzhou University, Zhengzhou, China.
| | - Xue-Jing Wang
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China. .,Institute of Parkinson and Movement Disorder, Zhengzhou University, Zhengzhou, China.
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Michael Gach H, Curcuru AN, Wittland EJ, Maraghechi B, Cai B, Mutic S, Green OL. MRI quality control for low-field MR-IGRT systems: Lessons learned. J Appl Clin Med Phys 2019; 20:53-66. [PMID: 31541542 PMCID: PMC6806483 DOI: 10.1002/acm2.12713] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Revised: 06/27/2019] [Accepted: 08/12/2019] [Indexed: 11/25/2022] Open
Abstract
Purpose To present lessons learned from magnetic resonance imaging (MRI) quality control (QC) tests for low‐field MRI‐guided radiation therapy (MR‐IGRT) systems. Methods MRI QC programs were established for low‐field MRI‐60Co and MRI‐Linac systems. A retrospective analysis of MRI subsystem performance covered system commissioning, operations, maintenance, and quality control. Performance issues were classified into three groups: (a) Image noise and artifact; (b) Magnetic field homogeneity and linearity; and (c) System reliability and stability. Results Image noise and artifacts were attributed to room noise sources, unsatisfactory system cabling, and broken RF receiver coils. Gantry angle‐dependent magnetic field inhomogeneities were more prominent on the MRI‐Linac due to the high volume of steel shielding in the gantry. B0 inhomogeneities measured in a 24‐cm spherical phantom were <5 ppm for both MR‐IGRT systems after using MRI gradient offset (MRI‐GO) compensation on the MRI‐Linac. However, significant signal dephasing occurred on the MRI‐Linac while the gantry was rotating. Spatial integrity measurements were sensitive to gradient calibration and vulnerable to shimming. The most common causes of MR‐IGRT system interruptions were software disconnects between the MRI and radiation therapy delivery subsystems caused by patient table, gantry, and multi‐leaf collimator (MLC) faults. The standard deviation (SD) of the receiver coil signal‐to‐noise ratio was 1.83 for the MRI‐60Co and 1.53 for the MRI‐Linac. The SD of the deviation from the mean for the Larmor frequency was 1.41 ppm for the MRI‐60Co and 1.54 ppm for the MRI‐Linac. The SD of the deviation from the mean for the transmitter reference amplitude was 0.90% for the MRI‐60Co and 1.68% for the MRI‐Linac. High SDs in image stability data corresponded to reports of spike noise. Conclusions There are significant technological challenges associated with implementing and maintaining MR‐IGRT systems. Most of the performance issues were identified and resolved during commissioning.
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Affiliation(s)
- H Michael Gach
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, Missouri, 63110, USA.,Department of Radiology, Washington University in St. Louis, St. Louis, Missouri, 63110, USA.,Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri, 63110, USA
| | - Austen N Curcuru
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri, 63110, USA
| | - Erin J Wittland
- Department of Radiation Oncology, Barnes Jewish Hospital, St. Louis, Missouri, 63110, USA
| | - Borna Maraghechi
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, Missouri, 63110, USA
| | - Bin Cai
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, Missouri, 63110, USA
| | - Sasa Mutic
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, Missouri, 63110, USA
| | - Olga L Green
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, Missouri, 63110, USA
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