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Newburn G, Condron P, Kwon EE, McGeown JP, Melzer TR, Bydder M, Griffin M, Scadeng M, Potter L, Holdsworth SJ, Cornfeld DM, Bydder GM. Diagnosis of Delayed Post-Hypoxic Leukoencephalopathy (Grinker's Myelinopathy) with MRI Using Divided Subtracted Inversion Recovery (dSIR) Sequences: Time for Reappraisal of the Syndrome? Diagnostics (Basel) 2024; 14:418. [PMID: 38396456 PMCID: PMC10888335 DOI: 10.3390/diagnostics14040418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Revised: 01/25/2024] [Accepted: 02/10/2024] [Indexed: 02/25/2024] Open
Abstract
Background: Delayed Post-Hypoxic Leukoencephalopathy (DPHL), or Grinker's myelinopathy, is a syndrome in which extensive changes are seen in the white matter of the cerebral hemispheres with MRI weeks or months after a hypoxic episode. T2-weighted spin echo (T2-wSE) and/or T2-Fluid Attenuated Inversion Recovery (T2-FLAIR) images classically show diffuse hyperintensities in white matter which are thought to be near pathognomonic of the condition. The clinical features include Parkinsonism and akinetic mutism. DPHL is generally regarded as a rare condition. Methods and Results: Two cases of DPHL imaged with MRI nine months and two years after probable hypoxic episodes are described. No abnormalities were seen on the T2-FLAIR images with MRI, but very extensive changes were seen in the white matter of the cerebral and cerebellar hemisphere on divided Subtraction Inversion Recovery (dSIR) images. dSIR sequences may produce ten times the contrast of conventional inversion recovery (IR) sequences from small changes in T1. The clinical findings in both cases were of cognitive impairment without Parkinsonism or akinetic mutism. Conclusion: The classic features of DPHL may only represent the severe end of a spectrum of diseases in white matter following global hypoxic injury to the brain. The condition may be much more common than is generally thought but may not be recognized using conventional clinical and MRI criteria for diagnosis. Reappraisal of the syndrome of DPHL to include clinically less severe cases and to encompass recent advances in MRI is advocated.
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Affiliation(s)
- Gil Newburn
- Mātai Medical Research Institute, Tairāwhiti Gisborne 4010, New Zealand; (G.N.); (M.S.); (S.J.H.)
| | - Paul Condron
- Mātai Medical Research Institute, Tairāwhiti Gisborne 4010, New Zealand; (G.N.); (M.S.); (S.J.H.)
- Department of Anatomy and Medical Imaging, Faculty of Medical and Health Sciences & Centre for Brain Research, University of Auckland, Auckland 1010, New Zealand
| | - Eryn E. Kwon
- Mātai Medical Research Institute, Tairāwhiti Gisborne 4010, New Zealand; (G.N.); (M.S.); (S.J.H.)
- Department of Anatomy and Medical Imaging, Faculty of Medical and Health Sciences & Centre for Brain Research, University of Auckland, Auckland 1010, New Zealand
| | - Joshua P. McGeown
- Mātai Medical Research Institute, Tairāwhiti Gisborne 4010, New Zealand; (G.N.); (M.S.); (S.J.H.)
| | - Tracy R. Melzer
- Department of Medicine, University of Otago, Christchurch 8011, New Zealand
- New Zealand Brain Research Institute, Christchurch 8011, New Zealand
| | - Mark Bydder
- Mātai Medical Research Institute, Tairāwhiti Gisborne 4010, New Zealand; (G.N.); (M.S.); (S.J.H.)
| | - Mark Griffin
- Mātai Medical Research Institute, Tairāwhiti Gisborne 4010, New Zealand; (G.N.); (M.S.); (S.J.H.)
- Insight Research Services Associated, Gold Coast 4215, Australia
| | - Miriam Scadeng
- Mātai Medical Research Institute, Tairāwhiti Gisborne 4010, New Zealand; (G.N.); (M.S.); (S.J.H.)
- Department of Anatomy and Medical Imaging, Faculty of Medical and Health Sciences & Centre for Brain Research, University of Auckland, Auckland 1010, New Zealand
| | - Leigh Potter
- Mātai Medical Research Institute, Tairāwhiti Gisborne 4010, New Zealand; (G.N.); (M.S.); (S.J.H.)
| | - Samantha J. Holdsworth
- Mātai Medical Research Institute, Tairāwhiti Gisborne 4010, New Zealand; (G.N.); (M.S.); (S.J.H.)
- Department of Anatomy and Medical Imaging, Faculty of Medical and Health Sciences & Centre for Brain Research, University of Auckland, Auckland 1010, New Zealand
| | - Daniel M. Cornfeld
- Mātai Medical Research Institute, Tairāwhiti Gisborne 4010, New Zealand; (G.N.); (M.S.); (S.J.H.)
- Department of Anatomy and Medical Imaging, Faculty of Medical and Health Sciences & Centre for Brain Research, University of Auckland, Auckland 1010, New Zealand
| | - Graeme M. Bydder
- Mātai Medical Research Institute, Tairāwhiti Gisborne 4010, New Zealand; (G.N.); (M.S.); (S.J.H.)
- Department of Radiology, University of California San Diego, San Diego, CA 92093, USA
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Ma YJ, Moazamian D, Port JD, Edjlali M, Pruvo JP, Hacein-Bey L, Hoggard N, Paley MNJ, Menon DK, Bonekamp D, Pravatà E, Garwood M, Danesh-Meyer H, Condron P, Cornfeld DM, Holdsworth SJ, Du J, Bydder GM. Targeted magnetic resonance imaging (tMRI) of small changes in the T 1 and spatial properties of normal or near normal appearing white and gray matter in disease of the brain using divided subtracted inversion recovery (dSIR) and divided reverse subtracted inversion recovery (drSIR) sequences. Quant Imaging Med Surg 2023; 13:7304-7337. [PMID: 37869282 PMCID: PMC10585510 DOI: 10.21037/qims-23-232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Accepted: 07/11/2023] [Indexed: 10/24/2023]
Abstract
This review describes targeted magnetic resonance imaging (tMRI) of small changes in the T1 and the spatial properties of normal or near normal appearing white or gray matter in disease of the brain. It employs divided subtracted inversion recovery (dSIR) and divided reverse subtracted inversion recovery (drSIR) sequences to increase the contrast produced by small changes in T1 by up to 15 times compared to conventional T1-weighted inversion recovery (IR) sequences such as magnetization prepared-rapid acquisition gradient echo (MP-RAGE). This increase in contrast can be used to reveal disease with only small changes in T1 in normal appearing white or gray matter that is not apparent on conventional MP-RAGE, T2-weighted spin echo (T2-wSE) and/or fluid attenuated inversion recovery (T2-FLAIR) images. The small changes in T1 or T2 in disease are insufficient to produce useful contrast with conventional sequences. To produce high contrast dSIR and drSIR sequences typically need to be targeted for the nulling TI of normal white or gray matter, as well as for the sign and size of the change in T1 in these tissues in disease. The dSIR sequence also shows high signal boundaries between white and gray matter. dSIR and drSIR are essentially T1 maps. There is a nearly linear relationship between signal and T1 in the middle domain (mD) of the two sequences which includes T1s between the nulling T1s of the two acquired IR sequences. The drSIR sequence is also very sensitive to reductions in T1 produced by Gadolinium based contrast agents (GBCAs), and when used with rigid body registration to align three-dimensional (3D) isotropic pre and post GBCA images may be of considerable value in showing subtle GBCA enhancement. In serial MRI studies performed at different times, the high signal boundaries generated by dSIR and drSIR sequences can be used with rigid body registration of 3D isotropic images to demonstrate contrast arising from small changes in T1 (without or with GBCA enhancement) as well as small changes in the spatial properties of normal tissues and lesions, such as their site, shape, size and surface. Applications of the sequences in cases of multiple sclerosis (MS) and methamphetamine dependency are illustrated. Using targeted narrow mD dSIR sequences, widespread abnormalities were seen in areas of normal appearing white matter shown with conventional T2-wSE and T2-FLAIR sequences. Understanding of the features of dSIR and drSIR images is facilitated by the use of their T1-bipolar filters; to explain their targeting, signal, contrast, boundaries, T1 mapping and GBCA enhancement. Targeted MRI (tMRI) using dSIR and drSIR sequences may substantially improve clinical MRI of the brain by providing unequivocal demonstration of abnormalities that are not seen with conventional sequences.
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Affiliation(s)
- Ya-Jun Ma
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Dina Moazamian
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - John D. Port
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Myriam Edjlali
- Department of Radiology, APHP, Hôpitaux Raymond-Poincaré, Paris, France
- Laboratoire d’Imagerie Biomédicale Multimodale (BioMaps), Université Paris-Saclay, CEA, CNRS, Inserm, Service Hospitalier Frédéric Joliot, Orsay, France
| | - Jean-Pierre Pruvo
- Inserm, U1172-LilNCog-Lille Neuroscience & Cognition, Univ Lille, Lille, France
- UMS 2014-US 41-PLBS-Plateformes Lilloises en Biologie & Santé, Univ Lille, Lille, France
- Department of Neuroradiology, CHU Lille, Rue Emile Laine, Lille, France
| | - Lotfi Hacein-Bey
- Neuroradiology, Radiology Department, University of California Davis School of Medicine, Sacramento, CA, USA
| | - Nigel Hoggard
- Academic Unit of Radiology, Department of Infection, Immunity and Cardiovascular Disease, The Medical School, University of Sheffield, Sheffield, UK
| | - Martyn N. J. Paley
- Academic Unit of Radiology, Department of Infection, Immunity and Cardiovascular Disease, The Medical School, University of Sheffield, Sheffield, UK
| | - David K. Menon
- Division of Anaesthesia, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - David Bonekamp
- Division of Radiology (E010), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Emanuele Pravatà
- Department of Neuroradiology, Neurocenter of Southern Switzerland, Lugano, Switzerland
- Faculty of Biomedical Sciences, Universita della Svizzera Italiana, Lugano, Switzerland
| | - Michael Garwood
- Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota, Minneapolis, MN, USA
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Helen Danesh-Meyer
- Department of Ophthalmology, University of Auckland, Auckland, New Zealand
- Eye Institute, Auckland, New Zealand
- Mātai Medical Research Institute, Tairāwhiti Gisborne, New Zealand
- Department of Anatomy and Medical Imaging and Centre for Brain Research, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Paul Condron
- Mātai Medical Research Institute, Tairāwhiti Gisborne, New Zealand
- Department of Anatomy and Medical Imaging and Centre for Brain Research, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Daniel M. Cornfeld
- Mātai Medical Research Institute, Tairāwhiti Gisborne, New Zealand
- Department of Anatomy and Medical Imaging and Centre for Brain Research, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Samantha J. Holdsworth
- Mātai Medical Research Institute, Tairāwhiti Gisborne, New Zealand
- Department of Anatomy and Medical Imaging and Centre for Brain Research, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Jiang Du
- Department of Radiology, University of California San Diego, San Diego, CA, USA
- Research Service, Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
- Department of Bioengineering, University of California San Diego, San Diego, CA, USA
| | - Graeme M. Bydder
- Department of Radiology, University of California San Diego, San Diego, CA, USA
- Mātai Medical Research Institute, Tairāwhiti Gisborne, New Zealand
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Kumar H, Green R, Cornfeld DM, Condron P, Emsden T, Elsayed A, Zhao D, Gilbert K, Nash MP, Clark AR, Tawhai MH, Burrowes K, Murphy R, Tayebi M, McGeown J, Kwon E, Shim V, Wang A, Choisne J, Carman L, Besier T, Handsfield G, Babarenda Gamage TP, Shen J, Maso Talou G, Safaei S, Maller JJ, Taylor D, Potter L, Holdsworth SJ, Wilson GA. Roadmap for an imaging and modelling paediatric study in rural NZ. Front Physiol 2023; 14:1104838. [PMID: 36969588 PMCID: PMC10036853 DOI: 10.3389/fphys.2023.1104838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 01/30/2023] [Indexed: 03/12/2023] Open
Abstract
Our study methodology is motivated from three disparate needs: one, imaging studies have existed in silo and study organs but not across organ systems; two, there are gaps in our understanding of paediatric structure and function; three, lack of representative data in New Zealand. Our research aims to address these issues in part, through the combination of magnetic resonance imaging, advanced image processing algorithms and computational modelling. Our study demonstrated the need to take an organ-system approach and scan multiple organs on the same child. We have pilot tested an imaging protocol to be minimally disruptive to the children and demonstrated state-of-the-art image processing and personalized computational models using the imaging data. Our imaging protocol spans brain, lungs, heart, muscle, bones, abdominal and vascular systems. Our initial set of results demonstrated child-specific measurements on one dataset. This work is novel and interesting as we have run multiple computational physiology workflows to generate personalized computational models. Our proposed work is the first step towards achieving the integration of imaging and modelling improving our understanding of the human body in paediatric health and disease.
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Affiliation(s)
- Haribalan Kumar
- Mātai Medical Research Institute, Gisborne, New Zealand
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- GE Healthcare (Australia & New Zealand), Auckland, New Zealand
| | - Robby Green
- Mātai Medical Research Institute, Gisborne, New Zealand
| | - Daniel M. Cornfeld
- Mātai Medical Research Institute, Gisborne, New Zealand
- Faculty of Medical and Health Sciences, Centre for Brain Research, University of Auckland, Auckland, New Zealand
| | - Paul Condron
- Mātai Medical Research Institute, Gisborne, New Zealand
- Faculty of Medical and Health Sciences, Centre for Brain Research, University of Auckland, Auckland, New Zealand
| | - Taylor Emsden
- Mātai Medical Research Institute, Gisborne, New Zealand
- Faculty of Medical and Health Sciences, Centre for Brain Research, University of Auckland, Auckland, New Zealand
| | - Ayah Elsayed
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- Auckland University of Technology, Auckland, New Zealand
| | - Debbie Zhao
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Kat Gilbert
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Martyn P. Nash
- Mātai Medical Research Institute, Gisborne, New Zealand
- Department of Engineering Science, University of Auckland, Auckland, New Zealand
| | - Alys R. Clark
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Merryn H. Tawhai
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Kelly Burrowes
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Rinki Murphy
- Faculty of Medical and Health Sciences, Centre for Brain Research, University of Auckland, Auckland, New Zealand
| | - Maryam Tayebi
- Mātai Medical Research Institute, Gisborne, New Zealand
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Josh McGeown
- Mātai Medical Research Institute, Gisborne, New Zealand
| | - Eryn Kwon
- Mātai Medical Research Institute, Gisborne, New Zealand
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- Faculty of Medical and Health Sciences, Centre for Brain Research, University of Auckland, Auckland, New Zealand
| | - Vickie Shim
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Alan Wang
- Mātai Medical Research Institute, Gisborne, New Zealand
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- Faculty of Medical and Health Sciences, Centre for Brain Research, University of Auckland, Auckland, New Zealand
| | - Julie Choisne
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Laura Carman
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Thor Besier
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Geoffrey Handsfield
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | | | - Jiantao Shen
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Gonzalo Maso Talou
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Soroush Safaei
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Jerome J. Maller
- GE Healthcare (Australia & New Zealand), Auckland, New Zealand
- Monash Alfred Psychiatry Research Centre, Melbourne, VIC, Australia
| | | | - Leigh Potter
- Mātai Medical Research Institute, Gisborne, New Zealand
| | - Samantha J. Holdsworth
- Mātai Medical Research Institute, Gisborne, New Zealand
- Faculty of Medical and Health Sciences, Centre for Brain Research, University of Auckland, Auckland, New Zealand
- *Correspondence: Samantha J. Holdsworth,
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Ma YJ, Moazamian D, Cornfeld DM, Condron P, Holdsworth SJ, Bydder M, Du J, Bydder GM. Improving the understanding and performance of clinical MRI using tissue property filters and the central contrast theorem, MASDIR pulse sequences and synergistic contrast MRI. Quant Imaging Med Surg 2022; 12:4658-4690. [PMID: 36060593 PMCID: PMC9403590 DOI: 10.21037/qims-22-394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 05/31/2022] [Indexed: 01/05/2023]
Abstract
This paper updates and extends three previous papers on tissue property filters (TP-filters), Multiplied, Added, Divided and/or Subtracted Inversion Recovery (MASTIR) pulse sequences and synergistic contrast MRI (scMRI). It does this by firstly adding the central contrast theorem (CCT) to TP-filters, secondly including division with MASTIR sequences to make them Multiplied, Added, Subtracted and/or Divided IR (MASDIR) sequences, and thirdly incorporating division into the image processing needed for scMR to increase synergistic T1 contrast. These updated concepts are then used to explain and improve contrast at tissue boundaries, as well as to develop imaging regimes to detect and monitor small changes to the brain over time and quantify T1. The CCT is in two parts: the first part states that contrast produced by each TP is the product of the change in TP multiplied by the TP sequence weighting which is the first partial derivative of the TP-filter. The second part states that the overall fractional contrast is the algebraic sum of the fractional contrasts produced by each of the TPs. Subtraction of two IR sequences alone about doubles contrast relative to a conventional single IR sequence. Division of this subtraction can amplify contrast 5-15 times compared with conventional IR sequences. Dividing sequences can be problematic in areas where the signal is zero but this is avoided by dividing the difference in signal of two magnitude reconstructed IR sequences by the sum of their signals. The basis for the production of high contrast, high spatial resolution boundaries at white-gray matter junctions, between cerebral cortex and cerebrospinal fluid (CSF) and at other sites with subtracted IR (SIR) and divided subtracted IR (dSIR) sequences is explained and examples are shown. A key concept is the tissue fraction f, which is the proportion of a tissue in a mixture of two tissues within a voxel. Contrast at boundaries is a function of the partial derivative of the TP-filter, the partial derivative of the relevant TP with respect to f, and the partial derivative of f with respect to distance, x. Location of tissue boundaries is important for segmentation and is helpful in determining if inversion times have been chosen correctly. In small change regimes, the high sensitivity to small changes in T1 provided by dSIR images, together with the high definition boundaries, afford mechanisms for detecting small changes due to contrast agents, disease, perfusion and other causes. 3D isotropic rigid body registration provides a technique for following these changes over time in serial studies. Images showing high lesion contrast, high definition tissue and fluid boundaries, and the detection of small changes are included. T1 maps can be created by linearly scaling dSIR images.
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Affiliation(s)
- Ya-Jun Ma
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Dina Moazamian
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Daniel M. Cornfeld
- Mātai Medical Research Institute, Tairāwhiti-Gisborne, New Zealand;,Department of Anatomy and Medical Imaging and Centre for Brain Research, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Paul Condron
- Mātai Medical Research Institute, Tairāwhiti-Gisborne, New Zealand;,Department of Anatomy and Medical Imaging and Centre for Brain Research, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Samantha J. Holdsworth
- Mātai Medical Research Institute, Tairāwhiti-Gisborne, New Zealand;,Department of Anatomy and Medical Imaging and Centre for Brain Research, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Mark Bydder
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Jiang Du
- Department of Radiology, University of California San Diego, San Diego, CA, USA;,Research Service, Veterans Affairs San Diego Healthcare System, San Diego, CA, USA;,Department of Bioengineering, University of California San Diego, San Diego, CA, USA
| | - Graeme M. Bydder
- Department of Radiology, University of California San Diego, San Diego, CA, USA;,Mātai Medical Research Institute, Tairāwhiti-Gisborne, New Zealand
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