1
|
Beck ES, Mullins WA, dos Santos Silva J, Filippini S, Parvathaneni P, Maranzano J, Morrison M, Suto DJ, Donnay C, Dieckhaus H, Luciano NJ, Sharma K, Gaitán MI, Liu J, de Zwart JA, van Gelderen P, Cortese I, Narayanan S, Duyn JH, Nair G, Sati P, Reich DS. Contribution of new and chronic cortical lesions to disability accrual in multiple sclerosis. Brain Commun 2024; 6:fcae158. [PMID: 38818331 PMCID: PMC11137753 DOI: 10.1093/braincomms/fcae158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 02/22/2024] [Accepted: 04/30/2024] [Indexed: 06/01/2024] Open
Abstract
Cortical lesions are common in multiple sclerosis and are associated with disability and progressive disease. We asked whether cortical lesions continue to form in people with stable white matter lesions and whether the association of cortical lesions with worsening disability relates to pre-existing or new cortical lesions. Fifty adults with multiple sclerosis and no new white matter lesions in the year prior to enrolment (33 relapsing-remitting and 17 progressive) and a comparison group of nine adults who had formed at least one new white matter lesion in the year prior to enrolment (active relapsing-remitting) were evaluated annually with 7 tesla (T) brain MRI and 3T brain and spine MRI for 2 years, with clinical assessments for 3 years. Cortical lesions and paramagnetic rim lesions were identified on 7T images. Seven total cortical lesions formed in 3/30 individuals in the stable relapsing-remitting group (median 0, range 0-5), four total cortical lesions formed in 4/17 individuals in the progressive group (median 0, range 0-1), and 16 cortical lesions formed in 5/9 individuals in the active relapsing-remitting group (median 1, range 0-10, stable relapsing-remitting versus progressive versus active relapsing-remitting P = 0.006). New cortical lesions were not associated with greater change in any individual disability measure or in a composite measure of disability worsening (worsening Expanded Disability Status Scale or 9-hole peg test or 25-foot timed walk). Individuals with at least three paramagnetic rim lesions had a greater increase in cortical lesion volume over time (median 16 µl, range -61 to 215 versus median 1 µl, range -24 to 184, P = 0.007), but change in lesion volume was not associated with disability change. Baseline cortical lesion volume was higher in people with worsening disability (median 1010 µl, range 13-9888 versus median 267 µl, range 0-3539, P = 0.001, adjusted for age and sex) and in individuals with relapsing-remitting multiple sclerosis who subsequently transitioned to secondary progressive multiple sclerosis (median 2183 µl, range 270-9888 versus median 321 µl, range 0-6392 in those who remained relapsing-remitting, P = 0.01, adjusted for age and sex). Baseline white matter lesion volume was not associated with worsening disability or transition from relapsing-remitting to secondary progressive multiple sclerosis. Cortical lesion formation is rare in people with stable white matter lesions, even in those with worsening disability. Cortical but not white matter lesion burden predicts disability worsening, suggesting that disability progression is related to long-term effects of cortical lesions that form early in the disease, rather than to ongoing cortical lesion formation.
Collapse
Affiliation(s)
- Erin S Beck
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - W Andrew Mullins
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | | | - Stefano Filippini
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
- Department of Neurosciences, Drug, and Child Health, University of Florence, Florence 50121, Italy
| | - Prasanna Parvathaneni
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Josefina Maranzano
- McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A2B4, Canada
- Department of Anatomy, University of Quebec, Trois-Rivieres, QC G9A5H7, Canada
| | - Mark Morrison
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Daniel J Suto
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Corinne Donnay
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Henry Dieckhaus
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Nicholas J Luciano
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Kanika Sharma
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - María Ines Gaitán
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Jiaen Liu
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
- Advanced Imaging Research Center and Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Jacco A de Zwart
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Peter van Gelderen
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Irene Cortese
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Sridar Narayanan
- McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A2B4, Canada
| | - Jeff H Duyn
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Govind Nair
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Pascal Sati
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Daniel S Reich
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| |
Collapse
|
2
|
Okar SV, Dieckhaus H, Beck ES, Gaitán MI, Norato G, Pham DL, Absinta M, Cortese IC, Fletcher A, Jacobson S, Nair G, Reich DS. Highly Sensitive 3-Tesla Real Inversion Recovery MRI Detects Leptomeningeal Contrast Enhancement in Chronic Active Multiple Sclerosis. Invest Radiol 2024; 59:243-251. [PMID: 37493285 PMCID: PMC10818009 DOI: 10.1097/rli.0000000000001011] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/27/2023]
Abstract
BACKGROUND Leptomeningeal contrast enhancement (LME) on T2-weighted Fluid-Attenuated Inversion Recovery (T2-FLAIR) MRI is a reported marker of leptomeningeal inflammation, which is known to be associated with progression of multiple sclerosis (MS). However, this MRI approach, as typically implemented on clinical 3-tesla (T) systems, detects only a few enhancing foci in ~25% of patients and has thus been criticized as poorly sensitive. PURPOSE To compare an optimized 3D real-reconstruction inversion recovery (Real-IR) MRI sequence on a clinical 3 T scanner to T2-FLAIR for prevalence, characteristics, and clinical/radiological correlations of LME. MATERIALS AND METHODS We obtained 3D T2-FLAIR and Real-IR scans before and after administration of standard-dose gadobutrol in 177 scans of 154 participants (98 women, 64%; mean ± SD age: 49 ± 12 years), including 124 with an MS-spectrum diagnosis, 21 with other neurological and/or inflammatory disorders, and 9 without neurological history. We calculated contrast-to-noise ratios (CNR) in 20 representative LME foci and determined association of LME with cortical lesions identified at 7 T (n = 19), paramagnetic rim lesions (PRL) at 3 T (n = 105), and clinical/demographic data. RESULTS We observed focal LME in 73% of participants on Real-IR (70% in established MS, 33% in healthy volunteers, P < 0.0001), compared to 33% on T2-FLAIR (34% vs. 11%, P = 0.0002). Real-IR showed 3.7-fold more LME foci than T2-FLAIR ( P = 0.001), including all T2-FLAIR foci. LME CNR was 2.5-fold higher by Real-IR ( P < 0.0001). The major determinant of LME status was age. Although LME was not associated with cortical lesions, the number of PRL was associated with the number of LME foci on both T2-FLAIR ( P = 0.003) and Real-IR ( P = 0.0003) after adjusting for age, sex, and white matter lesion volume. CONCLUSIONS Real-IR a promising tool to detect, characterize, and understand the significance of LME in MS. The association between PRL and LME highlights a possible role of the leptomeninges in sustaining chronic inflammation.
Collapse
Affiliation(s)
- Serhat Vahip Okar
- From the Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institute of Health, Bethesda, MD, USA (S.V.O., E.S.B., M.I.G., M.A., D.S.R.); qMRI Core facility, National Institute of Neurological Disorders and Stroke, National Institute of Health, Bethesda, MD, USA (H.D., G.N.); Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA (E.S.B.); Office of Biostatistics, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA (G.N.); Department of Radiology and Radiological Sciences, Uniformed Services University of the Health Sciences, Bethesda, MD, USA (D.L.P.); Division of Neuroscience, Vita-Salute San Raffaele University and Hospital, Milan, Italy (M.A.); Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA (M.A.); Experimental Immunotherapeutics Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA (I.C.M.C.); Neuroimmunology Clinic, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA (A.F.); and Viral Immunology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD20814, USA (S.J.)
| | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
3
|
Beck ES, Mullins WA, Dos Santos Silva J, Filippini S, Parvathaneni P, Maranzano J, Morrison M, Suto DJ, Donnay C, Dieckhaus H, Luciano NJ, Sharma K, Gaitán MI, Liu J, de Zwart JA, van Gelderen P, Cortese I, Narayanan S, Duyn JH, Nair G, Sati P, Reich DS. Cortical lesions uniquely predict motor disability accrual and form rarely in the absence of new white matter lesions in multiple sclerosis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.22.23295974. [PMID: 37886541 PMCID: PMC10602044 DOI: 10.1101/2023.09.22.23295974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Background and objectives Cortical lesions (CL) are common in multiple sclerosis (MS) and associate with disability and progressive disease. We asked whether CL continue to form in people with stable white matter lesions (WML) and whether the association of CL with worsening disability relates to pre-existing or new CL. Methods A cohort of adults with MS were evaluated annually with 7 tesla (T) brain magnetic resonance imaging (MRI) and 3T brain and spine MRI for 2 years, and clinical assessments for 3 years. CL were identified on 7T images at each timepoint. WML and brain tissue segmentation were performed using 3T images at baseline and year 2. Results 59 adults with MS had ≥1 7T follow-up visit (mean follow-up time 2±0.5 years). 9 had "active" relapsing-remitting MS (RRMS), defined as new WML in the year prior to enrollment. Of the remaining 50, 33 had "stable" RRMS, 14 secondary progressive MS (SPMS), and 3 primary progressive MS. 16 total new CL formed in the active RRMS group (median 1, range 0-10), 7 in the stable RRMS group (median 0, range 0-5), and 4 in the progressive MS group (median 0, range 0-1) (p=0.006, stable RR vs PMS p=0.88). New CL were not associated with greater change in any individual disability measure or in a composite measure of disability worsening (worsening Expanded Disability Status Scale or 9-hole peg test or 25-foot timed walk). Baseline CL volume was higher in people with worsening disability (median 1010μl, range 13-9888 vs median 267μl, range 0-3539, p=0.001, adjusted for age and sex) and in individuals with RRMS who subsequently transitioned to SPMS (median 2183μl, range 270-9888 vs median 321μl, range 0-6392 in those who remained RRMS, p=0.01, adjusted for age and sex). Baseline WML volume was not associated with worsening disability or transition from RRMS to SPMS. Discussion CL formation is rare in people with stable WML, even in those with worsening disability. CL but not WML burden predicts future worsening of disability, suggesting that the relationship between CL and disability progression is related to long-term effects of lesions that form in the earlier stages of disease, rather than to ongoing lesion formation.
Collapse
Affiliation(s)
- Erin S Beck
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - W Andrew Mullins
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | | | - Stefano Filippini
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
- Department of Neurosciences, Drug, and Child Health, University of Florence, Florence, Italy
| | - Prasanna Parvathaneni
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Josefina Maranzano
- McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
- Department of Anatomy, University of Quebec, Trois-Rivieres, QC, Canada
| | - Mark Morrison
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Daniel J Suto
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Corinne Donnay
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Henry Dieckhaus
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Nicholas J Luciano
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Kanika Sharma
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - María Ines Gaitán
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Jiaen Liu
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
- Advanced Imaging Research Center and Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Jacco A de Zwart
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Peter van Gelderen
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Irene Cortese
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Sridar Narayanan
- McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Jeff H Duyn
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Govind Nair
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Pascal Sati
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Daniel S Reich
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| |
Collapse
|
4
|
Wallace TE, Kober T, Stockmann JP, Polimeni JR, Warfield SK, Afacan O. Real-time shimming with FID navigators. Magn Reson Med 2022; 88:2548-2563. [PMID: 36093989 PMCID: PMC9529812 DOI: 10.1002/mrm.29421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 07/22/2022] [Accepted: 08/02/2022] [Indexed: 11/12/2022]
Abstract
PURPOSE To implement a method for real-time field control using rapid FID navigator (FIDnav) measurements and evaluate the efficacy of the proposed approach for mitigating dynamic field perturbations and improvingT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -weighted image quality. METHODS FIDnavs were embedded in a gradient echo sequence and a subject-specific linear calibration model was generated on the scanner to facilitate rapid shim updates in response to measured FIDnav signals. To confirm the accuracy of FID-navigated field updates, phantom and volunteer scans were performed with online updates of the scanner B0 shim settings. To evaluate improvement inT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -weighted image quality with real-time shimming, 10 volunteers were scanned at 3T while performing deep-breathing and nose-touching tasks designed to modulate the B0 field. Quantitative image quality metrics were compared with and without FID-navigated field control. An additional volunteer was scanned at 7T to evaluate performance at ultra-high field. RESULTS Applying measured FIDnav shim updates successfully compensated for applied global and linear field offsets in phantoms and across all volunteers. FID-navigated real-time shimming led to a substantial reduction in field fluctuations and a consequent improvement inT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -weighted image quality in volunteers performing deep-breathing and nose-touching tasks, with 7.57% ± 6.01% and 8.21% ± 10.90% improvement in peak SNR and structural similarity, respectively. CONCLUSION FIDnavs facilitate rapid measurement and application of field coefficients for slice-wise B0 shimming. The proposed approach can successfully counteract spatiotemporal field perturbations and substantially improvesT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -weighted image quality, which is important for a variety of clinical and research applications, particularly at ultra-high field.
Collapse
Affiliation(s)
- Tess E Wallace
- Computational Radiology Laboratory, Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Jason P Stockmann
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
| | - Jonathan R Polimeni
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
| | - Simon K Warfield
- Computational Radiology Laboratory, Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
| | - Onur Afacan
- Computational Radiology Laboratory, Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
| |
Collapse
|