Magnetic Resonance Spectroscopy (MRS) transforming multiple sclerosis (MS) diagnosis
Anna is one of the 1.8 million people worldwide with multiple sclerosis who live with the uncertainty of disease progression every day [1]. Traditional Magnetic Resonance Imaging scans every six months reveal brain lesions but can't predict how the disease will progress [2]. A new technology, M...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-03-01
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| Series: | Science Talks |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S277256932500009X |
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| author | Landoline Bonnin Pascal Bourdon Carole Guillevin Remy Guillevin Clement Giraud Christine Fernandez-Maloigne |
| author_facet | Landoline Bonnin Pascal Bourdon Carole Guillevin Remy Guillevin Clement Giraud Christine Fernandez-Maloigne |
| author_sort | Landoline Bonnin |
| collection | DOAJ |
| description | Anna is one of the 1.8 million people worldwide with multiple sclerosis who live with the uncertainty of disease progression every day [1]. Traditional Magnetic Resonance Imaging scans every six months reveal brain lesions but can't predict how the disease will progress [2]. A new technology, Magnetic Resonance Spectroscopy (MRS), shows promise in predicting disease progression by revealing cerebral metabolism and neurophysiological changes [3]. However, current MRS measurement methods vary between medical centers, affecting reliability [4–6]. Standardizing these measurements using Physics-Informed Neural Networks (PINNs), which are more reliable than traditional neural networks because they are based on the physics of spectra, could ensure accurate, comparable results worldwide [7–9]. This would reassure doctors and patients like Anna, and potentially improve their quality of life by enabling earlier and more precise treatment. |
| format | Article |
| id | doaj-art-7cddea884195449f951571da34869bea |
| institution | Kabale University |
| issn | 2772-5693 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Science Talks |
| spelling | doaj-art-7cddea884195449f951571da34869bea2025-02-08T05:01:41ZengElsevierScience Talks2772-56932025-03-0113100427Magnetic Resonance Spectroscopy (MRS) transforming multiple sclerosis (MS) diagnosisLandoline Bonnin0Pascal Bourdon1Carole Guillevin2Remy Guillevin3Clement Giraud4Christine Fernandez-Maloigne5Common laboratory I3M XLIM CNRS 7252, University of Poitiers, France; Corresponding author.Common laboratory I3M XLIM CNRS 7252, University of Poitiers, FranceCommon laboratory I3M LMA CNRS 7348, University Hospital Centre and University of Poitiers, FranceCommon laboratory I3M LMA CNRS 7348, University Hospital Centre and University of Poitiers, FranceCommon laboratory I3M LMA CNRS 7348, University Hospital Centre and University of Poitiers, FranceCommon laboratory I3M XLIM CNRS 7252, University of Poitiers, FranceAnna is one of the 1.8 million people worldwide with multiple sclerosis who live with the uncertainty of disease progression every day [1]. Traditional Magnetic Resonance Imaging scans every six months reveal brain lesions but can't predict how the disease will progress [2]. A new technology, Magnetic Resonance Spectroscopy (MRS), shows promise in predicting disease progression by revealing cerebral metabolism and neurophysiological changes [3]. However, current MRS measurement methods vary between medical centers, affecting reliability [4–6]. Standardizing these measurements using Physics-Informed Neural Networks (PINNs), which are more reliable than traditional neural networks because they are based on the physics of spectra, could ensure accurate, comparable results worldwide [7–9]. This would reassure doctors and patients like Anna, and potentially improve their quality of life by enabling earlier and more precise treatment.http://www.sciencedirect.com/science/article/pii/S277256932500009XPhysics Informed Neural NetworkPINNproton Magnetic Resonance Spectroscopy1H-MRSFitting |
| spellingShingle | Landoline Bonnin Pascal Bourdon Carole Guillevin Remy Guillevin Clement Giraud Christine Fernandez-Maloigne Magnetic Resonance Spectroscopy (MRS) transforming multiple sclerosis (MS) diagnosis Science Talks Physics Informed Neural Network PINN proton Magnetic Resonance Spectroscopy 1H-MRS Fitting |
| title | Magnetic Resonance Spectroscopy (MRS) transforming multiple sclerosis (MS) diagnosis |
| title_full | Magnetic Resonance Spectroscopy (MRS) transforming multiple sclerosis (MS) diagnosis |
| title_fullStr | Magnetic Resonance Spectroscopy (MRS) transforming multiple sclerosis (MS) diagnosis |
| title_full_unstemmed | Magnetic Resonance Spectroscopy (MRS) transforming multiple sclerosis (MS) diagnosis |
| title_short | Magnetic Resonance Spectroscopy (MRS) transforming multiple sclerosis (MS) diagnosis |
| title_sort | magnetic resonance spectroscopy mrs transforming multiple sclerosis ms diagnosis |
| topic | Physics Informed Neural Network PINN proton Magnetic Resonance Spectroscopy 1H-MRS Fitting |
| url | http://www.sciencedirect.com/science/article/pii/S277256932500009X |
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