| Home > Publications Database > CHARON: An Imaging-Based Diagnostic Algorithm to Navigate Through the Sea of Hereditary Degenerative Ataxias. > print |
| 001 | 272819 | ||
| 005 | 20250127091758.0 | ||
| 024 | 7 | _ | |a pmc:PMC11489197 |2 pmc |
| 024 | 7 | _ | |a 10.1007/s12311-024-01677-y |2 doi |
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| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Scaravilli, Alessandra |b 0 |
| 245 | _ | _ | |a CHARON: An Imaging-Based Diagnostic Algorithm to Navigate Through the Sea of Hereditary Degenerative Ataxias. |
| 260 | _ | _ | |a New York |c 2024 |b Springer US |
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| 520 | _ | _ | |a The complexity in diagnosing hereditary degenerative ataxias lies not only in their rarity, but also in the variety of different genetic conditions that can determine sometimes similar and overlapping clinical findings. In this light, Magnetic Resonance Imaging (MRI) plays a key role in the evaluation of these conditions, being a fundamental diagnostic tool needed not only to exclude other causes determining the observed clinical phenotype, but also to proper guide to an adequate genetic testing. Here, we propose an MRI-based diagnostic algorithm named CHARON (Characterization of Hereditary Ataxias Relying On Neuroimaging), to help in disentangling among the numerous, and apparently very similar, hereditary degenerative ataxias. Being conceived from a neuroradiological standpoint, it is based primarily on an accurate evaluation of the observed MRI findings, with the first and most important being the pattern of cerebellar atrophy. Along with the evaluation of the presence, or absence, of additional signal changes and/or supratentorial involvement, CHARON allows for the identification of a small groups of ataxias sharing similar imaging features. The integration of additional MRI findings, demographic, clinical and laboratory data allow then for the identification of typical, and in some cases pathognomonic, phenotypes of hereditary ataxias. |
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| 650 | _ | 7 | |a Algorithm |2 Other |
| 650 | _ | 7 | |a Ataxia |2 Other |
| 650 | _ | 7 | |a Magnetic Resonance Imaging |2 Other |
| 650 | _ | 7 | |a Neuroimaging |2 Other |
| 650 | _ | 2 | |a Humans |2 MeSH |
| 650 | _ | 2 | |a Algorithms |2 MeSH |
| 650 | _ | 2 | |a Magnetic Resonance Imaging: methods |2 MeSH |
| 650 | _ | 2 | |a Neuroimaging: methods |2 MeSH |
| 700 | 1 | _ | |a Tranfa, Mario |b 1 |
| 700 | 1 | _ | |a Pontillo, Giuseppe |b 2 |
| 700 | 1 | _ | |a Brais, Bernard |b 3 |
| 700 | 1 | _ | |a De Michele, Giovanna |b 4 |
| 700 | 1 | _ | |a La Piana, Roberta |b 5 |
| 700 | 1 | _ | |a Saccà, Francesco |b 6 |
| 700 | 1 | _ | |a Santorelli, Filippo Maria |b 7 |
| 700 | 1 | _ | |a Synofzik, Matthis |0 P:(DE-2719)2811275 |b 8 |u dzne |
| 700 | 1 | _ | |a Brunetti, Arturo |b 9 |
| 700 | 1 | _ | |a Cocozza, Sirio |b 10 |
| 773 | _ | _ | |a 10.1007/s12311-024-01677-y |g Vol. 23, no. 5, p. 2122 - 2129 |0 PERI:(DE-600)2071266-2 |n 5 |p 2122 - 2129 |t The cerebellum |v 23 |y 2024 |x 1473-4222 |
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