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000285633 0247_ $$2doi$$a10.1148/radiol.251386
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000285633 037__ $$aDZNE-2026-00272
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000285633 1001_ $$aPontillo, Giuseppe$$b0
000285633 245__ $$aIdentification of Biological Subtypes of Friedreich Ataxia with Structural MRI-based Machine Learning.
000285633 260__ $$aOak Brook, Ill.$$bSoc.$$c2026
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000285633 520__ $$aBackground Friedreich ataxia (FRDA) is an inherited, progressive neurodegenerative disease. Interindividual heterogeneity in the rate and phenotypic profile of disease progression indicates a biologic variability in the pattern and spatial evolution of underlying changes, but the occurrence of possible FRDA subgroups, which could aid in clinical trial design and treatment, are still unknown. Purpose To obtain a structural MRI-based stratification of participants with FRDA using the Subtype and Stage Inference (SuStaIn) algorithm and determine whether these subgroups are biologically meaningful and clinically relevant. Materials and Methods This multicenter secondary analysis of prospectively acquired data included structural MRI and clinical-demographic data from participants from the ENIGMA-Ataxia working group. MRI biomarkers were analyzed using the SuStaIn algorithm to identify subgroups with distinct patterns and disease stages. The clinical and genetic relevance of these subgroups were assessed within a linear model framework. Results This study included 565 participants (mean age, 32 years ± 13.1 [SD]; 286 women; 275 participants with FRDA and 290 healthy controls). SuStaIn identified three subtypes: (a) a classical subtype (66.5% [183 of 275 participants]), characterized by an ascending gradient of damage from brainstem to cerebellar cortex to cerebrum; (b) an early cerebral subtype (25.8% [71 of 275 participants]) with cerebral atrophy preceding the involvement of cerebellar cortex; and (c) and an early cerebellar subtype (7.64% [21 of 275 participants]) showing cerebellar lobule atrophy before upper brainstem or cerebral involvement. More advanced disease stages (MRI-based SuStaIn stages) correlated with greater symptom duration (unstandardized coefficient B = 0.422, standard error = 0.065, P < .001) and severity (B = 1.404, standard error = 0.201, P < .001), and these relationships were moderated by subtype, with biologic stage progression in the early cerebral subtype mapping less strongly to clinical variables relative to the others (interaction term early cerebral subtype × stage: B = -0.925, standard error = 0.410, P = .02). Conclusion Using the SuStaIn algorithm, three distinct structural MRI-based subtypes of FRDA were identified, with different patterns of brain degeneration and associations with clinical severity. © RSNA, 2026 Supplemental material is available for this article.
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000285633 650_2 $$2MeSH$$aHumans
000285633 650_2 $$2MeSH$$aFriedreich Ataxia: diagnostic imaging
000285633 650_2 $$2MeSH$$aFriedreich Ataxia: classification
000285633 650_2 $$2MeSH$$aFriedreich Ataxia: pathology
000285633 650_2 $$2MeSH$$aMagnetic Resonance Imaging: methods
000285633 650_2 $$2MeSH$$aFemale
000285633 650_2 $$2MeSH$$aMale
000285633 650_2 $$2MeSH$$aAdult
000285633 650_2 $$2MeSH$$aMachine Learning
000285633 650_2 $$2MeSH$$aProspective Studies
000285633 650_2 $$2MeSH$$aBrain: diagnostic imaging
000285633 650_2 $$2MeSH$$aBrain: pathology
000285633 650_2 $$2MeSH$$aMiddle Aged
000285633 650_2 $$2MeSH$$aDisease Progression
000285633 650_2 $$2MeSH$$aYoung Adult
000285633 7001_ $$00009-0000-0934-0595$$aPenna, Simone$$b1
000285633 7001_ $$00000-0002-5508-1149$$aArrigoni, Filippo$$b2
000285633 7001_ $$0P:(DE-2719)9001506$$aBender, Benjamin$$b3
000285633 7001_ $$00000-0003-1657-7368$$aBoesch, Sylvia$$b4
000285633 7001_ $$00000-0001-7057-3494$$aBrunetti, Arturo$$b5
000285633 7001_ $$00000-0001-9336-9568$$aCendes, Fernando$$b6
000285633 7001_ $$00000-0003-0866-3477$$aChopra, Sidhant$$b7
000285633 7001_ $$00000-0001-8767-4582$$aCorben, Louise A$$b8
000285633 7001_ $$00000-0002-2427-1302$$aDeistung, Andreas$$b9
000285633 7001_ $$aDelatycki, Martin B$$b10
000285633 7001_ $$00000-0001-8778-7819$$aDiciotti, Stefano$$b11
000285633 7001_ $$00000-0002-6632-197X$$aDogan, Imis$$b12
000285633 7001_ $$00000-0002-3186-4026$$aEgan, Gary F$$b13
000285633 7001_ $$00000-0003-0898-2419$$aFrança, Marcondes C$$b14
000285633 7001_ $$00000-0003-0718-6760$$aGeorgiou-Karistianis, Nellie$$b15
000285633 7001_ $$aGöricke, Sophia L$$b16
000285633 7001_ $$00000-0002-8270-1956$$aHenry, Pierre-Gilles$$b17
000285633 7001_ $$00000-0003-1208-5577$$aHernandez-Castillo, Carlos R$$b18
000285633 7001_ $$aHutter, Diane$$b19
000285633 7001_ $$00000-0002-8444-2185$$aJoers, James M$$b20
000285633 7001_ $$00000-0003-4646-3185$$aLenglet, Christophe$$b21
000285633 7001_ $$0P:(DE-2719)9000938$$aLindig, Tobias$$b22
000285633 7001_ $$aLodi, Raffaele$$b23
000285633 7001_ $$aManners, David N$$b24
000285633 7001_ $$00000-0001-7160-0853$$aMartinez, Alberto R M$$b25
000285633 7001_ $$aMartinuzzi, Andrea$$b26
000285633 7001_ $$00000-0002-1791-3573$$aMarzi, Chiara$$b27
000285633 7001_ $$00000-0002-5537-2982$$aMascalchi, Mario$$b28
000285633 7001_ $$aNachbauer, Wolfgang$$b29
000285633 7001_ $$00000-0002-3459-2644$$aPane, Chiara$$b30
000285633 7001_ $$00000-0002-9480-379X$$aPeruzzo, Denis$$b31
000285633 7001_ $$00000-0002-0756-1199$$aPishardy, Pramod K$$b32
000285633 7001_ $$00000-0002-9730-9228$$aReetz, Kathrin$$b33
000285633 7001_ $$00000-0001-8453-0313$$aRezende, Thiago J R$$b34
000285633 7001_ $$aRomanzetti, Sandro$$b35
000285633 7001_ $$aSaccà, Francesco$$b36
000285633 7001_ $$0P:(DE-2719)2810795$$aSchoels, Ludger$$b37
000285633 7001_ $$00000-0002-8903-0593$$aSchulz, Jorg B$$b38
000285633 7001_ $$00000-0003-4259-8824$$aStefani, Ambra$$b39
000285633 7001_ $$0P:(DE-2719)2811275$$aSynofzik, Matthis$$b40
000285633 7001_ $$aThomopoulos, Sophia I$$b41
000285633 7001_ $$00000-0002-4720-8867$$aThompson, Paul M$$b42
000285633 7001_ $$00000-0003-1935-416X$$aTimmann, Dagmar$$b43
000285633 7001_ $$aTonon, Caterina$$b44
000285633 7001_ $$aVavla, Marinela$$b45
000285633 7001_ $$00000-0002-6843-9592$$aHarding, Ian H$$b46
000285633 7001_ $$00000-0002-0300-5160$$aCocozza, Sirio$$b47
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