title: DTI measurements for Alzheimer's classification.
abstract: Diffusion tensor imaging (DTI) is a promising imaging technique that provides insight into white matter microstructure integrity and it has greatly helped identifying white matter regions affected by Alzheimer's disease (AD) in its early stages. DTI can therefore be a valuable source of information when designing machine-learning strategies to discriminate between healthy control (HC) subjects, AD patients and subjects with mild cognitive impairment (MCI). Nonetheless, several studies have reported so far conflicting results, especially because of the adoption of biased feature selection strategies. In this paper we firstly analyzed DTI scans of 150 subjects from the Alzheimer's disease neuroimaging initiative (ADNI) database. We measured a significant effect of the feature selection bias on the classification performance (p-value  <  0.01), leading to overoptimistic results (10% up to 30% relative increase in AUC). We observed that this effect is manifest regardless of the choice of diffusion index, specifically fractional anisotropy and mean diffusivity. Secondly, we performed a test on an independent mixed cohort consisting of 119 ADNI scans; thus, we evaluated the informative content provided by DTI measurements for AD classification. Classification performances and biological insight, concerning brain regions related to the disease, provided by cross-validation analysis were both confirmed on the independent test.
authors.affiliation: Dipartimento Interateneo di Fisica 'M. Merlin', Università degli Studi di Bari 'A. Moro', Via Giovanni Amendola, 173, 70125 Bari, Italy. Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Via Orabona, 4, 70123, Bari, Italy.
authors.forename: Tommaso
authors.initials: T
authors.lastname: Maggipinto
authors.forename: Roberto
authors.initials: R
authors.lastname: Bellotti
authors.forename: Nicola
authors.initials: N
authors.lastname: Amoroso
authors.forename: Domenico
authors.initials: D
authors.lastname: Diacono
authors.forename: Giacinto
authors.initials: G
authors.lastname: Donvito
authors.forename: Eufemia
authors.initials: E
authors.lastname: Lella
authors.forename: Alfonso
authors.initials: A
authors.lastname: Monaco
authors.forename: Marzia
authors.initials: M
authors.lastname: Antonella Scelsi
authors.forename: Sabina
authors.initials: S
authors.lastname: Tangaro
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000145:classification / Q000000981:diagnostic imaging*; D016880:Anisotropy; D001921:Brain / Q000000981:diagnostic imaging; D060825:Cognitive Dysfunction / Q000000981:diagnostic imaging; D003937:Diagnosis, Differential; D056324:Diffusion Tensor Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D066127:White Matter / Q000000981:diagnostic imaging