TY - GEN
T1 - Brain Tortuosity as Biomarker to Classify Mild Cognitive Impairment and Control Subjects
AU - Morales, Eduardo Barbará
AU - Saavedra, Karla C.Rojas
AU - Ángeles, Luis Jiménez
AU - Bañuelos, Verónica Medina
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020/1/1
Y1 - 2020/1/1
N2 - Mild cognitive impairment (MCI) is an abnormal deterioration of cognitive functions, whose prevalence is considerable in adults older than 65 years old. Several of these cases will convert to Alzheimer’s disease and therefore, MCI’s simple, proper and opportune diagnosis continues to be a research field with great impact in public health. In this paper we propose tortuosity, which is defined as a shape measure that has been applied to quantify morphological changes in several anatomical structures, as a potential biomarker sensitive enough to depict early brain changes that appear in MCI subjects in comparison with healthy controls (HC). Also, a random forest (RF) classification strategy was implemented to discriminate between MCI and HC populations. A training population selected from the ADNI database and a test group of 21 mexican subjects were analyzed. Statistical analysis showed significant differences (p < 0.05) in tortuosity indices determined for MCI vs HC populations in most of the measured cortical structures. Classification rates increased by 6.7% during training and 4.77% during the test stage, when incorporating tortuosity to other image-based features set. This suggests that tortuosity is a promising morphological parameter to be considered for early stages of Alzheimer disease (AD) and that, combined with an RF classifier, it can adequately separate HC and MCI subjects.
AB - Mild cognitive impairment (MCI) is an abnormal deterioration of cognitive functions, whose prevalence is considerable in adults older than 65 years old. Several of these cases will convert to Alzheimer’s disease and therefore, MCI’s simple, proper and opportune diagnosis continues to be a research field with great impact in public health. In this paper we propose tortuosity, which is defined as a shape measure that has been applied to quantify morphological changes in several anatomical structures, as a potential biomarker sensitive enough to depict early brain changes that appear in MCI subjects in comparison with healthy controls (HC). Also, a random forest (RF) classification strategy was implemented to discriminate between MCI and HC populations. A training population selected from the ADNI database and a test group of 21 mexican subjects were analyzed. Statistical analysis showed significant differences (p < 0.05) in tortuosity indices determined for MCI vs HC populations in most of the measured cortical structures. Classification rates increased by 6.7% during training and 4.77% during the test stage, when incorporating tortuosity to other image-based features set. This suggests that tortuosity is a promising morphological parameter to be considered for early stages of Alzheimer disease (AD) and that, combined with an RF classifier, it can adequately separate HC and MCI subjects.
KW - Mild Cognitive Impairment
KW - Random forest
KW - Tortuosity biomarker
UR - http://www.scopus.com/inward/record.url?scp=85075671494&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-30648-9_43
DO - 10.1007/978-3-030-30648-9_43
M3 - Contribución a la conferencia
AN - SCOPUS:85075671494
SN - 9783030306472
T3 - IFMBE Proceedings
SP - 327
EP - 333
BT - 8th Latin American Conference on Biomedical Engineering and 42nd National Conference on Biomedical Engineering - Proceedings of CLAIB-CNIB 2019
A2 - González Díaz, César A.
A2 - Chapa González, Christian
A2 - Laciar Leber, Eric
A2 - Vélez, Hugo A.
A2 - Puente, Norma P.
A2 - Flores, Dora-Luz
A2 - Andrade, Adriano O.
A2 - Galván, Héctor A.
A2 - Martínez, Fabiola
A2 - García, Renato
A2 - Trujillo, Citlalli J.
A2 - Mejía, Aldo R.
PB - Springer
T2 - 8th Latin American Conference on Biomedical Engineering and the 42nd National Conference on Biomedical Engineering, CLAIB-CNIB 2019
Y2 - 2 October 2019 through 5 October 2019
ER -