Accurate Classification of Chronic Migraine via Brain Magnetic Resonance Imaging

被引:102
|
作者
Schwedt, Todd J. [1 ]
Chong, Catherine D. [1 ]
Wu, Teresa [2 ]
Gaw, Nathan [2 ]
Fu, Yinlin [2 ]
Li, Jing [2 ]
机构
[1] Mayo Clin, Dept Neurol, Phoenix, AZ 85054 USA
[2] Arizona State Univ, Sch Comp, Informat, Decis Syst Engn, Phoenix, AZ USA
来源
HEADACHE | 2015年 / 55卷 / 06期
基金
美国国家科学基金会;
关键词
migraine; cortical thickness; cortical surface area; diagnostic classifier; magnetic resonance imaging; STATE FUNCTIONAL CONNECTIVITY; RESTING-STATE; NETWORK CONNECTIVITY; PAIN; ABNORMALITIES; SEGMENTATION; RESPONSES; ATTACKS; MODELS; CORTEX;
D O I
10.1111/head.12584
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Background.-The International Classification of Headache Disorders provides criteria for the diagnosis and subclassification of migraine. Since there is no objective gold standard by which to test these diagnostic criteria, the criteria are based on the consensus opinion of content experts. Accurate migraine classifiers consisting of brain structural measures could serve as an objective gold standard by which to test and revise diagnostic criteria. The objectives of this study were to utilize magnetic resonance imaging measures of brain structure for constructing classifiers: (1) that accurately identify individuals as having chronic vs episodic migraine vs being a healthy control; and (2) that test the currently used threshold of 15 headache days/month for differentiating chronic migraine from episodic migraine. Methods.-Study participants underwent magnetic resonance imaging for determination of regional cortical thickness, cortical surface area, and volume. Principal components analysis combined structural measurements into principal components accounting for 85% of variability in brain structure. Models consisting of these principal components were developed to achieve the classification objectives. Tenfold cross validation assessed classification accuracy within each of the 10 runs, with data from 90% of participants randomly selected for classifier development and data from the remaining 10% of participants used to test classification performance. Headache frequency thresholds ranging from 5-15 headache days/month were evaluated to determine the threshold allowing for the most accurate subclassification of individuals into lower and higher frequency subgroups. Results.-Participants were 66 migraineurs and 54 healthy controls, 75.8% female, with an average age of 36 +/- 11 years. Average classifier accuracies were: (1) 68% for migraine (episodic + chronic) vs healthy controls; (2) 67.2% for episodic migraine vs healthy controls; (3) 86.3% for chronic migraine vs healthy controls; and (4) 84.2% for chronic migraine vs episodic migraine. The classifiers contained principal components consisting of several structural measures, commonly including the temporal pole, anterior cingulate cortex, superior temporal lobe, entorhinal cortex, medial orbital frontal gyrus, and pars triangularis. A threshold of 15 headache days/month allowed for the most accurate subclassification of migraineurs into lower frequency and higher frequency subgroups. Conclusions.-Classifiers consisting of cortical surface area, cortical thickness, and regional volumes were highly accurate for determining if individuals have chronic migraine. Furthermore, results provide objective support for the current use of 15 headache days/month as a threshold for dividing migraineurs into lower frequency (ie, episodic migraine) and higher frequency (ie, chronic migraine) subgroups.
引用
收藏
页码:762 / 777
页数:16
相关论文
共 50 条
  • [41] Magnetic resonance brain imaging in patients with visual vertigo
    Pollak, Lea
    Osherov, Michael
    Berkovitz, Nadav
    Beckerman, Inessa
    Stryjer, Rafael
    Tal, Sigal
    BRAIN AND BEHAVIOR, 2015, 5 (11):
  • [42] Improved Cerebellar Tissue Classification on Magnetic Resonance Images of Brain
    Datta, Sushmita
    Tao, Guozhi
    He, Renjie
    Wolinsky, Jerry S.
    Narayana, Ponnada A.
    JOURNAL OF MAGNETIC RESONANCE IMAGING, 2009, 29 (05) : 1035 - 1042
  • [43] Brain magnetic resonance imaging in tyrosinemia
    Sener, RN
    ACTA RADIOLOGICA, 2005, 46 (06) : 618 - 620
  • [44] Magnetic resonance imaging of the neonatal brain
    Prager, Ariel
    Roychowdhury, Sudipta
    INDIAN JOURNAL OF PEDIATRICS, 2007, 74 (02) : 173 - 184
  • [45] Evaluation of cortical thickness and brain volume on 3 Tesla magnetic resonance imaging in children with frontal lobe epilepsy
    Rahatli, Feride Kural
    Sezer, Taner
    Has, Arzu Ceylan
    Agildere, Ahmet Muhtesem
    NEUROLOGICAL SCIENCES, 2020, 41 (04) : 825 - 833
  • [46] MAGNETIC-RESONANCE-IMAGING OF THE BRAIN
    WALLACE, CJ
    JOURNAL OF THE CANADIAN ASSOCIATION OF RADIOLOGISTS-JOURNAL DE L ASSOCIATION CANADIENNE DES RADIOLOGISTES, 1991, 42 (01): : 13 - 20
  • [47] Magnetic field gradient imaging for material classification by magnetic resonance imaging
    Pei, Cuixiang
    Zhu, Haitao
    Demachi, Kazuyuki
    Sekino, Masaki
    Uesaka, Mitsuru
    INTERNATIONAL JOURNAL OF APPLIED ELECTROMAGNETICS AND MECHANICS, 2012, 39 (1-4) : 335 - 340
  • [48] Migraine-associated seizures with recurrent and reversible magnetic resonance imaging abnormalities
    Mateo, I
    Foncea, N
    Vicente, I
    Beldarrain, MG
    Garcia-Monco, JC
    HEADACHE, 2004, 44 (03): : 265 - 270
  • [49] Magnetic resonance imaging of the neonatal brain
    Ariel Prager
    Sudipta Roychowdhury
    The Indian Journal of Pediatrics, 2007, 74 : 173 - 184
  • [50] Magnetic resonance imaging of the fetal brain
    Rutherford, Mary A.
    CURRENT OPINION IN OBSTETRICS & GYNECOLOGY, 2009, 21 (02) : 180 - 186