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Clinical Article
Application of automated fiber quantification in research of facial emotion recognition in patients with Alzheimer's disease
JIABA Jianming  LUO Lin  YUAN Xiaojun  CHEN Qiang 

Cite this article as: JIABA J M, LUO L, YUAN X J, et al. Application of automated fiber quantification in research of facial emotion recognition in patients with Alzheimer's disease[J]. Chin J Magn Reson Imaging, 2023, 14(5): 66-71. DOI:10.12015/issn.1674-8034.2023.05.013.

[Abstract] Objective To explore the application of automated fiber quantification (AFQ) based on diffusion tensor imaging (DTI) in the neurological basic research of facial emotion recognition (FER) disorder in patients with Alzheimer's disease (AD).Materials and Methods FER test and 3.0T MR Scan were performed in 17 AD patients (AD group) and 2l normal control patients (NC group). Fibers like inferior fronto-occipital fasciculus (IFOF), uncinate fasciculus (UF) and inferior longitudinal fasciculus (ILF) were divided into 100 nodes using AFQ, and then extracted the fractional anisotropy (FA) and mean diffusivity (MD) values of main fibers. The differences in FA and MD values between the two groups of fibers mentioned above were compared using two-tailed t-tests. Age, gender and mini-mental state examination were regarded as covariates, partial correlation analysis was conducted between DTI parameters of damaged fibers and FER scores.Results AFQ analysis showed that the FA values of the middle part (nodes 44-46) of left IFOF and the inferior segment (nodes 89-99) of left UF in AD group were significantly lower than that in NC group (t values were -6.319 and -7.825, both P<0.05), and were positively correlated with the negative FER scores (r values were 0.386 and 0.384, both P<0.05). The MD value of the middle part (nodes 45-64) of left inferior ILF in AD group was significantly higher than that in NC group (t=3.059, P<0.05), and was negatively correlated with the negative FER scores (r=-0.485, P=0.003).Conclusions AFQ can be used to detect the damaged segment of white matter fiber accurately. The impaired of the middle segment of left ILF, left IFOF, and the inferior part of left UF may be the potential neural basis of negative FER disorder in AD patients.
[Keywords] Alzheimer's disease;facial emotion recognition;diffusion tensor imaging;automated fiber quantification;magnetic resonance imaging

JIABA Jianming1, 2   LUO Lin2   YUAN Xiaojun2   CHEN Qiang2*  

1 Baotou Medical College, Inner Mongolia University of Science & Technology, Baotou 014040, China

2 Department of Medical Imaging, the First Affiliated Hospital of Baotou Medical College, Inner Mongolia University of Science & Technology, Baotou 014010, China

Corresponding author: Chen Q, E-mail:

Conflicts of interest   None.

ACKNOWLEDGMENTS Scientific Research Project of Colleges and Universities in Inner Mongolia Autonomous Region (No. NJZY23021).
Received  2022-11-14
Accepted  2023-04-23
DOI: 10.12015/issn.1674-8034.2023.05.013
Cite this article as: JIABA J M, LUO L, YUAN X J, et al. Application of automated fiber quantification in research of facial emotion recognition in patients with Alzheimer's disease[J]. Chin J Magn Reson Imaging, 2023, 14(5): 66-71. DOI:10.12015/issn.1674-8034.2023.05.013.

SCHELTENS P, BLENNOW K, BRETELER M M, et al. Alzheimer's disease[J]. Lancet, 2016, 388(10043): 505-517. DOI: 10.1016/s0140-6736(15)01124-1">10.1016/s0140-6736(15)01124-1">10.1016/s0140-6736(15)01124-1.
ZHOU M G, WANG H D, ZENG X Y, et al. Mortality, morbidity, and risk factors in China and its provinces, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017[J]. Lancet, 2019, 394(10204): 1145-1158. DOI: 10.1016/S0140-6736(19)30427-1">10.1016/S0140-6736(19)30427-1">10.1016/S0140-6736(19)30427-1.
ZHANG Y Q, WANG C F, XU G, et al. Mortality of alzheimer's disease patients: a 10-year follow-up pilot study in Shanghai[J]. Can J Neurol Sci, 2020, 47(2): 226-230. DOI: 10.1017/cjn.2019.333">10.1017/cjn.2019.333">10.1017/cjn.2019.333.
SURCINELLI P, CODISPOTI M, MONTEBAROCCI O, et al. Facial emotion recognition in trait anxiety[J]. J Anxiety Disord, 2006, 20(1): 110-117. DOI: 10.1016/j.janxdis.2004.11.010">10.1016/j.janxdis.2004.11.010">10.1016/j.janxdis.2004.11.010.
TAKAHASHI M, KITAMURA S, MATSUOKA K, et al. Uncinate fasciculus disruption relates to poor recognition of negative facial emotions in Alzheimer's disease: a cross-sectional diffusion tensor imaging study[J]. Psychogeriatrics, 2020, 20(3): 296-303. DOI: 10.1111/psyg.12498">10.1111/psyg.12498">10.1111/psyg.12498.
CERESETTI R, ROUCH I, LAURENT B, et al. Processing of facial expressions of emotions and pain in alzheimer's disease[J]. J Alzheimers Dis, 2022, 89(1): 389-398. DOI: 10.3233/JAD-220236">10.3233/JAD-220236">10.3233/JAD-220236.
JIABA J M, JIANG M K, YUAN W H, et al. Research progresses of MRI in facial emotion recognition of patients with Alzheimer's disease[J]. Chin J Med Imaging Technol, 2022, 38(10)1582-1585. DOI: 10.13929/j.issn.1003-3289.2022.10.031">10.13929/j.issn.1003-3289.2022.10.031">10.13929/j.issn.1003-3289.2022.10.031
LOPE-PIEDRAFITA S. Diffusion tensor imaging (DTI)[J]. Methods Mol Biol, 2018, 1718: 103-116. DOI: 10.1007/978-1-4939-7531-0_7">10.1007/978-1-4939-7531-0_7">10.1007/978-1-4939-7531-0_7.
WANG H Y, WANG P, XIANG S T. Research progress of white matter microstructure analysis methods based on diffusion tensor imaging in visual pathway injury[J]. Chin J Magn Reson Imaging, 2022, 13(1): 147-150. DOI: 10.12015/issn.1674-8034.2022.01.034">10.12015/issn.1674-8034.2022.01.034">10.12015/issn.1674-8034.2022.01.034.
UNGER A, ALM K H, COLLINS J A, et al. Variation in white matter connectivity predicts the ability to remember faces and discriminate their emotions[J]. J Int Neuropsychol Soc, 2016, 22(2): 180-190. DOI: 10.1017/S1355617715001009">10.1017/S1355617715001009">10.1017/S1355617715001009.
BAGGIO H C, SEGURA B, IBARRETXE-BILBAO N, et al. Structural correlates of facial emotion recognition deficits in Parkinson's disease patients[J]. Neuropsychologia, 2012, 50(8): 2121-2128. DOI: 10.1016/j.neuropsychologia.2012.05.020">10.1016/j.neuropsychologia.2012.05.020">10.1016/j.neuropsychologia.2012.05.020.
HAGHSHOMAR M, DOLATSHAHI M, GHAZI SHERBAF F, et al. Disruption of inferior longitudinal Fasciculus microstructure in parkinson's disease: a systematic review of diffusion tensor imaging studies[J/OL]. Front Neurol, 2018, 9: 598 [2022-10-20]. DOI: 10.3389/fneur.2018.00598">10.3389/fneur.2018.00598">10.3389/fneur.2018.00598.
COAD B M, POSTANS M, HODGETTS C J, et al. Structural connections support emotional connections: Uncinate Fasciculus microstructure is related to the ability to decode facial emotion expressions[J/OL]. Neuropsychologia, 2020, 145: 106562 [2022-10-20]. DOI: 10.1016/j.neuropsychologia.2017.11.006">10.1016/j.neuropsychologia.2017.11.006">10.1016/j.neuropsychologia.2017.11.006.
YEATMAN J D, DOUGHERTY R F, MYALL N J, et al. Tract profiles of white matter properties: automating fiber-tract quantification[J/OL]. PLoS One, 2012, 7(11): e49790 [2022-10-20]. DOI: 10.1371/journal.pone.0049790.
KREILKAMP B A K, LISANTI L, GLENN G R, et al. Comparison of manual and automated fiber quantification tractography in patients with temporal lobe epilepsy[J/OL]. Neuroimage Clin, 2019, 24: 102024 [2022-10-20]. DOI: 10.1016/j.nicl.2019.102024">10.1016/j.nicl.2019.102024">10.1016/j.nicl.2019.102024.
MCKHANN G M, KNOPMAN D S, CHERTKOW H, et al. The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease[J]. Alzheimers Dement, 2011, 7(3): 263-269. DOI: 10.1016/j.jalz.2011.03.005">10.1016/j.jalz.2011.03.005">10.1016/j.jalz.2011.03.005.
HAGIYA K, SUMIYOSHI T, KANIE A, et al. Facial expression perception correlates with verbal working memory function in schizophrenia[J]. Psychiatry Clin Neurosci, 2015, 69(12): 773-781. DOI: 10.1111/pcn.12329">10.1111/pcn.12329">10.1111/pcn.12329.
TORRES MENDONÇA DE MELO FÁDEL B, SANTOS DE CARVALHO R L, BELFORT ALMEIDA DOS SANTOS T T, et al. Facial expression recognition in Alzheimer's disease: a systematic review[J]. J Clin Exp Neuropsychol, 2019, 41(2): 192-203. DOI: 10.1080/13803395.2018.1501001">10.1080/13803395.2018.1501001">10.1080/13803395.2018.1501001.
PARK S, KIM T, SHIN S A, et al. Behavioral and neuroimaging evidence for facial emotion recognition in elderly Korean adults with mild cognitive impairment, alzheimer's disease, and frontotemporal dementia[J/OL]. Front Aging Neurosci, 2017, 9: 389 [2022-10-20]. DOI: 10.3389/fnagi.2017.00389">10.3389/fnagi.2017.00389">10.3389/fnagi.2017.00389.
WIECHETEK OSTOS M, SCHENK F, BAENZIGER T, et al. An exploratory study on facial emotion recognition capacity in beginning Alzheimer's disease[J]. Eur Neurol, 2011, 65(6): 361-367. DOI: 10.1159/000327979">10.1159/000327979">10.1159/000327979.
COMON M, ROUCH I, EDJOLO A, et al. Impaired facial emotion recognition and gaze direction detection in mild alzheimer's disease: results from the PACO study[J]. J Alzheimers Dis, 2022, 89(4): 1427-1437. DOI: 10.3233/JAD-220401">10.3233/JAD-220401">10.3233/JAD-220401.
SINGLETON E H, FIELDHOUSE J L P, VAN 'T HOOFT J J, et al. Social cognition deficits and biometric signatures in the behavioural variant of Alzheimer's disease[J]. Brain, 2023, 146(5): 2163-2174. DOI: 10.1093/brain/awac382">10.1093/brain/awac382">10.1093/brain/awac382.
DE LA TORRE-LUQUE A, VIERA-CAMPOS A, BILDERBECK A C, et al. Relationships between social withdrawal and facial emotion recognition in neuropsychiatric disorders[J/OL]. Prog Neuropsychopharmacol Biol Psychiatry, 2022, 113: 110463 [2022-10-20]. DOI: 10.1016/j.pnpbp.2021.110463">10.1016/j.pnpbp.2021.110463">10.1016/j.pnpbp.2021.110463.
ROUX A, LEMAITRE A L, DEVERDUN J, et al. Combining electrostimulation with fiber tracking to stratify the inferior Fronto-occipital Fasciculus[J/OL]. Front Neurosci, 2021, 15: 683348 [2022-10-20]. DOI: 10.3389/fnins.2021.683348">10.3389/fnins.2021.683348">10.3389/fnins.2021.683348.
THOMAS C, MOY A, AVIDAN G, et al. Reduction in white matter connectivity, revealed by diffusion tensor imaging, may account for age-related changes in face perception[J]. J Cogn Neurosci, 2008, 20(2): 268-284. DOI: 10.1162/jocn.2008.20025">10.1162/jocn.2008.20025">10.1162/jocn.2008.20025.
ANDICA C, KAMAGATA K, HATANO T, et al. MR biomarkers of degenerative brain disorders derived from diffusion imaging[J]. J Magn Reson Imaging, 2020, 52(6): 1620-1636. DOI: 10.1002/jmri.27019">10.1002/jmri.27019">10.1002/jmri.27019.
ZEMMOURA I, BURKHARDT E, HERBET G. The inferior longitudinal fasciculus: anatomy, function and surgical considerations[J]. J Neurosurg Sci, 2021, 65(6): 590-604. DOI: 10.23736/S0390-5616.21.05391-1">10.23736/S0390-5616.21.05391-1">10.23736/S0390-5616.21.05391-1.
VON DER HEIDE R J, SKIPPER L M, KLOBUSICKY E, et al. Dissecting the uncinate fasciculus: disorders, controversies and a hypothesis[J]. Brain, 2013, 136(Pt 6): 1692-1707. DOI: 10.1093/brain/awt094">10.1093/brain/awt094">10.1093/brain/awt094.
MORITA T, SAITO D N, BAN M, et al. Self-face recognition shares brain regions active during proprioceptive illusion in the right inferior fronto-parietal superior longitudinal fasciculus III network[J]. Neuroscience, 2017, 348: 288-301. DOI: 10.1016/j.neuroscience.2017.02.031">10.1016/j.neuroscience.2017.02.031">10.1016/j.neuroscience.2017.02.031.
MARTINEZ M, MULTANI N, ANOR C J, et al. Emotion detection deficits and decreased empathy in patients with alzheimer's disease and parkinson's disease affect caregiver mood and burden[J/OL]. Front Aging Neurosci, 2018, 10: 120 [2022-10-18]. DOI: 10.3389/fnagi.2018.00120">10.3389/fnagi.2018.00120">10.3389/fnagi.2018.00120.
SPITZER N, SHAFIR T, LERMAN Y, et al. The relationship between caregiver burden and emotion recognition deficits in persons with MCI and early AD: the mediating role of caregivers' subjective evaluations[J]. Alzheimer Dis Assoc Disord, 2019, 33(3): 266-271. DOI: 10.1097/WAD.0000000000000323">10.1097/WAD.0000000000000323">10.1097/WAD.0000000000000323.
GARCÍA-CASAL J A, GOÑI-IMIZCOZ M, PEREA-BARTOLOMÉ M V, et al. The efficacy of emotion recognition rehabilitation for people with alzheimer's disease[J]. J Alzheimers Dis, 2017, 57(3): 937-951. DOI: 10.3233/JAD-160940">10.3233/JAD-160940">10.3233/JAD-160940.

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