近红外光谱脑功能成像在辅助诊断精神分裂症的临床应用

doi:10.3969/j.issn.1006-5725.2025.14.021

摘要/Abstract

摘要：

目的探讨近红外光谱脑功能成像技术在评估稳定期精神分裂症患者执行言语流畅性任务时前额与双侧颞区的脑功能特征，及其在辅助诊断精神分裂症的临床应用。方法纳入45例稳定期精神分裂症患者及30例健康志愿者。入组时应用近红外光谱脑功能成像检测执行言语流畅性任务时的额叶和双侧颞叶脑激活特征，测定额叶和双侧颞叶积分值、重心值及斜率。比较患者组与健康对照组在一般资料、组词数及近红外光谱脑功能成像指标的差异，应用logistic回归模型及受试者工作特征（ROC）曲线分析近红外光谱脑功能成像指标对精神分裂症患病的影响及诊断效果。结果在执行言语流畅性任务时，患者组组词数低于健康对照组，其额叶积分值、斜率和双侧颞叶积分值均低于对照组，差异均具有统计学意义（均P < 0.05）；而额叶重心值、颞叶重心值和双侧颞叶斜率在两组间差异无统计学意义（均P > 0.05）。二元logistic回归模型表明颞叶积分值与精神分裂症患病相关（OR = 0.979， P = 0.005）；ROC曲线分析显示额叶积分值、额叶斜率和颞叶积分值对是否患病分类较好，曲线下面积（AUC）分别为0.681、0.644和0.779（均P < 0.05）。结论稳定期精神分裂症在执行言语流畅性任务时额叶及颞叶的积分值降低、额叶斜率降低；这些指标对区分精神分裂症患者与健康对照者有一定的临床价值。

关键词: 精神分裂症, 近红外光谱脑功能成像, 言语流畅性任务, 辅助诊断

Abstract:

Objective To investigate the functional brain characteristics of the frontal and bilateral temporal regions during a verbal fluency task （VFT） in patients with stable schizophrenia using functional near-infrared spectroscopy （fNIRS）， and to evaluate its potential clinical application in assisting the diagnosis of schizophrenia. Methods A total of 45 stable schizophrenia patients and 30 healthy controls were enrolled in the study. fNIRS was employed to assess brain activation patterns in the frontal and bilateral temporal lobes during the VFT. The integral values， centroid values， and slopes of the frontal and bilateral temporal lobes were measured. Differences in demographic characteristics， word count， and fNIRS-derived parameters between the two groups were analyzed. A logistic regression model and receiver operating characteristic （ROC） curve analysis were conducted to evaluate the diagnostic performance of the fNIRS measures in distinguishing schizophrenia patients from healthy controls. Results During VFT， the patient group demonstrated reduced word count and decreased integral values and slopes in the frontal lobe， as well as lower integral values in the bilateral temporal lobes， compared to the healthy control group （all P < 0.05）. However， no statistically significant differences were observed between the two groups in terms of frontal lobe centroid value， temporal lobe centroid value， or bilateral temporal lobe slope （all P > 0.05）. The logistic regression model indicated that the temporal lobe integral value was significantly associated with the diagnosis of schizophrenia （OR = 0.979， P = 0.005）. ROC curve analysis revealed that the frontal lobe integral value， frontal lobe slope， and temporal lobe integral value exhibited acceptable discriminatory power for disease classification， with area under the curve （AUC） values of 0.681， 0.644， and 0.779， respectively （all P < 0.05）. Conclusion In stable schizophrenia， the integral values of the frontal and temporal lobes， as well as the slope of the frontal lobe， decrease during the VFT， suggesting potential clinical utility in differentiating individuals with schizophrenia from healthy controls.

Key words: schizophrenia, near infrared spectroscopy, verbal fluency task, diagnosis

中图分类号:

R749.3

慕永刚,陈龙云,从痛快,井绪秀,张素贞. 近红外光谱脑功能成像在辅助诊断精神分裂症的临床应用[J]. 实用医学杂志, 2025, 41(14): 2264-2268.

Yonggang MU,Longyun CHEN,Tongkuai CONG,Xuxiu JING,Suzhen. ZHANG. Clinical application of near⁃infrared spectroscopy in assisting the diagnosis of schizophrenia[J]. The Journal of Practical Medicine, 2025, 41(14): 2264-2268.

图/表 5

表1

表2

表3

图1

表4

参考文献 25

[1]	MARDER S R， CANNON T D. Schizophrenia ［J］. N Engl J Med， 2019， 381（18）： 1753-1761. doi:10.1056/nejmra1808803 doi: 10.1056/nejmra1808803
[2]	CHEN J， MULLER V I， DUKSRT J， et al. Intrinsic Connectivity Patterns of Task-Defined Brain Networks Allow Individual Prediction of Cognitive Symptom Dimension of Schizophrenia and Are Linked to Molecular Architecture ［J］. Biol Psychiatry， 2021， 89（3）： 308-319. doi:10.1016/j.biopsych.2020.09.024 doi: 10.1016/j.biopsych.2020.09.024
[3]	ZHANG S， LI W， XIANG Q， et al. Longitudinal alterations of modular functional-metabolic coupling in first-episode schizophrenia ［J］. J Psychiatr Res， 2022， 156：705-712. doi:10.1016/j.jpsychires.2022.10.067 doi: 10.1016/j.jpsychires.2022.10.067
[4]	俞天悦，郭茜，胡昊，等. 精神分裂症中氧化应激相关通路与诊断和预测价值的研究进展［J］. 实用医学杂志， 2024，40（20）：2935-2940.
[5]	AYANO G， DEMELASH S， YOHANNES Z， et al. Misdiagnosis， detection rate， and associated factors of severe psychiatric disorders in specialized psychiatry centers in Ethiopia ［J］. Ann Gen Psychiatry， 2021， 20（1）： 10. doi:10.1186/s12991-021-00333-7 doi: 10.1186/s12991-021-00333-7
[6]	郝飞，范丰梅，朱小林，等. 精神分裂症近红外光谱脑功能成像研究进展［J］. 中华精神科杂志， 2016， 49（2）： 113-117.
[7]	KOIKE S， SATMOURA Y， KAWASAKI S， et al. Application of functional near infrared spectroscopy as supplementary examination for diagnosis of clinical stages of psychosis spectrum ［J］. Psychiatry Clin Neurosci， 2017， 71（12）： 794-806. doi:10.1111/pcn.12551 doi: 10.1111/pcn.12551
[8]	WEI Y， CHEN Q， CURTIN A， et al. Functional near-infrared spectroscopy （fNIRS） as a tool to assist the diagnosis of major psychiatric disorders in a Chinese population ［J］. Eur Arch Psychiatry Clin Neurosci， 2021， 271（4）： 745-757. doi:10.1007/s00406-020-01125-y doi: 10.1007/s00406-020-01125-y
[9]	QIAO Y， SONG X， YAN J， et al. Neurological activation during verbal fluency task and resting-state functional connectivity abnormalities in obsessive-compulsive disorder： A functional near-infrared spectroscopy study ［J］. Front Psychiatry， 2024， 15：151416810. doi:10.3389/fpsyt.2024.1416810 doi: 10.3389/fpsyt.2024.1416810
[10]	ROSENBAUM D， HAGEN K， DEPPERMANN S， et al. State-dependent altered connectivity in late-life depression： A functional near-infrared spectroscopy study［J］.Neurobiol Aging， 2016， 39： 57-68. doi:10.1016/j.neurobiolaging.2015.11.022 doi: 10.1016/j.neurobiolaging.2015.11.022
[11]	RIVHSRDS A L， PARDINAS A F， FRIZZATI A， et al. The Relationship Between Polygenic Risk Scores and Cognition in Schizophrenia ［J］. Schizophr Bull， 2020， 46（2）： 336-344.
[12]	RAHMAN M A， SIDDIK A B， GHOSH T K， et al. A Narrative Review on Clinical Applications of fNIRS ［J］. J Digit Imaging， 2020， 33（5）： 1167-1184. doi:10.1007/s10278-020-00387-1 doi: 10.1007/s10278-020-00387-1
[13]	徐若愚，李献云. 稳定期精神分裂症在不同情绪启动下反应抑制特点［J］. 中国神经精神疾病杂志， 2022， 48（10）： 614-618.
[14]	管晓枫，胡欣怡，陆峥. 精神分裂症诊断标准更新与分类变化［J］. 重庆医科大学学报，2021，46（7）：760-763.
[15]	VITA A， GAEBEL W， MUCCI A， et al. European Psychiatric Association guidance on assessment of cognitive impairment in schizophrenia［J］. Eur Psychiatry， 2022， 65（1）： e58. doi:10.1192/j.eurpsy.2022.2316 doi: 10.1192/j.eurpsy.2022.2316
[16]	李佳，林荫，吉训琦，等. 载脂蛋白E和MTHFR C677T基因多态性与精神分裂症及患者认知功能的关联性［J］. 实用医学杂志， 2021，37（18）：2391-2394.
[17]	RUND B R， BARDER H E， EVENSEN J， et al. Neurocognition and Duration of Psychosis： A 10-year Follow-up of First-Episode Patients ［J］. Schizophr Bull， 2016， 42（1）： 87-95.
[18]	LIU D， JI C， ZHUO K， et al. Impaired cue identification and intention retrieval underlie prospective memory deficits in patients with first-episode schizophrenia ［J］. Aust N Z J Psychiatry， 2017， 51（3）： 270-277. doi:10.1177/0004867416640097 doi: 10.1177/0004867416640097
[19]	LIANG J， CHEN L， LI Y， et al. Unraveling the Prefrontal Cortex-Basolateral Amygdala Pathway's Role on Schizophrenia's Cognitive Impairments： A Multimodal Study in Patients and Mouse Models ［J］. Schizophr Bull， 2024， 50（4）：913-923. doi:10.1093/schbul/sbae063 doi: 10.1093/schbul/sbae063
[20]	HUSAIN S F， TANG T B， YU R， et al. Cortical haemodynamic response measured by functional near infrared spectroscopy during a verbal fluency task in patients with major depression and borderline personality disorder ［J］. EBioMedicine， 2020， 51： 102586. doi:10.1016/j.ebiom.2019.11.047 doi: 10.1016/j.ebiom.2019.11.047
[21]	YAMAMURO K， KIMOTO S， IIDA J， et al. Distinct patterns of blood oxygenation in the prefrontal cortex in clinical phenotypes of schizophrenia and bipolar disorder ［J］. J Affect Disord， 2018， 234：45-53. doi:10.1016/j.jad.2018.02.065 doi: 10.1016/j.jad.2018.02.065
[22]	PAUL T， SEE J W， VIJAKUMAR V， et al. Neurostructural changes in schizophrenia and treatment-resistance： A narrative review ［J］. Psychoradiology， 2024， 4：kkae015. doi:10.1093/psyrad/kkae015 doi: 10.1093/psyrad/kkae015
[23]	YEUNG M K， LIN J. Probing depression， schizophrenia， and other psychiatric disorders using fNIRS and the verbal fluency test： A systematic review and meta-analysis ［J］. J Psychiatr Res， 2021， 140：416-435. doi:10.1016/j.jpsychires.2021.06.015 doi: 10.1016/j.jpsychires.2021.06.015
[24]	ZHANG K， JIN X， HE Y， et al. Atypical frontotemporal cortical activity in first-episode adolescent-onset schizophrenia during verbal fluency task： A functional near-infrared spectroscopy study ［J］. Front Psychiatry， 2023， 14：1126131.
[25]	CHOU P H， LIU W C， LIN W H， et al. NIRS-aided differential diagnosis among patients with major depressive disorder， bipolar disorder， and schizophrenia ［J］. J Affect Disord， 2023， 15（341）： 366-373.

项目	精神分裂症组	健康对照组	t/χ²值	P值
年龄/岁	42.78 ± 6.88	40.57 ± 8.47	1.242	0.218
性别（男/女）/例	21/24	15/15	0.800	0.777
受教育年限	14.53 ± 2.62	15.23 ± 2.92	-1.083	0.282

项目	精神分裂症组	健康对照组	t/Z值	P值
组词数/个	8.98 ± 3.22	11.97 ± 3.44	3.817	< 0.001
额叶积分值［M（Q₁，Q₃）］	25.40（-3.00，66.90）	57.70（35.30，77.00）	2.742	0.006
额叶重心值/s	59.59 ± 15.33	56.43 ± 8.80	-0.102	0.310
额叶斜率	0.000 5 ± 0.001 1	0.001 0 ± 0.001 1	2.214	0.027
颞叶积分值［M（Q₁，Q₃）］	28.00（-1.55， 65.20）	110.10（49.98，157.50）	4.110	< 0.001
颞叶重心值/s	58.66 ± 15.21	59.67 ± 7.65	0.340	0.735
颞叶斜率	0.000 4 ± 0.000 1	0.000 6 ± 0.000 8	1.593	0.111

项目	β	SE	P值	OR	95%CI
组词数	-0.149	0.078	0.057	0.861	0.739 ~ 1.004
额叶积分值	0.005	0.008	0.562	1.005	0.989 ~ 1.021
额叶斜率^a	-0.024	0.029	0.417	0.976	0.922 ~ 1.034
颞叶积分值	-0.021	0.007	0.005	0.979	0.965 ~ 0.994

项目	最佳截断值	灵敏度	特异度	P值	AUC	95%CI
组词数	8.5	0.900	0.364	0.086	0.618	0.491 ~ 0.745
额叶积分值	50.9	0.667	0.682	0.008	0.681	0.558 ~ 0.805
额叶斜率	0.011 5	0.533	0.864	0.036	0.644	0.504 ~ 0.783
颞叶积分值	72.6	0.633	0.844	< 0.001	0.779	0.664 ~ 0.894