Neuroimaging-aided differential diagnosis of the depressive state

Ryu Takizawa, Masato Fukuda, Shingo Kawasaki, Kiyoto Kasai, Masaru Mimura, Shenghong Pu, Takamasa Noda, Shin ichi Niwa, Yuji Okazaki, Masashi Suda, Yuichi Takei, Yoshiyuki Aoyama, Kosuke Narita, Masahiko Mikuni, Masaki Kameyama, Toru Uehara, Masaru Kinou, Shinsuke Koike, Ayaka Ishii-Takahashi, Noriyoshi Ichikawa & 18 others Michiyuki Fujiwara, Haruhisa Ohta, Hiroi Tomioka, Bun Yamagata, Kaori Yamanaka, Kazuyuki Nakagome, Taro Matsuda, Sumiko Yoshida, Soichi Kono, Hirooki Yabe, Sachie Miura, Yukika Nishimura, Hisashi Tanii, Ken Inoue, Chika Yokoyama, Yoichiro Takayanagi, Katsuyoshi Takahashi, Mayumi Nakakita

Research output: Contribution to journalArticle

113 Citations (Scopus)

Abstract

A serious problem in psychiatric practice is the lack of specific, objective biomarker-based assessments to guide diagnosis and treatment. The use of such biomarkers could assist clinicians in establishing differential diagnosis, which may improve specific individualised treatment. This multi-site study sought to develop a clinically suitable neuroimaging-guided diagnostic support system for differential diagnosis at the single-subject level among multiple psychiatric disorders with depressive symptoms using near-infrared spectroscopy, which is a compact and portable neuroimaging method. We conducted a multi-site, case-control replication study using two cohorts, which included seven hospitals in Japan. The study included 673 patients (women/men: 315/358) with psychiatric disorders (major depressive disorder, bipolar disorder, or schizophrenia) who manifested depressive symptoms, and 1007 healthy volunteers (530/477). We measured the accuracy of the single-subject classification in differential diagnosis among major psychiatric disorders, based on spatiotemporal characteristics of fronto-temporal cortical haemodynamic response patterns induced by a brief (<. 3. min) verbal fluency task. Data from the initial site were used to determine an optimal threshold, based on receiver-operator characteristics analysis, and to generate the simplest and most significant algorithm, which was validated using data from the remaining six sites. The frontal haemodynamic patterns detected by the near-infrared spectroscopy method accurately distinguished between patients with major depressive disorder (74.6%) and those with the two other disorders (85.5%; bipolar disorder or schizophrenia) that presented with depressive symptoms. These results suggest that neuroimaging-guided differential diagnosis of major psychiatric disorders developed using the near-infrared spectroscopy method can be a promising biomarker that should aid in personalised care in real clinical settings. Potential confounding effects of clinical (e.g., age, sex) and systemic (e.g., autonomic nervous system indices) variables on brain signals will need to be clarified to improve classification accuracy.

Original languageEnglish
Pages (from-to)498-507
Number of pages10
JournalNeuroImage
Volume85
DOIs
Publication statusPublished - 2014 Jan 15

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Neuroimaging
Psychiatry
Differential Diagnosis
Near-Infrared Spectroscopy
Biomarkers
Major Depressive Disorder
Depression
Bipolar Disorder
Schizophrenia
Autonomic Nervous System
Case-Control Studies
Healthy Volunteers
Japan
Hemodynamics
Brain
Therapeutics

Keywords

  • Depressive state
  • Differential diagnosis
  • Near-infrared spectroscopy (NIRS)
  • Neuroimaging
  • Psychiatric disorder

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Neurology

Cite this

Takizawa, R., Fukuda, M., Kawasaki, S., Kasai, K., Mimura, M., Pu, S., ... Nakakita, M. (2014). Neuroimaging-aided differential diagnosis of the depressive state. NeuroImage, 85, 498-507. https://doi.org/10.1016/j.neuroimage.2013.05.126

Neuroimaging-aided differential diagnosis of the depressive state. / Takizawa, Ryu; Fukuda, Masato; Kawasaki, Shingo; Kasai, Kiyoto; Mimura, Masaru; Pu, Shenghong; Noda, Takamasa; Niwa, Shin ichi; Okazaki, Yuji; Suda, Masashi; Takei, Yuichi; Aoyama, Yoshiyuki; Narita, Kosuke; Mikuni, Masahiko; Kameyama, Masaki; Uehara, Toru; Kinou, Masaru; Koike, Shinsuke; Ishii-Takahashi, Ayaka; Ichikawa, Noriyoshi; Fujiwara, Michiyuki; Ohta, Haruhisa; Tomioka, Hiroi; Yamagata, Bun; Yamanaka, Kaori; Nakagome, Kazuyuki; Matsuda, Taro; Yoshida, Sumiko; Kono, Soichi; Yabe, Hirooki; Miura, Sachie; Nishimura, Yukika; Tanii, Hisashi; Inoue, Ken; Yokoyama, Chika; Takayanagi, Yoichiro; Takahashi, Katsuyoshi; Nakakita, Mayumi.

In: NeuroImage, Vol. 85, 15.01.2014, p. 498-507.

Research output: Contribution to journalArticle

Takizawa, R, Fukuda, M, Kawasaki, S, Kasai, K, Mimura, M, Pu, S, Noda, T, Niwa, SI, Okazaki, Y, Suda, M, Takei, Y, Aoyama, Y, Narita, K, Mikuni, M, Kameyama, M, Uehara, T, Kinou, M, Koike, S, Ishii-Takahashi, A, Ichikawa, N, Fujiwara, M, Ohta, H, Tomioka, H, Yamagata, B, Yamanaka, K, Nakagome, K, Matsuda, T, Yoshida, S, Kono, S, Yabe, H, Miura, S, Nishimura, Y, Tanii, H, Inoue, K, Yokoyama, C, Takayanagi, Y, Takahashi, K & Nakakita, M 2014, 'Neuroimaging-aided differential diagnosis of the depressive state', NeuroImage, vol. 85, pp. 498-507. https://doi.org/10.1016/j.neuroimage.2013.05.126
Takizawa, Ryu ; Fukuda, Masato ; Kawasaki, Shingo ; Kasai, Kiyoto ; Mimura, Masaru ; Pu, Shenghong ; Noda, Takamasa ; Niwa, Shin ichi ; Okazaki, Yuji ; Suda, Masashi ; Takei, Yuichi ; Aoyama, Yoshiyuki ; Narita, Kosuke ; Mikuni, Masahiko ; Kameyama, Masaki ; Uehara, Toru ; Kinou, Masaru ; Koike, Shinsuke ; Ishii-Takahashi, Ayaka ; Ichikawa, Noriyoshi ; Fujiwara, Michiyuki ; Ohta, Haruhisa ; Tomioka, Hiroi ; Yamagata, Bun ; Yamanaka, Kaori ; Nakagome, Kazuyuki ; Matsuda, Taro ; Yoshida, Sumiko ; Kono, Soichi ; Yabe, Hirooki ; Miura, Sachie ; Nishimura, Yukika ; Tanii, Hisashi ; Inoue, Ken ; Yokoyama, Chika ; Takayanagi, Yoichiro ; Takahashi, Katsuyoshi ; Nakakita, Mayumi. / Neuroimaging-aided differential diagnosis of the depressive state. In: NeuroImage. 2014 ; Vol. 85. pp. 498-507.
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