Medical & Biological Engineering & Computing

, Volume 57, Issue 6, pp 1285–1295 | Cite as

Multimodal neuroimaging study reveals dissociable processes between structural and functional networks in patients with subacute intracerebral hemorrhage

  • Xiaobing Zhang
  • Xuebin Yu
  • Qingquan Bao
  • Liming Yang
  • Yu SunEmail author
  • Peng QiEmail author
Original Article


Emerging evidence has revealed widespread stroke-induced brain dysconnectivity, which leads to abnormal network organization. However, there are apparent discrepancies in dysconnectivity between structural connectivity and functional connectivity studies. In this work, resting-state fMRI and structural diffusion tensor imaging were obtained from 26 patients with subacute (10–14 days) intracerebral hemorrhage (ICH) and 20 matched healthy participants (patients/controls = 21/18 after head motion rejection). Graph theoretical approaches were applied to multimodal brain networks to quantitatively compare topological properties between both groups. Prominent small-world properties were found in the structural and functional brain networks of both groups. However, a significant deficit in global integration was revealed in the structural brain networks of the patient group and was associated with more severe clinical manifestations of ICH. Regarding ICH-related nodal deficits, reduced nodal interconnectivity was mainly detected in motor-related regions. Moreover, in the functional brain network, topological properties were mostly comparable between patients with ICH and healthy participants. Beyond the prominent small-world architecture in multimodal brain networks, there are dissociable alterations between structural and functional brain networks in patients with ICH. These findings highlight the potential for using aberrant network metrics as neural biomarkers for evaluation of the severity of ICH.

Graphical abstract

Intracerebral hemorrhage (ICH) also known as cerebral bleed, a major type of stroke, would significantly affect brain structure and function. Using multimodal neuroimaging, Zhang et al. investigate the ICH-related dysconnectivity in structural and functional brain networks and show a significantly disintegrated structural brain network with a preserved functional network topology in subacute phase (10–14 days).


Subacute intracerebral hemorrhage (ICH) Resting-state fMRI Diffusion tensor imaging (DTI) Brain connectivity Graph theoretical analysis 



We would like to convey our appreciation to all the participants, especially patients with ICH and their families.

Funding information

This work was supported by the General Research Plan B of Zhejiang province (Grant no. 2017KY661 awarded to X. Z.), the ‘Hundred Talents Program’ of Zhejiang University (awarded to Y. S.), the National Natural Science Foundation of China (Grant no. 81801785 awarded to Y. S.), and the Fundamental Research Funds for the Central Universities (Grant no. 2018QNA5017 awarded to Y. S.).

Compliance with ethical standards

The study was approved by the local ethics committee in Shaoxing People’s Hospital, and written informed consent was obtained from each participant (control group) or from the patient’s first degree relatives (patient group).

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© International Federation for Medical and Biological Engineering 2019

Authors and Affiliations

  1. 1.Department of NeurosurgeryShaoxing People’s Hospital (Shaoxing Hospital, Zhejiang University School of Medicine)ZhejiangChina
  2. 2.Department of RadiologyShaoxing People’s Hospital (Shaoxing Hospital, Zhejiang University School of Medicine)ZhejiangChina
  3. 3.Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical EngineeringZhejiang UniversityZhejiangChina
  4. 4.Singapore Institute for Neurotechnology (SINAPSE), Centre for Life ScienceNational University of SingaporeSingaporeSingapore
  5. 5.Department of Control Science and Engineering, College of Electronics and Information EngineeringTongji UniversityShanghaiChina

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