CAAos platform: an integrated platform for analysis of cerebral hemodynamics data

Author(s)

Salinet, Joao ^[1] ; de Moura, Fernando Silva ^[1] ; Romaneli, Renata ^[1] ; Nery dos Santos, Pedro Machado ^[1] ; Zamai, Matheus ^[1] ; Panerai, Ronney B. ^{[2, 3]} ; Duarte, Andre M. ^[1] ; Bor-Seng-Shu, Edson ^[4] ; Macedo Salinet, Angela Salomao ^{[1, 4]}

Affiliation

^[1] Fed Univ ABC, Biomed Engn, Engn Modelling & Appl Social Sci Ctr, Sao Bernardo Do Campo - Brazil

^[2] Univ Leicester, Dept Cardiovasc Sci, Cerebral Haemodynam Ageing & Stroke Med CHiASM Re, Leicester, Leics - England

^[3] Glenfield Hosp, British Heart Fdn, NIHR Leicester Biomed Res Ctr, Cardiovasc Res Ctr, Leicester, Leics - England

^[4] Univ Sao Paulo, Hosp Clin, Sch Med, Neurol Dept, Sao Paulo - Brazil

• Document type: Journal article
• Source: Physiological Measurement; v. 42, n. 10 OCT 1 2021.
• Web of Science Citations: 0

Abstract

Objective. The purpose of this article is to introduce readers to the concept and structure of the CAAos (Cerebral Autoregulation Assessment Open Source) platform, and provide evidence of its functionality. Approach. The CAAos platform is a new open-source software research tool, developed in Python 3 language, that combines existing and novel methods for interactive visual inspection, batch processing and analysis of multichannel records. The platform is scalable, allowing for the customization and inclusion of new tools. Main results. Currently, the CAAos platform is composed of two main modules, preprocessing (containing artefact removal, filtering and signal beat to beat extraction tools) and cerebral autoregulation (CA) analysis modules. Two methods for assessing CA have been implemented into the CAAos platform: transfer function analysis (TFA) and the autoregulation index (ARI). In order to provide validation of the TFA and ARI estimates derived from the CAAos platform, the results were compared with those derived from two other algorithms. Validation was performed using data from 28 participants, corresponding to 13 acute ischemic stroke patients and 13 age- and sex-matched control subjects. Agreement between estimates was assessed by intraclass correlation coefficient and Bland-Altman analysis. No significant statistical difference between the algorithms was found. Moreover, there was an excellent correspondence between the curves of all parameters analysed, with the intraclass correlation coefficient ranging from 0.98 (95%CI 0.976-0.999) to 1.00 (95%CI 1 -1). The mean differences revealed a very small magnitude bias indicating an excellent agreement between the estimates. Significance. As open-source software, the source code for the software is freely available for noncommercial use, reducing barriers to performing CA analysis, allowing inspection of the inner-workings of the algorithms, and facilitating networked activities with common standards. The CAAos platform is a tailored software solution for the scientific community in the cerebral hemodynamic field and contributes to the increasing use and reproducibility of CA assessment. (AU)

• FAPESP's process: 18/25606-2 - Accurate mapping of cardiac fibrillation activity: an experimental contribution
• Grantee: João Loures Salinet Júnior
• Support Opportunities: Research Grants - Young Investigators Grants
• FAPESP's process: 19/09154-7 - Construction of dynamic models of the cerebral circulation for electrical impedance tomography applied in the classification and monitoring of cerebrovascular accidents
• Grantee: Fernando Silva de Moura
• Support Opportunities: Scholarships abroad - Research
• FAPESP's process: 20/02366-6 - CAAos platform - cerebral autoregulation assessment open source platform: validation of the autoregulation index
• Grantee: Renata Romanelli da Costa
• Support Opportunities: Scholarships in Brazil - Scientific Initiation