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Fernández-Rodicio S, Ferro-Costas G, Sampedro-Viana A, Bazarra-Barreiros M, Ferreirós A, López-Arias E, Pérez-Mato M, Ouro A, Pumar JM, Mosqueira AJ, Alonso-Alonso ML, Castillo J, Hervella P, Iglesias-Rey R. Perfusion-weighted software written in Python for DSC-MRI analysis. Front Neuroinform 2023; 17:1202156. [PMID: 37593674 PMCID: PMC10431979 DOI: 10.3389/fninf.2023.1202156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 06/27/2023] [Indexed: 08/19/2023] Open
Abstract
Introduction Dynamic susceptibility-weighted contrast-enhanced (DSC) perfusion studies in magnetic resonance imaging (MRI) provide valuable data for studying vascular cerebral pathophysiology in different rodent models of brain diseases (stroke, tumor grading, and neurodegenerative models). The extraction of these hemodynamic parameters via DSC-MRI is based on tracer kinetic modeling, which can be solved using deconvolution-based methods, among others. Most of the post-processing software used in preclinical studies is home-built and custom-designed. Its use being, in most cases, limited to the institution responsible for the development. In this study, we designed a tool that performs the hemodynamic quantification process quickly and in a reliable way for research purposes. Methods The DSC-MRI quantification tool, developed as a Python project, performs the basic mathematical steps to generate the parametric maps: cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), signal recovery (SR), and percentage signal recovery (PSR). For the validation process, a data set composed of MRI rat brain scans was evaluated: i) healthy animals, ii) temporal blood-brain barrier (BBB) dysfunction, iii) cerebral chronic hypoperfusion (CCH), iv) ischemic stroke, and v) glioblastoma multiforme (GBM) models. The resulting perfusion parameters were then compared with data retrieved from the literature. Results A total of 30 animals were evaluated with our DSC-MRI quantification tool. In all the models, the hemodynamic parameters reported from the literature are reproduced and they are in the same range as our results. The Bland-Altman plot used to describe the agreement between our perfusion quantitative analyses and literature data regarding healthy rats, stroke, and GBM models, determined that the agreement for CBV and MTT is higher than for CBF. Conclusion An open-source, Python-based DSC post-processing software package that performs key quantitative perfusion parameters has been developed. Regarding the different animal models used, the results obtained are consistent and in good agreement with the physiological patterns and values reported in the literature. Our development has been built in a modular framework to allow code customization or the addition of alternative algorithms not yet implemented.
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Affiliation(s)
- Sabela Fernández-Rodicio
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | | | - Ana Sampedro-Viana
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - Marcos Bazarra-Barreiros
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | | | - Esteban López-Arias
- Translational Stroke Laboratory (TREAT), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - María Pérez-Mato
- Neurological Sciences and Cerebrovascular Research Laboratory, Department of Neurology and Stroke Center, La Paz University Hospital, Neuroscience Area of IdiPAZ Health Research Institute, Universidad Autónoma de Madrid, Madrid, Spain
| | - Alberto Ouro
- NeuroAging Group (NEURAL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - José M. Pumar
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
- Department of Neuroradiology, Hospital Clínico Universitario, Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - Antonio J. Mosqueira
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
- Department of Neuroradiology, Hospital Clínico Universitario, Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - María Luz Alonso-Alonso
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - José Castillo
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - Pablo Hervella
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - Ramón Iglesias-Rey
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
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Vázquez M, Anfossi L, Ben-Yoav H, Diéguez L, Karopka T, Della Ventura B, Abalde-Cela S, Minopoli A, Di Nardo F, Shukla VK, Teixeira A, Tvarijonaviciute A, Franco-Martínez L. Use of some cost-effective technologies for a routine clinical pathology laboratory. LAB ON A CHIP 2021; 21:4330-4351. [PMID: 34664599 DOI: 10.1039/d1lc00658d] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Classically, the need for highly sophisticated instruments with important economic costs has been a major limiting factor for clinical pathology laboratories, especially in developing countries. With the aim of making clinical pathology more accessible, a wide variety of free or economical technologies have been developed worldwide in the last few years. 3D printing and Arduino approaches can provide up to 94% economical savings in hardware and instrumentation in comparison to commercial alternatives. The vast selection of point-of-care-tests (POCT) currently available also limits the need for specific instruments or personnel, as they can be used almost anywhere and by anyone. Lastly, there are dozens of free and libre digital tools available in health informatics. This review provides an overview of the state-of-the-art on cost-effective alternatives with applications in routine clinical pathology laboratories. In this context, a variety of technologies including 3D printing and Arduino, lateral flow assays, plasmonic biosensors, and microfluidics, as well as laboratory information systems, are discussed. This review aims to serve as an introduction to different technologies that can make clinical pathology more accessible and, therefore, contribute to achieve universal health coverage.
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Affiliation(s)
- Mercedes Vázquez
- National Centre For Sensor Research, School of Chemical Sciences, Dublin City University, Glasnevin, Dublin 9, Ireland
| | - Laura Anfossi
- Department of Chemistry, University of Turin, Via Giuria, 5, I-10125 Turin, Italy
| | - Hadar Ben-Yoav
- Nanobioelectronics Laboratory (NBEL), Department of Biomedical Engineering, Ilse Katz Institute of Nanoscale Science and Technology, Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel
| | - Lorena Diéguez
- Medical Devices Research Group, International Iberian Nanotechnology Laboratory - INL, 4715-330 Braga, Portugal
| | | | - Bartolomeo Della Ventura
- Department of Physics "E. Pancini", University of Naples Federico II, Via Cintia 26, I-80126 Napoli, Italy
| | - Sara Abalde-Cela
- Medical Devices Research Group, International Iberian Nanotechnology Laboratory - INL, 4715-330 Braga, Portugal
| | - Antonio Minopoli
- Department of Physics "E. Pancini", University of Naples Federico II, Via Cintia 26, I-80126 Napoli, Italy
| | - Fabio Di Nardo
- Department of Chemistry, University of Turin, Via Giuria, 5, I-10125 Turin, Italy
| | - Vikas Kumar Shukla
- Nanobioelectronics Laboratory (NBEL), Department of Biomedical Engineering, Ilse Katz Institute of Nanoscale Science and Technology, Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel
| | - Alexandra Teixeira
- Medical Devices Research Group, International Iberian Nanotechnology Laboratory - INL, 4715-330 Braga, Portugal
| | - Asta Tvarijonaviciute
- Interdisciplinary Laboratory of Clinical Pathology, Interlab-UMU, Regional Campus of International Excellence 'Campus Mare Nostrum', University of Murcia, 30100 Murcia, Spain.
| | - Lorena Franco-Martínez
- Interdisciplinary Laboratory of Clinical Pathology, Interlab-UMU, Regional Campus of International Excellence 'Campus Mare Nostrum', University of Murcia, 30100 Murcia, Spain.
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Lacalle-Aurioles M, Navas-Sánchez FJ, Alemán-Gómez Y, Olazarán J, Guzmán-De-Villoria JA, Cruz-Orduña I, Mateos-Pérez JM, Desco M. The Disconnection Hypothesis in Alzheimer's Disease Studied Through Multimodal Magnetic Resonance Imaging: Structural, Perfusion, and Diffusion Tensor Imaging. J Alzheimers Dis 2016; 50:1051-64. [PMID: 26890735 DOI: 10.3233/jad-150288] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
According to the so-called disconnection hypothesis, the loss of synaptic inputs from the medial temporal lobes (MTL) in Alzheimer's disease (AD) may lead to reduced activity of target neurons in cortical areas and, consequently, to decreased cerebral blood flow (CBF) in those areas. The aim of this study was to assess whether hypoperfusion in parietotemporal and frontal cortices of patients with mild cognitive impairment who converted to AD (MCI-c) and patients with mild AD is associated with atrophy in the MTL and/or microstructural changes in the white matter (WM) tracts connecting these areas. We assessed these relationships by investigating correlations between CBF in hypoperfused areas, mean cortical thickness in atrophied regions of the MTL, and fractional anisotropy (FA) in WM tracts. In the MCI-c group, a strong correlation was observed between CBF of the superior parietal gyri and FA in the parahippocampal tracts (left: r = 0.90, p < 0.0001; right: r = 0.597, p = 0.024), and between FA in the right parahippocampal tract and the right precuneus (r = 0.551, p = 0.041). No significant correlations between CBF in hypoperfused regions and FA in the WM tract were observed in the AD group. These results suggest an association between perfusion deficits and altered WM tracts in prodromal AD, while microvasculature impairments may have a greater influence in more advanced stages. We did not find correlations between cortical thinning in the medial temporal lobes and decreased FA in the WM tracts of the limbic system in either group.
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Affiliation(s)
- María Lacalle-Aurioles
- Departamento de Bioingeniería e Ingeniería Aeroespacial, Universidad Carlos III de Madrid, Leganés, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain.,Centro de Investigación Biomédica en Red de Salud Mental CIBERSAM, Spain
| | - Francisco Javier Navas-Sánchez
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain.,Centro de Investigación Biomédica en Red de Salud Mental CIBERSAM, Spain
| | - Yasser Alemán-Gómez
- Departamento de Bioingeniería e Ingeniería Aeroespacial, Universidad Carlos III de Madrid, Leganés, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain.,Centro de Investigación Biomédica en Red de Salud Mental CIBERSAM, Spain
| | - Javier Olazarán
- Servicio de Neurología, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | | | - Isabel Cruz-Orduña
- Servicio de Neurología, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - José María Mateos-Pérez
- Centro de Investigación Biomédica en Red de Salud Mental CIBERSAM, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
| | - Manuel Desco
- Departamento de Bioingeniería e Ingeniería Aeroespacial, Universidad Carlos III de Madrid, Leganés, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain.,Centro de Investigación Biomédica en Red de Salud Mental CIBERSAM, Spain
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