title: Monitoring microvascular perfusion variations with laser speckle contrast imaging using a view-based temporal template method.
abstract: Laser speckle contrast imaging (LSCI) continues to gain an increased interest in clinical and research studies to monitor microvascular perfusion. Due to its high spatial and temporal resolutions, LSCI may lead to a large amount of data. The analysis of such data, as well as the determination of the regions where the perfusion varies, can become a lengthy and tedious task. We propose here to analyze if a view-based temporal template method, the motion history image (MHI) algorithm, may be of use in detecting the perfusion variations locations.
  
  
  
  LSCI data recorded during three different kinds of perfusion variations are considered: (i) cerebral blood flow during spreading depolarization (SD) in a mouse; (ii) cerebral blood flow during SD in a rat; (iii) cerebral blood flow during cardiac arrest in a rat. Each of these recordings was processed with MHI.
  
  
  
  We show that, for the three pathophysiological situations, MHI identifies the area in which perfusion evolves with time. The results are more easily obtained compared with a visual inspection of all of the frames constituting the recordings. MHI also has the advantage of relying on a rather simple algorithm.
  
  
  
  MHI can be tested in clinical and research studies to aid the user in perfusion analyses.
authors.affiliation: Department of Physics, Cambridge Institute of Polytechnic, Baheya, Angara, Ranchi 835103, Jharkhand, India. Electronic address: mohamedzaheer1@gmail.com.
authors.forename: Mohammad Zaheer
authors.initials: MZ
authors.lastname: Ansari
authors.affiliation: Department of Experimental Neurology, Charité University Medicine Berlin, Charitéplatz 1, 10117 Berlin, Germany; Department of Neurology, Charité University Medicine Berlin, Charitéplatz 1, 10117 Berlin, Germany; Center for Stroke Research, Charité University Medicine Berlin, Charitéplatz 1, 10117 Berlin, Germany.
authors.forename: Eun-Jeung
authors.initials: EJ
authors.lastname: Kang
authors.affiliation: University of Pittsburgh, Safar Center for Resuscitation Research, USA.
authors.forename: Mioara D
authors.initials: MD
authors.lastname: Manole
authors.affiliation: Department of Experimental Neurology, Charité University Medicine Berlin, Charitéplatz 1, 10117 Berlin, Germany; Department of Neurology, Charité University Medicine Berlin, Charitéplatz 1, 10117 Berlin, Germany; Center for Stroke Research, Charité University Medicine Berlin, Charitéplatz 1, 10117 Berlin, Germany.
authors.forename: Jens P
authors.initials: JP
authors.lastname: Dreier
authors.affiliation: Univ Angers, LARIS - Laboratoire Angevin de Recherche en Ingénierie des Systèmes, Angers, France.
authors.forename: Anne
authors.initials: A
authors.lastname: Humeau-Heurtier
mesh_terms: D000465:Algorithms; D000818:Animals; D001783:Blood Flow Velocity; D002536:Cerebral Arteries / Q000503:physiopathology*; D002560:Cerebrovascular Circulation; D013181:Cortical Spreading Depression; D004195:Disease Models, Animal; D005240:Feasibility Studies; D006323:Heart Arrest / Q000175:diagnosis* / Q000503:physiopathology; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D017078:Laser-Doppler Flowmetry / Q000379:methods*; D051379:Mice; D008833:Microcirculation; D055420:Perfusion Imaging / Q000379:methods*; D011237:Predictive Value of Tests; D011921:Rats, Inbred WKY; D012039:Regional Blood Flow; D013997:Time Factors
keywords: Biomedical signal processing; Cerebral blood flow; Microcirculation; Motion history image