Pernot Mathieu

Pernot Mathieu

Director of Physics for Medicine Paris
Research director at Inserm
mathieu.pernot@espci.fr
ResearcherID: G-3404-2013
ORCID: 0000-0001-6713-4642
See the ResearchGate profile >

Education

  • 2015 – “Habilitation à Diriger des Recherches”, Université Paris Diderot, France
  • 2004 – PhD in Physics, Université Paris Diderot, France
    “Ultrasound therapy and monitoring: new techniques”
  • 2001 – Master of Science in Acoustics, Université Paris Diderot, France
  • 2001 – Engineering degree at ESPCI (Ecole Supérieure de Physique et Chimie Industrielles), Paris, France

Professional experience

  • since 2025 – Director of Physics for Medicine Paris (ESPCI-Paris PSL, INSERM, CNRS), Paris, France
  • since 2016 – Tenured research director, Inserm, Paris, France
  • 2019-2024 – Deputy director of Physics for Medicine Paris laboratory, Paris, France
  • 2007-2016 – Tenured research officer, Inserm, Paris, France
  • 2006-2007 – Research Engineer, SuperSonic Imagine, Aix-en-provence, France
  • 2004-2005 – Postdoctoral fellow, Columbia University, New York, USA

Activities and Responsabilities

  • Director of Physics for Medicine Paris institute, Paris, France
  • Co-founder of the company eMyosound
  • Co-founder of the company Iconeus
  • Co-founder of the company Cardiawave
  • Associate Editor of IEEE Transactions of Ultrasonics, Ferroelectrics and Frequency Control
  • Member of the IEEE UFFC Technical Program Committee
  • Member of the International Advisory Board of Physics in Medicine and Biology
  • Editorial advisory panel member: Scientific Reports
  • Co-inventor of more than 40 patents families in the field of biomedical ultrasound
  • Co-author of more than 200 publications in peer-reviewed international journals
  • Citations: 13855, h-index: 65 on Google scholar / Citations: 8810 (h-index: 54) on Web of Science

Main awards and distinctions

  • Prix de la fondation Langlois (2024)
  • Innovator award of Paris – Ile de France (2021)
  • Rotblat Medal, citation prize from Physics in Medicine and Biology (2019)
  • 2016 Outstanding Paper Award of the IEEE Transactions in Ultrasonics, Ferroelectrics and Frequency Control
  • Roberts Prize from the Institute of Physics and Engineering in Medicine (IPEM) (2015)
  • Winner of the BPI ILab Competition for the creation of innovative technology companies in 2014 (project Valvopulse) and 2015 (project Neuroflow)
  • Winner of the Concours Mondial de l’Innovation, phase I, II & III (project Valvosoft)
  • ERC Starting Grant 2012 (project ULTRAECHOCARDIO)

Research topics

  • Biomedical ultrasound
  • Cardiovascular ultrasound imaging
  • Functional ultrasound imaging
  • Ultrafast ultrasound imaging
  • 3D ultrasound imaging
  • Non-invasive ultrasound therapy

Main publications

4989618 {151195:ZV3HIJJG},{151195:5AQNTQNS},{151195:HCR48RYC},{151195:HE55MS5W},{151195:BXDDCDWA},{151195:FZQWW8A4},{151195:KBV4JIKB} 1 national-institute-of-health-research 50 date desc 7229 https://www.physicsformedicine.espci.fr/wp-content/plugins/zotpress/

Latest publications

4989618 94NJIV78 pernot 1 national-institute-of-health-research 6 date desc 7229 https://www.physicsformedicine.espci.fr/wp-content/plugins/zotpress/
%7B%22status%22%3A%22success%22%2C%22updateneeded%22%3Afalse%2C%22instance%22%3Afalse%2C%22meta%22%3A%7B%22request_last%22%3A0%2C%22request_next%22%3A0%2C%22used_cache%22%3Atrue%7D%2C%22data%22%3A%5B%7B%22key%22%3A%22D3BTJF99%22%2C%22library%22%3A%7B%22id%22%3A4989618%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Zhang%20et%20al.%22%2C%22parsedDate%22%3A%222026-01-08%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BZhang%20G%2C%20Leroy%20H%2C%20Haidour%20N%2C%20Zucker%20N%2C%20Rivera%20DE%2C%20Jimenez%20A%2C%20%26lt%3Bi%26gt%3Bet%20al.%26lt%3B%5C%2Fi%26gt%3B%20Exploiting%20harmonic%20signature%20of%20gas%20vesicles%20in%20amplitude-modulated%20singular%20value%20decomposition%20for%20ultrafast%20ultrasound%20molecular%20imaging.%20%26lt%3Bi%26gt%3BPhys%20Med%20Biol%26lt%3B%5C%2Fi%26gt%3B%202026.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1088%5C%2F1361-6560%5C%2Fae35c7%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1088%5C%2F1361-6560%5C%2Fae35c7%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Exploiting%20harmonic%20signature%20of%20gas%20vesicles%20in%20amplitude-modulated%20singular%20value%20decomposition%20for%20ultrafast%20ultrasound%20molecular%20imaging%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ge%22%2C%22lastName%22%3A%22Zhang%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Henri%22%2C%22lastName%22%3A%22Leroy%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Nabil%22%2C%22lastName%22%3A%22Haidour%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Nicolas%22%2C%22lastName%22%3A%22Zucker%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Deyver%20Esteban%22%2C%22lastName%22%3A%22Rivera%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Anatole%22%2C%22lastName%22%3A%22Jimenez%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thomas%22%2C%22lastName%22%3A%22Deffieux%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Dina%22%2C%22lastName%22%3A%22Malounda%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Rohit%22%2C%22lastName%22%3A%22Nayak%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sophie%22%2C%22lastName%22%3A%22Pezet%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mathieu%22%2C%22lastName%22%3A%22Pernot%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mikhail%20G%22%2C%22lastName%22%3A%22Shapiro%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mickael%22%2C%22lastName%22%3A%22Tanter%22%7D%5D%2C%22abstractNote%22%3A%22Objective%3A%20Ultrafast%20nonlinear%20ultrasound%20imaging%20of%20gas%20vesicles%20%28GVs%29%20promises%20high-sensitivity%20biomolecular%20visualization%20for%20applications%20such%20as%20targeted%20molecular%20imaging%20and%20real-time%20tracking%20of%20gene%20expression.%20However%2C%20separating%20GV-specific%20signals%20from%20tissue%20remains%20challenging%20due%20to%20tissue%20clutter%20and%20limitations%20of%20current%20methods%2C%20which%20require%20complex%20transmit%20schemes%20and%20suffer%20from%20incomplete%20tissue%20suppression.%20This%20study%20aims%20to%20develop%20and%20validate%20harmonic%20amplitude-modulated%20singular%20value%20decomposition%20%28HAM-SVD%29%2C%20a%20novel%20technique%20that%20represents%20a%20shift%20from%20current%20GV%20imaging%20methods%20by%20exploiting%20the%20unique%20nonlinear%20pressure-dependence%20of%20the%20GV%20harmonic%20signature.%22%2C%22date%22%3A%222026-01-08%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1088%5C%2F1361-6560%5C%2Fae35c7%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fiopscience.iop.org%5C%2Farticle%5C%2F10.1088%5C%2F1361-6560%5C%2Fae35c7%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%220031-9155%2C%201361-6560%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%2294NJIV78%22%5D%2C%22dateModified%22%3A%222026-01-27T12%3A47%3A58Z%22%7D%7D%2C%7B%22key%22%3A%222BHE4WP4%22%2C%22library%22%3A%7B%22id%22%3A4989618%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Buffle%20et%20al.%22%2C%22parsedDate%22%3A%222026-01-01%22%2C%22numChildren%22%3A2%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BBuffle%20E%2C%20Leroy%20H%2C%20Caudoux%20M%2C%20Baranger%20J%2C%20Ait%20Ouaret%20R%2C%20Baron%20I%2C%20%26lt%3Bi%26gt%3Bet%20al.%26lt%3B%5C%2Fi%26gt%3B%20Evaluation%20of%20mitral%20regurgitation%20using%20ultrafast%20ultrasound%3A%20in%20vitro%20validation%20in%20a%20pulsatile%20flow%20phantom.%20%26lt%3Bi%26gt%3BEur%20Heart%20J%20Cardiovasc%20Imaging%26lt%3B%5C%2Fi%26gt%3B%202026%3B%26lt%3Bb%26gt%3B27%26lt%3B%5C%2Fb%26gt%3B%3Ajeaf367.003.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-ItemURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1093%5C%2Fehjci%5C%2Fjeaf367.003%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1093%5C%2Fehjci%5C%2Fjeaf367.003%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Evaluation%20of%20mitral%20regurgitation%20using%20ultrafast%20ultrasound%3A%20in%20vitro%20validation%20in%20a%20pulsatile%20flow%20phantom%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22E%22%2C%22lastName%22%3A%22Buffle%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22H%22%2C%22lastName%22%3A%22Leroy%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22M%22%2C%22lastName%22%3A%22Caudoux%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22J%22%2C%22lastName%22%3A%22Baranger%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22R%22%2C%22lastName%22%3A%22Ait%20Ouaret%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22I%22%2C%22lastName%22%3A%22Baron%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22G%22%2C%22lastName%22%3A%22Esclozas%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22M%22%2C%22lastName%22%3A%22Stucki%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22C%22%2C%22lastName%22%3A%22Papadacci%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22E%22%2C%22lastName%22%3A%22Messas%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22N%22%2C%22lastName%22%3A%22Karam%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22N%22%2C%22lastName%22%3A%22Aissaoui%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22E%22%2C%22lastName%22%3A%22Mousseaux%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22G%22%2C%22lastName%22%3A%22Soulat%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22M%22%2C%22lastName%22%3A%22Pernot%22%7D%5D%2C%22abstractNote%22%3A%22The%20regurgitant%20volume%20%28RVol%29%20is%20used%20to%20decide%20which%20patient%20with%20mitral%20valve%20regurgitation%20%28MR%29%20needs%20to%20be%20referred%20to%20invasive%20therapeutic%20procedure.%20It%20is%20currently%20computed%20with%20the%20proximal%20isovelocity%20surface%20area%20%28PISA%2C%20fig.%201a%29%20method%20which%20uses%20a%20single%20velocity%20value%20at%20the%20aliasing%20point%20%28fig.%201b%29.%20The%20RVol%20is%20then%20obtained%20by%20integrating%20all%20the%20PISA%20over%20time.%20This%20method%20used%20in%20the%20clinic%20with%20focused%20echocardiography%20is%20known%20to%20underestimate%20the%20RVol%20%5B1%5D.%20Ultrafast%20ultrasound%20color%20Doppler%20can%20map%20the%20flow%20field%20of%20interest%20at%20any%20point%20in%20the%20field%20of%20view%20with%20high%20temporal%20and%20spatial%20resolution.%20In%20this%20study%2C%20we%20investigated%20whether%20we%20can%20improve%20the%20precision%20of%20the%20RVol%20quantification%20with%20ultrafast%20ultrasound%20with%20respect%20to%20the%20clinical%20standard%20PISA%20method.In%20a%20left%20heart%20phantom%2C%20different%20physiological%20RVols%20were%20delivered%20by%20a%20pulsatile%20pump%20through%20a%20regurgitant%20orifice.%20Data%20were%20acquired%20at%206000%20frames%5C%2Fs%20by%20a%20conventional%20cardiac%20phased%20array%20probe%20%28central%20frequency%20at%202.75MHz%29%20emitting%20ultrafast%20diverging%20waves%2C%20connected%20to%20an%20ultrafast%20scanner.%20Power%20Doppler%20was%20first%20computed%20to%20select%20the%20area%20of%20the%20image%20with%20higher%20signal%20%28fig.%201c%29.%20Color%20Doppler%20mapping%20%28fig.%201d%29%20was%20computed%20over%20the%20systolic%20phase.%20A%20point%20on%20the%20central%20line%20in%20the%20axis%20of%20the%20orifice%20was%20selected%20in%20in%20the%20convergence%20zone%20were%20the%20mean%20velocity%20was%200.25m%5C%2Fs%20on%20average.%20On%20this%20point%2C%20RVols%20were%20computed%20as%20the%20surface%20integral%20of%20the%20velocity%20through%20a%20planar%20disk%20at%20the%20input%20of%20the%20orifice%20and%20was%20integrated%20over%20the%20systolic%20phase%20%28blue%20dotted%20line%2C%20fig.%201e%29%20and%20with%20the%20PISA%20method%20at%20this%20same%20point%20%28red%20point%20fig%201e%29.%20The%20accuracy%20of%20the%202%20methods%20were%20compared%20by%20computing%20the%20difference%20in%20their%20mean%20absolute%20value%20and%20percentage.RVol%20estimation%20using%20planar%20disk%20method%20yielded%20statistically%20significant%20lower%20absolute%20values%20than%20the%20clinical%20standard%20PISA%20method%20%289%5Cu00b18ml%20vs%2031%5Cu00b110%20ml%2C%20p%26lt%3B0.001%3B%2019%5Cu00b112%25%20vs%2073%5Cu00b111%25%2C%20p%26lt%3B0.001%29%20as%20depicted%20in%20fig.%202.In%20conclusion%2C%20we%20could%20demonstrate%20a%20more%20accurate%20method%20to%20calculate%20the%20RVol%20using%20the%20velocity%20field%20mapping%20of%20ultrafast%20ultrasound%20in%20a%20MR%20model.Figure%201%20%5Cu00a0FIgure%202%22%2C%22date%22%3A%222026-01-01%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1093%5C%2Fehjci%5C%2Fjeaf367.003%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1093%5C%2Fehjci%5C%2Fjeaf367.003%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222047-2412%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%2294NJIV78%22%5D%2C%22dateModified%22%3A%222026-02-09T15%3A14%3A26Z%22%7D%7D%2C%7B%22key%22%3A%224BDMZTNF%22%2C%22library%22%3A%7B%22id%22%3A4989618%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Reydet%20et%20al.%22%2C%22parsedDate%22%3A%222026-01-01%22%2C%22numChildren%22%3A2%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BReydet%20J%2C%20Favre%20H%2C%20Dizeux%20A%2C%20Haidour%20N%2C%20Pernot%20M%2C%20Tanter%20M%2C%20%26lt%3Bi%26gt%3Bet%20al.%26lt%3B%5C%2Fi%26gt%3B%20Human%20brain%20hemodynamics%20for%203D%20ultrasound%20localization%20microscopy%20benchmarking.%20%26lt%3Bi%26gt%3BComputers%20in%20Biology%20and%20Medicine%26lt%3B%5C%2Fi%26gt%3B%202026%3B%26lt%3Bb%26gt%3B200%26lt%3B%5C%2Fb%26gt%3B%3A111370.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.compbiomed.2025.111370%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.compbiomed.2025.111370%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Human%20brain%20hemodynamics%20for%203D%20ultrasound%20localization%20microscopy%20benchmarking%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Juliette%22%2C%22lastName%22%3A%22Reydet%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hugues%22%2C%22lastName%22%3A%22Favre%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexandre%22%2C%22lastName%22%3A%22Dizeux%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Nabil%22%2C%22lastName%22%3A%22Haidour%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mathieu%22%2C%22lastName%22%3A%22Pernot%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mickael%22%2C%22lastName%22%3A%22Tanter%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Cl%5Cu00e9ment%22%2C%22lastName%22%3A%22Papadacci%22%7D%5D%2C%22abstractNote%22%3A%22Ultrasound%20Localization%20Microscopy%20%28ULM%29%20has%20emerged%20as%20a%20promising%20technique%20for%20imaging%20microvascular%20networks%20at%20subwavelength%20resolution.%20However%2C%20its%203D%20translation%20in%20clinics%20for%20complex%20organs%20like%20the%20brain%20remains%20limited%20due%20to%20technological%20and%20experimental%20challenges%2C%20including%20probe%20design%20constraints%2C%20motions%20artifacts%2C%20and%20both%20acoustic%20attenuation%20and%20aberrations%20caused%20by%20the%20skull.%20In%20this%20study%2C%20we%20present%20a%20fast%20and%20versatile%20simulation%20framework%20for%203D%20ULM%20based%20on%20a%20realistic%20human%20brain%20vasculature%20model%20that%20includes%20small%20vessels%20down%20to%20the%20precapillary%20scale%2C%20along%20with%20its%20hemodynamics%20driven%20by%20conservation%20and%20Murray%26%23039%3Bs%20law.%20This%20novel%20framework%20enables%20comparison%20of%20ultrasound%20probe%20configurations%2C%20ULM%20algorithm%20performance%2C%20and%20experimental%20parameters%20such%20as%20microbubble%20%28MB%29%20concentration%2C%20subpixel%20motion%2C%20and%20skull-induced%20aberrations%20in%20transcranial%20imaging%20conditions.%20To%20illustrate%20a%20range%20of%20case%20scenarios%2C%20three%20matrix%20array%20probes%20were%20evaluated%20including%20a%20matrix%20probe%20with%20large%20elements%20combined%20with%20diverging%20lenses.%20We%20evaluated%20localization%20accuracy%2C%20tracking%20performance%2C%20velocity%20distribution%20and%20the%20extent%20of%20the%20field%20of%20view.%20As%20expected%2C%20the%20simulations%20also%20highlighted%20the%20negative%20impact%20of%20high%20MB%20concentration%20and%20motions%20artifacts%20on%20detection%20performance%2C%20as%20well%20as%20the%20significant%20effect%20of%20skull-induced%20aberrations.%20The%20proposed%20framework%20provides%20a%20robust%20interface%20for%20developing%2C%20testing%20and%20optimizing%203D%20ULM%20systems%2C%20with%20potential%20applications%20extending%20to%20other%20organs%20and%20clinical%20scenarios.%22%2C%22date%22%3A%222026-01-01%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.compbiomed.2025.111370%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.sciencedirect.com%5C%2Fscience%5C%2Farticle%5C%2Fpii%5C%2FS001048252501724X%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%220010-4825%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%2294NJIV78%22%5D%2C%22dateModified%22%3A%222025-12-08T08%3A39%3A52Z%22%7D%7D%2C%7B%22key%22%3A%22HUJMR8XH%22%2C%22library%22%3A%7B%22id%22%3A4989618%7D%2C%22meta%22%3A%7B%22lastModifiedByUser%22%3A%7B%22id%22%3A804678%2C%22username%22%3A%22j%5Cu00e9r%5Cu00f4me%20baranger%22%2C%22name%22%3A%22%22%2C%22links%22%3A%7B%22alternate%22%3A%7B%22href%22%3A%22https%3A%5C%2F%5C%2Fwww.zotero.org%5C%2Fjrme_baranger%22%2C%22type%22%3A%22text%5C%2Fhtml%22%7D%7D%7D%2C%22creatorSummary%22%3A%22Meki%20et%20al.%22%2C%22parsedDate%22%3A%222025-11-06%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BMeki%20T%2C%20Pedreira%20O%2C%20Reydet%20J%2C%20Dizeux%20A%2C%20Papadacci%20C%2C%20Pernot%20M.%20In-vivo%20muscle%20characterization%20by%203D%20Elastic%20and%20Backscatter%20Tensor%20Imaging%20using%20a%20low%20channel%20count%20system.%20%26lt%3Bi%26gt%3BIEEE%20Trans%20Biomed%20Eng%26lt%3B%5C%2Fi%26gt%3B%202025%3B%26lt%3Bb%26gt%3BPP%26lt%3B%5C%2Fb%26gt%3B%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1109%5C%2FTBME.2025.3630001%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1109%5C%2FTBME.2025.3630001%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22In-vivo%20muscle%20characterization%20by%203D%20Elastic%20and%20Backscatter%20Tensor%20Imaging%20using%20a%20low%20channel%20count%20system%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Touka%22%2C%22lastName%22%3A%22Meki%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Olivier%22%2C%22lastName%22%3A%22Pedreira%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Juliette%22%2C%22lastName%22%3A%22Reydet%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexandre%22%2C%22lastName%22%3A%22Dizeux%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Clement%22%2C%22lastName%22%3A%22Papadacci%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mathieu%22%2C%22lastName%22%3A%22Pernot%22%7D%5D%2C%22abstractNote%22%3A%22Over%20the%20last%20decade%2C%203D%20ultrafast%20ultrasound%20imaging%20has%20been%20used%20in%20different%20applications%20including%20Elastic%20Tensor%20Imaging%20%28ETI%29%20based%20on%203D%20Shear%20Wave%20Elastography%20and%20Backscatter%20Tensor%20Imaging%20%28BTI%29.%20BTI%20and%20ETI%20can%20provide%20important%20biomechanical%20and%20structural%20parameters%20of%20fibrous%20soft%20tissues%20such%20as%20the%20skeletal%20muscles%20or%20the%20myocardium.%20However%2C%203D%20ultrafast%20imaging%20requires%202D%20transducers%20arrays%20with%20a%20large%20number%20of%20elements%2C%20which%20mainly%20limits%20their%20use%20to%20laboratory%20research%20settings.%20This%20study%20aims%20to%20develop%20a%20clinically%20transposable%20ultrasound%20system%20combining%203D-ETI%20and%20BTI%20to%20characterize%20anisotropic%20tissues.%20A%20low%20channel%20count%20system%20with%20128%20channels%20based%20on%20a%20vantage%20system%20and%20a%20dedicated%20matrix%20transducer%20driven%20at%202.5MHz%20was%20developed.%20The%20performance%20of%20the%20approach%20was%20demonstrated%20on%20anisotropic%20and%20fibrous%20phantoms.%20In-vivo%20feasibility%20was%20performed%20on%20the%20brachii%20biceps%20of%204%20healthy%20volunteers%20at%20controlled%20contractions%20levels%20using%20weights%20held%20in%20the%20hand.%20Using%20this%20approach%2C%20we%20could%20investigate%20the%20functional%20change%20of%20muscle%20stiffness%20during%20contraction%20%28shear%20wave%20speed%20from%203.2%5Cu00b10.20m%5C%2Fs%20to%206.6%5Cu00b10.58m%5C%2Fs%2C%20and%20elastic%20fractional%20anisotropy%20from%200.26%5Cu00b10.04%20to%200.49%5Cu00b10.07%29.%20Structural%20characterization%20was%20performed%20with%20BTI%2C%20fiber%20organization%20and%20coherence%20fractional%20anisotropy%20remained%20constant%20with%20contraction%20%280.27%5Cu00b10.05%29.%20This%20novel%20device%20enables%20non-invasive%20characterization%20of%20anisotropic%20tissues%2C%20discerning%20stress%20and%20structural%20anisotropy%20in%20promising%20applications%20in%20musculoskeletal%20and%20myocardial%20pathologies.%22%2C%22date%22%3A%222025-11-06%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1109%5C%2FTBME.2025.3630001%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22%22%2C%22PMID%22%3A%2241196779%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%221558-2531%22%2C%22language%22%3A%22eng%22%2C%22collections%22%3A%5B%2294NJIV78%22%5D%2C%22dateModified%22%3A%222025-11-20T10%3A32%3A37Z%22%7D%7D%2C%7B%22key%22%3A%22WJMX8TJS%22%2C%22library%22%3A%7B%22id%22%3A4989618%7D%2C%22meta%22%3A%7B%22lastModifiedByUser%22%3A%7B%22id%22%3A804678%2C%22username%22%3A%22j%5Cu00e9r%5Cu00f4me%20baranger%22%2C%22name%22%3A%22%22%2C%22links%22%3A%7B%22alternate%22%3A%7B%22href%22%3A%22https%3A%5C%2F%5C%2Fwww.zotero.org%5C%2Fjrme_baranger%22%2C%22type%22%3A%22text%5C%2Fhtml%22%7D%7D%7D%2C%22creatorSummary%22%3A%22Haidour%20et%20al.%22%2C%22parsedDate%22%3A%222025-10-28%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BHaidour%20N%2C%20Favre%20H%2C%20Mateo%20P%2C%20Reydet%20J%2C%20Biz%26%23xE9%3B%20A%2C%20Sambin%20L%2C%20%26lt%3Bi%26gt%3Bet%20al.%26lt%3B%5C%2Fi%26gt%3B%20Multi-lens%20ultrasound%20arrays%20enable%20large%20scale%20three-dimensional%20micro-vascularization%20characterization%20over%20whole%20organs.%20%26lt%3Bi%26gt%3BNat%20Commun%26lt%3B%5C%2Fi%26gt%3B%202025%3B%26lt%3Bb%26gt%3B16%26lt%3B%5C%2Fb%26gt%3B%3A9317.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1038%5C%2Fs41467-025-64911-z%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1038%5C%2Fs41467-025-64911-z%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Multi-lens%20ultrasound%20arrays%20enable%20large%20scale%20three-dimensional%20micro-vascularization%20characterization%20over%20whole%20organs%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Nabil%22%2C%22lastName%22%3A%22Haidour%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hugues%22%2C%22lastName%22%3A%22Favre%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Philippe%22%2C%22lastName%22%3A%22Mateo%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Juliette%22%2C%22lastName%22%3A%22Reydet%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alain%22%2C%22lastName%22%3A%22Biz%5Cu00e9%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lucien%22%2C%22lastName%22%3A%22Sambin%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jianping%22%2C%22lastName%22%3A%22Dai%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Paul-Matthieu%22%2C%22lastName%22%3A%22Chiaroni%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Bijan%22%2C%22lastName%22%3A%22Ghaleh%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mathieu%22%2C%22lastName%22%3A%22Pernot%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mickael%22%2C%22lastName%22%3A%22Tanter%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Clement%22%2C%22lastName%22%3A%22Papadacci%22%7D%5D%2C%22abstractNote%22%3A%22Mapping%20microcirculation%20at%20the%20whole-organ%20scale%20in%203D%20is%20crucial%20for%20understanding%20vascular%20pathologies%20and%20improving%20diagnostics.%20Although%203D%20ultrasound%20localization%20microscopy%20%28ULM%29%20enables%20microscopic%20resolution%20by%20localizing%20intravenously%20injected%20microbubbles%20in%20small%20animal%20models%2C%20visualizing%20entire%20organs%20in%20large%20animals%20or%20humans%20remains%20challenging%20due%20to%20limited%20field%20of%20view%2C%20low%20sensitivity%2C%20and%20probe%20technological%20complexity.%20Here%2C%20we%20demonstrate%20how%20a%20multi-lens%20array%20method%20overcomes%20these%20limitations.%20Combined%20with%203D%20ULM%2C%20it%20maps%20and%20quantifies%20large%20vascular%20volumes%20%28up%20to%20120%20%5Cu00d7%20100%20%5Cu00d7%2082%5Cu2009mm%5Cu00b3%29%20at%20high%20spatial%20resolution%20%28125%5Cu2013200%5Cu2009%5Cu00b5m%29%20with%20a%20volumetric%20acquisition%20rate%20of%20312%5Cu2009Hz%2C%20using%20low-cost%20technology.%20This%20approach%20enables%20deeper%20insights%20into%20hemodynamics%20from%20large%20vessels%20to%20pre-capillary%20arterioles%2C%20by%20providing%20vast%20and%20rich%20datasets%20of%20whole-organ%20vascularization.%20It%20could%20also%20facilitate%20diagnosis%20of%20microcirculation%20disorders%20and%20monitoring%20of%20small-vessel%20disease%20treatments%20by%20addressing%20key%20limitations%20of%20current%20imaging%20modalities.%22%2C%22date%22%3A%222025-10-28%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1038%5C%2Fs41467-025-64911-z%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.nature.com%5C%2Farticles%5C%2Fs41467-025-64911-z%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222041-1723%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%2294NJIV78%22%5D%2C%22dateModified%22%3A%222025-11-04T15%3A34%3A34Z%22%7D%7D%2C%7B%22key%22%3A%22XWUX4B3D%22%2C%22library%22%3A%7B%22id%22%3A4989618%7D%2C%22meta%22%3A%7B%22lastModifiedByUser%22%3A%7B%22id%22%3A111638%2C%22username%22%3A%22tdeffieux%22%2C%22name%22%3A%22%22%2C%22links%22%3A%7B%22alternate%22%3A%7B%22href%22%3A%22https%3A%5C%2F%5C%2Fwww.zotero.org%5C%2Ftdeffieux%22%2C%22type%22%3A%22text%5C%2Fhtml%22%7D%7D%7D%2C%22creatorSummary%22%3A%22Venet%20et%20al.%22%2C%22parsedDate%22%3A%222025-06-01%22%2C%22numChildren%22%3A3%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BVenet%20M%2C%20Baranger%20J%2C%20Malik%20A%2C%20Nguyen%20MB%2C%20Mital%20S%2C%20Friedberg%20MK%2C%20%26lt%3Bi%26gt%3Bet%20al.%26lt%3B%5C%2Fi%26gt%3B%20Towards%20non-invasive%20assessment%20of%20myocardial%20work%20using%20myocardial%20stiffness%20and%20strain%3A%20a%20human%20pilot%20study.%20%26lt%3Bi%26gt%3BEur%20Heart%20J%20Cardiovasc%20Imaging%26lt%3B%5C%2Fi%26gt%3B%202025%3B%26lt%3Bb%26gt%3B26%26lt%3B%5C%2Fb%26gt%3B%3A1051%26%23x2013%3B64.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-ItemURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1093%5C%2Fehjci%5C%2Fjeaf089%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1093%5C%2Fehjci%5C%2Fjeaf089%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Towards%20non-invasive%20assessment%20of%20myocardial%20work%20using%20myocardial%20stiffness%20and%20strain%3A%20a%20human%20pilot%20study%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maelys%22%2C%22lastName%22%3A%22Venet%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jerome%22%2C%22lastName%22%3A%22Baranger%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Aimen%22%2C%22lastName%22%3A%22Malik%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Minh%20B%22%2C%22lastName%22%3A%22Nguyen%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Seema%22%2C%22lastName%22%3A%22Mital%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mark%20K%22%2C%22lastName%22%3A%22Friedberg%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mathieu%22%2C%22lastName%22%3A%22Pernot%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Clement%22%2C%22lastName%22%3A%22Papadacci%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sebastien%22%2C%22lastName%22%3A%22Salles%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Rajiv%22%2C%22lastName%22%3A%22Chaturvedi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Luc%22%2C%22lastName%22%3A%22Mertens%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Olivier%22%2C%22lastName%22%3A%22Villemain%22%7D%5D%2C%22abstractNote%22%3A%22Myocardial%20work%20assessment%20has%20emerged%20as%20a%20promising%20tool%20for%20left%20ventricular%20%28LV%29%20performance%20evaluation.%20Existing%20non-invasive%20methods%20for%20assessing%20it%20rely%20on%20assumptions%20on%20LV%20pressure%20and%20geometry.%20Recently%2C%20shear%20wave%20elastography%20allowed%20to%20quantify%20changes%20in%20myocardial%20stiffness%20throughout%20the%20cardiac%20cycle.%20Based%20on%20Hooke%5Cu2019s%20law%2C%20it%20becomes%20theoretically%20possible%20to%20calculate%20myocardial%20stress%20and%20work%20from%20myocardial%20stiffness%20and%20strain%20measurements.%20The%20main%20objective%20of%20this%20study%20is%20to%20demonstrate%20the%20feasibility%20of%20this%20comprehensive%20ultrasound%20approach%20and%20to%20compare%20myocardial%20work%20values%20between%20populations%20where%20variations%20are%20anticipated.Children%20with%20hypertrophic%20cardiomyopathy%20%28HCM%29%2C%20aortic%20stenosis%20%28AS%29%20and%20healthy%20volunteers%20%28HV%29%20were%20included%20in%20this%20study.%20Segment%20dimensions%2C%20strain%2C%20thickness%2C%20and%20segmental%20myocardial%20stiffness%20were%20assessed%20in%20the%20basal%20antero-septal%20segment%20throughout%20the%20cardiac%20cycle.%20One-beat%20segmental%20work%2C%20the%20stress%5Cu2013strain%20loop%20area%2C%20and%20contributive%20and%20dissipative%20work%20were%20compared%20between%20groups.%20Twenty%20HV%20%289.8%20%5Cu00b1%205.3%20years%20of%20age%29%2C%2020%20HCM%20%2810.0%20%5Cu00b1%206.1%20years%20of%20age%29%2C%20and%205%20AS%20%285.3%20%5Cu00b1%204.3%20years%20of%20age%29%20subjects%20were%20included.%20One-beat%20segmental%20work%20was%20significantly%20higher%20in%20AS%20%28272.0%20%5Cu00b1%20102.9%20%5Cu00b5J%5C%2Fmm%29%20and%20lower%20in%20HCM%20%2838.2%20%5Cu00b1%20106.9%20%5Cu00b5J%5C%2Fmm%29%20compared%20with%20HV%20%28131.1%20%5Cu00b1%2083.3%20%5Cu00b5J%5C%2Fmm%29%2C%20P%20%3D%200.02%20and%20P%20%3D%200.01%2C%20respectively.%20Desynchronized%20work%20was%20prevailing%20in%20HCM%20with%20dissipative%20work%20during%20systole%20measured%20at%2017.3%20%5Cu00b1%2028.9%20%5Cu00b5J%5C%2Fmm%20and%20contributive%20work%20during%20diastole%20measured%20at%2015.3%20%5Cu00b1%2018.0%20%5Cu00b5J%5C%2Fmm.%20The%20stress%5Cu2013strain%20loop%20area%20was%20higher%20in%20AS%20%2895.2%20%5Cu00b1%2031.1%20kPa%25%29%20and%20HV%20%2866.2%20%5Cu00b1%2035.9%20kPa%25%29%20than%20in%20HCM%20%285.8%20%5Cu00b1%2013.0%20kPa%25%29%2C%20P%20%26lt%3B%200.01.Calculating%20segmental%20myocardial%20work%20based%20on%20myocardial%20stiffness%20and%20strain%20measurements%20is%20technically%20feasible.%20This%20approach%20overcomes%20the%20inherent%20limitations%20of%20current%20methods%20by%20introducing%20a%20direct%20quantitative%20measure%20of%20myocardial%20stress.%22%2C%22date%22%3A%222025-06-01%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1093%5C%2Fehjci%5C%2Fjeaf089%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1093%5C%2Fehjci%5C%2Fjeaf089%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222047-2412%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%2294NJIV78%22%5D%2C%22dateModified%22%3A%222025-11-20T10%3A32%3A38Z%22%7D%7D%5D%7D
1
Zhang G, Leroy H, Haidour N, Zucker N, Rivera DE, Jimenez A, et al. Exploiting harmonic signature of gas vesicles in amplitude-modulated singular value decomposition for ultrafast ultrasound molecular imaging. Phys Med Biol 2026. https://doi.org/10.1088/1361-6560/ae35c7.
1
Buffle E, Leroy H, Caudoux M, Baranger J, Ait Ouaret R, Baron I, et al. Evaluation of mitral regurgitation using ultrafast ultrasound: in vitro validation in a pulsatile flow phantom. Eur Heart J Cardiovasc Imaging 2026;27:jeaf367.003. https://doi.org/10.1093/ehjci/jeaf367.003.
1
Reydet J, Favre H, Dizeux A, Haidour N, Pernot M, Tanter M, et al. Human brain hemodynamics for 3D ultrasound localization microscopy benchmarking. Computers in Biology and Medicine 2026;200:111370. https://doi.org/10.1016/j.compbiomed.2025.111370.
1
Meki T, Pedreira O, Reydet J, Dizeux A, Papadacci C, Pernot M. In-vivo muscle characterization by 3D Elastic and Backscatter Tensor Imaging using a low channel count system. IEEE Trans Biomed Eng 2025;PP: https://doi.org/10.1109/TBME.2025.3630001.
1
Haidour N, Favre H, Mateo P, Reydet J, Bizé A, Sambin L, et al. Multi-lens ultrasound arrays enable large scale three-dimensional micro-vascularization characterization over whole organs. Nat Commun 2025;16:9317. https://doi.org/10.1038/s41467-025-64911-z.
1
Venet M, Baranger J, Malik A, Nguyen MB, Mital S, Friedberg MK, et al. Towards non-invasive assessment of myocardial work using myocardial stiffness and strain: a human pilot study. Eur Heart J Cardiovasc Imaging 2025;26:1051–64. https://doi.org/10.1093/ehjci/jeaf089.
Nov 21, 2022 | |
Previous

Tanter Mickael
Next

Aubry Jean-François