Nanodroplet-Based Super-Resolution Ultrasound Localization Microscopy.

activation diagnosis microbubbles nanodroplets recondensation super-resolution therapy ultrasound imaging ultrasound localization microscopy

Journal

ACS sensors
ISSN: 2379-3694
Titre abrégé: ACS Sens
Pays: United States
ID NLM: 101669031

Informations de publication

Date de publication:
22 09 2023
Historique:
medline: 25 9 2023
pubmed: 22 8 2023
entrez: 22 8 2023
Statut: ppublish

Résumé

Over the past decade, super-resolution ultrasound localization microscopy (SR-ULM) has revolutionized ultrasound imaging with its capability to resolve the microvascular structures below the ultrasound diffraction limit. The introduction of this imaging technique enables the visualization, quantification, and characterization of tissue microvasculature. The early implementations of SR-ULM utilize microbubbles (MBs) that require a long image acquisition time due to the requirement of capturing sparsely isolated microbubble signals. The next-generation SR-ULM employs nanodroplets that have the potential to significantly reduce the image acquisition time without sacrificing the resolution. This review discusses various nanodroplet-based ultrasound localization microscopy techniques and their corresponding imaging mechanisms. A summary is given on the preclinical applications of SR-ULM with nanodroplets, and the challenges in the clinical translation of nanodroplet-based SR-ULM are presented while discussing the future perspectives. In conclusion, ultrasound localization microscopy is a promising microvasculature imaging technology that can provide new diagnostic and prognostic information for a wide range of pathologies, such as cancer, heart conditions, and autoimmune diseases, and enable personalized treatment monitoring at a microlevel.

Identifiants

pubmed: 37607403
doi: 10.1021/acssensors.3c00418
doi:

Types de publication

Journal Article Review Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3294-3306

Auteurs

Ge Zhang (G)

Department of Medical Ultrasound, China Resources & Wisco General Hospital, Wuhan University of Science and Technology, Wuhan 430080, People's Republic of China.
Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Wuhan University of Science and Technology, Wuhan 430065, People's Republic of China.
Physics for Medicine Paris, Inserm U1273, ESPCI Paris, PSL University, CNRS, Paris 75015, France.

Chen Liao (C)

Department of Medical Ultrasound, China Resources & Wisco General Hospital, Wuhan University of Science and Technology, Wuhan 430080, People's Republic of China.
Medical College, Wuhan University of Science and Technology, Wuhan 430065, People's Republic of China.

Jun-Rui Hu (JR)

Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, People's Republic of China.

Hai-Man Hu (HM)

Department of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, People's Republic of China.

Yu-Meng Lei (YM)

Department of Medical Ultrasound, China Resources & Wisco General Hospital, Wuhan University of Science and Technology, Wuhan 430080, People's Republic of China.

Sevan Harput (S)

Department of Electrical and Electronic Engineering, London South Bank University, London SE1 0AA, U.K.

Hua-Rong Ye (HR)

Department of Medical Ultrasound, China Resources & Wisco General Hospital, Wuhan University of Science and Technology, Wuhan 430080, People's Republic of China.

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Classifications MeSH