{"doi":"10.34133/2022/9891510","title":"High-Frequency 3D Photoacoustic Computed Tomography Using an Optical Microring Resonator","abstract":"3D photoacoustic computed tomography (3D-PACT) has made great advances in volumetric imaging of biological tissues, with high spatial-temporal resolutions and large penetration depth. The development of 3D-PACT requires high-performance acoustic sensors with a small size, large detection bandwidth, and high sensitivity. In this work, we present a new high-frequency 3D-PACT system that uses a microring resonator (MRR) as the acoustic sensor. The MRR sensor has a size of 80 μ m in diameter and was fabricated using the nanoimprint lithography technology. Using the MRR sensor, we have developed a transmission-mode 3D-PACT system that has achieved a detection bandwidth of ~23 MHz, an imaging depth of ~8 mm, a lateral resolution of 114 μ m, and an axial resolution of 57 μ m. We have demonstrated the 3D PACT’s performance on in vitro phantoms, ex vivo mouse brain, and in vivo mouse ear and tadpole. The MRR-based 3D-PACT system can be a promising tool for structural, functional, and molecular imaging of biological tissues at depths.","journal":"BME Frontiers","year":2022,"id":250664,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":26,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.958,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":892886,"name":"Youngseop Lee","orcid":"0000-0002-8879-142X","position":1,"is_corresponding":false},{"id":568515,"name":"Yuqi Tang","orcid":"0000-0003-0419-5004","position":2,"is_corresponding":false},{"id":257429,"name":"Tri Vu","orcid":"0000-0002-1384-8647","position":3,"is_corresponding":false},{"id":863225,"name":"Carlos Taboada","orcid":"0000-0002-7074-1897","position":4,"is_corresponding":false},{"id":892887,"name":"Wenhan Zheng","orcid":"0000-0003-3639-5158","position":5,"is_corresponding":false},{"id":368412,"name":"Jun Xia","orcid":"0000-0002-9864-7835","position":6,"is_corresponding":false},{"id":892888,"name":"David A. Czaplewski","orcid":"0000-0003-2262-0908","position":7,"is_corresponding":false},{"id":409028,"name":"Hao F. Zhang","orcid":"0000-0001-5089-1196","position":8,"is_corresponding":false},{"id":456664,"name":"Cheng Sun","orcid":"0000-0002-2744-0896","position":9,"is_corresponding":false},{"id":257434,"name":"Junjie Yao","orcid":"0000-0002-2381-706X","position":10,"is_corresponding":false},{"id":892885,"name":"Qiangzhou Rong","orcid":"0000-0003-0325-6864","position":0,"is_corresponding":true}],"reference_count":46,"raw_metadata":null,"created_at":"2026-07-19T00:24:32.960657Z","pmid":"36818003","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}