{"doi":"10.1109/tbme.2023.3260735","title":"Needle Aligned Ultrasound Image-Guided Access Through Dual-Segment Array","abstract":"Ultrasound (US) guided access for percutaneous nephrolithotomy (PCNL) is gaining popularity in the urology community as it reduces radiation risk. The most popular technique involves manual image-needle alignment. A misaligned needle however needs to be retracted and reinserted, resulting in a lengthened operation time and complications such as bleeding. These limitations can be mitigated through the co-registration between the US array and needle. The through-hole array concept provides the primary solution, including a hole at the center of the array. Because of the central opening, the image-needle alignment is achieved inherently. Previous literature has described applications that are limited to superficial and intravascular procedures, suggesting that developing a through-hole array for deeper target applications would be a new breakthrough. OBJECTIVE: Here, we present a dual-segment array with a central opening. As the prototype development, two segments of 32-element arrays are combined with an open space of 10 mm in length in between them. METHOD: We conducted phantom and ex-vivo studies considering the target depth of the 80-100 mm range. The image quality and needle visibility are evaluated by comparing the signal-to-noise ratio (SNR), full width at half maximum (FWHM), and contrast-to-noise ratio (CNR) results measured with a no-hole linear array under equivalent conditions. An ex-vivo study is performed using porcine kidneys with ceramic balls embedded to evaluate the needle access accuracy. RESULTS AND CONCLUSION: The mean needle access error of 20 trials is found to be 2.94 ±1.09 mm, suggesting its potential impact on realizing a simple and intuitive deep US image-guided access.","journal":"IEEE Transactions on Biomedical Engineering","year":2023,"id":381687,"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":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9535,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":735185,"name":"Yichuan Tang","orcid":"0000-0003-1681-5944","position":1,"is_corresponding":false},{"id":575756,"name":"Shang Gao","orcid":"0000-0001-9921-7899","position":2,"is_corresponding":false},{"id":804248,"name":"Xihan Ma","orcid":"0000-0003-1007-0910","position":3,"is_corresponding":false},{"id":1147654,"name":"Igor Sorokin","orcid":"0000-0001-5472-9807","position":4,"is_corresponding":false},{"id":377269,"name":"Haichong K. Zhang","orcid":"0000-0002-1314-8456","position":5,"is_corresponding":false},{"id":889208,"name":"Ashiqur Rahaman","orcid":"0000-0002-4724-2205","position":0,"is_corresponding":true}],"reference_count":43,"raw_metadata":null,"created_at":"2026-07-19T01:17:12.933204Z","pmid":"37030673","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":[]}