{"doi":"10.2967/jnumed.123.265686","title":"Ambient Light Resistant Shortwave Infrared Fluorescence Imaging for Preclinical Tumor Delineation via the pH Low-Insertion Peptide Conjugated to Indocyanine Green","abstract":"Shortwave infrared (900–1,700 nm) fluorescence imaging (SWIRFI) has shown significant advantages over visible (400–650 nm) and near-infrared (700–900 nm) fluorescence imaging (reduced autofluorescence, improved contrast, tissue resolution, and depth sensitivity). However, there is a major lag in the clinical translation of preclinical SWIRFI systems and targeted SWIRFI probes. <b>Methods:</b> We preclinically show that the pH low-insertion peptide conjugated to indocyanine green (pHLIP ICG), currently in clinical trials, is an excellent candidate for cancer-targeted SWIRFI. <b>Results:</b> pHLIP ICG SWIRFI achieved picomolar sensitivity (0.4 nM) with binary and unambiguous tumor screening and resection up to 96 h after injection in an orthotopic breast cancer mouse model. SWIRFI tumor screening and resection had ambient light resistance (possible without gating or filtering) with outstanding signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) values at exposures from 10 to 0.1 ms. These SNR and CNR values were also found for the extended emission of pHLIP ICG in&nbsp;vivo (&gt;1,100 nm, 300 ms). <b>Conclusion:</b> SWIRFI sensitivity and ambient light resistance enabled continued tracer clearance tracking with unparalleled SNR and CNR values at video rates for tumor delineation (achieving a tumor-to-muscle ratio above 20). In total, we provide a direct precedent for the democratic translation of an ambient light resistant SWIRFI and pHLIP ICG ecosystem, which can instantly improve tumor resection.","journal":"Journal of Nuclear Medicine","year":2023,"id":364403,"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":7,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9575,"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":296334,"name":"Mijin Kim","orcid":"0000-0002-7781-9466","position":1,"is_corresponding":false},{"id":408501,"name":"Sheryl Roberts","orcid":"0000-0002-2326-9120","position":2,"is_corresponding":false},{"id":724488,"name":"Magdalena Skubal","orcid":"0000-0003-3446-5415","position":3,"is_corresponding":false},{"id":287003,"name":"Hsiao‐Ting Hsu","orcid":null,"position":4,"is_corresponding":false},{"id":908095,"name":"Anuja Ogirala","orcid":"0009-0005-1852-806X","position":5,"is_corresponding":false},{"id":383725,"name":"Edwin C. Pratt","orcid":"0000-0002-6054-6983","position":6,"is_corresponding":false},{"id":291557,"name":"Nagavarakishore Pillarsetty","orcid":"0000-0002-1750-7436","position":7,"is_corresponding":false},{"id":228781,"name":"Daniel A. Heller","orcid":"0000-0002-6866-0000","position":8,"is_corresponding":false},{"id":235762,"name":"Jason S. Lewis","orcid":"0000-0001-7065-4534","position":9,"is_corresponding":false},{"id":383728,"name":"Jan Grimm","orcid":"0000-0002-5282-9385","position":10,"is_corresponding":false},{"id":724487,"name":"Benedict Mc Larney","orcid":"0000-0002-6165-7431","position":0,"is_corresponding":true}],"reference_count":46,"raw_metadata":null,"created_at":"2026-07-19T01:14:36.728255Z","pmid":"37620049","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":[]}