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• W4313648921 endingPage "110689" @default.
• W4313648921 startingPage "110689" @default.
• W4313648921 abstract "This study aimed to identify regions with at least 20% tumor cell content in lung cancer tumors by using spectral parameters from dual-layer spectral detector computed tomography (SDCT) to design the puncture path for transthoracic lung biopsy (TTLB).This prospective study recruited patients with suspected lung cancer. Forty-one patients were enrolled to identify the high tumor cell proportion region (HTPR) and then another 15 patients to validate the accuracy of the HTPR. In each of the 41 patients, the suspected regions with high or low tumor cell proportions were punctured according to local iodine density (IoD) values for separate biopsies. The tumor cell proportions of 82 specimens were assessed and classified into high and low tumor cell proportions based on the threshold value of 20 %. The performance of spectral parameters was analyzed to distinguish the HTPR (tumor cell proportion ≥ 20 %) from the low tumor cell proportion region (LTPR). The cutoff value of optimal spectral parameter was used to prospectively guide the biopsy of the HTPR in 15 cases for further validation, and then the accuracy was calculated.The AUC values of spectral parameters were all higher than those of CTconventional in identifying the HTPR (all P < 0.05). The IoD with a cutoff value of 0.59 mg/mL in arterial phase (AP) yielded good performance (specificity: 97.10 %) in identifying the HTPR. It was applied to 15 cases for validation, and the accuracy rate was 100 %.Spectral CT parameters can be used to identify regions with at least 20% tumor cell content in lung cancer for biopsies." @default.
• W4313648921 created "2023-01-07" @default.
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• W4313648921 date "2023-03-01" @default.
• W4313648921 modified "2023-10-13" @default.
• W4313648921 title "Role of iodine density value on dual-energy CT for detection of high tumor cell proportion region in lung cancer during CT-guided transthoracic biopsy" @default.
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• W4313648921 doi "https://doi.org/10.1016/j.ejrad.2023.110689" @default.
• W4313648921 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36669332" @default.
• W4313648921 hasPublicationYear "2023" @default.
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