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Using complementing PET\/CT parameters, a composite model was developed. A receiver operating characteristic (ROC) analysis assessed the combined model and each independent parameter's differential diagnostic efficacies. Furthermore, this study investigated the improvement in diagnostic efficacy using other metrics, such as integrated discriminatory improvement (IDI) and net reclassification improvement (NRI).<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>The highest discriminative diagnostic value was obtained by the independent parameters energy (1,039,358.1 [95126.2\u20131,965,032.2] vs. 92,011.0 [45916.3\u2013365,322.9], <jats:italic>P<\/jats:italic>\u2009=\u20090.001). In comparison to peak standardized uptake value (SUVpeak), total lesion glycolysis (TLG), energy, lobulation, and spiculation alone, the combined model (addition of these factors) significantly improved the differential diagnostic efficacy of SPLCs and PMs (sensitivity\u2009=\u200976.2%, specificity\u2009=\u200983.8%, area under the curve [AUC]\u2009=\u20090.826) and permitted reclassification using IDI\u2009=\u20090.176 (<jats:italic>P<\/jats:italic>\u2009&lt;\u20090.001), 0.169 (<jats:italic>P<\/jats:italic>\u2009&lt;\u20090.001), 0.127 (<jats:italic>P<\/jats:italic>\u2009&lt;\u20090.001), and categorical NRI\u2009=\u20090.678 (<jats:italic>P<\/jats:italic>\u2009&lt;\u20090.001), 0.637 (<jats:italic>P<\/jats:italic>\u2009&lt;\u20090.001), and 0.592 (<jats:italic>P<\/jats:italic>\u2009&lt;\u20090.001) compared to SUVpeak, TLG and energy separately. DeLong\u2019s test revealed a statistically significant enhancement in ROC when compared to SUVpeak (Z\u2009=\u20092.372, <jats:italic>P<\/jats:italic>\u2009=\u20090.018), TLG (Z\u2009=\u20092.095, <jats:italic>P<\/jats:italic>\u2009=\u20090.036), and energy (Z\u2009=\u20092.318, <jats:italic>P<\/jats:italic>\u2009=\u20090.020).<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>Combining multiple parameters using <jats:sup>18<\/jats:sup>F-FDG PET\/CT may further improve distinguishing between SPLCs and PMs in patients with single solitary pulmonary lesion and extrapulmonary malignant tumor.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1007\/s12149-025-02034-7","type":"journal-article","created":{"date-parts":[[2025,3,5]],"date-time":"2025-03-05T13:08:20Z","timestamp":1741180100000},"page":"567-575","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Differentiating second primary lung cancer from pulmonary metastasis in patients of single solitary pulmonary lesion with extrapulmonary tumor using multiparametric analysis of FDG PET\/CT"],"prefix":"10.1007","volume":"39","author":[{"given":"Honghong","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaolin","family":"Meng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guanyun","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shulin","family":"Yao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanmei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruimin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,3,5]]},"reference":[{"issue":"6","key":"2034_CR1","doi-asserted-by":"publisher","first-page":"397","DOI":"10.3109\/07357907.2013.800092","volume":"31","author":"J Ge","year":"2013","unstructured":"Ge J, Gou HF, Chen Y, et al. 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