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Patients with pathologically confirmed solid pancreatic lesions were enrolled from one tertiary medical centre from March 2011 to June 2021 and in two tertiary institutions between January 2015 and June 2021. A prediction nomogram model was established in the training set by using precontrast US and CEUS imaging features that were independently associated with MSPLs. The performance of the prediction model was further externally validated.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>A total of 155 patients (mean age, 55 \u00b1 14.6 years, M\/F = 84\/71) and 78 patients (mean age, 59 \u00b1 13.4 years, M\/F = 36\/42) were included in the training and validation cohorts, respectively. In the training set, an ill-defined border and dilated main pancreatic duct on precontrast ultrasound, CEUS patterns of hypoenhancement in both the arterial and venous phases of CEUS, and hyperenhancement\/isoenhancement followed by washout were independently associated with MSPLs. The prediction nomogram model developed with the aforementioned variables showed good performance in differentiating MSPLs from BSPLs with an area under the curve (AUC) of 0.938 in the training set and 0.906 in the validation set.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>Hypoenhancement in all phases, hyperenhancement\/isoenhancement followed by washout on CEUS, an ill-defined border, and a dilated main pancreatic duct were independent risk factors for MSPLs. The nomogram constructed based on these predictors can be used to diagnose MSPLs.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Key Points<\/jats:title>\n                <jats:p><jats:italic>\u2022 An ill-defined border and dilated main pancreatic duct on precontrast ultrasound, hypoenhancement in all phases of CEUS, and hyperenhancement\/isoenhancement followed by washout were independently associated with MSPLs.<\/jats:italic><\/jats:p>\n                <jats:p><jats:italic>\u2022 The ultrasound-based prediction model showed good performance in differentiating MSPLs from BSPLs with an AUC of 0.938 in the training set and 0.906 in the external validation set.<\/jats:italic><\/jats:p>\n                <jats:p><jats:italic>\u2022 An ultrasound-based nomogram is an easy-to-use tool to differentiate between MSPLs and BSPLs with high efficacy.<\/jats:italic><\/jats:p>\n              <\/jats:sec>","DOI":"10.1007\/s00330-022-08930-0","type":"journal-article","created":{"date-parts":[[2022,6,25]],"date-time":"2022-06-25T06:02:41Z","timestamp":1656136961000},"page":"8296-8305","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Development and validation of an ultrasound-based prediction model for differentiating between malignant and benign solid pancreatic lesions"],"prefix":"10.1007","volume":"32","author":[{"given":"Jiayan","family":"Huang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianming","family":"Ding","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rui","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiawu","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Luo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4057-1997","authenticated-orcid":false,"given":"Qiang","family":"Lu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,6,25]]},"reference":[{"key":"8930_CR1","doi-asserted-by":"publisher","first-page":"7","DOI":"10.3322\/caac.21654","volume":"71","author":"RL Siegel","year":"2021","unstructured":"Siegel RL, Miller KD, Fuchs HE, Jemal A (2021) Cancer statistics, 2021. 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