{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T11:44:51Z","timestamp":1740138291687,"version":"3.37.3"},"reference-count":32,"publisher":"Oxford University Press (OUP)","issue":"1165","license":[{"start":{"date-parts":[[2024,10,9]],"date-time":"2024-10-09T00:00:00Z","timestamp":1728432000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>To investigate the utility of voxel histogram analysis (HA) for differentiating hyperdense renal cysts from small solid masses on unenhanced CT scans.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>A retrospective analysis of 99 hyperdense cystic lesions and 28 solid malignant lesions was conducted using a radiological database (from 2015 to 2021) and a pathological database (from 2010 to 2020). The study investigated the distribution of voxel attenuation values using percentiles to establish reliable criteria for differentiation after drawing a region of interest (ROI) in the centre of the lesions. The standard of reference was a histopathological diagnosis for malignant masses and contrast-enhanced CT or MRI for cysts.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>HA provided higher diagnostic accuracy than the conventional mean attenuation value of 70 Hounsfield Units (HU). For the 75th and 90th percentiles \u00b1 1 standard deviation, accuracies of 77.2% (95% confidence interval 68.9%-84.2%) for the 75th and 68.5% (59.7%-76.4%) for the 90th were found, versus 37.0% (28.6%-46.0%) for the 70 HU threshold criterion. A Gaussian distribution of voxel attenuation values was observed in 88.9% of the lesions, suggesting that it is feasible to calculate these parameters from a single measurement.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>The study underscores the potential of HA as a valuable tool for characterizing hyperdense cysts on unenhanced CT by using the same ROI for measuring lesion attenuation. HA could offer additional value beyond the 70 HU criterion and possibly influence clinical decisions. Multi-institutional studies are necessary for external validation to confirm its generalizability and more extensive applicability.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Advances in knowledge<\/jats:title>\n                  <jats:p>(1) A single measurement on unenhanced CT images, using mean attenuation and standard deviation, accurately reflects the voxel distribution of both cystic and solid masses, allowing for the application of histogram analysis. (2) The 75th percentile threshold of 65 HU or higher could potentially increase sensitivity in diagnosing hyperdense cysts, compared to the 70 HU mean attenuation threshold, without compromising specificity.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bjr\/tqae198","type":"journal-article","created":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T16:09:55Z","timestamp":1730218195000},"page":"100-106","source":"Crossref","is-referenced-by-count":0,"title":["The incremental value of histogram analysis in the differentiation between hyperdense cysts and solid renal masses on unenhanced CT images"],"prefix":"10.1093","volume":"98","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8578-3136","authenticated-orcid":false,"given":"Cec\u00edlia Vidal","family":"de Souza Torres","sequence":"first","affiliation":[{"name":"Department of Imaging, Oncology and Hematology, Ribeirao Preto School of Medicine, University of Sao Paulo , Ribeir\u00e3o Preto, S\u00e3o Paulo 14049-900,","place":["Brazil"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0996-2463","authenticated-orcid":false,"given":"Andr\u00e9","family":"de Freitas Secaf","sequence":"additional","affiliation":[{"name":"Department of Imaging, Oncology and Hematology, Ribeirao Preto School of Medicine, University of Sao Paulo , Ribeir\u00e3o Preto, S\u00e3o Paulo 14049-900,","place":["Brazil"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2920-7710","authenticated-orcid":false,"given":"David Freire","family":"Maia Vieira","sequence":"additional","affiliation":[{"name":"Department of Imaging, Oncology and Hematology, Ribeirao Preto School of Medicine, University of Sao Paulo , Ribeir\u00e3o Preto, S\u00e3o Paulo 14049-900,","place":["Brazil"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-2932-1050","authenticated-orcid":false,"given":"Alexandre 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