{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T14:22:44Z","timestamp":1787667764980,"version":"build-2736575974"},"reference-count":20,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T00:00:00Z","timestamp":1768348800000},"content-version":"vor","delay-in-days":13,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The detection of lacunar strokes in CT perfusion (CTP) imaging may be improved by reducing the reconstructed CTP slice thickness. However, this increases noise, necessitating the use of robust noise filters.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>To Investigate the impact of slice thickness and three state\u2010of\u2010the\u2010art noise filters on the detection of lacunar strokes of varying sizes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Artificial spherical lacunar infarcts (diameter: 5, 7, and 10\u00a0mm) were added to 40 thin slice CTP acquisitions. The performance of time\u2010intensity profile guided filtering, temporal\u2010average guided filtering, and a U\u2010Net based filter were compared based on infarct detectability in cerebral blood volume maps of thick\u2010 (4.9\u00a0mm) and thin\u2010slice (0.7\u00a0mm) reconstructions. One observer evaluated the maps for each combination of filter and slice thickness. A second observer repeated the evaluation for the two best performing combinations. F1\u2010score, contrast\u2010to\u2010noise ratio, and observer confidence were calculated for every combination of filter, slice thickness, and observer.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The highest F1\u2010scores were achieved with the temporal\u2010average guided filter (thin slices: 0.70, thick slices: 0.49). The other filters did not exceed an F1\u2010score of 0.36 on either thin\u2010 or thick slices. Thin\u2010slice temporal\u2010average guided filtering also achieved the highest contrast\u2010to\u2010noise ratio and observer confidence, which resulted in a sensitivity of 10% for 5\u00a0mm, 73% for 7\u00a0mm, and 75% for 10\u00a0mm diameter lacunar infarcts.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study demonstrates that robust noise filtering, particularly temporal\u2010average guided filtering, enables improved detection of lacunar strokes (\u22657\u00a0mm) in CTP imaging using thin\u2010slice reconstructions.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mp.70271","type":"journal-article","created":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T16:12:21Z","timestamp":1768407141000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Robust filtering of thin\u2010slice reconstructions improves lacunar stroke detection in CT perfusion imaging"],"prefix":"10.1002","volume":"53","author":[{"given":"Joris","family":"Vromans","sequence":"first","affiliation":[{"name":"Department of Radiology and Nuclear Medicine University Medical Center Utrecht  Utrecht The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Edwin","family":"Bennink","sequence":"additional","affiliation":[{"name":"Department of Radiology and Nuclear Medicine University Medical Center Utrecht  Utrecht The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jan Willem","family":"Dankbaar","sequence":"additional","affiliation":[{"name":"Department of Radiology and Nuclear Medicine University Medical Center Utrecht  Utrecht The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Birgitta K.","family":"Velthuis","sequence":"additional","affiliation":[{"name":"Department of Radiology and Nuclear Medicine University Medical Center Utrecht  Utrecht The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hugo W. A. M.","family":"de Jong","sequence":"additional","affiliation":[{"name":"Department of Radiology and Nuclear Medicine University Medical Center Utrecht  Utrecht The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,1,14]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1161\/STROKEAHA.119.028402"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamaneurol.2018.1073"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1136\/jnnp\u20102021\u2010326308"},{"key":"e_1_2_8_5_1","volume-title":"StatPearls","author":"Gore M","year":"2025"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1159\/000350200"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.3174\/ajnr.A1487"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics13091564"},{"key":"e_1_2_8_9_1","unstructured":"WuD RenH LiQ Self\u2010supervised dynamic CT perfusion image denoising with deep neural networks. 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Published online October 29 2018. doi:10.48550\/arXiv.1803.04189"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1177\/0271678x15610586"},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.1161\/STROKEAHA.120.030696"},{"key":"e_1_2_8_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2006.01.015"},{"key":"e_1_2_8_21_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0077428"}],"container-title":["Medical Physics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/mp.70271","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/mp.70271","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/mp.70271","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T01:56:48Z","timestamp":1773885408000},"score":1,"resource":{"primary":{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/10.1002\/mp.70271"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1]]},"references-count":20,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,1]]}},"alternative-id":["10.1002\/mp.70271"],"URL":"https:\/\/doi.org\/10.1002\/mp.70271","archive":["Portico"],"relation":{},"ISSN":["0094-2405","2473-4209"],"issn-type":[{"value":"0094-2405","type":"print"},{"value":"2473-4209","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1]]},"assertion":[{"value":"2025-06-15","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-11-26","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-01-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70271"}}