Optimal slice thickness of brain computed tomography using a hybrid iterative reconstruction algorithm for identifying hyperdense middle cerebral artery sign of acute ischemic stroke
Purpose To determine the optimal slice thickness of brain non-contrast computed tomography using a hybrid iterative reconstruction algorithm to identify hyperdense middle cerebral artery sign in patients with acute ischemic stroke. Methods We retrospectively enrolled 30 patients who had presented hy...
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| Veröffentlicht in: | Emergency radiology 2021-04, Vol.28 (2), p.309-315 |
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| creator | Ichikawa, Shota Hamada, Misaki Watanabe, Daiki Ito, Osamu Moriya, Takafumi Yamamoto, Hiroyuki |
| description | Purpose
To determine the optimal slice thickness of brain non-contrast computed tomography using a hybrid iterative reconstruction algorithm to identify hyperdense middle cerebral artery sign in patients with acute ischemic stroke.
Methods
We retrospectively enrolled 30 patients who had presented hyperdense middle cerebral artery sign and 30 patients who showed no acute ischemic change in acute magnetic resonance imaging. Reformatted axial images at an angle of the orbitomeatal line in slice thicknesses of 0.5, 1, 3, 5, and 7 mm were generated. Optimal slice thickness for identifying hyperdense middle cerebral artery sign was evaluated by a receiver operating characteristics curve analysis and area under the curve (AUC).
Results
The mean AUC value of 0.5-mm slice (0.921; 95% confidence interval (95% CI), 0.868 to 0.975) was significantly higher than those of 3-mm (0.791; 95% CI, 0.686 to 0.895;
p
= 0.041), 5-mm (0.691; 95% CI, 0.583 to 0.799,
p
|
| doi_str_mv | 10.1007/s10140-020-01864-4 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2451135770</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2451135770</sourcerecordid><originalsourceid>FETCH-LOGICAL-c441t-c4dbba5e7a7c6cb7b4ea6690c36df08c2625bfe00ba068feb9992854ea06d4683</originalsourceid><addsrcrecordid>eNp9kc1u1TAQhSMEoj_wAizQSGzYBMaJ4-QuUVWgUqVuYG3ZziRxm9jBdpDyYjwfvtwCEgsWHo_lM9-M5hTFK4bvGGL7PjJkHEus8mGd4CV_UpwzXndlDs3TnGOLZY3Iz4qLGO8RURxE97w4q2tsqgbZefHjbk12UTPE2RqCNFnz4ChG8APooKwD45d1S9RD8osfg1qnHbZo3QgKpl0H24NNFFSy3wkCGe9iCptJ1jtQ8-iDTdMCgw9ge3LJDvuxdtpXCvkdCRbb9zOBoUC54wwqZNwO0Y7uOIUyuTvYaCZarIEM9w_0ong2qDnSy8f7svj68frL1efy9u7TzdWH29JwzlKOvdaqoVa1Rhjdak5KiAOaWvQDdqYSVaMHQtQKRTeQPhwOVddkFYqei66-LN6euGvw3zaKSS55Eppn5chvUVa8Yaxu2haz9M0_0nu_BZenk3nVGS9YfQRWJ5UJPsZAg1xD3n_YJUN5dFWeXJXZVfnLVclz0etH9KYX6v-U_LYxC-qTIOYvN1L42_s_2J808rKM</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2500686138</pqid></control><display><type>article</type><title>Optimal slice thickness of brain computed tomography using a hybrid iterative reconstruction algorithm for identifying hyperdense middle cerebral artery sign of acute ischemic stroke</title><source>Springer Nature - Complete Springer Journals</source><creator>Ichikawa, Shota ; Hamada, Misaki ; Watanabe, Daiki ; Ito, Osamu ; Moriya, Takafumi ; Yamamoto, Hiroyuki</creator><creatorcontrib>Ichikawa, Shota ; Hamada, Misaki ; Watanabe, Daiki ; Ito, Osamu ; Moriya, Takafumi ; Yamamoto, Hiroyuki</creatorcontrib><description>Purpose
To determine the optimal slice thickness of brain non-contrast computed tomography using a hybrid iterative reconstruction algorithm to identify hyperdense middle cerebral artery sign in patients with acute ischemic stroke.
Methods
We retrospectively enrolled 30 patients who had presented hyperdense middle cerebral artery sign and 30 patients who showed no acute ischemic change in acute magnetic resonance imaging. Reformatted axial images at an angle of the orbitomeatal line in slice thicknesses of 0.5, 1, 3, 5, and 7 mm were generated. Optimal slice thickness for identifying hyperdense middle cerebral artery sign was evaluated by a receiver operating characteristics curve analysis and area under the curve (AUC).
Results
The mean AUC value of 0.5-mm slice (0.921; 95% confidence interval (95% CI), 0.868 to 0.975) was significantly higher than those of 3-mm (0.791; 95% CI, 0.686 to 0.895;
p
= 0.041), 5-mm (0.691; 95% CI, 0.583 to 0.799,
p
< 0.001), and 7-mm (0.695; 95% CI, 0.593 to 0.797,
p
< 0.001) slices, whereas it was equivalent to that of 1-mm slice (0.901; 95% CI, 0.837 to 0.965,
p
= 0.751).
Conclusion
Thin slice thickness of ≤ 1 mm has a better diagnostic performance for identifying hyperdense artery sign on brain non-contrast computed tomography with a hybrid iterative reconstruction algorithm in patients with acute ischemic stroke.</description><identifier>ISSN: 1070-3004</identifier><identifier>EISSN: 1438-1435</identifier><identifier>DOI: 10.1007/s10140-020-01864-4</identifier><identifier>PMID: 33052501</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Algorithms ; Brain ; Computed tomography ; Confidence intervals ; Emergency Medicine ; Image reconstruction ; Imaging ; Iterative methods ; Magnetic resonance imaging ; Medicine ; Medicine & Public Health ; Original Article ; Radiology ; Stroke ; Thickness ; Tomography</subject><ispartof>Emergency radiology, 2021-04, Vol.28 (2), p.309-315</ispartof><rights>American Society of Emergency Radiology 2020</rights><rights>American Society of Emergency Radiology 2020.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c441t-c4dbba5e7a7c6cb7b4ea6690c36df08c2625bfe00ba068feb9992854ea06d4683</citedby><cites>FETCH-LOGICAL-c441t-c4dbba5e7a7c6cb7b4ea6690c36df08c2625bfe00ba068feb9992854ea06d4683</cites><orcidid>0000-0002-4275-1422</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10140-020-01864-4$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10140-020-01864-4$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33052501$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ichikawa, Shota</creatorcontrib><creatorcontrib>Hamada, Misaki</creatorcontrib><creatorcontrib>Watanabe, Daiki</creatorcontrib><creatorcontrib>Ito, Osamu</creatorcontrib><creatorcontrib>Moriya, Takafumi</creatorcontrib><creatorcontrib>Yamamoto, Hiroyuki</creatorcontrib><title>Optimal slice thickness of brain computed tomography using a hybrid iterative reconstruction algorithm for identifying hyperdense middle cerebral artery sign of acute ischemic stroke</title><title>Emergency radiology</title><addtitle>Emerg Radiol</addtitle><addtitle>Emerg Radiol</addtitle><description>Purpose
To determine the optimal slice thickness of brain non-contrast computed tomography using a hybrid iterative reconstruction algorithm to identify hyperdense middle cerebral artery sign in patients with acute ischemic stroke.
Methods
We retrospectively enrolled 30 patients who had presented hyperdense middle cerebral artery sign and 30 patients who showed no acute ischemic change in acute magnetic resonance imaging. Reformatted axial images at an angle of the orbitomeatal line in slice thicknesses of 0.5, 1, 3, 5, and 7 mm were generated. Optimal slice thickness for identifying hyperdense middle cerebral artery sign was evaluated by a receiver operating characteristics curve analysis and area under the curve (AUC).
Results
The mean AUC value of 0.5-mm slice (0.921; 95% confidence interval (95% CI), 0.868 to 0.975) was significantly higher than those of 3-mm (0.791; 95% CI, 0.686 to 0.895;
p
= 0.041), 5-mm (0.691; 95% CI, 0.583 to 0.799,
p
< 0.001), and 7-mm (0.695; 95% CI, 0.593 to 0.797,
p
< 0.001) slices, whereas it was equivalent to that of 1-mm slice (0.901; 95% CI, 0.837 to 0.965,
p
= 0.751).
Conclusion
Thin slice thickness of ≤ 1 mm has a better diagnostic performance for identifying hyperdense artery sign on brain non-contrast computed tomography with a hybrid iterative reconstruction algorithm in patients with acute ischemic stroke.</description><subject>Algorithms</subject><subject>Brain</subject><subject>Computed tomography</subject><subject>Confidence intervals</subject><subject>Emergency Medicine</subject><subject>Image reconstruction</subject><subject>Imaging</subject><subject>Iterative methods</subject><subject>Magnetic resonance imaging</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Original Article</subject><subject>Radiology</subject><subject>Stroke</subject><subject>Thickness</subject><subject>Tomography</subject><issn>1070-3004</issn><issn>1438-1435</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp9kc1u1TAQhSMEoj_wAizQSGzYBMaJ4-QuUVWgUqVuYG3ZziRxm9jBdpDyYjwfvtwCEgsWHo_lM9-M5hTFK4bvGGL7PjJkHEus8mGd4CV_UpwzXndlDs3TnGOLZY3Iz4qLGO8RURxE97w4q2tsqgbZefHjbk12UTPE2RqCNFnz4ChG8APooKwD45d1S9RD8osfg1qnHbZo3QgKpl0H24NNFFSy3wkCGe9iCptJ1jtQ8-iDTdMCgw9ge3LJDvuxdtpXCvkdCRbb9zOBoUC54wwqZNwO0Y7uOIUyuTvYaCZarIEM9w_0ong2qDnSy8f7svj68frL1efy9u7TzdWH29JwzlKOvdaqoVa1Rhjdak5KiAOaWvQDdqYSVaMHQtQKRTeQPhwOVddkFYqei66-LN6euGvw3zaKSS55Eppn5chvUVa8Yaxu2haz9M0_0nu_BZenk3nVGS9YfQRWJ5UJPsZAg1xD3n_YJUN5dFWeXJXZVfnLVclz0etH9KYX6v-U_LYxC-qTIOYvN1L42_s_2J808rKM</recordid><startdate>20210401</startdate><enddate>20210401</enddate><creator>Ichikawa, Shota</creator><creator>Hamada, Misaki</creator><creator>Watanabe, Daiki</creator><creator>Ito, Osamu</creator><creator>Moriya, Takafumi</creator><creator>Yamamoto, Hiroyuki</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FE</scope><scope>8FG</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-4275-1422</orcidid></search><sort><creationdate>20210401</creationdate><title>Optimal slice thickness of brain computed tomography using a hybrid iterative reconstruction algorithm for identifying hyperdense middle cerebral artery sign of acute ischemic stroke</title><author>Ichikawa, Shota ; Hamada, Misaki ; Watanabe, Daiki ; Ito, Osamu ; Moriya, Takafumi ; Yamamoto, Hiroyuki</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c441t-c4dbba5e7a7c6cb7b4ea6690c36df08c2625bfe00ba068feb9992854ea06d4683</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Brain</topic><topic>Computed tomography</topic><topic>Confidence intervals</topic><topic>Emergency Medicine</topic><topic>Image reconstruction</topic><topic>Imaging</topic><topic>Iterative methods</topic><topic>Magnetic resonance imaging</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Original Article</topic><topic>Radiology</topic><topic>Stroke</topic><topic>Thickness</topic><topic>Tomography</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ichikawa, Shota</creatorcontrib><creatorcontrib>Hamada, Misaki</creatorcontrib><creatorcontrib>Watanabe, Daiki</creatorcontrib><creatorcontrib>Ito, Osamu</creatorcontrib><creatorcontrib>Moriya, Takafumi</creatorcontrib><creatorcontrib>Yamamoto, Hiroyuki</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><jtitle>Emergency radiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ichikawa, Shota</au><au>Hamada, Misaki</au><au>Watanabe, Daiki</au><au>Ito, Osamu</au><au>Moriya, Takafumi</au><au>Yamamoto, Hiroyuki</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimal slice thickness of brain computed tomography using a hybrid iterative reconstruction algorithm for identifying hyperdense middle cerebral artery sign of acute ischemic stroke</atitle><jtitle>Emergency radiology</jtitle><stitle>Emerg Radiol</stitle><addtitle>Emerg Radiol</addtitle><date>2021-04-01</date><risdate>2021</risdate><volume>28</volume><issue>2</issue><spage>309</spage><epage>315</epage><pages>309-315</pages><issn>1070-3004</issn><eissn>1438-1435</eissn><abstract>Purpose
To determine the optimal slice thickness of brain non-contrast computed tomography using a hybrid iterative reconstruction algorithm to identify hyperdense middle cerebral artery sign in patients with acute ischemic stroke.
Methods
We retrospectively enrolled 30 patients who had presented hyperdense middle cerebral artery sign and 30 patients who showed no acute ischemic change in acute magnetic resonance imaging. Reformatted axial images at an angle of the orbitomeatal line in slice thicknesses of 0.5, 1, 3, 5, and 7 mm were generated. Optimal slice thickness for identifying hyperdense middle cerebral artery sign was evaluated by a receiver operating characteristics curve analysis and area under the curve (AUC).
Results
The mean AUC value of 0.5-mm slice (0.921; 95% confidence interval (95% CI), 0.868 to 0.975) was significantly higher than those of 3-mm (0.791; 95% CI, 0.686 to 0.895;
p
= 0.041), 5-mm (0.691; 95% CI, 0.583 to 0.799,
p
< 0.001), and 7-mm (0.695; 95% CI, 0.593 to 0.797,
p
< 0.001) slices, whereas it was equivalent to that of 1-mm slice (0.901; 95% CI, 0.837 to 0.965,
p
= 0.751).
Conclusion
Thin slice thickness of ≤ 1 mm has a better diagnostic performance for identifying hyperdense artery sign on brain non-contrast computed tomography with a hybrid iterative reconstruction algorithm in patients with acute ischemic stroke.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>33052501</pmid><doi>10.1007/s10140-020-01864-4</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0002-4275-1422</orcidid></addata></record> |
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| ispartof | Emergency radiology, 2021-04, Vol.28 (2), p.309-315 |
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| language | eng |
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| source | Springer Nature - Complete Springer Journals |
| subjects | Algorithms Brain Computed tomography Confidence intervals Emergency Medicine Image reconstruction Imaging Iterative methods Magnetic resonance imaging Medicine Medicine & Public Health Original Article Radiology Stroke Thickness Tomography |
| title | Optimal slice thickness of brain computed tomography using a hybrid iterative reconstruction algorithm for identifying hyperdense middle cerebral artery sign of acute ischemic stroke |
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