Automatic tube potential selection with tube current modulation in coronary CT angiography: Can it achieve consistent image quality among various individuals?
The present study included a total of 111 consecutive patients who had undergone coronary computed tomography (CT) angiography, using a first-generation dual-source CT with automatic tube potential selection and tube current modulation. Body weight (BW) and body mass index (BMI) were recorded prior...
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| Veröffentlicht in: | Experimental and therapeutic medicine 2018-07, Vol.16 (1), p.253-259 |
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| creator | Wang, Xiao-Ping Zhu, Xiao-Mei Zhu, Yin-Su Liu, Wang-Yan Yang, Xiao-Han Huang, Wei-Wei Xu, Yi Tang, Li-Jun |
| description | The present study included a total of 111 consecutive patients who had undergone coronary computed tomography (CT) angiography, using a first-generation dual-source CT with automatic tube potential selection and tube current modulation. Body weight (BW) and body mass index (BMI) were recorded prior to CT examinations. Image noise and attenuation of the proximal ascending aorta (AA) and descending aorta (DA) at the middle level of the left ventricle were measured. Correlations between BW, BMI and objective image quality were evaluated using linear regression. In addition, two subgroups based on BMI (BMI ≤25 and >25 kg/m
) were analyzed. Subjective image quality, image noise, the signal-to-noise ratio (SNR) and the contrast-to-noise ratio (CNR) were all compared between those. The image noise of the AA increased with the BW and BMI (BW: r=0.453, P |
| doi_str_mv | 10.3892/etm.2018.6158 |
| format | Article |
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) were analyzed. Subjective image quality, image noise, the signal-to-noise ratio (SNR) and the contrast-to-noise ratio (CNR) were all compared between those. The image noise of the AA increased with the BW and BMI (BW: r=0.453, P<0.001; BMI: r=0.545, P<0.001). The CNR and SNR of the AA were inversely correlated with BW and BMI, respectively. The image noise of the DA and the CNR and SNR of the DA exhibited a similar association to those with the BW or BMI. The BMI >25 kg/m
group had a significant increase in image noise (33.1±6.9 vs. 27.8±4.0 HU, P<0.05) and a significant reduction in CNR and SNR, when compared with those in the BMI ≤25 kg/m
group (CNR: 18.9±4.3 vs. 16.1±3.7, P<0.05; SNR: 16.0±3.8 vs. 13.6±3.2, P<0.05). Patients with a BMI of ≤25 kg/m
had more coronary artery segments scored as excellent, compared with patients with a BMI of >25 kg/m
(P=0.02). In conclusion, this method is not able to achieve a consistent objective image quality across the entire patient population. The impact of BW and BMI on objective image quality was not completely eliminated. BMI-based adjustment of the tube potential may achieve a more consistent image quality compared to automatic tube potential selection, particularly in patients with a larger body habitus.</description><identifier>ISSN: 1792-0981</identifier><identifier>EISSN: 1792-1015</identifier><identifier>DOI: 10.3892/etm.2018.6158</identifier><identifier>PMID: 29896246</identifier><language>eng</language><publisher>Greece: Spandidos Publications</publisher><subject>Algorithms ; Body mass index ; Cardiovascular disease ; Care and treatment ; CAT scans ; Coronary angiography ; Coronary heart disease ; Coronary vessels ; Heart rate ; Medical imaging ; Noise ; Patients ; Quality ; Standard deviation ; Studies</subject><ispartof>Experimental and therapeutic medicine, 2018-07, Vol.16 (1), p.253-259</ispartof><rights>COPYRIGHT 2018 Spandidos Publications</rights><rights>Copyright Spandidos Publications UK Ltd. 2018</rights><rights>Copyright: © Wang et al. 2018</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c482t-b86bfffb2b4b5837a4682a3c98fe8bfcd7c0d9e01d74d9dac7898ca8eed559a13</citedby><cites>FETCH-LOGICAL-c482t-b86bfffb2b4b5837a4682a3c98fe8bfcd7c0d9e01d74d9dac7898ca8eed559a13</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5995055/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5995055/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27903,27904,53770,53772</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29896246$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wang, Xiao-Ping</creatorcontrib><creatorcontrib>Zhu, Xiao-Mei</creatorcontrib><creatorcontrib>Zhu, Yin-Su</creatorcontrib><creatorcontrib>Liu, Wang-Yan</creatorcontrib><creatorcontrib>Yang, Xiao-Han</creatorcontrib><creatorcontrib>Huang, Wei-Wei</creatorcontrib><creatorcontrib>Xu, Yi</creatorcontrib><creatorcontrib>Tang, Li-Jun</creatorcontrib><title>Automatic tube potential selection with tube current modulation in coronary CT angiography: Can it achieve consistent image quality among various individuals?</title><title>Experimental and therapeutic medicine</title><addtitle>Exp Ther Med</addtitle><description>The present study included a total of 111 consecutive patients who had undergone coronary computed tomography (CT) angiography, using a first-generation dual-source CT with automatic tube potential selection and tube current modulation. Body weight (BW) and body mass index (BMI) were recorded prior to CT examinations. Image noise and attenuation of the proximal ascending aorta (AA) and descending aorta (DA) at the middle level of the left ventricle were measured. Correlations between BW, BMI and objective image quality were evaluated using linear regression. In addition, two subgroups based on BMI (BMI ≤25 and >25 kg/m
) were analyzed. Subjective image quality, image noise, the signal-to-noise ratio (SNR) and the contrast-to-noise ratio (CNR) were all compared between those. The image noise of the AA increased with the BW and BMI (BW: r=0.453, P<0.001; BMI: r=0.545, P<0.001). The CNR and SNR of the AA were inversely correlated with BW and BMI, respectively. The image noise of the DA and the CNR and SNR of the DA exhibited a similar association to those with the BW or BMI. The BMI >25 kg/m
group had a significant increase in image noise (33.1±6.9 vs. 27.8±4.0 HU, P<0.05) and a significant reduction in CNR and SNR, when compared with those in the BMI ≤25 kg/m
group (CNR: 18.9±4.3 vs. 16.1±3.7, P<0.05; SNR: 16.0±3.8 vs. 13.6±3.2, P<0.05). Patients with a BMI of ≤25 kg/m
had more coronary artery segments scored as excellent, compared with patients with a BMI of >25 kg/m
(P=0.02). In conclusion, this method is not able to achieve a consistent objective image quality across the entire patient population. The impact of BW and BMI on objective image quality was not completely eliminated. BMI-based adjustment of the tube potential may achieve a more consistent image quality compared to automatic tube potential selection, particularly in patients with a larger body habitus.</description><subject>Algorithms</subject><subject>Body mass index</subject><subject>Cardiovascular disease</subject><subject>Care and treatment</subject><subject>CAT scans</subject><subject>Coronary angiography</subject><subject>Coronary heart disease</subject><subject>Coronary vessels</subject><subject>Heart rate</subject><subject>Medical imaging</subject><subject>Noise</subject><subject>Patients</subject><subject>Quality</subject><subject>Standard deviation</subject><subject>Studies</subject><issn>1792-0981</issn><issn>1792-1015</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><recordid>eNptUk1v1DAUjBCIVqVHrsgSFy5ZbCdObA6g1YoWpEpcytl6sZ2sq8Te2s5W-2f4rTjsUrUI-_Asz7x5H5qieEvwquKCfjRpWlFM-KohjL8ozkkraEkwYS9Pbyw4OSsuY7zD-bCGcM5eF2dUcNHQujkvfq3n5CdIVqE0dwbtfDIuWRhRNKNRyXqHHmzaHlE1h5BhNHk9j_AHtA4pH7yDcECbWwRusH4IsNsePqENZDwhUFtr9jnbu2jjoo_sBINB9zOMNh0QTN4NaA_B-jlmRW33VmcsfnlTvOpzNJeneFH8vPp6u_lW3vy4_r5Z35Sq5jSVHW-6vu872tUd41ULdcMpVErw3vCuV7pVWAuDiW5rLTSolguugBujGRNAqovi81F3N3eT0Sr3GGCUu5AbDQfpwcrniLNbOfi9ZEIwzFgW-HASCP5-NjHJyUZlxhGcyUNJilktal5VS633_1Dv_BxcHi-zBKsr3DRPWAOMRlrX-1xXLaJyzRjldc0EzqzVf1j5ajPZvG_T2_z_LKE8JqjgYwymf5yRYLl4SmZPycVTcvFU5r97uphH9l8HVb8BKrHL_Q</recordid><startdate>20180701</startdate><enddate>20180701</enddate><creator>Wang, Xiao-Ping</creator><creator>Zhu, Xiao-Mei</creator><creator>Zhu, Yin-Su</creator><creator>Liu, Wang-Yan</creator><creator>Yang, Xiao-Han</creator><creator>Huang, Wei-Wei</creator><creator>Xu, Yi</creator><creator>Tang, Li-Jun</creator><general>Spandidos Publications</general><general>Spandidos Publications UK Ltd</general><general>D.A. Spandidos</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AN0</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20180701</creationdate><title>Automatic tube potential selection with tube current modulation in coronary CT angiography: Can it achieve consistent image quality among various individuals?</title><author>Wang, Xiao-Ping ; Zhu, Xiao-Mei ; Zhu, Yin-Su ; Liu, Wang-Yan ; Yang, Xiao-Han ; Huang, Wei-Wei ; Xu, Yi ; Tang, Li-Jun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c482t-b86bfffb2b4b5837a4682a3c98fe8bfcd7c0d9e01d74d9dac7898ca8eed559a13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Algorithms</topic><topic>Body mass index</topic><topic>Cardiovascular disease</topic><topic>Care and treatment</topic><topic>CAT scans</topic><topic>Coronary angiography</topic><topic>Coronary heart disease</topic><topic>Coronary vessels</topic><topic>Heart rate</topic><topic>Medical imaging</topic><topic>Noise</topic><topic>Patients</topic><topic>Quality</topic><topic>Standard deviation</topic><topic>Studies</topic><toplevel>online_resources</toplevel><creatorcontrib>Wang, Xiao-Ping</creatorcontrib><creatorcontrib>Zhu, Xiao-Mei</creatorcontrib><creatorcontrib>Zhu, Yin-Su</creatorcontrib><creatorcontrib>Liu, Wang-Yan</creatorcontrib><creatorcontrib>Yang, Xiao-Han</creatorcontrib><creatorcontrib>Huang, Wei-Wei</creatorcontrib><creatorcontrib>Xu, Yi</creatorcontrib><creatorcontrib>Tang, Li-Jun</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>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>British Nursing Database</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Nursing & Allied Health Premium</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><collection>PubMed Central (Full Participant titles)</collection><jtitle>Experimental and therapeutic medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Xiao-Ping</au><au>Zhu, Xiao-Mei</au><au>Zhu, Yin-Su</au><au>Liu, Wang-Yan</au><au>Yang, Xiao-Han</au><au>Huang, Wei-Wei</au><au>Xu, Yi</au><au>Tang, Li-Jun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Automatic tube potential selection with tube current modulation in coronary CT angiography: Can it achieve consistent image quality among various individuals?</atitle><jtitle>Experimental and therapeutic medicine</jtitle><addtitle>Exp Ther Med</addtitle><date>2018-07-01</date><risdate>2018</risdate><volume>16</volume><issue>1</issue><spage>253</spage><epage>259</epage><pages>253-259</pages><issn>1792-0981</issn><eissn>1792-1015</eissn><abstract>The present study included a total of 111 consecutive patients who had undergone coronary computed tomography (CT) angiography, using a first-generation dual-source CT with automatic tube potential selection and tube current modulation. Body weight (BW) and body mass index (BMI) were recorded prior to CT examinations. Image noise and attenuation of the proximal ascending aorta (AA) and descending aorta (DA) at the middle level of the left ventricle were measured. Correlations between BW, BMI and objective image quality were evaluated using linear regression. In addition, two subgroups based on BMI (BMI ≤25 and >25 kg/m
) were analyzed. Subjective image quality, image noise, the signal-to-noise ratio (SNR) and the contrast-to-noise ratio (CNR) were all compared between those. The image noise of the AA increased with the BW and BMI (BW: r=0.453, P<0.001; BMI: r=0.545, P<0.001). The CNR and SNR of the AA were inversely correlated with BW and BMI, respectively. The image noise of the DA and the CNR and SNR of the DA exhibited a similar association to those with the BW or BMI. The BMI >25 kg/m
group had a significant increase in image noise (33.1±6.9 vs. 27.8±4.0 HU, P<0.05) and a significant reduction in CNR and SNR, when compared with those in the BMI ≤25 kg/m
group (CNR: 18.9±4.3 vs. 16.1±3.7, P<0.05; SNR: 16.0±3.8 vs. 13.6±3.2, P<0.05). Patients with a BMI of ≤25 kg/m
had more coronary artery segments scored as excellent, compared with patients with a BMI of >25 kg/m
(P=0.02). In conclusion, this method is not able to achieve a consistent objective image quality across the entire patient population. The impact of BW and BMI on objective image quality was not completely eliminated. BMI-based adjustment of the tube potential may achieve a more consistent image quality compared to automatic tube potential selection, particularly in patients with a larger body habitus.</abstract><cop>Greece</cop><pub>Spandidos Publications</pub><pmid>29896246</pmid><doi>10.3892/etm.2018.6158</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Algorithms Body mass index Cardiovascular disease Care and treatment CAT scans Coronary angiography Coronary heart disease Coronary vessels Heart rate Medical imaging Noise Patients Quality Standard deviation Studies |
| title | Automatic tube potential selection with tube current modulation in coronary CT angiography: Can it achieve consistent image quality among various individuals? |
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