Investigated geometrical characteristics and image density of left ventricle of multi-detector computed tomography in early coronary artery disease patients
Coronary artery disease (CAD) remains the leading cause of death worldwide. Currently, cardiac multi-detector computed tomography (MDCT) is widely used to diagnose CAD. The purpose in this study is to identify informative and useful predictors from left ventricular (LV) in the early CAD patients usi...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Lu, Nan-Han [verfasserIn] |
|---|
| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2016 |
|---|
| Übergeordnetes Werk: |
Enthalten in: Journal of x-ray science and technology - Duluth, Minn. : Academic Press, 1989, 24(2016), 3, Seite 353-359 |
|---|---|
| Übergeordnetes Werk: |
volume:24 ; year:2016 ; number:3 ; pages:353-359 |
| Links: |
|---|
| DOI / URN: |
10.3233/XST-160545 |
|---|
| Katalog-ID: |
OLC1978155824 |
|---|
| LEADER | 01000caa a2200265 4500 | ||
|---|---|---|---|
| 001 | OLC1978155824 | ||
| 003 | DE-627 | ||
| 005 | 20230714200637.0 | ||
| 007 | tu | ||
| 008 | 160719s2016 xx ||||| 00| ||eng c | ||
| 024 | 7 | |a 10.3233/XST-160545 |2 doi | |
| 028 | 5 | 2 | |a PQ20160719 |
| 035 | |a (DE-627)OLC1978155824 | ||
| 035 | |a (DE-599)GBVOLC1978155824 | ||
| 035 | |a (PRQ)c826-a6b5f2a283dc989707cc143b6c20d6e648118270904aec6f3541dad117f537d90 | ||
| 035 | |a (KEY)0169687420160000024000300353investigatedgeometricalcharacteristicsandimagedens | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 610 |q DNB |
| 100 | 1 | |a Lu, Nan-Han |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Investigated geometrical characteristics and image density of left ventricle of multi-detector computed tomography in early coronary artery disease patients |
| 264 | 1 | |c 2016 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ohne Hilfsmittel zu benutzen |b n |2 rdamedia | ||
| 338 | |a Band |b nc |2 rdacarrier | ||
| 520 | |a Coronary artery disease (CAD) remains the leading cause of death worldwide. Currently, cardiac multi-detector computed tomography (MDCT) is widely used to diagnose CAD. The purpose in this study is to identify informative and useful predictors from left ventricular (LV) in the early CAD patients using cardiac MDCT images. Study groups comprised 42 subjects who underwent a screening health examination, including laboratory testing and cardiac angiography by 64-slice MDCT angiography. Two geometrical characteristics and one image density were defined as shape, size and stiffness on MDCT image. The t-test, logistic regression, and receiver operating characteristic curve were applied to assess and identify the significant predictors. The Kappa statistics was used to exam the agreements with physician's judgments (i.e., Golden of True, GOT). The proposed three characteristics of LV MDCT images are important predictors and risk factors for the early CAD patients. These predictors present over 80% of AUC and higher odds ratio. The Kappa statistics was 0.68 for the combinations of shape and stiffness into logistic regression. The shape, size and stiffness of the left ventricular on MDCT can be used to be the effective indicators in the early CAD patients. Besides, the combinations of shape and stiffness into logistic regression could provide substantial agreement with physician's judgments. | ||
| 700 | 1 | |a Chen, Tai-Been |4 oth | |
| 700 | 1 | |a Liu, Kuo-Ying |4 oth | |
| 700 | 1 | |a Hsu, Shih-Yen |4 oth | |
| 700 | 1 | |a Twan, Wen-Hung |4 oth | |
| 700 | 1 | |a Ding, Hueisch-Jy |4 oth | |
| 700 | 1 | |a Hung, Chao-Ming |4 oth | |
| 700 | 1 | |a Lin, Li-Wei |4 oth | |
| 700 | 1 | |a Huang, Yung-Hui |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |t Journal of x-ray science and technology |d Duluth, Minn. : Academic Press, 1989 |g 24(2016), 3, Seite 353-359 |w (DE-627)182387127 |w (DE-600)1203221-9 |w (DE-576)09450377X |x 0895-3996 |7 nnns |
| 773 | 1 | 8 | |g volume:24 |g year:2016 |g number:3 |g pages:353-359 |
| 856 | 4 | 1 | |u http://dx.doi.org/10.3233/XST-160545 |3 Volltext |
| 856 | 4 | 2 | |u http://www.ncbi.nlm.nih.gov/pubmed/27257874 |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a SYSFLAG_A | ||
| 912 | |a GBV_OLC | ||
| 912 | |a SSG-OLC-PHY | ||
| 912 | |a SSG-OLC-PHA | ||
| 912 | |a SSG-OLC-DE-84 | ||
| 912 | |a GBV_ILN_70 | ||
| 912 | |a GBV_ILN_170 | ||
| 951 | |a AR | ||
| 952 | |d 24 |j 2016 |e 3 |h 353-359 | ||
| author_variant |
n h l nhl |
|---|---|
| matchkey_str |
article:08953996:2016----::netgtdemtiacaatrsisniaeestolfvnrcefutdtcocmuetmgahi |
| hierarchy_sort_str |
2016 |
| publishDate |
2016 |
| allfields |
10.3233/XST-160545 doi PQ20160719 (DE-627)OLC1978155824 (DE-599)GBVOLC1978155824 (PRQ)c826-a6b5f2a283dc989707cc143b6c20d6e648118270904aec6f3541dad117f537d90 (KEY)0169687420160000024000300353investigatedgeometricalcharacteristicsandimagedens DE-627 ger DE-627 rakwb eng 610 DNB Lu, Nan-Han verfasserin aut Investigated geometrical characteristics and image density of left ventricle of multi-detector computed tomography in early coronary artery disease patients 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Coronary artery disease (CAD) remains the leading cause of death worldwide. Currently, cardiac multi-detector computed tomography (MDCT) is widely used to diagnose CAD. The purpose in this study is to identify informative and useful predictors from left ventricular (LV) in the early CAD patients using cardiac MDCT images. Study groups comprised 42 subjects who underwent a screening health examination, including laboratory testing and cardiac angiography by 64-slice MDCT angiography. Two geometrical characteristics and one image density were defined as shape, size and stiffness on MDCT image. The t-test, logistic regression, and receiver operating characteristic curve were applied to assess and identify the significant predictors. The Kappa statistics was used to exam the agreements with physician's judgments (i.e., Golden of True, GOT). The proposed three characteristics of LV MDCT images are important predictors and risk factors for the early CAD patients. These predictors present over 80% of AUC and higher odds ratio. The Kappa statistics was 0.68 for the combinations of shape and stiffness into logistic regression. The shape, size and stiffness of the left ventricular on MDCT can be used to be the effective indicators in the early CAD patients. Besides, the combinations of shape and stiffness into logistic regression could provide substantial agreement with physician's judgments. Chen, Tai-Been oth Liu, Kuo-Ying oth Hsu, Shih-Yen oth Twan, Wen-Hung oth Ding, Hueisch-Jy oth Hung, Chao-Ming oth Lin, Li-Wei oth Huang, Yung-Hui oth Enthalten in Journal of x-ray science and technology Duluth, Minn. : Academic Press, 1989 24(2016), 3, Seite 353-359 (DE-627)182387127 (DE-600)1203221-9 (DE-576)09450377X 0895-3996 nnns volume:24 year:2016 number:3 pages:353-359 http://dx.doi.org/10.3233/XST-160545 Volltext http://www.ncbi.nlm.nih.gov/pubmed/27257874 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_70 GBV_ILN_170 AR 24 2016 3 353-359 |
| spelling |
10.3233/XST-160545 doi PQ20160719 (DE-627)OLC1978155824 (DE-599)GBVOLC1978155824 (PRQ)c826-a6b5f2a283dc989707cc143b6c20d6e648118270904aec6f3541dad117f537d90 (KEY)0169687420160000024000300353investigatedgeometricalcharacteristicsandimagedens DE-627 ger DE-627 rakwb eng 610 DNB Lu, Nan-Han verfasserin aut Investigated geometrical characteristics and image density of left ventricle of multi-detector computed tomography in early coronary artery disease patients 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Coronary artery disease (CAD) remains the leading cause of death worldwide. Currently, cardiac multi-detector computed tomography (MDCT) is widely used to diagnose CAD. The purpose in this study is to identify informative and useful predictors from left ventricular (LV) in the early CAD patients using cardiac MDCT images. Study groups comprised 42 subjects who underwent a screening health examination, including laboratory testing and cardiac angiography by 64-slice MDCT angiography. Two geometrical characteristics and one image density were defined as shape, size and stiffness on MDCT image. The t-test, logistic regression, and receiver operating characteristic curve were applied to assess and identify the significant predictors. The Kappa statistics was used to exam the agreements with physician's judgments (i.e., Golden of True, GOT). The proposed three characteristics of LV MDCT images are important predictors and risk factors for the early CAD patients. These predictors present over 80% of AUC and higher odds ratio. The Kappa statistics was 0.68 for the combinations of shape and stiffness into logistic regression. The shape, size and stiffness of the left ventricular on MDCT can be used to be the effective indicators in the early CAD patients. Besides, the combinations of shape and stiffness into logistic regression could provide substantial agreement with physician's judgments. Chen, Tai-Been oth Liu, Kuo-Ying oth Hsu, Shih-Yen oth Twan, Wen-Hung oth Ding, Hueisch-Jy oth Hung, Chao-Ming oth Lin, Li-Wei oth Huang, Yung-Hui oth Enthalten in Journal of x-ray science and technology Duluth, Minn. : Academic Press, 1989 24(2016), 3, Seite 353-359 (DE-627)182387127 (DE-600)1203221-9 (DE-576)09450377X 0895-3996 nnns volume:24 year:2016 number:3 pages:353-359 http://dx.doi.org/10.3233/XST-160545 Volltext http://www.ncbi.nlm.nih.gov/pubmed/27257874 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_70 GBV_ILN_170 AR 24 2016 3 353-359 |
| allfields_unstemmed |
10.3233/XST-160545 doi PQ20160719 (DE-627)OLC1978155824 (DE-599)GBVOLC1978155824 (PRQ)c826-a6b5f2a283dc989707cc143b6c20d6e648118270904aec6f3541dad117f537d90 (KEY)0169687420160000024000300353investigatedgeometricalcharacteristicsandimagedens DE-627 ger DE-627 rakwb eng 610 DNB Lu, Nan-Han verfasserin aut Investigated geometrical characteristics and image density of left ventricle of multi-detector computed tomography in early coronary artery disease patients 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Coronary artery disease (CAD) remains the leading cause of death worldwide. Currently, cardiac multi-detector computed tomography (MDCT) is widely used to diagnose CAD. The purpose in this study is to identify informative and useful predictors from left ventricular (LV) in the early CAD patients using cardiac MDCT images. Study groups comprised 42 subjects who underwent a screening health examination, including laboratory testing and cardiac angiography by 64-slice MDCT angiography. Two geometrical characteristics and one image density were defined as shape, size and stiffness on MDCT image. The t-test, logistic regression, and receiver operating characteristic curve were applied to assess and identify the significant predictors. The Kappa statistics was used to exam the agreements with physician's judgments (i.e., Golden of True, GOT). The proposed three characteristics of LV MDCT images are important predictors and risk factors for the early CAD patients. These predictors present over 80% of AUC and higher odds ratio. The Kappa statistics was 0.68 for the combinations of shape and stiffness into logistic regression. The shape, size and stiffness of the left ventricular on MDCT can be used to be the effective indicators in the early CAD patients. Besides, the combinations of shape and stiffness into logistic regression could provide substantial agreement with physician's judgments. Chen, Tai-Been oth Liu, Kuo-Ying oth Hsu, Shih-Yen oth Twan, Wen-Hung oth Ding, Hueisch-Jy oth Hung, Chao-Ming oth Lin, Li-Wei oth Huang, Yung-Hui oth Enthalten in Journal of x-ray science and technology Duluth, Minn. : Academic Press, 1989 24(2016), 3, Seite 353-359 (DE-627)182387127 (DE-600)1203221-9 (DE-576)09450377X 0895-3996 nnns volume:24 year:2016 number:3 pages:353-359 http://dx.doi.org/10.3233/XST-160545 Volltext http://www.ncbi.nlm.nih.gov/pubmed/27257874 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_70 GBV_ILN_170 AR 24 2016 3 353-359 |
| allfieldsGer |
10.3233/XST-160545 doi PQ20160719 (DE-627)OLC1978155824 (DE-599)GBVOLC1978155824 (PRQ)c826-a6b5f2a283dc989707cc143b6c20d6e648118270904aec6f3541dad117f537d90 (KEY)0169687420160000024000300353investigatedgeometricalcharacteristicsandimagedens DE-627 ger DE-627 rakwb eng 610 DNB Lu, Nan-Han verfasserin aut Investigated geometrical characteristics and image density of left ventricle of multi-detector computed tomography in early coronary artery disease patients 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Coronary artery disease (CAD) remains the leading cause of death worldwide. Currently, cardiac multi-detector computed tomography (MDCT) is widely used to diagnose CAD. The purpose in this study is to identify informative and useful predictors from left ventricular (LV) in the early CAD patients using cardiac MDCT images. Study groups comprised 42 subjects who underwent a screening health examination, including laboratory testing and cardiac angiography by 64-slice MDCT angiography. Two geometrical characteristics and one image density were defined as shape, size and stiffness on MDCT image. The t-test, logistic regression, and receiver operating characteristic curve were applied to assess and identify the significant predictors. The Kappa statistics was used to exam the agreements with physician's judgments (i.e., Golden of True, GOT). The proposed three characteristics of LV MDCT images are important predictors and risk factors for the early CAD patients. These predictors present over 80% of AUC and higher odds ratio. The Kappa statistics was 0.68 for the combinations of shape and stiffness into logistic regression. The shape, size and stiffness of the left ventricular on MDCT can be used to be the effective indicators in the early CAD patients. Besides, the combinations of shape and stiffness into logistic regression could provide substantial agreement with physician's judgments. Chen, Tai-Been oth Liu, Kuo-Ying oth Hsu, Shih-Yen oth Twan, Wen-Hung oth Ding, Hueisch-Jy oth Hung, Chao-Ming oth Lin, Li-Wei oth Huang, Yung-Hui oth Enthalten in Journal of x-ray science and technology Duluth, Minn. : Academic Press, 1989 24(2016), 3, Seite 353-359 (DE-627)182387127 (DE-600)1203221-9 (DE-576)09450377X 0895-3996 nnns volume:24 year:2016 number:3 pages:353-359 http://dx.doi.org/10.3233/XST-160545 Volltext http://www.ncbi.nlm.nih.gov/pubmed/27257874 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_70 GBV_ILN_170 AR 24 2016 3 353-359 |
| allfieldsSound |
10.3233/XST-160545 doi PQ20160719 (DE-627)OLC1978155824 (DE-599)GBVOLC1978155824 (PRQ)c826-a6b5f2a283dc989707cc143b6c20d6e648118270904aec6f3541dad117f537d90 (KEY)0169687420160000024000300353investigatedgeometricalcharacteristicsandimagedens DE-627 ger DE-627 rakwb eng 610 DNB Lu, Nan-Han verfasserin aut Investigated geometrical characteristics and image density of left ventricle of multi-detector computed tomography in early coronary artery disease patients 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Coronary artery disease (CAD) remains the leading cause of death worldwide. Currently, cardiac multi-detector computed tomography (MDCT) is widely used to diagnose CAD. The purpose in this study is to identify informative and useful predictors from left ventricular (LV) in the early CAD patients using cardiac MDCT images. Study groups comprised 42 subjects who underwent a screening health examination, including laboratory testing and cardiac angiography by 64-slice MDCT angiography. Two geometrical characteristics and one image density were defined as shape, size and stiffness on MDCT image. The t-test, logistic regression, and receiver operating characteristic curve were applied to assess and identify the significant predictors. The Kappa statistics was used to exam the agreements with physician's judgments (i.e., Golden of True, GOT). The proposed three characteristics of LV MDCT images are important predictors and risk factors for the early CAD patients. These predictors present over 80% of AUC and higher odds ratio. The Kappa statistics was 0.68 for the combinations of shape and stiffness into logistic regression. The shape, size and stiffness of the left ventricular on MDCT can be used to be the effective indicators in the early CAD patients. Besides, the combinations of shape and stiffness into logistic regression could provide substantial agreement with physician's judgments. Chen, Tai-Been oth Liu, Kuo-Ying oth Hsu, Shih-Yen oth Twan, Wen-Hung oth Ding, Hueisch-Jy oth Hung, Chao-Ming oth Lin, Li-Wei oth Huang, Yung-Hui oth Enthalten in Journal of x-ray science and technology Duluth, Minn. : Academic Press, 1989 24(2016), 3, Seite 353-359 (DE-627)182387127 (DE-600)1203221-9 (DE-576)09450377X 0895-3996 nnns volume:24 year:2016 number:3 pages:353-359 http://dx.doi.org/10.3233/XST-160545 Volltext http://www.ncbi.nlm.nih.gov/pubmed/27257874 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_70 GBV_ILN_170 AR 24 2016 3 353-359 |
| language |
English |
| source |
Enthalten in Journal of x-ray science and technology 24(2016), 3, Seite 353-359 volume:24 year:2016 number:3 pages:353-359 |
| sourceStr |
Enthalten in Journal of x-ray science and technology 24(2016), 3, Seite 353-359 volume:24 year:2016 number:3 pages:353-359 |
| format_phy_str_mv |
Article |
| institution |
findex.gbv.de |
| dewey-raw |
610 |
| isfreeaccess_bool |
false |
| container_title |
Journal of x-ray science and technology |
| authorswithroles_txt_mv |
Lu, Nan-Han @@aut@@ Chen, Tai-Been @@oth@@ Liu, Kuo-Ying @@oth@@ Hsu, Shih-Yen @@oth@@ Twan, Wen-Hung @@oth@@ Ding, Hueisch-Jy @@oth@@ Hung, Chao-Ming @@oth@@ Lin, Li-Wei @@oth@@ Huang, Yung-Hui @@oth@@ |
| publishDateDaySort_date |
2016-01-01T00:00:00Z |
| hierarchy_top_id |
182387127 |
| dewey-sort |
3610 |
| id |
OLC1978155824 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC1978155824</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230714200637.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">160719s2016 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3233/XST-160545</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20160719</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC1978155824</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC1978155824</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)c826-a6b5f2a283dc989707cc143b6c20d6e648118270904aec6f3541dad117f537d90</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0169687420160000024000300353investigatedgeometricalcharacteristicsandimagedens</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">DNB</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Lu, Nan-Han</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Investigated geometrical characteristics and image density of left ventricle of multi-detector computed tomography in early coronary artery disease patients</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Coronary artery disease (CAD) remains the leading cause of death worldwide. Currently, cardiac multi-detector computed tomography (MDCT) is widely used to diagnose CAD. The purpose in this study is to identify informative and useful predictors from left ventricular (LV) in the early CAD patients using cardiac MDCT images. Study groups comprised 42 subjects who underwent a screening health examination, including laboratory testing and cardiac angiography by 64-slice MDCT angiography. Two geometrical characteristics and one image density were defined as shape, size and stiffness on MDCT image. The t-test, logistic regression, and receiver operating characteristic curve were applied to assess and identify the significant predictors. The Kappa statistics was used to exam the agreements with physician's judgments (i.e., Golden of True, GOT). The proposed three characteristics of LV MDCT images are important predictors and risk factors for the early CAD patients. These predictors present over 80% of AUC and higher odds ratio. The Kappa statistics was 0.68 for the combinations of shape and stiffness into logistic regression. The shape, size and stiffness of the left ventricular on MDCT can be used to be the effective indicators in the early CAD patients. Besides, the combinations of shape and stiffness into logistic regression could provide substantial agreement with physician's judgments.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Chen, Tai-Been</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Liu, Kuo-Ying</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hsu, Shih-Yen</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Twan, Wen-Hung</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ding, Hueisch-Jy</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hung, Chao-Ming</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lin, Li-Wei</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Huang, Yung-Hui</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of x-ray science and technology</subfield><subfield code="d">Duluth, Minn. : Academic Press, 1989</subfield><subfield code="g">24(2016), 3, Seite 353-359</subfield><subfield code="w">(DE-627)182387127</subfield><subfield code="w">(DE-600)1203221-9</subfield><subfield code="w">(DE-576)09450377X</subfield><subfield code="x">0895-3996</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:24</subfield><subfield code="g">year:2016</subfield><subfield code="g">number:3</subfield><subfield code="g">pages:353-359</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">http://dx.doi.org/10.3233/XST-160545</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://www.ncbi.nlm.nih.gov/pubmed/27257874</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHY</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-DE-84</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">24</subfield><subfield code="j">2016</subfield><subfield code="e">3</subfield><subfield code="h">353-359</subfield></datafield></record></collection>
|
| author |
Lu, Nan-Han |
| spellingShingle |
Lu, Nan-Han ddc 610 Investigated geometrical characteristics and image density of left ventricle of multi-detector computed tomography in early coronary artery disease patients |
| authorStr |
Lu, Nan-Han |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)182387127 |
| format |
Article |
| dewey-ones |
610 - Medicine & health |
| delete_txt_mv |
keep |
| author_role |
aut |
| collection |
OLC |
| remote_str |
false |
| illustrated |
Not Illustrated |
| issn |
0895-3996 |
| topic_title |
610 DNB Investigated geometrical characteristics and image density of left ventricle of multi-detector computed tomography in early coronary artery disease patients |
| topic |
ddc 610 |
| topic_unstemmed |
ddc 610 |
| topic_browse |
ddc 610 |
| format_facet |
Aufsätze Gedruckte Aufsätze |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
nc |
| author2_variant |
t b c tbc k y l kyl s y h syh w h t wht h j d hjd c m h cmh l w l lwl y h h yhh |
| hierarchy_parent_title |
Journal of x-ray science and technology |
| hierarchy_parent_id |
182387127 |
| dewey-tens |
610 - Medicine & health |
| hierarchy_top_title |
Journal of x-ray science and technology |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)182387127 (DE-600)1203221-9 (DE-576)09450377X |
| title |
Investigated geometrical characteristics and image density of left ventricle of multi-detector computed tomography in early coronary artery disease patients |
| ctrlnum |
(DE-627)OLC1978155824 (DE-599)GBVOLC1978155824 (PRQ)c826-a6b5f2a283dc989707cc143b6c20d6e648118270904aec6f3541dad117f537d90 (KEY)0169687420160000024000300353investigatedgeometricalcharacteristicsandimagedens |
| title_full |
Investigated geometrical characteristics and image density of left ventricle of multi-detector computed tomography in early coronary artery disease patients |
| author_sort |
Lu, Nan-Han |
| journal |
Journal of x-ray science and technology |
| journalStr |
Journal of x-ray science and technology |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
600 - Technology |
| recordtype |
marc |
| publishDateSort |
2016 |
| contenttype_str_mv |
txt |
| container_start_page |
353 |
| author_browse |
Lu, Nan-Han |
| container_volume |
24 |
| class |
610 DNB |
| format_se |
Aufsätze |
| author-letter |
Lu, Nan-Han |
| doi_str_mv |
10.3233/XST-160545 |
| dewey-full |
610 |
| title_sort |
investigated geometrical characteristics and image density of left ventricle of multi-detector computed tomography in early coronary artery disease patients |
| title_auth |
Investigated geometrical characteristics and image density of left ventricle of multi-detector computed tomography in early coronary artery disease patients |
| abstract |
Coronary artery disease (CAD) remains the leading cause of death worldwide. Currently, cardiac multi-detector computed tomography (MDCT) is widely used to diagnose CAD. The purpose in this study is to identify informative and useful predictors from left ventricular (LV) in the early CAD patients using cardiac MDCT images. Study groups comprised 42 subjects who underwent a screening health examination, including laboratory testing and cardiac angiography by 64-slice MDCT angiography. Two geometrical characteristics and one image density were defined as shape, size and stiffness on MDCT image. The t-test, logistic regression, and receiver operating characteristic curve were applied to assess and identify the significant predictors. The Kappa statistics was used to exam the agreements with physician's judgments (i.e., Golden of True, GOT). The proposed three characteristics of LV MDCT images are important predictors and risk factors for the early CAD patients. These predictors present over 80% of AUC and higher odds ratio. The Kappa statistics was 0.68 for the combinations of shape and stiffness into logistic regression. The shape, size and stiffness of the left ventricular on MDCT can be used to be the effective indicators in the early CAD patients. Besides, the combinations of shape and stiffness into logistic regression could provide substantial agreement with physician's judgments. |
| abstractGer |
Coronary artery disease (CAD) remains the leading cause of death worldwide. Currently, cardiac multi-detector computed tomography (MDCT) is widely used to diagnose CAD. The purpose in this study is to identify informative and useful predictors from left ventricular (LV) in the early CAD patients using cardiac MDCT images. Study groups comprised 42 subjects who underwent a screening health examination, including laboratory testing and cardiac angiography by 64-slice MDCT angiography. Two geometrical characteristics and one image density were defined as shape, size and stiffness on MDCT image. The t-test, logistic regression, and receiver operating characteristic curve were applied to assess and identify the significant predictors. The Kappa statistics was used to exam the agreements with physician's judgments (i.e., Golden of True, GOT). The proposed three characteristics of LV MDCT images are important predictors and risk factors for the early CAD patients. These predictors present over 80% of AUC and higher odds ratio. The Kappa statistics was 0.68 for the combinations of shape and stiffness into logistic regression. The shape, size and stiffness of the left ventricular on MDCT can be used to be the effective indicators in the early CAD patients. Besides, the combinations of shape and stiffness into logistic regression could provide substantial agreement with physician's judgments. |
| abstract_unstemmed |
Coronary artery disease (CAD) remains the leading cause of death worldwide. Currently, cardiac multi-detector computed tomography (MDCT) is widely used to diagnose CAD. The purpose in this study is to identify informative and useful predictors from left ventricular (LV) in the early CAD patients using cardiac MDCT images. Study groups comprised 42 subjects who underwent a screening health examination, including laboratory testing and cardiac angiography by 64-slice MDCT angiography. Two geometrical characteristics and one image density were defined as shape, size and stiffness on MDCT image. The t-test, logistic regression, and receiver operating characteristic curve were applied to assess and identify the significant predictors. The Kappa statistics was used to exam the agreements with physician's judgments (i.e., Golden of True, GOT). The proposed three characteristics of LV MDCT images are important predictors and risk factors for the early CAD patients. These predictors present over 80% of AUC and higher odds ratio. The Kappa statistics was 0.68 for the combinations of shape and stiffness into logistic regression. The shape, size and stiffness of the left ventricular on MDCT can be used to be the effective indicators in the early CAD patients. Besides, the combinations of shape and stiffness into logistic regression could provide substantial agreement with physician's judgments. |
| collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_70 GBV_ILN_170 |
| container_issue |
3 |
| title_short |
Investigated geometrical characteristics and image density of left ventricle of multi-detector computed tomography in early coronary artery disease patients |
| url |
http://dx.doi.org/10.3233/XST-160545 http://www.ncbi.nlm.nih.gov/pubmed/27257874 |
| remote_bool |
false |
| author2 |
Chen, Tai-Been Liu, Kuo-Ying Hsu, Shih-Yen Twan, Wen-Hung Ding, Hueisch-Jy Hung, Chao-Ming Lin, Li-Wei Huang, Yung-Hui |
| author2Str |
Chen, Tai-Been Liu, Kuo-Ying Hsu, Shih-Yen Twan, Wen-Hung Ding, Hueisch-Jy Hung, Chao-Ming Lin, Li-Wei Huang, Yung-Hui |
| ppnlink |
182387127 |
| mediatype_str_mv |
n |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| author2_role |
oth oth oth oth oth oth oth oth |
| doi_str |
10.3233/XST-160545 |
| up_date |
2024-07-03T20:47:53.921Z |
| _version_ |
1803592321127677954 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC1978155824</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230714200637.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">160719s2016 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3233/XST-160545</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20160719</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC1978155824</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC1978155824</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)c826-a6b5f2a283dc989707cc143b6c20d6e648118270904aec6f3541dad117f537d90</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0169687420160000024000300353investigatedgeometricalcharacteristicsandimagedens</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">DNB</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Lu, Nan-Han</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Investigated geometrical characteristics and image density of left ventricle of multi-detector computed tomography in early coronary artery disease patients</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Coronary artery disease (CAD) remains the leading cause of death worldwide. Currently, cardiac multi-detector computed tomography (MDCT) is widely used to diagnose CAD. The purpose in this study is to identify informative and useful predictors from left ventricular (LV) in the early CAD patients using cardiac MDCT images. Study groups comprised 42 subjects who underwent a screening health examination, including laboratory testing and cardiac angiography by 64-slice MDCT angiography. Two geometrical characteristics and one image density were defined as shape, size and stiffness on MDCT image. The t-test, logistic regression, and receiver operating characteristic curve were applied to assess and identify the significant predictors. The Kappa statistics was used to exam the agreements with physician's judgments (i.e., Golden of True, GOT). The proposed three characteristics of LV MDCT images are important predictors and risk factors for the early CAD patients. These predictors present over 80% of AUC and higher odds ratio. The Kappa statistics was 0.68 for the combinations of shape and stiffness into logistic regression. The shape, size and stiffness of the left ventricular on MDCT can be used to be the effective indicators in the early CAD patients. Besides, the combinations of shape and stiffness into logistic regression could provide substantial agreement with physician's judgments.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Chen, Tai-Been</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Liu, Kuo-Ying</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hsu, Shih-Yen</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Twan, Wen-Hung</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ding, Hueisch-Jy</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hung, Chao-Ming</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lin, Li-Wei</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Huang, Yung-Hui</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of x-ray science and technology</subfield><subfield code="d">Duluth, Minn. : Academic Press, 1989</subfield><subfield code="g">24(2016), 3, Seite 353-359</subfield><subfield code="w">(DE-627)182387127</subfield><subfield code="w">(DE-600)1203221-9</subfield><subfield code="w">(DE-576)09450377X</subfield><subfield code="x">0895-3996</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:24</subfield><subfield code="g">year:2016</subfield><subfield code="g">number:3</subfield><subfield code="g">pages:353-359</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">http://dx.doi.org/10.3233/XST-160545</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://www.ncbi.nlm.nih.gov/pubmed/27257874</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHY</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-DE-84</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">24</subfield><subfield code="j">2016</subfield><subfield code="e">3</subfield><subfield code="h">353-359</subfield></datafield></record></collection>
|
| score |
7.401026 |