PURPOSE: To investigate the potential of a new detection tool for multislice CT (MSCT) coronary angiography with automatic display of curved multiplanar reformations and orthogonal cross-sections. MATERIALS AND METHODS: Thirty-five patients were consecutively enrolled in a prospective intention-to-diagnose study and examined using a MSCT scanner with 16 x 0.5 mm detector collimation and 400 ms gantry rotation time (Aquilion, Toshiba). A multisegment algorithm using up to four segments was applied for ECG-gated reconstruction. Automatic and manual detection of coronary arteries was conducted using the coronary artery CT protocol of a workstation (Vitrea 2, Version 3.3, Vital Images) to detect significant stenoses (> or = 50 %) in all segments of > or = 1.5 mm in diameter. Each detection tool was used by one reader who was blinded to the results of the other detection method and the results of conventional coronary angiography. RESULTS: The overall sensitivity, specificity, nondiagnostic rate, and accuracy of the automatic and manual approach were 90 vs. 94 %, 89 vs. 84 %, 6 vs. 6 %, and 89 vs. 88 %, respectively (p = n. s.). The vessel length detected with the automatic and manual approach were highly correlated for the left main/left anterior descending (143 +/- 30 vs. 146 +/- 24 mm, r = 0.923, p < 0.001), left circumflex (94 +/- 35 vs. 93 +/- 33 mm, r = 0.945, p < 0.001), and right coronary artery (145 +/- 36 vs. 144 +/- 37 mm, r = 0.925, p < 0.001). The time required to create reformations along the coronary arteries was significantly shorter with the automatic tool compared to the manual approach (203 +/- 77 vs. 391 +/- 104 sec, p < 0.005). In 90 % of the coronary branches automatic detection required less time than the manual approach. CONCLUSION: Automatic coronary vessel detection is feasible and reduces the time required to create reformations by a factor of approximately two without deteriorating the diagnostic accuracy.
PURPOSE: To investigate the potential of a new detection tool for multislice CT (MSCT) coronary angiography with automatic display of curved multiplanar reformations and orthogonal cross-sections. MATERIALS AND METHODS: Thirty-five patients were consecutively enrolled in a prospective intention-to-diagnose study and examined using a MSCT scanner with 16 x 0.5 mm detector collimation and 400 ms gantry rotation time (Aquilion, Toshiba). A multisegment algorithm using up to four segments was applied for ECG-gated reconstruction. Automatic and manual detection of coronary arteries was conducted using the coronary artery CT protocol of a workstation (Vitrea 2, Version 3.3, Vital Images) to detect significant stenoses (> or = 50 %) in all segments of > or = 1.5 mm in diameter. Each detection tool was used by one reader who was blinded to the results of the other detection method and the results of conventional coronary angiography. RESULTS: The overall sensitivity, specificity, nondiagnostic rate, and accuracy of the automatic and manual approach were 90 vs. 94 %, 89 vs. 84 %, 6 vs. 6 %, and 89 vs. 88 %, respectively (p = n. s.). The vessel length detected with the automatic and manual approach were highly correlated for the left main/left anterior descending (143 +/- 30 vs. 146 +/- 24 mm, r = 0.923, p < 0.001), left circumflex (94 +/- 35 vs. 93 +/- 33 mm, r = 0.945, p < 0.001), and right coronary artery (145 +/- 36 vs. 144 +/- 37 mm, r = 0.925, p < 0.001). The time required to create reformations along the coronary arteries was significantly shorter with the automatic tool compared to the manual approach (203 +/- 77 vs. 391 +/- 104 sec, p < 0.005). In 90 % of the coronary branches automatic detection required less time than the manual approach. CONCLUSION: Automatic coronary vessel detection is feasible and reduces the time required to create reformations by a factor of approximately two without deteriorating the diagnostic accuracy.
Authors: Marco A S Cordeiro; Albert C Lardo; Marcelo S V Brito; Miguel A Rosário Neto; Maria H A Siqueira; José R Parga; Luiz F Avila; José A F Ramires; João A C Lima; Carlos E Rochitte Journal: Int J Cardiovasc Imaging Date: 2006-03-15 Impact factor: 2.357
Authors: Anja J Reimann; Ilias Tsiflikas; Harald Brodoefel; Michael Scheuering; Daniel Rinck; Andreas F Kopp; Claus D Claussen; Martin Heuschmid Journal: Int J Cardiovasc Imaging Date: 2008-09-28 Impact factor: 2.357
Authors: Julie M Miller; Marc Dewey; Andrea L Vavere; Carlos E Rochitte; Hiroyuki Niinuma; Armin Arbab-Zadeh; Narinder Paul; John Hoe; Albert de Roos; Kunihiro Yoshioka; Pedro A Lemos; David E Bush; Albert C Lardo; John Texter; Jeffery Brinker; Christopher Cox; Melvin E Clouse; João A C Lima Journal: Eur Radiol Date: 2008-11-08 Impact factor: 5.315