TY - JOUR
T1 - Reliable and Accurate Calcium Volume Measurement in Coronary Artery Using Intravascular Ultrasound Videos
AU - Araki, Tadashi
AU - Banchhor, Sumit K.
AU - Londhe, Narendra D.
AU - Ikeda, Nobutaka
AU - Radeva, Petia
AU - Shukla, Devarshi
AU - Saba, Luca
AU - Balestrieri, Antonella
AU - Nicolaides, Andrew
AU - Shafique, Shoaib
AU - Laird, John R.
AU - Suri, Jasjit S.
PY - 2016/3/1
Y1 - 2016/3/1
N2 - Quantitative assessment of calcified atherosclerotic volume within the coronary artery wall is vital for cardiac interventional procedures. The goal of this study is to automatically measure the calcium volume, given the borders of coronary vessel wall for all the frames of the intravascular ultrasound (IVUS) video. Three soft computing fuzzy classification techniques were adapted namely Fuzzy c-Means (FCM), K-means, and Hidden Markov Random Field (HMRF) for automated segmentation of calcium regions and volume computation. These methods were benchmarked against previously developed threshold-based method. IVUS image data sets (around 30,600 IVUS frames) from 15 patients were collected using 40 MHz IVUS catheter (Atlantis® SR Pro, Boston Scientific®, pullback speed of 0.5 mm/s). Calcium mean volume for FCM, K-means, HMRF and threshold-based method were 37.84 ± 17.38 mm(3), 27.79 ± 10.94 mm(3), 46.44 ± 19.13 mm(3) and 35.92 ± 16.44 mm(3) respectively. Cross-correlation, Jaccard Index and Dice Similarity were highest between FCM and threshold-based method: 0.99, 0.92 ± 0.02 and 0.95 + 0.02 respectively. Student's t-test, z-test and Wilcoxon-test are also performed to demonstrate consistency, reliability and accuracy of the results. Given the vessel wall region, the system reliably and automatically measures the calcium volume in IVUS videos. Further, we validated our system against a trained expert using scoring: K-means showed the best performance with an accuracy of 92.80%. Out procedure and protocol is along the line with method previously published clinically.
AB - Quantitative assessment of calcified atherosclerotic volume within the coronary artery wall is vital for cardiac interventional procedures. The goal of this study is to automatically measure the calcium volume, given the borders of coronary vessel wall for all the frames of the intravascular ultrasound (IVUS) video. Three soft computing fuzzy classification techniques were adapted namely Fuzzy c-Means (FCM), K-means, and Hidden Markov Random Field (HMRF) for automated segmentation of calcium regions and volume computation. These methods were benchmarked against previously developed threshold-based method. IVUS image data sets (around 30,600 IVUS frames) from 15 patients were collected using 40 MHz IVUS catheter (Atlantis® SR Pro, Boston Scientific®, pullback speed of 0.5 mm/s). Calcium mean volume for FCM, K-means, HMRF and threshold-based method were 37.84 ± 17.38 mm(3), 27.79 ± 10.94 mm(3), 46.44 ± 19.13 mm(3) and 35.92 ± 16.44 mm(3) respectively. Cross-correlation, Jaccard Index and Dice Similarity were highest between FCM and threshold-based method: 0.99, 0.92 ± 0.02 and 0.95 + 0.02 respectively. Student's t-test, z-test and Wilcoxon-test are also performed to demonstrate consistency, reliability and accuracy of the results. Given the vessel wall region, the system reliably and automatically measures the calcium volume in IVUS videos. Further, we validated our system against a trained expert using scoring: K-means showed the best performance with an accuracy of 92.80%. Out procedure and protocol is along the line with method previously published clinically.
KW - Accuracy
KW - Atherosclerosis
KW - calcium volume
KW - Coronary arteries
KW - Interventional cardiology
KW - IVUS
KW - Performance
KW - Reliability
KW - Soft computing
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U2 - 10.1007/s10916-015-0407-z
DO - 10.1007/s10916-015-0407-z
M3 - Article
C2 - 26643081
AN - SCOPUS:84949232347
VL - 40
SP - 51
JO - Journal of Medical Systems
JF - Journal of Medical Systems
SN - 0148-5598
IS - 3
ER -