Automatic centerline extraction of coronary arteries in coronary computed tomographic angiography

Coronary computed tomographic angiography (CCTA) is a non-invasive imaging modality for the visualization of the heart and coronary arteries. To fully exploit the potential of the CCTA datasets and apply it in clinical practice, an automated coronary artery extraction approach is needed. The purpose of this paper is to present and validate a fully automatic centerline extraction algorithm for coronary arteries in CCTA images. The algorithm is based on an improved version of Frangi’s vesselness filter which removes unwanted step-edge responses at the boundaries of the cardiac chambers. Building upon this new vesselness filter, the coronary artery extraction pipeline extracts the centerlines of main branches as well as side-branches automatically. This algorithm was first evaluated with a standardized evaluation framework named Rotterdam Coronary Artery Algorithm Evaluation Framework used in the MICCAI Coronary Artery Tracking challenge 2008 (CAT08). It includes 128 reference centerlines which were manually delineated. The average overlap and accuracy measures of our method were 93.7% and 0.30 mm, respectively, which ranked at the 1st and 3rd place compared to five other automatic methods presented in the CAT08. Secondly, in 50 clinical datasets, a total of 100 reference centerlines were generated from lumen contours in the transversal planes which were manually corrected by an expert from the cardiology department. In this evaluation, the average overlap and accuracy were 96.1% and 0.33 mm, respectively. The entire processing time for one dataset is less than 2 min on a standard desktop computer. In conclusion, our newly developed automatic approach can extract coronary arteries in CCTA images with excellent performances in extraction ability and accuracy

Novel iodinated tracers, MIBG and BMIPP, for nuclear cardiology

With the rapid growth of molecular biology, in vivo imaging of such molecular process (i.e., molecular imaging) has been well developed. The molecular imaging has been focused on justifying advanced treatments and for assessing the treatment effects. Most of molecular imaging has been developed using PET camera and suitable PET radiopharmaceuticals. However, this technique cannot be widely available and we need alternative approach. 123I-labeled compounds have been also suitable for molecular imaging using single-photon computed tomography (SPECT) 123I-labeled meta-iodobenzylguanidine (MIBG) has been used for assessing severity of heart failure and prognosis. In addition, it has a potential role to predict fatal arrhythmia, particularly for those who had and are planned to receive implantable cardioverter-defibrillator treatment. 123I-beta-methyl-iodophenylpentadecanoic acid (BMIPP) plays an important role for identifying ischemia at rest, based on the unique capability to represent persistent metabolic alteration after recovery of ischemia, so called ischemic memory. Since BMIPP abnormalities may represent severe ischemia or jeopardized myocardium, it may permit risk analysis in CAD patients, particularly for those with chronic kidney disease and/or hemodialysis patients. This review will discuss about recent development of these important iodinated compounds

Quantitative Gated SPECT-Derived Phase Analysis on Gated Myocardial Perfusion SPECT Detects Left Ventricular Dyssynchrony and Predicts Response to Cardiac Resynchronization Therapy

The significance of left ventricular (LV) dyssynchrony for the prediction of response to cardiac resynchronization therapy (CRT) has been demonstrated. Parameters reflecting LV dyssynchrony (phase SD, histogrambandwidth) can be derived from gated myocardial perfusion SPECT (GMPS) using phase analysis. The feasibility of LV dyssynchrony assessment with phase analysis on GMPS using Quantitative Gated SPECT (QGS) software has not been demonstrated in patients undergoing CRT. The aim of the present study was to validate the QGS algorithm for phase analysis on GMPS in a direct comparison with echocardiography using tissue Doppler imaging (TDI) for LV dyssynchrony assessment. Also, prediction of response to CRT using GMPS and phase analysis was evaluated. Methods: Patients (n = 40) with severe heart failure (New York Heart Association class III-IV), an LV ejection fraction of no more than 35%, and a QRS complex greater than or equal to 120 ms were evaluated for LV dyssynchrony using GMPS and echocardiography with TDI. At baseline and after 6 mo of CRT, clinical status, LV volumes, and LV ejection fraction were evaluated. Patients with functional improvement were classified as CRT responders. Results: Both histogram bandwidth (r = 0.69, r(2) = 0.48, SEE = 25.4, P < 0.01) and phase SD (r = 0.65, r(2) = 0.42, SEE = 26.8, P < 0.01) derived from GMPS correlated significantly with TDI for assessment of LV dyssynchrony. At baseline, CRT responders showed a significantly larger histogram bandwidth (94 degrees +/- 23 degrees vs. 68 degrees +/- 21 degrees, P < 0.01) and a larger phase SD (26 degrees +/- 6 degrees vs. 18 degrees +/- 5 degrees, P < 0.01) than did nonresponders. Receiver-operating-characteristic curve analysis identified an optimal cutoff value of 72.5 degrees for histogram bandwidth to predict CRT response, yielding a sensitivity of 83% and a specificity of 81%. For phase SD, sensitivity and specificity similar to those for histogram bandwidth were obtained at a cutoff value of 19.6 degrees. Conclusion: QGS phase analysis on GMPS correlated significantly with TDI for the assessment of LV dyssynchrony. Moreover, a high accuracy for prediction of response to CRT was obtained using either histogram bandwidth or phase SD