A framework to measure myocardial extracellular volume fraction using dual‐phase low dose CT images. Issue 10 (10th September 2013)

• Record Type: Journal Article
• Authors: Liu, Yixun; Liu, Songtao; Nacif, Marcelo S.; Sibley, Christopher T.; Bluemke, David A.; Summers, Ronald M.; Yao, Jianhua
• Is Part Of: Medical physics. Volume 40:Issue 10(2013)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2013-09-10
• Subjects: Computed tomography -- Cell processes -- Contrast -- Registration -- Segmentation; cardiology -- cellular biophysics -- computerised tomography -- image registration -- image segmentation -- medical image processing; extracellular volume fraction -- low dose -- cardiac CT -- deformable model -- modeling; Computerised tomographs -- Biological material, e.g. blood, urine; Haemocytometers -- Digital computing or data processing equipment or methods, specially adapted for specific applications -- Image data processing or generation, in general; Computed tomography -- Medical imaging -- Heart -- Tissues -- Medical image segmentation -- Medical image contrast -- Visualization -- Medical image quality -- Statistical analysis -- Heart disease; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1118/1.4819936
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: : Myocardial extracellular volume fraction (ECVF) is a surrogate imaging biomarker of diffuse myocardial fibrosis, a hallmark of pathologic ventricular remodeling. Low dose cardiac CT is emerging as a promising modality to detect diffuse interstitial myocardial fibrosis due to its fast acquisition and low radiation; however, the insufficient contrast in the low dose CT images poses great challenge to measure ECVF from the image. Methods: : To deal with this difficulty, the authors present a complete ECVF measurement framework including a point‐guided myocardial modeling, a deformable model‐based myocardium segmentation, nonrigid registration of pre‐ and post‐CT, and ECVF calculation. Results: : The proposed method was evaluated on 20 patients by two observers. Compared to the manually delineated reference segmentations, the accuracy of our segmentation in terms of true positive volume fraction (TPVF), false positive volume fraction (FPVF), and average surface distance (ASD), were 92.18% ± 3.52%, 0.31% ± 0.10%, 0.69 ± 0.14 mm, respectively. The interobserver variability measured by concordance correlation coefficient regarding TPVF, FPVF, and ASD were 0.95, 0.90, 0.94, respectively, demonstrating excellent agreement. Bland‐Altman method showed 95% limits of agreement between ECVF at CT and ECVF at MR. Conclusions: : The proposed framework demonstrates its efficiency, accuracy, and noninvasiveness in ECVF measurement and dramatically advances the ECVF at cardiac CT toward its clinical use.