Manual versus Automated Carotid Artery Plaque Component Segmentation in High and Lower Quality 3.0 Tesla MRI Scans

<div><p>Purpose</p><p>To study the interscan reproducibility of manual versus automated segmentation of carotid artery plaque components, and the agreement between both methods, in high and lower quality MRI scans.</p><p>Methods</p><p>24 patients with 30–70% carotid artery stenosis were planned for 3T carotid MRI, followed by a rescan within 1 month. A multicontrast protocol (T1w,T2w, PDw and TOF sequences) was used. After co-registration and delineation of the lumen and outer wall, segmentation of plaque components (lipid-rich necrotic cores (LRNC) and calcifications) was performed both manually and automated. Scan quality was assessed using a visual quality scale.</p><p>Results</p><p>Agreement for the detection of LRNC (<i>Cohen’s</i> kappa (<i>k)</i> is 0.04) and calcification (<i>k</i> = 0.41) between both manual and automated segmentation methods was poor. In the high-quality scans (visual quality score ≥ 3), the agreement between manual and automated segmentation increased to <i>k</i> = <i>0</i>.55 and <i>k</i> = 0.58 for, respectively, the detection of LRNC and calcification larger than 1 mm². Both manual and automated analysis showed good interscan reproducibility for the quantification of LRNC (intraclass correlation coefficient (ICC) of 0.94 and 0.80 respectively) and calcified plaque area (ICC of 0.95 and 0.77, respectively).</p><p>Conclusion</p><p>Agreement between manual and automated segmentation of LRNC and calcifications was poor, despite a good interscan reproducibility of both methods. The agreement between both methods increased to moderate in high quality scans. These findings indicate that image quality is a critical determinant of the performance of both manual and automated segmentation of carotid artery plaque components.</p></div

Representative images of manual and automated segmentation of LRNC and calcifications.

<p>Representative images of the manual and automated segmentation of a calcified plaque area and a lipid-rich necrotic core (LRNC) using a multicontrast MRI protocol of the carotid artery. Shown are all the individual MRI sequences (T1w,PDw,T2w,TOF), as well as the manual and automated analysis. Lumen contours were delineated in red for both methods, and outer wall contours were delineated in green for manual segmentation, and light blue for automated segmentation. Calcified plaque areas were coloured orange in manual segmentation, and delineated white in automated segmentation. LRNCs were delineated yellow in both manual and automated segmentation. In these examples, both methods agree on the identification of a large calcified plaque area (left example) and large LRNC (right example). Please also note the identification of three small LRNC areas using automated segmentation (*), which are not detected by manual segmentation.</p

Interscan reproducibility of quantification of plaque components using manual and automated segmentation.

<p>Interscan reproducibility of quantification of plaque components using manual and automated segmentation.</p

Post-hoc manual analysis of patients with a mismatch in the detection of LRNC and calcifications by manual and automated analysis.

<p>Post-hoc manual analysis of patients with a mismatch in the detection of LRNC and calcifications by manual and automated analysis.</p

Agreement between manual and automated detection of plaque components.

<p>Agreement between the detection of LRNC- and calcification- containing plaques by manual and automated analysis. Cohen’s kappa values for agreement between manual and automated analysis are shown for all plaque components in all scans; plaque components > 1 mm² in all scans; and plaque components > 1 mm² in high quality scans only.</p

Open and closed segmented calcified surface area measurements for HR and LR carotid arterial wall measurements.

<p>* = p-value for paired t-test between HR scan and LR scan.</p><p>† = p-value for paired t-test between HR rescan and LR rescan using the closed segmentation method.</p><p>‡ = p-value for Levene’s test between HR and LR measurements for the corresponding segmentation. HR = high resolution; LR = low resolution; ICC = intraclass correlation coefficient; CV = coefficient of variation; SD = standard deviation.</p><p>Data are presented as number with percentage or mean with SD. ICCs are given with the corresponding 95% confidence interval.</p

Open and closed fibrous cap thickness measurements for HR and LR carotid arterial wall measurements.

<p>* = p-value for paired t-test between HR scan and LR scan.</p><p>† = p-value for paired t-test between HR rescan and LR rescan using the closed segmentation method.</p><p>‡ = p-value for Levene’s test between HR and LR measurements for the corresponding segmentation. HR = high resolution; LR = low resolution; ICC = intraclass correlation coefficient; SD = standard deviation.</p><p>Data are presented as mean with ± SD. ICCs are given with the corresponding 95% confidence interval.</p

Scan parameters for the HR and LR carotid arterial wall dimension measurements.

<p>* Scan times at heart rate of 60 min^-1</p><p>HR = high resolution; LR = low resolution; TSE = turbo spin-echo, FFE = fast field echo, FOV = field of view, DIR = double inversion-recovery, NEX = number of excitations.</p

Number of identified carotid plaque components with corresponding scan-rescan mismatch.

<p>Data are presented as number.</p

Within-reader and between-reader reproducibility for the HR and LR carotid arterial wall component measurements.

<p>Data are presented as mean with (95% CI). Last column contains p-value for Levene’s test between HR and LR measurements. HR = high resolution; LR = low resolution.</p