Quantification of serial changes in plaque burden using multi-detector computed tomography in experimental atherosclerosis

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1 Atherosclerosis 202 (2009) Quantification of serial changes in plaque burden using multi-detector computed tomography in experimental atherosclerosis Borja Ibanez a,b, Giovanni Cimmino a,b, Juan Bénézet-Mazuecos a,b, Carlos G. Santos-Gallego a,b, Antonio Pinero a,b, Susanna Prat-González b, Walter S. Speidl a,b, Valentin Fuster b, Mario J. García b, Javier Sanz b, Juan J. Badimon a,b, a Cardiovascular Biology Research Laboratory, Mount Sinai School of Medicine, New York, NY, USA b The Zena and Michael A. Wiener Cardiovascular Institute, Mount Sinai School of Medicine, New York, NY, USA Received 11 January 2008; received in revised form 28 February 2008; accepted 20 March 2008 Available online 30 March 2008 Abstract Assessment of changes in plaque volume is increasingly used as a surrogate-endpoint in clinical trials testing the efficacy of antiatherosclerotic interventions. Multi-detector computed tomography (MDCT) can detect and quantify non-calcified atherosclerotic plaques, but its ability to monitor changes in plaque volume has not yet been tested. We sought to test the ability of MDCT to detect and quantify serial changes in atheroma burden in comparison with magnetic resonance imaging (MRI). Methods: Rabbits (n = 12) with experimentally induced abdominal atherosclerosis were randomized to receive a plaque-regressing agent (recombinant apoa-i Milano, n = 8) or placebo (n = 4). All animals underwent two 64-slice MDCT angiography and MRI studies (pre- and post-treatment). The primary endpoint was the change in plaque burden (defined as vessel wall volume in the 5 cm distal to the left renal artery) between pre- and post-treatment MDCT in comparison with MRI. Results: MDCT detected a significant decrease in plaque burden caused by recombinant apoa-i Milano (464 [ ] to 405 [ ] mm 3, p = 0.03) that was confirmed by MRI (324 [ ] to 298 [ ] mm 3, p = 0.03). No significant effect was noted in the placebo group either by MDCT or MRI. There were strong correlations between both modalities for the quantification of plaque burden (r = 0.750, p < 0.001) and change in plaque burden (r = 0.657, p = 0.020). MDCT overestimated plaque burden compared to MRI. On MDCT, the mean interobserver variability for plaque burden was 2.5 ± 0.4%. Conclusions: In an animal model of atherosclerosis, MDCT accurately documented serial changes in aortic plaque burden, demonstrating good correlation and agreement with MRI-derived measurements and low interobserver variability Elsevier Ireland Ltd. All rights reserved. Keywords: Atherosclerosis; Magnetic resonance imaging; MDCT; Plaque; Plaque regression 1. Introduction Until recently, atherogenesis was envisioned as a progressive cumulative phenomenon with continuous lipid deposition. However, it is well known today that anti- Corresponding author at: Cardiovascular Biology Research Laboratory, Mount Sinai School of Medicine. One Gustave L. Levy Place, Box 1030, New York, NY 10029, USA. Tel.: ; fax: address: juan.badimon@mssm.edu (J.J. Badimon). atherogenic therapies are able to halter progression [1,2] or even cause regression of atherosclerotic disease [3 7]. One of these therapies, recombinant apoa-i Milano (rapoa-i M ), has been consistently associated with rapid reduction in the extent of atherosclerosis [8,9]. We have recently shown, in a study employing magnetic resonance imaging (MRI), that the administration rapoa-i M induces marked plaque regression after only 4 days of treatment [10]. MRI has been extensively validated for the non-invasive assessment of serial changes in atherosclerotic extent [1,4,7,11,12]. In addition, it has been /$ see front matter 2008 Elsevier Ireland Ltd. All rights reserved. doi: /j.atherosclerosis

2 186 B. Ibanez et al. / Atherosclerosis 202 (2009) shown to have very high inter-study reproducibility for plaque volume quantification [13]. Although there is no direct proof that atheroma regression leads to a reduction in clinical events, extensive indirect evidence strongly suggests this association [14,15]. Therefore, current clinical trials testing the efficacy of anti-atherogenic therapies frequently use imaging-based surrogate endpoints. Imaging modalities employed to monitor changes in atheroma burden include intravascular ultrasound (IVUS) [2,6], MRI [1,4,7], and ultrasound determination of arterial intima media thickening [16]. There is growing interest in the use of multi-detector computed tomography (MDCT) for atherosclerosis imaging due to its high resolution, short imaging time, and ability to depict not only arterial calcification and luminal stenosis but also the presence and morphology of non-stenotic, non-calcified plaques, even in the coronary arteries [17 20]. Hence, MDCT potentially represents an attractive alternative modality to non-invasively track changes in atheroma burden. However, to date there is no available data on its utility to accurately monitor atherosclerosis progression/regression. The aim of the current study was to determine whether MDCT is able to detect and quantify, in comparison with MRI, the changes in atheroma burden associated with the administration of rapoa-i M in an animal model of experimental atherosclerosis. 2. Methods 2.1. Study design Abdominal aortic atherosclerosis was induced in rabbits (n = 12) by a combination of 9 months of 0.2% cholesterolenriched diet plus 2 aortic balloon denudations, as previously described [10,11]. At the end of atherosclerosis induction, all animals underwent baseline (pre-treatment) MDCT and MRI studies (with state-of-the-art equipments: 64-Slice MDCT and 1.5 T magnet) for plaque burden quantification. Animals were subsequently randomized (2:1) to receive 2 intravenous injections, 4 days apart, of 75 mg/kg of rapoa-i M (ETC- 216, Pfizer. n = 8) or an equal volume of placebo (n =4)[10]. Four days after the last dose (8 days after the initial imaging studies), final (post-treatment) MDCT and MRI studies were performed. Study protocol is shown in Supplementary Fig. 1. The study protocol was approved by the institutional animal research committee, and all animals received humane care in compliance with the Guide for the Care and Use of Laboratory Animals MDCT protocol MDCT studies were performed with a 64-Slice MDCT scanner (Sensation 64, Siemens Medical Solutions, Forchheim, Germany). For the scans, the rabbits were sedated by intramuscular injection of ketamine (30 mg/kg) and xylazine (2.2 mg/kg). An intravenous access was placed in the central vein of the rabbits ear with a 21-gauge line. Before initiation of the protocol, different dilutions of the nonionic, low-osmolar, iodinated contrast agent ioversol (Optiray 370, Mallinckrodt Inc.) were tested in an animal not included in the study group. The purpose was to determine the optimal concentration leading to intra-aortic lumen attenuation similar to that routinely obtained in clinical human MDCT angiography examinations ( 300 Hounsfield units). The determined mixture subsequently used in this study was a 1:2 dilution of the contrast agent with saline, yielding a concentration of mg of iodine per ml. The animals were imaged in the craniocaudal direction and in the supine position. An initial localizer image served to confirm an adequate position of the animal and prescribe the angiographic study covering the abdominal aorta. The contrast dilution was then infused (8 ml at a rate of 0.5 ml/s) and scanning was initiated after a fixed delay of 10 s. Imaging parameters were as follows: 120 kv, 180 ma, rotation time 330 ms, collimation, and pitch Axial images (3-mm thickness with no overlap) were reconstructed using a sharp kernel (B46f), a field of view of 160 mm 160 mm and a matrix, resulting in an in-plane spatial resolution of 400 m 400 m [21].A reconstructed slice thickness of 3 mm was chosen to match the MRI images (below) MRI protocol MRI studies were performed in a 1.5 T magnet (Magnetom Sonata, Siemens Medical Solutions, Erlangen, Germany) using a conventional extremity coil. Gradient-echo coronal and sagittal images were used to localize the abdominal aorta, and sequential axial images (3-mm thickness segments with no gap) of the abdominal aorta were obtained using a fast spin-echo sequence with an in-plane resolution of 230 m 230 m (proton density weighted [PDW]: TR/TE, 2300/5.6 ms; T2 weighted [T2W]: TR/TE, 2300/62 ms; field of view 120 mm 12 mm; matrix ; echo train length = 8; signal averages = 4). Fat suppression and flow saturation pulses were used as previously reported [11,22] MDCT and MRI data analysis The 17 consecutive 3-mm slices ( 5 cm) immediately distal to the left renal artery were pre-specified as the area of study for the pre- and post-treatment MDCT and MRI studies. The initial and final MDCT and MRI images were matched for anatomic position by using distances from the renal arteries and iliac bifurcation as previously described [17] (see Fig. 1). The MDCT images were transferred to a dedicated workstation (Aquarius, Terarecon Inc) for analysis. A region of interest ( 3mm 2 ) was placed in the centre of the vessel in each of the slices and the average attenuation was recorded. The mean luminal attenuation in each study was calculated by averaging the values of the 17 indi-

3 B. Ibanez et al. / Atherosclerosis 202 (2009) Fig. 1. Matching of axial images obtained with both modalities. Matching of individual 3-mm segments in MRI (panels A and C) and MDCT (panels B and D). Left renal (panels A and B, arrows) was used as a landmark point for the segmental matching. Panels C and D correspond to the segments located 5 levels below (15 mm) the left renal. vidual slices. The display setting used for lumen and total vessel area quantification was determined from a subset of six animals (selected at random from the study population). In each animal, four consecutive 3-mm slices located above the left renal artery (outside the area of study) were selected for this purpose and analyzed simultaneously with the matching MRI images. The image display settings were then manipulated so that the lumen and vessel wall areas of each MDCT section matched the corresponding MRI image. The values for window width and level of every section were recorded and related to the mean intensity within the lumen. The results of this analysis were selected as the optimal setting to detect outer vessel boundaries (total vessel area) and corresponded to a window width and level of 140% and 70% of the mean luminal attenuation, respectively. The optimal setting for delineation of the lumen was obtained by keeping the window level at 70% of the mean intensity within the lumen and reducing the window width to 1. This combination generates a black and white image for the detection of lumen area. An investigator not involved in the actual comparative analysis performed these initial measurements. Lumen and vessel wall boundaries in each of the 17 axial sections were then manually traced by 2 independent investigators blinded to the time of the study, the treatment arm and the MRI results. The average of the two measurements was used for analysis. The MRI studies were transferred to a Macintosh computer system (Apple) for analysis. Cross-sectional areas of the lumen and vessel wall were determined by a third blinded researcher using by a validated semi-automatic quantification method programmed on ImageJ (National Institutes of Health; Bethesda, Maryland) [22]. Final values were the result of averaging PDW and T2W measurements. For both MDCT and MRI, the volume of the vessel wall (plaque volume, mm 3 ) of each 3-mm slice was calculated as: (total vessel area lumen area) 3. The total vessel wall volume (plaque burden, mm 3 ) was quantified by adding the plaque volumes of each of the 17 slices within the 5-cm segment of interest. The primary endpoint of the study was the change in plaque burden between pre- and post-treatment MDCT in comparison with MRI. A secondary analysis included the change in volume in the most diseased lesion (MDL) of each animal, defined as the largest plaque volume in 3 consecutive slices on the baseline MRI Statistical analysis Continuous variables are expressed as median (interquartile range) unless otherwise noted. Statistical comparisons were made by Wilcoxon and Mann Whitney tests. To calculate the correlation of variables, Spearman s rank correlation

4 188 B. Ibanez et al. / Atherosclerosis 202 (2009) coefficients were used. The limits of agreement for plaque volume quantification between modalities or observers were quantified with the Bland-Altman method. A value of p < 0.05 (two-tailed) was considered statistically significant. All analyses were performed with the statistical software package SPSS 15.0 (SPSS Inc., Chicago, IL, USA). 3. Results MDCT and MRI were performed in all animals without complications. Total acquisition times in MDCT and MRI were approximately 10 s and 30 min, respectively. Preparation time was similar for both techniques, approximately 3 min MDCT and MRI plaque measurements Taken together both pre- and post-treatment measurements for each imaging modality, there were good correlations between MDCT and MRI for the quantification of plaque burden (r = 0.750, p < 0.001) and MDL volume (r = 0.522, p = 0.009). In comparison to MRI, MDCT provided larger values for both plaque burden and MDL volume: 436 ( ) mm 3 versus 330 ( ) mm 3 (p = 0.01) and 87 (71 101) mm 3 versus 64 (55 92) mm 3 (p = 0.03), respectively. The results of the Bland Altman test confirmed this overestimation, with a mean bias of 85 mm 3 (limits of agreement 287/ 117 mm 3 ) for plaque burden and 20 mm 3 (limits of agreement 62/ 22 mm 3 ) for MDL volume Effect of treatment on plaque volume assessed by MDCT and MRI The results of plaque burden and MDL the quantification pre- and post-treatment are displayed in Table 1. Both by MDCT and MRI, there was significant regression, in plaque burden and MDL volume in animals receiving rapoa-i M, while in the placebo group no significant changes were documented. Fig. 2 shows an example of plaque regression in an animal receiving rapoa-i M. There were strong correlations between MDCT- and MRI-determined serial changes in plaque burden (r = 0.657, p = 0.020) and MDL volume (r = 0.699, p = 0.011), see Fig. 3. Bland-Altman analyses showed also good agreement between both techniques for changes in plaque burden (mean Fig. 2. Plaque regression assessed by MDCT an animal receiving apoa-i Milano. MDCT axial sections acquired pre- (panels A and B) and post-treatment (panels C and D) in an animal receiving recombinant ApoA-I Milano treatment. The 2 axial sections correspond to the same level of the abdominal aorta. Total vessel (A and C) and lumen (B and D) contours have been traced using the pre-specified display settings (see text). Segmental plaque volume on pre-treatment study was 48 mm 3. After 2 doses of apoa-i Milano, plaque volume quantified in this segment was 35.4 mm 3.

5 B. Ibanez et al. / Atherosclerosis 202 (2009) Table 1 Pre-and post-treatment plaque burden and most diseased lesion volumes by MRI and MDCT in both treatment arms. MRI MDCT Plaque burden MDL Plaque burden MDL Pre-treatment Placebo 346 ( ) 84 (53 113) 484 ( ) 84 (68 127) rapoa-i Milano 324 ( ) 64 (58 88) 464 ( ) 97 (81 102) Post-treatment Placebo 346 ( ); p = NS 82 (57 113); p = NS 447 ( ); p = NS 80 (67 114); p =NS rapoa-i Milano 298 ( ); p = (54 83); p = ( ); p = (71 93); p = 0.02 Data is expressed as median (interquartile range) in mm 3. MDL: most diseased lesion; p values reported are for the difference vs. pre-treatment. MRI: Magnetic resonance imaging; MDCT: multi-detector computed tomography. Fig. 3. Correlation between % change in plaque volume (most diseased lesion) by MDCT and MRI. Left panel illustrates the changes in plaque burden induced by treatments, while right panel shows the changes in the most diseased lesion (MDL). ( ) apoa-i Milano animals; ( ) placebo. bias 8.3, limits of agreement 26/ 9) and MDL volume (mean bias 4.2, limits of agreement 22/ 14) Interobserver variability for MDCT Table 2 displays the results of plaque volume quantification by both observers. There were excellent correlations and agreement between the 2 blinded observers in the quantification of plaque burden, MDL volume, and individual segmental plaque volumes. The interobsever variability for individual segment plaque volume was 6.5 ± 0.3%, while it was 4.8 ± 0.8% for MDL volume, and 2.5 ± 0.4% for plaque burden quantification (Supplementary Fig. 2). 4. Discussion The results of the current study support that MDCT is able to assess serial changes in atheroma burden. MRI was used as the reference for non-invasive quantification of plaque volume and its serial changes, based on previous validation [1,4,7,11 13]. Abdominal aortic lesions were induced in a well established animal model of atherosclerosis, in which both MRI and MDCT have been previously shown to accurately quantify plaque size [17]. The arterial segment chosen for this experiment is similar in size to the human coronary arteries. All animals underwent two 64-slice MDCT and MRI studies (one week apart), and thus every animal served as its own control for the changes in atheroma volume. We employed rapoa-i M due to its rapid and well-demonstrated plaque-regressing effects both in human and experimental atherosclerosis [8 10]. MDCT accurately detected and quantified aortic plaque regression caused by rapoa-i M and the absence of a significant effect of placebo administration, showing good correlation with MRI. Moreover, the interobserver variability of MDCT analysis was 6.5% for segmental plaque volume, 4.8% for MDL volume, and 2.5% for plaque burden quantification, indicating excellent reproducibility of the analysis method employed. Earlier studies have suggested the ability of MDCT to detect and characterize atherosclerotic plaques in the coronary and extra-coronary circulation [23 26]. MDCT has also shown good correlations with the measurements obtained by IVUS for the quantification of coronary plaque size [19,27,28]. Besides anecdotal experience [29,30] our study is, to the best of our knowledge, the first to systematically inves-

6 190 B. Ibanez et al. / Atherosclerosis 202 (2009) Table 2 MDCT plaque volume measurements, correlations and agreement between both observers. Median (IQR) Mean (S.E.M.) R value p value Mean bias Limits of agreement Plaque burden Obs ( ) ± < /33.5 Obs ( ) ± 25.9 MDL volume Obs 1 92 (74 116) 97.5 ± < /14 Obs 2 93 (75 120) 97.9 ± 6.2 Segmental plaque volume Obs 1 26 (23 31) 28.5 ± < /5.4 Obs 2 26 (22 31) 28.2 ± 0.5 Plaque volume, bias and limits of agreement are expressed in mm 3. All measurements (pre- and post-treatment) are included in this analysis. MDL: Most diseased lesion; IQR: Interquartile range; Obs: observer; S.E.M.: standard error of the mean. tigate the use of MDCT to monitor changes in non-calcified atheroma burden. MDCT demonstrated good correlations and agreement with MRI for the quantification of the degree of plaque regression. MDCT however overestimated absolute plaque volume. This finding is probably related to the easier differentiation of the outer vessel boundary from surrounding fat/muscle with MRI, favoured by the use of two different contrast weighting sequences. Moreover, the in-plane spatial resolution of the MRI protocol employed is slightly higher than that achievable with current MDCT scanners. However, the higher spatial resolution with MRI comes at the expense of limited temporal resolution and/or prolonged acquisition time. Therefore, MDCT currently represents a much faster imaging method for the evaluation of atherosclerotic plaques in different vascular beds, and feasible also in the coronary arteries. One of the limitations of MDCT for plaque quantification is the high interobserver variability so far published. Leber et al. reported that the interobserver variability for plaque quantification of 3-mm individual coronary slices was 37% [27]. Conversely, Pflederer et al. showed that the interobserver variability was much lower (17%) when analyzing the plaque volume in a long segment of the left anterior descending coronary artery [31]. The interobserver variability in our work was 6.5% for individual 3-mm segments and only 2.5% when analyzing the plaque burden in the entire 5-cm area of interest. This is probably due to averaging of small, random over/underestimations for individual segments by the 2 different observers. The improved reproducibility observed in our study may be due to several reasons. First, because plaque signal intensity is influenced by mean luminal attenuation [32,33], we employed a systematic approach for setting the window width and length that accounts for this factor. This likely avoided the expected differences between the readers in image display parameters. Second, the abdominal aorta is a structure with much less mobility than the coronary arteries. Finally this model of atherosclerosis lacks large amounts of vascular calcification, another factor that may hamper accurate plaque quantification. The imaging protocol used in this study was also different from the one routinely employed in cardiac studies, which employ electrocardiographic gating. Altogether, extrapolation of our results to the evaluation of atherosclerosis progression/regression in human coronary atherosclerosis requires caution. MDCT may be nonetheless an attractive approach for the evaluation of serial changes in other vascular territories, due to its extremely fast imaging time and increasing availability. However, it should be taken into account that the use of MDCT involves the exposure to X-ray radiation and iodinated contrast agents. 5. Conclusions In an experimental model of atherosclerosis and in comparison with MRI, MDCT accurately detected and quantified regression in aortic plaque burden induced by rapoa-i M, while no significant changes were observed after placebo. Interobserver variability of MDCT analysis was low, particularly when longer arterial segments were evaluated. MDCT is a promising tool to non-invasively track serial changes in atheroma volume. Acknowledgements Borja Ibanez is granted by the Working Group on Ischemic Heart Disease of the Spanish Society of Cardiology. The drug administered to the animals (apoa-i Milano, ETC- 216) was provided by Pfizer Research and Development, USA. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi: /j.atherosclerosis References [1] Corti R, Fayad ZA, Fuster V, et al. Effects of lipid-lowering by simvastatin on human atherosclerotic lesions: a longitudinal study by high-resolution, noninvasive magnetic resonance imaging. Circulation 2001;104:

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