Abstract
Purpose:
Identifying plaque components such as intraplaque hemorrhage, lipid rich necrosis, and calcification is important to evaluate vulnerability of carotid atherosclerotic plaque; however, conventional vessel wall MR imaging may fail to discriminate plaque components. We aimed to evaluate the components of plaques using quantitative susceptibility mapping (QSM), a newly developed post-processing technique to provide voxel-based quantitative susceptibilities.
Methods:
Seven patients scheduled for carotid endarterectomy were enrolled. Magnitude and phase images of five-echo 3D fast low angle shot (FLASH) were obtained using a 3T MRI, and QSM was calculated from the phase images. Conventional carotid vessel wall images (black-blood T1-weighted images [T1WI], T2-weighted images [T2WI], proton-density weighted images [PDWI], and time-of-flight images [TOF]) were also obtained. Pathological findings including intraplaque hemorrhage, calcification, and lipid rich necrosis at the thickest plaque section were correlated with relative susceptibility values with respect to the sternocleidomastoid muscle on QSM. On conventional vessel wall images, the contrast–noise ratio (CNR) between the three components and sternocleidomastoid muscle was measured respectively. Wilcoxon signed-rank test analyses were performed to assess the relative susceptibility values and CNR.
Results:
Pathologically, lipid rich necrosis was proved in all of seven cases, and intraplaque hemorrhage in five of seven cases. Mean relative susceptibility value of hemorrhage was higher than lipid rich necrosis unexceptionally (P = 0.0313). There were no significant differences between CNR of hemorrhage and lipid rich necrosis on all sequences. In all six cases with plaque calcification, susceptibility value of calcification was significantly lower than lipid rich necrosis unexceptionally (P = 0.0156). There were significant differences between CNRs of lipid rich necrosis and calcification on T1WI, PDWI, TOF (P < 0.05).
Conclusion:
QSM of carotid plaque would provide a novel quantitative MRI contrast that enables reliable differentiation among intraplaque hemorrhage, lipid rich necrosis, and calcification, and be useful to identify vulnerable plaques.
Keywords: magnetic resonance imaging, plaque imaging, intraplaque hemorrhage, quantitative susceptibility mapping
Introduction
About 15% of strokes are thought to be caused by carotid artery atherosclerosis.1 There has been a lot of interest in the evaluation of carotid plaque characteristics with various imaging techniques and biochemical markers.2–4
Based on early histopathologic studies, intraplaque hemorrhage is more highly associated with ischemic events than any other plaque components including ulceration, calcification, and lipid rich necrosis.5,6 Another study has shown that increased stroke risk is related to plaque thrombus, macrophage infiltration, high microvessel density.7 Several plaque imaging studies have shown that development of intraplaque hemorrhage is associated with carotid plaque progression, and it is also associated with risk factors for future ipsilateral stroke events.8–10 Carotid vessel wall imaging is useful for tissue characterization of carotid atherosclerotic plaques. Intraplaque hemorrhage exhibits high signal intensity on T1-weighted images (T1WI)11–14; however, T1W images were hampered by false positives from T1W hyperintense lipid rich necrosis.15 There are limitations on the detection of slight hemorrhage/thrombus and the discrimination of hemorrhage and lipid rich necrosis.
Quantitative susceptibility mapping (QSM) is a recently developed MRI technique that provides a quantitative measure of tissue magnetic susceptibility using gradient echo phase data. The QSM values depend on the concentration of paramagnetic species, which have positive susceptibility values, and diamagnetic species, which have negative susceptibility values. Whereas conventional susceptibility weighted images qualitatively show hypointensity for both paramagnetic and diamagnetic species, QSM can be used to differentiate paramagnetic materials (such as iron derived from hemoglobin), which have positive values, and diamagnetic materials (such as calcium), which have negative values.16–18 Although there are few reports on the QSM of carotid atherosclerotic plaques, QSM might detect slight hemorrhage sensitively and differentiate various components of the plaque. We aimed to evaluate the components of carotid atherosclerotic plaques using QSM.
Materials and Methods
The study was conducted with the approval of our Institutional Review Board. Seven patients scheduled for carotid endarterectomy were enrolled. All patients were male, and the median age was 70 years (range 39–82). Five patients of them had cerebral infarction due to carotid atherosclerotic plaques. One patient suffered from transient ischemic attack due to carotid atherosclerotic plaque. The other patient was non-symptomatic, and carotid atherosclerotic plaques were incidentally found. All patients underwent MRI examination on a 3T MR system (Skyra, Siemens, Erlangen, Germany) with a 20-channel head and neck coil (Siemens Healthcare, Erlangen, Germany). Multi-echo 3D fast low angle shot (FLASH) was performed using the following parameters: number of TEs, 5; first TE, 4.38 ms; TE spacing, 2.26 ms; TR, 25 ms; flip angle, 11°; FOV, 15 × 15 cm2; acquisition matrices, 160 × 160; section thickness, 0.45 mm; imaging time, 2 min 31 s. QSM was calculated from the phase images of 3D gradient echo data using STI Suite version 2.2. (https://people.eecs.berkeley.edu/∼chunlei.liu/software.html). Mask images were generated from magnitude images by threshold for background phase removal. QSM with harmonic phase removal using the Laplacian operator (HARPERELLA) was then calculated from each local tissue phase by solving an inverse problem using the iLSQR method. Conventional carotid vessel wall images were also acquired in the same examination using multicontrast sequences. The imaging parameters for T1WI/T2-weighted images (T2WI), and proton-density weighted images (PDWI) were as follows: black-blood (presaturation pulse technique) two-dimensional fast-spin echo, TR/TE, 500/9.8, 4000/78, and 3000/11 ms, respectively; flip angle, 123°, 160°, and 150°, respectively; FOV, 16 × 16 cm2; acquisition matrices, 256 × 256; section thickness, 3 mm, with a fat suppression technique. For the time-of-flight (TOF) images, the following imaging parameters were used; three-dimensional gradient echo, TR/TE, 26/2.46 ms; flip angle, 15°; FOV, 16 × 16 cm2; acquisition matrices, 256 × 256; section thickness, 1 mm. All images were obtained in the axial plane. All patients underwent carotid endarterectomy within 40 days (range 7–39 days) from MRI, and the endarterectomy specimens were resected en bloc, fixed in buffered formalin, examined macroscopically, and sectioned serially at 5-mm intervals. Paraffin sections (5 μm thick) were stained with hematoxylin–eosin. The thickest plaque section, which was the narrowest portion of internal carotid artery, was selected for imaging pathologic correlation and examined for the following three components: hemorrhage, calcification, and lipid rich necrosis. Areas containing red blood cells were classified as hemorrhage. Areas containing amorphous material and cholesterol crystals were classified as lipid rich necrosis. The exact level of the selected sections was defined by reference to the level of the carotid bifurcation, and a corresponding image slice was selected. On conventional vessel wall images, the contrast–noise ratio (CNR) between the three components and sternocleidomastoid muscle was measured respectively, and we correlated CNR on each sequence and investigated the ability to identify each component. Susceptibility values of intraplaque hemorrhage, calcification, and lipid rich necrosis were measured on QSM using the ImageJ 1.49 (National Institutes of Health [NIH], Bethesda, MD, USA). QSM does not generate an absolute susceptibility because no information is available at k = 0 but rather a relative susceptibility between tissues. The sternocleidomastoid muscle was used as reference region for each component in our study. ROI corresponding with histopathologic findings were manually drawn by consensus with two neuroradiologists (Y.I. and H.I.). ROIs of QSM and conventional images were placed with reference to pathological findings. Wilcoxon signed-rank test analyses were performed to assess the differences among these three components.
Results
Image acquisition and post processing generating QSM succeeded in all seven cases. Intraplaque hemorrhage was proved pathologically in five of seven cases. In these five cases, the area of intraplaque hemorrhage showed markedly high relative susceptibility values on QSM (Table 1). Lipid rich necrosis was pathologically proved in all of seven cases, and the corresponding areas exhibited various relative susceptibility values. Intraplaque hemorrhage showed unexceptionally higher relative susceptibility values than lipid rich necrosis component in all five cases. Statistical analysis proved that the values of hemorrhage were significantly higher than lipid rich necrosis (P = 0.0313, n = 5). There were no significant differences between CNRs of hemorrhage and lipid rich necrosis on all conventional vessel wall images (Table 2).
Table 1.
The relative susceptibility values between each component (hemorrhage, lipid rich necrosis and calcification) and sternocleidomastoid muscle
| Case no. | Age (years) | Sex | History of infarction | Mean relative susceptibility values | |||
|---|---|---|---|---|---|---|---|
| Hemorrhage | Lipid rich necrosis | Calcification | |||||
| 1 | 66 | Male | + | 632 | 343 | −709 | |
| 2 | 68 | Male | + | 699 | 127 | −623 | |
| 3 | 82 | Male | + | None | 14 | −735 | |
| 4 | 76 | Male | − | 146 | −125 | −802 | |
| 5 | 39 | Male | + | 203 | 56 | None | |
| 6 | 80 | Male | − | None | −50 | −357 | |
| 7 | 70 | Male | + | 321 | 21 | −401 | |
Mean relative susceptibility value of hemorrhage was higher than lipid rich necrosis in all five cases, and mean relative susceptibility value of calcification was lower than lipid rich necrosis in all six cases. Statistical analysis proved that the mean relative susceptibility values of hemorrhage were significantly higher than the values of lipid rich necrosis (P = 0.0313, Wilcoxon signed-rank test, n = 5), and the values of calcification were statistically significantly lower than the values of lipid rich necrosis (P = 0.0156, Wilcoxon signed-rank test, n = 6).
Table 2.
The CNRs between each component (hemorrhage, lipid rich necrosis and calcification) and sternocleidomastoid muscle on conventional vessel wall imaging
| Contrast–noise ratios | |||||
|---|---|---|---|---|---|
| T1WI | T2WI | PDWI | TOF | ||
| Case 1 | Hemorrhage | 115.3 | 8.7 | 18.3 | 38.7 |
| Lipid rich necrosis | −15.2 | 19 | 11.7 | 27.7 | |
| Calcification | 4.7 | 0.7 | −1 | 0.3 | |
| Case 2 | Hemorrhage | 16.3 | 8.8 | −3.1 | 20 |
| Lipid rich necrosis | −17.5 | 24.8 | 4.2 | 9 | |
| Calcification | 2 | 25.8 | 5.4 | 9.5 | |
| Case 3 | Lipid rich necrosis | −2 | 8.5 | 4 | 19.2 |
| Calcification | 20.8 | 16.3 | −10.3 | 1.6 | |
| Case 4 | Hemorrhage | −5.2 | 14.6 | −6.9 | −6.7 |
| Lipid rich necrosis | −16.3 | 28 | 7.6 | 4 | |
| Calcification | −8.7 | 1 | −6.4 | −8 | |
| Case 5 | Hemorrhage | 13.8 | 93.7 | 14.3 | 46.3 |
| Lipid rich necrosis | −28.6 | 66.7 | 14.8 | 17.7 | |
| Case 6 | Lipid rich necrosis | −4.3 | 9 | 9.6 | 37 |
| Calcification | 2 | 7.8 | 1 | 26.7 | |
| Case 7 | Hemorrhage | 14.2 | 16.5 | −3.4 | −2.5 |
| Lipid rich necrosis | −18.6 | 30.5 | −0.6 | 1.5 | |
| Calcification | −9.8 | 3.8 | −4.4 | −20 | |
There were no significant differences between CNRs of hemorrhage and lipid rich necrosis on all conventional vessel wall images (T1WI; P = 0.2188, T2WI; P = 0.3125, PDWI; P = 0.1563, TOF; P = 0.125, Wilcoxon signed-rank test, n = 5). There were significant differences between CNRs of lipid rich necrosis and calcification on T1WI, PDWI, TOF. Although there was no significant difference on T2WI, calcification could be identified on conventional vessel wall images (T1WI; P = 0.0156, T2WI; P = 0.1094, PDWI; P = 0.0313, TOF; P = 0.0313, Wilcoxon signed-rank test, n = 5). CNR, contrast-to-noise ratio; T1WI, T1-weighted image; T2WI, T2-weighted image; PDWI, proton-density weighted images; TOF, time-of-flight.
Calcification was pathologically proved in six of seven cases. Areas corresponding to calcification showed markedly low relative susceptibility values on QSM in these six cases (Table 1). In all six cases, calcification showed significantly lower relative susceptibility values than lipid rich necrosis component on QSM in all six cases (P = 0.0156, n = 6). There were significant differences between CNRs of lipid rich necrosis and calcification on T1WI, PDWI, TOF (Table 2, T1WI; P = 0.0156, PDWI; P = 0.0313, TOF; P = 0.0313, n = 6). On T2WI, there was no significant difference (P = 0.1094, n = 6). An example was shown in Fig. 1.
Fig. 1.
(a and b) A case example (case 1). (a) Quantitative susceptibility mapping (QSM) image. (b) Focus on left carotid plaque. (A) Hematoxylin–eosin-stained histopathological cross-section (Hemorrhage, lipid rich necrosis, and calcification are surrounded by red, green, and blue dot lines, respectively.). (B) QSM, (C) T1-weighted image (T1WI), (D) T2-weighted image (T2WI), (E) proton-density weighted images (PDWI), (F) time-of-flight (TOF). Hemorrhage (red arrow) and lipid rich necrosis component (surrounded by green dot lines) were clearly differentiated on QSM (B), whereas on black-blood T1WI and TOF (C and F) intraplaque hemorrhage and lipid rich necrosis showed similar signals. On TOF, calcification (blue arrow) showed low signal, but the low signal of calcification is clear on QSM.
Discussion
In this study, the area corresponding to intraplaque hemorrhage showed markedly high relative susceptibility values on QSM in all five cases as expected. Normal vessel walls and calcification are diamagnetic, whereas intraplaque hemorrhage is paramagnetic.19 This leads to opposite phase polarities, which could be utilized in QSM for better differentiation of diamagnetic components from intraplaque hemorrhage.20 The correlations reported in this study between intraplaque hemorrhages and high relative susceptibility values would facilitate QSM-based identification of intraplaque hemorrhage. The detection and quantification of tiny foci of hemorrhage in asymptomatic carotid plaque might be possible using QSM.
Lipid rich necrosis components showed various but lower relative susceptibility values than intraplaque hemorrhage. Since lipid is diamagnetic, lipid rich necrosis was expected to show low values; however, lipid rich necrosis showed slightly high values on QSM in some cases. Although lipid content in plaques would be derived from foam cells, Kolodgie et al.21 observed that advanced atherosclerotic plaques contained erythrocyte membranes in the necrotic core, suggesting that erythrocytes may actively contribute to plaque growth. We hypothesize that necrotic core might contain some paramagnetic material derived from erythrocytes. Further immunohistological analyses of the necrotic core are necessary to solve this question.
Distinctive differentiation between hemorrhage and lipid rich necrosis was difficult on conventional vessel wall images. On the other hand, intraplaque hemorrhage was clearly distinguished from lipid rich necrosis on QSM, since the relative susceptibility values of hemorrhage were significantly higher than lipid rich necrosis. Because carotid intraplaque hemorrhage has a much stronger association with ipsilateral ischemic events than does lipid rich necrosis, differentiation between the two components is clinically important. It is reported that carotid plaque hyperintensity on magnetization prepared rapid acquisition with gradient echo (MPRAGE), a heavy 3D T1WI technique, is associated with previous cerebral ischemic events,22 but MPRAGE may not differentiate the two components, because T1W images were hampered by false-positives from T1W hyperintense lipid rich necrosis.15
Calcification, which is a relatively common structural feature in human carotid atherosclerosis showed markedly low relative susceptibility values in all six cases, and the relative susceptibility values of calcification was significantly lower than lipid rich necrosis. Although there was no significant difference on T2WI, calcification could be identified on conventional vessel wall images. Although there were significant differences between CNRs of lipid rich necrosis and calcification on T1WI, PDWI, and TOF, QSM might offer much better contrast than that of conventional images. A recent study reported a performance of susceptibility weighted imaging for the detection of calcification,23 and QSM can also be used to detect calcification as suggested by our study. Calcified carotid atherosclerotic plaques are less prone to disrupt and result in symptoms when compared with noncalcified plaques and carotid plaque calcification confers structural stability.24 Fibrous cap inflammation and susceptibility to disruption are less likely to occur in calcified than in noncalcified plaques.25
Although QSM of carotid atherosclerosis was mentioned in an article,26 histopathological correlation was not performed. To the best of our knowledge, this pilot study is the first to report QSM findings with histopathologic correlation. However, this study has several limitations. First, the small number of patients compromises the statistical power of the performed measurements. We therefore present these results as preliminary, suggestive rather than definitive findings. Second, we analyzed only the thickest plaque section of serial sections for one specimen, because it is difficult to evaluate the properties of small plaques due to pathological artifacts related to handling of the specimen and the low spatial resolution of QSM at this time. Third, ROI of images were drawn manually with reference to pathological findings, and the susceptibility values may be biased. Forth, we did not use a water–fat separation method to remove the chemical shift by subcutaneous fat, which can affect the phase signal and QSM quantification. Fifth, imaging time of QSM was relatively long, and there was effect of motion artifacts caused by swallowing and vessel pulsation. They also could lead complex susceptibility values in some degree. Sixth, because there was no patient with fibrous plaque in our study, we could not discuss about fibrous component of plaque.
Conclusion
Intraplaque hemorrhages showed markedly high values on QSM. Lipid rich necrosis components showed various but significantly lower relative susceptibility values than intraplaque hemorrhages. QSM would be superior to conventional vessel wall images in distinct discrimination of intraplaque hemorrhage and lipid rich necrosis. Areas corresponding to calcification showed markedly low relative susceptibility values on QSM. QSM of carotid atherosclerotic plaque would provide a novel quantitative MRI contrast that enables reliable differentiation among intraplaque hemorrhage, lipid rich necrosis, and calcification.
Supplementary Information
(This supplementary is available online.)
Supplementary material 1
Case 2, plaque with hemorrhage, lipid rich necrosis, and calcification.
Red arrow and surrounded by red dot lines: hemorrhage.
Blue arrow and surrounded by blue dot lines: calcification.
Surrounded by green dot lines: lipid rich necrosis component.
White dot lines: lumen and outer layer of the artery.
Supplementary material 2
Case 3, plaque with lipid rich necrosis and calcification.
Supplementary material 3
Case 4, plaque with hemorrhage, lipid rich necrosis, and calcification.
Supplementary material 4
Case 5, plaque with hemorrhage and lipid rich necrosis.
Supplementary material 5
Case 6, plaque with lipid rich necrosis and calcification.
Supplementary material 6
Case 7, plaque with hemorrhage, lipid rich necrosis, and calcification.
Footnotes
Conflicts of Interest
Hiroshi Imai is an employee of Siemens Healthcare. The other authors declare that they have no conflicts of interest.
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