Gray blood late gadolinium enhancement cardiovascular magnetic resonance for improved detection of myocardial scar

Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) is an established technique for imaging myocardial fibrosis and left ventricular (LV) scar [1]. In addition, LGE imaging has been shown to have potential for detecting scarred tissues in other cardiac structures, including the left atrium and papillary muscles [2‐4]. In LGE, a gadolinium-based contrast agent is injected 10-15 min prior to imaging. The LGE imaging sequence uses an inversion pulse followed by an image acquisition after an inversion delay, at which point the myocardial signal is nulled. The inversion delay is determined prior to the LGE imaging using a Look-Locker sequence [5]. The fast recovery of scar signal (shorter T₁) lead to scarred tissues appearing bright in LGE images. However, due to the short T₁ of blood, blood also appears bright and thus leads to low scar-to-blood contrast. This makes detection of myocardial scar in the vicinity of the blood pool challenging [6].

Several approaches have been investigated to improve blood to scar contrast by suppressing the blood pool. One approach utilizes the out-of-slice blood flow to selectively suppress the blood using dual [6] or quadruple [7] inversion pulses. However, sluggish blood flow and the sensitivity of the technique to predetermined timing parameters can be a limitation of this approach [8]. To avoid this limitation, flow-independent approaches have been proposed to null the blood signal based on T₁ differences among the blood, scar, and normal myocardium. This includes using non-selective dual inversion recovery [8] and blood signal nulling using phase-sensitive LGE [9]. Magnetization preparations before inversion have been also proposed [10‐12] for selectively suppressing the blood pool signal relative to the myocardium. We recently proposed a dark-blood LGE (DB-LGE) sequence by inserting the T₂ magnetization preparation pulse between the inversion pulse and image acquisition [13, 14] to achieve simultaneous nulling of the blood pool and the myocardium. This technique was subsequently used in combination with phase-sensitive inversion recovery (PSIR) [15]. PSIR-based DB-LGE techniques [12, 15‐17] are optimized to null the blood pool after the myocardium and thus the negative signal appears darker. A black blood contrast is then generated by means of intensity windowing where blood and myocardium appear black and gray, respectively. This results in a more conspicuous myocardium-blood border due to a high contrast to noise ratio between blood and normal myocardium. A validation study by Francis et al. [16] showed that using T₂-preparation after the inversion recovery pulse in PSIR LGE increases the observer confidence in detecting subendocardial scar. A flow-independent PSIR-based DB-LGE technique was recently presented and validated by Kim et al. [17]. Magnetization-transfer preparation module was used prior to the inversion recovery pulse to achieve blood suppression. The technique was validated using canine model as a reference standard and human subject data [17].

Prior work of complete suppression of the blood signal [6, 10, 13, 14] can be limited by making the clinical interpretation of LGE images more difficult. For example, simultaneous nulling of healthy myocardium and the blood pool makes it difficult to localize a scar and to assess the transmurality. This approach may also artifactually enhance noise/artifacts in patients without scarring. Therefore, LGE with improved contrast between all 3 tissues (i.e. blood pool, healthy and scarred myocardium) may be preferred to complete blood signal nulling.

In this study, we present a 3D gray-blood LGE (GB-LGE) sequence based on our previous DB-LGE sequence [13, 14] by introducing a parameter optimization approach that allows flexible adjustment of tissue contrast. Numerical simulations, phantoms and in-vivo studies in both humans and a swine model of infarction are used to study the performance of the proposed method.

A block diagram of the DB-LGE sequence is shown in Fig. 1a, indicating the three timing parameters D ₁ , D ₂ and D ₃ that are to be determined for GB-LGE [13]. At the beginning of acquisition, the acquired signal is given by [13],where, \( {T}_1^r \) and \( {T}_2^r \) are the T₁- and T₂- parameters of the myocardium, blood, or scar, and \( {M}_{ss}^r \) is the tissue steady-state magnetization (normalized by the fully-recovered magnetization) available immediately before the inversion-recovery pulse. The subscript r can take the symbol: ‘myo’, ‘blood’, or ‘scar’ to indicate the tissue type (myocardium, blood, or scar, respectively). The steady state magnetization, \( {M}_{ss}^r \) can be analytically derived given the image acquisition sequence (Appendix).

To allow adjustment of the LGE image contrast, the following cost function, Q, is formulated to represent the desired image contrast,where, M ^r is given by Eq. 1, and α and β are arbitrary non-negative weights less than 1. The first term in the above equation ensures that the optimal solution minimizes the normal myocardium signal. Minimization of the second term leads to a blood signal that is approximately equal to a desired fraction (β) of the scar signal. To obtain a black-blood LGE (BB-LGE) contrast, β is set to zero to suppress both the blood and the myocardium signals (Fig. 1c). To partially attenuate the blood signal, β is set to a fraction (e.g., 0.1) to obtain GB-LGE contrast (Fig. 1c). In this work, α is set to 0.5 in BB-LGE to equally suppress both the blood and the myocardium signals. For GB-LGE contrast, α is set to a relatively large value (= 0.9) to prioritize the myocardium nulling over strictly equating the blood signal to a given signal level. The other parameters of the cost function include the T₁ and T₂ of the myocardium, the blood, and the scar. The T₁ values are determined using a T₁ mapping scan as discussed below, while the T₂ values of the myocardium, blood, and scar are fixed to previously-reported values equal to 50, 200 and 55 ms, respectively [18, 19]. Changing these fixed values can be shown to have no significant effect on the optimized signal (Additional files 1, 2, 3 and 4).

Since there are only two physical phenomena controlling the optimal solution- namely, T₂ decay and T₁ recovery- only two optimization parameters are sufficient to adjust the image contrast. In this work, we use D ₂ (to control T₂ decay) and D ₃ (to control T₁ recovery), while the parameter D ₁ is fixed to a predetermined arbitrary value. The optimization problem in Eq. 2 is numerically solved using the Levenberg-Marquadt algorithm [20] implemented in Matlab (Mathworks Inc., Natick, Massachusetts, USA). Numerical iterations were terminated when the changes in Q were below 10^− 8.

The numerical simulation of the effect of D ₁ on the resulting scar signal is summarized in Fig. 2. The maximum scar signal (= 0.23 ± 0.04 and 0.24 ± 0.04 in BB-LGE and GB-LGE, respectively) occurred at the lowest value of D ₁ (= 5 ms), and continued to decrease with increased D ₁ . Therefore, to obtain maximum scar signal, D ₁ should be set to its minimum feasible value. Based on this finding, D ₁ was set to the minimum value allowing the use of adiabatic and/or water-selective inversion-recovery pulses in addition to the crushing gradients (= 20 ms).

The phantom experiment demonstrated flexible adjustment of the signal from different vials (Fig. 3). Increasing β from 0 to 0.08 resulted in a gradual increase of the signal ratio between vial-B and vial-S from 0.07 to 0.35. For all values of β, the signal ratio of vial-M to vial-S was below 0.06 showing a suppression of the myocardium-mimicking vial.

For the in-vivo imaging, the estimated timing parameters were variable among different patients depending on T₁ tissue parameters. The estimated parameter D ₂ for the BB-LGE and GB-LGE sequences varied from 7 to 26 ms (median = 15 ms), and from 4 to 28 ms (median = 9 ms), respectively. The parameter D ₃ varied from 146 to 208 ms (median = 183 ms), and from 184 to 273 ms (median = 217 ms) for the BB-LGE and GB-LGE sequences, respectively. The computation time for determining the optimal parameters was less than 1 s.

Both GB-LGE and BB-LGE showed improved blood and scar contrast (Fig. 4), however GB-LGE images showed improved visualization of healthy myocardium. Compared to the conventional LGE images, suppression of the blood signal in GB-LGE and BB-LGE sequences allowed clear visualization of the hyper-enhanced atria (red arrow), left and right ventricular hyper-enhancement (yellow arrows), and chordae tendineae and papillary muscles (blue arrows) in both GB-LGE and BB-LGE images (Fig. 4 and Additional files 2 and 3).

The Friedman test of the quantitative analysis of the human subjects’ images showed a significant difference among the three sequences in the scar-to-blood relative contrast (P < 0.001). Pairwise comparisons indicated that the scar-to-blood relative contrast in GB-LGE (1.1 ± 0.5) was significantly higher than that in the conventional LGE images (0.6 ± 0.4) with P < 0.001 (Table 1). Due to the complete nulling of the blood signal, the BB-LGE scar-to-blood relative contrast (3.61 ± 1.83) was significantly higher than that of both GB-LGE (P < 0.001) and conventional LGE (P < 0.001). The scar-to-myocardium relative contrast in GB-LGE, BB-LGE, and standard LGE were 5.1 ± 3.1, 6.1 ± 4.1, and 5.9 ± 3.5, respectively (Table 1). The scar-to-myocardium relative contrast of the conventional LGE was comparable to that of GB-LGE (P = 0.19) and BB-LGE (P = 0.59). The GB-LGE showed significantly higher scar-to-myocardium relative contrast than that of BB-LGE (P = 0.023) which could be due to the shorter T₂ preparation pulses in GB-LGE compared to BB-LGE. As expected, suppression of the blood signal has significantly reduced the blood-to-myocardium relative contrast in GB-LGE (1.7 ± 1.4) and BB-LGE (0.7 ± 1.2) compared to conventional LGE (3.8 ± 3.5) with P < 0.001 for all pair-wise tests (Table 1).

In the subjective assessment, both readers assigned an image quality score of ‘good’ to 44 GB-LGE datasets, 44 BB-LGE datasets, and 42 conventional LGE datasets. Both readers confirmed presence of LV scar in 17 datasets (out of 45): 9 in patient group 1 and 8 in patient group 2 (Table 2). All cases were correctly identified in GB-LGE and BB-LGE images by both readers. Among these 17 datasets, reader 1 and reader 2 missed the presence of the scar in 5 and 4 cases in the conventional LGE images, respectively. None of the GB-LGE datasets was assigned an ‘uncertain’ score by either of the readers. In contrast, readers 1 and 2 assigned ‘uncertain’ assessment scores to 2 and 4 conventional LGE datasets, respectively and both assigned ‘uncertain’ to 1 BB-LGE dataset. Also, more papillary scar were identified by both readers in GB-LGE compared to BB-LGE and conventional LGE images (Table 2).

There was a statistically significant difference by the Friedman test between the subjective diagnostic value scores (i.e., the ability to detect LV scar, localize LV scar and detect papillary scar) among the three different sequences (Table 3 and Additional file 4: Table S2). Comparisons between each pair of sequences indicated that all subjective scores for the diagnostic value of GB-LGE were significantly higher than those of the conventional LGE images (P < 0.001 for all score comparisons). The GB-LGE scores were also significantly higher than those of BB-LGE images to localize LV scar (P = 0.024) and papillary muscle scar (P = 0.014). The GB-LGE was similar to BB-LGE in the ability to detect the LV scar (P = 0.10).

3D GB-LGE and 3D BB-LGE were successfully acquired in all animals (Fig. 5). The average scar-to-blood relative contrast in GB-LGE (1.5 ± 0.2) was higher than that of the conventional LGE images (− 0.03 ± 0.2) but lower than that in BB-LGE (5.2 ± 1.3) due to the complete nulling of the blood signal (Table 4). The scar-to-myocardium relative contrast in GB-LGE (8.9 ± 4.9) and conventional LGE (7.1 ± 6.2) were comparable but higher than that of BB-LGE (4.7 ± 1.5) (Table 4). The blood-to-myocardium relative contrast was reduced in GB-LGE (2.9 ± 1.7) and BB-LGE (0.1 ± 0.2) compared to conventional LGE (7.2 ± 5.9) (Table 4). Both reviewers assessed all images of diagnostic quality in all animals. There was no difference between readers in identifying hyper-enhancements in GB-LGE and BB-LGE images (Table 2). The subjective assessment of the ability to localize LV scar indicated that GB-LGE had consistently higher scores (4.0 ± 0.0) compared to BB-LGE (3.2 ± 0.5) and conventional LGE (2.0 ± 0.7) (Table 5).

We present a 3D GB-LGE sequence that yields improved scar visualization by increasing the contrast between scar, blood and normal myocardium. Phantom and in-vivo images show partial suppression of the blood signal can be achieved by choosing the appropriate sequence parameters. In our human datasets, GB-LGE contrast improved localization of the myocardium hyper-enhancements compared to BB-LGE and conventional LGE. In the animal datasets, despite the higher scar contrast in BB-LGE images, both readers consistently scored the GB-LGE images higher for the ability to localize LV scar compared to both BB-LGE and conventional LGE. While GB-LGE shares recently presented DB-LGE techniques the use of T₂-preparation to adjust the image contrast [13, 15], it allows more flexibility to adjust the blood contrast compared to the method by Basha et al. [13].

Simple imaging parameter scouting was used in GB-LGE that included single breath-hold T₁ mapping scan (9 heartbeats) and fast numerical solution of the optimization cost function (< 1 s). Compared to conventional LGE, GB-LGE requires additional steps of manual drawing of regions of interest to determine tissue T₁ and running the optimization solver. This process usually takes 10-15 s and is performed by imaging technologists. The same concept of using T₁ mapping for scouting the imaging parameters has been employed earlier in DB-LGE by Kellman et al. [15], where parameter computations were performed on the scanner main computer.

Both GB-LGE and BB-LGE data were acquired in 1 R-R (i.e. one heart-beat), while conventional PSIR-LGE images were acquired in 2 R-R. This resulted in improved signal-to-noise ratio (SNR) and fewer artifacts due to incorrect nulling. The 3D acquisition in GB-LGE and BB-LGE inherently improves the SNR despite the effect of T₂ preparation pulses. However, 3D PSIR images will be 2× longer which will be clinically prohibitive especially for higher-spatial resolution scar imaging where scan time is 4-7 min [25‐27]. That said, GB-LGE sequence can be easily modified to achieve PSIR GB-LGE, similar to BB-LGE [15]. Optimizing the contrast cost function in the proposed method results in shorter T₂ preparation times (4-28 ms) compared to our prior parameter selection algorithm for DB-LGE (35 ms) [13] or PSIR-based DB-LGE (10-40 ms) [15]. A shorter T₂ preparation time will result in increased SNR in the new parameters selection scheme; however we did not directly compare the SNR improvements between the two sequences.

In general, flow-independent DB-LGE imaging sequences can potentially generate GB-LGE contrast through some modifications. For example, increasing the time delay between T₂ preparation and acquisition in DB-LGE [13] or changing the parameter selection function in PSIR DB-LGE [15] can result in GB-LGE contrast. However, this may require relaxing the constraints of fixing or minimizing the T₂ preparation echo times in DB-LGE and PSIR DB-LGE, respectively. In other T₂-prepared LGE imaging sequences [10‐12], our parameter optimization methodology can be followed to generate the GB-LGE contrast. In PSIR DB-LGE (without magnetization preparation) method [9], increasing the inversion-to-acquisition time delay can generate GB-LGE contrast but will reduce the scar-to-blood relative contrast. In flow-based DB-LGE methods [6, 7], changing the sequence timing parameters results in incomplete blood suppression, which may lead to inhomogeneous and patchy signal within the blood pool.

In our study, we used different contrast agents, types and doses in animals and humans. Despite these differences, we successfully achieved GB-LGE in both human and animal studies. Use of a high-relaxivity contrast agent and dose in animal experiments resulted in higher blood pool signal in conventional PSIR-LGE images, and further demonstrated the effectiveness of GB-LGE in blood suppression and scar detection. This difference also highlights the robustness of the parameter optimization for parameter selection for different contrast types and doses. The proposed contrast function was intended to provide a simplified analytical approximation of the LGE image contrast to enable tractable optimization of the imaging parameters. The observed differences between the actual and the prescribed blood to scar contrast in GB-LGE in our study can be explained by several factors. First, the optimization solver was weighted to prioritize nulling the myocardium signal than achieving specific blood to scar ratio. Also, the actual scar T₁ is controlled by many factors (including the dose and washout rate of the contrast material) while it is assumed fixed relative to the blood T₁ in the contrast model. The latter factor leads to variability of the blood signal between patients. However, this effect also presents in conventional LGE but with a lesser extent (Additional files 1, 2, 3 and 4). This observation was confirmed in the quantified image contrast, where the standard deviation of the scar-to-blood relative contrast in GB-LGE was higher compared to conventional LGE (Table 1).

Our study has several limitations. While we found differences in the ability of different sequences to detect scarring, we do not have any histological evidence of the presence/extent of scarring in those patients. We have not performed histological validation of the GB-LGE sequence. Larger studies in patients are warranted to further assess the diagnostic and prognostic value of GB-LGE for scar detection.

GB-LGE imaging improves the ability to identify and localize scarred tissues compared to BB-LGE and conventional LGE.