Cardiac intravoxel incoherent motion diffusion-weighted imaging to assess myocardial microcirculation dysfunction in hypertension

Introduction

Hypertension has been considered the primary and common clinical cardiovascular risk factor for a long time, which often remains undiagnosed or untreated (1,2). Hypertension is closely associated with altered myocardial microcirculation status (3). Myocardial microcirculation, consisting of resistance arteries, arterioles, capillaries, and venules, plays an important role as a common denominator of different heart diseases and has attracted increasing research attention in recent years (4-8). Myocardial microcirculation dysfunction in hypertension mostly manifests by two different types of diffuse structural changes: (I) capillary rarefaction, which consists of abnormally low spatial densities of arterioles, capillaries, and possibly venules, and (II) remodeling of small resistance arteries, which reduces lumen diameter (3,9,10). Myocardial microcirculation dysfunction occurs in the early phases of hypertension (3,10). Persisting hypertension, microcirculation, and microcirculation dysfunction are tightly interconnected into a dangerous cross-link and further worsen cardiac damage (4). Myocardial microcirculation dysfunction is considered the most potent predictor of adverse cardiovascular events in hypertension (3). Quantitative and accurate assessment of myocardial microcirculation dysfunction may provide crucial insights into the pathophysiological processes of hypertension (10,11).

Cardiac magnetic resonance (CMR) is an established noninvasive tool for diagnosing and evaluating cardiac diseases (12,13). Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) is a tool that quantitatively assesses in vivo diffusion modeling without contrast agent injection. It has been widely used in various body systems (14-19). Traditional cardiac DWI using ordinary single-index model may reflect myocardial tissue changes at the cellular level and could be applied to assess mean diffusion, including actual water molecule diffusion and random blood flow microcirculation perfusion in the capillary network. Based on non-Gaussian diffusion, IVIM-DWI applies multiple b-value scan imaging to separate actual diffusion and micro-circulation perfusion for the tissue (15-18). IVIM-DWI indexes include the D (reflecting water molecular diffusion), D* (reflecting microcirculation) and f (reflecting perfusion fraction) parameters (20). Due to technical cardiac and respiratory motion restrictions, IVIM-DWI could not apply in CMR until 2003 (21). Recent studies have examined the feasibility and repeatability of IVIM-DWI in characterizing myocardial microcirculation dysfunction in multiple cardiac diseases (22-27). Large sample studies utilizing IVIM-DWI to evaluate myocardial microcirculation dysfunction in hypertension are still required.

This study aimed to assess the value of IVIM-DWI in the assessment of myocardial microcirculation dysfunction in hypertensive patients. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-24-108/rc).

Methods

In this prospective single-center study, 72 hypertensive individuals were recruited from Shandong Provincial Hospital Affiliated to Shandong First Medical University between June 2020 and September 2022 and 30 healthy controls were also enrolled. Inclusion criteria for hypertensive individuals were: (I) 18–65 years old; (II) meeting the diagnostic criteria of hypertension (28) [mean systolic blood pressure (SBP) ≥140 mmHg and/or diastolic blood pressure (DBP) ≥90 mmHg, including individuals with current antihypertensive drug treatment]; (III) no coronary artery diseases, congenital heart diseases, cardiomyopathies, or other medical histories of cardiac diseases; (IV) no systemic diseases that might cause myocardial microcirculation dysfunction, e.g., diabetes, amyloidosis and sarcoidosis; (V) no contraindications for CMR; and (VI) no abnormality on the electrocardiogram (ECG) or detected by echocardiography. Blood pressure (BP) was measured with a clinically validated semiautomatic sphygmomanometer, Omron HEM-737 Intellisense (Omron Healthcare GmbH, Hamburg, Germany). BP measurements were obtained twice after resting for 5 minutes, with ≥2 minutes between measurements before the CMR examination. According to BP categories, patients with hypertension were divided into 3 subgroups, including the H1 (Grade 1 hypertension, 140/90 mmHg ≤ BP ≤159/99 mmHg), H2 (Grade 2 hypertension, 160/100 mmHg ≤ BP ≤179/109 mmHg) and H3 (Grade 3 hypertension, BP ≥180/110 mmHg) groups. The participants meeting the following criteria were included in the healthy control group: (I) mean BP ≤140/90 mmHg; (II) no history of hypertension or anti-hypertensive treatment; (III) no history of cardiac or systemic disease. Baseline demographic and clinical characteristics were recorded. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the ethics committee of Shandong Provincial Hospital Affiliated to Shandong First Medical University (NSFC: No. 2020-382), and written informed consent was obtained from all participants.

CMR imaging protocol

CMR was carried out on a 3.0T clinical MR imaging unit (Philips Healthcare, Amsterdam, Netherlands) with a 16-channel phase-array body coil. The scanning sequences included cine imaging and IVIM-DWI sequences. All cine imaging data were acquired under retrospective electrocardiograph (ECG) trigger and at the end-expiratory condition. Cine images were acquired in the horizontal long axis (HLA) and sequential short axis (SA) orientations from ventricular base to apex. Cine imaging parameters were: repetition time (TR)/echo time (TE), 2.8 ms/1.4 ms; FA, 45°; voxel size, 2.0×2.0×8.0 mm³. IVIM-DWI was carried out with a tri-directional, single-shot spin-echo echo-planar imaging (EPI) sequence with 8 b values, including 0, 50, 80, 100, 150, 200, 250 and 500 s/mm². DWI was conducted along three orthogonal directions simultaneously. Specifically, diffusion gradients were applied along the x, y, and z axes during image acquisition. To compensate for the loss of signal-to-noise ratio (SNR) induced by high b values in IVIM-DWI sequences, different numbers of excitations were applied for different b values: “(0) 1”, “(10) 1”, “(50) 1”, “(100) 2”, “(150) 3”, “(200) 4”, “(250) 5” and “(500) 6”. Other imaging parameters were: TR/TE, 1,000/46 ms; matrix size, 160×160; field of view, 310×270 mm²; slice thickness, 8 mm; Gap, parallel imaging factor sensitivity encoding (SENSE), 3. Cardiac triggering was utilized to minimize motion-related artifacts. A rapid scout axial cine MRI study was carried out to assess the pattern of gross cardiac motion and to identify the optimal imaging window, with the acquisition window placed in the mid-to-late diastolic phase of the cardiac cycle when myocardial motion is minimal. Image acquisition was carried out during free breathing, applying a navigator echo-based respiratory motion compensation technique to further reduce motion artifacts. Motion correction was performed before fitting the IVIM model to ensure the accuracy of the acquired data. Four saturation slabs were set to zero the signal from the areas of chest wall, lung, liver and stomach, immediately above the heart, which may cause artifacts during respiratory motion. Images were acquired in the mid-ventricular SA slice (papillary muscle level). Imaging parameters were: TR, 57 ms; TE, 45.6 ms; matrix size, 96×128; voxel size, 3.0×3.0×8.0 mm²; acquisition time, 90–180 s.

CMR imaging analysis

All original image data, excluding IVIM-DWI, were analyzed with a commercial postprocessing software, CVI42 (Circle Cardiovascular Imaging Inc., AB, Canada). IVIM-DWI images were post-processed in MITK software (MitkWorkbench, www.mitk.org). Two experienced CMR radiologists (C.W. and H.W., with >5 years of experience in CMR analysis) independently assessed all CMR images. More than 2 weeks later, H.W. repeated the IVIM-DWI image analysis for the assessment of intra-observer agreement. Patients with poor IVIM-DWI image quality (severe artifacts or loss of myocardium signal in >2 IVIM-DWI images with different b values) were excluded from the final analysis.

Left ventricle (LV) cardiac function parameters were assessed in cine images. LV endocardial and epicardial contours were delineated manually for each diastolic and systolic frame in sequential SA cine images. Then, LV cardiac function indexes, including end-diastolic volume (EDV), end-systolic volume (ESV), left ventricle ejection fraction (LVEF) and LV mass, were automatically analyzed. Papillary muscles and trabeculations are part of the ventricular cavity (29). LV cardiac function indexes were standardized by body surface area (BSA) (30). The LV chamber was examined with the American Heart Association (AHA) 17 segments model (apical segments excluded) (31). Maximal LV wall thickness was defined as the most significant linear dimension at any site within the LV myocardium.

IVIM-DWI images were motion-corrected, and a region of interest (ROI) ≥3 mm width was delineated manually on the mid-wall area of the full circumference of the LV in the SA orientation, avoiding the intracardiac blood flow, papillary muscles, and edge pixels (Figures 1,2). IVIM-DWI-associated parameters were automatically acquired using a bi-exponential model as follows (32):

Sb/S0=(1−f)×exp(−bD)+f×exp(−bD*)[1]

Figure 1 Typical IVIM-DWI images of a 54-year-old male normal subject. (A-H) IVIM-DWI images with different b values (0, 10, 20, 50, 80, 100, 250 and 500 sec/mm²). The original images were analyzed with the MITK post-processing software, and D (I), D* (J) and f (K) maps were acquired. The ROI region was shown (L). D value: 1.3 mm²/s; D* value: 120.3 mm²/s; f value: 12.0%. IVIM-DWI, intravoxel incoherent motion diffusion-weighted imaging; MITK, MitkWorkbench; ROI, region of interest; D, water molecular diffusion; D*, pseudo diffusion; f, perfusion fraction.

Figure 2 Typical IVIM-DWI images in a 72-year-old female patient with Grade 3 hypertension (very high risk). (A-H) IVIM-DWI images with different b values (0, 10, 20, 50, 80, 100, 250 and 500 sec/mm²). The original images were analyzed with the MITK post-processing software, and D (I), D* (J) and f (K) maps were acquired. The ROI region was shown (L). D value: 2.0 mm²/s; D* value: 71.3 mm²/s; f value: 29.0%. IVIM-DWI, intravoxel incoherent motion diffusion-weighted imaging; MITK, MitkWorkbench; ROI, region of interest; D, water molecular diffusion; D*, pseudo diffusion; f, perfusion fraction.

The fit method was fit D and f in the higher b-value regime first, then fit D*, as the article of Xiang et al. (32). Where S0 is signal intensity at b=0 s/mm², Sb is signal intensity at other b values, D reflects tissue structure (water molecular diffusion), D* reflects microcirculation (pseudo diffusion), and f reflects perfusion fraction. The IVIM fitting curves are shown in Figure S1.

Statistical analysis

Statistical Package from the Social Sciences (SPSS, version 26.0, IL, USA) was used for data analysis. Categorical data were presented as percentage (%), and continuous data as mean ± standard deviation (SD) or median (range). The Shapiro-Wilk test was performed to evaluate data normality. Baseline demographic and clinical characteristics were compared by the chi-square test for categorical variables, t-test and analysis of variance (ANOVA) for normally distributed continuous variables, and the Mann-Whitney U test for skewedly distributed continuous variables. Intra- and Inter-observer reproducibility for various parameters were measured by Bland-Altman analysis and intraclass correlation coefficient (ICC). Two-sided P<0.05 was considered statistically significant.

Results

Clinical characteristics

Totally 62 participants with hypertension (38 males, mean age of 49.9±11.4 years) and 27 healthy controls (12 males, mean age of 49.7±12.5 years) were included in this study. Totally 13 participants were excluded for poor quality of IVIM-DWI images.

In the hypertension group, 17 patients (11 males, mean age of 46.6±14.3 years) were assigned to the H1, 26 (15 males, mean age of 50.5±9.0 years) were assigned to the H2 group, and 19 (12 males, mean age of 53.5±11.9 years) were assigned to the H3 group. There were no significant differences in clinical characteristics between the hypertension and healthy control groups, except for BMI (25.9±2.3 vs. 24.5±1.6 kg/m², P<0.001). The clinical characteristics of hypertensive patients and healthy controls are presented in Table 1.

Cardiac function parameters

Standard cardiac function parameters in the hypertension and healthy control groups are shown in Table 2. There were significant differences in maximal LV wall thickness (10.3±2.0 vs. 8.6±1.4 mm, P<0.001) and LV mass index (49.0±9.1 vs. 42.1±7.5 g/m², P<0.05) between the hypertension group (including H1–H3 subgroups) and healthy control group, with no statistical differences in other cardiac function parameters.

IVIM-DWI parameters

Compared with the healthy control group, D* values were significantly lower (81.3±16.3 vs. 111.8±18.9 mm²/s, P<0.001) in the hypertension group (including H1–H3 subgroups). There were no significant differences between the two groups in D and f values. Among the three hypertension subgroups, significant differences in D* values were detected (99.4±13.9 vs. 79.7±10.6 vs. 67.1±6.6 mm²/s, P<0.001). No significant differences were found in D and f values. The IVIM-DWI images of normal subject are shown in Figure 1 and the images of a hypertensive patient are shown in Figure 2. IVIM-DWI-associated parameters in different groups are shown in Figure 3 and Table 2.

Figure 3 Scatter plots of IVIM-DWI parameters. Scatter plots indicating the distributions of D (A), D* (B) and f (C) values between the hypertension and healthy control groups. Significantly differences in D* values were found between the hypertension and healthy control groups, as well as among the three hypertension subgroups. *, P<0.05; **, P<0.001. NC, normal control; H1, Grade 1 hypertension; H2, Grade 2 hypertension; H3, Grade 3 hypertension; D, water molecular diffusion; D*, pseudo diffusion; f, perfusion fraction; IVIM-DWI, intravoxel incoherent motion diffusion-weighted imaging.

Interobserver and intra-observer variability of IVIM-DWI-associated parameters

Two independent observers analyzed all IVIM-DWI images for assessing inter-observer variability. One observer repeated the IVIM-DWI image analysis twice within one month for the assessment of intra-observer agreement. Bland-Altman plots for D, D*, and f values are shown in Figure 4, indicating good inter-observer and intra-observer agreement.

Figure 4 Bland-Altman plots for D, D* and f value measurements indicating good inter-observer and intra-observer agreement. SD, standard deviation; D*, pseudo diffusion; D, water molecular diffusion; f, perfusion fraction.

Factors affecting IVIM-DWI image quality

In this study, 13 participants were excluded because of the poor quality of IVIM-DWI images. Totally 13 participants were included in the failure group and the remaining 89 participants were assigned to the success group. The clinical characteristics were compared between the two groups. A significant difference in heart rate was found between the two groups (62.0±8.1 vs. 72.2±10.0 bpm, P<0.001). The clinical characteristics in the failure and success groups are shown in Table 3.

Discussion

In this study, the value of IVIM-DWI for the assessment of myocardial microcirculation dysfunction in hypertension was evaluated. We found significant differences in D* values between the hypertension and healthy control groups, as well as among the three hypertension subgroups. IVIM-DWI has proven feasible in the quantitative evaluation of myocardial microcirculation dysfunction in hypertensive patients. D* parameter has a potential value in assessing the severity of microcirculation dysfunction in different BP categories.

Nowadays, the pathophysiology of myocardial microcirculation dysfunction in hypertension has been extensively examined (3-10). Hypertension, myocardial microcirculation, and microcirculation dysfunction are tightly interconnected into a dangerous cross-link (4). Myocardial microcirculation dysfunction can deteriorate cardiac damage resulting from elevated hemodynamic load in hypertension, including LV hypertrophy, impaired systolic and diastolic functions, left atria enlargement, and new onset of atrial fibrillation. The interaction between microcirculation dysfunction, LV hypertrophy, and left ventricular diastolic dysfunction may further promote aortic stiffness, reduce microcirculatory flow reserve, impair tissue perfusion, and induce susceptibility in ischemia (3-5). This study found myocardial microcirculation reflected by IVIM-DWI is impaired in hypertensive individuals, consistent with the pathophysiology of hypertension. The extensively examined pathophysiology of myocardial microcirculation dysfunction in hypertension provided a pathological foundation for this study.

Quantitative and accurate assessment of microcirculation dysfunction is of great significance in providing insights into the pathophysiological features of different cardiovascular diseases. A range of noninvasive and invasive methods are available or emerging for the evaluation of various aspects of microcirculation in animals and humans, each of which has advantages and limitations (33-37). As a “one-stop” exam, CMR could simultaneously assess cardiac anatomy, morphology, function, myocardial perfusion, and myocardial activity (11-13). CMR stress perfusion has been recommended as a routine diagnostic tool to identify inducible myocardial ischemia, and also has a diagnostic and prognostic value in individuals with suspected microcirculation dysfunction (38,39). However, it is hard to apply in clinic. IVIM-DWI is a novel tool to assess myocardial perfusion status. It could quantitatively evaluate in vivo diffusion modeling without contrast agent injection. Compared with traditional DWI, IVIM-DWI could provide more details concerning water molecular motion among myocytes, microcirculation, and vascular flow. Recent studies have examined the feasibility and repeatability of IVIM-DWI in characterizing myocardial microcirculation dysfunction in multiple cardiac diseases (22-27). Mou et al. performed cardiac IVIM-DWI in patients with hypertrophic cardiomyopathy, diabetes mellitus, and/or hypertension, and found that D* values were significantly lower in patient groups than in healthy volunteers (22). An et al. evaluated myocardial perfusion in myocardial infarction patients after percutaneous transluminal coronary intervention (PCI) by IVIM-DWI. The authors demonstrated that D* and f values were significantly reduced at infarct regions (23). Significantly decreased D* and f values were also found in the fibrotic regions of the myocardium in hypertrophic cardiomyopathy patients, indicating impaired myocardial perfusion (25,26). Besides, IVIM-DWI was applied to examine different myocardial perfusion patterns in acute myocardial infarction and infarct-like myocarditis, and lower myocardial perfusion status was detected in acute myocardial infarction (27). The present study found significantly lower D* values in hypertensive patients, corroborating the above report. We found no significant differences in f values between hypertensive patients and healthy controls, which was similar to Mou et al. Compared with acute myocardial infarction, infarct-like myocarditis and hypertrophic cardiomyopathy, the myocardium of hypertension shows diffuse and mild myocardial fibrosis. Significant correlations have been determined between IVIM-DWI parameters and myocardial infarct/fibrosis (23-26). There were significantly lower f values at infarct/fibrotic regions of the myocardium, which demonstrated focal and remarkable late gadolinium enhancement (LGE) or increased T1 values/extracellular volume (ECV). The severity of myocardial damage might result from no significant difference in f values. The D* parameter might be utilized as a more sensitive IVIM-DWI index to evaluate myocardial perfusion status compared with the f parameter. We also found significant differences among the three hypertension subgroups in D* values. The negative correlation between D* value and hypertension severity indicated that higher BP could aggravate myocardial microcirculation dysfunction, which was consistent with the pathophysiology of hypertension.

The IVIM-DWI sequence, derived from diffusion-weighted imaging, still remains many deficiencies. First of all, it is very sensitive to the patient’s heart and lung motions. Second, the scan time is long because of its multi-b values. Third, the results depend heavily on the fitting methodology (39-41). In this study, respiratory navigator and retrospective ECG gating techniques were applied, and all IVIM-DWI indexes were acquired under free-breathing conditions and end-diastole of the cardiac cycle. Still, 13 participants were excluded from the present analysis because of poor image quality. We analyzed the clinical features of the excluded participants and found significant differences in heart rate between the two groups (62.0±8.1 vs. 72.2±10.0 bpm, P<0.001). Our results confirmed heart rate as one of the essential factors affecting image quality for the IVIM-DWI sequence (22). High heartbeat may shorten the signal acquisition time to decrease image quality. In a further study, heart rate control measurements could be performed to ensure image quality for the IVIM-DWI sequence. In the future, the application of some new technologies, such as diffusion-derived vessel density (DVDD), may reduce these deficiencies and be better applied in clinic (40,41).

This study had several limitations. First, as a novel imaging method to assess myocardial microcirculation status, the diagnostic accuracy of IVIM-DWI has been less examined compared with other methods, including stress perfusion CMR, single photon emission computed tomography and invasive coronary angiography with fractional flow reserve. Furthermore, we recognize the potential benefits of advanced analysis techniques such as tractography or diffusion tensor imaging (DTI), which can provide additional insights into tissue microstructure and connectivity by modeling the diffusion tensor in multiple directions. These techniques may complement ROI-based analyses and offer a more comprehensive understanding of anisotropic diffusion effects. Further studies are required to evaluate its value and potential for further improvement. Secondly, IVIM-DWI images may have artifacts from other bulk flow phenomena, and the number of b values and b value distribution still need further optimization; Suitable software could minimize the misalignment between volumes used averaging of DWIs, such as DIPY (Diffusion Imaging in Python), a library for the analysis of diffusion MRI data (42). It would be of great benefit for our further studies. In addition, motion compensation gradient waveforms in DWI sequences may further improve the quality of DWI images as well as the stability and reliability of IVIM-related parameters. Thirdly, as the hypertension group was subdivided according to BP categories, the sample size of each subgroup was still small.

Conclusions

In conclusion, IVIM-DWI has proven feasible in quantitatively evaluating myocardial microcirculation dysfunction in hypertension. The D* parameter has a potential value in the assessment of the severity of microcirculation dysfunction in different BP categories.

Acknowledgments

Funding: This work was supported by the Shandong Provincial Natural Science Foundation of China Grants (No. ZR2019MH125 to C.W.) and the Shandong Provincial Natural Science Foundation of China Grants (No. ZR2020QH266 to H.W.).

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-24-108/rc

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-24-108/coif). W.C. reports that he is an MR collaborating scientist from Philips Healthcare providing technical support under the Philips collaboration regulations and has no financial or other conflicts for this study. C.W. reports that study was supported by the Shandong Provincial Natural Science Foundation of China Grants (No. ZR2019MH125). H.W. reports that study was supported by the Shandong Provincial Natural Science Foundation of China Grants (No. ZR2020QH266). The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the ethics committee of Shandong Provincial Hospital Affiliated to Shandong First Medical University (NSFC: No. 2020-382), and written informed consent was obtained from all participants.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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