Assessment of Non-contrast-enhanced Dixon Water-fat Separation Compressed Sensing Whole-heart Coronary MR Angiography at 3.0 T: A Single-center Experience

Diagnostic performance of 3.0 T unenhanced Dixon water-fat separation coronary MR angiography in patients with low-to-intermediate risk of coronary artery disease

PURPOSE

To evaluate the diagnostic performance of 3.0 T unenhanced compressed-sensing sensitivity encoding (CS-SENSE) Dixon water-fat separation coronary MR angiography (CMRA) in patients with low-to-intermediate risk of coronary artery disease (CAD) and its ability to grade the severity of CAD based on Coronary Artery Disease Reporting and Data System (CAD-RADS).

METHODS

A total of 55 patients who was clinically evaluated as low-to-intermediate risk of CAD were finally included to undergo both 3.0 T CS-SENSE water-fat separation CMRA and coronary computed tomography angiography (CCTA), and 11 of them also underwent X-ray coronary angiography (CAG). The severity of coronary artery disease was graded in patients who had completed both CCTA and CMRA examinations by the use of CAD-RADS reports for the patients with stable chest pain, and the diagnostic consistency between the two approaches was evaluated. Diagnostic performance of CMRA was assessed using the combination of CCTA and CAG as the reference standard for excluding or confirming CAD respectively.

RESULTS

The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic accuracy of 3.0 T unenhanced water-fat separation coronary MRA were 90.0%, 95.0%, 81.8%, 97.4% and 94.0% for a patient-based analysis respectively. In comparison with CCTA, 3.0 T Dixon water-fat separation CMRA demonstrated excellent consistency in grading the severity of coronary heart disease according to CAD-RADS (0.77 for kappa value).

CONCLUSION

In the group of low-to-intermediate probability for CAD, 3.0 T unenhanced CS-SENSE Dixon water-fat separation CMRA can present satisfactory diagnostic performance for the exclusion of CAD with high sensitivity and negative predictive value as well as the evaluation of grading the severity of coronary artery disease.

Feasibility of accelerated non-contrast-enhanced whole-heart bSSFP coronary MR angiography by deep learning-constrained compressed sensing

OBJECTIVES

To examine a compressed sensing artificial intelligence (CSAI) framework to accelerate image acquisition in non-contrast-enhanced whole-heart bSSFP coronary magnetic resonance (MR) angiography.

METHODS

Thirty healthy volunteers and 20 patients with suspected coronary artery disease (CAD) scheduled for coronary computed tomography angiography (CCTA) were enrolled. Non-contrast-enhanced coronary MR angiography was performed with CSAI, compressed sensing (CS), and sensitivity encoding (SENSE) methods in healthy participants and with CSAI in patients. Acquisition time, subjective image quality score, and objective image quality measurement (blood pool homogeneity, signal-to-noise ratio [SNR], and contrast-to-noise ratio [CNR]) were compared among the three protocols. The diagnostic performance of CASI coronary MR angiography for predicting significant stenosis (≥ 50% diameter stenosis) on CCTA was evaluated. The Friedman test was performed to compare the three protocols.

RESULTS

Acquisition time was significantly shorter in the CSAI and CS groups than in the SENSE group (10.2 ± 3.2 min vs. 10.9 ± 2.9 min vs. 13.0 ± 4.1 min, p < 0.001). However, the CSAI approach had the highest image quality scores, blood pool homogeneity, mean SNR value, and mean CNR value (all p < 0.001) compared with the CS and SENSE approaches. The sensitivity, specificity, and accuracy of CSAI coronary MR angiography per patient were 87.5% (7/8), 91.7% (11/12), and 90.0% (18/20); those per vessel were 81.8% (9/11), 93.9% (46/49), and 91.7% (55/60); and those per segment were 84.6% (11/13), 98.0% (244/249), and 97.3% (255/262), respectively.

CONCLUSIONS

CSAI yielded superior image quality within a clinically feasible acquisition time in healthy participants and patients with suspected CAD.

CLINICAL RELEVANCE STATEMENT

The non-invasive and radiation-free CSAI framework could be a promising tool for rapid screening and comprehensive examination of the coronary vasculature in patients with suspected CAD.

KEY POINTS

• This prospective study showed that CSAI enables a reduction in acquisition time by 22% with superior diagnostic image quality compared with the SENSE protocol. • CSAI replaces the wavelet transform with a CNN as a sparsifying transform in the CS algorithm, achieving high coronary MR image quality with reduced noise. • CSAI achieved per-patient sensitivity of 87.5% (7/8) and specificity of 91.7% (11/12) respectively for detecting significant coronary stenosis.

Deep Learning-Based Acceleration of Compressed Sensing for Noncontrast-Enhanced Coronary Magnetic Resonance Angiography in Patients With Suspected Coronary Artery Disease

BACKGROUND

The clinical application of coronary MR angiography (MRA) remains limited due to its long acquisition time and often unsatisfactory image quality. A compressed sensing artificial intelligence (CSAI) framework was recently introduced to overcome these limitations, but its feasibility in coronary MRA is unknown.

PURPOSE

To evaluate the diagnostic performance of noncontrast-enhanced coronary MRA with CSAI in patients with suspected coronary artery disease (CAD).

STUDY TYPE

Prospective observational study.

POPULATION

A total of 64 consecutive patients (mean age ± standard deviation [SD]: 59 ± 10 years, 48.4% females) with suspected CAD.

FIELD STRENGTH/SEQUENCE

A 3.0-T, balanced steady-state free precession sequence.

ASSESSMENT

Three observers evaluated the image quality for 15 coronary segments of the right and left coronary arteries using a 5-point scoring system (1 = not visible; 5 = excellent). Image scores ≥3 were considered diagnostic. Furthermore, the detection of CAD with ≥50% stenosis was evaluated in comparison to reference standard coronary computed tomography angiography (CTA). Mean acquisition times for CSAI-based coronary MRA were measured.

STATISTICAL TESTS

For each patient, vessel and segment, sensitivity, specificity, and diagnostic accuracy of CSAI-based coronary MRA for detecting CAD with ≥50% stenosis according to coronary CTA were calculated. Intraclass correlation coefficients (ICCs) were used to assess the interobserver agreement.

RESULTS

The mean MR acquisition time ± SD was 8.1 ± 2.4 minutes. Twenty-five (39.1%) patients had CAD with ≥50% stenosis on coronary CTA and 29 (45.3%) patients on MRA. A total of 885 segments on the CTA images and 818/885 (92.4%) coronary MRA segments were diagnostic (image score ≥3). The sensitivity, specificity, and diagnostic accuracy were as follows: per patient (92.0%, 84.6%, and 87.5%), per vessel (82.9%, 93.4%, and 91.1%), and per segment (77.6%, 98.2%, and 96.6%), respectively. The ICCs for image quality and stenosis assessment were 0.76-0.99 and 0.66-1.00, respectively.

DATA CONCLUSION

The image quality and diagnostic performance of coronary MRA with CSAI may show good results in comparison to coronary CTA in patients with suspected CAD.

EVIDENCE LEVEL

1.

TECHNICAL EFFICACY

2.

3.0 T unenhanced Dixon water-fat separation whole-heart coronary magnetic resonance angiography: compressed-sensing sensitivity encoding imaging versus conventional 2D sensitivity encoding imaging

This study was aimed to investigate 3.0 T unenhanced Dixon water-fat whole-heart CMRA (coronary magnetic resonance angiography) using compressed-sensing sensitivity encoding (CS-SENSE) and conventional sensitivity encoding (SENSE) in vitro and in vivo. The key parameters of CS-SENSE and conventional 1D/2D SENSE were compared in vitro phantom study. In vivo study, fifty patients with suspected coronary artery disease (CAD) completed unenhanced Dixon water-fat whole-heart CMRA at 3.0 T using both CS-SENSE and conventional 2D SENSE methods. We compared mean acquisition time, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and the diagnostic accuracy between two techniques. In vitro study, CS-SENSE achieved better effectiveness between higher SNR/CNR and shorter scan times using the appropriate acceleration factor compared with conventional 2D SENSE. In vivo study, CS-SENSE CMRA had better performance than 2D SENSE in terms of the mean acquisition time, SNR and CNR (7.4 ± 3.2 min vs. 8.3 ± 3.4 min, P = 0.001; SNR: 115.5 ± 35.4 vs. 103.3 ± 32.2; CNR: 101.1 ± 33.2 vs. 90.6 ± 30.1, P < 0.001 for both). The diagnostic accuracy between CS-SENSE and 2D SENSE had no significant difference on a patient-based analysis (sensitivity: 97.3% vs. 91.9%; specificity: 76.9% vs. 61.5%; accuracy: 92.0% vs. 84.0%; P > 0.05 for each). Unenhanced CS-SENSE Dixon water-fat separation whole-heart CMRA at 3.0 T can improve the SNR and CNR, shorten the acquisition time while providing equally satisfactory image quality and diagnostic accuracy compared with 2D SENSE CMRA.

Diagnostic accuracy of whole heart coronary magnetic resonance angiography: a systematic review and meta-analysis

BACKGROUND

The purpose of this meta-analysis was to comprehensively investigate the diagnostic ability of 1.5 T and 3.0 T whole heart coronary angiography (WHCA) to detect significant coronary artery disease (CAD) on X-ray coronary angiography.

METHODS

A literature search of electronic databases, including PubMed, Web of Science Core Collection, Cochrane advanced search, and EMBASE, was performed to retrieve and integrate articles showing significant CAD detectability of 1.5 and 3.0 T WHCA.

RESULTS

Data from 1899 patients from 34 studies were included in the meta-analysis. 1.5 T WHCA had a summary area under ROC of 0.88 in the patient-based analysis, 0.90 in the vessel-based analysis, and 0.92 in the segment-based analysis. These values for 3.0 T WHCA were 0.94, 0.95, 0.96, respectively. Contrast-enhanced 3.0 T WHCA had significantly higher specificity than non-contrast-enhanced 1.5 T WHCA on a patient-based analysis (0.87, 95% CI 0.80-0.92 vs. 0.74, 95% CI 0.64-0.82, P = 0.02). There were no differences in diagnostic performance on a patient-based analysis by use of vasodilators, beta-blockers or between Asian and Western countries.

CONCLUSIONS

The diagnostic performance of WHCA was deemed satisfactory, with contrast-enhanced 3.0 T WHCA exhibiting higher specificity compared to non-contrast-enhanced 1.5 T WHCA in a patient-based analysis. There were no significant differences in diagnostic performance on a patient-based analysis in terms of vasodilator or beta-blocker use, nor between Asian and Western countries. However, further large-scale multicentre studies are crucial for the widespread global adoption of WHCA.

3D whole-heart noncontrast coronary MR angiography based on compressed SENSE technology: a comparative study of conventional SENSE sequence and coronary computed tomography angiography

OBJECTIVE

The relatively long scan time has hampered the clinical use of whole-heart noncontrast coronary magnetic resonance angiography (NCMRA). The compressed sensitivity encoding (SENSE) technique, also known as the CS technique, has been found to improve scan times. This study aimed to identify the optimal CS acceleration factor for NCMRA.

METHODS

Thirty-six participants underwent four NCMRA sequences: three sequences using the CS technique with acceleration factors of 4, 5, and 6, and one sequence using the conventional SENSE technique with the acceleration factor of 2. Coronary computed tomography angiography (CCTA) was considered as a reference sequence. The acquisition times of the four NCMRA sequences were assessed. The correlation and agreement between the visible vessel lengths obtained via CCTA and NCMRA were also assessed. The image quality scores and contrast ratio (CR) of eight coronary artery segments from the four NCMRA sequences were quantitatively evaluated.

RESULTS

The mean acquisition time of the conventional SENSE was 343 s, while that of CS4, CS5, and CS6 was 269, 215, and 190 s, respectively. The visible vessel length from the CS4 sequence showed good correlation and agreement with CCTA. The image quality score and CR from the CS4 sequence were not statistically significantly different from those in the other groups (p > 0.05). Moreover, the image score and CR showed a decreasing trend with the increase in the CS factor.

CONCLUSIONS

The CS technique could significantly shorten the acquisition time of NCMRA. The CS sequence with an acceleration factor of 4 was generally acceptable for NCMRA in clinical settings to balance the image quality and acquisition time.