Comparing compressed sensing breath-hold 3D MR cholangiopancreatography with two parallel imaging MRCP strategies in main pancreatic duct and common bile duct

Deep Learning Reconstruction for Enhanced Resolution and Image Quality in Breath-Hold MRCP: A Preliminary Study

OBJECTIVE

This preliminary study aims to assess the image quality of enhanced-resolution deep learning reconstruction (ER-DLR) in magnetic resonance cholangiopancreatography (MRCP) and compare it with non-ER-DLR MRCP images.

METHODS

Our retrospective study incorporated 34 patients diagnosed with biliary and pancreatic disorders. We obtained MRCP images using a single breath-hold MRCP on a 3T MRI system. We reconstructed MRCP images with ER-DLR (matrix = 768 × 960) and without ER-DLR (matrix = 256 × 320). Quantitative evaluation involved measuring the signal-to-noise ratio (SNR), contrast, contrast-to-noise ratio (CNR) between the common bile duct and periductal tissues, and slope. Two radiologists independently scored image noise, contrast, artifacts, sharpness, and overall image quality for the 2 image types using a 4-point scale. Results are expressed as median and interquartile range (IQR), and we compared quantitative and qualitative scores employing the Wilcoxon test.

RESULTS

In quantitative analyses, ER-DLR significantly improved SNR (21.08 [IQR: 14.85, 31.5] vs 15.07 [IQR: 9.57, 25.23], P  < 0.001), CNR (19.29 [IQR: 13.87, 24.98] vs 11.23 [IQR: 8.98, 15.74], P  < 0.001), contrast (0.96 [IQR: 0.94, 0.97] vs 0.9 [IQR: 0.87, 0.92], P  < 0.001), and slope of MRCP (0.62 [IQR: 0.56, 0.66] vs 0.49 [IQR: 0.45, 0.53], P  < 0.001). The qualitative evaluation demonstrated significant improvements in the perceived noise ( P  < 0.001), contrast ( P  = 0.013), sharpness ( P  < 0.001), and overall image quality ( P  < 0.001).

CONCLUSIONS

ER-DLR markedly increased the resolution, SNR, and CNR of breath-hold-MRCP compared to cases without ER-DLR.

Clinical application of prone position to suppress respiratory movement artifacts in supine position during magnetic resonance cholangiopancreatography/MRI

PURPOSE

To compare the image quality of magnetic resonance cholangiopancreatography (MRCP) in the supine position and prone position under the conditions of the same equipment, the same sequence (3D Navigator Triggered Sampling Perfection with Application-Optimized Contrast Using Different Flip-angle Evolutions, 3D-NT-SPACE) and the same patient, and to explore the clinical application value of prone position in MRCP examination to suppress respiratory motion artifacts.

METHODS

53 participants who underwent MRCP in our hospital from April 2020 to August 2022 were prospectively collected. The 3D-NT-SPACE sequence was used in these patients. The visibility of the common bile duct, common hepatic duct, main pancreatic duct, and first- and second- and third-level branches of the intrahepatic bile duct and the comfort of the participants in two positions were subjective-evaluated. The Signal-to-noise ratio (SNR) and contrast-to-noise ratio were objective-evaluated. Statistical analysis was performed using Shapiro-Wilk, Levene's, Mann Whitney U test, Pearson chi-square test, and one-sample chi-square test.

RESULTS

53 patients (51.92 years ± 2.02, 20 men) were evaluated. There were significant differences in the second- and third-level branches visibility score, the main pancreatic duct visibility score, the image quality score of the pancreaticobiliary tree, the blur and motion artifact score, the total image quality score, and SNR between the two positions (p < 0.05).

CONCLUSIONS

The overall image quality of the prone position was better than that of the supine position. The prone position is a useful complement to the supine position.

Compressed sensing 3D T2WI radiomics model: improving diagnostic performance in muscle invasion of bladder cancer

BACKGROUND

Preoperative discrimination between non-muscle-invasive bladder cancer (NMIBC) and the muscle invasive bladder cancer (MIBC) is a determinant of management. The purpose of this research is to employ radiomics to evaluate the diagnostic value in determining muscle invasiveness of compressed sensing (CS) accelerated 3D T2-weighted-SPACE sequence with high resolution and short acquisition time.

METHODS

This prospective study involved 108 participants who underwent preoperative 3D-CS-T2-weighted-SPACE, 3D-T2-weighted-SPACE and T2-weighted sequences. The cohort was divided into training and validation cohorts in a 7:3 ratio. In the training cohort, a Rad-score was constructed based on radiomic features selected by intraclass correlation coefficients, pearson correlation coefficient and least absolute shrinkage and selection operator . Multivariate logistic regression was used to develop a nomogram combined radiomics and clinical indices. In the validation cohort, the performances of the models were evaluated by ROC, calibration, and decision curves.

RESULTS

In the validation cohort, the area under ROC curve of 3D-CS-T2-weighted-SPACE, 3D-T2-weighted-SPACE and T2-weighted models were 0.87(95% confidence interval (CI):0.73-1.00), 0.79(95%CI:0.63-0.96) and 0.77(95%CI:0.60-0.93), respectively. The differences in signal-to-noise ratio and contrast-to-noise ratio between 3D-CS-T2-weighted-SPACE and 3D-T2-weighted-SPACE sequences were not statistically significant(p > 0.05). While the clinical model composed of three clinical indices was 0.74(95%CI:0.55-0.94) and the radiomics-clinical nomogram model was 0.88(95%CI:0.75-1.00). The calibration curves confirmed high goodness of fit, and the decision curve also showed that the radiomics model and combined nomogram model yielded higher net benefits than the clinical model.

CONCLUSION

The radiomics model based on compressed sensing 3D T2WI sequence, which was acquired within a shorter acquisition time, showed superior diagnostic efficacy in muscle invasion of bladder cancer. Additionally, the nomogram model could enhance the diagnostic performance.

Accelerated 3D MR neurography of the brachial plexus using deep learning-constrained compressed sensing

OBJECTIVES

To explore the use of deep learning-constrained compressed sensing (DLCS) in improving image quality and acquisition time for 3D MRI of the brachial plexus.

METHODS

Fifty-four participants who underwent contrast-enhanced imaging and forty-one participants who underwent unenhanced imaging were included. Sensitivity encoding with an acceleration of 2 × 2 (SENSE4x), CS with an acceleration of 4 (CS4x), and DLCS with acceleration of 4 (DLCS4x) and 8 (DLCS8x) were used for MRI of the brachial plexus. Apparent signal-to-noise ratios (aSNRs), apparent contrast-to-noise ratios (aCNRs), and qualitative scores on a 4-point scale were evaluated and compared by ANOVA and the Friedman test. Interobserver agreement was evaluated by calculating the intraclass correlation coefficients.

RESULTS

DLCS4x achieved higher aSNR and aCNR than SENSE4x, CS4x, and DLCS8x (all p < 0.05). For the root segment of the brachial plexus, no statistically significant differences in the qualitative scores were found among the four sequences. For the trunk segment, DLCS4x had higher scores than SENSE4x (p = 0.04) in the contrast-enhanced group and had higher scores than SENSE4x and DLCS8x in the unenhanced group (all p < 0.05). For the divisions, cords, and branches, DLCS4x had higher scores than SENSE4x, CS4x, and DLCS8x (all p ≤ 0.01). No overt difference was found among SENSE4x, CS4x, and DLCS8x in any segment of the brachial plexus (all p > 0.05).

CONCLUSIONS

In three-dimensional MRI for the brachial plexus, DLCS4x can improve image quality compared with SENSE4x and CS4x, and DLCS8x can maintain the image quality compared to SENSE4x and CS4x.

CLINICAL RELEVANCE STATEMENT

Deep learning-constrained compressed sensing can improve the image quality or accelerate acquisition of 3D MRI of the brachial plexus, which should be benefit in evaluating the brachial plexus and its branches in clinical practice.

KEY POINTS

•Deep learning-constrained compressed sensing showed higher aSNR, aCNR, and qualitative scores for the brachial plexus than SENSE and CS at the same acceleration factor with similar scanning time. •Deep learning-constrained compressed sensing at acceleration factor of 8 had comparable aSNR, aCNR, and qualitative scores to SENSE4x and CS4x with approximately half the examination time. •Deep learning-constrained compressed sensing may be helpful in clinical practice for improving image quality and acquisition time in three-dimensional MRI of the brachial plexus.

Evaluation of three-dimensional dual-energy CT cholangiopancreatography image quality in patients with pancreatobiliary dilatation: Comparison with conventional single-energy CT

Objective

This study aimed to evaluate three-dimensional (3D) negative-contrast CT cholangiopancreatography (nCTCP) image quality using dual-energy CT (DECT) with iterative reconstruction (IR) technique in patients with pancreatobiliary dilatation compared with single-energy CT (SECT).

Methods

Of the patients, 67 and 56 underwent conventional SECT (SECT set) and DECT with IR technique (DECT set), respectively. All patients were retrospectively analyzed during the portal phase to compare objective image quality and other data including patient demographics, hepatic and pancreatic parenchymal enhancement, noise, and attenuation difference (AD) between dilated ducts and enhanced hepatic parenchyma, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and CT volume dose index (CTDIvol). Two radiologists used the five-point Likert scale to evaluate the subjective image quality of 3D nCTCP regarding image noise, sharpness of dilated ducts, and overall image quality. Statistical analyses used the Mann-Whitney U test.

Results

No significant difference in patient demographics in either CT set was showed during objective evaluation (p > 0.05). However, higher hepatic and pancreatic parenchymal enhancement, AD, SNR, and CNR and lower hepatic and pancreatic noise (p < 0.005) as well as CTDIvol (p = 0.005) on DECT than on SECT were observed. Higher mean grades on DECT than on SECT were showed for image noise (4.65 vs 3.92), sharpness of dilated ducts (4.52 vs 3.94), and overall image quality (4.45 vs 3.91; p < 0.001), respectively during subjective evaluation.

Conclusion

A higher overall image quality and lower radiation dose on 3D nCTCP can be obtained by DECT with IR technique than with conventional SECT in patients with pancreatobiliary dilatation.

Deep learning-based reconstruction and 3D hybrid profile order technique for MRCP at 3T: evaluation of image quality and acquisition time

OBJECTIVES

To evaluate the image quality of the 3D hybrid profile order technique and deep-learning-based reconstruction (DLR) for 3D magnetic resonance cholangiopancreatography (MRCP) within a single breath-hold (BH) at 3 T magnetic resonance imaging (MRI).

METHODS

This retrospective study included 32 patients with biliary and pancreatic disorders. BH images were reconstructed with and without DLR. The signal-to-noise ratio (SNR), contrast, contrast-to-noise ratio (CNR) between the common bile duct (CBD) and periductal tissues, and full width at half maximum (FWHM) of CBD on 3D-MRCP were evaluated quantitatively. Two radiologists scored image noise, contrast, artifacts, blur, and overall image quality of the three image types using a 4-point scale. Quantitative and qualitative scores were compared using the Friedman test and post hoc Nemenyi test.

RESULTS

The SNR and CNR were not significantly different when under respiratory gating- and BH-MRCP without DLR. However, they were significantly higher under BH with DLR than under respiratory gating (SNR, p = 0.013; CNR, p = 0.027). The contrast and FWHM of MRCP under BH with and without DLR were lower than those under respiratory gating (contrast, p < 0.001; FWHM, p = 0.015). Qualitative scores for noise, blur, and overall image quality were higher under BH with DLR than those under respiratory gating (blur, p = 0.003; overall, p = 0.008).

CONCLUSIONS

The combination of the 3D hybrid profile order technique and DLR is useful for MRCP within a single BH and does not lead to the deterioration of image quality and space resolution at 3 T MRI.

CLINICAL RELEVANCE STATEMENT

Considering its advantages, this sequence might become the standard protocol for MRCP in clinical practice, at least at 3.0 T.

KEY POINTS

• The 3D hybrid profile order can achieve MRCP within a single breath-hold without a decrease in spatial resolution. • The DLR significantly improved the CNR and SNR of BH-MRCP. • The 3D hybrid profile order technique with DLR reduces the deterioration of image quality in MRCP within a single breath-hold.

Rapid 3D breath-hold MR cholangiopancreatography using deep learning-constrained compressed sensing reconstruction

OBJECTIVES

To compare the image quality of three-dimensional breath-hold magnetic resonance cholangiopancreatography with deep learning-based compressed sensing reconstruction (3D DL-CS-MRCP) to those of 3D breath-hold MRCP with compressed sensing (3D CS-MRCP), 3D breath-hold MRCP with gradient and spin-echo (3D GRASE-MRCP) and conventional 2D single-shot breath-hold MRCP (2D MRCP).

METHODS

In total, 102 consecutive patients who underwent MRCP at 3.0 T, including 2D MRCP, 3D GRASE-MRCP, 3D CS-MRCP, and 3D DL-CS-MRCP, were prospectively included. Two radiologists independently analyzed the overall image quality, background suppression, artifacts, and visualization of pancreaticobiliary ducts using a five-point scale. The signal-to-noise ratio (SNR) of the common bile duct (CBD), contrast-to-noise ratio (CNR) of the CBD and liver, and contrast ratio between the periductal tissue and CBD were measured. The Friedman test was performed to compare the four protocols.

RESULTS

3D DL-CS-MRCP resulted in improved SNR and CNR values compared with those in the other three protocols, and better contrast ratio compared with that in 3D CS-MRCP and 3D GRASE-MRCP (all, p < 0.05). Qualitative image analysis showed that 3D DL-CS-MRCP had better performance for second-level intrahepatic ducts and distal main pancreatic ducts compared with 3D CS-MRCP (all, p < 0.05). Compared with 2D MRCP, 3D DL-CS-MRCP demonstrated better performance for the second-order left intrahepatic duct but was inferior in assessing the main pancreatic duct (all, p < 0.05). Moreover, the image quality was significantly higher in 3D DL-CS-MRCP than in 3D GRASE-MRCP.

CONCLUSION

3D DL-CS-MRCP has superior performance compared with that of 3D CS-MRCP or 3D GRASE-MRCP. Deep learning reconstruction also provides a comparable image quality but with inferior main pancreatic duct compared with that revealed by 2D MRCP.

KEY POINTS

• 3D breath-hold MRCP with deep learning reconstruction (3D DL-CS-MRCP) demonstrated improved image quality compared with that of 3D MRCP with compressed sensing or GRASE. • Compared with 2D MRCP, 3D DL-CS-MRCP had superior performance in SNR and CNR, better visualization of the left second-level intrahepatic bile ducts, and comparable overall image quality, but an inferior main pancreatic duct.

Predicting the image quality of respiratory-gated and breath-hold 3D MRCP from the breathing curve: a prospective study

OBJECTIVES

To compare the image quality of breath-hold magnetic resonance cholangiopancreatography (BH-MRCP) and respiratory-gating MRCP (RG-MRCP), and to explore breathing curve-based factors and patient-related data affecting image quality.

METHODS

A total of 126 participants who underwent RG-MRCP and BH-MRCP on a 3-T magnetic resonance (MR) scanner were enrolled from May to December 2021. The images were evaluated by three radiologists on a 5-point scale. Respiratory parameters were extracted from the breathing curves. The Wilcoxon test was used to compare the image quality between the two MRCPs. Logistic regression analyzes were performed to identify age, sex, abdominal pain, and breathing predictor variables of better image quality.

RESULTS

BH-MRCP performed better in visualizing intrahepatic bile ducts and overall image quality than RG-MRCP (p < 0.01). Factors predicting relatively good image quality included lower standard deviation of the respiratory amplitude (SD_amp)-minimum-peak (odds ratio = 0.16, p < 0.01) for RG-MRCP and lower SD_amp (OR = 0.69, p < 0.01) for BH-MRCP.

CONCLUSIONS

BH-MRCP had significantly better overall image quality than RG-MRCP. Respiratory conditions exerted a significant impact on MRCP image quality, and parameters derived from the breathing curve could help predict the image quality of both sequences.

KEY POINTS

• Both breath-hold (BH) and respiratory-gating (RG) MRCP demonstrate satisfying image quality. • BH-GRASE-MRCP is significantly better than RG-MRCP at the group level, but not for every individual. • Respiratory conditions exert a significant impact on the image quality, and the breathing curve can help predict the image quality.

Feasibility of 3D Breath-Hold MR Cholangiopancreatography with a Spatially Selective Radiofrequency Excitation Pulse: Prospective Comparison with Parallel Imaging Technique and Compressed Sensing Method

RATIONALE AND OBJECTIVES

The purpose of the present study was to evaluate the clinical feasibility of the modified 3D breath-hold magnetic resonance cholangiopancreatography with parallel imaging (3D-BH-PI-MRCP) using a spatially selective radiofrequency excitation pulse in patients with suspected pancreaticobiliary diseases. Moreover, we also compared its image quality with those of the original 3D-BH-PI-MRCP with a nonselective exciting pulse and the 3D breath hold compressed sensing magnetic resonance cholangiopancreatography (3D-BH-CS-MRCP).

MATERIALS AND METHODS

Between January 2021 and July 2021, 106 patients prospectively underwent modified 3D-BH-PI-MRCP, original 3D-BH-PI-MRCP and 3D-BH-CS-MRCP at 3T in this study. The Friedman test was performed to compare the contrast, signal-to-noise-ratio (SNR), and contrast-noise-ratio, overall image quality, and duct visualization among the three protocols.

RESULTS

The contrast ratio, SNR and contrast-to-noise ratio of the common bile duct differed significantly among the three sequences (p < 0.001). Compared to the 3D-BH-CS-MRCP protocol, the overall imaging quality of the two 3D-BH-PI-MRCP was higher but not significantly different. The scores for the anterior and posterior branches visualization were significantly higher in the original 3D-BH-PI-MRCP compared to the 3D-BH-CS-MRCP, but were no significant differences between the modified 3D-BH-PI-MRCP and the 3D-BH-CS-MRCP.

CONCLUSION

The modified 3D-BH-PI-MRCP with a spatially selective radiofrequency excitation pulse could provide comparable image quality to the original 3D-BH-PI-MRCP and the 3D-BH-CS-MRCP during a single breath hold (22 seconds), and showed improved SNR and superior visualization of the pancreaticobiliary tree.

Accelerated 3D high-resolution T2-weighted breast MRI with deep learning constrained compressed sensing, comparison with conventional T2-weighted sequence on 3.0 T

PURPOSE

To evaluate the feasibility of isotropic 3D high-resolution T2-weighted imaging (T2WI) MRI sequences and compare the images reconstructed by integrating artificial intelligence-compressed sensing (AI-CS), compressed sensing (CS), and conventional 2D T2WI sequences for quality.

MATERIALS AND METHODS

Fifty-two female patients (ages: 26-80 years) with suspected breast cancer were enrolled. They underwent breast MRI examinations using three sequences: conventional T2WI, CS 3D T2WI, and AI-CS 3D T2WI. Image quality, signal-to-noise ratio (SNR), contrast-to-noise ratio, tumor volume, and maximal tumor diameter were compared using the Friedman test. Image quality was scored on a 5-point scale, with 1 indicating nonassessable quality and 5 indicating excellent quality. Tumor volume and maximal tumor diameter were compared based on AI-CS 3D T2WI (slightly high signal), conventional T2WI, and dynamic contrast-enhanced (DCE) sequences.

RESULTS

All three T2WI were successfully performed in all patients. 3D CS and AI-CS were significantly better than conventional T2WI in terms of lesion conspicuity and morphology, structural details, overall image quality, diagnostic information for breast lesions, and breast tissue delineation (P < 0.001). The SNR of conventional T2WI was significantly higher for 3D T2WI sequences. The contrast-to-noise ratio was significantly higher for AI-CS 3D T2WI than for conventional T2WI sequence. There was no significant difference in tumor volume between DCE (8.08 ± 16.51) and AI-CS 3D T2WI (8.25 ± 16.29) sequences and no significant differences in tumor diameter among DCE, AI-CS 3D T2WI, and conventional T2WI sequences.

CONCLUSION

Isotropic-resolution 3D T2WI sequences can be acquired using AI-CS while maintaining image quality and diagnostic value, which may pave the way for isotropic 3D high-resolution T2WI for clinical application.