Free-Breathing Dynamic Contrast-Enhanced Imaging of the Upper Abdomen Using a Cartesian Compressed-Sensing Sequence With Hard-Gated and Motion-State-Resolved Reconstruction:

Motion-compensated image reconstruction for improved kidney function assessment using dynamic contrast-enhanced MRI

Accurately measuring renal function is crucial for pediatric patients with kidney conditions. Traditional methods have limitations, but dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provides a safe and efficient approach for detailed anatomical evaluation and renal function assessment. However, motion artifacts during DCE-MRI can degrade image quality and introduce misalignments, leading to unreliable results. This study introduces a motion-compensated reconstruction technique for DCE-MRI data acquired using golden-angle radial sampling. Our proposed method achieves three key objectives: (1) identifying and removing corrupted data (outliers) using a Gaussian process model fitting with a k -space center navigator, (2) efficiently clustering the data into motion phases and performing interphase registration, and (3) utilizing a novel formulation of motion-compensated radial reconstruction. We applied the proposed motion correction (MoCo) method to DCE-MRI data affected by varying degrees of motion, including both respiratory and bulk motion. We compared the outcomes with those obtained from the conventional radial reconstruction. Our evaluation encompassed assessing the quality of images, concentration curves, and tracer kinetic model fitting, and estimating renal function. The proposed MoCo reconstruction improved the temporal signal-to-noise ratio for all subjects, with a 21.8% increase on average, while total variation values of the aorta, right, and left kidney concentration were improved for each subject, with 32.5%, 41.3%, and 42.9% increases on average, respectively. Furthermore, evaluation of tracer kinetic model fitting indicated that the median standard deviation of the estimated filtration rate (σ F T ), mean normalized root-mean-squared error (nRMSE), and chi-square goodness-of-fit of tracer kinetic model fit were decreased from 0.10 to 0.04, 0.27 to 0.24, and, 0.43 to 0.27, respectively. The proposed MoCo technique enabled more reliable renal function assessment and improved image quality for detailed anatomical evaluation in the case of bulk and respiratory motion during the acquisition of DCE-MRI.

Feasibility of deep learning-reconstructed thin-slice single-breath-hold HASTE for detecting pancreatic lesions: A comparison with two conventional T2-weighted imaging sequences

Objective

The objective of this study was to evaluate the clinical feasibility of deep learning reconstruction-accelerated thin-slice single-breath-hold half-Fourier single-shot turbo spin echo imaging (HASTEDL) for detecting pancreatic lesions, in comparison with two conventional T2-weighted imaging sequences: compressed-sensing HASTE (HASTECS) and BLADE.

Methods

From March 2022 to January 2023, a total of 63 patients with suspected pancreatic-related disease underwent the HASTEDL, HASTECS, and BLADE sequences were enrolled in this retrospectively study. The acquisition time, the pancreatic lesion conspicuity (LCP), respiratory motion artifact (RMA), main pancreatic duct conspicuity (MPDC), overall image quality (OIQ), signal-to-noise ratio (SNR), and contrast-noise-ratio (CNR) of the pancreatic lesions were compared among the three sequences by two readers.

Results

The acquisition time of both HASTEDL and HASTECS was 16 s, which was significantly shorter than that of 102 s for BLADE. In terms of qualitative parameters, Reader 1 and Reader 2 assigned significantly higher scores to the LCP, RMA, MPDC, and OIQ for HASTEDL compared to HASTECS and BLADE sequences; As for the quantitative parameters, the SNR values of the pancreatic head, body, tail, and lesions, the CNR of the pancreatic lesion measured by the two readers were also significantly higher for HASTEDL than for HASTECS and BLADE sequences.

Conclusions

Compared to conventional T2WI sequences (HASTECS and BLADE), deep-learning reconstructed HASTE enables thin slice and single-breath-hold acquisition with clinical acceptable image quality for detection of pancreatic lesions.

Pancreatic ductal adenocarcinoma (PDAC) regional nodal disease at standard lymphadenectomy: is MRI accurate for identifying node-positive patients?

OBJECTIVE

To determine the accuracy of qualitative and quantitative MRI features for the diagnosis of pathologic regional lymph nodes at standard lymphadenectomy in patients with pancreatic ductal adenocarcinoma (PDAC).

METHODS

All adult patients with pancreatic MRI performed from 2011 to 2021 within 3 months of a pancreaticoduodenectomy were eligible for inclusion in this single-center retrospective cohort study. Regional nodes at standard lymphadenectomy were independently reviewed by two fellowship-trained abdominal radiologists for the following qualitative features: heterogeneous T2 signal, round shape, indistinct margin, peri-nodal fat stranding, and restricted diffusion greater than the spleen. Quantitative characteristics including primary tumor size, largest node short- and long-axes length, number of regional nodes, absolute apparent diffusion coefficient (ADC) values, and ADC node-to-spleen signal index were assessed. Analysis was at the patient-level with surgical pathology as the reference standard.

RESULTS

Of 75 patients, 85% (64/75) were positive for regional nodal disease on histopathology. None of the qualitative variables evaluated on MRI was associated with pathologic nodes. Median primary tumor maximum diameter was slightly larger for patients with pathologic nodes compared to those without (18 mm (10-42 mm) vs 16 mm (9-22 mm), p = 0.027). None of the other quantitative features was associated with pathologic nodes. Radiologist opinion was not associated with pathologic nodes (p = 0.520). Interobserver agreement was fair (kappa = 0.257).

CONCLUSIONS

Lymph node morphologic features and radiologist opinion using MRI are of limited value for diagnosing PDAC regional nodal disease. Improved diagnostic techniques are needed given the prognostic implications of pathologic lymph nodes in these patients.

KEY POINTS

• Multiple lymph node morphologic features routinely assessed on MRI for malignancies elsewhere in the body are likely not applicable when assessing for pancreatic ductal adenocarcinoma nodal disease. • Interobserver agreement for the presence or absence of pancreatic ductal adenocarcinoma lymph node morphologic features on MRI is fair (kappa = 0.257). • Many more lymph nodes are resected at PDAC standard lymphadenectomy than are detectable on MRI, median 25 vs 5 (p < 0.001), suggesting improved diagnostic techniques are needed to identify PDAC nodal disease.

Comprehensive Clinical Evaluation of a Deep Learning-Accelerated, Single-Breath-Hold Abdominal HASTE at 1.5 T and 3 T

To evaluate the clinical performance of a deep learning-accelerated single-breath-hold half-Fourier acquisition single-shot turbo spin echo (HASTE_DL)-sequence for T2-weighted fat-suppressed MRI of the abdomen at 1.5 T and 3 T in comparison to standard T2-weighted fat-suppressed multi-shot turbo spin echo-sequence. A total of 320 patients who underwent a clinically indicated liver MRI at 1.5 T and 3 T between August 2020 and February 2021 were enrolled in this single-center, retrospective study. HASTE_DL and standard sequences were assessed regarding overall and organ-based image quality, noise, contrast, sharpness, artifacts, diagnostic confidence, as well as lesion detectability using a Likert scale ranging from 1 to 4 (4 = best). The number of visible lesions of each organ was counted and the largest diameter of the major lesion was measured. HASTE_DL showed excellent image quality (median 4, interquartile range 3-4), although BLADE (median 4, interquartile range 4-4) was rated significantly higher for overall and organ-based image quality of the adrenal gland (P < .001), contrast (P < 0.001), sharpness (P < 0.001), artifacts (P < 0.001), as well as diagnostic confidence (P < .001). No significant differences were found concerning noise (P = 0.886), organ-based image quality of the liver, pancreas, spleen, and kidneys (P = 0.120-0.366), number and measured diameter of the detected lesions (ICC = 0.972-1.0). Reduction of the aquisition time (TA) was at least 89% for 1.5 T images and 86% for 3 T images. HASTE_DL provided excellent image quality, good diagnostic confidence and lesion detection compared to a standard T2-sequences, allowing an eminent reduction of the acquisition time.

Contrast-enhanced magnetic resonance imaging perfusion can predict microvascular invasion in patients with hepatocellular carcinoma (between 1 and 5 cm)

PURPOSE

To evaluate the role of perfusion parameters with MR imaging of the liver in diagnosing MVI in hepatocellular carcinoma (HCC) (between 1 and 5 cm).

MATERIALS AND METHODS

This retrospective study was approved by the institutional review board. In 80 patients with 43 MVI( +) and 42 MVI( -) HCC, whole-liver perfusion MR imaging with Cartesian k-space undersampling and compressed sensing reconstruction was performed after injection of 0.1 mmol/kg gadopentetate dimeglumine. Parameters derived from a dual-input single-compartment model of arterial flow (Fa), portal venous flow (Fp), total blood flow (Ft = Fa + Fp), arterial fraction (ART), distribution volume (DV), and mean transit time (MTT) were measured. The significant parameters between the two groups were included to correlate with the presence of MVI at simple and multiple regression analysis.

RESULTS

In MVI-positive HCC, Fp was significantly higher than in MVI-negative HCC, whereas the reverse was seen for ART (p < 0.001). Tumor size (β = 1.2, p = 0.004; odds ratio, 3.20; 95% CI 1.45, 7.06), Fp (β = 1.1, p = 0.004; odds ratio, 3.09; 95% CI 1.42, 6.72), and ART (β =  - 3.1, p = 0.001; odds ratio, 12.13; 95% CI 2.85, 51.49) were independent risk factors for MVI. The AUC value of the combination of all three metrics was 0.931 (95% CI 0.855, 0.975), with sensitivity of 97.6% and specificity of 76.2%.

CONCLUSION

The combination of Fp, ART, and tumor size demonstrated a higher diagnostic accuracy compared with each parameter used individually when evaluating MVI in HCC (between 1 and 5 cm).

Three-dimensional ultrashort echo time magnetic resonance imaging in assessment of idiopathic pulmonary fibrosis, in comparison with high-resolution computed tomography

Background

We aimed to evaluate the image quality, feasibility, and diagnostic performance of three-dimensional ultrashort echo time magnetic resonance imaging (3D UTE-MRI) to assess idiopathic pulmonary fibrosis (IPF) compared with high-resolution computed tomography (HRCT) and half-Fourier single-shot turbo spin-echo (HASTE) MRI.

Methods

A total of 36 patients with IPF (34 men; mean age: 62±8 years, age range: 43 to 78 years) were prospectively included and underwent HRCT and chest MRI on the same day. Chest MRI was performed with a free-breathing 3D spiral UTE pulse sequence and HASTE sequence on a 1.5 T MRI. Two radiologists independently evaluated the image quality of the HRCT, HASTE, and 3D UTE-MRI. They assessed the representative imaging features of IPF, including honeycombing, reticulation, traction bronchiectasis, and ground-glass opacities. Image quality of the 3D UTE-MRI, HASTE, and HRCT were assessed using a 5-point visual scoring method. Kappa and weighted kappa analysis were used to measure intra- and inter-observer and inter-method agreements. Sensitivity (SE), specificity (SP), and accuracy (AC) were used to assess the performance of 3D UTE-MRI for detecting image features of IPF and monitoring the extent of pulmonary fibrosis. Linear regressions and Bland-Altman plots were generated to assess the correlation and agreement between the assessment of the extent of pulmonary fibrosis made by the 2 observers.

Results

The image quality of HRCT was higher than that of HASTE and UTE-MRI (HRCT vs. UTE-MRI vs. HASTE: 4.9±0.3 vs. 4.1±0.7 vs. 3.0±0.3; P<0.001). Interobserver agreement of HRCT, HASTE, and 3D UTE-MRI when assessing pulmonary fibrosis was substantial and excellent (HRCT: 0.727≤ κ ≤1, P<0.001; HASTE: 0.654≤ κ ≤1, P<0.001; 3D UTE-MRI: 0.719≤ κ ≤0.824, P<0.001). In addition, reticulation (SE: 97.1%; SP: 100%; AC: 97.2%; κ =0.654), honeycombing (SE: 83.3%; SP: 100%; AC: 86.1%; κ =0.625) patterns, and traction bronchiectasis (SE: 94.1%; SP: 100%; AC: 94.4%, κ =0.640) were also well-visualized on 3D UTE-MRI, which was significantly superior to HASTE. Compared with HRCT, the sensitivity of 3D UTE-MRI to detect signs of pulmonary fibrosis (n=35) was 97.2%. The interobserver agreement in elevation of the extent of pulmonary fibrosis with HRCT and 3D UTE-MRI was R²=0.84 (P<0.001) and R²=0.84 (P<0.001), respectively. The extent of pulmonary fibrosis assessed with 3D UTE-MRI [median =9, interquartile range (IQR): 6.25 to 10.00] was lower than that from HRCT (median =12, IQR: 9.25 to 13.00; U=320.00, P<0.001); however, they had a positive correlation (R=0.72, P<0.001).

Conclusions

As a radiation-free non-contrast enhanced imaging method, although the image quality of 3D UTE-MRI is inferior to that of HRCT, it has high reproducibility to identify the imaging features of IPF and evaluate the extent of pulmonary fibrosis.

Dynamic contrast-enhanced MRI parametric mapping using high spatiotemporal resolution Golden-angle RAdial Sparse Parallel MRI and iterative joint estimation of the arterial input function and pharmacokinetic parameters

The aim of this work is to develop a data-driven quantitative dynamic contrast-enhanced (DCE) MRI technique using Golden-angle RAdial Sparse Parallel (GRASP) MRI with high spatial resolution and high flexible temporal resolution and pharmacokinetic (PK) analysis with an arterial input function (AIF) estimated directly from the data obtained from each patient. DCE-MRI was performed on 13 patients with gynecological malignancy using a 3-T MRI scanner with a single continuous golden-angle stack-of-stars acquisition and image reconstruction with two temporal resolutions, by exploiting a unique feature in GRASP that reconstructs acquired data with user-defined temporal resolution. Joint estimation of the AIF (both AIF shape and delay) and PK parameters was performed with an iterative algorithm that alternates between AIF and PK estimation. Computer simulations were performed to determine the accuracy (expressed as percentage error [PE]) and precision of the estimated parameters. PK parameters (volume transfer constant [K^trans ], fractional volume of the extravascular extracellular space [v_e ], and blood plasma volume fraction [v_p ]) and normalized root-mean-square error [nRMSE] (%) of the fitting errors for the tumor contrast kinetic data were measured both with population-averaged and data-driven AIFs. On patient data, the Wilcoxon signed-rank test was performed to compare nRMSE. Simulations demonstrated that GRASP image reconstruction with a temporal resolution of 1 s/frame for AIF estimation and 5 s/frame for PK analysis resulted in an absolute PE of less than 5% in the estimation of K^trans and v_e , and less than 11% in the estimation of v_p . The nRMSE (mean ± SD) for the dual temporal resolution image reconstruction and data-driven AIF was 0.16 ± 0.04 compared with 0.27 ± 0.10 (p < 0.001) with 1 s/frame using population-averaged AIF, and 0.23 ± 0.07 with 5 s/frame using population-averaged AIF (p < 0.001). We conclude that DCE-MRI data acquired and reconstructed with the GRASP technique at dual temporal resolution can successfully be applied to jointly estimate the AIF and PK parameters from a single acquisition resulting in data-driven AIFs and voxelwise PK parametric maps.

Comparison of utility of deep learning reconstruction on 3D MRCPs obtained with three different k-space data acquisitions in patients with IPMN

OBJECTIVE

To compare the utility of deep learning reconstruction (DLR) for improving acquisition time, image quality, and intraductal papillary mucinous neoplasm (IPMN) evaluation for 3D MRCP obtained with parallel imaging (PI), multiple k-space data acquisition for each repetition time (TR) technique (Fast 3D mode multiple: Fast 3Dm) and compressed sensing (CS) with PI.

MATERIALS AND METHODS

A total of 32 IPMN patients who had undergone 3D MRCPs obtained with PI, Fast 3Dm, and CS with PI and reconstructed with and without DLR were retrospectively included in this study. Acquisition time, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) obtained with all protocols were compared using Tukey's HSD test. Results of endoscopic ultrasound, ERCP, surgery, or pathological examination were determined as standard reference, and distribution classifications were compared among all 3D MRCP protocols by McNemar's test.

RESULTS

Acquisition times of Fast 3Dm and CS with PI with and without DLR were significantly shorter than those of PI with and without DLR (p < 0.05). Each MRCP sequence with DLR showed significantly higher SNRs and CNRs than those without DLR (p < 0.05). IPMN distribution accuracy of PI with and without DLR and Fast 3Dm with DLR was significantly higher than that of Fast 3Dm without DLR and CS with PI without DLR (p < 0.05).

CONCLUSION

DLR is useful for improving image quality and IPMN evaluation capability on 3D MRCP obtained with PI, Fast 3Dm, or CS with PI. Moreover, Fast 3Dm and CS with PI may play as substitution to PI for MRCP in patients with IPMN.

KEY POINTS

• Mean examination times of multiple k-space data acquisitions for each TR and compressed sensing with parallel imaging were significantly shorter than that of parallel imaging (p < 0.0001). • When comparing image quality of 3D MRCPs with and without deep learning reconstruction, deep learning reconstruction significantly improved signal-to-noise ratio and contrast-to-noise ratio (p < 0.05). • IPMN distribution accuracies of parallel imaging with and without deep learning reconstruction (with vs. without: 88.0% vs. 88.0%) and multiple k-space data acquisitions for each TR with deep learning reconstruction (86.0%) were significantly higher than those of others (p < 0.05).

Dynamic Liver Magnetic Resonance Imaging During Free Breathing: A Feasibility Study With a Motion Compensated Variable Density Radial Acquisition and a Viewsharing High-Pass Filtering Reconstruction

OBJECTIVE

Robust dynamic contrast-enhanced T1-weighted images are crucial for accurate detection and categorization of focal liver lesions in liver/abdominal magnetic resonance imaging (MRI). As optimal dynamic imaging usually requires multiple breath-holds, its inherent susceptibility to motion artifacts frequently results in degraded image quality in incompliant patients. Because free-breathing imaging may overcome this drawback, the intention of this study was to evaluate a dynamic MRI sequence acquired during free breathing using the variable density, elliptical centric golden angle radial stack-of-stars radial sampling scheme, which so far has not been implemented in 4-dimensional applications.

MATERIALS AND METHODS

In a prospective pilot study, 27 patients received a routine abdominal MRI protocol including the prototype free-breathing sequence (4DFreeBreathing) for dynamic imaging. This enables more convenient and faster reconstruction through variable density, elliptical centric golden angle radial stack-of-stars without the use of additional reconstruction hardware, and even higher motion robustness through soft-gating. A standard breath-hold sequence performed subsequently served as reference standard. Of the continuous dynamic data sets, each dynamic phase was analyzed regarding image quality, motion artifacts and vessel conspicuity using 5-point Likert scales. Furthermore, correct timing of the late arterial phase was compared with the preexaminations.

RESULTS

4DFreeBreathing delivered motion-free dynamic images with high temporal resolution in each subject. Overall image quality scores were rated good or excellent for 4DFreeBreathing and the gold standard without significant differences (P = 0.34). There were significantly less motion artifacts in the 4DFreeBreathing sequence (P < 0.0001), whereas vessel conspicuity in each dynamic phase was comparable for both groups (P = 0.45, P > 0.99, P = 0.22, respectively). Correct timing of the late arterial phase could be achieved in 27 of 27 (100%) examinations using 4DFreeBreathing versus 35 of 53 (66%) preexaminations using gold standard (P < 0.001).

CONCLUSION

The benefit of convenient and fast image reconstruction combined with the superiority in motion robustness and timing compared with standard breath hold sequences renders 4DFreeBreathing an attractive alternative to existing free-breathing techniques in dynamic liver MRI.

Phase2Phase: Respiratory Motion-Resolved Reconstruction of Free-Breathing Magnetic Resonance Imaging Using Deep Learning Without a Ground Truth for Improved Liver Imaging

OBJECTIVES

Respiratory binning of free-breathing magnetic resonance imaging data reduces motion blurring; however, it exacerbates noise and introduces severe artifacts due to undersampling. Deep neural networks can remove artifacts and noise but usually require high-quality ground truth images for training. This study aimed to develop a network that can be trained without this requirement.

MATERIALS AND METHODS

This retrospective study was conducted on 33 participants enrolled between November 2016 and June 2019. Free-breathing magnetic resonance imaging was performed using a radial acquisition. Self-navigation was used to bin the k-space data into 10 respiratory phases. To simulate short acquisitions, subsets of radial spokes were used in reconstructing images with multicoil nonuniform fast Fourier transform (MCNUFFT), compressed sensing (CS), and 2 deep learning methods: UNet3DPhase and Phase2Phase (P2P). UNet3DPhase was trained using a high-quality ground truth, whereas P2P was trained using noisy images with streaking artifacts. Two radiologists blinded to the reconstruction methods independently reviewed the sharpness, contrast, and artifact-freeness of the end-expiration images reconstructed from data collected at 16% of the Nyquist sampling rate. The generalized estimating equation method was used for statistical comparison. Motion vector fields were derived to examine the respiratory motion range of 4-dimensional images reconstructed using different methods.

RESULTS

A total of 15 healthy participants and 18 patients with hepatic malignancy (50 ± 15 years, 6 women) were enrolled. Both reviewers found that the UNet3DPhase and P2P images had higher contrast (P < 0.01) and fewer artifacts (P < 0.01) than the CS images. The UNet3DPhase and P2P images were reported to be sharper than the CS images by 1 reviewer (P < 0.01) but not by the other reviewer (P = 0.22, P = 0.18). UNet3DPhase and P2P were similar in sharpness and contrast, whereas UNet3DPhase had fewer artifacts (P < 0.01). The motion vector lengths for the MCNUFFT800 and P2P800 images were comparable (10.5 ± 4.2 mm and 9.9 ± 4.0 mm, respectively), whereas both were significantly larger than CS2000 (7.0 ± 3.9 mm; P < 0.0001) and UNnet3DPhase800 (6.9 ± 3.2; P < 0.0001) images.

CONCLUSIONS

Without a ground truth, P2P can reconstruct sharp, artifact-free, and high-contrast respiratory motion-resolved images from highly undersampled data. Unlike the CS and UNet3DPhase methods, P2P did not artificially reduce the respiratory motion range.

Qualitative and Quantitative Analysis of a Spiral Gradient Echo Sequence for Contrast-Enhanced Fat-Suppressed T1-Weighted Spine Magnetic Resonance Imaging

OBJECTIVES

Pulse sequences with non-Cartesian k-space sampling enable improved imaging in anatomical areas with high degrees of motion artifacts. We analyzed a novel spiral 3-dimensional (3D) gradient echo (GRE) magnetic resonance imaging (MRI) sequence ("spiral," 114.7 ± 11 seconds) and compared it with a radial 3D GRE ("vane," 216.7 ± 2 seconds) and a conventional Cartesian 2D turbo spin echo (TSE) sequence ("TSE," 266.7 ± 82 seconds) for contrast-enhanced fat-suppressed T1-weighted spine imaging.

MATERIALS AND METHODS

Forty consecutive patients referred for contrast-enhanced MRI were prospectively scanned with all 3 sequences. A qualitative analysis was performed by 3 readers using 4- or 5-point Likert scales to independently grade images in terms of overall image quality, occurrence of artifacts, lesion conspicuity, and conspicuity of nerve roots. The numbers of visible nerve roots per sequence and patient were counted in consensus. Coefficient of variation measurements were performed for the paravertebral musculature (CVPM) and the spinal cord (CVSC).

RESULTS

Spiral (median [interquartile range], 5 [4-5]) exhibited improved overall image quality in comparison to TSE (3 [3-4]) and vane (4 [4-5]; both P < 0.001). Vane surpassed TSE in terms of overall image quality (P < 0.001). Spiral (4 [3.75-4]) and vane (3.5 [3-4]) presented with less artifacts than TSE (3 [2.75-3.25]; both P < 0.001). Spiral (4 [4-5]) outperformed vane (4 [3-5]; P = 0.01) and TSE (4 [3-4]; P = 0.04) in terms of lesion conspicuity. Conspicuity of nerve roots was superior on spiral (3 [3-4]) and vane (4 [3-4]) when compared with TSE (1.5 [1-2]; both P < 0.001). Readers discerned significantly more nerve roots on spiral (4 [2.75-8]) and vane (4 [3.75-7.25]) images when compared with TSE (2 [0-4]; both P < 0.001). Interreader agreement ranged from moderate (α = 0.639) to almost perfect (α = 0.967). CVPM and CVSC were significantly lower on spiral as compared with vane and TSE (P < 0.001, P = 0.04). Vane exhibited lower CVPM and CVSC than TSE (P < 0.001, P = 0.01).

CONCLUSIONS

A novel spiral 3D GRE sequence improves contrast-enhanced fat-suppressed T1-weighted spinal imaging qualitatively and quantitatively in comparison with a conventional Cartesian 2D TSE sequence and to a lesser extent with a radial 3D GRE sequence at shorter scan times.

Image Quality Improvement of Dynamic Contrast-Enhanced Gradient Echo Magnetic Resonance Imaging by Iterative Denoising and Edge Enhancement

OBJECTIVES

The aim of this study was to investigate the impact of a novel edge enhancement and iterative denoising algorithm in 1.5-T T1-weighted dynamic contrast-enhanced (DCE) gradient echo (GRE) magnetic resonance imaging of the abdomen on image quality, noise levels, diagnostic confidence, and lesion detectability.

MATERIALS AND METHODS

Fifty patients who underwent a clinically indicated magnetic resonance imaging with DCE imaging of the abdomen between June and August 2020 were included in this retrospective, monocentric, institutional review board-approved study. For DCE imaging, a series of 3 volume interpolated breath-hold examinations (VIBEs) was performed. The raw data of all DCE imaging studies were processed twice, once using standard reconstruction (DCES) and again using an edge enhancement and iterative denoising approach (DCEDE). All imaging studies were randomly reviewed by 2 radiologists independently regarding noise levels, arterial contrast, sharpness of vessels, overall image quality, and diagnostic confidence using a Likert scale ranging from 1 to 4, with 4 being the best. Furthermore, lesion detectability was evaluated using the same ranking system.

RESULTS

All 50 imaging studies were successfully reconstructed with both methods. Interreader agreement (Cohen κ) was substantial to perfect for both readers. Arterial contrast and sharpness of vessels were rated superior by both readers with a median of 4 in DCEDE versus a median of 3 in DCES (P < 0.001). Furthermore, noise levels as well as overall image quality were rated higher with a median of 4 in DCEDE compared with a median of 3 in DCES (P < 0.001). Lesion detectability was evaluated to be superior in DCEDE with a median of 4 versus DCES with a median of 3 (P < 0.001). Consequently, diagnostic confidence was also rated to be superior in DCEDE with a median of 4 versus DCES with a median of 3 (P < 0.001).

CONCLUSIONS

Iterative denoising and edge enhancement are feasible in DCE imaging of the abdomen providing superior arterial contrast, noise levels, and overall image quality. Furthermore, lesion detectability and diagnostic confidence were significantly improved using this novel reconstruction method. Further reduction of acquisition time might be possible via reduction of increased noise levels using this presented method.

Intraindividual Comparison of Compressed Sensing-Accelerated Cartesian and Radial Arterial Phase Imaging of the Liver in an Experimental Tumor Model

OBJECTIVES

The aim of this study was to intraindividually compare the performance of 2 compressed sensing (CS)-accelerated magnetic resonance imaging (MRI) sequences, 1 featuring Cartesian (compressed sensing volumetric interpolated breath-hold examination [CS-VIBE]) and the other radial (golden-angle radial sparse parallel [GRASP]) k-space sampling in continuous dynamic imaging during hepatic vascular phases, using extracellular and hepatocyte-specific contrast agents.

MATERIALS AND METHODS

Seven New Zealand white rabbits, with induced VX2 liver tumors (median number of lesions, 2 ± 0.83; range, 1-3), received 2 continuously acquired T1-weighted prototype CS-accelerated MRI sequences (CS-VIBE and GRASP) with high spatial (0.8 × 0.8 × 1.5 mm) and temporal resolution (3.5 seconds) in randomized order on 2 separate days using a 1.5-T scanner. In all animals, imaging was performed using first gadobutrol at a dose of 0.1 mmol/kg and, then 45 minutes later, gadoxetic acid at a dose of 0.025 mmol/kg.The following qualitative parameters were assessed using 3- and 5-point Likert scales (3 and 5 being the highest scores respectively): image quality (IQ), arterial and venous vessel delineation, tumor enhancement, motion artifacts, and sequence-specific artifacts. Furthermore, the following quantitative parameters were obtained: relative peak signal enhancement, time to peak, mean transit time, and plasma flow ratios. Paired sampled t tests and Wilcoxon signed rank tests were used for intraindividual comparison. Image analysis was performed by 2 radiologists.

RESULTS

Six of 7 animals underwent the full imaging protocol and obtained data were analyzed statistically. Overall IQ was rated moderate to excellent, not differing significantly between the 2 sequences.Gadobutrol-enhanced CS-VIBE examinations revealed the highest mean Likert scale values in terms of vessel delineation and tumor enhancement (arterial 4.4 [4-5], venous 4.3 [3-5], and tumor 2.9 [2-3]). Significantly, more sequence-specific artifacts were seen in GRASP examinations (P = 0.008-0.031). However, these artifacts did not impair IQ. Excellent Likert scale ratings were found for motion artifacts in both sequences. In both sequences, a maximum of 4 hepatic arterial dominant phases were obtained. Regarding the relative peak signal enhancement, CS-VIBE and GRASP showed similar results. The relative peak signal enhancement values did not differ significantly between the 2 sequences in the aorta, the hepatic artery, or the inferior vena cava (P = 0.063-0.536). However, significantly higher values were noted for CS-VIBE in gadoxetic acid-enhanced examinations in the portal vein (P = 0.031) and regarding the tumor enhancement (P = 0.005). Time to peak and mean transit time or plasma flow ratios did not differ significantly between the sequences.

CONCLUSIONS

Both CS-VIBE and GRASP provide excellent results in dynamic liver MRI using extracellular and hepatocyte-specific contrast agents, in terms of IQ, peak signal intensity, and presence of artifacts.

Can Dynamic Contrast-enhanced MRI Contribute to Improved Assessment of Rectosigmoid Involvement in Deep Infiltrating Endometriosis?

BACKGROUND/AIM

To determine whether a prototypical compressed-sensing volume-interpolated breath-hold (csVIBE) provides diagnostic value in detecting rectosigmoid infiltration in deep infiltrating endometriosis (DIE).

PATIENTS AND METHODS

csVIBE was employed in 151 women undergoing pelvic magnetic resonance imaging, of whom 43 had undergone surgery for suspected endometriosis. The accuracy of T2-weighted BLADE and BLADE/csVIBE, additional diagnostic value of csVIBE, and diagnostic confidence were rated by two readers. Additionally, the presence of the "mushroom cap sign" was assessed on BLADE and csVIBE.

RESULTS

The diagnostic accuracy, sensitivity, and specificity of BLADE and BLADE/csVIBE were not significantly different between Readers A and B. For both readers, the confidence in the diagnosis increased with csVIBE, but this increase in the odds ratio was not significant for both readers. Both readers preferred csVIBE over BLADE with regard to detection of the "mushroom cap sign."

CONCLUSION

csVIBE may provide a diagnostic benefit for surgical strategy selection through better delineation of the "mushroom cap sign."

Spiral 3-Dimensional T1-Weighted Turbo Field Echo: Increased Speed for Magnetization-Prepared Gradient Echo Brain Magnetic Resonance Imaging

OBJECTIVES

Spiral magnetic resonance imaging acquisition may enable improved image quality and higher scan speeds than Cartesian trajectories. We tested the performance of four 3D T1-weighted (T1w) TFE sequences (magnetization-prepared gradient echo magnetic resonance sequence) with isotropic spatial resolution for brain imaging at 1.5 T in a clinical patient cohort based on qualitative and quantitative image quality metrics. Two prototypical spiral TFE sequences (spiral 1.0 and spiral 0.85) and a Cartesian compressed sensing technology accelerated TFE sequence (CS 2.5; acceleration factor of 2.5) were compared with a conventional (reference standard) Cartesian parallel imaging accelerated TFE sequence (SENSE; acceleration factor of 1.8).

MATERIALS AND METHODS

The SENSE (5:52 minutes), CS 2.5 (3:17 minutes), and spiral 1.0 (2:16 minutes) sequences all had identical spatial resolutions (1.0 mm). The spiral 0.85 (3:47 minutes) had a higher spatial resolution (0.85 mm). The 4 TFE sequences were acquired in 41 patients (20 with and 21 without contrast media). Three readers rated qualitative image quality (12 categories) and selected their preferred sequence for each patient. Two readers performed quantitative analysis whereby 6 metrics were derived: contrast-to-noise ratio for white and gray matter (CNRWM/GM), contrast ratio for gray matter-CSF (CRGM/CSF), and white matter-CSF (CRWM/CSF); and coefficient of variations for gray matter (CVGM), white matter (CVWM), and CSF (CVCSF). Friedman tests with post hoc Nemenyi tests, exact binomial tests, analysis of variance with post hoc Dunnett tests, and Krippendorff alphas were computed.

RESULTS

Concerning qualitative analysis, the CS 2.5 sequence significantly outperformed the SENSE in 4/1 (with/without contrast) categories, whereas the spiral 1.0 and spiral 0.85 showed significantly improved scores in 10/9and 7/7 categories, respectively (P's < 0.001-0.039). The spiral 1.0 was most frequently selected as the preferred sequence (reader 1, 10/15 times; reader 2, 9/12 times; reader 3, 11/13times [with/without contrast]). Interreader agreement ranged from substantial to almost perfect (alpha = 0.615-0.997). Concerning quantitative analysis, compared with the SENSE, the CS 2.5 had significantly better scores in 2 categories (CVWM, CVCSF) and worse scores in 2 categories (CRGM/CSF, CRWM/CSF), the spiral 1.0 had significantly improved scores in 4 categories (CNRWM/GM, CRGM/CSF, CRWM/CSF, CVWM), and the spiral 0.85 had significantly better scores in 2 categories (CRGM/CSF, CRWM/CSF).

CONCLUSIONS

Spiral T1w TFE sequences may deliver high-quality clinical brain imaging, thus matching the performance of conventional parallel imaging accelerated T1w TFEs. Imaging can be performed at scan times as short as 2:16 minutes per sequence (61.4% scan time reduction compared with SENSE). Optionally, spiral imaging enables increased spatial resolution while maintaining the scan time of a Cartesian-based acquisition schema.

Diagnostic Confidence and Feasibility of a Deep Learning Accelerated HASTE Sequence of the Abdomen in a Single Breath-Hold

OBJECTIVE

The aim of this study was to evaluate the feasibility of a single breath-hold fast half-Fourier single-shot turbo spin echo (HASTE) sequence using a deep learning reconstruction (HASTEDL) for T2-weighted magnetic resonance imaging of the abdomen as compared with 2 standard T2-weighted imaging sequences (HASTE and BLADE).

MATERIALS AND METHODS

Sixty-six patients who underwent 1.5-T liver magnetic resonance imaging were included in this monocentric, retrospective study. The following T2-weighted sequences in axial orientation and using spectral fat suppression were compared: a conventional respiratory-triggered BLADE sequence (time of acquisition [TA] = 4:00 minutes), a conventional multiple breath-hold HASTE sequence (HASTES) (TA = 1:30 minutes), as well as a single breath-hold HASTE with deep learning reconstruction (HASTEDL) (TA = 0:16 minutes). Two radiologists assessed the 3 sequences regarding overall image quality, noise, sharpness, diagnostic confidence, and lesion detectability as well as lesion characterization using a Likert scale ranging from 1 to 4 with 4 being the best. Comparative analyses were conducted to assess the differences between the 3 sequences.

RESULTS

HASTEDL was successfully acquired in all patients. Overall image quality for HASTEDL was rated as good (median, 3; interquartile range, 3-4) and was significantly superior to HASTEs (P < 0.001) and inferior to BLADE (P = 0.001). Noise, sharpness, and artifacts for HASTEDL reached similar levels to BLADE (P ≤ 0.176) and were significantly superior to HASTEs (P < 0.001). Diagnostic confidence for HASTEDL was rated excellent by both readers and significantly superior to HASTEs (P < 0.001) and inferior to BLADE (P = 0.044). Lesion detectability and lesion characterization for HASTEDL reached similar levels to those of BLADE (P ≤ 0.523) and were significantly superior to HASTEs (P < 0.001). Concerning the number of detected lesions and the measured diameter of the largest lesion, no significant differences were found comparing BLADE, HASTES, and HASTEDL (P ≤ 0.912).

CONCLUSIONS

The single breath-hold HASTEDL is feasible and yields comparable image quality and diagnostic confidence to standard T2-weighted TSE BLADE and may therefore allow for a remarkable time saving in abdominal imaging.

Morphological and functional assessment of the uterus: "one-stop shop imaging" using a compressed-sensing accelerated, free-breathing T1-VIBE sequence

BACKGROUND

The combination of motion-insensitive, high-temporal, and spatial resolution imaging with evaluation of quantitative perfusion has the potential to increase the diagnostic capabilities of magnetic resonance imaging (MRI) in the female pelvis.

PURPOSE

To compare a free-breathing compressed-sensing VIBE (fbVIBE) with flexible temporal resolution (range = 4.6-13.8 s) with breath-hold VIBE (bhVIBE) and to evaluate the potential value of quantifying uterine perfusion.

MATERIAL AND METHODS

A total of 70 datasets from 60 patients (bhVIBE: n = 30; fbVIBE: n = 40) were evaluated by two radiologists. Only temporally resolved reconstruction (fbVIBE) was performed on 30 of the fbVIBE datasets. For a subset (n = 10) of the fbVIBE acquisitions, a time- and motion-resolved reconstruction (mrVIBE) was evaluated. Image quality (IQ), artifacts, diagnostic confidence (DC), and delineation of uterine structures (DoS) were graded on Likert scales (IQ/DC/DoS: 1 (non-diagnostic) to 5 (perfect); artifacts: 1 (no artifacts) to 5 (severe artifacts)). A Tofts model was applied for perfusion analysis. Ktrans was obtained in the myometrium (Mm), junctional zone (Jz), and cervix (Cx).

RESULTS

The median IQ/DoS/DC scores of fbVIBE (4/5/5 κ >0.7-0.9) and bhVIBE (4/4/4; κ = 0.5-0.7; P > 0.05) were high, but Artifacts were graded low (fbVIBE/bhVIBE: 2/2; κ = 0.6/0.5; P > 0.05). Artifacts were only slightly improved by the additional motion-resolved reconstruction (fbVIBE/mrVIBE: 2/1.5; P = 0.08); fbVIBE was preferred in most cases (7/10). Significant differences of Ktrans values were found between Cx, Jz, and Mm (0.12/0.21/0.19; P < 0.05).

CONCLUSION

The fbVIBE sequence allows functional and morphological assessment of the uterus at comparable IQ to bhVIBE.

Modeling dynamic radial contrast enhanced MRI with linear time invariant systems for motion correction in quantitative assessment of kidney function

Early identification of kidney function deterioration is essential to determine which newborn patients with congenital kidney disease should be considered for surgical intervention as opposed to observation. Kidney function can be measured by fitting a tracer kinetic (TK) model onto a series of Dynamic Contrast Enhanced (DCE) MR images and estimating the filtration rate parameter from the model. Unfortunately, breathing and large bulk motion events due to patient movement in the scanner create outliers and misalignments that introduce large errors in the TK model parameter estimates even when using a motion-robust dynamic radial VIBE sequence for DCE-MR imaging. The misalignments between the series of volumes are difficult to correct using standard registration due to 1) the large differences in geometry and contrast between volumes of the dynamic sequence and 2) the requirement of fast dynamic imaging to achieve high temporal resolution and motion deteriorates image quality. These difficulties reduce the accuracy and stability of registration over the dynamic sequence. An alternative registration approach is to generate noise and motion free templates of the original data from the TK model and use them to register each volume to its contrast-matched template. However, the TK models used to characterize DCE-MRI are tissue specific, non-linear and sensitive to the same motion and sampling artifacts that hinder registration in the first place. Hence, these can only be applied to register accurately pre-segmented regions of interest, such as kidneys, and might converge to local minima under the presence of large artifacts. Here we introduce a novel linear time invariant (LTI) model to characterize DCE-MR data for different tissue types within a volume. We approximate the LTI model as a sparse sum of first order LTI functions to introduce robustness to motion and sampling artifacts. Hence, this model is well suited for registration of the entire field of view of DCE-MR data with artifacts and outliers. We incorporate this LTI model into a registration framework and evaluate it on both synthetic data and data from 20 children. For each subject, we reconstructed the sequence of DCE-MR images, detected corrupted volumes acquired during motion, aligned the sequence of volumes and recovered the corrupted volumes using the LTI model. The results show that our approach correctly aligned the volumes, provided the most stable registration in time and improved the tracer kinetic model fit.

Compressed sensing and parallel imaging accelerated T2 FSE sequence for head and neck MR imaging: Comparison of its utility in routine clinical practice

PURPOSE

To directly compare the capability of compressed sensing (CS) and parallel imaging (PI) accelerated T2 FSE (Fast Spin Echo) sequence with PI for head and neck MR imaging.

METHODS

Thirty consecutive patients with various head and neck diseases (15 men and 15 women, mean age 53 ± 22 years) underwent MR imaging by PI with CS and by PI. Reduction factors were as follows: PI with CS, 3 and PI, 1.5. Examination times for PI with CS and PI were all recorded. For quantitative image quality assessment, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. For qualitative assessment, two investigators assessed overall image quality, artifacts and diagnostic confidence level using a 5-point scoring system, and final scores were determined by consensus of two readers. Mean examination time and all indexes were compared by means of paired t-test and Wilcoxon signed-rank test. Inter-observer agreement for each qualitative index was assessed in terms of kappa statistics.

RESULTS

Mean examination time for PI with CS (83.5 ± 11.0 s) was significantly shorter than that for PI (173.0 ± 54.4 s, p < 0.0001). SNR and CNR of PI with CS were significantly better than those with PI (mean SNR; 11.2 ± 3.6 vs 8.9 ± 2.6, median of CNR; 7.4 vs. 6.1, p < 0.0001). All inter-observer agreements were assessed as significant and substantial (0.62 < κ < 0.81).

CONCLUSION

PI with CS accelerated T2 weighted sequence performs equally well or even slightly better than its PI accelerated, conventional counterpart at reduced scan times in the context of head and neck MR imaging.

Compressed sensing and deep learning reconstruction for women's pelvic MRI denoising: Utility for improving image quality and examination time in routine clinical practice

PURPOSE

To demonstrate the utility of compressed sensing with parallel imaging (Compressed SPEEDER) and AiCE compared with that of conventional parallel imaging (SPEEDER) for shortening examination time and improving image quality of women's pelvic MRI.

METHOD

Thirty consecutive patients with women's pelvic diseases (mean age 50 years) underwent T2-weighted imaging using Compressed SPEEDER as well as conventional SPEEDER reconstructed with and without AiCE. The examination times were recorded, and signal-to-noise ratio (SNR) was calculated for every patient. Moreover, overall image quality was assessed using a 5-point scoring system, and final scores for all patients were determined by consensus of two readers. Mean examination time, SNR and overall image quality were compared among the four data sets by Wilcoxon signed-rank test.

RESULTS

Examination times for Compressed SPEEDER with and without AiCE were significantly shorter than those for conventional SPEEDER with and without AiCE (with AiCE: p < 0.0001, without AiCE: p < 0.0001). SNR of Compressed SPEEDER and of SPEEDER with AiCE was significantly superior to that of Compressed SPEEDER without AiCE (vs. Compressed SPEEDER, p = 0.01; vs. SPEEDER, p = 0.009). Overall image quality of Compressed SPEEDER with AiCE and of SPEEDER with and without AiCE was significantly higher than that of Compressed SPEEDER without AiCE (vs. Compressed SPEEDER with AiCE, p < 0.0001; vs. SPEEDER with AiCE, p < 0.0001; SPEEDER without AiCE, p = 0.0003).

CONCLUSION

Image quality and shorten examination time for T2-weighted imaging in women's pelvic MRI can be significantly improved by using Compressed SPEEDER with AiCE in comparison with conventional SPEEDER, although other sequences were not tested.

Clinical feasibility of ultrafast intracranial vessel imaging with non-Cartesian spiral 3D time-of-flight MR angiography at 1.5T: An intra-individual comparison study

Objectives

Non-Cartesian Spiral readout can be implemented in 3D Time-of-flight (TOF) MR angiography (MRA) with short acquisition times. In this intra-individual comparison study we evaluated the clinical feasibility of Spiral TOF MRA in comparison with compressed sensing accelerated TOF MRA at 1.5T for intracranial vessel imaging as it has yet to be determined.

Materials and methods

Forty-four consecutive patients with suspected intracranial vascular disease were imaged with two Spiral 3D TOFs (Spiral, 0.82x0.82x1.2 mm³, 01:32 min; Spiral 0.8, 0.8x0.8x0.8 mm^3, 02:12 min) and a Compressed SENSE accelerated 3D TOF (CS 3.5, 0.82x0.82x1.2 mm³, 03:06 min) at 1.5T. Two neuroradiologists assessed qualitative (visualization of central and peripheral vessels) and quantitative image quality (Contrast Ratio, CR) and performed lesion and variation assessment for all three TOFs in each patient. After the rating process, the readers were questioned and representative cases were reinspected in a non-blinded fashion. For statistical analysis, the Friedman and Nemenyi post-hoc test, Kendall W tests, repeated measure ANOVA and weighted Cohen's Kappa tests were used.

Results

The Spiral and Spiral 0.8 outperformed the CS 3.5 in terms of peripheral image quality (p<0.001) and performed equally well in terms of central image quality (p>0.05). The readers noted slight differences in the appearance of maximum intensity projection images. A good to high degree of interstudy agreement between the three TOFs was observed for lesion and variation assessment (W = 0.638, p<0.001 –W = 1, p<0.001). CR values did not differ significantly between the three TOFs (p = 0.534). Interreader agreement ranged from good (K = 0.638) to excellent (K = 1).

Conclusions

Compared to the CS 3.5, both the Spiral and Spiral 0.8 exhibited comparable or better image quality and comparable diagnostic performance at much shorter acquisition times.