Fat suppression using frequency-sweep RF saturation and iterative reconstruction.

PURPOSE: To introduce an alternative idea for fat suppression that is suited both for low-field applications where conventional fat-suppression approaches become ineffective due to narrow spectral separation and for applications with strong B0 homogeneities. METHODS: Separation of fat and water is achieved by sweeping the frequency of RF saturation pulses during continuous radial acquisition and calculating frequency-resolved images using regularized iterative reconstruction. Voxel-wise signal-response curves are extracted that reflect tissue's response to RF saturation at different frequencies and allow the classification into fat or water. This information is then utilized to generate water-only composite images. The principle is demonstrated in free-breathing abdominal and neck examinations using stack-of-stars 3D balanced SSFP (bSSFP) and gradient-recalled echo (GRE) sequences at 0.55 and 3T. Moreover, a potential extension toward quantitative fat/water separation is described. RESULTS: Experiments with a proton density fat fraction (PDFF) phantom validated the reliability of fat/water separation using signal-response curves. As demonstrated for abdominal imaging at 0.55T, the approach resulted in more uniform fat suppression without loss of water signal and in improved CSF-to-fat signal ratio. Moreover, the approach provided consistent fat suppression in 3T neck exams where conventional spectrally-selective fat saturation failed due to strong local B0 inhomogeneities. The feasibility of simultaneous fat/water quantification has been demonstrated in a PDFF phantom. CONCLUSION: The proposed principle achieves reliable fat suppression in low-field applications and adapts to high-field applications with strong B0 inhomogeneity. Moreover, the principle potentially provides a basis for developing an alternative approach for PDFF quantification.

Presentation of microstructural diffusion components by color schemes in abdominal organs.

PURPOSE: Development of a color scheme representation to facilitate the interpretation of tri-exponential DWI data from abdominal organs, where multi-exponential behavior is more pronounced. METHODS: Multi-exponential analysis of DWI data provides information about the microstructure of the tissue under study. The tri-exponential signal analysis generates numerous parameter images that are difficult to analyze individually. Summarized color images can simplify at-a-glance analysis. A color scheme was developed in which the slow, intermediate, and fast diffusion components were each assigned to a different red, green, and blue color channel. To improve the appearance of the image, histogram equalization, gamma correction, and white balance were used, and the processing parameters were adjusted. Examples of the resulting color maps of the diffusion fractions of healthy and pathological kidney and prostate are shown. RESULTS: The color maps obtained by the presented method show the merged information of the slow, intermediate, and fast diffusion components in a single view. A differentiation of the different fractions becomes clearly visible. Fast diffusion regimes, such as in the renal hilus, can be clearly distinguished from slow fractions, such as in dense tumor tissue. CONCLUSION: Combining the diffusion information from tri-exponential DWI analysis into a single color image allows for simplified interpretation of the diffusion fractions. In the future, such color images may provide additional information about the microstructural nature of the tissue under study.

Image quality of whole-body diffusion MR images comparing deep-learning accelerated and conventional sequences.

OBJECTIVES: To compare the image quality of deep learning accelerated whole-body (WB) with conventional diffusion sequences. METHODS: Fifty consecutive patients with bone marrow cancer underwent WB-MRI. Two experts compared axial b900 s/mm2 and the corresponding maximum intensity projections (MIP) of deep resolve boost (DRB) accelerated diffusion-weighted imaging (DWI) sequences (time of acquisition: 6:42 min) against conventional sequences (time of acquisition: 14 min). Readers assessed paired images for noise, artefacts, signal fat suppression, and lesion conspicuity using Likert scales, also expressing their overall subjective preference. Signal-to-noise and contrast-to-noise ratios (SNR and CNR) and the apparent diffusion coefficient (ADC) values of normal tissues and cancer lesions were statistically compared. RESULTS: Overall, radiologists preferred either axial DRB b900 and/or corresponding MIP images in almost 80% of the patients, particularly in patients with a high body-mass index (BMI > 25 kg/m2). In qualitative assessments, axial DRB images were preferred (preferred/strongly preferred) in 56-100% of cases, whereas DRB MIP images were favoured in 52-96% of cases. DRB-SNR/CNR was higher in all normal tissues (p < 0.05). For cancer lesions, the DRB-SNR was higher (p < 0.001), but the CNR was not different. DRB-ADC values were significantly higher for the brain and psoas muscles, but not for cancer lesions (mean difference: + 53 µm2/s). Inter-class correlation coefficient analysis showed good to excellent agreement (95% CI 0.75-0.93). CONCLUSION: DRB sequences produce higher-quality axial DWI, resulting in improved MIPs and significantly reduced acquisition times. However, differences in the ADC values of normal tissues need to be considered. CLINICAL RELEVANCE STATEMENT: Deep learning accelerated diffusion sequences produce high-quality axial images and MIP at reduced acquisition times. This advancement could enable the increased adoption of Whole Body-MRI for the evaluation of patients with bone marrow cancer. KEY POINTS: Deep learning reconstruction enables a more than 50% reduction in acquisition time for WB diffusion sequences. DRB images were preferred by radiologists in almost 80% of cases due to fewer artefacts, improved background signal suppression, higher signal-to-noise ratio, and increased lesion conspicuity in patients with higher body mass index. Cancer lesion diffusivity from DRB images was not different from conventional sequences.

Accelerated Diffusion-Weighted Magnetic Resonance Imaging of the Liver at 1.5 T With Deep Learning-Based Image Reconstruction: Impact on Image Quality and Lesion Detection.

OBJECTIVE: To perform image quality comparison between deep learning-based multiband diffusion-weighted sequence (DL-mb-DWI), accelerated multiband diffusion-weighted sequence (accelerated mb-DWI), and conventional multiband diffusion-weighted sequence (conventional mb-DWI) in patients undergoing clinical liver magnetic resonance imaging (MRI). METHODS: Fifty consecutive patients who underwent clinical MRI of the liver at a 1.5-T scanner, between September 1, 2021, and January 31, 2022, were included in this study. Three radiologists independently reviewed images using a 5-point Likert scale for artifacts and image quality factors, in addition to assessing the presence of liver lesions and lesion conspicuity. RESULTS: DL-mb-DWI acquisition time was 65.0 ± 2.4 seconds, significantly (P < 0.001) shorter than conventional mb-DWI (147.5 ± 19.2 seconds) and accelerated mb-DWI (94.3 ± 1.8 seconds). DL-mb-DWI received significantly higher scores than conventional mb-DWI for conspicuity of the left lobe (P < 0.001), sharpness of intrahepatic vessel margin (P < 0.001), sharpness of the pancreatic contour (P < 0.001), in-plane motion artifact (P = 0.002), and overall image quality (P = 0.005) by reader 2. DL-mb-DWI received significantly higher scores for conspicuity of the left lobe (P = 0.006), sharpness of the pancreatic contour (P = 0.020), and in-plane motion artifact (P = 0.042) by reader 3. DL-mb-DWI received significantly higher scores for strength of fat suppression (P = 0.004) and sharpness of the pancreatic contour (P = 0.038) by reader 1. The remaining quality parameters did not reach statistical significance for reader 1. CONCLUSIONS: Novel diffusion-weighted MRI sequence with deep learning-based image reconstruction demonstrated significantly decreased acquisition times compared with conventional and accelerated mb-DWI sequences, while maintaining or improving image quality for routine abdominal MRI. DL-mb-DWI offers a potential alternative to conventional mb-DWI in routine clinical liver MRI.

Spatial profiling of in vivo diffusion-weighted MRI parameters in the healthy human kidney.

OBJECTIVE: Diffusion-weighted MRI is a technique that can infer microstructural and microcirculatory features from biological tissue, with particular application to renal tissue. There is extensive literature on diffusion tensor imaging (DTI) of anisotropy in the renal medulla, intravoxel incoherent motion (IVIM) measurements separating microstructural from microcirculation effects, and combinations of the two. However, interpretation of these features and adaptation of more specific models remains an ongoing challenge. One input to this process is a whole organ distillation of corticomedullary contrast of diffusion metrics, as has been explored for other renal biomarkers. MATERIALS AND METHODS: In this work, we probe the spatial dependence of diffusion MRI metrics with concentrically layered segmentation in 11 healthy kidneys at 3 T. The metrics include those from DTI, IVIM, a combined approach titled "REnal Flow and Microstructure AnisotroPy (REFMAP)", and a multiply encoded model titled "FC-IVIM" providing estimates of fluid velocity and branching length. RESULTS: Fractional anisotropy decreased from the inner kidney to the outer kidney with the strongest layer correlation in both parenchyma (including cortex and medulla) and medulla with Spearman correlation coefficients and p-values (r, p) of (0.42, <0.001) and (0.37, <0.001), respectively. Also, dynamic parameters derived from the three models significantly decreased with a high correlation from the inner to the outer parenchyma or medulla with (r, p) ranges of (0.46-0.55, <0.001). CONCLUSIONS: These spatial trends might find implications for indirect assessments of kidney physiology and microstructure using diffusion MRI.

Generating High-Resolution Synthetic CT from Lung MRI with Ultrashort Echo Times: Initial Evaluation in Cystic Fibrosis.

Background Lung MRI with ultrashort echo times (UTEs) enables high-resolution and radiation-free morphologic imaging; however, its image quality is still lower than that of CT. Purpose To assess the image quality and clinical applicability of synthetic CT images generated from UTE MRI by a generative adversarial network (GAN). Materials and Methods This retrospective study included patients with cystic fibrosis (CF) who underwent both UTE MRI and CT on the same day at one of six institutions between January 2018 and December 2022. The two-dimensional GAN algorithm was trained using paired MRI and CT sections and tested, along with an external data set. Image quality was assessed quantitatively by measuring apparent contrast-to-noise ratio, apparent signal-to-noise ratio, and overall noise and qualitatively by using visual scores for features including artifacts. Two readers evaluated CF-related structural abnormalities and used them to determine clinical Bhalla scores. Results The training, test, and external data sets comprised 82 patients with CF (mean age, 21 years ± 11 [SD]; 42 male), 28 patients (mean age, 18 years ± 11; 16 male), and 46 patients (mean age, 20 years ± 11; 24 male), respectively. In the test data set, the contrast-to-noise ratio of synthetic CT images (median, 303 [IQR, 221-382]) was higher than that of UTE MRI scans (median, 9.3 [IQR, 6.6-35]; P < .001). The median signal-to-noise ratio was similar between synthetic and real CT (88 [IQR, 84-92] vs 88 [IQR, 86-91]; P = .96). Synthetic CT had a lower noise level than real CT (median score, 26 [IQR, 22-30] vs 42 [IQR, 32-50]; P < .001) and the lowest level of artifacts (median score, 0 [IQR, 0-0]; P < .001). The concordance between Bhalla scores for synthetic and real CT images was almost perfect (intraclass correlation coefficient, ≥0.92). Conclusion Synthetic CT images showed almost perfect concordance with real CT images for the depiction of CF-related pulmonary alterations and had better image quality than UTE MRI. Clinical trial registration no. NCT03357562 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Schiebler and Glide-Hurst in this issue.

Lung Function in Patients with Cystic Fibrosis before and during CFTR-Modulator Therapy Using 3D Ultrashort Echo Time MRI.

Background The triple combination of the cystic fibrosis transmembrane regulator (CFTR) modulators elexacaftor, tezacaftor, and ivacaftor (hereafter, elexacaftor/tezacaftor/ivacaftor) has a positive effect on lung function in patients with cystic fibrosis (CF). Purpose To compare three-dimensional (3D) ultrashort echo time (UTE) MRI functional lung data to common functional lung parameters in assessing lung function in patients with CF undergoing elexacaftor/tezacaftor/ivacaftor therapy. Materials and Methods In this prospective feasibility study, 16 participants with CF consented to undergo pulmonary MRI with a breath-hold 3D UTE sequence at baseline (April 2018-June 2019) and follow-up (April-July 2021). Eight participants received elexacaftor/tezacaftor/ivacaftor after baseline, and eight participants with unchanged treatment served as the control group. Lung function was assessed with body plethysmography and lung clearance index (LCI). Image-based functional lung parameters, such as ventilation inhomogeneity and ventilation defect percentage (VDP), were calculated from signal intensity change between MRI scans at inspiration and expiration. Metrics at baseline and follow-up were compared within groups (permutation test), correlation was tested (Spearman rank correlation), and 95% CIs were calculated (bootstrapping technique). Results MRI ventilation inhomogeneity correlated with LCI at baseline (r = 0.92, P < .001) and follow-up (r = 0.81, P = .002). Mean MRI ventilation inhomogeneity (baseline, 0.74 ± 0.15 [SD]; follow-up, 0.64 ± 0.11; P = .02) and mean VDP (baseline, 14.1% ± 7.4; follow-up, 8.5% ± 3.3; P = .02) decreased from baseline to follow-up in the treatment group. Lung function was stable over time (mean LCI: 9.3 turnovers ± 4.1 at baseline vs 11.5 turnovers ± 7.4 at follow-up; P = .34) in the control group. In all participants, correlation of forced expiratory volume in 1 second with MRI ventilation inhomogeneity was good at baseline (r = -0.61, P = .01) but poor during follow-up (r = -0.06, P = .82). Conclusion Noncontrast 3D UTE lung MRI functional parameters of ventilation inhomogeneity and VDP can be used to assess lung function over time in patients with CF and can add regional information to established global parameters, such as LCI. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Iwasawa in this issue.

Reduction of the cardiac pulsation artifact and improvement of lesion conspicuity in flow-compensated diffusion images in the liver-A quantitative evaluation of postprocessing algorithms.

PURPOSE: To enhance image quality of flow-compensated diffusion-weighted liver MRI data by increasing the lesion conspicuity and reducing the cardiac pulsation artifact using postprocessing algorithms. METHODS: Diffusion-weighted image data of 40 patients with liver lesions had been acquired at 1.5 T. These data were postprocessed with 5 different algorithms (weighted averaging, p-mean, percentile, outlier exclusion, and exception set). Four image properties of the postprocessed data were evaluated for optimizing the algorithm parameters. These properties were the lesion to tissue contrast-to-noise ratio (CNR), the reduction of the cardiac pulsation artifact, the data consistency, and the vessel darkness. They were combined into a total quality score ( Q total , $$ {Q}_{\mathrm{total}}, $$ set to 1 for the trace-weighted reference image), which was used to rate the image quality objectively. RESULTS: The weighted averaging algorithm performed best according to the total quality score ( Q total = 1.111 ± 0.067 $$ {Q}_{\mathrm{total}}=1.111\pm 0.067 $$ ). The further ranking was outlier exclusion algorithm ( Q total = 1.086 ± 0.061 $$ {Q}_{\mathrm{total}}=1.086\pm 0.061 $$ ), p-mean algorithm ( Q total = 1.045 ± 0.049 $$ {Q}_{\mathrm{total}}=1.045\pm 0.049 $$ ), percentile algorithm ( Q total = 1.012 ± 0.049 $$ {Q}_{\mathrm{total}}=1.012\pm 0.049 $$ ), and exception set algorithm ( Q total = 0.957 ± 0.027 $$ {Q}_{\mathrm{total}}=0.957\pm 0.027 $$ ). All optimized algorithms except for the exception set algorithm corrected the pulsation artifact and increased the lesion CNR. Changes in Q total $$ {Q}_{\mathrm{total}} $$ were significant for all optimized algorithms except for the percentile algorithm. Liver ADC was significantly reduced (except for the exception set algorithm), particularly in the left lobe. CONCLUSION: Postprocessing algorithms should be used for flow-compensated liver DWI. The proposed weighted averaging algorithm seems to be suited best to increase the image quality of artifact-corrupted flow-compensated diffusion-weighted liver data.

Longitudinal Evaluation of Bronchial Changes in Cystic Fibrosis Patients Undergoing Elexacaftor/Tezacaftor/Ivacaftor Therapy Using Lung MRI With Ultrashort Echo-Times.

BACKGROUND: Lung magnetic resonance imaging (MRI) with ultrashort echo-times (UTE-MRI) allows high-resolution and radiation-free imaging of the lung structure in cystic fibrosis (CF). In addition, the combination of elexacaftor/tezacaftor/ivacaftor (ETI) has improved CF clinical outcomes such as need for hospitalization. However, the effect on structural disease still needs longitudinal evaluation at high resolution. PURPOSE: To analyze the effects of ETI on lung structural alterations using UTE-MRI, with a focus on bronchiectasis reversibility. STUDY TYPE: Retrospective. POPULATION: Fifty CF patients (mean age 24.3 ± 9.2; 23 males). FIELD STRENGTH/SEQUENCE: 1.5 T, UTE-MRI. ASSESSMENT: All subjects completed both UTE-MRI and pulmonary function tests (PFTs) during two annual visits (M0 and M12), and 30 of them completed a CT scan. They initiated ETI treatment after M0 within a maximum of 3 months from the annual examinations. Three observers scored a clinical MRI Bhalla score on UTE-MRI. Bronchiectasis reversibility was defined as a reduction in both outer and inner bronchial dimensions. Correlations were searched between the Bhalla score and PFT such as the forced expiratory volume in 1 second percentage predicted (FEV1%p). STATISTICAL TESTS: Comparison was assessed using the paired t-test, correlation using the Spearman correlation test with a significance level of 0.05. Concordance and reproducibility were assessed using intraclass correlation coefficient (ICC). RESULTS: There was a significant improvement in MRI Bhalla score after ETI treatment. UTE-MRI demonstrated bronchiectasis reversibility in a subgroup of 18 out of 50 CF patients (36%). These patients with bronchiectasis reversibility were significantly younger, with lower severity of wall thickening but no difference in mucus plugging extent (P = 0.39) was found. The reproducibility of UTE-MRI evaluations was excellent (ICC ≥ 0.95), was concordant with CT scan (N = 30; ICC ≥ 0.90) and significantly correlated to FEV1% at PFT at M0 (N = 50; r = 0.71) and M12 (N = 50; r = 0.72). DATA CONCLUSION: UTE-MRI is a reproducible tool for the longitudinal follow-up of CF patients, allowing to quantify the response to ETI and demonstrating the reversibility of some structural alterations such as bronchiectasis in a substantial fraction of this study population. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 2.

Noninvasive Assessment of the Renal Function, Oxford Classification and Prognostic Risk Stratification of IgAN by Using Intravoxel Incoherent Motion Diffusion-Weighted Imaging and Blood Oxygenation Level-Dependent MRI.

BACKGROUND: Immunoglobulin A nephropathy (IgAN) is the most common primary glomerulonephritis worldwide. Oxford classification including mesangial hypercellularity (M), endothelial hypercellularity (E), segmental sclerosis (S), interstitial fibrosis/tubular atrophy (T), and crescent (C) were recommended to predict the prognosis of IgAN. PURPOSE: To explore whether multiparametric magnetic resonance imaging (MRI) can be applied to assess the renal function, Oxford classification, and risk of progression to end-stage kidney disease within 5 years of IgAN. STUDY TYPE: Prospective. POPULATION: A total of 46 patients with pathologically confirmed IgAN and 20 healthy volunteers. FIELD STRENGTH/SEQUENCE: A 3-T, blood oxygenation level-dependent (BOLD)-MRI, intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI). ASSESSMENT: Two radiologists measured the cortex and medulla T2*, apparent diffusion coefficient (ADC), true diffusion (Dt), pseudo-diffusion (Dp), perfusion fraction (fp). All participants were divided into three groups: group 1, healthy volunteers; group 2, patients with estimated glomerular filtration rate (eGFR) ≥60 mL/min/1.73 m2 ; group 3, patients with eGFR <60 mL/min/1.73 m2 . Or two groups: group A, 5-year risk scores ≤10% and group B, 5-year risk scores >10%. STATISTICAL TESTS: Intraclass correlation coefficient, one-way analysis of variance, least-significant difference, Student's t-test, Pearson product-moment correlation, Spearman's rank correlation, and receiver operating characteristics (ROC) with the area under the curve (AUC). A P value <0.05 was considered statistically significant. RESULTS: Except for cortical Dp, all other MRI parameters showed significant differences between group 1 and group 2. None of the MRI parameters showed a significant correlation with M, E, or C scores. Cortical T2*, Dt, fp, and medullary Dt and fp showed low-to-moderate significant correlations with S scores. Except for cortical and medullary Dp, all other MRI parameters were significantly correlated with T scores. Cortical Dt showed the largest AUC for differentiating group A from group B (AUC = 0.927) and T0 from T1/T2 (AUC = 0.963). DATA CONCLUSION: Imaging by IVIM-DWI and BOLD-MRI could facilitate noninvasive assessment of the renal function, Oxford classification, and prognostic risk of IgAN patients. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 3.

Cardiac Phase and Flow Compensation Effects on REnal Flow and Microstructure AnisotroPy MRI in Healthy Human Kidney.

BACKGROUND: Renal diffusion-weighted imaging (DWI) involves microstructure and microcirculation, quantified with diffusion tensor imaging (DTI), intravoxel incoherent motion (IVIM), and hybrid models. A better understanding of their contrast may increase specificity. PURPOSE: To measure modulation of DWI with cardiac phase and flow-compensated (FC) diffusion gradient waveforms. STUDY TYPE: Prospective. POPULATION: Six healthy volunteers (ages: 22-48 years, five females), water phantom. FIELD STRENGTH/SEQUENCE: 3-T, prototype DWI sequence with 2D echo-planar imaging, and bipolar (BP) or FC gradients. 2D Half-Fourier Single-shot Turbo-spin-Echo (HASTE). Multiple-phase 2D spoiled gradient-echo phase contrast (PC) MRI. ASSESSMENT: BP and FC water signal decays were qualitatively compared. Renal arteries and velocities were visualized on PC-MRI. Systolic (peak velocity), diastolic (end stable velocity), and pre-systolic (before peak velocity) phases were identified. Following mutual information-based retrospective self-registration of DWI within each kidney, and Marchenko-Pastur Principal Component Analysis (MPPCA) denoising, combined IVIM-DTI analysis estimated mean diffusivity (MD), fractional anisotropy (FA), and eigenvalues (λi) from tissue diffusivity (Dt ), perfusion fraction (fp ), and pseudodiffusivity (Dp , Dp,axial , Dp,radial ), for each tissue (cortex/medulla, segmented on b0/FA respectively), phase, and waveform (BP, FC). Monte Carlo water diffusion simulations aided data interpretation. STATISTICAL TESTS: Mixed model regression probed differences between tissue types and pulse sequences. Univariate general linear model analysis probed variations among cardiac phases. Spearman correlations were measured between diffusion metrics and renal artery velocities. Statistical significance level was set at P < 0.05. RESULTS: Water BP and FC signal decays showed no differences. Significant pulse sequence dependence occurred for λ1 , λ3 , FA, Dp , fp , Dp,axial , Dp,radial in cortex and medulla, and medullary λ2 . Significant cortex/medulla differences occurred with BP for all metrics except MD (systole [P = 0.224]; diastole [P = 0.556]). Significant phase dependence occurred for Dp , Dp,axial , Dp,radial for BP and medullary λ1 , λ2 , λ3 , MD for FC. FA correlated significantly with velocity. Monte Carlo simulations indicated medullary measurements were consistent with a 34 µm tubule diameter. DATA CONCLUSION: Cardiac gating and flow compensation modulate of measurements of renal diffusion. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY STAGE: 2.

Deep Learning k-Space-to-Image Reconstruction Facilitates High Spatial Resolution and Scan Time Reduction in Diffusion-Weighted Imaging Breast MRI.

BACKGROUND: For time-consuming diffusion-weighted imaging (DWI) of the breast, deep learning-based imaging acceleration appears particularly promising. PURPOSE: To investigate a combined k-space-to-image reconstruction approach for scan time reduction and improved spatial resolution in breast DWI. STUDY TYPE: Retrospective. POPULATION: 133 women (age 49.7 ± 12.1 years) underwent multiparametric breast MRI. FIELD STRENGTH/SEQUENCE: 3.0T/T2 turbo spin echo, T1 3D gradient echo, DWI (800 and 1600 sec/mm2 ). ASSESSMENT: DWI data were retrospectively processed using deep learning-based k-space-to-image reconstruction (DL-DWI) and an additional super-resolution algorithm (SRDL-DWI). In addition to signal-to-noise ratio and apparent diffusion coefficient (ADC) comparisons among standard, DL- and SRDL-DWI, a range of quantitative similarity (e.g., structural similarity index [SSIM]) and error metrics (e.g., normalized root mean square error [NRMSE], symmetric mean absolute percent error [SMAPE], log accuracy error [LOGAC]) was calculated to analyze structural variations. Subjective image evaluation was performed independently by three radiologists on a seven-point rating scale. STATISTICAL TESTS: Friedman's rank-based analysis of variance with Bonferroni-corrected pairwise post-hoc tests. P < 0.05 was considered significant. RESULTS: Both DL- and SRDL-DWI allowed for a 39% reduction in simulated scan time over standard DWI (5 vs. 3 minutes). The highest image quality ratings were assigned to SRDL-DWI with good interreader agreement (ICC 0.834; 95% confidence interval 0.818-0.848). Irrespective of b-value, both standard and DL-DWI produced superior SNR compared to SRDL-DWI. ADC values were slightly higher in SRDL-DWI (+0.5%) and DL-DWI (+3.4%) than in standard DWI. Structural similarity was excellent between DL-/SRDL-DWI and standard DWI for either b value (SSIM ≥ 0.86). Calculation of error metrics (NRMSE ≤ 0.05, SMAPE ≤ 0.02, and LOGAC ≤ 0.04) supported the assumption of low voxel-wise error. DATA CONCLUSION: Deep learning-based k-space-to-image reconstruction reduces simulated scan time of breast DWI by 39% without influencing structural similarity. Additionally, super-resolution interpolation allows for substantial improvement of subjective image quality. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 1.

Capability of arterial spin labeling and intravoxel incoherent motion diffusion-weighted imaging to detect early kidney injury in chronic kidney disease.

OBJECTIVES: To prospectively investigate the capability of arterial spin labeling (ASL) and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) for the identification of early kidney injury in chronic kidney disease (CKD) patients with normal estimated glomerular filtration rate (eGFR). METHODS: Fifty-four CKD patients confirmed by renal biopsy (normal eGFR group [eGFR ≥ 90 mL/min/1.73 m2]: n = 26; abnormal eGFR group [eGFR < 90 mL/min/1.73 m2]: n = 28) and 20 healthy volunteers (HV) were recruited. All subjects were examined by IVIM-DWI and ASL imaging. Renal blood flow (RBF) derived from ASL, true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) derived from IVIM-DWI were measured from the renal cortex. One-way analysis of variance was used to compare MRI parameters among the three groups. The correlation between eGFR and MRI parameters was evaluated by Spearman correlation analysis. Diagnostic performances of MRI parameters for detecting kidney injury were assessed by receiver operating characteristic (ROC) curves. RESULTS: The renal cortical D, D*, f, and RBF values showed statistically significant differences among the three groups. eGFR was positively correlated with MRI parameters (D: r = 0.299, D*: r = 0.569, f: r = 0.733, RBF: r = 0.586). The areas under the curve (AUCs) for discriminating CKD patients from HV were 0.725, 0.752, 0.947, and 0.884 by D, D*, f, and RBF, respectively. D, D*, f, RBF, and eGFR identified CKD patients with normal eGFR with AUCs of 0.735, 0.612, 0.917, 0.827, and 0.733, respectively, and AUC of f value was significantly larger than that of eGFR. CONCLUSION: IVIM-DWI and ASL were useful for detecting underlying pathologic injury in early CKD patients with normal eGFR. KEY POINTS: • The renal cortical f and RBF values in the control group were significantly higher than those in the normal eGFR group. • A negative correlation was observed between the renal cortical D, D*, f, and RBF values and SCr and 24 h-UPRO, while eGFR was significantly positively correlated with renal cortical D, D*, f, and RBF values. • The AUC of renal cortical f values was statistically larger than that of eGFR for the discrimination between the CKD with normal eGFR group and the control group.

Evaluation of interstitial fibrosis in chronic kidney disease by multiparametric functional MRI and histopathologic analysis.

OBJECTIVES: To investigate the diagnostic value of functional MRI to assess renal interstitial fibrosis in patients with chronic kidney disease (CKD). METHODS: We prospectively recruited 80 CKD patients who underwent renal biopsies and 16 healthy volunteers to undergo multiparametric functional MRI examinations. The Oxford MEST-C classification was used to score the interstitial fibrosis. The diagnostic performance of functional MRI to discriminate interstitial fibrosis was evaluated by calculating the area under the receiver operating characteristic (ROC) curves. RESULTS: IgA nephropathy (60%) accounted for the majority of pathologic type in the CKD patients. Apparent diffusion coefficient (ADC) from diffusion-weighted imaging (DWI) was correlated with interstitial fibrosis (rho = -0.73). Decreased renal blood flow (RBF) derived from arterial spin labeling (rho = -0.78) and decreased perfusion fraction (f) derived from DWI (rho = -0.70) were accompanied by increased interstitial fibrosis. The T1 value from T1 mapping correlated with interstitial fibrosis (rho = 0.67) (all p < 0.01). The areas under the ROC curve for the discrimination of ≤ 25% vs. > 25% and ≤ 50% vs. > 50% interstitial fibrosis were 0.87 (95% confidence interval, 0.78 to 0.94) and 0.93 (0.86 to 0.98) by ADC, 0.84 (0.74 to 0.91) and 0.94 (0.86 to 0.98) by f, 0.93 (0.85 to 0.98) and 0.90 (0.82 to 0.96) by RBF, and 0.91 (0.83 to 0.96) and 0.77 (0.66 to 0.85) by T1, respectively. CONCLUSIONS: Functional MRI parameters were strongly correlated with the interstitial fibrosis of CKD. Therefore, it might a powerful tool to assess interstitial fibrosis of CKD noninvasively. KEY POINTS: • In CKD patients, the renal cortical ADC value decreased and T1 value increased significantly compared with healthy volunteers. • Functional MRI revealed significantly decreased renal perfusion in CKD patients compared with healthy volunteers. • The renal cortical ADC, f, RBF, and T1 values were strongly correlated with the interstitial fibrosis of CKD.

Simultaneous multislice diffusion-weighted imaging versus standard diffusion-weighted imaging in whole-body PET/MRI.

OBJECTIVE: To compare standard (STD-DWI) single-shot echo-planar imaging DWI and simultaneous multislice (SMS) DWI during whole-body positron emission tomography (PET)/MRI regarding acquisition time, image quality, and lesion detection. METHODS: Eighty-three adults (47 females, 57%), median age of 64 years (IQR 52-71), were prospectively enrolled from August 2018 to March 2020. Inclusion criteria were (a) abdominal or pelvic tumors and (b) PET/MRI referral from a clinician. Patients were excluded if whole-body acquisition of STD-DWI and SMS-DWI sequences was not completed. The evaluated sequences were axial STD-DWI at b-values 50-400-800 s/mm2 and the apparent diffusion coefficient (ADC), and axial SMS-DWI at b-values 50-300-800 s/mm2 and ADC, acquired with a 3-T PET/MRI scanner. Three radiologists rated each sequence's quality on a five-point scale. Lesion detection was quantified using the anatomic MRI sequences and PET as the reference standard. Regression models were constructed to quantify the association between all imaging outcomes/scores and sequence type. RESULTS: The median whole-body STD-DWI acquisition time was 14.8 min (IQR 14.1-16.0) versus 7.0 min (IQR 6.7-7.2) for whole-body SMS-DWI, p < 0.001. SMS-DWI image quality scores were higher than STD-DWI in the abdomen (OR 5.31, 95% CI 2.76-10.22, p < 0.001), but lower in the cervicothoracic junction (OR 0.21, 95% CI 0.10-0.43, p < 0.001). There was no significant difference in the chest, mediastinum, pelvis, and rectum. STD-DWI detected 276/352 (78%) lesions while SMS-DWI located 296/352 (84%, OR 1.46, 95% CI 1.02-2.07, p = 0.038). CONCLUSIONS: In cancer staging and restaging, SMS-DWI abbreviates acquisition while maintaining or improving the diagnostic yield in most anatomic regions. KEY POINTS: • Simultaneous multislice diffusion-weighted imaging enables faster whole-body image acquisition. • Simultaneous multislice diffusion-weighted imaging maintains or improves image quality when compared to single-shot echo-planar diffusion-weighted imaging in most anatomical regions. • Simultaneous multislice diffusion-weighted imaging leads to superior lesion detection.

Comparison of diagnostic quality of 3D ultrashort-echo-time techniques for pulmonary magnetic resonance imaging in free-breathing.

BACKGROUND: Ultrashort-echo-time (UTE) sequences have been developed to overcome technical limitations of pulmonary magnetic resonance imaging (MRI). Recently, it has been shown that UTE sequences with breath-hold allow rapid image acquisition with sufficient image quality. However, patients with impaired respiration require alternative acquisition strategies while breathing freely. PURPOSE: To compare the diagnostic performance of free-breathing three-dimensional (3D)-UTE sequences with different trajectories based on pulmonary imaging of immunocompromised patients. MATERIAL AND METHODS: In a prospective study setting, two 3D-UTE sequences performed in free-breathing and exploiting non-Cartesian trajectories-one using a stack-of-spirals and the other exploiting a radial trajectory-were acquired at 3 T in patients undergoing hematopoietic stem cell transplantation. Two radiologists assessed the images regarding presence of pleural effusions and pulmonary infiltrations. Computed tomography (CT) was used as reference. RESULTS: A total of 28 datasets, each consisting of free-breathing 3D-UTE MRI with the two sequence techniques and a reference CT scan, were acquired in 20 patients. Interrater agreement was substantial for pulmonary infiltrations using both sequence techniques (κ = 0.77 - 0.78). Regarding pleural effusions, agreement was almost perfect in the stack-of-spirals (κ = 0.81) and moderate in the radial sequence (κ = 0.59). No significant differences in detectability of the assessed pulmonary pathologies were observed between both 3D-UTE sequence techniques (P > 0.05), and their level of agreement was substantial throughout (κ = 0.62-0.81). Both techniques provided high sensitivities and specificities (79%-100%) for the detection of pulmonary infiltrations and pleural effusions compared to reference CT. CONCLUSION: The diagnostic performance of the assessed 3D-UTE MRI sequences was similar. Both sequences enable the detection of typical inflammatory lung pathologies.

Whole-body diffusion magnetic resonance imaging with simultaneous multi-slice excitation in children and adolescents.

BACKGROUND: Whole-body magnetic resonance imaging (WB-MRI) is an increasingly used guideline-based imaging modality for oncological and non-oncological pathologies during childhood and adolescence. While diffusion-weighted imaging (DWI), a part of WB-MRI, enhances image interpretation and improves sensitivity, it also requires the longest acquisition time during a typical WB-MRI scan protocol. Interleaved short tau inversion recovery (STIR) DWI with simultaneous multi-slice (SMS) acquisition is an effective way to speed up examinations. OBJECTIVE: In this study of children and adolescents, we compared the acquisition time, image quality, signal-to-noise ratio (SNR) and apparent diffusion coefficient (ADC) values of an interleaved STIR SMS-DWI sequence with a standard non-accelerated DWI sequence for WB-MRI. MATERIALS AND METHODS: Twenty children and adolescents (mean age: 13.9 years) who received two WB-MRI scans at a maximum interval of 18 months, consisting of either standard DWI or SMS-DWI MRI, respectively, were included. For quantitative evaluation, the signal-to-noise ratio (SNR) was determined for b800 images and ADC maps of seven anatomical regions. Image quality evaluation was independently performed by two experienced paediatric radiologists using a 5-point Likert scale. The measurement time per slice stack, pause between measurements including shim and total measurement time of DWI for standard DWI and SMS-DWI were extracted directly from the scan data. RESULTS: When including the shim duration, the acquisition time for SMS-DWI was 43% faster than for standard DWI. Qualitatively, the scores of SMS-DWI were higher in six locations in the b800 images and four locations in the ADC maps. There was substantial agreement between both readers, with a Cohen's kappa of 0.75. Quantitatively, the SNR in the b800 images and the ADC maps did not differ significantly from one another. CONCLUSION: Whole body-MRI with SMS-DWI provided equivalent image quality and reduced the acquisition time almost by half compared to the standard WB-DWI protocol.

Evaluation of diffusion-weighted magnetic resonance imaging of the rectal cancers: comparison between modified reduced field-of-view single-shot echo-planar imaging with tilted two-dimensional radiofrequency excitation pulses and conventional full field-of-view readout-segmented echo-planar imaging.

PURPOSE: To evaluate the image quality qualitatively and quantitatively, as well as apparent diffusion coefficient (ADC) values of modified reduced field-of-view diffusion-weighted magnetic resonance imaging (MRI) using spatially tailored two-dimensional radiofrequency pulses with tilted excitation plane (tilted r-DWI) based on single-shot echo planar imaging (SS-EPI) compared with full-size field-of-view DWI (f-DWI) using readout segmented (RS)-EPI in patients with rectal cancer. MATERIALS AND METHODS: Twenty-two patients who underwent an MRI for further evaluation of rectal cancer were included in this retrospective study. All MR images were analyzed to compare image quality, lesion conspicuity, and artifacts between f-DWI with RS-EPI and tilted r-DWI with SS-EPI. Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and ADC values were also compared. The Wilcoxon signed-rank test or paired t test was performed to compare the qualitative and quantitative assessments. RESULTS: All image quality scores, except aliasing artifacts, were significantly higher (p < 0.01 for all) in tilted r-DWI than f-DWI with RS-EPI. CNR in tilted r-DWI was significantly higher than in f-DWI with RS-EPI (p < 0.01), while SNR was not significantly different. Regarding the ADC values, no significant difference was observed between tilted r-DWI and f-DWI with RS-EPI (p = 0.27). CONCLUSION: Tilted r-DWI provides a better image quality with fewer artifacts and higher rectal lesion conspicuity than f-DWI with RS-EPI, indicating the feasibility of this MR sequence in evaluating rectal cancer in clinical practice.

Spatially resolved free-induction decay spectroscopy using a 3D ultra-short echo time multi-echo imaging sequence with systematic echo shifting and compensation of B0 field drifts.

PURPOSE: Biologically interesting signals can exhibit fast transverse relaxation and frequency shifts compared to free water. For spectral assignment, a ultra-short echo time (UTE) imaging sequence was modified to provide pixel-wise free-induction decay (FID) acquisition. METHODS: The UTE-FID approach presented relies on a multi-echo 3D spiral UTE sequence with six echoes per radiofrequency (RF) excitation (TEmin 0.05 ms, echo spacing 3 ms). A complex pixel-wise raw data set for FID spectroscopy is obtained by several multi-echo UTE measurements with systematic shifting of the readout by 0.25 or 0.5 ms, until the time domain is filled for 18 or 45 ms. B0 drifts are compensated by mapping and according phase correction. Autoregressive extrapolation of the signal is performed before Gaussian filtering. This method was applied to a phantom containing collagen-water solutions of different concentrations. To calculate the collagen content, a 19-peak collagen model was extracted from a non-selective FID spectrum (50% collagen solution). Proton-density-collagen-fraction (PDCF) was calculated for 10 collagen solutions (2%-50%). Furthermore, an in vivo UTE-FID spectrum of adipose tissue was recorded. RESULTS: UTE-FID signal patterns agreed well with the non-spatially selective pulse-acquire FID spectrum from a sphere filled with 50% collagen. Differentiation of collagen solution from distilled water in the PDCF map was possible from 4% collagen concentration for a UTE-FID sequence with 128 × 128 × 64 matrix (voxel size 1 × 1 × 2.85 mm3 ). The mean values of the PDCF correlate linearly with collagen concentration. CONCLUSION: The presented UTE-FID approach allows pixel-wise raw data acquisition similar to non-spatially selective pulse-acquire spectroscopy. Spatially resolved applications for assessment of spectra of rapidly decaying signals seem feasible.

Robust partial Fourier reconstruction for diffusion-weighted imaging using a recurrent convolutional neural network.

PURPOSE: To develop an algorithm for robust partial Fourier (PF) reconstruction applicable to diffusion-weighted (DW) images with non-smooth phase variations. METHODS: Based on an unrolled proximal splitting algorithm, a neural network architecture is derived, which alternates between data consistency operations and regularization implemented by recurrent convolutions. In order to exploit correlations, multiple repetitions of the same slice are jointly reconstructed under consideration of permutation-equivariance. The algorithm is trained on DW liver data of 60 volunteers and evaluated on retrospectively and prospectively subsampled data of different anatomies and resolutions. RESULTS: The proposed method is able to significantly outperform conventional PF techniques on retrospectively subsampled data in terms of quantitative measures as well as perceptual image quality. In this context, joint reconstruction of repetitions as well as the particular type of recurrent network unrolling are found to be beneficial with respect to reconstruction quality. On prospectively PF-sampled data, the proposed method enables DW imaging with higher signal without sacrificing image resolution or introducing additional artifacts. Alternatively, it can be used to counter the TE increase in acquisitions with higher resolution. Furthermore, generalizability can be shown to prospective brain data exhibiting anatomies and contrasts not present in the training set. CONCLUSION: This work demonstrates that robust PF reconstruction of DW data is feasible even at strong PF factors in anatomies prone to phase variations. Since the proposed method does not rely on smoothness priors of the phase but uses learned recurrent convolutions instead, artifacts of conventional PF methods can be avoided.