Tomoelastography and Pancreatic Extracellular Volume Fraction Derived From MRI for Predicting Clinically Relevant Postoperative Pancreatic Fistula.

BACKGROUND: Pancreatic stiffness and extracellular volume fraction (ECV) are potential imaging biomarkers for pancreatic fibrosis. Clinically relevant postoperative fistula (CR-POPF) is one of the most severe complications after pancreaticoduodenectomy. Which imaging biomarker performs better for predicting the risk of CR-POPF remains unknown. PURPOSE: To evaluate the diagnostic performance of ECV and tomoelastography-derived pancreatic stiffness for predicting the risk of CR-POPF in patients undergoing pancreaticoduodenectomy. STUDY TYPE: Prospective. POPULATION: Eighty patients who underwent multiparametric pancreatic MRI before pancreaticoduodenectomy, among whom 16 developed CR-POPF and 64 did not. FIELD STRENGTH/SEQUENCE: 3 T/tomoelastography and precontrast and postcontrast T1 mapping of the pancreas. ASSESSMENT: Pancreatic stiffness was measured on the tomographic c-map, and pancreatic ECV was calculated from precontrast and postcontrast T1 maps. Pancreatic stiffness and ECV were compared with histological fibrosis grading (F0-F3). The optimal cutoff values for predicting CR-POPF were determined, and the correlation between CR-POPF and imaging parameters was evaluated. STATISTICAL TESTS: The Spearman's rank correlation and multivariate linear regression analysis was conducted. The receiver operating characteristic curve analysis and logistic regression analysis was performed. A double-sided P < 0.05 indicated a statistically significant difference. RESULTS: Pancreatic stiffness and ECV both showed a significantly positive correlation with histological pancreatic fibrosis (r = 0.73 and 0.56, respectively). Patients with advanced pancreatic fibrosis had significantly higher pancreatic stiffness and ECV compared to those with no/mild fibrosis. Pancreatic stiffness and ECV were also correlated with each other (r = 0.58). Lower pancreatic stiffness (<1.38 m/sec), lower ECV (<0.28), nondilated main pancreatic duct (<3 mm) and pathological diagnosis other than pancreatic ductal adenocarcinoma were associated with higher risk of CR-POPF at univariate analysis, and pancreatic stiffness was independently associated with CR-POPF at multivariate analysis (odds ratio: 18.59, 95% confidence interval: 4.45, 77.69). DATA CONCLUSION: Pancreatic stiffness and ECV were associated with histological fibrosis grading, and pancreatic stiffness was an independent predictor for CR-POPF. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 5.

Hepatobiliary phase imaging in cirrhotic patients using compressed sensing and controlled aliasing in parallel imaging results in higher acceleration.

OBJECTIVE: We aimed to compare the image quality and focal lesion detection ability of hepatobiliary phase (HBP) images obtained using compressed sensing (CS) and controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA) in patients with liver cirrhosis. MATERIALS AND METHODS: We retrospectively included 244 gadoxetic acid-enhanced liver MRI from 244 patients with cirrhosis obtained by two HBP images using CS and CAIPIRINHA from July 2020 to December 2020. The optimized resolution and scan time for CS-HBP and CAIPIRINHA-HBP were 0.9 × 0.9 × 1.5 mm3 and 15 s and 1.3 × 1.3 × 3 mm3 and 16 s, respectively. We compared the image quality between the two sets of images in 244 patients and focal lesion (n = 294) analyses for 112 patients. RESULTS: CS-HBP showed comparable overall image quality (3.7 ± 0.9 vs. 3.6 ± 0.8, p = 0.680), superior liver edge sharpness (3.9 ± 0.6 vs. 3.6 ± 0.5, p < 0.001), and fewer respiratory motion artifacts (4.0 ± 0.7 vs. 3.8 ± 0.5, p < 0.001), but higher non-respiratory artifacts (3.4 ± 0.7 vs. 3.6 ± 0.6, p < 0.001) and subjective image noise (3.5 ± 0.8 vs. 3.6 ± 0.7, p = 0.014) than CAIPIRINHA-HBP. CS-HBP showed a higher signal-to-noise ratio in the liver than CAIPIRINHA-HBP (20.9 ± 9.0 vs. 18.9 ± 7.1, p = 0.008). The pooled sensitivity, specificity, and AUC were 90.0%, 77.5%, and 0.84 for CS-HBP and 73.5%, 82.4%, and 0.78 for CAIPIRINHA-HBP, respectively. CONCLUSIONS: CS-HBP showed better focal lesion detection ability, comparable overall image quality, and fewer respiratory motion artifacts, but higher non-respiratory artifacts and noise compared to CAIPIRINHA-HBP. Thus, CS-HBP could be recommended for liver MRI in patients with cirrhosis to improve diagnostic performance. CLINICAL RELEVANCE STATEMENT: Thin-slice CS-HBP may be useful for detecting sub-centimeter hepatocellular carcinoma in cirrhotic patients with Child-Pugh classification A while maintaining comparable subjective image quality. KEY POINTS: • Compared with controlled aliasing in parallel imaging results in higher acceleration, compressed sensing hepatobiliary phase yielded thinner slices and shorter scan time at a higher accelerating factor. • Compressed sensing hepatobiliary phase showed comparable overall image quality, superior liver edge sharpness, and fewer respiratory motion artifacts, but higher non-respiratory artifacts and subjective image noise than controlled aliasing in parallel imaging results in higher acceleration-hepatobiliary phase. • Compressed sensing hepatobiliary phase can detect sub-centimeter hepatocellular carcinoma in cirrhotic patients with Child-Pugh classification A.

Evaluation of simultaneous multi-slice acquisition with advanced processing for free-breathing diffusion-weighted imaging in patients with liver metastasis.

OBJECTIVES: Diffusion-weighted imaging (DWI) with simultaneous multi-slice (SMS) acquisition and advanced processing can accelerate acquisition time and improve MR image quality. This study evaluated the image quality and apparent diffusion coefficient (ADC) measurements of free-breathing DWI acquired from patients with liver metastases using a prototype SMS-DWI acquisition (with/without an advanced processing option) and conventional DWI. METHODS: Four DWI schemes were compared in a pilot 5-patient cohort; three DWI schemes were further assessed in a 24-patient cohort. Two readers scored image quality of all b-value images and ADC maps across the three methods. ADC measurements were performed, for all three methods, in left and right liver parenchyma, spleen, and liver metastases. The Friedman non-parametric test (post-hoc Wilcoxon test with Bonferroni correction) was used to compare image quality scoring; t-test was used for ADC comparisons. RESULTS: SMS-DWI was faster (by 24%) than conventional DWI. Both readers scored the SMS-DWI with advanced processing as having the best image quality for highest b-value images (b750) and ADC maps; Cohen's kappa inter-reader agreement was 0.6 for b750 image and 0.56 for ADC maps. The prototype SMS-DWI sequence with advanced processing allowed a better visualization of the left lobe of the liver. ADC measured in liver parenchyma, spleen, and liver metastases using the SMS-DWI with advanced processing option showed lower values than those derived from the SMS-DWI method alone (t-test, p < 0.0001; p < 0.0001; p = 0.002). CONCLUSIONS: Free-breathing SMS-DWI with advanced processing was faster and demonstrated better image quality versus a conventional DWI protocol in liver patients. CLINICAL RELEVANCE STATEMENT: Free-breathing simultaneous multi-slice- diffusion-weighted imaging (DWI) with advanced processing was faster and demonstrated better image quality versus a conventional DWI protocol in liver patients. KEY POINTS: • Diffusion-weighted imaging (DWI) with simultaneous multi-slice (SMS) can accelerate acquisition time and improve image quality. • Apparent diffusion coefficients (ADC) measured in liver parenchyma, spleen, and liver metastases using the simultaneous multi-slice DWI with advanced processing were significantly lower than those derived from the simultaneous multi-slice DWI method alone. • Simultaneous multi-slice DWI sequence with inline advanced processing was faster and demonstrated better image quality in liver patients.

Enhancing gadoxetic acid-enhanced liver MRI: a synergistic approach with deep learning CAIPIRINHA-VIBE and optimized fat suppression techniques.

OBJECTIVE: To investigate whether a deep learning (DL) controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA)-volumetric interpolated breath-hold examination (VIBE) technique can improve image quality, lesion conspicuity, and lesion detection compared to a standard CAIPIRINHA-VIBE technique in gadoxetic acid-enhanced liver MRI. METHODS: This retrospective single-center study included 168 patients who underwent gadoxetic acid-enhanced liver MRI at 3 T using both standard CAIPIRINHA-VIBE and DL CAIPIRINHA-VIBE techniques on pre-contrast and hepatobiliary phase (HBP) images. Additionally, high-resolution (HR) DL CAIPIRINHA-VIBE was obtained with 1-mm slice thickness on the HBP. Three abdominal radiologists independently assessed the image quality and lesion conspicuity of pre-contrast and HBP images. Statistical analyses involved the Wilcoxon signed-rank test for image quality assessment and the generalized estimation equation for lesion conspicuity and detection evaluation. RESULTS: DL and HR-DL CAIPIRINHA-VIBE demonstrated significantly improved overall image quality and reduced artifacts on pre-contrast and HBP images compared to standard CAIPIRINHA-VIBE (p < 0.001), with a shorter acquisition time (DL vs standard, 11 s vs 17 s). However, the former presented a more synthetic appearance (both p < 0.05). HR-DL CAIPIRINHA-VIBE showed superior lesion conspicuity to standard and DL CAIPIRINHA-VIBE on HBP images (p < 0.001). Moreover, HR-DL CAIPIRINHA-VIBE exhibited a significantly higher detection rate of small (< 2 cm) solid focal liver lesions (FLLs) on HBP images compared to standard CAIPIRINHA-VIBE (92.5% vs 87.4%; odds ratio = 1.83; p = 0.036). CONCLUSION: DL and HR-DL CAIPIRINHA-VIBE achieved superior image quality compared to standard CAIPIRINHA-VIBE. Additionally, HR-DL CAIPIRINHA-VIBE improved the lesion conspicuity and detection of small solid FLLs. DL and HR-DL CAIPIRINHA-VIBE hold the potential clinical utility for gadoxetic acid-enhanced liver MRI. CLINICAL RELEVANCE STATEMENT: DL and HR-DL CAIPIRINHA-VIBE hold promise as potential alternatives to standard CAIPIRINHA-VIBE in routine clinical liver MRI, improving the image quality and lesion conspicuity, enhancing the detection of small (< 2 cm) solid focal liver lesions, and reducing the acquisition time. KEY POINTS: • DL and HR-DL CAIPIRINHA-VIBE demonstrated improved overall image quality and reduced artifacts on pre-contrast and HBP images compared to standard CAIPIRINHA-VIBE, in addition to a shorter acquisition time. • DL and HR-DL CAIPIRINHA-VIBE yielded a more synthetic appearance than standard CAIPIRINHA-VIBE. • HR-DL CAIPIRINHA-VIBE showed improved lesion conspicuity than standard CAIPIRINHA-VIBE on HBP images, with a higher detection of small (< 2 cm) solid focal liver lesions.

Prediction of Recurrent Cervical Cancer in 2-Year Follow-Up After Treatment Based on Quantitative and Qualitative Magnetic Resonance Imaging Parameters: A Preliminary Study.

PURPOSE: This study investigated predictors of cervical cancer (CC) recurrence from native T1 mapping, conventional imaging, and clinicopathologic metrics. PATIENTS AND METHODS: In total, 144 patients with histopathologically confirmed CC (90 with and 54 without surgical treatment) were enrolled in this prospective study. Native T1 relaxation time, conventional imaging, and clinicopathologic characteristics were acquired. The association of quantitative and qualitative parameters with post-treatment tumor recurrence was assessed using univariate and multivariate Cox proportional hazard regression analyses. Independent risk factors were combined into a model and individual prognostic index equation for predicting recurrence risk. The receiver operating characteristic (ROC) curve determined the optimal cutoff point. RESULTS: In total, 12 of 90 (13.3%) surgically treated patients experienced tumor recurrence. Native T1 values (X1) [hazard ratio (HR) 1.008; 95% confidence interval (CI) 1.001-1.016], maximum tumor diameter (X2) (HR 1.065; 95% CI 1.020-1.113), and parametrial invasion (X3) (HR 3.930; 95% CI 1.013-15.251) were independent tumor recurrence risk factors. The individual prognostic index (PI) of the established recurrence risk model was PI = 0.008X1 + 0.063X2 + 1.369X3. The area under the ROC curve (AUC) of the Cox regression model was 0.923. A total of 20 of 54 (37.0%) non-surgical patients experienced tumor recurrence. Native T1 values (X1) (HR 1.012; 95% CI 1.007-1.016) and lymph node metastasis (X2) (HR 4.064; 95% CI 1.378-11.990) were independent tumor recurrence risk factors. The corresponding PI was calculated as follows: PI = 0.011X1 + 1.402X2; the Cox regression model AUC was 0.921. CONCLUSIONS: Native T1 values combined with conventional imaging and clinicopathologic variables could facilitate the pretreatment prediction of CC recurrence.

T1 mapping and extracellular volume fraction measurement to evaluate the poor-prognosis factors in patients with cervical squamous cell carcinoma.

PURPOSE: To evaluate the clinical feasibility of T1 mapping and extracellular volume fraction (ECV) measurement in assessing prognostic factors in patients with cervical squamous cell carcinoma (CSCC). MATERIALS AND METHODS: A total of 117 CSCC patients and 59 healthy volunteers underwent T1 mapping and diffusion-weighted imaging (DWI) on a 3 T system. Native T1 , contrast-enhanced T1 , ECV, and apparent diffusion coefficient (ADC) were calculated and compared based on surgico-pathologically verified deep stromal infiltration, parametrial invasion (PMI), lymphovascular space invasion (LVSI), lymph node metastasis, stage, histologic grade, and the Ki-67 labeling index (LI). RESULTS: Native T1 , contrast-enhanced T1 , ECV, and ADC values were significantly different between CSCC and the normal cervix (all p < 0.05). No significant differences were observed in any parameters of CSCC when the tumors were grouped by stromal infiltration or lymph node status, respectively (all p > 0.05). In subgroups of the tumor stage and PMI, native T1 was significantly higher for advanced-stage (p = 0.032) and PMI-positive CSCC (p = 0.001). In subgroups of the grade and Ki-67 LI, contrast-enhanced T1 was significantly higher for high-grade (p = 0.012) and Ki-67 LI ≥ 50% tumors (p = 0.027). ECV was significantly higher in LVSI-positive CSCC than in LVSI-negative CSCC (p < 0.001). ADC values showed a significant difference for the grade (p < 0.001) but none for the other subgroups. CONCLUSION: Both T1 mapping and DWI could stratify the CSCC histologic grade. In addition, T1 mapping and ECV measurement might provide more quantitative metrics for noninvasively predicting poor prognostic factors and aiding in preoperative risk assessment in CSCC patients.

Model-Free and Model-based Parameters Derived From CAIPIRINHA-Dixon-TWIST-VIBE DCE-MRI: Associations With Prognostic Factors and Molecular Subtypes of Invasive Ductal Breast Cancer.

BACKGROUND: CAIPIRINHA-Dixon-TWIST-VIBE (CDTV) dynamic contrast-enhanced MRI (DCE-MRI) can be used to characterize breast cancer. However, the influence of the clinicopathologic factors and molecular subtypes of invasive breast carcinoma (IDC) on the model-free and model-based parameters has not been investigated. PURPOSE: To compare model-free and model-based parameters of CDTV DCE-MRI with both clinicopathologic factors and molecular subtypes of IDC. STUDY TYPE: Prospective. POPULATION: A total of 152 patients (mean age, 52 years) with IDC including 42 luminal A, 64 luminal B, 22 human epidermal growth factor receptor-2 (HER2) positive, and 24 triple-negative subtypes. FIELD STRENGTH/SEQUENCE: A 3 T; turbo-FLASH, Dixon VIBE, and CDTV. ASSESSMENT: Model-free parameters (initial enhancement rate [IER] and maximum slope [MS]) were estimated from the time-intensity curve. The mean, minimum, maximum, and range between the minimum and maximum values of inline model-based parameters (Ktrans , kep , and ve ) were measured to assess intratumoral heterogeneity of IDC lesions. STATISTICAL TESTS: Student's t tests, Mann-Whitney U tests, Kruskal-Wallis tests, post hoc Steel-Dwass tests, and receiver operating characteristic (ROC) curves. P < 0.05 was considered significant. RESULTS: No significant differences in IER and MS values were seen among the clinicopathologic factors and molecular subtypes (Bonferroni-corrected P = 0.011-0.862, P = 0.145-0.601, respectively). The minimum kep values in HER2-positive IDC were significantly lower than those in HER2-negative IDC. The mean and range kep values were independent predictors for distinguishing the high (grade 3) and low (grade 1 or 2) nuclear grade groups according to multivariable analyses. The post hoc test showed that the kep minimum and kep range values were significantly different between luminal A and HER2-positive tumor subtypes, yielding an area-under-the-curve of 0.820. DATA CONCLUSION: Compared with the model-free parameters, inline kep related model-based parameters on CDTV DCE-MRI can be applied as a feasible tool to differentiate luminal A from HER2-positive breast cancers. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 2.

Comparison of a Deep Learning-Accelerated vs. Conventional T2-Weighted Sequence in Biparametric MRI of the Prostate.

BACKGROUND: Demand for prostate MRI is increasing, but scan times remain long even in abbreviated biparametric MRIs (bpMRI). Deep learning can be leveraged to accelerate T2-weighted imaging (T2WI). PURPOSE: To compare conventional bpMRIs (CL-bpMRI) with bpMRIs including a deep learning-accelerated T2WI (DL-bpMRI) in diagnosing prostate cancer. STUDY TYPE: Retrospective. POPULATION: Eighty consecutive men, mean age 66 years (47-84) with suspected prostate cancer or prostate cancer on active surveillance who had a prostate MRI from December 28, 2020 to April 28, 2021 were included. Follow-up included prostate biopsy or stability of prostate-specific antigen (PSA) for 1 year. FIELD STRENGTH AND SEQUENCES: A 3 T MRI. Conventional axial and coronal T2 turbo spin echo (CL-T2), 3-fold deep learning-accelerated axial and coronal T2-weighted sequence (DL-T2), diffusion weighted imaging (DWI) with b = 50 sec/mm2 , 1000 sec/mm2 , calculated b = 1500 sec/mm2 . ASSESSMENT: CL-bpMRI and DL-bpMRI including the same conventional diffusion-weighted imaging (DWI) were presented to three radiologists (blinded to acquisition method) and to a deep learning computer-assisted detection algorithm (DL-CAD). The readers evaluated image quality using a 4-point Likert scale (1 = nondiagnostic, 4 = excellent) and graded lesions using Prostate Imaging Reporting and Data System (PI-RADS) v2.1. DL-CAD identified and assigned lesions of PI-RADS 3 or greater. STATISTICAL TESTS: Quality metrics were compared using Wilcoxon signed rank test, and area under the receiver operating characteristic curve (AUC) were compared using Delong's test. SIGNIFICANCE: P = 0.05. RESULTS: Eighty men were included (age: 66 ± 9 years; 17/80 clinically significant prostate cancer). Overall image quality results by the three readers (CL-T2, DL-T2) are reader 1: 3.72 ± 0.53, 3.89 ± 0.39 (P = 0.99); reader 2: 3.33 ± 0.82, 3.31 ± 0.74 (P = 0.49); reader 3: 3.67 ± 0.63, 3.51 ± 0.62. In the patient-based analysis, the reader results of AUC are (CL-bpMRI, DL-bpMRI): reader 1: 0.77, 0.78 (P = 0.98), reader 2: 0.65, 0.66 (P = 0.99), reader 3: 0.57, 0.60 (P = 0.52). Diagnostic statistics from DL-CAD (CL-bpMRI, DL-bpMRI) are sensitivity (0.71, 0.71, P = 1.00), specificity (0.59, 0.44, P = 0.05), positive predictive value (0.23, 0.24, P = 0.25), negative predictive value (0.88, 0.88, P = 0.48). CONCLUSION: Deep learning-accelerated T2-weighted imaging may potentially be used to decrease acquisition time for bpMRI. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

Performance of free-breathing dynamic T1-weighted sequences in patients at risk of developing motion artifacts undergoing gadoxetic acid-enhanced liver MRI.

OBJECTIVES: To evaluate the recall rate and performance of free-breathing T1W dynamic imaging in patients who underwent gadoxetic acid-enhanced liver MRI. METHODS: We retrospectively reviewed patients who underwent free-breathing dynamic T1WI liver MRI using Cartesian (XD-VIBE) or self-gated radial (SG-GRASP) sequences at two institutions. Four radiologists independently reviewed the overall image quality, streak, and motion artifacts for precontrast, arterial, and portal venous phases on a 4-point scale. Hepatic observations were annotated and assessed according to LI-RADS v2018. RESULTS: In total, 360 patients were included (XD-VIBE [n = 253], SG-GRASP [n = 107]). The overall image quality of free-breathing T1WI was 3.4 ± 0.4, 3.2 ± 0.4, and 3.5 ± 0.4 for precontrast, arterial, and portal venous phases, respectively. The actual recall rate was 0.6% (2/360). The SG-GRASP group showed fewer motion artifacts and more streak artifacts than the XD-VIBE group in all phases (p < 0.001 for all). The overall image quality was not significantly different between the two sequences in arterial (3.2 ± 0.4 in both, p = 0.607) and portal venous phases (3.5 ± 0.4 in XD-VIBE, 3.4 ± 0.4 in SG-GRASP, p = 0.214). Two sequences did not show significant differences in the lesion detection rate (figure of merit, FOM: 0.67 vs. 0.68, p = 0.876) or diagnostic performance for hepatocellular carcinoma (FOM: 0.55 vs. 0.62, p = 0.105). CONCLUSIONS: Both XD-VIBE and SG-GRASP provided sufficient image quality for patients at risk of developing motion artifacts, without significant differences in image quality or the lesion detection rate between sequences. KEY POINTS: • The overall image quality of free-breathing T1-weighted images using Cartesian or radial sequences was 3.4 ± 0.4, 3.2 ± 0.4, and 3.5 ± 0.4 for precontrast, arterial, and portal venous phases, respectively. • Only 0.3% (1/360) had undiagnostic exams and the actual recall rate was 0.6% (2/360) in patients who underwent free-breathing dynamic T1WI. • The overall lesion detection rate was 0.67 without a significant difference between Cartesian and radial sequences (figure of merit: 0.67 vs. 0.68, respectively, p = 0.876).

Ultrafast DCE-MRI for discriminating pregnancy-associated breast cancer lesions from lactation related background parenchymal enhancement.

OBJECTIVE: To investigate the utility of ultrafast dynamic-contrast-enhanced (DCE) MRI in visualization and quantitative characterization of pregnancy-associated breast cancer (PABC) and its differentiation from background-parenchymal-enhancement (BPE) among lactating patients. MATERIALS AND METHODS: Twenty-nine lactating participants, including 10 PABC patients and 19 healthy controls, were scanned on 3-T MRI using a conventional DCE protocol interleaved with a golden-angle radial sparse parallel (GRASP) ultrafast sequence for the initial phase. The timing of the visualization of PABC lesions was compared to lactational BPE. Contrast-noise ratio (CNR) was compared between the ultrafast and conventional DCE sequences. The differences in each group's ultrafast-derived kinetic parameters including maximal slope (MS), time to enhancement (TTE), and area under the curve (AUC) were statistically examined using the Mann-Whitney test and receiver operator characteristic (ROC) curve analysis. RESULTS: On ultrafast MRI, breast cancer lesions enhanced earlier than BPE (p < 0.0001), enabling breast cancer visualization freed from lactation BPE. A higher CNR was found for ultrafast acquisitions vs. conventional DCE (p < 0.05). Significant differences in AUC, MS, and TTE values were found between the tumor and BPE (p < 0.05), with ROC-derived AUC of 0.86 ± 0.06, 0.82 ± 0.07, and 0.68 ± 0.08, respectively. The BPE grades of the lactating PABC patients were reduced as compared with the healthy lactating controls (p < 0.005). CONCLUSION: Ultrafast DCE MRI allows BPE-free visualization of lesions, improved tumor conspicuity, and kinetic quantification of breast cancer during lactation. Implementation of this method may assist in the utilization of breast MRI for lactating patients. CLINICAL RELEVANCE: The ultrafast sequence appears to be superior to conventional DCE MRI in the challenging evaluation of the lactating breast. Thus, supporting its possible utilization in the setting of high-risk screening during lactation and the diagnostic workup of PABC. KEY POINTS: • Differences in the enhancement slope of cancer relative to BPE allowed the optimal visualization of PABC lesions on mid-acquisitions of ultrafast DCE, in which the tumor enhanced prior to the background parenchyma. • The conspicuity of PABC lesions on top of the lactation-related BPE was increased using an ultrafast sequence as compared with conventional DCE MRI. • Ultrafast-derived maps provided further characterization and parametric contrast between PABC lesions and lactation-related BPE.

Image quality and lesion detectability of deep learning-accelerated T2-weighted Dixon imaging of the cervical spine.

OBJECTIVES: To validate the subjective image quality and lesion detectability of deep learning-accelerated Dixon (DL-Dixon) imaging of the cervical spine compared with routine Dixon imaging. MATERIALS AND METHODS: A total of 50 patients underwent sagittal routine Dixon and DL-Dixon imaging of the cervical spine. Acquisition parameters were compared and non-uniformity (NU) values were calculated. Two radiologists independently assessed the two imaging methods for subjective image quality and lesion detectability. Interreader and intermethod agreements were estimated with weighted kappa values. RESULTS: Compared with the routine Dixon imaging, the DL-Dixon imaging reduced the acquisition time by 23.76%. The NU value is slightly higher in DL-Dixon imaging (p value: 0.015). DL-Dixon imaging showed superior visibility of all four anatomical structures (spinal cord, disc margin, dorsal root ganglion, and facet joint) for both readers (p value: < 0.001 ~ 0.002). The motion artifact scores were slightly higher in the DL-Dixon images than in routine Dixon images (p value = 0.785). Intermethod agreements were almost perfect for disc herniation, facet osteoarthritis, uncovertebral arthritis, central canal stenosis (κ range: 0.830 ~ 0.980, all p values < 0.001) and substantial to almost perfect for foraminal stenosis (κ = 0.955, 0.705 for each reader). There was an improvement in the interreader agreement of foraminal stenosis by DL-Dixon images, from moderate to substantial agreement. CONCLUSION: The DLR sequence can substantially decrease the acquisition time of the Dixon sequence with subjective image quality at least as good as the conventional sequence. And no significant differences in lesion detectability were observed between the two sequence types.

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.

Deep learning-guided weighted averaging for signal dropout compensation in DWI of the liver.

PURPOSE: To develop an algorithm for the retrospective correction of signal dropout artifacts in abdominal DWI resulting from cardiac motion. METHODS: Given a set of image repetitions for a slice, a locally adaptive weighted averaging is proposed that aims to suppress the contribution of image regions affected by signal dropouts. Corresponding weight maps were estimated by a sliding-window algorithm, which analyzed signal deviations from a patch-wise reference. In order to ensure the computation of a robust reference, repetitions were filtered by a classifier that was trained to detect images corrupted by signal dropouts. The proposed method, named Deep Learning-guided Adaptive Weighted Averaging (DLAWA), was evaluated in terms of dropout suppression capability, bias reduction in the ADC, and noise characteristics. RESULTS: In the case of uniform averaging, motion-related dropouts caused signal attenuation and ADC overestimation in parts of the liver, with the left lobe being affected particularly. Both effects could be substantially mitigated by DLAWA while preventing global penalties with respect to SNR due to local signal suppression. Performing evaluations on patient data, the capability to recover lesions concealed by signal dropouts was demonstrated as well. Further, DLAWA allowed for transparent control of the trade-off between SNR and signal dropout suppression by means of a few hyperparameters. CONCLUSION: This work presents an effective and flexible method for the local compensation of signal dropouts resulting from motion and pulsation. Because DLAWA follows a retrospective approach, no changes to the acquisition are required.

Free-breathing contrast-enhanced multiphase MRI of the liver in patients with a high risk of breath-holding failure: comparison of compressed sensing-accelerated radial and Cartesian acquisition techniques.

BACKGROUND: Knowing the advantages and disadvantages of each magnetic resonance (MR) technique, would allow us to choose a sequence better suited in patients with a high risk of breath-holding failure. PURPOSE: To compare the image quality of free-breathing contrast-enhanced multiphase MR imaging (MRI) using incoherent Cartesian k-space sampling combined with a motion-resolved compressed sensing reconstruction (XD-VIBE) and Golden-Angle Radial Sparse Parallel MRI (GRASP). MATERIAL AND METHODS: A total of 67 patients were included. Overall image quality, motion artifacts, and liver edge sharpness on arterial and portal-venous phase were evaluated by two radiologists. We evaluated the signal intensity ratio between liver in the late arterial phase to aorta at peak enhancement and the detection rate of hypervascular lesions. RESULTS: Overall image quality, artifact, and liver edge sharpness scores of XD-VIBE and GRASP were not significantly different (P = 0.070-0.397). Four (reviewer 1, 12.1%) and seven patients (reviewer 2, 21.2%) received non-diagnostic quality in the XD-VIBE group whereas one patient (reviewer 2, 2.9%) received non-diagnostic quality in the GRASP group. The ratio between the aorta and liver signal for GRASP was significantly higher than that of XD-VIBE (0.32 ± 0.10 vs. 0.47 ± 0.13; P < 0.001). The hypervascular lesion detection rate of XD-VIBE (86.7%) was higher than that of GRASP (57.1%) in the arterial phase without a statistically significant difference (P = 0.081). CONCLUSION: Overall image quality of XD-VIBE and GRASP were not significantly different. More XD-VIBE examinations were rated non-diagnostic. On the other hand, the relative liver parenchymal enhancement to the aorta in the late arterial phase of GRASP was higher than that of XD-VIBE, which potentially leads to lower detectability of hypervascular lesions on arterial phase images.

T2 mapping in gadoxetic acid-enhanced MRI: utility for predicting decompensation and death in cirrhosis.

OBJECTIVES: To determine whether T2 mapping in liver MRI can predict decompensation and death in cirrhotic patients. METHODS: This retrospective study included 292 cirrhotic patients who underwent gadoxetic acid-enhanced MRI, including T1 and T2 mapping at 10-min hepatobiliary phase by using the Look-Locker and radial turbo spin-echo sequences, respectively. T1 and T2 values of the liver and spleen were measured. The association of MR parameters and serum markers with decompensation and death was investigated. Risk models combining T2Liver, serum albumin level, and Model for End-Stage Liver Disease (MELD) score were created for predicting decompensation (T2Liver, < 49.3 versus ≥ 49.3 ms) and death (< 57.4 versus ≥ 57.4 ms). RESULTS: In patients with compensated cirrhosis at baseline and in the full patient cohort, 9.6% (19 of 197) and 5.1% (15 of 292) developed decompensation and died during the mean follow-up periods of 18.7 and 19.2 months, respectively. A prolonged T2Liver (hazard ratio (HR), 2.59; 95% confidence interval (CI), 1.26, 5.31) was independently predictive of decompensation along with the serum albumin level (HR, 0.28; 95% CI, 0.12, 0.68) and MELD score (HR, 1.34; 95% CI, 1.08, 1.66). T2Liver (HR, 2.61; 95% CI, 1.19, 5.72) and serum albumin level (HR, 0.46; 95% CI, 0.19, 1.14) were independent predictors of death. The mean times to decompensation (12.9 versus 29.2 months) and death (16.5 versus 29.6 months) were significantly different between the high- and low-risk groups (p < 0.001). CONCLUSION: T2Liver from T2 mapping can predict decompensation and death in patients with cirrhosis. KEY POINTS: • Liver T2 values from the radial turbo spin-echo (TSE) T2 mapping sequence with tiered echo sharing and pseudo golden-angle (pGA) reordering were significantly higher in decompensated cirrhosis than compensated cirrhosis. • Liver T2 values from the radial TSE T2 mapping sequence with tiered echo sharing and pGA reordering can predict decompensation and death in patients with cirrhosis. • T2 mapping is recommended as part of liver MRI examinations for cirrhotic patients because it can provide a noninvasive prognostic marker for the development of decompensation and death.

Ultrafast Dynamic Contrast-Enhanced MRI Using Compressed Sensing: Associations of Early Kinetic Parameters With Prognostic Factors of Breast Cancer.

OBJECTIVE. The purpose of this study was to investigate whether early kinetic parameters derived from ultrafast dynamic contrast-enhanced MRI (DCE-MRI) using compressed sensing are associated with prognostic factors for breast cancer. MATERIALS AND METHODS. We evaluated 201 consecutive women (mean age, 54.6 years) with breast cancer (168 invasive, 33 ductal carcinoma in situ) who underwent both ultrafast DCE-MRI using compressed sensing (temporal resolution, 4.7 seconds; spatial resolution, 0.8 × 1.1 × 0.9 mm) and surgery between 2018 and 2019. Early kinetic parameters (time to enhancement [TTE] and maximum slope [MS]) were measured in breast lesions by two radiologists using a software program and were correlated with histopathologic prognostic factors. The Mann-Whitney U test and linear regression analysis were used. RESULTS. The median TTE and MS values for breast cancer were 11.9 seconds and 7.7%/s, respectively. The median MS was significantly larger in invasive cancer lesions than in ductal carcinoma in situ lesions (8.4%/s vs 4.7%/s, p < .001). In women with invasive cancer, multivariate linear regression analyses showed that a larger tumor size (> 2 cm) (p = .048) and estrogen receptor-negative status (p < .001) were significantly associated with a shorter TTE. A higher histologic grade (grade 3) (p = .01) was significantly associated with a larger MS. We observed excellent interobserver agreement between two readers in the measurements of TTE and MS (intraclass correlation coefficients, 0.943 and 0.890, respectively). CONCLUSION. Ultrafast MRI-derived early enhancement parameters, such as TTE and MS, are associated with histopathologic prognostic factors in women with breast cancer.

New parameters of ultrafast dynamic contrast-enhanced breast MRI using compressed sensing.

BACKGROUND: Ultrafast dynamic contrast-enhanced (UF-DCE) breast MRI is considered a promising method of accelerated breast MRI. However, the value of new kinetic parameters derived from UF-DCE need clinical evaluation. PURPOSE: To evaluate the diagnostic performance of the maximum slope (MS), time to enhancement (TTE), and time interval between arterial and venous visualization (AVI) derived from UF-DCE MRI using compressed sensing (CS). STUDY TYPE: Retrospective. POPULATION: Seventy-five patients with histologically proven breast lesions. The total number of analyzed lesions was 90 (61 malignant and 29 benign). FIELD STRENGTH/SEQUENCE: 3T MRI with UF-DCE MRI based on the 3D gradient-echo volumetric interpolated breath-hold examination (VIBE) sequence using incoherent k-space sampling combined with a CS reconstruction followed by conventional DCE MRI. ASSESSMENT: The diagnostic performance of the MS, TTE, AVI, and conventional kinetic analysis was analyzed and compared with histology. STATISTICAL TESTS: Wilcoxon rank sum test, receiver operating characteristic analysis. RESULTS: The MS was larger and the TTE and AVI were smaller for malignant lesions compared with benign lesions: MS: 29.3%/s and 18.4%/s (P < 0.001), TTE: 7.0 and 12.0 seconds (P < 0.001), AVI: 2.7 and 4.4 frames (P = 0.006) for malignant and benign lesions. The discriminating power of the MS (area under the curve [AUC], 0.76) was slightly better than that of conventional kinetic analysis (AUC, 0.69) and comparable to that of the TTE and AVI (AUC, 0.78 and 0.76 for TTE and AVI, respectively). Invasive lobular carcinoma had smaller MS (21.8%/s) among malignant lesions (29.3%/s). DATA CONCLUSION: The MS, TTE, and AVI can be used to evaluate breast lesions with clinical performance equivalent to that of conventional kinetic analysis. These parameters vary among histologies. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:164-174.

Application of whole-lesion histogram analysis of pharmacokinetic parameters in dynamic contrast-enhanced MRI of breast lesions with the CAIPIRINHA-Dixon-TWIST-VIBE technique.

PURPOSE: To investigate the application of whole-lesion histogram analysis of pharmacokinetic parameters for differentiating malignant from benign breast lesions on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). MATERIALS AND METHODS: In all, 92 women with 97 breast lesions (26 benign and 71 malignant lesions) were enrolled in this study. Patients underwent dynamic breast MRI at 3T using a prototypical CAIPIRINHA-Dixon-TWIST-VIBE (CDT-VIBE) sequence and a subsequent surgery or biopsy. Inflow rate of the agent between plasma and interstitium (Ktrans ), outflow rate of agent between interstitium and plasma (Kep ), extravascular space volume per unit volume of tissue (ve ) including mean value, 25th/50th/75th/90th percentiles, skewness, and kurtosis were then calculated based on the whole lesion. A single-sample Kolmogorov-Smirnov test, paired t-test, and receiver operating characteristic curve (ROC) analysis were used for statistical analysis. RESULTS: Malignant breast lesions had significantly higher Ktrans , Kep , and lower ve in mean values, 25th/50th/75th/90th percentiles, and significantly higher skewness of ve than benign breast lesions (all P < 0.05). There was no significant difference in kurtosis values between malignant and benign breast lesions (all P > 0.05). The 90th percentile of Ktrans , the 90th percentile of Kep , and the 50th percentile of ve showed the greatest areas under the ROC curve (AUC) for each pharmacokinetic parameter derived from DCE-MRI. The 90th percentile of Kep achieved the highest AUC value (0.927) among all histogram-derived values. CONCLUSION: The whole-lesion histogram analysis of pharmacokinetic parameters can improve the diagnostic accuracy of breast DCE-MRI with the CDT-VIBE technique. The 90th percentile of Kep may be the best indicator in differentiation between malignant and benign breast lesions. LEVEL OF EVIDENCE: 4 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2018;47:91-96.

Ultrafast dynamic contrast-enhanced mri of the breast using compressed sensing: breast cancer diagnosis based on separate visualization of breast arteries and veins.

PURPOSE: To evaluate the feasibility of ultrafast dynamic contrast-enhanced (UF-DCE) magnetic resonance imaging (MRI) with compressed sensing (CS) for the separate identification of breast arteries/veins and perform temporal evaluations of breast arteries and veins with a focus on the association with ipsilateral cancers. MATERIALS AND METHODS: Our Institutional Review Board approved this study with retrospective design. Twenty-five female patients who underwent UF-DCE MRI at 3T were included. UF-DCE MRI consisting of 20 continuous frames was acquired using a prototype 3D gradient-echo volumetric interpolated breath-hold sequence including a CS reconstruction: temporal resolution, 3.65 sec/frame; spatial resolution, 0.9 × 1.3 × 2.5 mm. Two readers analyzed 19 maximum intensity projection images reconstructed from subtracted images, separately identified breast arteries/veins and the earliest frame in which they were respectively visualized, and calculated the time interval between arterial and venous visualization (A-V interval) for each breast. RESULTS: In total, 49 breasts including 31 lesions (breast cancer, 16; benign lesion, 15) were identified. In 39 of the 49 breasts (breasts with cancers, 16; breasts with benign lesions, 10; breasts with no lesions, 13), both breast arteries and veins were separately identified. The A-V intervals for breasts with cancers were significantly shorter than those for breasts with benign lesions (P = 0.043) and no lesions (P = 0.007). CONCLUSION: UF-DCE MRI using CS enables the separate identification of breast arteries/veins. Temporal evaluations calculating the time interval between arterial and venous visualization might be helpful in the differentiation of ipsilateral breast cancers from benign lesions. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:97-104.