Breath-hold High-resolution T1-weighted Gradient Echo Liver MR Imaging with Compressed Sensing Obtained during the Gadoxetic Acid-enhanced Hepatobiliary Phase: Image Quality and Lesion Visibility Compared with a Standard T1-weighted Sequence

PURPOSE

To evaluate the feasibility of breath-hold (BH) high-resolution (HR) T1-weighted gradient echo hepatobiliary phase (HBP) imaging using compressed sensing (CS) in gadoxetic acid-enhanced liver MRI in comparison with standard HBP imaging using parallel imaging (PI).

METHODS

The study included 122 patients with liver tumors with hypointensity in the HBP who underwent both HR HBP imaging with CS and standard HBP imaging with PI. Two radiologists evaluated the liver edge sharpness, hepatic vessel conspicuity, bile duct conspicuity, image noise, and overall image quality, as well as the lesion conspicuity on HR and standard HBP imaging and the contrast-enhanced (CE) MR cholangiography (MRC) image quality reconstructed from HBP images. As a quantitative analysis, the SNR of the liver and the liver to lesion signal intensity ratio (LLSIR) were also determined.

RESULTS

The liver edge sharpness, hepatic vessel conspicuity, bile duct conspicuity, and overall image quality as well as the lesion conspicuity and the LLSIR on HR HBP imaging with CS were significantly higher than those on standard HBP imaging (all of P < 0.001). The image quality of CE-MRC reconstructed from HR HBP imaging with CS was also significantly higher than that from standard HBP imaging (P < 0.001). Conversely, the SNR of liver in standard HBP was significantly higher than that in HR HBP with CS (P < 0.001).

CONCLUSION

BH HR HBP imaging with CS provided an improved overall image quality, lesion conspicuity, and CE-MRC visualization when compared with standard HBP imaging without extending the acquisition time.

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.

Deep learning-based image reconstruction for the multi-arterial phase images: improvement of the image quality to assess the small hypervascular hepatic tumor on gadoxetic acid-enhanced liver MRI

PURPOSE

To evaluated the impact of a deep learning (DL)-based image reconstruction on multi-arterial-phase magnetic resonance imaging (MA-MRI) for small hypervascular hepatic masses in patients who underwent gadoxetic acid-enhanced liver MRI.

METHODS

We retrospectively enrolled 55 adult patients (aged ≥ 18 years) with small hepatic hypervascular mass (≤ 3 cm) between December 2022 and February 2023. All patients underwent MA-MRI, subsequently reconstructed with a DL-based application. Qualitative assessment with Linkert scale including motion artifact (MA), liver edge (LE), hepatic vessel clarity (HVC) and image quality (IQ) was performed. Quantitative image analysis including signal to noise ratio (SNR), contrast to noise ratio (CNR) and noise was performed.

RESULTS

On both arterial phases (APs), all qualitative parameters were significantly improved after DL-based image reconstruction. (LE on 1st AP, 1.22 vs 1.61; LE on 2nd AP, 1.21 vs 1.65; HVC on 1st AP, 1.24 vs 1.39; HVC on 2nd AP, 1.24 vs 1.44; IQ on 1st AP, 1.17 vs 1.45; IQ on 2nd AP, 1.17 vs 1.47, all p values < 0.05). The SNR, CNR and noise were significantly improved after DL-based image reconstruction. (SNR on AP1, 279.08 vs 176.14; SNR on AP2, 334.34 vs 199.24; CNR on AP1, 106.09 vs 64.14; CNR on AP2, 129.66 vs 73.73; noise on AP1, 1.51 vs 2.33; noise on AP2, 1.45 vs 2.28, all p values < 0.05).

CONCLUSIONS

Gadoxetic acid-enhanced MA-MRI with DL-based image reconstruction improved the qualitative and quantitative parameters. Despite the short acquisition time, high-quality MA-MRI is now achievable.

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.

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.

Advanced Abdominal MRI Techniques and Problem-Solving Strategies

MRI plays an important role in abdominal imaging because of its ability to detect and characterize focal lesions. However, MRI examinations have several challenges, such as comparatively long scan times and motion management through breath-holding maneuvers. Techniques for reducing scan time with acceptable image quality, such as parallel imaging, compressed sensing, and cutting-edge deep learning techniques, have been developed to enable problem-solving strategies. Additionally, free-breathing techniques for dynamic contrast-enhanced imaging, such as extra-dimensional-volumetric interpolated breath-hold examination, golden-angle radial sparse parallel, and liver acceleration volume acquisition Star, can help patients with severe dyspnea or those under sedation to undergo abdominal MRI. We aimed to present various advanced abdominal MRI techniques for reducing the scan time while maintaining image quality and free-breathing techniques for dynamic imaging and illustrate cases using the techniques mentioned above. A review of these advanced techniques can assist in the appropriate interpretation of sequences.

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.

A multiparametric approach to predict triple-negative breast cancer including parameters derived from ultrafast dynamic contrast-enhanced MRI

OBJECTIVE

Triple-negative breast cancer (TNBC) is a highly proliferative breast cancer subtype. We aimed to identify TNBC among invasive cancers presenting as masses using maximum slope (MS) and time to enhancement (TTE) measured on ultrafast (UF) DCE-MRI, ADC measured on DWI, and rim enhancement on UF DCE-MRI and early-phase DCE-MRI.

METHODS

This retrospective single-center study, between December 2015 and May 2020, included patients with breast cancer presenting as masses. Early-phase DCE-MRI was performed immediately after UF DCE-MRI. Interrater agreements were evaluated using the intraclass correlation coefficient (ICC) and Cohen's kappa. Univariate and multivariate logistic regression analyses of the MRI parameters, lesion size, and patient age were performed to predict TNBC and create a prediction model. The programmed death-ligand 1 (PD-L1) expression statuses of the patients with TNBCs were also evaluated.

RESULTS

In total, 187 women (mean age, 58 years ± 12.9 [standard deviation]) with 191 lesions (33 TNBCs) were evaluated. The ICC for MS, TTE, ADC, and lesion size were 0.95, 0.97, 0.83, and 0.99, respectively. The kappa values of rim enhancements on UF and early-phase DCE-MRI were 0.88 and 0.84, respectively. MS on UF DCE-MRI and rim enhancement on early-phase DCE-MRI remained significant parameters after multivariate analyses. The prediction model created using these significant parameters yielded an area under the curve of 0.74 (95% CI, 0.65, 0.84). The PD-L1-expressing TNBCs tended to have higher rim enhancement rates than the non-PD-L1-expressing TNBCs.

CONCLUSION

A multiparametric model using UF and early-phase DCE-MRI parameters may be a potential imaging biomarker to identify TNBCs.

CLINICAL RELEVANCE STATEMENT

Prediction of TNBC or non-TNBC at an early point of diagnosis is crucial for appropriate management. This study offers the potential of UF and early-phase DCE-MRI to offer a solution to this clinical issue.

KEY POINTS

• It is crucial to predict TNBC at an early clinical period. • Parameters on UF DCE-MRI and early-phase conventional DCE-MRI help in predicting TNBC. • Prediction of TNBC by MRI may be useful in determining appropriate clinical management.

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.

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.

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.

The Role of Native T1 and T2 Mapping Times in Identifying PD-L1 Expression and the Histological Subtype of NSCLCs

We investigated the association of T1/T2 mapping values with programmed death-ligand 1 protein (PD-L1) expression in lung cancer and their potential in distinguishing between different histological subtypes of non-small cell lung cancers (NSCLCs). Thirty-five patients diagnosed with stage III NSCLC from April 2021 to December 2022 were included. Conventional MRI sequences were acquired with a 1.5 T system. Mean T1 and T2 mapping values were computed for six manually traced ROIs on different areas of the tumor. Data were analyzed through RStudio. Correlation between T1/T2 mapping values and PD-L1 expression was studied with a Wilcoxon-Mann-Whitney test. A Kruskal-Wallis test with a post-hoc Dunn test was used to study the correlation between T1/T2 mapping values and the histological subtypes: squamocellular carcinoma (SCC), adenocarcinoma (ADK), and poorly differentiated NSCLC (PD). There was no statistically significant correlation between T1/T2 mapping values and PD-L1 expression in NSCLC. We found statistically significant differences in T1 mapping values between ADK and SCC for the periphery ROI (p-value 0.004), the core ROI (p-value 0.01), and the whole tumor ROI (p-value 0.02). No differences were found concerning the PD NSCLCs.

Usefulness of Breath-Hold Fat-Suppressed T2-Weighted Images With Deep Learning-Based Reconstruction of the Liver: Comparison to Conventional Free-Breathing Turbo Spin Echo

OBJECTIVES

The aim of this study was to evaluate the usefulness of breath-hold turbo spin echo with deep learning-based reconstruction (BH-DL-TSE) in acquiring fat-suppressed T2-weighted images (FS-T2WI) of the liver by comparing this method with conventional free-breathing turbo spin echo (FB-TSE) and breath-hold half Fourier single-shot turbo spin echo with deep learning-based reconstruction (BH-DL-HASTE).

MATERIALS AND METHODS

The study cohort comprised 111 patients with suspected liver disease who underwent 3 T magnetic resonance imaging. Fifty-eight focal solid liver lesions ≥10 mm were also evaluated. Three sets of FS-T2WI were acquired using FB-TSE, prototypical BH-DL-TSE, and prototypical BH-DL-HASTE, respectively. In the qualitative analysis, 2 radiologists evaluated the image quality using a 5-point scale. In the quantitative analysis, we calculated the lesion-to-liver signal intensity ratio (LEL-SIR). Friedman test and Dunn multiple comparison test were performed to assess differences among 3 types of FS-T2WI with respect to image quality and LEL-SIR.

RESULTS

The mean acquisition time was 4 minutes and 43 seconds ± 1 minute and 21 seconds (95% confidence interval, 4 minutes and 28 seconds to 4 minutes and 58 seconds) for FB-TSE, 40 seconds for BH-DL-TSE, and 20 seconds for BH-DL-HASTE. In the qualitative analysis, BH-DL-HASTE resulted in the fewest respiratory motion artifacts ( P < 0.0001). BH-DL-TSE and FB-TSE exhibited significantly less motion-related signal loss and clearer intrahepatic vessels than BH-DL-HASTE ( P < 0.0001). Regarding the edge sharpness of the left lobe, BH-DL-HASTE scored the highest ( P < 0.0001), and BH-DL-TSE scored higher than FB-TSE ( P = 0.0290). There were no significant differences among 3 types of FS-T2WI with respect to the edge sharpness of the right lobe ( P = 0.1290), lesion conspicuity ( P = 0.5292), and LEL-SIR ( P = 0.6026).

CONCLUSIONS

BH-DL-TSE provides a shorter acquisition time and comparable or better image quality than FB-TSE, and could replace FB-TSE in acquiring FS-T2WI of the liver. BH-DL-TSE and BH-DL-HASTE have their own advantages and may be used complementarily.

Extracellular volume fraction of the pancreas predicts glucose intolerance in patients undergoing major pancreatic surgeries

PURPOSE

Pancreatic T1 value and extracellular volume fraction (ECV) are potential imaging biomarkers for pancreatic exocrine and endocrine function. This study aims to evaluate the ability of native T1 value and ECV of the pancreas in predicting postoperative new-onset diabetes (NODM) and worsened glucose tolerance in patients undergoing major pancreatic surgeries.

METHODS

This retrospective study involved 73 patients who underwent 3 T pancreatic MRI with pre- and postcontrast T1 mapping before major pancreatic surgeries. Patients were divided into non-diabetic, pre-diabetic and diabetic groups based on their glycated hemoglobin (HbA1c) value. Preoperative native T1 value and ECV of the pancreas were compared among the three groups. The correlation of pancreatic T1 value and ECV with HbA1c was assessed by linear regression analysis, and the ability of pancreatic T1 value and ECV for predicting postoperative NODM and worsened glucose tolerance was assessed using Cox Proportional hazards regression analysis.

RESULTS

Native pancreatic T1 value and ECV were both significantly higher in diabetic patients compared to pre-diabetic/non-diabetic patients, and ECV was also significantly higher in pre-diabetic patients compared to non-diabetic patients (all p < 0.05). Both native pancreatic T1 value and ECV showed positive correlation with preoperative HbA1c value (r = 0.50 and 0.55, respectively, both p < 0.001). ECV > 30.7% was the only independent predictor for NODM (HR = 5.687, 95% CI: 1.557, 13.468, p = 0.012) and worsened glucose tolerance (HR = 6.783, 95% CI:, 1.753, 15.842, p = 0.010) after surgery.

CONCLUSIONS

Pancreatic ECV predicts the risk of postoperative NODM and worsened glucose tolerance in patients undergoing major pancreatic surgeries.

Risk factors for the recurrence of cervical cancer using MR-based T1 mapping: A pilot study

Objectives

This study aimed to identify risk factors for recurrence in patients with cervical cancer (CC) through quantitative T1 mapping.

Methods

A cohort of 107 patients histopathologically diagnosed with CC at our institution between May 2018 and April 2021 was categorized into surgical and non-surgical groups. Patients in each group were further divided into recurrence and non-recurrence subgroups depending on whether they showed recurrence or metastasis within 3 years of treatment. The longitudinal relaxation time (native T1) and apparent diffusion coefficient (ADC) value of the tumor were calculated. The differences between native T1 and ADC values of the recurrence and non-recurrence subgroups were analyzed, and receiver operating characteristic (ROC) curves were drawn for parameters with statistical differences. Logistic regression was performed for analysis of significant factors affecting CC recurrence. Recurrence-free survival rates were estimated by Kaplan–Meier analysis and compared using the log-rank test.

Results

Thirteen and 10 patients in the surgical and non-surgical groups, respectively, showed recurrence after treatment. There were significant differences in native T1 values between the recurrence and non-recurrence subgroups in the surgical and non-surgical groups (P&lt;0.05); however, there was no difference in ADC values (P&gt;0.05). The areas under the ROC curve of native T1 values for discriminating recurrence of CC after surgical and non-surgical treatment were 0.742 and 0.780, respectively. Logistic regression analysis indicated that native T1 values were risk factors for tumor recurrence in the surgical and non-surgical groups (P=0.004 and 0.040, respectively). Compared with cut-offs, recurrence-free survival curves of patients with higher native T1 values of the two groups were significantly different from those with lower ones (P=0.000 and 0.016, respectively).

Conclusion

Quantitative T1 mapping could help identify CC patients with a high risk of recurrence, supplementing information on tumor prognosis other than clinicopathological features and providing the basis for individualized treatment and follow-up schemes.

Comparison of Ultrafast Dynamic Contrast-Enhanced (DCE) MRI with Conventional DCE MRI in the Morphological Assessment of Malignant Breast Lesions

Ultrafast (UF) dynamic contrast-enhanced (DCE)-MRI offers the potential for a faster and, therefore, less expensive examination of breast lesions; however, there are no reports that have evaluated whether UF DCE-MRI can be used the same as conventional DCE-MRI in the reading of morphological information. This study evaluated the agreement in morphological information obtained from malignant breast mass lesions between UF DCE-MRI and conventional DCE-MRI. UF DCE-MRI data were obtained over the first 60 s post-contrast injection, followed by the conventional DCE images. Two readers evaluated the size and morphology of the lesions in the final phase of the UF DCE-MRI and the early phase of the conventional DCE-MRI. Inter-method agreement in morphological information was evaluated for the two readers using the intraclass correlation coefficient for size, and the kappa statistics for the morphological descriptors. Differences in the proportion of each descriptor were examined using Fisher’s test of independence. Most inter-method agreements were higher than substantial. UF DCE-MRI showed a circumscribed margin and homogeneous enhancement more often than conventional imaging. However, the percentages of readings showing the same morphology assessment between the UF DCE-MRI and conventional DCE-MRI were 71.2% (136/191) for Reader 1 and 69.1% (132/191) for Reader 2. We conclude that UF DCE-MRI may replace conventional DCE-MRI to evaluate the morphological information of malignant breast mass lesions.

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.

Motion-Corrected versus Conventional Diffusion-Weighted Magnetic Resonance Imaging of the Liver Using Non-Rigid Registration

It is challenging to overcome motion artifacts in diffusion-weighted imaging (DWI) of the abdomen. This study aimed to evaluate the image quality of motion-corrected DWI of the liver using non-rigid registration in comparison with conventional DWI (c-DWI) in patients with liver diseases. Eighty-nine patients who underwent 3-T magnetic resonance imaging (MRI) of the liver were retrospectively included. DWI was performed using c-DWI and non-rigid motion-corrected (moco) DWI was performed in addition to c-DWI. The image quality and conspicuity of hepatic focal lesions were scored using a five-point scale by two radiologists and compared between the two DWI image sets. The apparent diffusion coefficient (ADC) was measured in three regions of the liver parenchyma and in hepatic focal lesions, and compared between the two DWI image sets. Moco-DWI achieved higher scores in image quality compared to c-DWI in terms of liver edge sharpness and hepatic vessel margin delineation. The conspicuity scores of hepatic focal lesions were higher in moco-DWI. The standard deviation values of ADC of the liver parenchyma were lower in the moco-DWI than in the c-DWI. Moco-DWI using non-rigid registration showed improved overall image quality and provided more reliable ADC measurement, with an equivalent scan time, compared with c-DWI.

Water-Fat Separated T1 Mapping in the Liver and Correlation to Hepatic Fat Fraction

(1) Background: T1 mapping in magnetic resonance imaging (MRI) of the liver has been proposed to estimate liver function or to detect the stage of liver disease, among others. Thus far, the impact of intrahepatic fat on T1 quantification has only been sparsely discussed. Therefore, the aim of this study was to evaluate the potential of water-fat separated T1 mapping of the liver. (2) Methods: A total of 386 patients underwent MRI of the liver at 3 T. In addition to routine imaging techniques, a 3D variable flip angle (VFA) gradient echo technique combined with a two-point Dixon method was acquired to calculate T1 maps from an in-phase (T1_in) and water-only (T1_W) signal. The results were correlated with proton density fat fraction using multi-echo 3D gradient echo imaging (PDFF) and multi-echo single voxel spectroscopy (PDFF_MRS). Using T1_in and T1_W, a novel parameter FF_T1 was defined and compared with PDFF and PDFF_MRS. Furthermore, the value of retrospectively calculated T1_W (T1_W_calc) based on T1_in and PDFF was assessed. Wilcoxon test, Pearson correlation coefficient and Bland-Altman analysis were applied as statistical tools. (3) Results: T1_in was significantly shorter than T1_W and the difference of both T1 values was correlated with PDFF (R = 0.890). FF_T1 was significantly correlated with PDFF (R = 0.930) and PDFF_MRS (R = 0.922) and yielded only minor bias compared to both established PDFF methods (0.78 and 0.21). T1_W and T1_W_calc were also significantly correlated (R = 0.986). (4) Conclusion: T1_W acquired with a water-fat separated VFA technique allows to minimize the influence of fat on liver T1. Alternatively, T1_W can be estimated retrospectively from T1_in and PDFF, if a Dixon technique is not available for T1 mapping.

Undersampling artifact reduction for free-breathing 3D stack-of-radial MRI based on a deep adversarial learning network

PURPOSE

Stack-of-radial MRI allows free-breathing abdominal scans, however, it requires relatively long acquisition time. Undersampling reduces scan time but can cause streaking artifacts and degrade image quality. This study developed deep learning networks with adversarial loss and evaluated the performance of reducing streaking artifacts and preserving perceptual image sharpness.

METHODS

A 3D generative adversarial network (GAN) was developed for reducing streaking artifacts in stack-of-radial abdominal scans. Training and validation datasets were self-gated to 5 respiratory states to reduce motion artifacts and to effectively augment the data. The network used a combination of three loss functions to constrain the anatomy and preserve image quality: adversarial loss, mean-squared-error loss and structural similarity index loss. The performance of the network was investigated for 3-5 times undersampled data from 2 institutions. The performance of the GAN for 5 times accelerated images was compared with a 3D U-Net and evaluated using quantitative NMSE, SSIM and region of interest (ROI) measurements as well as qualitative scores of radiologists.

RESULTS

The 3D GAN showed similar NMSE (0.0657 vs. 0.0559, p = 0.5217) and significantly higher SSIM (0.841 vs. 0.798, p < 0.0001) compared to U-Net. ROI analysis showed GAN removed streaks in both the background air and the tissue and was not significantly different from the reference mean and variations. Radiologists' scores showed GAN had a significant improvement of 1.6 point (p = 0.004) on a 4-point scale in streaking score while no significant difference in sharpness score compared to the input.

CONCLUSION

3D GAN removes streaking artifacts and preserves perceptual image details.

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).

Comparison of a deep learning-accelerated T2-weighted turbo spin echo sequence and its conventional counterpart for female pelvic MRI: reduced acquisition times and improved image quality

OBJECTIVES

To investigate the feasibility of a deep learning-accelerated T2-weighted turbo spin echo (TSE) sequence (T2_DL) applied to female pelvic MRI, using standard T2-weighted TSE (T2_S) as reference.

METHODS

In total, 24 volunteers and 48 consecutive patients with benign uterine diseases were enrolled. Patients in the menstrual phase were excluded. T2_S and T2_DL sequences in three planes were performed for each participant. Quantitative image evaluation was conducted by calculating the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Image geometric distortion was evaluated by measuring the diameters in all three directions of the uterus and lesions. Qualitative image evaluation including overall image quality, artifacts, boundary sharpness of the uterine zonal layers, and lesion conspicuity were assessed by three radiologists using a 5-point Likert scale, with 5 indicating the best quality. Comparative analyses were conducted for the two sequences.

RESULTS

T2_DL resulted in a 62.7% timing reduction (1:54 min for T2_DL and 5:06 min for T2_S in axial, sagittal, and coronal imaging, respectively). Compared to T2_S, T2_DL had significantly higher SNR (p ≤ 0.001) and CNR (p ≤ 0.007), and without geometric distortion (p = 0.925-0.981). Inter-observer agreement regarding qualitative evaluation was excellent (Kendall's W > 0.75). T2_DL provided superior image quality (all p < 0.001), boundary sharpness of the uterine zonal layers (all p < 0.001), lesion conspicuity (p = 0.002, p < 0.001, and p = 0.021), and fewer artifacts (all p < 0.001) in sagittal, axial, and coronal imaging.

CONCLUSIONS

Compared with standard TSE, deep learning-accelerated T2-weighted TSE is feasible to reduce acquisition time of female pelvic MRI with significant improvement of image quality.

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.

Combined Deep Learning-based Super-Resolution and Partial Fourier Reconstruction for Gradient Echo Sequences in Abdominal MRI at 3 Tesla: Shortening Breath-Hold Time and Improving Image Sharpness and Lesion Conspicuity

RATIONALE AND OBJECTIVES

To investigate the impact of a prototypical deep learning-based super-resolution reconstruction algorithm tailored to partial Fourier acquisitions on acquisition time and image quality for abdominal T1-weighted volume-interpolated breath-hold examination (VIBE_SR) at 3 Tesla. The standard T1-weighted images were used as the reference standard (VIBE_SD).

MATERIALS AND METHODS

Patients with diverse abdominal pathologies, who underwent a clinically indicated contrast-enhanced abdominal VIBE magnetic resonance imaging at 3T between March and June 2021 were retrospectively included. Following the acquisition of the standard VIBE_SD sequences, additional images for the non-contrast, dynamic contrast-enhanced and post-contrast T1-weighted VIBE acquisition were retrospectively reconstructed using the same raw data and employing a prototypical deep learning-based super-resolution reconstruction algorithm. The algorithm was designed to enhance edge sharpness by avoiding conventional k-space filtering and to perform a partial Fourier reconstruction in the slice phase-encoding direction for a predefined asymmetric sampling ratio. In the retrospective reconstruction, the asymmetric sampling was realized by omitting acquired samples at the end of the acquisition and therefore corresponding to a shorter acquisition. Four radiologists independently analyzed the image datasets (VIBE_SR and VIBE_SD) in a blinded manner. Outcome measures were: sharpness of abdominal organs, sharpness of vessels, image contrast, noise, hepatic lesion conspicuity and size, overall image quality and diagnostic confidence. These parameters were statistically compared and interrater reliability was computed using Fleiss' Kappa and intraclass correlation coefficient (ICC). Finally, the rate of detection of hepatic lesions was documented and was statistically compared using the paired Wilcoxon test.

RESULTS

A total of 32 patients aged 59 ± 16 years (23 men (72%), 9 women (28%)) were included. For VIBE_SR, breath-hold time was significantly reduced by approximately 13.6% (VIBE_SR 11.9 ± 1.2 seconds vs. VIBE_SD: 13.9 ± 1.4 seconds, p < 0.001). All readers rated sharpness of abdominal organs, sharpness of vessels to be superior in images with VIBE_SR (p values ranged between p = 0.005 and p < 0.001). Despite reduction of acquisition time, image contrast, noise, overall image quality and diagnostic confidence were not compromised, as there was no evidence of a difference between VIBE_SR and VIBE_SD (p > 0.05). The inter-reader agreement was substantial with a Fleiss' Kappa of >0.7 in all contrast phases. A total of 13 hepatic lesions were analyzed. The four readers observed a superior lesion conspicuity in VIBE_SR than in VIBE_SD (p values ranged between p = 0.046 and p < 0.001). In terms of lesion size, there was no significant difference between VIBE_SD and VIBE_SR for all readers. Finally, there was an excellent inter-reader agreement regarding lesion size (ICC > 0.9). For all readers, no statistically significant difference was observed regarding detection of hepatic lesions between VIBE_SD and VIBE_SR.

CONCLUSION

The deep learning-based super-resolution reconstruction with partial Fourier in the slice phase-encoding direction enabled a reduction of breath-hold time and improved image sharpness and lesion conspicuity in T1-weighted gradient echo sequences in abdominal magnetic resonance imaging at 3 Tesla. Faster acquisition time without compromising image quality or diagnostic confidence was possible by using this deep learning-based reconstruction technique.

Native T1 mapping for differentiating the histopathologic type, grade, and stage of rectal adenocarcinoma: a pilot study

Background

Previous studies have indicated that T1 relaxation time could be utilized for the analysis of tissue characteristics. T1 mapping technology has been gradually used on research of body tumor. In this study, the application of native T1 relaxation time for differentiating the histopathologic type, grade, and stage of rectal adenocarcinoma was investigated.

Methods

One hundred and twenty patients with pathologically confirmed rectal adenocarcinoma were retrospectively evaluated. All patients underwent high-resolution anatomical magnetic resonance imaging (MRI), diffusion-weighted imaging (DWI), and T1 mapping sequences. Parameters of T1 relaxation time and apparent diffusion coefficient (ADC) were measured between the different groups. The diagnostic power was evaluated though the receiver operating characteristic (ROC) curve.

Results

The T1 and ADC values varied significantly between rectal mucinous adenocarcinoma (MC) and non-mucinous rectal adenocarcinoma (AC) ([1986.1 ± 163.3 ms] vs. [1562.3 ± 244.2 ms] and [1.38 ± 0.23 × 10⁻³mm²/s] vs. [1.03 ± 0.15 × 10⁻³mm²/s], respectively; P < 0.001). In the AC group, T1 relaxation time were significantly different between the low- and high-grade adenocarcinoma cases ([1508.7 ± 188.6 ms] vs. [1806.5 ± 317.5 ms], P < 0.001), while no differences were apparent in the ADC values ([1.03 ± 0.14 × 10⁻³mm²/s] vs. [1.04 ± 0.18 × 10⁻³mm²/s], P > 0.05). No significant differences in T1 and ADC values were identified between the different T and N stage groups for both MC and AC (all P > 0.05).

Conclusions

Native T1 relaxation time can be used to discriminate MC from AC. The T1 relaxation time was helpful for differentiating the low- and high-grade of AC.

Fast T2-weighted liver MRI: Image quality and solid focal lesions conspicuity using a deep learning accelerated single breath-hold HASTE fat-suppressed sequence

PURPOSE

Acceleration of MRI acquisitions and especially of T2-weighted sequences is essential to reduce the duration of MRI examinations but also kinetic artifacts in liver imaging. The purpose of this study was to compare the acquisition time and the image quality of a single-shot fat-suppressed turbo spin-echo (TSE) T2-weighted sequence with deep learning reconstruction (HASTE_DL) with that of a fat-suppressed T2-weighted BLADE TSE sequence in patients with focal liver lesions.

MATERIALS AND METHODS

Ninety-five patients (52 men, 43 women; mean age: 61 ± 14 [SD]; age range: 28-87 years) with 42 focal liver lesions (17 hepatocellular carcinomas, 10 sarcoidosis lesions, 9 myeloma lesions, 3 liver metastases and 3 focal nodular hyperplasias) who underwent liver MRI at 1.5 T including HASTE_DL and BLADE sequences were retrospectively included. Overall image quality, noise level in the liver, lesion conspicuity and sharpness of liver lesion contours were assessed by two independent readers. Liver signal-to-noise ratio (SNR) and lesion contrast-to-noise ratio (CNR) were measured and compared between the two sequences, as well as the mean duration of the sequences (Student t-test or Wilcoxon test for paired data).

RESULTS

Median overall quality on HASTE_DL images (3; IQR: 3, 3) was significantly greater than that on BLADE images (2; IQR: 1, 3) (P < 0.001). Median noise level in the liver on HASTE_DL images (0; IQR: 0, 0.5) was significantly lower than that on BLADE images (1; IQR: 1, 2) (P < 0.001). On HASTE_DL images, mean liver SNR (107.3 ± 39.7 [SD]) and mean focal liver lesion CNR (87.0 ± 76.6 [SD]) were significantly greater than those on BLADE images (67.1 ± 23.8 [SD], P < 0.001 and 48.6 ± 43.9 [SD], P = 0.027, respectively). Acquisition time was significantly shorter with the HASTE_DL sequence (18 ± [0] s; range: 18-18 s) compared to BLADE sequence (152 ± 47 [SD] s; range: 87-263 s) (P < 0.001).

CONCLUSION

By comparison with the BLADE sequence, HASTE_DL sequence significantly reduces acquisition time while improving image quality, liver SNR and focal liver lesions CNR.

Preliminary results of abdominal simultaneous multi-slice accelerated diffusion-weighted imaging with motion-correction in patients with cystic fibrosis and impaired compliance

OBJECTIVES

The aim of this prospective study was to compare scan time, image quality, signal-to-noise Ratio (SNR), and apparent diffusion coefficient (ADC) values of simultaneous multi-slice accelerated diffusion-weighted imaging with motion-correction (DWI SMS Moco) to standard diffusion-weighted imaging (sDWI) in free-breathing abdominal magnetic resonance imaging (MRI) in pediatric and young adult patients with cystic fibrosis (CF).

MATERIAL AND METHODS

16 patients (7 male and 9 female, 12-41 years old) with CF were examined prospectively in a single-center from November 2020 to March 2021 on a 1.5 Tesla clinical MR scanner. The characteristics of overall image quality and delimitability of mesenteric lymph nodes were evaluated using a 5-point Likert scale by two experienced pediatric radiologists independently from each other. Quantitative parameters with SNR and ADC values were assessed in 8 different locations and compared using a Wilcoxon signed-rank test.

RESULTS

The acquisition time for DWI SMS Moco was 32% shorter than for sDWI. Regarding quality comparison, overall image quality and delimitability of mesenteric lymph nodes were significant higher in DWI SMS Moco (p ≤ 0.05 for both readers). The readers preferred DWI SMS Moco to sDWI in all cases (16/16). Mean SNR values from DWI SMS Moco and sDWI were similar in 7 from 8 locations. The ADC values showed no significant difference between DWI SMS Moco and sDWI in any of the evaluated locations (p > 0.05).

CONCLUSIONS

The DWI SMS Moco improves overall image quality and delimitability of mesenteric lymph nodes compared to sDWI with similar SNR and ADC values and a distinguished reduction of scan time in free-breathing by one third. We conclude that MRI with DWI SMS Moco could be helpful in monitoring the effect of the high-efficiency modulator (HEM) therapy in cystic fibrosis (CF) patients homozygous or heterozygous for F508del in the abdomen.

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.

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.

Extracellular volume fraction with MRI: As an alternative predictive biomarker to dynamic contrast-enhanced MRI for chemotherapy response of pancreatic ductal adenocarcinoma

PURPOSE

To assess the feasibility of extracellular volume (ECV) fraction determined with equilibrium contrast-enhanced MRI for prediction of treatment response to chemotherapy in pancreatic ductal adenocarcinoma (PDAC) in comparison with dynamic contrast-enhanced MRI (DCE-MRI), and to clarify the association between ECV fraction and DCE-MRI-derived pharmacokinetic parameters.

METHODS

This retrospective study included 58 consecutive patients with histologically confirmed PDAC who underwent DCE-MRI before systemic chemotherapy. Tumor pharmacokinetic parameters, including the volume transfer coefficient (K^trans), rate constant (k_ep), and extracellular extravascular volume fraction (v_e) of DCE-MRI, and ECV fraction determined with equilibrium contrast-enhanced MRI were compared between the response and non-response groups. The correlation of tumor ECV fraction with each DCE-MRI-derived pharmacokinetic parameter was examined using Spearman's rank correlation coefficient.

RESULTS

Tumor K^trans, v_e, and ECV fraction were significantly higher in the response group than in the non-response group (all, P < 0.001), whereas no significant difference was found in k_ep (P = 0.119). Tumor ECV fraction showed the highest area under receiver operating characteristic curve of 0.918, with a sensitivity of 89.3%, specificity of 90.0%, and accuracy of 89.7% (cut off, >37.6%). The ECV fraction showed a significant positive correlation with K^trans (Spearman's coefficient = 0.66, P < 0.001) and v_e (Spearman's coefficient = 0.79, P < 0.001).

CONCLUSIONS

ECV fraction determined with equilibrium contrast-enhanced MRI was as useful as DCE-MRI-derived pharmacokinetic parameters for predicting treatment response to chemotherapy in patients with PDAC.

Consistency of Pituitary Adenoma: Prediction by Pharmacokinetic Dynamic Contrast-Enhanced MRI and Comparison with Histologic Collagen Content

Simple Summary

Transsphenoidal resection of hard pituitary adenomas have a particularly high risk of residual tumor and complications. Therefore, prediction of tumor consistency is valuable for planning pituitary adenoma surgery. We prospectively examined whether quantitative pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is useful for predicting consistency of pituitary adenoma in 49 participants. We found that the measure of volume of extravascular extracellular space per unit volume of tissue derived from DCE-MRI could predict the consistency of pituitary adenomas. Furthermore, the volume of extravascular extracellular space per unit volume of tissue was significantly positively correlated with histopathologic collagen content of the adenoma. Our results suggest that volume of extravascular extracellular space per unit volume of tissue derived from quantitative pharmacokinetic analysis of DCE-MRI has a predictive value for consistency of pituitary adenomas.

Abstract

Prediction of tumor consistency is valuable for planning transsphenoidal surgery for pituitary adenoma. A prospective study was conducted involving 49 participants with pituitary adenoma to determine whether quantitative pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is useful for predicting consistency of adenomas. Pharmacokinetic parameters in the adenomas including volume of extravascular extracellular space (EES) per unit volume of tissue (v_e), blood plasma volume per unit volume of tissue (v_p), volume transfer constant between blood plasma and EES (K^trans), and rate constant between EES and blood plasma (k_ep) were obtained. The pharmacokinetic parameters and the histologic percentage of collagen content (PCC) were compared between soft and hard adenomas using Mann–Whitney U test. Pearson’s correlation coefficient was used to correlate pharmacokinetic parameters with PCC. Hard adenomas showed significantly higher PCC (44.08 ± 15.14% vs. 6.62 ± 3.47%, p < 0.01), v_e (0.332 ± 0.124% vs. 0.221 ± 0.104%, p < 0.01), and K^trans (0.775 ± 0.401/min vs. 0.601 ± 0.612/min, p = 0.02) than soft adenomas. Moreover, a significant positive correlation was found between v_e and PCC (r = 0.601, p < 0.01). The v_e derived using DCE-MRI may have predictive value for consistency of pituitary adenoma.

Accelerated T2-Weighted TSE Imaging of the Prostate Using Deep Learning Image Reconstruction: A Prospective Comparison with Standard T2-Weighted TSE Imaging

Multiparametric MRI (mpMRI) of the prostate has become the standard of care in prostate cancer evaluation. Recently, deep learning image reconstruction (DLR) methods have been introduced with promising results regarding scan acceleration. Therefore, the aim of this study was to investigate the impact of deep learning image reconstruction (DLR) in a shortened acquisition process of T2-weighted TSE imaging, regarding the image quality and diagnostic confidence, as well as PI-RADS and T2 scoring, as compared to standard T2 TSE imaging. Sixty patients undergoing 3T mpMRI for the evaluation of prostate cancer were prospectively enrolled in this institutional review board-approved study between October 2020 and March 2021. After the acquisition of standard T2 TSE imaging (T2_S), the novel T2 TSE sequence with DLR (T2_DLR) was applied in three planes. Overall, the acquisition time for T2_S resulted in 10:21 min versus 3:50 min for T2_DLR. The image evaluation was performed by two radiologists independently using a Likert scale ranging from 1-4 (4 best) applying the following criteria: noise levels, artifacts, overall image quality, diagnostic confidence, and lesion conspicuity. Additionally, T2 and PI-RADS scoring were performed. The mean patient age was 69 ± 9 years (range, 49-85 years). The noise levels and the extent of the artifacts were evaluated to be significantly improved in T2_DLR versus T2_S by both readers (p < 0.05). Overall image quality was also evaluated to be superior in T2_DLR versus T2_S in all three acquisition planes (p = 0.005-<0.001). Both readers evaluated the item lesion conspicuity to be superior in T2_DLR with a median of 4 versus a median of 3 in T2_S (p = 0.001 and <0.001, respectively). T2-weighted TSE imaging of the prostate in three planes with an acquisition time reduction of more than 60% including DLR is feasible with a significant improvement of image quality.

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."

Effect of hepatic steatosis on native T1 mapping of 3T magnetic resonance imaging in the assessment of T1 values for patients with non-alcoholic fatty liver disease

PURPOSE

This study investigated whether T1 values in native T1 mapping of 3T magnetic resonance imaging (MRI) of the liver were affected by the fatty component.

METHODS

This prospective study involved 340 participants from a population-based cohort study between May 8, 2018 and August 8, 2019. Data obtained included: (1) hepatic stiffness according to magnetic resonance elastography (MRE); (2) T1 value according to T1 mapping; (3) fat fraction and iron concentration from multi-echo Dixon; and (4) clinical indices of hepatic steatosis including body mass index, waist circumference, history of diabetes, aspartate aminotransferase, alanine aminotransferase, gamma-glutamyl transpeptidase, and triglycerides. The correlations between T1 value and fat fraction, and between T1 value and liver stiffness were assessed using Pearson's correlation coefficient. The independent two-sample t-test was used to evaluate the differences in T1 values according to the presence or absence of hepatic steatosis, and the one-way analysis of variance was used to evaluate the difference in T1 value by grading of hepatic steatosis according to MRI-based proton density fat fraction (PDFF). In addition, univariate and multivariate linear regression analyses were performed to determine whether other variables influenced the T1 value.

RESULTS

T1 value showed a positive correlation with the fat fraction obtained from PDFF (r = 0.615, P < 0.001) and with the liver stiffness obtained from MRE (r = 0.370, P < 0.001). Regardless of the evaluation method, the T1 value was significantly increased in subjects with hepatic steatosis (P < 0.001). When comparing hepatic steatosis grades based on MRI-PDFF, the mean T1 values were significantly different in all grades, and the T1 value tended to increase as the grade increased (P < 0.001, P for trend <0.001). On multiple linear regression analysis, the T1 value was influenced by MRI-PDFF, calculated liver iron concentration, liver stiffness, and serum aspartate aminotransferase level.

CONCLUSION

The T1 value obtained by current T1 mapping of 3T MRI was affected by the liver fat component and several other factors such as liver stiffness, iron concentration, and inflammation.

Simultaneous multi-slice accelerated diffusion-weighted imaging with higher spatial resolution for patients with liver metastases from neuroendocrine tumours

AIM

To evaluate the imaging characteristics of simultaneous multi-slice (SMS) accelerated diffusion-weighted imaging (DWI) with decreased section thickness, with and without motion correction, in comparison to conventional DWI (cDWI) for the detection of lesions in patients with neuroendocrine tumour (NET) liver metastases.

MATERIALS AND METHODS

Fifteen patients with NET liver metastases underwent cDWI (section thickness [SL]=4 mm) and SMS-DWI (SL=2 mm). Non-linear motion-corrected (Moco)-SMS-DWI was generated in addition to the original series. Qualitative imaging characteristics (five-point Likert scale), the number of high signal lesions, and the detectability and delineation of lesions were evaluated and compared using the Friedman and the Dunn-Bonferroni tests. The test-retest variability (TRV) of the cDWI and SMS-DWI techniques was investigated among 11 healthy volunteers who underwent cDWI (SL=4 mm) and SMS-DWI (SL=4 mm) twice. The Friedman and the Dunn-Bonferroni post-hoc tests were used to compare the mean apparent diffusion coefficient (ADC) and the TRV in different liver regions between the three series.

RESULTS

Moco-SMS-DWI demonstrated significantly superior overall image quality (p<0.001) with significantly fewer artefacts (p=0.003) than cDWI. The number of lesions detected by cDWI, SMS-DWI, and Moco-SMS-DWI were 348, 504, and 523, respectively. The detectability and delineation of the lesions and the ADC values were significantly higher on the SMS-DWI and Moco-SMS-DWI images than on the cDWI images (all p<0.001). Moco-SMS-DWI showed significantly higher TRV than cDWI in regions near the liver edge (p=0.018).

CONCLUSIONS

SMS-DWI achieves higher spatial resolution than cDWI within the same acquisition time, detects more lesions, and provides better lesion delineation. By applying motion correction, the TRV of DWI could be enhanced in regions near the liver edge.

Rapid Imaging: Recent Advances in Abdominal MRI for Reducing Acquisition Time and Its Clinical Applications

Magnetic resonance imaging (MRI) plays an important role in abdominal imaging. The high contrast resolution offered by MRI provides better lesion detection and its capacity to provide multiparametric images facilitates lesion characterization more effectively than computed tomography. However, the relatively long acquisition time of MRI often detrimentally affects the image quality and limits its accessibility. Recent developments have addressed these drawbacks. Specifically, multiphasic acquisition of contrast-enhanced MRI, free-breathing dynamic MRI using compressed sensing technique, simultaneous multi-slice acquisition for diffusion-weighted imaging, and breath-hold three-dimensional magnetic resonance cholangiopancreatography are recent notable advances in this field. This review explores the aforementioned state-of-the-art techniques by focusing on their clinical applications and potential benefits, as well as their likely future direction.

Background parenchymal enhancement and its effect on lesion detectability in ultrafast dynamic contrast-enhanced MRI

PURPOSE

Background parenchymal enhancement (BPE) often affects interpretation of dynamic contrast-enhanced (DCE) MRI. There is limited evidence that reduced BPE is a feature of ultrafast DCE (UF-DCE) MRI. We aimed to evaluate the effect of BPE levels on lesion detectability on UF-DCE MRI in comparison with conventional DCE MRI.

METHOD

MRIs of 70 patients with histologically proven breast lesions were retrospectively evaluated. The total number of analyzed lesions was 84 (56 malignant and 28 benign). Using 3 T MRI, 20 phases of UF-DCE MRI based on the three-dimensional gradient-echo VIBE sequence combined with a compressed sensing reconstruction were acquired followed by conventional DCE MRI. Three maximum intensity projection (MIP) images were generated from the 12th phase, the 20th phase of UF-DCE MRI and the initial phase of conventional DCE MRI. Two radiologists independently evaluated the degree of BPE and lesion detectability of the three MIP images for each breast with histologically confirmed lesions. The degree of BPE was scored on a four-point scale and lesion detectability (conspicuity and confidence levels) was scored on a three-point scale. Data were analyzed using the Wilcoxon signed-rank test with Bonferroni correction.

RESULTS

BPE was lower on UF-DCE MRI than on conventional DCE MRI. Lesion detectability was higher on UF-DCE MRI among patients with higher BPE on conventional DCE MRI or premenopausal women.

CONCLUSIONS

Images with lower BPE can be achieved using UF-DCE MRI and may be advantageous when assessing breast lesions among patients with higher BPE or premenopausal women.

Quantitative pharmacokinetic analysis of high-temporal-resolution dynamic contrast-enhanced MRI to differentiate the normal-appearing pituitary gland from pituitary macroadenoma

PURPOSE

To evaluate the usefulness of high-temporal-resolution dynamic contrast-enhanced (DCE) MRI and quantitative pharmacokinetic analysis to differentiate the normal-appearing pituitary gland from a pituitary macroadenoma.

MATERIALS AND METHODS

Twenty-seven patients with macroadenomas underwent preoperative DCE-MRI with a temporal resolution of 5 s using compressed sensing to obtain pharmacokinetic parameters. Two independent observers localized the normal-appearing pituitary gland on post-contrast T1-weighted images before and after referring to the corresponding K^trans maps. Agreements between the localizations and intraoperative findings were evaluated using the kappa statistics. The Mann-Whitney U test was used to compare the pharmacokinetic parameters of the normal-appearing pituitary gland and adenoma.

RESULTS

For both observers, the agreement between the MRI-based localization and the intraoperative findings increased after referring to the K^trans maps (observer 1, 0.930-1; observer 2, 0.636-0.855). The normal-appearing pituitary gland had significantly higher K^trans [/min] (1.50 ± 0.80 vs 0.58 ± 0.49, P < 0.0001), k_ep [/min] (3.19 ± 1.29 vs 2.15 ± 1.18, P = 0.0049), and v_e (0.43 ± 0.15 vs 0.25 ± 0.17, P = 0.0003) than adenoma.

CONCLUSION

High-temporal-resolution DCE-MRI and quantitative pharmacokinetic analysis help accurately localize the normal-appearing pituitary gland in patients with macroadenomas. The normal-appearing pituitary gland was characterized by higher K^trans, k_ep, and v_e than macroadenoma. Dynamic contrast-enhanced MRI with high-temporal-resolution using compressed sensing was used for quantitative pharmacokinetic analysis of pituitary macroadenomas. An observer study, the use of K^trans maps improved accuracy in localizing the normal-appearing pituitary gland. As compared to an adenoma, the normal-appearing pituitary gland had significantly higher K^trans, k_ep, and v_e values.

A Comparison between 6-point Dixon MRI and MR Spectroscopy to Quantify Muscle Fat in the Thigh of Subjects with Sarcopenia

BACKGROUND

Changes in muscle fat composition as for example observed in sarcopenia, affect physical performance and muscular function, like strength and power.

OBJECTIVES

The purpose of this study was to compare 6-point Dixon magnetic resonance imaging and multi-echo magnetic resonance spectroscopy sequences to quantify muscle fat. Setting, participants and measurements: Two groups were recruited (G1: 23 healthy young men (28 ± 4 years), G2: 56 men with sarcopenia (80 ± 5 years)). Proton density fat fraction was measured with a 6-point product and a 6-point prototype Dixon sequence in the left thigh muscle and with a high-speed multi-echo T2*-corrected H1 magnetic resonance spectroscopy sequence within the semitendinosus muscle of the left thigh. To evaluate the comparability among the different methods, Bland-Altman and linear regression analyses of the proton density fat fraction results were performed.

RESULTS

Mean differences ± 1.96 * standard deviation between spectroscopy and 6pt Dixon sequences were 1.9 ± 3.3% and 1.5 ± 3.6% for the product and prototype sequences, respectively. High correlations were measured between the proton density fat fraction results of the 6-point Dixon sequences and spectroscopy (R = 0.95 for the product sequence and R = 0.97 for the prototype sequence).

CONCLUSIONS

Dixon imaging and spectroscopy sequences show comparable accuracy for fat measurements in the thigh. Spectroscopy is a local measurement, whereas Dixon sequences provide maps of the fat distribution. The high correlations of the 6-point Dixon sequences with spectroscopy support their clinical use. They provide higher spatial resolution than spectroscopy, but are not suitable for a more complicated spectral analysis to separate extra- and intramyocellular lipids.

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.

Impact of the Number of Iterations in Compressed Sensing Reconstruction on Ultrafast Dynamic Contrast-enhanced Breast MR Imaging

Purpose:

To assess the impact of the number of iterations of compressed sensing (CS) reconstruction on the kinetic parameters and image quality in dynamic contrast-enhanced (DCE)-MRI of the breast, with prospectively undersampled CS-accelerated scans.

Materials and Methods:

Breast examinations including ultrafast DCE-MRI using CS were conducted for 21 patients. Images were reconstructed with different numbers of iterations. The peak enhancement ratio of the aorta and wash-in slope, initial area under the curve, and K^trans of the breast lesions were measured. The root mean square error and structural similarity between the images using 50 iterations and images with a lower number of iterations were evaluated as criterion for quantitative image evaluation.

Results:

Using an insufficient number of iterations, the contrast-enhanced effect was highly underestimated. In all semi-quantitative parameters, the number of iterations that stabilized the parameters in malignant lesions was higher than that in benign lesions. At least 15 iterations were needed for semi-quantitative parameters. For K^trans, there were no significant differences between 10 and 50 iterations in both malignant and benign lesions.

Conclusion:

The kinetic parameters using ultrafast DCE-MRI with CS are affected by the number of iterations, especially in malignant lesions. However, if the images are reconstructed with an adequate number of iterations, ultrafast DCE-MRI with CS can be a powerful technique having high temporal and spatial resolution.

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 (K^trans ), outflow rate of agent between interstitium and plasma (K_ep ), extravascular space volume per unit volume of tissue (v_e ) 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 K^trans , K_ep , and lower v_e in mean values, 25th/50th/75th/90th percentiles, and significantly higher skewness of v_e 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 K^trans , the 90th percentile of K_ep , and the 50th percentile of v_e showed the greatest areas under the ROC curve (AUC) for each pharmacokinetic parameter derived from DCE-MRI. The 90th percentile of K_ep 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 K_ep 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.