Diffusion-weighted imaging of the abdomen using echo planar imaging with compressed SENSE: Feasibility, image quality, and ADC value evaluation

CT/MRI technical pitfalls for diagnosis and treatment response assessment using LI-RADS and how to optimize

Hepatocellular carcinoma (HCC), the most common primary liver cancer, is a significant global health burden. Accurate imaging is crucial for diagnosis and treatment response assessment, often eliminating the need for biopsy. The Liver Imaging Reporting and Data System (LI-RADS) standardizes the interpretation and reporting of liver imaging for diagnosis and treatment response assessment, categorizing observations using defined categories that are based on the probability of malignancy or post-treatment tumor viability. Optimized imaging protocols are essential for accurate visualization and characterization of liver findings by LI-RADS. Common technical pitfalls, such as suboptimal postcontrast phase timing, and MRI-specific challenges like subtraction misregistration artifacts, can significantly reduce image quality and diagnostic accuracy. The use of hepatobiliary contrast agents introduces additional challenges including arterial phase degradation and suboptimal uptake in advanced cirrhosis. This review provides radiologists with comprehensive insights into the technical aspects of liver imaging for LI-RADS. We discuss common pitfalls encountered in routine clinical practice and offer practical solutions to optimize imaging techniques. We also highlight technical advances in liver imaging, including multi-arterial MR acquisition and compressed sensing. By understanding and addressing these technical aspects, radiologists can improve accuracy and confidence in the diagnosis and treatment response assessment for hepatocellular carcinoma.

Accelerated diffusion-weighted imaging of the prostate employing echo planar imaging with compressed SENSE based reconstruction

Aim was to evaluate accelerated diffusion-weighted imaging (DWI) of the prostate using echo planar imaging with compressed SENSE based reconstruction (EPICS) and assess its performance in comparison to conventional DWI with parallel imaging. In this single-center, prospective study, 35 men with clinically suspected prostate cancer underwent prostate MRI at 3T. In each patient, two different DWI sequences, one with 3 b-values (b = 100, 400, 800s/mm²) for ADC-calculation and one with b = 1500s/mm², were acquired with conventional SENSE and with EPICS. Quantitative evaluation was done by regions-of-interest (ROIs) analysis of prostate lesions and normal appearing peripheral zones (PZ). Apparent contrast-to-noise (aCNR) and apparent signal-to-noise ratios (aSNR) were calculated. Mean ADC and coefficient of variation (CV) of ADC were compared. For qualitative assessment, artifacts, lesion conspicuity, and overall image quality were rated using a 5-point-Likert-scale (1: nondiagnostic to 5: excellent). Additionally, the Prostate Imaging Reporting and Data System (PIRADS 2.1) was rated for DWI. The average total scan time reduction with EPICS was 43%. Quantitative analysis showed no significant differences between conventional SENSE and EPICS, neither for aSNRLesion (e.g. b1500conv: 24.37 ± 10.28 vs. b1500EPICS: 24.08 ± 12.2; p = 0.98) and aCNRLesion (e.g. b1500conv:9.53 ± 7.22 vs. b1500EPICS:8.88 ± 6.16; p = 0.55) nor for aSNRPZ (e.g. b1500conv:15.18 ± 6.48 vs. b1500EPICS: 15 ± 7.4; p = 0.94). Rating of artifacts, lesion conspicuity, overall image quality and PIRADS-scores yielded comparable results for the two techniques (e.g. lesion conspicuity for ADCconv: 4(2-5) vs. ADCEPICS 4(2-5); p = 0.99 and for b1500conv: 4(2-5) vs. b1500EPICS 4(2-5); p = 0.25). Overall, accelerated DWI of the prostate using EPICS significantly reduced acquisition time without compromising image quality compared to conventional DWI.

Exploratory high b value diffusion-weighted MR for quantitative differentiation of ileocecal inflammatory conditions and tumors

OBJECTIVES

To explore the quantitative analysis of high b value (2000 s/mm2) diffusion-weighted imaging (DWI) for the differentiation of ileocecal inflammatory conditions and tumors, compared with conventional b value (800 s/mm2) DWI.

METHODS

Sixty-six patients with 30 tumors and 36 inflammatory conditions underwent MR enterography with conventional and high b values DWI. Quantitative apparent diffusion coefficient (ADC) values and signal intensity ratios (SIRs) of lesions of the psoas muscle were measured from the two b value DWIs. The receiver operating characteristic (ROC) curve was applied to determine the diagnostic value of ADC and SIR for differentiating tumors from inflammatory conditions.

RESULTS

The ADC values of tumors were significantly lower than those of inflammatory conditions in 800 s/mm2 (p = 0.001) and 2000 s/mm2 (p < 0.001) DWI. In addition, tumors exhibited significantly higher SIR values compared to inflammatory conditions (p < 0.001 in 800 s/mm2 and 2000 s/mm2 DWI). Areas under the curve (AUC) of ADC and SIR derived from high b value (0.828 for ADC, 0.947 for SIR) were superior to those from conventional b value DWI (0.731 and 0.849, respectively). Compared to ADC, SIR values achieved better AUCs in both two b values DWI.

CONCLUSIONS

Quantitative ADC values and SIR could be used as non-invasive tools to distinguish ileocecal tumors from inflammatory conditions. The use of high b value DWI would improve this ability. Furthermore, SIR obtained from high b value DWI was the most promising quantitative parameter.

CRITICAL RELEVANCE STATEMENT

This study indicated that quantitative DWI parameters might be applied as non-invasive imaging biomarkers for distinguishing bowel tumors from inflammatory conditions. The SIR from high b value DWI could improve the differentiation, providing invaluable information for establishing appropriate therapeutic strategies.

KEY POINTS

Differentiation between bowel inflammatory conditions and tumors is still a dilemma. Quantitative DWI contributed to distinguishing ileocecal tumors from inflammatory conditions. SIR from DWI is a promising parameter for differentiating these pathologies.

Deep Learning-Based Super-Resolution Reconstruction on Undersampled Brain Diffusion-Weighted MRI for Infarction Stroke: A Comparison to Conventional Iterative Reconstruction

BACKGROUND AND PURPOSE

DWI is crucial for detecting infarction stroke. However, its spatial resolution is often limited, hindering accurate lesion visualization. Our aim was to evaluate the image quality and diagnostic confidence of deep learning (DL)-based super-resolution reconstruction for brain DWI of infarction stroke.

MATERIALS AND METHODS

This retrospective study enrolled 114 consecutive participants who underwent brain DWI. The DWI images were reconstructed with 2 schemes: 1) DL-based super-resolution reconstruction (DWIDL); and 2) conventional compressed sensing reconstruction (DWICS). Qualitative image analysis included overall image quality, lesion conspicuity, and diagnostic confidence in infarction stroke of different lesion sizes. Quantitative image quality assessments were performed by measurements of SNR, contrast-to-noise ratio (CNR), ADC, and edge rise distance. Group comparisons were conducted by using a paired t test for normally distributed data and the Wilcoxon test for non-normally distributed data. The overall agreement between readers for qualitative ratings was assessed by using the Cohen κ coefficient. A P value less than .05 was considered statistically significant.

RESULTS

A total of 114 DWI examinations constituted the study cohort. For the qualitative assessment, overall image quality, lesion conspicuity, and diagnostic confidence in infarction stroke lesions (lesion size <1.5 cm) improved by DWIDL compared with DWICS (all P < .001). For the quantitative analysis, edge rise distance of DWIDL was reduced compared with that of DWICS (P < .001), and no significant difference in SNR, CNR, and ADC values (all P > .05).

CONCLUSIONS

Compared with the conventional compressed sensing reconstruction, the DL-based super-resolution reconstruction demonstrated superior image quality and was feasible for achieving higher diagnostic confidence in infarction stroke.

Second-Order Motion-Compensated Echo-Planar Cardiac Diffusion-Weighted MRI: Usefulness of Compressed Sensitivity Encoding

BACKGROUND

Cardiac diffusion-weighted imaging (DWI) using second-order motion-compensated spin echo (M2C) can provide noninvasive in-vivo microstructural assessment, but limited by relatively low signal-to-noise ratio (SNR). Echo-planar imaging (EPI) with compressed sensitivity encoding (EPICS) could address these issues.

PURPOSE

To combine M2C DWI and EPCIS (M2C EPICS DWI), and compare image quality for M2C DWI.

STUDY TYPE

Prospective.

POPULATION

Ten ex-vivo hearts, 10 healthy volunteers (females, 5 [50%]; mean ± SD of age, 25 ± 4 years), and 12 patients with diseased hearts (female, 1 [8.3%]; mean ± SD of age, 44 ± 16 years; including coronary artery heart disease, congenital heart disease, dilated cardiomyopathy, amyloidosis, and myocarditis).

FIELD STRENGTH/SEQUENCE

3-T, M2C EPICS DWI, and M2C DWI.

ASSESSMENT

The apparent SNR (aSNR) and the rating scores were used to evaluate and compared image quality of all three groups. The aSNR was calculated using aSNR = Mean intensity myocardium / Standard deviation myocardium , and the myocardium was segmented manually. Three observers independently rated subjective image quality using a 5-point Likert scale.

STATISTICAL TESTS

Bland-Altman analysis and paired t-tests. The threshold for statistical significance was set at P < 0.05.

RESULTS

In healthy volunteers, the aSNR with a b-value of 450 s/mm2 acquired by M2C EPICS DWI was significantly higher than M2C DWI at in-plane resolutions of 3.0 × 3.0, 2.5 × 2.5, and 2.0 × 2.0 mm2. In patients with diseased hearts, the aSNR ofM2C EPICS DWI was also significantly higher than that for M2C DWI (bias of M2C EPICS-M2C = 1.999, 95% limits of agreement, 0.362 to 3.636; mean ± SD, 7.80 ± 1.37 vs. 5.80 ± 0.81). The ADC values of M2C EPICS was significantly higher than M2C DWI in in-vivo hearts. Over 80% of the images with rating scores for M2C EPICS DWI were higher than M2C DWI in in-vivo hearts.

DATA CONCLUSION

Cardiac imaging by M2C EPICS DWI may demonstrate better overall image quality and higher aSNR than M2C DWI.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 1.

Deep learning-based compressed SENSE improved diffusion-weighted image quality and liver cancer detection: A prospective study

PURPOSE

To assess whether diffusion-weighted imaging (DWI) with Compressed SENSE (CS) and deep learning (DL-CS-DWI) can improve image quality and lesion detection in patients at risk for hepatocellular carcinoma (HCC).

METHODS

This single-center prospective study enrolled consecutive at-risk participants who underwent 3.0 T gadoxetate disodium-enhanced MRI. Conventional DWI was acquired using parallel imaging (PI) with SENSE (PI-DWI). In CS-DWI and DL-CS-DWI, CS but not PI with SENSE was used to accelerate the scan with 2.5 as the acceleration factor. Qualitative and quantitative image quality were independently assessed by two masked reviewers, and were compared using the Wilcoxon signed-rank test. The detection rates of clinically-relevant (LR-4/5/M based on the Liver Imaging Reporting and Data System v2018) liver lesions for each DWI sequence were independently evaluated by another two masked reviewers against their consensus assessments based on all available non-DWI sequences, and were compared by the McNemar test.

RESULTS

67 participants (median age, 58.0 years; 56 males) with 197 clinically-relevant liver lesions were enrolled. Among the three DWI sequences, DL-CS-DWI showed the best qualitative and quantitative image qualities (p range, <0.001-0.039). For clinically-relevant liver lesions, the detection rates (91.4%-93.4%) of DL-CS-DWI showed no difference with CS-DWI (87.3%-89.8%, p = 0.230-0.231) but were superior to PI-DWI (82.7%-85.8%, p = 0.015-0.025). For lesions located in the hepatic dome, DL-CS-DWI demonstrated the highest detection rates (94.8%-97.4% vs 76.9%-79.5% vs 64.1%-69.2%, p = 0.002-0.045) among the three DWI sequences.

CONCLUSION

In patients at high-risk for HCC, DL-CS-DWI improved image quality and detection for clinically-relevant liver lesions, especially for the hepatic dome.

Utility of Echo-planar Imaging with Compressed Sensitivity Encoding (EPICS) in the Evaluation of Small Breast Cancers Using Diffusion-weighted Imaging with Background Suppression (DWIBS)

PURPOSE

High b-value acquisition and diffusion-weighted imaging with background suppression (DWIBS) are desirable in high-specificity breast cancer diagnosis on non-contrast-enhanced magnetic resonance imaging; however, this inherently results in a lower signal-to-noise ratio (SNR). Compressed sensitivity encoding (C-SENSE), which combines SENSE with compressed sensing, improves the SNR by reducing noise. Recent technological improvements allow us to incorporate this acceleration technique into echo-planar imaging, called echo-planar imaging with C-SENSE (EPICS). This study aimed to compare image quality and reliability of the apparent diffusion coefficient (ADC) between DWIBS obtained using SENSE and EPICS in patients with small breast cancers.

METHODS

Thirty-seven patients with pathologically confirmed breast cancer underwent DWIBS, and images were reconstructed using both conventional SENSE (SENSE-DWIBS) and EPICS (EPICS-DWIBS). Two board-certified radiologists independently evaluated lesion conspicuity (LC) and noise using a 5-point grading scale. The same 2 radiologists independently measured SNR, contrast-to-noise ratio (CNR), and the mean cancer ADC. The Pearson coefficient and Bland-Altman plot were applied to assess the accuracy of ADCs.

RESULTS

LC scores were higher with EPICS than with SENSE, reaching significance for one reviewer but not the other reviewer. Noise ratings on visual evaluation were significantly lower with EPICS than with SENSE (P < 0.001 for both reviewers). SNR was significantly higher with EPICS than with SENSE (P < 0.005 for both reviewers). CNR was significantly higher with EPICS than with SENSE (P < 0.001 for both reviewers). Bland-Altman plots of cancer ADCs using EPICS-DWIBS and SENSE-DWIBS showed excellent concordance, with a bias of 0.026 × 10-3 mm2/s and limits of agreement ranging 0.054 × 10-3 mm2/s; the Pearson's correlation coefficient was 0.997 (P < 0.0001).

CONCLUSION

EPICS enhances breast DWIBS image quality, with improved SNR and CNR and reduced noise levels. The ADCs of breast cancers obtained using EPICS were almost perfectly correlated with those obtained using conventional SENSE.

Utility of Echo Planar Imaging With Compressed Sensing-Sensitivity Encoding (EPICS) for the Evaluation of the Head and Neck Region

Purpose This study aimed to compare the image quality between echo planar imaging (EPI) with compressed sensing-sensitivity encoding (EPICS)-based diffusion-weighted imaging (DWI) and conventional parallel imaging (PI)-based DWI of the head and neck. Materials and methods Ten healthy volunteers participated in this study. EPICS-DWI was acquired based on an axial spin-echo EPI sequence with EPICS acceleration factors of 2, 3, and 4, respectively. Conventional PI-DWI was acquired using the same acceleration factors (i.e., 2, 3, and 4). Quantitative assessment was performed by measuring the signal-to-noise ratio (SNR) and apparent diffusion coefficient (ADC) in a circular region of interest (ROI) on the parotid and submandibular glands. For qualitative evaluation, a three-point visual grading system was used to assess the (1) overall image quality and (2) degree of image distortion. Results In the quantitative assessment, the SNR of the parotid gland in EPICS-DWI was significantly higher than that of PI-DWI in acceleration factors of 3 and 4 (p<0.05). In a comparison of ADC values, significant differences were not observed between EPICS-DWI and PI-DWI. In the qualitative assessment, the overall image quality of EPICS-DWI was significantly higher than that of PI-DWI for acceleration factors 3 and 4 (p<0.05). The degree of image distortion was significantly larger in EPICS-DWI with an acceleration factor of 2 than that of 3 or 4 (p<0.01, respectively). Conclusion Under the appropriate parameter setting, EPICS-DWI demonstrated higher SNR and better overall image quality for head and neck imaging than PI-DWI, without increasing image distortion.

Reproducibility of quantitative ADC, T1, and T2 measurement on the cerebral cortex: Utility of whole brain echo-planar DWI with compressed SENSE (EPICS-DWI): A pilot study

Purpose

To assess the reproducibility of ADC, T1, T2, and proton density (PD) measurements on the cortex across the entire brain using high-resolution pseudo-3D diffusion-weighted imaging using echo-planar imaging with compressed SENSE (EPICS-DWI) and 3D quantification with an interleaved Look-Locker acquisition sequence with T2 preparation pulse (3D-QALAS) in normal healthy adults.

Methods

Twelve healthy participants (median age, 33 years; range, 28-51 years) were recruited to evaluate the reproducibility of whole-brain EPICS-DWI and synthetic MRI. EPICS-DWI utilizes a compressed SENSE reconstruction framework while maintaining the EPI sampling pattern. The 3D-QALAS sequence is based on multi-acquisition 3D gradient echo, with five acquisitions equally spaced in time, interleaved with a T2 preparation pulse and an inversion pulse. EPICS-DWI (b values, 0 and 1000 s/mm2) and 3D-QALAS sequence with identical voxel size on a 3.0-T MR system were performed twice (for test-retest scan). Intraclass correlation coefficients (ICCs) for ADC, T1, T2, and PD for all parcellated volume of interest (VOI) per subject on scan-rescan tests were calculated to assess reproducibility. Bland-Altman plots were used to investigate discrepancies in ADCs, T1s, T2s, and PDs obtained from the two MR scans.

Results

The ICC of ADCs was 0.785, indicating "good" reproducibility. The ICCs of T1s, T2s, and PDs were 0.986, 0.978, and 0.968, indicating "excellent" reproducibility.

Conclusion

The combination of EPICS-DWI and 3D-QALAS sequences with identical voxel size could reproducible ADC, T1, T2, and PD measurements for the cortex across the entire brain in healthy adults.

Diagnostic ability of diffusion-weighted imaging using echo planar imaging with compressed SENSE (EPICS) for differentiating hepatic hemangioma and liver metastasis

PURPOSE

To assess the diagnostic abilities of diffusion-weighted imaging (DWI) with parallel imaging (PI-DWI) and that with Compressed SENSE (EPICS-DWI) for differentiating hepatic hemangiomas (HHs) and liver metastases (LMs).

METHOD

This prospective study included 30 participants with HH and/or LM who underwent PI-DWI and EPICS-DWI. Two radiologists assessed the DWI images and assigned confidence scores for hepatic lesions conspicuity using 4-point scale. One of the radiologists additionally calculated the contrast-to-noise ratio (CNR) and measured ADC value of the hepatic lesions. The conspicuity, CNR, and ADC values were compared between the two sequences. A receiver operating characteristic (ROC) analysis was performed to assess the diagnostic abilities of the two sequences for differentiating HHs and LMs.

RESULTS

The conspicuity of LMs was better in EPICS-DWI than in PI-DWI (P < .05 in both radiologists). The CNR of LMs was higher in EPICS-DWI than in PI-DWI (P = .008). No difference was found in the CNR of HHs (P = .52), ADC values for HHs (P = .79), and LMs (P = .29) between the two sequences. To differentiate between HHs and LMs, the cutoff ADC values were 1.38 × 10-3 mm2/s in PI-DWI and 1.37 × 10-3 mm2/s in EPICS-DWI. The area under the ROC curve (P = .86), sensitivity (P > .99), and specificity (P > .99) did not vary.

CONCLUSIONS

The LMs were more visible in EPICS-DWI than in PI-DWI. However, the cutoff ADC values and diagnostic abilities for differentiating HHs and LMs were almost comparable between the two sequences.

Clinical utility of single-shot echo-planar diffusion-weighted imaging using L1-regularized iterative sensitivity encoding in prostate MRI

We investigated the ability of echo-planar imaging with L1-regularized iterative sensitivity encoding-based diffusion-weighted imaging (DWI) to improve the image quality and reduce the scanning time in prostate magnetic resonance imaging. We retrospectively analyzed 109 cases of prostate magnetic resonance imaging. We compared variables in the quantitative and qualitative assessments among 3 imaging groups: conventional parallel imaging-based DWI (PI-DWI) with an acquisition time of 3 minutes 15 seconds; echo-planar imaging with L1-regularized iterative sensitivity encoding-based DWI (L1-DWI) with a normal acquisition time (L1-DWINEX12) of 3 minutes 15 seconds; and L1-DWI with a half acquisition time (L1-DWINEX6) of 1 minute 45 seconds. As a quantitative assessment, the signal-to-noise ratio (SNR) of DWI (SNR-DWI), the contrast-to-noise ratio (CNR) of DWI (CNR-DWI), and the CNR of apparent diffusion coefficient were measured. As a qualitative assessment, the image quality and visual detectability of prostate carcinoma were evaluated. In the quantitative analysis, L1-DWINEX12 showed significantly higher SNR-DWI than PI-DWI (P = .0058) and L1-DWINEX6 (P < .0001). In the qualitative analysis, the image quality score for L1-DWINEX12 was significantly higher than those of PI-DWI and L1-DWINEX6. A non-inferiority assessment demonstrated that L1-DWINEX6 was non-inferior to PI-DWI in terms of both quantitative CNR-DWI and qualitative grading of image quality with a <20% inferior margin. L1-DWI successfully demonstrated a reduced scanning time while maintaining good image quality.

MRI: Evaluating the Application of FOCUS-MUSE Diffusion-Weighted Imaging in the Pancreas in Comparison With FOCUS, MUSE, and Single-Shot DWIs

BACKGROUND

Diffusion-weighted imaging (DWI) is a useful technique to detect pancreatic lesion. In DWIs, field-of-view optimized and constrained undistorted single-shot (FOCUS) can improve the spatial resolution and multiplexed sensitivity-encoding (MUSE) can gain a high signal-to-noise ratio (SNR). Based on the advantage of FOCUS and MUSE, a new DWI sequence-named FOCUS-MUSE DWI (FOCUS combined with MUSE)-was developed to delineate the pancreas.

PURPOSE

To investigate the reliability of FOCUS-MUSE DWI compared to FOCUS, MUSE and single-shot (SS) DWI via the systematical evaluation of the apparent diffusion coefficient (ADC) measurements, SNR and image quality.

STUDY TYPE

Prospective.

SUBJECTS

A total of 33 healthy volunteers and 9 patients with pancreatic lesion.

FIELD STRENGTH/SEQUENCE

A 3.0 T scanner. FOCUS-MUSE DWI, FOCUS DWI, MUSE DWI, SS DWI.

ASSESSMENT

For volunteers, ADC and SNR were measured by two readers in the pancreatic head, body, and tail. For all subjects, the diagnostic image quality score was assessed by three other readers on above four DWIs.

STATISTICAL TESTS

Paired-sample T-test, intraclass correlation (ICC), Bland-Altman method, Friedman test, Dunn-Bonferroni post hoc test and kappa coefficient. A significance level of 0.05 was used.

RESULTS

FOCUS-MUSE DWI had the best intersession repeatability of ADC measurements (head: 59.53, body: 101.64, tail: 42.30) among the four DWIs, and also maintained the significantly highest SNR (reader 1 [head: 19.68 ± 3.23, body: 23.42 ± 5.00, tail: 28.85 ± 4.96], reader 2 [head: 19.93 ± 3.52, body: 23.02 ± 5.69, tail: 29.77 ± 6.33]) except for MUSE DWI. Furthermore, it significantly achieved better image quality in volunteers (median value: 4 score) and 9 patients (most in 4 score).

DATA CONCLUSION

FOCUS-MUSE DWI improved the reliability of pancreatic images with the most stable ADC measurement, best image quality score and sufficient SNR among four DWIs.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Technical Advancements in Abdominal Diffusion-weighted Imaging

Since its first observation in the 18th century, the diffusion phenomenon has been actively studied by many researchers. Diffusion-weighted imaging (DWI) is a technique to probe the diffusion of water molecules and create a MR image with contrast based on the local diffusion properties. The DWI pixel intensity is modulated by the hindrance the diffusing water molecules experience. This hindrance is caused by structures in the tissue and reflects the state of the tissue. This characteristic makes DWI a unique and effective tool to gain more insight into the tissue's pathophysiological condition. In the past decades, DWI has made dramatic technical progress, leading to greater acceptance in clinical practice. In the abdominal region, however, acquiring DWI with good quality is challenging because of several reasons, such as large imaging volume, respiratory and other types of motion, and difficulty in achieving homogeneous fat suppression. In this review, we discuss technical advancements from the past decades that help mitigate these problems common in abdominal imaging. We describe the use of scan acceleration techniques such as parallel imaging and compressed sensing to reduce image distortion in echo planar imaging. Then we compare techniques developed to mitigate issues due to respiratory motion, such as free-breathing, respiratory-triggering, and navigator-based approaches. Commonly used fat suppression techniques are also introduced, and their effectiveness is discussed. Additionally, the influence of the abovementioned techniques on image quality is demonstrated. Finally, we discuss the current and future clinical applications of abdominal DWI, such as whole-body DWI, simultaneous multiple-slice excitation, intravoxel incoherent motion, and the use of artificial intelligence. Abdominal DWI has the potential to develop further in the future, thanks to scan acceleration and image quality improvement driven by technological advancements. The accumulation of clinical proof will further drive clinical acceptance.

Clinical impact of artificial intelligence-based solutions on imaging of the pancreas and liver

Artificial intelligence (AI) has experienced substantial progress over the last ten years in many fields of application, including healthcare. In hepatology and pancreatology, major attention to date has been paid to its application to the assisted or even automated interpretation of radiological images, where AI can generate accurate and reproducible imaging diagnosis, reducing the physicians’ workload. AI can provide automatic or semi-automatic segmentation and registration of the liver and pancreatic glands and lesions. Furthermore, using radiomics, AI can introduce new quantitative information which is not visible to the human eye to radiological reports. AI has been applied in the detection and characterization of focal lesions and diffuse diseases of the liver and pancreas, such as neoplasms, chronic hepatic disease, or acute or chronic pancreatitis, among others. These solutions have been applied to different imaging techniques commonly used to diagnose liver and pancreatic diseases, such as ultrasound, endoscopic ultrasonography, computerized tomography (CT), magnetic resonance imaging, and positron emission tomography/CT. However, AI is also applied in this context to many other relevant steps involved in a comprehensive clinical scenario to manage a gastroenterological patient. AI can also be applied to choose the most convenient test prescription, to improve image quality or accelerate its acquisition, and to predict patient prognosis and treatment response. In this review, we summarize the current evidence on the application of AI to hepatic and pancreatic radiology, not only in regard to the interpretation of images, but also to all the steps involved in the radiological workflow in a broader sense. Lastly, we discuss the challenges and future directions of the clinical application of AI methods.

Compressed SENSEを用いたhigh reduction factor EPI DWIの定量評価

PURPOSE

The purposes of this study were to clarify the difference in image characteristics of EPI with compressed SENSE (EPICS) DWI and conventional EPI-SENSE DWI when the reduction factor is increased, and to investigate the optimal reduction factor setting for EPICS DWI.

METHODS

Using Philips MRI Ingenia Elition 3.0T and a phantom, we compared the SNR, CNR, and ADC values between the EPI-SENSE and EPICS methods with increasing reduction factor. The presence of deployment failure artifacts was verified by the dynamic noise scan method. P<0.05 was set as the significance level.

RESULTS

The EPICS method showed significantly higher SNR (1.1-1.4 times) and CNR (1.3-1.8 times) than the EPI-SENSE method at reduction factors 2-5 (P<0.05), with less deployment failure artifacts. The ADC of the EPICS method was 0.03-0.07×10^-3 mm²/s lower at reduction factors 3-5.

CONCLUSION

EPICS DWI is a useful imaging method that is highly effective in reducing image degradation in high reduction factor imaging.

State-of-the-art magnetic resonance imaging sequences for pediatric body imaging

Longer examination time, need for anesthesia in smaller children and the inability of most children to hold their breath are major limitations of MRI in pediatric body imaging. Fortunately, with technical advances, many new and upcoming MRI sequences are overcoming these limitations. Advances in data acquisition and k-space sampling methods have enabled sequences with improved temporal and spatial resolution, and minimal artifacts. Sequences to minimize movement artifacts mainly utilize radial k-space filling, and examples include the stack-of-stars method for T1-weighted imaging and the periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER)/BLADE method for T2-weighted imaging. Similarly, the sequences with improved temporal resolution and the ability to obtain multiple phases in a single breath-hold in dynamic imaging mainly use some form of partial k-space filling method. New sequences use a variable combination of data sampling methods like compressed sensing, golden-angle radial k-space filling, parallel imaging and partial k-space filling to achieve free-breathing, faster sequences that could be useful for pediatric abdominal and thoracic imaging. Simultaneous multi-slice method has improved diffusion-weighted imaging (DWI) with reduction in scan time and artifacts. In this review, we provide an overview of data sampling methods like parallel imaging, compressed sensing, radial k-space sampling, partial k-space sampling and simultaneous multi-slice. This is followed by newer available and upcoming sequences for T1-, T2- and DWI based on these other advances. We also discuss the Dixon method and newer approaches to reducing metal artifacts.

Clinical application of single-shot echo-planar diffusion-weighted imaging with compressed SENSE in prostate MRI at 3T: preliminary experience

OBJECTIVES

Image quality (IQ) of diffusion-weighted imaging (DWI) with single-shot echo-planar imaging (ssEPI) suffers from low signal-to-noise ratio (SNR) in high b-value acquisitions. Compressed SENSE (C-SENSE), which combines SENSE with compressed sensing, enables SNR to be improved by reducing noise. The aim of this study was to compare IQ and prostate cancer (PC) detectability between DWI with ssEPI using SENSE (EPIS) and using C-SENSE (EPICS).

MATERIALS AND METHODS

Twenty-five patients with pathologically proven PC underwent multi-parametric magnetic resonance imaging at 3T. DW images acquired with EPIS and EPICS were assessed for the following: lesion conspicuity (LC), SNR, contrast-to-noise ratio (CNR), mean and standard deviation (SD) of apparent diffusion coefficient (ADC) of lesion (lADCm and lADCsd), coefficient of variation of lesion ADC (lADCcv), and mean ADC of benign prostate (bADCm).

RESULTS

LC were comparable between EPIS and EPICS (p > 0.050), and SNR and CNR were significantly higher in EPICS than EPIS (p = 0.001 and p < 0.001). In both EPIS and EPICS, lADCm was significantly lower than bADCm (p < 0.001). In addition, lADCcv was significantly lower in EPICS than in EPIS (p < 0.001).

CONCLUSION

Compared with EPIS, EPICS has improved IQ and comparable diagnostic performance in PC.

Comparing the clinical utility of single-shot, readout-segmented and zoomit echo-planar imaging in diffusion-weighted imaging of the kidney at 3 T

We compared the clinical utility of single-shot echo-planar imaging (SS-EPI) using different breathing schemes, readout-segmented EPI and zoomit EPI in the repeatability of apparent diffusion coefficient (ADC) measurements, cortico-medullary contrast to noise ratio (c-mCNR) and image quality. In this institutional review board-approved prospective study, some common clinically applicable diffusion-weighted imaging (b = 50, 400, 800 s/mm²) of kidney on 3.0 T MRI were performed on 22 volunteers using SS-EPI with breath-hold diffusion-weighted imaging (BH-DWI), free-breathing (FB-DWI), navigator-triggered (NT-DWI) and respiratory-triggered (RT-DWI), readout-segmented DWI (RS-DWI), and Zoomit DWI (Z-DWI). ADC and c-mCNR were measured in 12 anatomic locations (the upper, middle, and lower pole of the renal cortex and medulla), and image quality was assessed on these DWI sequences. A DWI with the optimal clinical utility was decided by systematically assessing the ADC repeatability, c-mCNR and image quality among the DWIs. For ADC measurements, Z-DWI had an excellent intra-observer agreement (intra-class correlation coefficients (ICCs): 0.876–0.944) and good inter-observer agreement (inter-class ICCs: 0.798–0.856) in six DWI sequences. Z-DWI had the highest ADC repeatability in most of the 12 anatomic locations of the kidneys (mean ADC absolute difference: 0.070–0.111 × 10⁻³ mm²/s, limit of agreement: 0.031–0.056 × 10⁻³ mm²/s). In all DWIs, Z-DWI yielded a slightly higher c-mCNR than other DWIs in most representative locations (P > 0.05), which was significantly higher than BH-DWI and FB-DWI in the middle pole of both kidneys and the upper pole of the left kidney (P < 0.05). In addition, Z-DWI yielded image quality that was similar to RT-DWI and NT-DWI (P > 0.05) and superior to BH-DWI, FB-DWI and RS-DWI (P < 0.05). Our results suggest that Z-DWI provides the highest ADC reproducibility, better c-mCNR and good image quality on 3.0 T MRI, making it the recommended sequence for clinical DWI of the kidney.

Multi-parameter quantitative mapping of R1, R2*, PD, and MTsat is reproducible when accelerated with Compressed SENSE

Multi-parameter mapping (MPM) magnetic resonance imaging (MRI) provides quantitative estimates of the longitudinal and effective transverse relaxation rates R1 and R2*, proton density (PD), and magnetization transfer saturation (MTsat). Thereby, MPM enables better comparability across sites and time than conventional weighted MRI. However, for MPM, several contrasts must be acquired, resulting in prolonged measurement durations and thus preventing MPM's application in clinical routines. State-of-the-art imaging acceleration techniques such as Compressed SENSE (CS), a combination of compressed sensing and sensitivity encoding, can be used to reduce the scan time of MPM. However, the accuracy and precision of the resulting quantitative parameter maps have not been systematically evaluated. In this study, we therefore investigated the effect of CS acceleration on the fidelity and reproducibility of MPM acquisitions. In five healthy volunteers and in a phantom, we compared MPM metrics acquired without imaging acceleration, with the standard acceleration (SENSE factor 2.5), and with Compressed SENSE with acceleration factors 4 and 6 using a 32-channel head coil. We evaluated the reproducibility and repeatability of accelerated MPM using data from three scan sessions in gray and white matter volumes-of-interest (VOIs). Accelerated MPM provided precise and accurate quantitative parameter maps. For most parameters, the results of the CS-accelerated protocols correlated more strongly with the non-accelerated protocol than the standard SENSE-accelerated protocols. Furthermore, for most VOIs and contrasts, coefficients of variation were lower when calculated from data acquired with different imaging accelerations within a single scan session than from data acquired in different scan sessions. These results suggest that MPM with Compressed SENSE acceleration factors up to at least 6 yields reproducible quantitative parameter maps that are highly comparable to those acquired without imaging acceleration. Compressed SENSE can thus be used to considerably reduce the scan duration of R1, R2*, PD, and MTsat mapping, and is highly promising for clinical applications of MPM.

Noninvasive assessment of clinical and pathological characteristics of patients with IgA nephropathy by diffusion kurtosis imaging

Objectives

To explore the diagnostic performance of diffusion kurtosis imaging (DKI) in evaluating the clinical and pathological characteristics of patients with immunoglobulin A nephropathy (IgAN) compared with conventional DWI.

Materials and methods

A total of 28 IgAN patients and 14 healthy volunteers prospectively underwent MRI examinations including coronal T2WI, axial T1WI, T2WI, and DWI sequences from September 2020 to August 2021. We measured mean kurtosis (MK), mean diffusivity (MD), and apparent diffusion coefficient (ADC) by using MR Body Diffusion Toolbox v1.4.0 (Siemens Healthcare). Patients were divided into three groups according to their estimated glomerular filtration rate (eGFR) (Group1, healthy volunteers without kidney disease or other diseases that affect renal function; Group2, IgAN patients with eGFR > 60 mL/min/1.73 m²; Group3, IgAN patients with eGFR < 60 mL/min/1.73 m²). One-way analysis of variance, Pearson or Spearman correlation, and receiver operating characteristic curves were applied in our statistical analysis.

Results

MK_Cortex and ADC_Cortex showed significant differences between the Group1 and Group2. MK_Cortex, MD_Cortex, ADC_Cortex, MK_Medulla, and ADC_Medulla showed significant differences between Group2 and Group3. MK_Cortex had the highest correlation with CKD stages (r = 0.749, p < 0.001), and tubulointerstitial lesion score (r = 0.656, p < 0.001). MD_Cortex had the highest correlation with glomerular lesion score (r = − 0.475, p = 0.011). MK_Cortex had the highest AUC (AUC = 0.923) for differentiating Group1 from Group2, and MD_Cortex had the highest AUC (AUC = 0.924) for differentiating Group2 from Group3, followed by MK_Medulla (AUC = 0.923).

Conclusions

DKI is a feasible and reliable technique that can assess the clinical and pathological characteristics of IgAN patients and can provide more valuable information than conventional DWI, especially MK_Cortex.