Reduction of ADC bias in diffusion MRI with deep learning-based acceleration: A phantom validation study at 3.0 T.

PURPOSE: Further acceleration of DWI in diagnostic radiology is desired but challenging mainly due to low SNR in high b-value images and associated bias in quantitative ADC values. Deep learning-based reconstruction and denoising may provide a solution to address this challenge. METHODS: The effects of SNR reduction on ADC bias and variability were investigated using a commercial diffusion phantom and numerical simulations. In the phantom, performance of different reconstruction methods, including conventional parallel (SENSE) imaging, compressed sensing (C-SENSE), and compressed SENSE acceleration with an artificial intelligence deep learning-based technique (C-SENSE AI), was compared at different acceleration factors and flip angles using ROI-based analysis. ADC bias was assessed by Lin's Concordance correlation coefficient (CCC) followed by bootstrapping to calculate confidence intervals (CI). ADC random measurement error (RME) was assessed by the mean coefficient of variation (CV¯) and non-parametric statistical tests. RESULTS: The simulations predicted increasingly negative bias and loss of precision towards lower SNR. These effects were confirmed in phantom measurements of increasing acceleration, for which CCC decreased from 0.947 to 0.279 and CV¯ increased from 0.043 to 0.439, and of decreasing flip angle, for which CCC decreased from 0.990 to 0.063 and CV¯ increased from 0.037 to 0.508. At high acceleration and low flip angle, C-SENSE AI reconstruction yielded best denoised ADC maps. For the lowest investigated flip angle, CCC = {0.630, 0.771 and 0.987} and CV¯={0.508, 0.426 and 0.254} were obtained for {SENSE, C-SENSE, C-SENSE AI}, the improvement by C-SENSE AI being significant as compared to the other methods (CV: p = 0.033 for C-SENSE AI vs. C-SENSE and p < 0.001 for C-SENSE AI vs. SENSE; CCC: non-overlapping CI between reconstruction methods). For the highest investigated acceleration factor, CCC = {0.479,0.926,0.960} and CV¯={0.519,0.119,0.118} were found, confirming the reduction of bias and RME by C-SENSE AI as compared to C-SENSE (by trend) and to SENSE (CV: p < 0.001; CCC: non-overlapping CI). CONCLUSION: ADC bias and random measurement error in DWI at low SNR, typically associated with scan acceleration, can be effectively reduced by deep-learning based C-SENSE AI reconstruction.

Comparison of Echo-Planar Imaging and Compressed Sensing in the Estimation of Flow Metrics from Aortic 4D Flow MR Imaging: A Healthy Volunteer Study.

PURPOSE: Prolonged scanning of time-resolved 3D phase-contrast MRI (4D flow MRI) limits its routine use in clinical practice. An echo-planar imaging (EPI)-based sequence and compressed sensing can reduce the scan duration. We aimed to determine the impact of EPI for 4D flow MRI on the scan duration, image quality, and quantitative flow metrics. METHODS: This was a prospective study of 15 healthy volunteers (all male, mean age 33 ± 5 years). Conventional sensitivity encoding (SENSE), EPI with SENSE (EPI), and compressed SENSE (CS) (reduction factors: 6 and 12, respectively) were scanned.Scan duration, qualitative indexes of image quality, and quantitative flow parameters of net flow volume, maximum flow velocity, wall shear stress (WSS), and energy loss (EL) in the ascending aorta were assessed. Two-dimensional phase-contrast cine MRI (2D-PC) was considered the gold standard of net flow volume and maximum flow velocity. RESULTS: Compared to SENSE, EPI and CS12 shortened scan durations by 71% and 73% (EPI, 4 min 39 sec; CS6, 7 min 29 sec; CS12, 4 min 14 sec; and SENSE, 15 min 51 sec). Visual image quality was significantly better for EPI than for SENSE and CS (P < 0.001). The net flow volumes obtained with SENSE, EPI, and CS12 and those obtained with 2D-PC were correlated well (r = 0.950, 0.871, and 0.850, respectively). However, the maximum velocity obtained with EPI was significantly underestimated (P < 0.010). The average WSS was significantly higher with EPI than with SENSE, CS6, and CS12 (P < 0.001, P = 0.040, and P = 0.012, respectively). The EL was significantly lower with EPI than with CS6 and CS12 (P = 0.002 and P = 0.007, respectively). CONCLUSION: EPI reduced the scan duration, improved visual image quality, and was associated with more accurate net flow volume than CS. However, the flow velocity, WSS, and EL values obtained with EPI and other sequences may not be directly comparable.

Improved image quality in contrast-enhanced 3D-T1 weighted sequence by compressed sensing-based deep-learning reconstruction for the evaluation of head and neck.

PURPOSE: To assess the utility of deep learning (DL)-based image reconstruction with the combination of compressed sensing (CS) denoising cycle by comparing images reconstructed by conventional CS-based method without DL in fat-suppressed (Fs)-contrast enhanced (CE) three-dimensional (3D) T1-weighted images (T1WIs) of the head and neck. MATERIALS AND METHODS: We retrospectively analyzed the cases of 39 patients who had undergone head and neck Fs-CE 3D T1WI applying reconstructions based on conventional CS and CS augmented by DL, respectively. In the qualitative assessment, we evaluated overall image quality, visualization of anatomical structures, degree of artifacts, lesion conspicuity, and lesion edge sharpness based on a five-point system. In the quantitative assessment, we calculated the signal-to-noise ratios (SNRs) of the lesion and the posterior neck muscle and the contrast-to-noise ratio (CNR) between the lesion and the adjacent muscle. RESULTS: For all items of the qualitative analysis, significantly higher scores were awarded to images with DL-based reconstruction (p < 0.001). In the quantitative analysis, DL-based reconstruction resulted in significantly higher values for both the SNR of lesions (p < 0.001) and posterior neck muscles (p < 0.001). Significantly higher CNRs were also observed in images with DL-based reconstruction (p < 0.001). CONCLUSION: DL-based image reconstruction integrating into the CS-based denoising cycle offered superior image quality compared to the conventional CS method. This technique will be useful for the assessment of patients with head and neck disease.

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.

Comparison of 3D Magnetization-transfer- and Spectral-presaturation-with-inversion-recovery-based Neuromelanin Imaging.

PURPOSE: Neuromelanin is visualized by optimizing the conditions of longitudinal relaxation (T1)-weighted imaging (T1WI). Although it was originally developed in 2D imaging, 3D imaging has been also reported, and T1WI sequences with magnetization transfer (MT) pulses are now widely used in 3D gradient echo (GRE) sequences. In this study, we assert that the use of spectral presaturation with inversion recovery (SPIR) may also be useful as an alternative to MT pulses, and we optimize SPIR and compare it with MT. METHODS: Neuromelanin images with MT pulse and SPIR (flip angles [FAs] = 19º, 22º, and 25º) were acquired from 30 healthy volunteers. To achieve the same acquisition time of 5 min, the slab thickness of the MT images was less than 1/3 of those of the SPIR images; the acquisition areas for MT and SPIR were the brainstem and the whole brain, respectively. Visual and quantitative evaluation was performed and compared on the four sequences acquired for the substantia nigra pars compacta (SNc) and the locus coeruleus (LC). For visual assessment, we used the mean score from a 3-point scale by two evaluators. For quantitative evaluation, the contrast ratios of SNc and LC were calculated in comparison with the background tissue signal. RESULTS: In visual assessments, the mean scores of the SPIR FA19º and FA22º images were better than others in the SNc. Regarding LC, the SPIR FA22º image yielded the best mean score. In quantitative evaluations, the MT image was significantly lower than the other three images in SNc. Regarding LC, there were no significant differences among the four acquired images (MT and SPIR FA19º, FA22º, and FA25º). CONCLUSIONS: Detection of neuromelanin in SNc and LC was improved by the use of SPIR compared to MT pulse in 3D neuromelanin imaging.

Non-contrast magnetic resonance angiography for systemic artery evaluation in Kawasaki disease.

BACKGROUND: Kawasaki disease (KD) is a systemic vasculitis; systemic arteries other than the coronary arteries should therefore also be evaluated. This study investigated the feasibility of evaluating coronary aneurysms, systemic artery aneurysms (SAAs), and cerebrovascular diseases in patients with KD using non-contrast magnetic resonance angiography (NC-MRA). METHODS: Coronary artery protocols, including coronary magnetic resonance angiography (MRA) and vessel wall imaging, were performed in 57 examinations of 28 patients. Systemic artery protocol, including SAA scans and head MRA, along with coronary artery protocol, were performed in 42 examinations of 42 patients. The image quality of the SAAs was evaluated on a 4-point scale. Examination time and sedation dosage were compared between the protocols. The presence of SAAs and cerebrovascular disease was also evaluated. RESULTS: The image quality score of SAAs was 4 (interquartile range [IQR]: 4-4) for the aorta, 4 (IQR: 3-4) for the subclavian artery, 4 (IQR: 3-4) for the renal artery, and 3 (IQR: 3-4) for the iliac artery. No differences were found between examination time (47.0 [IQR: 43.0-61.0] min vs. 51.0 [IQR: 45.0-60.0] min, p = 0.48) and sedative dose (4.63 [IQR: 3.93-5.79] mg/kg vs. 4.21 [IQR: 3.56-5.71] mg/kg, p = 0.37) between the protocols. Systemic artery protocol detected SAAs in three patients (7.1%), and cerebrovascular disease was not detected. CONCLUSIONS: Evaluating the coronary and systemic arteries in patients with KD using NC-MRA on a single examination was possible without compromising examination time or sedation dose. The systemic artery protocol was useful in finding SAAs.

MR Fingerprinting for Contrast Agent-free and Quantitative Characterization of Focal Liver Lesions.

Purpose To evaluate the feasibility of liver MR fingerprinting (MRF) for quantitative characterization and diagnosis of focal liver lesions. Materials and Methods This single-site, prospective study included 89 participants (mean age, 62 years ± 15 [SD]; 45 women, 44 men) with various focal liver lesions who underwent MRI between October 2021 and August 2022. The participants underwent routine clinical MRI, non-contrast-enhanced liver MRF, and reference quantitative MRI with a 1.5-T MRI scanner. The bias and repeatability of the MRF measurements were assessed using linear regression, Bland-Altman plots, and coefficients of variation. The diagnostic capability of MRF-derived T1, T2, T2*, proton density fat fraction (PDFF), and a combination of these metrics to distinguish benign from malignant lesions was analyzed according to the area under the receiver operating characteristic curve (AUC). Results Liver MRF measurements showed moderate to high agreement with reference measurements (intraclass correlation = 0.94, 0.77, 0.45, and 0.61 for T1, T2, T2*, and PDFF, respectively), with underestimation of T2 values (mean bias in lesion = -0.5%, -29%, 5.8%, and -8.2% for T1, T2, T2*, and PDFF, respectively). The median coefficients of variation for repeatability of T1, T2, and T2* values were 2.5% (IQR, 3.6%), 3.1% (IQR, 5.6%), and 6.6% (IQR, 13.9%), respectively. After considering multicollinearity, a combination of MRF measurements showed a high diagnostic performance in differentiating benign from malignant lesions (AUC = 0.92 [95% CI: 0.86, 0.98]). Conclusion Liver MRF enabled the quantitative characterization of various focal liver lesions in a single breath-hold acquisition. Keywords: MR Imaging, Abdomen/GI, Liver, Imaging Sequences, Technical Aspects, Tissue Characterization, Technology Assessment, Diagnosis, Liver Lesions, MR Fingerprinting, Quantitative Characterization Supplemental material is available for this article. © RSNA, 2023.

Improvement of image quality in diffusion-weighted imaging with model-based deep learning reconstruction for evaluations of the head and neck.

OBJECTIVES: To investigate the utility of deep learning (DL)-based image reconstruction using a model-based approach in head and neck diffusion-weighted imaging (DWI). MATERIALS AND METHODS: We retrospectively analyzed the cases of 41 patients who underwent head/neck DWI. The DWI in 25 patients demonstrated an untreated lesion. We performed qualitative and quantitative assessments in the DWI analyses with both deep learning (DL)- and conventional parallel imaging (PI)-based reconstructions. For the qualitative assessment, we visually evaluated the overall image quality, soft tissue conspicuity, degree of artifact(s), and lesion conspicuity based on a five-point system. In the quantitative assessment, we measured the signal-to-noise ratio (SNR) of the bilateral parotid glands, submandibular gland, the posterior muscle, and the lesion. We then calculated the contrast-to-noise ratio (CNR) between the lesion and the adjacent muscle. RESULTS: Significant differences were observed in the qualitative analysis between the DWI with PI-based and DL-based reconstructions for all of the evaluation items (p < 0.001). In the quantitative analysis, significant differences in the SNR and CNR between the DWI with PI-based and DL-based reconstructions were observed for all of the evaluation items (p = 0.002 ~ p < 0.001). DISCUSSION: DL-based image reconstruction with the model-based technique effectively provided sufficient image quality in head/neck DWI.

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.

Accelerating TOF-MRA: The impact of the combined use of compressed sensitivity encoding and spiral imaging.

PURPOSE: To evaluate the image quality of the combined technique of compressed sensitivity encoding (CS) and spiral imaging in time-of-flight magnetic resonance angiography (TOF-MRA), which is approximately 2.5 times faster than conventional methods. METHODS: Twenty volunteers underwent four TOF-MRA sequences: sensitivity encoding (SENSE) with acceleration factor of 4 (acquisition time: 4:55 min), CS with acceleration factor of 10.9, and spiral and CS-spiral (both 1:55 min). A quantitative image analysis (signal-to-noise ratio [SNR], contrast, and full width at half maximum [FWHM] edge criterion measurements) was performed on four TOF sequences. For qualitative image analysis, two board-certified radiologists evaluated the overall depiction of the proximal, intermediate, and distal branches in CS, spiral, and CS-spiral images using SENSE as a reference. RESULTS: The SNR of BA in spiral and CS-spiral imaging was significantly lower than that in SENSE (p = 0.009). The contrasts of ACA and BA in CS-spiral were significantly higher and those in spiral were significantly lower than those in SENSE (p < 0.001). The FWHM in the CS image was significantly higher than that of SENSE; however, no significant differences were observed between the spiral or CS-spiral and SENSE. In qualitative analysis, the depiction of proximal vascular branches was significantly impaired in spiral than in others and that of distal vascular branches was significantly impaired in CS than in others (p < 0.001). CONCLUSIONS: In TOF-MRA, which is approximately 2.5 times faster than conventional methods, the combined use of CS and spiral imaging demonstrated an improvement in image quality compared to either CS or spiral imaging alone. SUMMARY STATEMENT: The image quality of Compressed SENSE and spiral imaging is particularly poor in the proximal and distal vascular branches, respectively at an extremely high acceleration factor; however, CS-spiral provided stable image quality in all regions as compared with the SENSE technique.

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.

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 evaluation of cylindrical regional suppression in dynamic contrast-enhanced breast MRI: An intra-individual comparison study on image quality and lesion conspicuity.

PURPOSE: To evaluate the effect of a cylindrical regional-suppression technique (CREST) on image quality and lesion conspicuity in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast. METHOD: This was a comparative study of 67 women with 44 lesions who underwent breast DCE-MRI with CREST (CREST-DCE) and had a previous DCE-MRI without CREST (conv-DCE) available. Two radiologists assessed image quality parameters and lesion conspicuity using five-point Likert scales. In an intra-individual comparison, the effects of CREST on image quality (strong degradation to strong improvement) were assessed. Moreover, both radiologists identified the post-contrast phase, which benefited the most from using CREST in direct comparison. The statistical analysis included the Wilcoxon signed-rank test. RESULTS: Cardiac motion-rated artefacts were significantly reduced in CREST-DCE compared to conv-DCE (3.6 ± 1.2 [CREST-DCE] vs 2.1 ± 0.8 [conv-DCE], p < 0.001). At the axilla, the visualisation of anatomical structures (3.9 ± 1.0 vs 2.3 ± 1.2, p < 0.001) and the skin contour (4.3 ± 0.8 vs 3.0 ± 1.1, p < 0.001) were significantly improved in CREST-DCE, whereas ghosting artefacts were significantly less pronounced (3.8 ± 1.1 vs 2.4 ± 1.0, p < 0.001). The parasternal region was similarly assessable using both techniques (4.3 ± 1.1 vs 4.2 ± 1.2, p = 0.47). In direct comparison, CREST-DCE images were classified as "improved" in 54/67 and "equivalent" in 13/67 exams. The effects of CREST were found to be most pronounced in the very early post-contrast phase (32/67). The lesion conspicuity was rated similar for CREST and conv-DCE (4.7 ± 0.7 vs 4.8 ± 0.2, p = 0.18). CONCLUSIONS: CREST appears to be an effective tool to reduce cardiac motion-related artefacts and, therefore, may improve image quality in breast DCE-MRI without impairing lesion conspicuity.

Grading of gliomas using 3D CEST imaging with compressed sensing and sensitivity encoding.

PURPOSE: We evaluated the usefulness of three-dimensional (3D) chemical exchange saturation transfer (CEST) imaging with compressed sensing and sensitivity encoding (CS-SENSE) for differentiating low-grade gliomas (LGGs) from high-grade gliomas (HGGs). METHODS: We evaluated 28 patients (mean age 51.0 ± 13.9 years, 13 males, 15 females) including 12 with LGGs and 16 with HGGs, all acquired using a 3 T magnetic resonance (MR) scanner. Nine slices were acquired for 3D CEST imaging, and one slice was acquired for two-dimensional (2D) CEST imaging. Two radiological technologists each drew a region of interest (ROI) surrounding the high-signal-intensity area(s) on the fluid-attenuated inversion recovery image of each patient. We compared the magnetization transfer ratio asymmetry (MTRasym) at 3.5 ppm in the tumors among the (i) single-slice 2D CEST imaging ("2D"), (ii) all tumor slices of the 3D CEST imaging (3Dall), and (iii) a representative tumor slice of 3D CEST imaging (maximum signal intensity [3Dmax]). The relationship between the MTRasym at 3.5 ppm values measured by these three methods and the Ki-67 labeling index (LI) of the tumors was assessed. Diagnostic performance was evaluated with a receiver operating characteristic analysis. The Ki-67LI and MTRasym at 3.5 ppm values were compared between the LGGs and HGGs. RESULTS: A moderate positive correlation between the MTRasym at 3.5 ppm and the Ki-67LI was observed with all three methods. All methods proved a significantly larger MTRasym at 3.5 ppm for the HGGs compared to the LGGs. All methods showed equivalent diagnostic performance. The signal intensity varied depending on the slice position in each case. CONCLUSIONS: The 3D CEST imaging provided the MTRasym at 3.5 ppm for each slice cross-section; its diagnostic performance was also equivalent to that of 2D CEST imaging.

MR Fingerprinting for Liver Tissue Characterization: A Histopathologic Correlation Study.

Background Liver MR fingerprinting (MRF) enables simultaneous quantification of T1, T2, T2*, and proton density fat fraction (PDFF) maps in single breath-hold acquisitions. Histopathologic correlation studies are desired for its clinical use. Purpose To compare liver MRF-derived metrics with separate reference quantitative MRI in participants with diffuse liver disease, evaluate scan-rescan repeatability of liver MRF, and validate MRF-derived measurements for histologic grading of liver biopsies. Materials and Methods This prospective study included participants with diffuse liver disease undergoing MRI from July 2021 to January 2022. Participants underwent two-dimensional single-section liver MRF and separate reference quantitative MRI. Linear regression, Bland-Altman plots, and coefficients of variation were used to assess the bias and repeatability of liver MRF measurements. For participants undergoing liver biopsy, the association between mapping and histologic grading was evaluated by using the Spearman correlation coefficient. Results Fifty-six participants (mean age, 59 years ± 15 [SD]; 32 women) were included to compare mapping techniques and 23 participants were evaluated with liver biopsy (mean age, 52.7 years ± 12.7; 14 women). The linearity of MRF with reference measurements in participants with diffuse liver disease (R2 value) for T1, T2, T2*, and PDFF maps was 0.86, 0.88, 0.54, and 0.99, respectively. The overall coefficients of variation for repeatability in the liver were 3.2%, 5.5%, 7.1%, and 4.6% for T1, T2, T2*, and PDFF maps, respectively. MRF-derived metrics showed high diagnostic performance in differentiating moderate or severe changes from mild or no changes (area under the receiver operating characteristic curve for fibrosis, inflammation, steatosis, and siderosis: 0.62 [95% CI: 0.52, 0.62], 0.92 [95% CI: 0.88, 0.92], 0.97 [95% CI: 0.96, 0.97], and 0.74 [95% CI: 0.57, 0.74], respectively). Conclusion Liver MR fingerprinting provided repeatable T1, T2, T2*, and proton density fat fraction maps in high agreement with reference quantitative mapping and may correlate with pathologic grades in participants with diffuse liver disease. © RSNA, 2022 Online supplemental material is available for this article.

Motion-robust MR imaging of the shoulder using compressed SENSE MultiVane.

Purpose: Motion artifacts caused by breathing or involuntary motion of patients, which may lead to reduced image quality and a loss of diagnostic information, are a major problem in shoulder magnetic resonance imaging (MRI). The MultiVane (MV) technique decreases motion artifacts; however, it tends to prolong the acquisition time. As a parallel imaging technique, SENSitivity Encoding (SENSE) can be combined with the compressed sensing method to produce compressed SENSE (C-SENSE), resulting in a markedly reduced acquisition time. This study aimed to evaluate the use of C-SENSE MV for MRI of the shoulder joint. Methods: Thirty-one patients who were scheduled to undergo MRI of the shoulder were included. This prospective study was approved by our institution's medical ethics committee, and written informed consent was obtained from all 31 patients. Two sets of oblique coronal images derived from the standard protocol were acquired without (standard) or with C-SENSE MV: proton-density weighted imaging (PDWI), PDWI with C-SENSE MV, T2-weighted imaging (T2WI) with fat suppression (fs), and T2WI fs with C-SENSE MV. Two radiologists graded motion artifacts and the detectability of anatomical shoulder structures on a 4-point scale (3, no artifacts/excellent delineation; 0, severe artifacts/difficulty with delineation). The Wilcoxon signed-rank test was used to compare the data for the standard and C-SENSE MV images. Results: Motion artifacts were significantly reduced on the C-SENSE MV images (p < 0.001). Regarding the detectability of anatomical structures, the ratings for the C-SENSE MV sequences were significantly better (p < 0.001).In conclusion, in shoulder MRI the newly developed C-SENSE MV technique reduces motion artifacts and increases the detectability of anatomical structures compared with standard sequences.

Echo planar imaging with compressed sensitivity encoding (EPICS): Usefulness for head and neck diffusion-weighted MRI.

PURPOSE: To evaluate diffusion-weighted imaging (DWI) using echo planar imaging (EPI) with compressed SENSE (EPICS) of the head and neck magnetic resonance imaging (MRI). METHOD: We retrospectively observed 32 patients who underwent head and neck DWI according to either the conventional method (SENSE, reduction factor = 2), fast scanning method (SENSE, reduction factor = 4), or fast scanning method with EPICS (EPICS, reduction factor = 4). For quantitative analysis, contrast-to-noise-ratio (CNR), apparent diffusion coefficient (ADC) values, geometric distortion, and coefficient of variations (CV) were measured and compared. For qualitative analysis, all images were independently and blindly evaluated by two board-certified radiologists. RESULTS: EPICS revealed the higher CNR between all location compared to those of SENSE with reduction factor = 4. Distortion in the anterior-posterior direction was significantly lower on EPICS than on the conventional scan (p = 0.02). A comparison between the ADC values of the EPICS and conventional scan revealed no significant differences. The CV was significantly lower for EPICS than the conventional scan [DWI: 0.22 (IQR: 0.15-0.30) vs 0.32 (IQR: 0.24-0.40), p = 0.02]. CONCLUSIONS: Compressed SENSE combined with the high acceleration factor can improve image quality, homogeneity, and distortion in the head and neck DWI maintaining ADC values and the scan time duration.

The utility of diffusion-weighted T2 mapping for the prediction of histological tumor grade in patients with head and neck squamous cell carcinoma.

Background: In head and neck cancers, histopathological information is important for the determination of the tumor characteristics and for predicting the prognosis. The aim of this study was to assess the utility of diffusion-weighted T2 (DW-T2) mapping for the evaluation of tumor histological grade in patients with head and neck squamous cell carcinoma (SCC). Methods: The cases of 41 patients with head and neck SCC (21 well/moderately and 17 poorly differentiated SCC) were retrospectively analyzed. All patients received MR scanning using a 3-Tesla MR unit. The conventional T2 value, DW-T2 value, ratio of DW-T2 value to conventional T2 value, and apparent diffusion coefficient (ADC) were calculated using signal information from the DW-T2 mapping sequence with a manually placed region of interest (ROI). Results: ADC values in the poorly differentiated SCC group were significantly lower than those in the moderately/well differentiated SCC group (P<0.05). The ratio of DW-T2 value to conventional T2 value was also significantly different between poorly and moderately/well differentiated SCC groups (P<0.01). Receiver operating characteristic (ROC) curve analysis of ADC values showed a sensitivity of 0.76, specificity of 0.67, positive predictive value (PPV) of 0.62, negative predictive value (NPV) of 0.8, accuracy of 0.71 and area under the curve (AUC) of 0.73, whereas the ROC curve analysis of the ratio of DW-T2 value to conventional T2 value showed a sensitivity of 0.76, specificity of 0.83, PPV of 0.76, NPV of 0.83, accuracy of 0.8 and AUC of 0.82. Conclusions: DW-T2 mapping might be useful as supportive information for the determination of tumor histological grade in patients with head and neck SCC.

Evaluating of the Quality of Hepatic Diffusion Weighted Imaging Using Multiband Imaging With Variable-Rate Selective Excitation.

OBJECTIVE: To assess the image quality of diffusion-weighted imaging (DWI) using multiband (MB) imaging with variable-rate selective excitation (VERSE) and compare it to conventional DWI. METHODS: We retrospectively evaluated hepatic DWI images of patients (n = 76) according to either the conventional method (SENSE, acceleration factor = 2) (n = 38) or fast scanning method (MB imaging with VERSE, acceleration factor = 2 × 2) (n = 38). We also conducted a volunteer study (n = 15) for those scanning methods. During quantitative analysis, the signal-to-noise ratio (SNR), apparent diffusion coefficient values, and contrast in the liver, spleen, and spinal cord were compared between the 2 groups. During qualitative analysis, all images were independently and blindly evaluated by 2 board-certified radiologists. The image contrast, noise, artifacts, and sharpness were assessed, and the performance of classification was measured using receiver operating characteristic curve analysis. RESULTS: In the retrospective study, the SNRs of the hepatic parenchyma and spinal cord between the 2 protocols were significantly different (liver, 8.9 [interquartile range {IQR}, 7.6-12.2] vs 13.0 [IQR, 10.0-16.7]; P < 0.001 and spinal cord, 6.0 [IQR, 4.7-9.4] vs 4.3 [IQR, 3.8-6.8]; P < 0.02). No significant differences between the 2 protocols in the other retrospective analyses were noted. In the receiver operating characteristic curve analysis, area under the curve was 0.49 (95% confidence intervals, 0.40-0.58). CONCLUSION: Multiband VERSE reduced scan time and SNR of hepatic DWI; however, subjective image quality parameters were not significantly impacted.