Turbo Spin Echo Research Articles

B1 Power Modification for Amide Proton Transfer Imaging in Parotid Glands: A Strategy for Image Quality Accommodation and Evaluation of Tumor Detection Feasibility.

In the application of APTw protocols for evaluating tumors and parotid glands, inhomogeneity and hyperintensity artifacts have remained an obstacle. This study aimed to improve APTw imaging quality and evaluate the feasibility of difference B1 values to detect parotid tumors. A total of 31 patients received three APTw sequences to acquire 32 lesions and 30 parotid glands (one patient had lesions on both sides). Patients received T2WI and 3D turbo-spin-echo (TSE) APTw imaging on a 3.0 T scanner for three sequences (B1 = 2 μT, 1 μT, and 0.7 μT in APTw 1, 2, and 3, respectively). APTw image quality was evaluated using four-point Likert scales in terms of integrity and hyperintensity artifacts. Image quality was compared between the three sequences. An evaluable group and a trustable group were obtained for APTmean value comparison. Tumors in both APT2 and APT3 had fewer hyperintensity artifacts than in APT1. With B1 values decreasing, tumors had less integrity in APTw imaging. APTmean values of tumors were higher than parotid glands in traditional APT1 sequence though not significant, while the APTmean subtraction value was significantly different. Applying a lower B1 value could remove hyperintensity but could also compromise its integrity. Combing different APTw sequences might increase the feasibility of tumor detection.

Fast online spectral-spatial pulse design for subject-specific fat saturation in cervical spine and foot imaging at 1.5 T

ObjectiveTo compensate subject-specific field inhomogeneities and enhance fat pre-saturation with a fast online individual spectral-spatial (SPSP) single-channel pulse design.MethodsThe RF shape is calculated online using subject-specific field maps and a predefined excitation k-space trajectory. Calculation acceleration options are explored to increase clinical viability. Four optimization configurations are compared to a standard Gaussian spectral selective pre-saturation pulse and to a Dixon acquisition using phantom and volunteer (N = 5) data at 1.5 T with a turbo spin echo (TSE) sequence. Measurements and simulations are conducted across various body parts and image orientations.ResultsPhantom measurements demonstrate up to a 3.5-fold reduction in residual fat signal compared to Gaussian fat saturation. In vivo evaluations show improvements up to sixfold for dorsal subcutaneous fat in sagittal cervical spine acquisitions. The versatility of the tailored trajectory is confirmed through sagittal foot/ankle, coronal, and transversal cervical spine experiments. Additional measurements indicate that excitation field (B1) information can be disregarded at 1.5 T. Acceleration methods reduce computation time to a few seconds.DiscussionAn individual pulse design that primarily compensates for main field (B0) inhomogeneities in fat pre-saturation is successfully implemented within an online "push-button" workflow. Both fat saturation homogeneity and the level of suppression are improved.

Deep learning-accelerated image reconstruction in back pain-MRI imaging: reduction of acquisition time and improvement of image quality

IntroductionLow back pain is a global health issue causing disability and missed work days. Commonly used MRI scans including T1-weighted and T2-weighted images provide detailed information of the spine and surrounding tissues. Artificial intelligence showed promise in improving image quality and simultaneously reducing scan time. This study evaluates the performance of deep learning (DL)-based T2 turbo spin-echo (TSE, T2DLR) and T1 TSE (T1DLR) in lumbar spine imaging regarding acquisition time, image quality, artifact resistance, and diagnostic confidence.Material and methodsThis retrospective monocentric study included 60 patients with lower back pain who underwent lumbar spinal MRI between February and April 2023. MRI parameters and DL reconstruction (DLR) techniques were utilized to acquire images. Two neuroradiologists independently evaluated image datasets based on various parameters using a 4-point Likert scale.ResultsAccelerated imaging showed significantly less image noise and artifacts, as well as better image sharpness, compared to standard imaging. Overall image quality and diagnostic confidence were higher in accelerated imaging. Relevant disk herniations and spinal fractures were detected in both DLR and conventional images. Both readers favored accelerated imaging in the majority of examinations. The lumbar spine examination time was cut by 61% in accelerated imaging compared to standard imaging.ConclusionIn conclusion, the utilization of deep learning-based image reconstruction techniques in lumbar spinal imaging resulted in significant time savings of up to 61% compared to standard imaging, while also improving image quality and diagnostic confidence. These findings highlight the potential of these techniques to enhance efficiency and accuracy in clinical practice for patients with lower back pain.

Understanding Spatial Correlation Between Multiparametric MRI Performance and Prostate Cancer.

Multiparametric MRI (mpMRI) has shown a substantial impact on prostate cancer (PCa) diagnosis. However, the understanding of the spatial correlation between mpMRI performance and PCa location is still limited. To investigate the association between mpMRI performance and tumor spatial location within the prostate using a prostate sector map, described by Prostate Imaging Reporting and Data System (PI-RADS) v2.1. Retrospective. One thousand one hundred forty-three men who underwent mpMRI before radical prostatectomy between 2010 and 2022. 3.0 T. T2-weighted turbo spin-echo, a single-shot spin-echo EPI sequence for diffusion-weighted imaging, and a gradient echo sequence for dynamic contrast-enhanced MRI sequences. Integrated relative cancer prevalence (rCP), detection rate (DR), and positive predictive value (PPV) maps corresponding to the prostate sector map for PCa lesions were created. The relationship between tumor location and its detection/missing by radiologists on mpMRI compared to WMHP as a reference standard was investigated. A weighted chi-square test was performed to examine the statistical differences for rCP, DR, and PPV of the aggregated sectors within the zone, anterior/posterior, left/right prostate, and different levels of the prostate with a statistically significant level of 0.05. A total of 1665 PCa lesions were identified in 1143 patients, and from those 1060 lesions were clinically significant (cs)PCa tumors (any Gleason score [GS] ≥7). Our sector-based analysis utilizing weighted chi-square tests suggested that the left posterior part of PZ had a high likelihood of missing csPCa lesions at a DR of 67.0%. Aggregated sector analysis indicated that the anterior or apex locations in PZ had the significantly lowest csPCa detection at 67.3% and 71.5%, respectively. Spatial characteristics of the per-lesion-based mpMRI performance for diagnosis of PCa were studied. Our results demonstrated that there is a spatial correlation between mpMRI performance and locations of PCa on the prostate. 4 TECHNICAL EFFICACY: Stage 2.

Deep learning-accelerated T2-weighted imaging versus conventional T2-weighted imaging in the female pelvic cavity: image quality and diagnostic performance.

The deep learning (DL)-based reconstruction algorithm reduces noise in magnetic resonance imaging (MRI), thereby enabling faster MRI acquisition. To compare the image quality and diagnostic performance of conventional turbo spin-echo (TSE) T2-weighted (T2W) imaging with DL-accelerated sagittal T2W imaging in the female pelvic cavity. This study evaluated 149 consecutive female pelvic MRI examinations, including conventional T2W imaging with TSE (acquisition time = 2:59) and DL-accelerated T2W imaging with breath hold (DL-BH) (1:05 [0:14 × 3 breath-holds]) in the sagittal plane. In 294 randomly ordered sagittal T2W images, two radiologists independently assessed image quality (sharpness, subjective noise, artifacts, and overall image quality), made a diagnosis for uterine leiomyomas, and scored diagnostic confidence. For the uterus and piriformis muscle, quantitative imaging analysis was also performed. Wilcoxon signed rank tests were used to compare the two sets of T2W images. In the qualitative analysis, DL-BH showed similar or significantly higher scores for all features than conventional T2W imaging (P <0.05). In the quantitative analysis, the noise in the uterus was lower in DL-BH, but the noise in the muscle was lower in conventional T2W imaging. In the uterus and muscle, the signal-to-noise ratio was significantly lower in DL-BH than in conventional T2W imaging (P <0.001). The diagnostic performance of the two sets of T2W images was not different for uterine leiomyoma. DL-accelerated sagittal T2W imaging obtained with three breath-holds demonstrated superior or comparable image quality to conventional T2W imaging with no significant difference in diagnostic performance for uterine leiomyomas.

In-phase and opposed-phase Dixon chemical shift imaging for the assessment of skeletal marrow lesions: comparison of measurements from longitudinal sequences to those from axial sequences.

In-phase and opposed-phase chemical shift imaging (CSI) is a useful technique for assessing skeletal lesions. This study determined the frequency of significant differences in measurements obtained from longitudinal (coronal or sagittal) sequences to those obtained from axial sequences. Chemical shift imaging was undertaken in 96 consecutive patients referred from the Musculoskeletal Sarcoma and Spinal Oncology services for assessment of possible bone tumours as part of a standard tumour protocol, which included turbo spin echo and inversion recovery sequences. For spinal lesions, CSI was obtained in the sagittal and axial planes, while for all other sites, it was obtained in the coronal and axial planes. The study included 49 (51.0%) males and 47 (49.0%) females with mean age 42.4 years (range 2-91 years). In 4 cases, 2 individual lesions were assessed, making a total of 100 lesions. Based on typical imaging features (n = 57) or histology (n = 43), 22 lesions (22%) were classified as non-neoplastic, 44 (44%) as benign neoplasms, 6 (6%) as intermediate-grade neoplasms, and 28 (28%) as malignant neoplasms. A significant discrepancy, wherein a lesion was classified as fat-containing (% SI drop >20%-25%) in the longitudinal plane, while in the axial plane it was classified as fat-replacing (% SI drop <20%-25%), or vice versa, occurred in 9%-14% of cases. However, this discrepancy had no appreciable effect on overall diagnostic accuracy, which was calculated at 79% for the longitudinal plane and 75%-80% for the axial plane. Significant differences in CSI measurements occur in 9%-14% of cases based on imaging plane, but with no significant effect on diagnostic accuracy. Radiologists should be aware that CSI measurements in different planes appear to have significant differences in up to 14% of lesions. However, diagnostic accuracy does not seem to be significantly affected.

Feasibility of deep learning-reconstructed thin-slice single-breath-hold HASTE for detecting pancreatic lesions: A comparison with two conventional T2-weighted imaging sequences

ObjectiveThe objective of this study was to evaluate the clinical feasibility of deep learning reconstruction-accelerated thin-slice single-breath-hold half-Fourier single-shot turbo spin echo imaging (HASTEDL) for detecting pancreatic lesions, in comparison with two conventional T2-weighted imaging sequences: compressed-sensing HASTE (HASTECS) and BLADE. MethodsFrom March 2022 to January 2023, a total of 63 patients with suspected pancreatic-related disease underwent the HASTEDL, HASTECS, and BLADE sequences were enrolled in this retrospectively study. The acquisition time, the pancreatic lesion conspicuity (LCP), respiratory motion artifact (RMA), main pancreatic duct conspicuity (MPDC), overall image quality (OIQ), signal-to-noise ratio (SNR), and contrast-noise-ratio (CNR) of the pancreatic lesions were compared among the three sequences by two readers. ResultsThe acquisition time of both HASTEDL and HASTECS was 16 s, which was significantly shorter than that of 102 s for BLADE. In terms of qualitative parameters, Reader 1 and Reader 2 assigned significantly higher scores to the LCP, RMA, MPDC, and OIQ for HASTEDL compared to HASTECS and BLADE sequences; As for the quantitative parameters, the SNR values of the pancreatic head, body, tail, and lesions, the CNR of the pancreatic lesion measured by the two readers were also significantly higher for HASTEDL than for HASTECS and BLADE sequences. ConclusionsCompared to conventional T2WI sequences (HASTECS and BLADE), deep-learning reconstructed HASTE enables thin slice and single-breath-hold acquisition with clinical acceptable image quality for detection of pancreatic lesions.

Unsupervised motion artifact correction of turbo spin-echo MRI using deep image prior.

In MRI, motion artifacts can significantly degrade image quality. Motion artifact correction methods using deep neural networks usually required extensive training on large datasets, making them time-consuming and resource-intensive. In this paper, an unsupervised deep learning-based motion artifact correction method for turbo-spin echo MRI is proposed using the deep image prior framework. The proposed approach takes advantage of the high impedance to motion artifacts offered by the neural network parameterization to remove motion artifacts in MR images. The framework consists of parameterization of MR image, automatic spatial transformation, and motion simulation model. The proposed method synthesizes motion-corrupted images from the motion-corrected images generated by the convolutional neural network, where an optimization process minimizes the objective function between the synthesized images and the acquired images. In the simulation study of 280 slices from 14 subjects, the proposed method showed a significant increase in the averaged structural similarity index measure by 0.2737 in individual coil images and by 0.4550 in the root-sum-of-square images. In addition, the ablation study demonstrated the effectiveness of each proposed component in correcting motion artifacts compared to the corrected images produced by the baseline method. The experiments on real motion dataset has shown its clinical potential. The proposed method exhibited significant quantitative and qualitative improvements in correcting rigid and in-plane motion artifacts in MR images acquired using turbo spin-echo sequence.

Interrelation Between Cerebrospinal Fluid Pressure, Intracranial Morphology and Venous Hemodynamics Studied by 4D Flow MRI.

To quantify the effects of CSF pressure alterations on intracranial venous morphology and hemodynamics in idiopathic intracranial hypertension (IIH) and spontaneous intracranial hypotension (SIH) and assess reversibility when the underlying cause is resolved. We prospectively examined venous volume, intracranial venous blood flow and velocity, including optic nerve sheath diameter (ONSD) as anoninvasive surrogate of CSF pressure changes in 11 patients with IIH, 11 age-matched and sex-matched healthy controls and 9 SIH patients, before and after neurosurgical closure of spinal dural leaks. We applied multiparametric MRI including 4D flow MRI, time-of-flight (TOF) and T2-weighted half-Fourier acquisition single-shot turbo-spin echo (HASTE). Sinus volume overlapped between groups at baseline but decreased after treatment of intracranial hypotension (p = 0.067) along with asignificant increase of ONSD (p = 0.003). Blood flow in the middle and dorsal superior sagittal sinus was remarkably lower in patients with higher CSF pressure (i.e., IIH versus controls and SIH after CSF leak closure) but blood flow velocity was comparable cross-sectionally between groups and longitudinally in SIH. We were able to demonstrate the interaction of CSF pressure, venous volumetry, venous hemodynamics and ONSD using multiparametric brain MRI. Closure of CSF leaks in SIH patients resulted in symptoms suggestive of increased intracranial pressure and caused asubsequent decrease of intracranial venous volume and of blood flow within the superior sagittal sinus while ONSD increased. In contrast, blood flow parameters from 4D flow MRI did not discriminate IIH, SIH and controls as hemodynamics at baseline overlapped at most vessel cross-sections.

Lax Uterosacral Ligament and Urge Urinary Incontinence: MRI Findings in Symptomatic Patients Versus Healthy Volunteers

Introduction and hypothesisThe objective was to explore the association between urge urinary incontinence (UUI) and lax uterosacral ligaments (USL) using MRI.MethodsSixty-seven female participants were recruited prospectively: 41 continent volunteers (control group) and 26 patients with UUI. Static proton density- and T2-weighted turbo spin echo sequences of MR images were used. A radiologist employed a standardized grid system to record structural observations of the USLs on sequentially numbered axial MR images and then applied a four-point grading scale to assess ligament visibility. MR images were interpreted by a radiologist and a urologist, and then validated by an expert radiologist.ResultsThe comparison between the mean length of uterosacral ligaments in the control and UUI groups was highly statistically significant (p < 0.001). The mean length of the right USL was 38 ± 11 mm, and the left USL was 35 ± 12 mm in the UUI group. In the control group, the mean length of the USL was 22 ± 9 mm on the right side and 18 ± 9 mm on the left side, along their craniocaudal extent. The highest inter-observer agreement was on the level of origin and insertion (image numbers), whereas the lowest agreement was on the anatomical site of origin and insertion of the USL in both the control and UUI groups.ConclusionsThe average length of USLs in patients with UUI is significantly longer than that in healthy continent women, indicating laxity. Our findings support the relationship between the laxity of the USL and UUI symptoms and have therapeutic implications.

Sorting lung tumor volumes from 4D-MRI data using an automatic tumor-based signal reduces stitching artifacts.

To investigate whether a novel signal derived from tumor motion allows more precise sorting of 4D-magnetic resonance (4D-MR) image data than do signals based on normal anatomy, reducing levels of stitching artifacts within sorted lung tumor volumes. (4D-MRI) scans were collected for 10 lung cancer patients using a 2D T2-weighted single-shot turbo spin echo sequence, obtaining 25 repeat frames per image slice. For each slice, a tumor-motion signal was generated using the first principal component of movement in the tumor neighborhood (TumorPC1). Signals were also generated from displacements of the diaphragm (DIA) and upper and lower chest wall (UCW/LCW) and from slice body area changes (BA). Pearson r coefficients of correlations between observed tumor movement and respiratory signals were determined. TumorPC1, DIA, and UCW signals were used to compile image stacks showing each patient's tumor volume in a respiratory phase. Unsorted image stacks were also built for comparison. For each image stack, the presence of stitching artifacts was assessed by measuring the roughness of the compiled tumor surface according to a roughness metric (Rg). Statistical differences in weighted means of Rg between any two signals were determined using an exact permutation test. The TumorPC1 signal was most strongly correlated with superior-inferior tumor motion, and had significantly higher Pearson r values (median 0.86) than those determined for correlations of UCW, LCW, and BA with superior-inferior tumor motion (p<0.05). Weighted means of ratios of Rg values in TumorPC1 image stacks to those in unsorted, UCW, and DIA stacks were 0.67, 0.69, and 0.71, all significantly favoring TumorPC1 (p=0.02-0.05). For other pairs of signals, weighted mean ratios did not differ significantly from one. Tumor volumes were smoother in 3D image stacks compiled using the first principal component of tumor motion than in stacks compiled with signals based on normal anatomy.

Vessel density mapping of small cerebral vessels on 3D high resolution black blood MRI

Small cerebral blood vessels are largely inaccessible to existing clinical in vivo imaging technologies. This study aims to present a novel analysis pipeline for vessel density mapping of small cerebral blood vessels from high-resolution 3D black-blood MRI at 3T. Twenty-eight subjects (10 under 35 years old, 18 over 60 years old) were imaged with the T1-weighted turbo spin-echo with variable flip angles (T1w TSE-VFA) sequence optimized for black-blood small vessel imaging with iso-0.5 mm spatial resolution (interpolated from 0.51×0.51×0.64 mm3) at 3T. Hessian-based vessel segmentation methods (Jerman, Frangi and Sato filter) were evaluated by vessel landmarks and manual annotation of lenticulostriate arteries (LSAs). Using optimized vessel segmentation, large vessel pruning and non-linear registration, a semiautomatic pipeline was proposed for quantification of small vessel density across brain regions and further for localized detection of small vessel changes across populations. Voxel-level statistics was performed to compare vessel density between two age groups. Additionally, local vessel density of aged subjects was correlated with their corresponding gross cognitive and executive function (EF) scores using Montreal Cognitive Assessment (MoCA) and EF composite scores compiled with Item Response Theory (IRT). Jerman filter showed better performance for vessel segmentation than Frangi and Sato filter which was employed in our pipeline. Small cerebral blood vessels including small artery, arterioles, small veins, and venules on the order of a few hundred microns can be delineated using the proposed analysis pipeline on 3D black-blood MRI at 3T. The mean vessel density across brain regions was significantly higher in young subjects compared to aged subjects. In the aged subjects, localized vessel density was positively correlated with MoCA and IRT EF scores. The proposed pipeline is able to segment, quantify, and detect localized differences in vessel density of small cerebral blood vessels based on 3D high-resolution black-blood MRI. This framework may serve as a tool for localized detection of small vessel density changes in normal aging and cerebral small vessel disease.

Quantifying 3D MR fingerprinting (3D-MRF) reproducibility across subjects, sessions, and scanners automatically using MNI atlases.

Quantitative MRI techniques such as MR fingerprinting (MRF) promise more objective and comparable measurements of tissue properties at the point-of-care than weighted imaging. However, few direct cross-modal comparisons of MRF's repeatability and reproducibility versus weighted acquisitions have been performed. This work proposes a novel fully automated pipeline for quantitatively comparing cross-modal imaging performance in vivo via atlas-based sampling. We acquire whole-brain 3D-MRF, turbo spin echo, and MPRAGE sequences three times each on two scanners across 10 subjects, for a total of 60 multimodal datasets. The proposed automated registration and analysis pipeline uses linear and nonlinear registration to align all qualitative and quantitative DICOM stacks to Montreal Neurological Institute (MNI) 152 space, then samples each dataset's native space through transformation inversion to compare performance within atlas regions across subjects, scanners, and repetitions. Voxel values within MRF-derived maps were found to be more repeatable (σT1 = 1.90, σT2 = 3.20) across sessions than vendor-reconstructed MPRAGE (σT1w = 6.04) or turbo spin echo (σT2w = 5.66) images. Additionally, MRF was found to be more reproducible across scanners (σT1 = 2.21, σT2 = 3.89) than either qualitative modality (σT1w = 7.84, σT2w = 7.76). Notably, differences between repeatability and reproducibility of in vivo MRF were insignificant, unlike the weighted images. MRF data from many sessions and scanners can potentially be treated as a single dataset for harmonized analysis or longitudinal comparisons without the additional regularization steps needed for qualitative modalities.

Deep learning-accelerated image reconstruction in MRI of the orbit to shorten acquisition time and enhance image quality.

This study explores the use of deep learning (DL) techniques in MRI of the orbit to enhance imaging. Standard protocols, although detailed, have lengthy acquisition times. We investigate DL-based methods for T2-weighted and T1-weighted, fat-saturated, contrast-enhanced turbo spin echo (TSE) sequences, aiming to improve image quality, reduce acquisition time, minimize artifacts, and enhance diagnostic confidence in orbital imaging. In a 3-Tesla MRI study of 50 patients evaluating orbital diseases from March to July 2023, conventional (TSES ) and DL TSE sequences (TSEDL ) were used. Two neuroradiologists independently assessed the image datasets for image quality, diagnostic confidence, noise levels, artifacts, and image sharpness using a randomized and blinded 4-point Likert scale. TSEDL significantly reduced image noise and artifacts, enhanced image sharpness, and decreased scan time, outperforming TSES (p<.05). TSEDL showed superior overall image quality and diagnostic confidence, with relevant findings effectively detected in both DL-based and conventional images. In 94% of cases, readers preferred accelerated imaging. The study proved that using DL for MRI image reconstruction in orbital scans significantly cut acquisition time by 69%. This approach also enhanced image quality, reduced image noise, sharpened images, and boosted diagnostic confidence.

7 T Lesion-Attenuated Magnetization-Prepared Gradient Echo Acquisition for Detection of Posterior Fossa Demyelinating Lesions in Multiple Sclerosis.

Detection of infratentorial demyelinating lesions in multiple sclerosis (MS) presents a challenge in magnetic resonance imaging (MRI), a difficulty that is further heightened in 7 T MRI. This study aimed to assess the efficacy of a novel MRI approach, lesion-attenuated magnetization-prepared gradient echo acquisition (LAMA), for detecting demyelinating lesions within the posterior fossa and upper cervical spine on 7 T MRI and contrast its performance with conventional double-inversion recovery (DIR) and T2-weighted turbo spin echo sequences. We conducted a retrospective cross-sectional study in 42 patients with a confirmed diagnosis of MS. All patients had 7 T MRI that incorporated LAMA, 3D DIR, and 2D T2-weighted turbo spin echo sequences. Three readers assessed lesion count in the brainstem, cerebellum, and upper cervical spinal cord using both DIR and T2-weighted images in one session. In a separate session, LAMA was analyzed alone. Contrast-to-noise ratio was also compared between LAMA and the conventional sequences. Lesion counts between methods were assessed using nonparametric Wilcoxon signed rank test. Interrater agreement in lesion detection was estimated by intraclass correlation coefficients. LAMA identified a significantly greater number of lesions than DIR + T2 (mean 6.4 vs 3.0; P < 0.001). LAMA also exhibited better interrater agreement (intraclass correlation coefficient [95% confidence interval], 0.75 [0.41-0.88] vs 0.61 [0.35-0.78]). The contrast-to-noise ratio for LAMA (3.7 ± 0.9) significantly exceeded that of DIR (1.94 ± 0.7) and T2 (1.2 ± 0.7) (all P 's < 0.001). In cases with no lesions detected using DIR + T2, at least 1 lesion was identified in 83.3% with LAMA. Across all analyzed brain regions, LAMA consistently detected more lesions than DIR + T2. LAMA significantly improves the detection of infratentorial demyelinating lesions in MS patients compared with traditional methods. Integrating LAMA with standard magnetization-prepared 2 rapid acquisition gradient echo acquisition provides a valuable tool for accurately characterizing the extent of MS disease.

Evaluation of Three Imaging Methods to Quantify Key Events in Pelvic Bone Metastasis.

The purpose of this study is to compare turbo spin echo diffusion-weighted images in radial trajectory (BLADE DWI) with multi-shot echoplanar imaging (RESOLVE DWI) for imaging the metastatic lesion in the pelvic bone to find a correlation between ADC values and standardized uptake values (SUVs) of FDG uptake in PET/CT. The study also seeks to compare the values of metastatic lesions with those of benign bone lesions, specifically red marrow hyperplasia. The retrospective IRB-approved study included patients with bone metastasis and red marrow hyperplasia in the pelvic bone who underwent 3.0 T MRI with BLADE/RESOLVE DWI sequences and F-18 FDG PET/CT within one month. BVC (best value comparator) was used in determining the nature of bone lesions. Apparent diffusion coefficient (ADC) and standardized uptake value (SUV) were measured by a radiologist and a nuclear medicine physician. MRI image quality was graded with a Likert scale regarding the visualization of the sacroiliac joint, sacral neural foramen, hamstring tendon at ischial tuberosity, and tumor border. Signal-to-noise ratio (SNR) and imaging time were compared between the two DWIs. Mean, peak, and maximum SUVs between metastatic and benign red marrow lesions were compared. SUVs and ADC values were compared. AUROC analyses and cut-off values were obtained for each parameter. Mann-Whitney U, Spearman's rho, and Kolmogorov-Smirnov tests were applied using SPSS. The final study group included 58 bone lesions (19 patients (male: female = 6:13, age 52.5 ± 9.6, forty-four (75.9%) bone metastasis, fourteen (24.1%) benign red marrow hyperplasia). ADCs from BLADE and RESOLVE were significantly higher in bone metastasis than red marrow hyperplasia. BLADE showed higher ADC values, higher anatomical scores, and higher SNR than RESOLVE DWI (p < 0.05). Imaging times were longer for BLADE than RESOLVE (6 min 3 s vs. 3 min 47 s, p < 0.05). There was a poor correlation between ADC values and SUVs (correlation coefficient from 0.04 to 0.31). The AUROC values of BLADE and RESOLVE MRI ranged from 0.892~0.995. Those of PET ranged from 0.877~0.895. The cut-off ADC values between the bone metastasis and red marrow hyperplasia were 355.0, 686.5, 531.0 for BLADE min, max, and average, respectively, and 112.5, 737.0, 273.0 for RESOLVE min, max, and average, respectively. The cut-off SUV values were 1.84, 5.01, and 3.81 for mean, peak, and max values, respectively (p < 0.05). Compared with RESOLVE DWI, BLADE DWI showed improved image quality of pelvic bone MRI in the aspect of anatomical depiction and SNR, higher ADC values, albeit longer imaging time. BLADE and RESOLVE could differentiate bone metastasis and red marrow hyperplasia with quantifiable cut-off values. Further study is necessary to evaluate the discrepancy between the quantifiers between PET and MRI.

Prospective Comparison of Standard and Deep Learning-reconstructed Turbo Spin-Echo MRI of the Shoulder.

Background Deep learning (DL)-based MRI reconstructions can reduce imaging times for turbo spin-echo (TSE) examinations. However, studies that prospectively use DL-based reconstructions of rapidly acquired, undersampled MRI in the shoulder are lacking. Purpose To compare the acquisition time, image quality, and diagnostic confidence of DL-reconstructed TSE (TSEDL) with standard TSE in patients indicated for shoulder MRI. Materials and Methods This prospective single-center study included consecutive adult patients with various shoulder abnormalities who were clinically referred for shoulder MRI between February and March 2023. Each participant underwent standard TSE MRI (proton density- and T1-weighted imaging; conventional TSE sequence was used as reference for comparison), followed by a prospectively undersampled accelerated TSEDL examination. Six musculoskeletal radiologists evaluated images using a four-point Likert scale (1, poor; 4, excellent) for overall image quality, perceived signal-to-noise ratio, sharpness, artifacts, and diagnostic confidence. The frequency of major pathologic features and acquisition times were also compared between the acquisition protocols. The intergroup comparisons were performed using the Wilcoxon signed rank test. Results Overall, 135 shoulders in 133 participants were evaluated (mean age, 47.9 years ± 17.1 [SD]; 73 female participants). The median acquisition time of the TSEDL protocol was lower than that of the standard TSE protocol (288 seconds [IQR, 288-288 seconds] vs 926 seconds [IQR, 926-950 seconds], respectively; P < .001), achieving a 69% lower acquisition time. TSEDL images were given higher scores for overall image quality, perceived signal-to-noise ratio, and artifacts (all P < .001). Similar frequency of pathologic features (P = .48 to > .99), sharpness (P = .06), or diagnostic confidence (P = .05) were noted between images from the two protocols. Conclusion In a clinical setting, TSEDL led to reduced examination time and higher image quality with similar diagnostic confidence compared with standard TSE MRI in the shoulder. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Chang and Chow in this issue.

Can Three-Dimensional T1-weighted MR Imaging Visualize the Vascular Lumen after Carotid Artery Stenting?

We aimed to evaluate the quality of various 3D T1-weighted images (T1WIs) of the stent lumen using a carotid stent phantom and determine the suitable T1WI sequence for visualization of the stent lumen after carotid artery stenting. The carotid stent phantom consisted of polypropylene tubes that mimicked common carotid arteries with and without stenting. On 1.5T and 3.0T MRI scanners, transverse T1WIs of the carotid stent phantom were obtained using 3D turbo spin-echo (TSE), 3D fast field-echo (3D-FFE), and 3D turbo field echo volumetric interpolated breath-hold examination (VIBE) under clinical conditions. The signal intensity ratio (SIR) was determined using the mean signal intensity of the stent lumen (SIstent) divided by the lumen without a stent in each T1WI. The SNR of the stent lumen (SNRstent) was calculated from SIstent divided by the standard deviation of the uniform region near the stent lumen. The 3D-FFE and VIBE had higher SNRstent than other T1WIs and clearly visualized the stent lumen. The 3D-TSE had the lowest SIR and SNRstent, preventing stent lumen visualization. T1WIs obtained using 3D-FFE and VIBE allows stent lumen visualization.

Prediction of diabetes insipidus occurrence after endoscopic endonasal removal of sellar lesions using MRI-based radiomics and machine learning.

Pituitary adenomas and craniopharyngiomas are the most common lesions of the sellar region. These tumors are responsible for invasion or compression of crucial neurovascular structures. The involvement of the pituitary stalk warrants high rates of both pre- and post- operative diabetes insipidus. The aim of our study was to assess the accuracy of machine learning analysis from preoperative MRI of pituitary adenomas and craniopharyngiomas for the prediction of DI occurrence. All patients underwent MRI exams either on a 1.5- or 3-T MR scanner from two Institutions, including coronal T2-weighted (T2-w) and contrast-enhanced T1-weighted (CE T1-w) Turbo Spin Echo sequences. Feature selection was carried out as a multi-step process, with a threshold of 0.75 to identify robust features. Further feature selection steps included filtering based on feature variance (threshold >0.01) and pairwise correlation (threshold <0.80). A Bayesian Network model was trained with 10-fold cross validation employing SMOTE to balance classes exclusively within the training folds. Thirty patients were included in this study. In total 2394 features were extracted and 1791 (75%) resulted stable after ICC analysis. The number of variant features was 1351 and of non-colinear features was 125. Finally, 10 features were selected by oneR ranking. The Bayesian Network model showed an accuracy of 63% with a precision of 77% for DI prediction (0.68 area under the precision-recall curve). We assessed the accuracy of machine learning analysis of texture-derived parameters from preoperative MRI of pituitary adenomas and craniopharyngiomas for the prediction of DI occurrence.

Evaluation of Refocus Flip Angle for Three-dimensional Proton Density-weighted Turbo Spin-echo Imaging in Cerebrovascular Black Blood MRA and Comparison with Three-dimensional Time-of-flight MRA

The three-dimensional time-of-flight (3D-TOF), which is currently the most common acquisition technique of intracranial magnetic resonance angiography (MRA), may result in poor branch visualization due to reduced blood flow velocity. Proton density-weighted volume isotropic turbo spin-echo acquisition (PDVISTA) is less susceptible to these factors and has been reported to be useful in assessing cerebral vasospasm after subarachnoid hemorrhage. In this study, we investigated the effect of refocus flip angle (RFA) for PDVISTA on the contrast between blood vessels and background brain tissue using flow velocity phantom and clinical images, assuming the usefulness of PDVISTA in daily clinical practice. The phantom experiments showed that the contrast ratio significantly improved with decreasing RFA; however, considering the signal-to-noise ratio, RFA 80° was determined as optimal for clinical use. Visual assessment was performed on PDVISTA (RFA 80°) and conventional 3D-TOF MRA clinical images, which suggested the superiority of PDVISTA over 3D-TOF in the delineation of peripheral branches of cerebral vessels. The results suggest that PDVISTA is useful not only for subarachnoid hemorrhage patients but also in daily clinical practice.