Prostate T2-weighted spin-echo MRI with and without glucagon: a paired scan quality assessment.

Purpose To evaluate the effectiveness of subcutaneous glucagon in reducing motion artifact during prostate MRI through intraindividual comparison. Methods At our institution patients undergoing a clinical prostate MRI exam receive 1 mg of subcutaneous glucagon before scanning. From February 15, 2024 to February 11, 2025 33 such patients were recruited to undergo an additional, research exam without glucagon. All exams were acquired at 3T. An axial T2-weighted spin-echo series (T2-WI) was acquired within both exams. Evaluation of the T2-WI series was done by three experienced radiologists using the criteria of diagnostic quality (0–3 scale), PI-QUALv2 (0–3 sum), motion artifact (significant, visible, none), and reviewer preference (five-point relative scale). Due to differences in prescribed coverage, the scan times for the two T2-WI sequences were in general different for each subject. Results were stratified using the acquisition time ratio (Trel) between the glucagon vs. non-glucagon scans. Wilcoxon tests assessed score differences. Results Across all 33 subjects, no significant differences were found between glucagon and non-glucagon scans. However, the observed negative correlation between glucagon preference and Trel (p = 0.026) led to stratification into low-Trel (n = 16) and high-Trel (n = 17) groups. In the low-Trel group the glucagon scans provided significantly improved diagnostic quality (p = 0.048), PI-QUALv2 sum (p = 0.049), motion scores (p = 0.047), and reader preference (p = 0.042). Conclusion Subcutaneous glucagon provides improved image quality in prostate T2-WI MRI when scan duration remains within 1.25× of that of a non-glucagon T2-WI series. The benefit appears to decrease with longer scan times.

To evaluate the diagnostic interchangeability, image quality, and scan time of deep learning (DL)-reconstructed magnetic resonance imaging (MRI) compared with conventional MRI for the temporomandibular joint (TMJ). Patients with suspected TMJ disorder underwent sagittal proton density-weighted (PDW) and T2-weighted fat-suppressed (T2W FS) MRI using both conventional and DL reconstruction protocols in a single session. Three oral radiologists independently assessed disc shape, disc position, and joint effusion. Diagnostic interchangeability for these findings was evaluated by comparing interobserver agreement, with equivalence defined as a 95% confidence interval (CI) within ±5%. Qualitative image quality (sharpness, noise, artifacts, overall) was rated on a 5-point scale. Quantitative image quality was assessed by measuring the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in the condyle, disc, and background air. Image quality scores were compared using the Wilcoxon signed-rank test, and SNR/CNR using paired t-tests. Scan times were directly compared. A total of 176 TMJs from 88 patients (mean age, 37 ± 16 years; 43 men) were analyzed. DL-reconstructed MRI demonstrated diagnostic equivalence to conventional MRI for disc shape, position, and effusion (equivalence indices < 3%; 95% CIs within ±5%). DL reconstruction significantly reduced noise in PDW and T2W FS sequences (p < 0.05) while maintaining sharpness and artifact levels. SNR and CNR were significantly improved (p < 0.05), except for disc SNR in PDW (p = 0.189). Scan time was reduced by 49.2%. DL-reconstructed TMJ MRI is diagnostically interchangeable with conventional MRI, offering improved image quality with a shorter scan time. Question Long MRI scan times in patients with temporomandibular disorders can increase pain and motion-related artifacts, often compromising image quality in diagnostic settings. Findings DL reconstruction is diagnostically interchangeable with conventional MRI for assessing disc shape, disc position, and effusion, while improving image quality and reducing scan time. Clinical relevance DL reconstruction enables faster and more tolerable TMJ MRI workflows without compromising diagnostic accuracy, facilitating broader adoption in clinical settings where long scan times and motion artifacts often limit diagnostic efficiency.

The use of MR imaging in emergency settings has been limited by availability, long scan times, and sensitivity to motion. This study assessed the diagnostic performance of an ultrafast brain MR imaging protocol for evaluation of acute intracranial pathology in the emergency department and inpatient settings. Sixty-six adult patients who underwent brain MR imaging in the emergency department and inpatient settings were included in the study. All patients underwent both the reference and the ultrafast brain MR protocols. Both brain MR imaging protocols consisted of T1-weighted, T2/T2*-weighted, FLAIR, and DWI sequences. The ultrafast MR images were reconstructed by using a machine-learning assisted framework. All images were reviewed by 2 blinded neuroradiologists. The average acquisition time was 2.1 minutes for the ultrafast brain MR protocol and 10 minutes for the reference brain MR protocol. There was 98.5% agreement on the main clinical diagnosis between the 2 protocols. In head-to-head comparison, the reference protocol was preferred in terms of image noise and geometric distortion (P < .05 for both). The ultrafast ms-EPI protocol was preferred over the reference protocol in terms of reduced motion artifacts (P < .01). Overall diagnostic quality was not significantly different between the 2 protocols (P > .05). The ultrafast brain MR imaging protocol provides high accuracy for evaluating acute pathology while only requiring a fraction of the scan time. Although there was greater image noise and geometric distortion on the ultrafast brain MR protocol images, there was significant reduction in motion artifacts with similar overall diagnostic quality between the 2 protocols.

BackgroundProstate imaging reporting and data system (PI-RADS) v2.1 guidelines for magnetic resonance imaging acquisition define a standard of 0.40 mm × 0.70 mm in-plane resolution (0.280 mm2 pixel area), but adherence has been challenging. We questioned if a modification of a PI-RADS-adherent T2-weighted (T2WI) sequence to one having equivalent pixel area could allow reduced acquisition time but provide improved diagnostic quality (DQ).MethodsAn adherent T2WI sequence was modified by reducing the frequency sampling, thereby reducing the signal bandwidth (BW). This was compensated by increasing the phase sampling for an equivalent pixel area (0.50 mm × 0.57 mm = 0.285 mm2). The BW reduction allowed a two-fold reduction in averaging, also enabling reduced acquisition time. The adherent and modified sequences were evaluated in phantoms and 62 consecutive prostate MRI subjects. Images were evaluated individually by four radiologists using a four-point DQ scale and using prostate imaging quality (PI-QUAL)v2. Each reviewer also indicated any sequence preference. The Wilcoxon test was used.ResultsIn the phantom, mean signal-to-noise ratios were equivalent for the two sequences; superior frequency resolution for the adherent sequence, and superior phase resolution for the modified sequence were shown. Across 62 participants, the median acquisition time was reduced by 23%, from 3:55 min:s to 3:01 min:s. For all three means of comparison (DQ, PI-QUALv2, reader preference), the modified sequence was significantly superior (p ≤ 0.037).ConclusionModification of the PI-RADS standard (0.40-mm frequency resolution) to an equivalent, more isotropic pixel area (0.28 mm2) reduced acquisition time and improved image quality.Relevance statementGeneralization of the PI-RADSv.2.1 minimum technical standard for T2WI in-plane resolution to be more isotropic preserves the targeted high resolution, allowing reduced acquisition time, also reducing motion sensitivity, and improving image quality. This approach may also reduce the need for rescanning poor-quality sequences.Key PointsPI-RADSv2.1 suggests a standard T2WI sequence with 0.40 × 0.70 mm2 in-plane resolution.A modified PI-RADSv.2.1-adherent T2WI sequence with equivalent but more isotropic pixel area (0.50 × 0.57 mm2) allowed reduced scan times by 23% and significantly improved DQ.Superiority of the modified sequence appears due to reduced motion sensitivity.Graphical

Practical Strategies to Reduce Pediatric CT Radiation Dose

Optical mapping is a high-resolution fluorescence imaging technique, which provides highly detailed visualizations of the electrophysiological wave phenomena, which trigger the beating of the heart. Recent advancements in optical mapping have demonstrated that the technique can now be performed with moving and contracting hearts and that motion and motion artifacts, once a major limitation, can now be overcome by numerically tracking and stabilizing the heart's motion. As a result, the optical measurement of electrical activity can be obtained from the moving heart surface in a co-moving frame of reference and motion artifacts can be reduced substantially. The aim of this study is to assess and validate the performance of a 2D marker-free motion tracking algorithm, which tracks motion and non-rigid deformations in video images. Because the tracking algorithm does not require markers to be attached to the tissue, it is necessary to verify that it accurately tracks the displacements of the cardiac tissue surface, which not only contracts and deforms, but also fluoresces and exhibits spatio-temporal physiology-related intensity changes. We used computer simulations to generate synthetic optical mapping videos, which show the contracting and fluorescing ventricular heart surface. The synthetic data reproduces experimental data as closely as possible and shows electrical waves propagating across the deforming tissue surface, as seen during voltage-sensitive imaging. We then tested the motion tracking and motion-stabilization algorithm on the synthetic as well as on experimental data. The motion tracking and motion-stabilization algorithm decreases motion artifacts approximately by 80% and achieves sub-pixel precision when tracking motion of 1–10 pixels (in a video image with 100 by 100 pixels), effectively inhibiting motion such that little residual motion remains after tracking and motion-stabilization. To demonstrate the performance of the algorithm, we present optical maps with a substantial reduction in motion artifacts showing action potential waves propagating across the moving and strongly deforming ventricular heart surface. The tracking algorithm reliably tracks motion if the tissue surface is illuminated homogeneously and shows sufficient contrast or texture which can be tracked or if the contrast is artificially or numerically enhanced. In this study, we also show how a reduction in dissociation-related motion artifacts can be quantified and linked to tracking precision. Our results can be used to advance optical mapping techniques, enabling them to image contracting hearts, with the ultimate goal of studying the mutual coupling of electrical and mechanical phenomena in healthy and diseased hearts.

Funding Acknowledgements Type of funding sources: None. Background Phase-sensitive inversion recovery improves tissue contrast by correcting for imperfect choice of inversion recovery time, however it is challenging to combine with a free-breathing acquisition. Deep learning (DL) algorithms have growing applications in cardiac MRI to improve image quality during image reconstruction. Purpose Here, we introduce a single-shot phase-sensitive myocardial delayed enhancement sequence with respiratory triggering (SShPSMDE-RT) (Figure 1). This novel sequence allows faster free-breathing acquisition of late gadolinium enhancement (LGE) images with reduced motion artifact (Figure 2.a). We combined this with a DL noise reduction algorithm to further improve image quality as compared to a standard segmented breath-hold (BH) PSMDE sequence. Methods 61 subjects (29 male, age 51±15) underwent cardiac MRI with the SShPSMDE-RT sequence and a standard BH sequence. The DL algorithm was applied at increasing levels (DL25, DL50, DL75, DL100) (Figure 2.b). Qualitative metrics were image quality, artifact severity, and diagnostic confidence, graded on a 5-point Likert scale. Quantitative metrics were sharpness of the left ventricle septum border and the LGE region (distance in mm for signal intensity to drop from 80% to 20%), blood-myocardium contrast-to-noise ratio (CNR), LGE-myocardium CNR, LGE signal-to-noise ratio (SNR), and LGE burden. 324 slices were included in the analysis. The sequences were compared via paired T-test. Results 27 subjects had positive LGE as determined by CMR experts. The average time to acquire a slice for SShPSMDE-RT is 4–7 seconds versus ∼30–40 seconds for the BH scan. The single-shot sequence had significantly better image quality (SShPSMDE-RT 2.1±0.8 vs. BH 1.5±0.6, p&amp;lt;0.001), less artifact (1.2±0.5 vs. 2.6±1.1, p&amp;lt;0.001), and better diagnostic confidence (3.4±0.7 vs. 2.6±0.8, p&amp;lt;0.001). Septum sharpness was slightly worse in SShPSMDE-RT images (4.1±1.7 mm vs. 3.8±1.6 mm, p = 0.008), but the DL algorithm improved sharpness of SShPSMDE-RT images such that there was no significant difference compared to BH images (p&amp;gt;0.5). There was no significant difference in LGE sharpness between the sequences. The SShPSMDE-RT images had superior blood-myocardium CNR (17.2±6.9 vs. 16.4±6.0, p = 0.040), LGE-myocardium CNR (12.1±7.2 vs. 10.4±6.6, p = 0.054), and LGE SNR (59.8±26.8 vs. 31.2±24.1, p&amp;lt;0.001); these metrics all improved with application of the DL algorithm. There was no significant difference in measured LGE burden (p = 0.12). Conclusions Our novel SShPSMDE-RT sequence significantly reduces scan time and motion artifact. This free-breathing sequence combined with a DL noise reduction algorithm provides better or similar image quality on both qualitative and quantitative metrics as compared to a standard BH PSMDE sequence. This technique can be used to obtain LGE imaging in patients who are unable to breath-hold or tolerate longer scan times.

ObjectivesThe reliability of image-based recommendations in the prostate cancer pathway is partially dependent on prostate MRI image quality. We evaluated the current compliance with PI-RADSv2.1 technical recommendations and the prostate MRI image quality in the Netherlands. To aid image quality improvement, we identified factors that possibly influence image quality.Materials and methodsA survey was sent to 68 Dutch medical centres to acquire information on prostate MRI acquisition. The responding medical centres were requested to provide anonymised prostate MRI examinations of biopsy-naive men suspected of prostate cancer. The images were evaluated for quality by three expert prostate radiologists. The compliance with PI-RADSv2.1 technical recommendations and the PI-QUALv2 score was calculated. Relationships between hardware, education of personnel, technical parameters, and/or patient preparation and both compliance and image quality were analysed using Pearson correlation, Mann–Whitney U-test, or Student's t-test where appropriate.ResultsForty-four medical centres submitted their compliance with PI-RADSv2.1 technical recommendations, and 26 medical centres completed the full survey. Thirteen hospitals provided 252 usable images. The mean compliance with technical recommendations was 79%. Inadequate PI-QUALv2 scores were given in 30.9% and 50.6% of the mp-MRI and bp-MRI examinations, respectively. Multiple factors with a possible relationship with image quality were identified.ConclusionIn the Netherlands, the average compliance with PI-RADSv2.1 technical recommendations is high. Prostate MRI image quality was inadequate in 30–50% of the provided examinations. Many factors not covered in the PI-RADSv2.1 technical recommendations can influence image quality. Improvement of prostate MRI image quality is needed.Critical relevance statementIt is essential to improve the image quality of prostate MRIs, which can be achieved by addressing factors not covered in the PI-RADSv2.1 technical recommendations.Key PointsProstate MRI image quality influences the diagnostic accuracy of image-based decisions.Thirty to fifty percent of Dutch prostate MRI examinations were of inadequate image quality.We identified multiple factors with possible influence on image quality.Graphical

Brain imaging: Comparison of T1W FLAIR BLADE with conventional T1W SE

Cone-beam computed tomography (CBCT), despite its advantages, has some drawbacks, such as artifacts and movement of the patient during scanning may lead to motion artifacts (MAs). This retrospective study aimed to evaluate the MAs in three different CBCT devices and to analyze their relationship with age, the gender of the patients, and scanning times. This study included 360 CBCT images from three institutions scanned in standing, sitting and supine positions. MAs presence, age, gender, and scanning times were recorded. Of the patients, 129 were scanned in standing position, 131 in sitting position, and 100 in supine position. MAs were found in 6.7% of patients in total; 8%, 7.6%, and 4% in standing, sitting, and supine positions, respectively. No statistically significant relationship was observed between MAs presence and patient position. The mean age of the patients with MAs was higher than patients without, in total and in standing positions. Scanning time showed no correlation with artifact presence. Patient position is not related to MAs presence. The age of the patient is a factor in movement, and has a high impact in standing position. Although insignificant, MAs were less common in supine position than sitting and standing positions. Sitting and supine positioning might reduce motion artifacts in older patients.

In coronary computed tomography angiography (CCTA), motion artifacts due to heartbeats can obscure coronary artery diagnoses. In this study, we introduce a cycle-consistent adversarial-network-based method for motion artifact correction in CCTA. Our methodology involves extracting image patches and using style transfer for synthetic ground truth creation, followed by CycleGAN network training for motion compensation. We employ Dynamic Time Warping (DTW) to align extracted image patches along the artery centerline with their corresponding motion-free phase patches, ensuring matched pixel correspondences and similar anatomical features for accuracy in subsequent processing steps. Our quantitative analysis, using metrics like the Dice Similarity Coefficient (DSC) and Hausdorff Distance (HD), demonstrates CycleGAN’s superior performance in reducing motion artifacts, with improvements in image quality and clarity. An observer study using a 5-point Likert scale further validates the reduction of motion artifacts and improved visibility of coronary arteries. Additionally, we present a quantitative analysis on clinical data, affirming the correction of motion artifacts through metric-based evaluations.

Objectives To assess the prevalence of motion artifacts and the factors associated with them in a cohort of suspected stroke patients, and to determine their impact on diagnostic accuracy for both AI and radiologists. Materials and methods This retrospective cross-sectional study included brain MRI scans of consecutive adult suspected stroke patients from a non-comprehensive Danish stroke center between January and April 2020. An expert neuroradiologist identified acute ischemic, hemorrhagic, and space-occupying lesions as references. Two blinded radiology residents rated MRI image quality and motion artifacts. The diagnostic accuracy of a CE-marked deep learning tool was compared to that of radiology reports. Multivariate analysis examined associations between patient characteristics and motion artifacts. Results 775 patients (68 years ± 16, 420 female) were included. Acute ischemic, hemorrhagic, and space-occupying lesions were found in 216 (27.9%), 12 (1.5%), and 20 (2.6%). Motion artifacts were present in 57 (7.4%). Increasing age (OR per decade, 1.60; 95% CI: 1.26, 2.09; p &lt; 0.001) and limb motor symptoms (OR, 2.36; 95% CI: 1.32, 4.20; p = 0.003) were independently associated with motion artifacts in multivariate analysis. Motion artifacts significantly reduced the accuracy of detecting hemorrhage. This reduction was greater for the AI tool (from 88 to 67%; p &lt; 0.001) than for radiology reports (from 100 to 93%; p &lt; 0.001). Ischemic and space-occupying lesion detection was not significantly affected. Conclusion Motion artifacts are common in suspected stroke patients, particularly in the elderly and patients with motor symptoms, reducing accuracy for hemorrhage detection by both AI and radiologists. Key Points Question Motion artifacts reduce the quality of MRI scans, but it is unclear which factors are associated with them and how they impact diagnostic accuracy. Findings Motion artifacts occurred in 7% of suspected stroke MRI scans, associated with higher patient age and motor symptoms, lowering hemorrhage detection by AI and radiologists. Clinical relevance Motion artifacts in stroke brain MRIs significantly reduce the diagnostic accuracy of human and AI detection of intracranial hemorrhages. Elderly patients and those with motor symptoms may benefit from a greater focus on motion artifact prevention and reduction. Graphical Abstract

Patient motion during computed tomography (CT) scan can result in serious degradation of imaging quality, and is of increasing concern due to the aging population and associated diseases. In this paper, we address this problem by focusing on the reduction of head motion artifacts. To achieve this, we introduce a head motion simulation system and a multi-scale deep learning architecture. The proposed motion simulation system can simulate rigid movement including translation and rotation. The images with simulated motion serve as the training set for the network, and the original motion free images serve as the gold standard. Motion artifacts exhibit in the image space as streaks and patchy shadows. We propose a multiscale neural network to learn the artifact. With different branches equipped with ResBlock and down-sampling, the network can learn long scale streaks and short scale shadow artifacts. Although we trained the network on simulated images, we find that the learned network generalizes well to images with real motion artifacts.

Pancreatic diffusion-weighted imaging (DWI) has numerous clinical applications, but conventional single-shot methods suffer from off resonance-induced artifacts like distortion and blurring while cardiovascular motion-induced phase inconsistency leads to quantitative errors and signal loss, limiting its utility. Multishot DWI (msDWI) offers reduced image distortion and blurring relative to single-shot methods but increases sensitivity to motion artifacts. Motion-compensated diffusion-encoding gradients (MCGs) reduce motion artifacts and could improve motion robustness of msDWI but come with the cost of extended echo time, further reducing signal. Thus, a method that combines msDWI with MCGs while minimizing the echo time penalty and maximizing signal would improve pancreatic DWI. In this work, we combine MCGs generated via convex-optimized diffusion encoding (CODE), which reduces the echo time penalty of motion compensation, with deep learning (DL)-based denoising to address residual signal loss. We hypothesize this method will qualitatively and quantitatively improve msDWI of the pancreas. This prospective institutional review board-approved study included 22 patients who underwent abdominal MR examinations from August 22, 2022 and May 17, 2023 on 3.0 T scanners. Following informed consent, 2-shot spin-echo echo-planar DWI (b = 0, 800 s/mm 2 ) without (M0) and with (M1) CODE-generated first-order gradient moment nulling was added to their clinical examinations. DL-based denoising was applied to the M1 images (M1 + DL) off-line. ADC maps were reconstructed for all 3 methods. Blinded pair-wise comparisons of b = 800 s/mm 2 images were done by 3 subspecialist radiologists. Five metrics were compared: pancreatic boundary delineation, motion artifacts, signal homogeneity, perceived noise, and diagnostic preference. Regions of interest of the pancreatic head, body, and tail were drawn, and mean ADC values were computed. Repeated analysis of variance and post hoc pairwise t test with Bonferroni correction were used for comparing mean ADC values. Bland-Altman analysis compared mean ADC values. Reader preferences were tabulated and compared using Wilcoxon signed rank test with Bonferroni correction and Fleiss κ. M1 was significantly preferred over M0 for perceived motion artifacts and signal homogeneity ( P < 0.001). M0 was significantly preferred over M1 for perceived noise ( P < 0.001), but DL-based denoising (M1 + DL) reversed this trend and was significantly favored over M0 ( P < 0.001). ADC measurements from M0 varied between different regions of the pancreas ( P = 0.001), whereas motion correction with M1 and M1 + DL resulted in homogeneous ADC values ( P = 0.24), with values similar to those reported for ssDWI with motion correction. ADC values from M0 were significantly higher than M1 in the head (bias 16.6%; P < 0.0001), body (bias 11.0%; P < 0.0001), and tail (bias 8.6%; P = 0.001). A small but significant bias (2.6%) existed between ADC values from M1 and M1 + DL. CODE-generated motion compensating gradients improves multishot pancreatic DWI as interpreted by expert readers and eliminated ADC variation throughout the pancreas. DL-based denoising mitigated signal losses from motion compensation while maintaining ADC consistency. Integrating both techniques could improve the accuracy and reliability of multishot pancreatic DWI.

SWI is valuable for characterization of intracranial hemorrhage and mineralization but has long acquisition times. We compared a highly accelerated wave-controlled aliasing in parallel imaging (CAIPI) SWI sequence with 2 commonly used alternatives, standard SWI and T2*-weighted gradient recalled-echo (T2*W GRE), for routine clinical brain imaging at 3T. A total of 246 consecutive adult patients were prospectively evaluated using a conventional SWI or T2*W GRE sequence and an optimized wave-CAIPI SWI sequence, which was 3-5 times faster than the standard sequence. Two blinded radiologists scored each sequence for the presence of hemorrhage, the number of microhemorrhages, and severity of motion artifacts. Wave-CAIPI SWI was then evaluated in head-to-head comparison with the conventional sequences for visualization of pathology, artifacts, and overall diagnostic quality. Forced-choice comparisons were used for all scores. Wave-CAIPI SWI was tested for superiority relative to T2*W GRE and for noninferiority relative to standard SWI using a 15% noninferiority margin. Compared with T2*W GRE, wave-CAIPI SWI detected hemorrhages in more cases (P < .001) and detected more microhemorrhages (P < .001). Wave-CAIPI SWI was superior to T2*W GRE for visualization of pathology, artifacts, and overall diagnostic quality (all P < .001). Compared with standard SWI, wave-CAIPI SWI showed no difference in the presence or number of hemorrhages identified. Wave-CAIPI SWI was noninferior to standard SWI for the visualization of pathology (P < .001), artifacts (P < .01), and overall diagnostic quality (P < .01). Motion was less severe with wave-CAIPI SWI than with standard SWI (P < .01). Wave-CAIPI SWI provided superior visualization of pathology and overall diagnostic quality compared with T2*W GRE and was noninferior to standard SWI with reduced scan times and reduced motion artifacts.