Deep learning (DL) accelerated controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA)-volumetric interpolated breath-hold examination (VIBE), provides high spatial resolution T1-weighted imaging of the upper abdomen. We aimed to investigate whether DL-CAIPIRINHA-VIBE can improve image quality, vessel conspicuity, and lesion detectability compared to a standard CAIPIRINHA-VIBE in renal imaging at 3 Tesla.

In this prospective study, 50 patients with 23 solid and 45 cystic renal lesions underwent MRI with clinical MR sequences, including standard CAIPIRINHA-VIBE and DL-CAIPIRINHA-VIBE sequences in the nephrographic phase at 3 Tesla. Two experienced radiologists independently evaluated both sequences and multiplanar reconstructions (MPR) of the sagittal and coronal planes for image quality with a Likert scale ranging from 1 to 5 (5 =best). Quantitative measurements including the size of the largest lesion and renal lesion contrast ratios were evaluated.

DL-CAIPIRINHA-VIBE compared to standard CAIPIRINHA-VIBE showed significantly improved overall image quality, higher scores for renal border delineation, renal sinuses, vessels, adrenal glands, reduced motion artifacts and reduced perceived noise in nephrographic phase images (all p < 0.001). DL-CAIPIRINHA-VIBE with MPR showed superior lesion conspicuity and diagnostic confidence compared to standard CAIPIRINHA-VIBE. However, DL-CAIPIRINHA-VIBE presented a more synthetic appearance and more aliasing artifacts (p < 0.023). The mean size and signal intensity of renal lesions for DL-CAIPIRINHA-VIBE showed no significant differences compared to standard CAIPIRINHA-VIBE (p > 0.9).

DL-CAIPIRINHA-VIBE is well suited for kidney imaging in the nephrographic phase, provides good image quality, improved delineation of anatomic structures and renal lesions.

Enhancement of the facial nerve can be seen on MRI due to its rich arteriovenous plexus. Classically, enhancement of the facial nerve beyond the geniculate ganglion has been described as a normal finding, while enhancement of the canalicular and labyrinthine segments is considered abnormal. We hypothesize facial nerve enhancement of the canalicular and labyrinthine segments is a normal finding on the postcontrast T1-weighted, fat-saturated volumetric interpolated breath-hold examination (VIBE) sequence on both 1.5T and 3T MRI scanners.

Fifty patients without facial nerve symptoms undergoing MRI by using the internal auditory canal protocol were identified at our institution, 25 cases on a 1.5T scanner and 25 cases on a 3T scanner; a total of 100 facial nerves. Presence or absence of enhancement of the facial nerve segments on the postcontrast T1-weighted, fat-saturated VIBE sequence were independently analyzed by 2 neuroradiologists.

On 1.5T, of 50 facial nerves evaluated, percentage of nerves with enhancement at each segment was as follows: 80% canalicular, 92% labyrinthine, 100% tympanic, 100% mastoid, and 80% intraparotid. On 3T, of 50 facial nerves evaluated, percentage of nerves with enhancement at each segment was as follows: 60% canalicular, 84% labyrinthine, 98% tympanic, 100% mastoid, and 93% intraparotid.

Enhancement of the canalicular and labyrinthine segments of the facial nerve is a normal finding on the postcontrast, T1-weighted, fat-saturated VIBE sequence. Careful attention to clinical history and asymmetry should be considered before calling abnormality of the facial nerve.

This retrospective study evaluated the utility of contrast-enhanced T1-weighted 3D fast spin-echo-based sampling perfection with application-optimized contrasts by using different flip angle evolutions (SPACE) sequences for brain metastasis detection on 3T MRI compared with a gradient-recalled echo-based 3D FLASH sequence.

We identified all patients at a single institution who underwent SPACE and 3D FLASH sequences as part of a practice quality-improvement project. Their medical records were retrospectively reviewed. Five certified neuroradiologists reviewed the images, with at least 2 weeks' separation between scoring sequences for the same patient. We evaluated the following parameters: number of metastatic lesions, number of indeterminate lesions, lesion margin, contrast-to-noise ratio (CNR), extent of image artifacts, and overall image quality. The CNR was also quantified for solidly enhancing lesions of >1 cm.

We identified 220 patients who underwent SPACE and 3D FLASH sequences (the order of the sequences was equally distributed). Of these, 79 had brain metastases on imaging, and 7 were excluded; thus, 72 patients were included in the study. Twenty patients were scored by 2 radiologists. Of the 92 evaluations, SPACE detected more lesions than 3D FLASH in 35, while 3D FLASH detected more lesions in 10. More indeterminate lesions were seen on 3D FLASH (n = 27) than on SPACE (n = 9). For the lesion margin, CNR, and overall image quality on a Likert scale, SPACE performed significantly better than 3D FLASH, with fewer image artifacts (P < .00001). Higher quantitative CNRs were found on SPACE than on 3D FLASH images, though this result was not statistically significant (median = 22.9 versus 15.5, respectively, P = .134). There was a high interreader lesion detection concordance with the Krippendorf α ordinals at 0.962 for SPACE, 0.870 for 3D FLASH, and 0.918 for the 2 sequences combined.

Compared with 3D FLASH, the SPACE sequence detected more metastatic lesions and was rated higher for image quality, lesion margin, and CNR, with fewer artifacts. Importantly, the SPACE sequence resulted in increased reader confidence, with fewer indeterminate lesions detected.

To compare liver image quality and lesion detection using an AI-augmented T1-weighted sequence on hepatobiliary-phase gadoxetate-enhanced magnetic resonance imaging (MRI).

Fifty patients undergoing gadoxetate-enhanced MRI were recruited. Two T1-weighted Dixon sequences were utilized: a 17-s breath-hold acquisition and an accelerated 12-s breath-hold acquisition (reduced phase resolution), both reconstructed using neural network (NN) and iterative denoising (ID), NN-alone, ID-alone, and the standard method. Contrast-to-noise ratio (CNR) was assessed quantitatively for all series (ANOVA). Two blinded radiologists independently analyzed three image sets: 17-s acquisition reconstructed with NN and ID (17-s NN + ID), 12-s acquisition reconstructed with NN and ID (12-s NN + ID), and 17-s acquisition with standard reconstruction (17-s standard). Overall image quality, qualitative CNR, lesion edge sharpness, vessel edge sharpness, and respiratory motion artifacts were scored (4-point Likert scale) and compared (Friedman test). Lesion detection was compared between 12-s NN + ID and 17-s standard reconstructions (Wilcoxon signed-rank test).

Quantitative liver-to-portal vein CNR was significantly higher for 17-s NN + ID than 17-s standard or 17-s NN-alone images (p = 0.001). Scores for overall image quality, qualitative CNR, vessel edge sharpness, and lesion edge sharpness were significantly higher for 17-s NN + ID and 12-s NN + ID than standard reconstruction (p < 0.001); there was no significant difference between 17-s and 12-s NN + ID. There was no significant difference in respiratory motion artifacts and number of lesions or diameter of the smallest detected lesion using 12-s NN + ID or 17-s standard reconstruction.

AI-augmented reconstructions can improve image quality while reducing breath-hold duration in T1-weighted hepatobiliary-phase gadoxetate-enhanced MRI, without compromising lesion detection.

AI-augmented reconstruction of T1-weighted MRI improves image quality and lesion detection in hepatobiliary phase liver imaging, reducing breath-hold duration without compromising clinical lesion detection.

Liver-to-portal vein CNR was significantly higher for 17-s NN + ID. AI-augmented reconstructions scored higher for image quality, contrast-to-noise, vessel-edge, and lesion-edge sharpness. No significant difference in lesion detection between 12-s NN + ID and 17-s standard reconstructions.

Deep learning (DL)-enabled magnetic resonance imaging (MRI) reconstructions can enable shortening of breath-hold examinations and improve image quality by reducing motion artifacts. Prospective studies with DL reconstructions of accelerated MRI of the upper abdomen in the context of pancreatic pathologies are lacking. In a clinical setting, the purpose of this study is to investigate the performance of a novel DL-based reconstruction algorithm in T1-weighted volumetric interpolated breath-hold examinations with partial Fourier sampling and Dixon fat suppression (hereafter, VIBE-Dixon DL ). The objective is to analyze its impact on acquisition time, image sharpness and quality, diagnostic confidence, pancreatic lesion conspicuity, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR).

This prospective single-center study included participants with various pancreatic pathologies who gave written consent from January 2023 to September 2023. During the same session, each participant underwent 2 MRI acquisitions using a 1.5 T scanner: conventional precontrast and postcontrast T1-weighted VIBE acquisitions with Dixon fat suppression (VIBE-Dixon, reference standard) using 4-fold parallel imaging acceleration and 6-fold accelerated VIBE-Dixon acquisitions with partial Fourier sampling utilizing a novel DL reconstruction tailored to the acquisition. A qualitative image analysis was performed by 4 readers. Acquisition time, image sharpness, overall image quality, image noise and artifacts, diagnostic confidence, as well as pancreatic lesion conspicuity and size were compared. Furthermore, a quantitative analysis of SNR and CNR was performed.

Thirty-two participants were evaluated (mean age ± SD, 62 ± 19 years; 20 men). The VIBE-Dixon DL method enabled up to 52% reduction in average breath-hold time (7 seconds for VIBE-Dixon DL vs 15 seconds for VIBE-Dixon, P < 0.001). A significant improvement of image sharpness, overall image quality, diagnostic confidence, and pancreatic lesion conspicuity was observed in the images recorded using VIBE-Dixon DL ( P < 0.001). Furthermore, a significant reduction of image noise and motion artifacts was noted in the images recorded using the VIBE-Dixon DL technique ( P < 0.001). In addition, for all readers, there was no evidence of a difference in lesion size measurement between VIBE-Dixon and VIBE-Dixon DL . Interreader agreement between VIBE-Dixon and VIBE-Dixon DL regarding lesion size was excellent (intraclass correlation coefficient, >90). Finally, a statistically significant increase of pancreatic SNR in VIBE-DIXON DL was observed in both the precontrast ( P = 0.025) and postcontrast images ( P < 0.001). Also, an increase of splenic SNR in VIBE-DIXON DL was observed in both the precontrast and postcontrast images, but only reaching statistical significance in the postcontrast images ( P = 0.34 and P = 0.003, respectively). Similarly, an increase of pancreas CNR in VIBE-DIXON DL was observed in both the precontrast and postcontrast images, but only reaching statistical significance in the postcontrast images ( P = 0.557 and P = 0.026, respectively).

The prospectively accelerated, DL-enhanced VIBE with Dixon fat suppression was clinically feasible. It enabled a 52% reduction in breath-hold time and provided superior image quality, diagnostic confidence, and pancreatic lesion conspicuity. This technique might be especially useful for patients with limited breath-hold capacity.

In vivo studies are often required to prove the functionality and safety of medical devices. Clinical trials are costly and complex, adding to ethical scrutiny of animal testing. Anthropomorphic phantoms with versatile functionalities can overcome these issues with regard to medical education or an effective development of assistance systems during image-guided interventions (e.g., robotics, navigation/registration algorithms). In this work, an MRI-compatible and customizable motion phantom is presented to mimic respiratory-triggered organ movement as well as human anatomy.

For this purpose, polyvinyl alcohol cryogel (PVA-C) was the foundation for muscles, liver, kidneys, tumors, and remaining abdominal tissue in different sizes of the abdominal phantom body (APB) with the ability to mimic human tissue in various properties. In addition, a semi-flexible rib cage was 3D-printed. The motion unit (MU) with an electromagnetically shielded stepper motor and mechanical extensions simulated a respiration pattern to move the APB.

Each compartment of the APB complied the relaxation times, dielectricity, and elasticity of human tissue. It showed resistance against mold and provided a resealable behavior after needle punctures. During long-term storage, the APB had a weight loss of 2.3%, followed by changes to relaxation times of 9.3% and elasticity up to 79%. The MU was able to physiologically appropriately mimic the organ displacement without reducing the MRI quality.

This work presents a novel modularizable and low-cost PVA-C based APB to mimic fundamental organ motion. Beside a further organ motion analysis, an optimization of APB's chemical composition is needed to ensure a realistic motion simulation and reproducible long-term use. This phantom enhances diverse and varied training environments for prospective physicians as well as effective R&D of medical devices with the possibility to reduce in vivo experiments.

Breath-held fat-suppressed volumetric T1-weighted MRI is an important and widely-used technique for evaluating the abdomen. Both fat-saturation and Dixon-based fat-suppression methods are used at conventional field strengths; however, both have challenges at lower field strengths (<1.5T) due to insufficient fat suppression and/or inadequate resolution. Specifically, at lower field strengths, fat saturation often fails due to the short T1 of lipid; and Cartesian Dixon imaging provides poor spatial resolution due to the need for a long ΔTE, due to the smaller Δf between water and lipid. The purpose of this work is to demonstrate a new approach capable of simultaneously achieving excellent fat suppression and high spatial resolution on a 0.55T whole-body system.

We applied 3D stack-of-spirals Dixon imaging at 0.55T, with compensation of concomitant field phase during reconstruction. The spiral readouts make efficient use of the requisite ΔTE. We compared this with 3D Cartesian Dixon imaging. Experiments were performed in 2 healthy and 10 elevated liver fat volunteers.

Stack-of-spirals Dixon imaging at 0.55T makes excellent use of the required ΔTE, provided high SNR efficiency and finer spatial resolution (1.7 × 1.7 × 5 mm3) compared Cartesian Dixon (3.5 × 3.5 × 5 mm3), within a 17-s breath-hold. We observed successful fat suppression, and improved definition of structures such as the liver, kidneys, and bowel.

We demonstrate that high-resolution single breath-hold volumetric abdominal T1-weighted imaging is feasible at 0.55T using spiral sampling and concomitant field correction. This is an attractive alternative to existing Cartesian-based methods, as it simultaneously provides high-resolution and excellent fat-suppression.

To develop a framework for simultaneous three-dimensional (3D) mapping ofT 1 $$ {\mathrm{T}}_1 $$ ,T 2 $$ {\mathrm{T}}_2 $$ , and fat signal fraction in the liver at 0.55 T.

The proposed sequence acquires four interleaved 3D volumes with a two-echo Dixon readout.T 1 $$ {\mathrm{T}}_1 $$ andT 2 $$ {\mathrm{T}}_2 $$ are encoded into each volume via preparation modules, and dictionary matching allows simultaneous estimation ofT 1 $$ {\mathrm{T}}_1 $$ ,T 2 $$ {\mathrm{T}}_2 $$ , andM 0 $$ {M}_0 $$ for water and fat separately. 2D image navigators permit respiratory binning, and motion fields from nonrigid registration between bins are used in a nonrigid respiratory-motion-corrected reconstruction, enabling 100% scan efficiency from a free-breathing acquisition. The integrated nature of the framework ensures the resulting maps are always co-registered.

T 1 $$ {\mathrm{T}}_1 $$ ,T 2 $$ {\mathrm{T}}_2 $$ , and fat-signal-fraction measurements in phantoms correlated strongly (adjustedr 2 > 0 . 98 $$ {r}^2>0.98 $$ ) with reference measurements. Mean liver tissue parameter values in 10 healthy volunteers were427 ± 22 $$ 427\pm 22 $$ ,47 . 7 ± 3 . 3   ms $$ 47.7\pm 3.3\;\mathrm{ms} $$ , and7 ± 2 % $$ 7\pm 2\% $$ forT 1 $$ {\mathrm{T}}_1 $$ ,T 2 $$ {\mathrm{T}}_2 $$ , and fat signal fraction, giving biases of71 $$ 71 $$ ,- 30 . 0   ms $$ -30.0\;\mathrm{ms} $$ , and- 5 $$ -5 $$ percentage points, respectively, when compared to conventional methods.

A novel sequence for comprehensive characterization of liver tissue at 0.55 T was developed. The sequence provides co-registered 3DT 1 $$ {\mathrm{T}}_1 $$ ,T 2 $$ {\mathrm{T}}_2 $$ , and fat-signal-fraction maps with full coverage of the liver, from a single nine-and-a-half-minute free-breathing scan. Further development is needed to achieve accurate proton-density fat fraction (PDFF) estimation in vivo.

To investigate whether deep cervical lymph node (DCLN) ligation alters intracranial cerebrospinal fluid (CSF) tracer dynamics and outflow using a rat model with intrathecal dynamic contrast-enhanced (DCE) MRI.

Six bilateral DCLN-ligated and six sham-operated rats were subjected to DCE MRI with Gd-BTDO3A, and dynamic T1-weighted images were acquired. ROIs were collected from the CSF at the C1 level (CSF_C1), CSF between the olfactory bulbs (CSF_OB), CSF at the pituitary recess (CSF_PitR), and CSF at the pineal recess (CSF_PinR), upper nasal turbinate (UNT), olfactory bulbs, cerebrum, and the jugular region. Time-intensity curves were evaluated, and the maximum slope, peak timing, peak signal ratio, and elimination half-life for the four CSF ROIs and UNT were calculated and compared.

Delayed tracer arrival in the rostral CSF space and the nasal cavity with tracer retention in the ventral CSF space were observed in the ligation group. The maximum slopes were smaller in the ligation group at UNT (sham: 0.075 ± 0.0061, ligation: 0.044 ± 0.0086/min, P = 0.011). A significant difference was not detected in peak timings. The peak signal ratio values were lower in the ligation group at UNT (sham: 2.12 ± 0.19, ligation: 1.72 ± 0.11, P = 0.011). The elimination half-life was delayed in the ligation group at CSF_C1 (sham: 30.5 ± 2.70, ligation: 44.4 ± 12.6 min, P = 0.043), CSF_OB (sham: 30.2 ± 2.67, ligation: 44.8 ± 7.47 min, P = 0.021), and CSF_PitR (sham: 30.2 ± 2.49, ligation: 41.3 ± 7.57 min, P = 0.021).

The DCLN ligation in rats blocked CSF outflow into the nasal cavity and caused CSF retention.

To investigate whether a deep learning (DL) controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA)-volumetric interpolated breath-hold examination (VIBE) technique can improve image quality, lesion conspicuity, and lesion detection compared to a standard CAIPIRINHA-VIBE technique in gadoxetic acid-enhanced liver MRI.

This retrospective single-center study included 168 patients who underwent gadoxetic acid-enhanced liver MRI at 3 T using both standard CAIPIRINHA-VIBE and DL CAIPIRINHA-VIBE techniques on pre-contrast and hepatobiliary phase (HBP) images. Additionally, high-resolution (HR) DL CAIPIRINHA-VIBE was obtained with 1-mm slice thickness on the HBP. Three abdominal radiologists independently assessed the image quality and lesion conspicuity of pre-contrast and HBP images. Statistical analyses involved the Wilcoxon signed-rank test for image quality assessment and the generalized estimation equation for lesion conspicuity and detection evaluation.

DL and HR-DL CAIPIRINHA-VIBE demonstrated significantly improved overall image quality and reduced artifacts on pre-contrast and HBP images compared to standard CAIPIRINHA-VIBE (p < 0.001), with a shorter acquisition time (DL vs standard, 11 s vs 17 s). However, the former presented a more synthetic appearance (both p < 0.05). HR-DL CAIPIRINHA-VIBE showed superior lesion conspicuity to standard and DL CAIPIRINHA-VIBE on HBP images (p < 0.001). Moreover, HR-DL CAIPIRINHA-VIBE exhibited a significantly higher detection rate of small (< 2 cm) solid focal liver lesions (FLLs) on HBP images compared to standard CAIPIRINHA-VIBE (92.5% vs 87.4%; odds ratio = 1.83; p = 0.036).

DL and HR-DL CAIPIRINHA-VIBE achieved superior image quality compared to standard CAIPIRINHA-VIBE. Additionally, HR-DL CAIPIRINHA-VIBE improved the lesion conspicuity and detection of small solid FLLs. DL and HR-DL CAIPIRINHA-VIBE hold the potential clinical utility for gadoxetic acid-enhanced liver MRI.

DL and HR-DL CAIPIRINHA-VIBE hold promise as potential alternatives to standard CAIPIRINHA-VIBE in routine clinical liver MRI, improving the image quality and lesion conspicuity, enhancing the detection of small (< 2 cm) solid focal liver lesions, and reducing the acquisition time.

• DL and HR-DL CAIPIRINHA-VIBE demonstrated improved overall image quality and reduced artifacts on pre-contrast and HBP images compared to standard CAIPIRINHA-VIBE, in addition to a shorter acquisition time. • DL and HR-DL CAIPIRINHA-VIBE yielded a more synthetic appearance than standard CAIPIRINHA-VIBE. • HR-DL CAIPIRINHA-VIBE showed improved lesion conspicuity than standard CAIPIRINHA-VIBE on HBP images, with a higher detection of small (< 2 cm) solid focal liver lesions.

Diffusion-based tractography in the optic nerve requires sampling strategies assisted by anatomical landmark information (regions of interest [ROIs]). We aimed to investigate the feasibility of expert-placed, high-resolution T1-weighted ROI-data transfer onto lower spatial resolution diffusion-weighted images. Slab volumes from 20 volunteers were acquired and preprocessed including distortion bias correction and artifact reduction. Constrained spherical deconvolution was used to generate a directional diffusion information grid (fibre orientation distribution-model [FOD]). Three neuroradiologists marked landmarks on both diffusion imaging variants and structural datasets. Structural ROI information (volumetric interpolated breath-hold sequence [VIBE]) was respectively registered (linear with 6/12 degrees of freedom [DOF]) onto single-shot EPI (ss-EPI) and readout-segmented EPI (rs-EPI) volumes, respectively. All eight ROI/FOD-combinations were compared in a targeted tractography task of the optic nerve pathway. Inter-rater reliability for placed ROIs among experts was highest in VIBE images (lower confidence interval 0.84 to 0.97, mean 0.91) and lower in both ss-EPI (0.61 to 0.95, mean 0.79) and rs-EPI (0.59 to 0.86, mean 0.70). Tractography success rate based on streamline selection performance was highest in VIBE-drawn ROIs registered (6-DOF) onto rs-EPI FOD (70.0% over 5%-threshold, capped to failed ratio 39/16) followed by both 12-DOF-registered (67.5%; 41/16) and nonregistered VIBE (67.5%; 40/23). On ss-EPI FOD, VIBE-ROI-datasets obtained fewer streamlines overall with each at 55.0% above 5%-threshold and with lower capped to failed ratio (6-DOF: 35/36; 12-DOF: 34/34, nonregistered 33/36). The combination of VIBE-placed ROIs (highest inter-rater reliability) with 6-DOF registration onto rs-EPI targets (best streamline selection performance) is most suitable for white matter template generation required in group studies.

This study aimed to assess the performance of 2-dimensional (2D) imaging with microscopy coils in delineating teeth and periodontal tissues compared with conventional 3-dimensional (3D) imaging on a 3 T magnetic resonance imaging (MRI) unit.

Twelve healthy participants (4 men and 8 women; mean age: 25.6 years; range: 20-52 years) with no dental symptoms were included. The left mandibular first molars and surrounding periodontal tissues were examined using the following 2 sequences: 2D proton density-weighted (PDw) images and 3D enhanced T1 high-resolution isotropic volume excitation (eTHRIVE) images. Two-dimensional MRI images were taken using a 3 T MRI unit and a 47 mm microscopy coil, while 3D MRI imaging used a 3 T MRI unit and head-neck coil. Oral radiologists assessed dental and periodontal structures using a 4-point Likert scale. Inter- and intra-observer agreement was determined using the weighted kappa coefficient. The Wilcoxon signed-rank test was used to compare 2D-PDw and 3D-eTHRIVE images.

Qualitative analysis showed significantly better visualization scores for 2D-PDw imaging than for 3D-eTHRIVE imaging (Wilcoxon signed-rank test). 2D-PDw images provided improved visibility of the tooth, root dental pulp, periodontal ligament, lamina dura, coronal dental pulp, gingiva, and nutrient tract. Inter-observer reliability ranged from moderate agreement to almost perfect agreement, and intra-observer agreement was in a similar range.

Two-dimensional-PDw images acquired using a 3 T MRI unit and microscopy coil effectively visualized nearly all aspects of teeth and periodontal tissues.

We aim to provide an overview of technical and clinical unmet needs in deep learning (DL) applications for quantitative and qualitative PET in PET/MR, with a focus on attenuation correction, image enhancement, motion correction, kinetic modeling, and simulated data generation. (1) DL-based attenuation correction (DLAC) remains an area of limited exploration for pediatric whole-body PET/MR and lung-specific DLAC due to data shortages and technical limitations. (2) DL-based image enhancement approximating MR-guided regularized reconstruction with a high-resolution MR prior has shown promise in enhancing PET image quality. However, its clinical value has not been thoroughly evaluated across various radiotracers, and applications outside the head may pose challenges due to motion artifacts. (3) Robust training for DL-based motion correction requires pairs of motion-corrupted and motion-corrected PET/MR data. However, these pairs are rare. (4) DL-based approaches can address the limitations of dynamic PET, such as long scan durations that may cause patient discomfort and motion, providing new research opportunities. (5) Monte-Carlo simulations using anthropomorphic digital phantoms can provide extensive datasets to address the shortage of clinical data. This summary of technical/clinical challenges and potential solutions may provide research opportunities for the research community towards the clinical translation of DL solutions.

To develop and evaluate a deep convolutional neural network (DCNN) for automated liver segmentation, volumetry, and radiomic feature extraction on contrast-enhanced portal venous phase magnetic resonance imaging (MRI).

This retrospective study included hepatocellular carcinoma patients from an institutional database with portal venous MRI. After manual segmentation, the data was randomly split into independent training, validation, and internal testing sets. From a collaborating institution, de-identified scans were used for external testing. The public LiverHccSeg dataset was used for further external validation. A 3D DCNN was trained to automatically segment the liver. Segmentation accuracy was quantified by the Dice similarity coefficient (DSC) with respect to manual segmentation. A Mann-Whitney U test was used to compare the internal and external test sets. Agreement of volumetry and radiomic features was assessed using the intraclass correlation coefficient (ICC).

In total, 470 patients met the inclusion criteria (63.9±8.2 years; 376 males) and 20 patients were used for external validation (41±12 years; 13 males). DSC segmentation accuracy of the DCNN was similarly high between the internal (0.97±0.01) and external (0.96±0.03) test sets (p=0.28) and demonstrated robust segmentation performance on public testing (0.93±0.03). Agreement of liver volumetry was satisfactory in the internal (ICC, 0.99), external (ICC, 0.97), and public (ICC, 0.85) test sets. Radiomic features demonstrated excellent agreement in the internal (mean ICC, 0.98±0.04), external (mean ICC, 0.94±0.10), and public (mean ICC, 0.91±0.09) datasets.

Automated liver segmentation yields robust and generalizable segmentation performance on MRI data and can be used for volumetry and radiomic feature extraction.

Liver volumetry, anatomic localization, and extraction of quantitative imaging biomarkers require accurate segmentation, but manual segmentation is time-consuming. A deep convolutional neural network demonstrates fast and accurate segmentation performance on T1-weighted portal venous MRI.

• This deep convolutional neural network yields robust and generalizable liver segmentation performance on internal, external, and public testing data. • Automated liver volumetry demonstrated excellent agreement with manual volumetry. • Automated liver segmentations can be used for robust and reproducible radiomic feature extraction.

Introduction: Many spine disorders are caused by disc degeneration or endplate defects. Because nutrients entering the avascular disc are channeled through the cartilaginous endplate (CEP), structural and compositional changes in the CEP may block this solute channel, thereby hindering disc cell function. Therefore, imaging the CEP region is important to improve the diagnostic accuracy of spine disorders. Methods: A clinically available T1-weighted and fat-suppressed spoiled gradient recalled-echo (FS-SPGR) sequence was optimized for high-contrast CEP imaging, which utilizes the short T1 property of the CEP. The FS-SPGR scans with and without breath-hold were performed for comparison on healthy subjects. Then, the FS-SPGR sequence which produced optimal image quality was employed for patient scans. In this study, seven asymptomatic volunteers and eight patients with lower back pain were recruited and scanned on a 3T whole-body MRI scanner. Clinical T2-weighted fast spin-echo (T2w-FSE) and T1-weighted FSE (T1w-FSE) sequences were also scanned for comparison. Results: For the asymptomatic volunteers, the FS-SPGR scans under free breathing conditions with NEX = 4 showed much higher contrast-to-noise ratio values between the CEP and bone marrow fat (BMF) (CNRCEP-BMF) (i.e., 7.8 ± 1.6) and between the CEP and nucleus pulposus (NP) (CNRCEP-NP) (i.e., 6.1 ± 1.2) compared to free breathing with NEX = 1 (CNRCEP-BMF: 4.0 ± 1.1 and CNRCEP-NP: 2.5 ± 0.9) and breath-hold condition with NEX = 1 (CNRCEP-BMF: 4.2 ± 1.3 and CNRCEP-NP: 2.8 ± 1.3). The CEP regions showed bright linear signals with high contrast in the T1-weighted FS-SPGR images in the controls, while irregularities of the CEP were found in the patients. Discussion: We have developed a T1-weighted 3D FS-SPGR sequence to image the CEP that is readily translatable to clinical settings. The proposed sequence can be used to highlight the CEP region and shows promise for the detection of intervertebral disc abnormalities.

This study aims at assessing approaches for generating high-resolution magnetic resonance imaging- (MRI-) based synthetic computed tomography (sCT) images suitable for orthopedic care using a deep learning model trained on low-resolution computed tomography (CT) data. To that end, paired MRI and CT data of three anatomical regions were used: high-resolution knee and ankle data, and low-resolution hip data. Four experiments were conducted to investigate the impact of low-resolution training CT data on sCT generation and to find ways to train models on low-resolution data while providing high-resolution sCT images. Experiments included resampling of the training data or augmentation of the low-resolution data with high-resolution data. Training sCT generation models using low-resolution CT data resulted in blurry sCT images. By resampling the MRI/CT pairs before the training, models generated sharper images, presumably through an increase in the MRI/CT mutual information. Alternatively, augmenting the low-resolution with high-resolution data improved sCT in terms of mean absolute error proportionally to the amount of high-resolution data. Overall, the morphological accuracy was satisfactory as assessed by an average intermodal distance between joint centers ranging from 0.7 to 1.2 mm and by an average intermodal root-mean-squared distances between bone surfaces under 0.7 mm. Average dice scores ranged from 79.8% to 87.3% for bony structures. To conclude, this paper proposed approaches to generate high-resolution sCT suitable for orthopedic care using low-resolution data. This can generalize the use of sCT for imaging the musculoskeletal system, paving the way for an MR-only imaging with simplified logistics and no ionizing radiation.

To assess how pars interarticularis fracture characteristics on T1-VIBE and STIR MRI relate to healing and identify anatomical parameters that may impact healing.

A retrospective review of an MRI series of lumbar pars interarticularis injuries in elite athletes over a 3-year period. Fracture configurations, signal intensities and anatomical parameters were recorded by two radiologists. Statistical analysis employed multilevel mixed-effects linear regressions, adjusted for repeated measures and baseline covariates.

Forty-seven lumbar pars interarticularis injuries among 31 athletes were assessed. On final scans for each athlete, 15% (7/47) injuries had worsened, 23% (11/47) remained stable, 43% (20/47) partially healed and 19% (9/47) healed completely. Healing times varied, quickest was 49 days for a chronic fracture in a footballer. Bone marrow oedema signal was highest in worsened fractures, followed by improved, and lowest in stable fractures. As healing progressed, T1-VIBE signal at the fracture line decreased. Bone marrow oedema and fracture line signal peaked at 90-120 days before decreasing until 210-240 days. Fractures with smaller dimensions, more vertical orientation and a longer superior articular facet beneath were significantly associated with better healing (p < 0.05).

Most diagnosed athletic pars interarticularis injuries improve. Normalising T1-VIBE signal at the fracture line is a novel measurable indicator of bony healing. Contrastingly, bone marrow oedema signal is higher in active fractures irrespective of healing or deterioration. Injuries initially perceived as worsening may be exhibiting the normal osteoclastic phase of healing. Better outcomes favour smaller, vertical fractures with a longer superior articular facet beneath.

This study presents two cases of tumors in contact with the inferior vena cava during radiotherapy, and introduces a clinically useful technique for identifying tumor boundaries adjacent to blood vessels by adjusting the position of the field-of-view (FOV) to enhance the inflow effect in magnetic resonance imaging. We named this technique "Shifting-FOV." This method consists of three steps: (1) remove the upper and lower saturation pulses outside the FOV, (2) align the FOV to position the lower edge of the imaging slab as close to the tumor as possible, and (3) manually adjust the table position to locate the tumor at the center of the magnetic field. The proposed method allowed for accurate identification of the tumor/vessel boundaries in both cases. This is a useful technique that can be readily applied to other facilities. Furthermore, images obtained using this technique may enable accurate tumor contouring in radiotherapy treatment planning.

Magnetic resonance imaging (MRI) is widely regarded as the primary modality for the morphological assessment of cartilage and all other joint tissues involved in osteoarthritis. 2D fast spin echo fat-suppressed intermediate-weighted (FSE FS IW) sequences with a TE between 30 and 40ms have stood the test of time and are considered the cornerstone of MRI protocols for clinical practice and trials. These sequences offer a good balance between sensitivity and specificity and provide appropriate contrast and signal within the cartilage as well as between cartilage, articular fluid, and subchondral bone. Additionally, FS IW sequences enable the evaluation of menisci, ligaments, synovitis/effusion, and bone marrow edema-like signal changes. This review article provides a rationale for the use of FSE FS IW sequences in the morphological assessment of cartilage and osteoarthritis, along with a brief overview of other clinically available sequences for this indication. Additionally, the article highlights ongoing research efforts aimed at improving FSE FS IW sequences through 3D acquisitions with enhanced resolution, shortened examination times, and exploring the potential benefits of different magnetic field strengths. While most of the literature on cartilage imaging focuses on the knee, the concepts presented here are applicable to all joints. KEY POINTS: 1. MRI is currently considered the modality of reference for a "whole-joint" morphological assessment of osteoarthritis. 2. Fat-suppressed intermediate-weighted sequences remain the keystone of MRI protocols for the assessment of cartilage morphology, as well as other structures involved in osteoarthritis. 3. Trends for further development in the field of cartilage and joint imaging include 3D FSE imaging, faster acquisition including AI-based acceleration, and synthetic imaging providing multi-contrast sequences.

Perforation of the lingual cortex while placing dental implants in the interforaminal region of the mandible can cause severe hemorrhage. The purpose of this study was to evaluate the features of mandibular lingual foraminals (MLFs) and locational relationship between them and lingual mucosal vessels (LMVs) by CT/MRI fusion volumetric images.

37 images within complete anterior mandibular region using both MSCT and three-dimensional volumetric interpolated breath-hold examination (3D-VIBE) MRI were taken from our imaging archives. After exclusion of 11 for lesions or artifacts, 26 CT/MRI fusion volumetric images were included to evaluate the frequency, diameter, and position of MLFs. The anterior mandibular region was divided into 4 equal segments under each teeth, and 40 regions were got from C5 to D5. Furthermore, the positional relationship between MLFs and LMVs was analyzed in this coordinate system.

62 MLFs (73.81%) were located below the incisors, followed by premolars (21.43%) and canines (4.76%). Female bias, the mean diameter of the female was 0.08 mm while the male was 0.21 mm. The total number of LMVs was most distributed on lingual side of C1 and D1. According to Spearman's correlation coefficient, the location of MLFs was related to LMVs. The MLFs in fourth segment of D1 were positively moderately correlated with LMVs in fourth segment of D4, while the MLFs in third segment of C1 showed a weak positive correlation with LMVs in third segment of D4.

The features and the correlation between MLFs and LMVs in CT/MRI fusion volumetric images may offer reference to dentists when only MLFs can been seen on routine preoperative CT examination of implants.

Retrospectively registered. (D2018-072).

This study aimed to investigate the effect of using slice partial Fourier (SPF), phase partial Fourier (PPF), and radial scan (Elliptical scanning) methods on image quality. Changes in signal-to-noise ratio (SNR), effective slice thickness, and in-plane resolution were measured in 3D-gradient echo when SPF, PPF, and radial scan were used. Effective slice thickness increased and SNR increased when SPF was used; in-plane resolution decreased and SNR decreased when PPF was used; effective slice thickness did not change, in-plane resolution decreased, and SNR increased when the radial scan method was used. The radial scan method reduces image quality and imaging time compared to those in the SPF and PPF methods.

APTw CEST MRI suffers from long preparation times and consequently long acquisition times (~5 min). Recently, a consensus on the preparation module for clinical APTw CEST at 3 T was found in the community, and we present a fast whole-brain APTw CEST MRI sequence following this consensus preparation of pulsed RF irradiation of 2 s duration at 90% RF duty-cycle and a B1,rms of 2 μT. After optimization of the snapshot CEST approach for APTw imaging regarding flip angle, voxel size and frequency offset sampling, we extend it by undersampled GRE acquisition and compressed sensing reconstruction. This allows 2 mm isotropic whole-brain APTw imaging for clinical research at 3 T below 2 min. With this sequence, a fast snapshot APTw imaging method is now available for larger clinical studies of brain tumors.

A retrospective study to compare the classification, as normal, hypoplastic or aplastic, of thoracic (T10-T13) caudal articular process (CAP) morphology in Pug dogs with a thoracolumbar myelopathy as normal, hypoplastic or aplastic, between T2 weighted Turbo Spin Echo (T2W-TSE), in sagittal and transverse planes, and Volumetric Interpolated Breath-hold Examination (VIBE) Magnetic Resonance Imaging (MRI) sequences, in comparison to Computed Tomography (CT). We hypothesized a stronger agreement for VIBE in comparison to T2W-TSE.

Diagnostic accuracy of T2W-TSE was inferior to VIBE for aplastic (60%, 95% CI 0.561-0.639 vs. 78%, 95%CI 0.744-0.815) hypoplastic (44%, 95%CI 0.427-0.452 vs. 62.5%, 95%CI 0.595-0.655) and normal CAP (70%, 95%CI 0.655-0.744 vs. 87%, 95%CI 0.848-0.892). Superior accuracy of classification using VIBE vs. T2W-TSE sequences using the McNemar Chi squared test was significant for aplastic (p = 0.0002) and normal CAP (p = 0.004). VIBE sequences had a sensitivity of 96% and specificity of 75% to detect CAP abnormality and with T2W-TSE imaging sensitivity 81% and specificity of 75%.

Three-dimensionally reconstructable VIBE sequences were significantly more accurate than traditional T2W-TSE MRI sequences in classifying CAP morphology, which should reduce the need for CT for pre-operative assessment.

Despite being thirteen years since the installation of the first PET-MR system, the scanners constitute a very small proportion of the total hybrid PET systems installed. This is in stark contrast to the rapid expansion of the PET-CT scanner, which quickly established its importance in patient diagnosis within a similar timeframe. One of the main hurdles is the development of an accurate, reproducible and easy-to-use method for attenuation correction. Quantitative discrepancies in PET images between the manufacturer-provided MR methods and the more established CT- or transmission-based attenuation correction methods have led the scientific community in a continuous effort to develop a robust and accurate alternative. These can be divided into four broad categories: (i) MR-based, (ii) emission-based, (iii) atlas-based and the (iv) machine learning-based attenuation correction, which is rapidly gaining momentum. The first is based on segmenting the MR images in various tissues and allocating a predefined attenuation coefficient for each tissue. Emission-based attenuation correction methods aim in utilising the PET emission data by simultaneously reconstructing the radioactivity distribution and the attenuation image. Atlas-based attenuation correction methods aim to predict a CT or transmission image given an MR image of a new patient, by using databases containing CT or transmission images from the general population. Finally, in machine learning methods, a model that could predict the required image given the acquired MR or non-attenuation-corrected PET image is developed by exploiting the underlying features of the images. Deep learning methods are the dominant approach in this category. Compared to the more traditional machine learning, which uses structured data for building a model, deep learning makes direct use of the acquired images to identify underlying features. This up-to-date review goes through the literature of attenuation correction approaches in PET-MR after categorising them. The various approaches in each category are described and discussed. After exploring each category separately, a general overview is given of the current status and potential future approaches along with a comparison of the four outlined categories.

The ultrasmall, superparamagnetic iron oxide (USPIO) nanoparticle ferumoxytol has unique applications in cardiac, vascular, and body magnetic resonance imaging (MRI) due to its long intravascular half-life and suitability as a blood pool agent. However, limited availability and high cost have hindered its clinical adoption. A new ferumoxytol generic, and the emergence of MoldayION as an alternative USPIO, represent opportunities to expand the use of USPIO-enhanced MRI techniques.

To compare in vitro and in vivo MRI relaxometry and enhancement of Feraheme, generic ferumoxytol, and MoldayION.

Prospective.

Ten healthy swine and six swine with artificially induced coronary narrowing underwent cardiac MRI.

3.0 T; T1-weighted (4D-MUSIC, 3D-VIBE, 2D-MOLLI) and T2-weighted (2D-HASTE) sequences pre- and post-contrast.

We compared the MRI relaxometry of Feraheme, generic ferumoxytol, and MoldayION using saline, plasma, and whole blood MRI phantoms with contrast concentrations from 0.26 mM to 2.10 mM. In-vivo contrast effects on T1- and T2-weighted sequences and fractional intravascular contrast distribution volume in myocardium, liver, and spleen were evaluated.

Analysis of variance and covariance were used for group comparisons. A P value <0.05 was considered statistically significant.

The r1 relaxivities for Feraheme, generic ferumoxytol, and MoldayION in saline (22 °C) were 7.11 ± 0.13 mM-1  s-1 , 8.30 ± 0.29 mM-1  s-1 , 8.62 ± 0.16 mM-1  s-1 , and the r2 relaxivities were 111.74 ± 3.76 mM-1  s-1 , 105.07 ± 2.20 mM-1  s-1 , and 109.68 ± 2.56 mM-1  s-1 , respectively. The relationship between contrast concentration and longitudinal (R1) and transverse (R2) relaxation rate was highly linear in saline and plasma. The three agents produced similar in vivo contrast effects on T1 and T2 relaxation time-weighted sequences.

Relative to clinically approved ferumoxytol formulations, MoldayION demonstrates minor differences in in vitro relaxometry and comparable in vivo MRI characteristics.

2 TECHNICAL EFFICACY: Stage 1.

The 2-point DIXON method is widely used to assess fat fractions (FFs) in magnetic resonance images (MRIs) of the tongue, pharyngeal wall, and surrounding tissues in patients with obstructive sleep apnea (OSA). However, the method is semiquantitative and is susceptible to B0 field inhomogeneities and R2* confounding factors. Using the method, although several studies have shown that patients with OSA have increased fat deposition around the pharyngeal cavity, conflicting findings was also reported in 1 study. This discrepancy necessitates that we examine the FF estimation method used in the earlier studies and seek a more accurate method to measure FFs.

We examined the advantages of using the GOOSE (globally optimal surface estimation) method to replace the 2-point DIXON method for quantifying fat in the tongue and surrounding tissues on MRIs. We first used phantoms with known FFs (true FFs) to validate the GOOSE method and examine the errors in the DIXON method. Then, we compared the 2 methods in the tongue, soft palate, pharyngeal wall, and parapharyngeal fat pad of 63 healthy participants to further assess the errors caused by the DIXON method. Six participants were excluded from the comparison of the tongue FFs because of technical failures. Paired Student t tests were performed on FFs to detect significant differences between the 2 methods. All measures were obtained using 3 T Siemens MRI scanners.

In the phantoms, the FFs measured by GOOSE agreed with the true FF, with only a 1.2% mean absolute error. However, the same measure by DIXON had a 10.5% mean absolute error. The FFs obtained by DIXON were significantly lower than those obtained by GOOSE (P < 0.0001) in the human participants. We found strong correlations between GOOSE and DIXON in the tongue (R2 = 0.90), soft palate (R2 = 0.66), and parapharyngeal fat pad (R2 = 0.88), but the correlation was weaker in the posterior pharyngeal walls (R2 = 0.32) in participants.

The widely used 2-point DIXON underestimated FFs, relative to GOOSE, in phantom measurements and tissues studied in vivo. Thus, an advanced method, such as GOOSE, that uses multiecho complex data is preferred for estimating FF.

Purpose: The purpose of this study was to test the technical feasibility and the impact on the image quality of a deep learning-based super-resolution reconstruction algorithm in 1.5 T abdominopelvic MR imaging. Methods: 44 patients who underwent abdominopelvic MRI were retrospectively included, of which 4 had to be subsequently excluded. After the acquisition of the conventional volume interpolated breath-hold examination (VIBEStd), images underwent postprocessing, using a deep learning-based iterative denoising super-resolution reconstruction algorithm for partial Fourier acquisitions (VIBESR). Image analysis of 40 patients with a mean age of 56 years (range 18−84 years) was performed qualitatively by two radiologists independently using a Likert scale ranging from 1 to 5, where 5 was considered the best rating. Results: Image analysis showed an improvement of image quality, noise, sharpness of the organs and lymph nodes, and sharpness of the intestine for pre- and postcontrast images in VIBESR compared to VIBEStd (each p < 0.001). Lesion detectability was better for VIBESR (p < 0.001), while there were no differences concerning the number of lesions. Average acquisition time was 16 s (±1) for the upper abdomen and 15 s (±1) for the pelvis for VIBEStd, and 15 s (±1) for the upper abdomen and 14 s (±1) for the pelvis for VIBESR. Conclusion: This study demonstrated the technical feasibility of a deep learning-based super-resolution algorithm including partial Fourier technique in abdominopelvic MR images and illustrated a significant improvement of image quality, noise, and sharpness while reducing TA.

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

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

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

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

The aim of this study was to investigate the feasibility and impact of a novel deep learning superresolution algorithm tailored to partial Fourier allowing retrospectively theoretical acquisition time reduction in 1.5 T T1-weighted gradient echo imaging of the abdomen.

Fifty consecutive patients who underwent a 1.5 T contrast-enhanced magnetic resonance imaging examination of the abdomen between April and May 2021 were included in this retrospective study. After acquisition of a conventional T1-weighted volumetric interpolated breath-hold examination using Dixon for water-fat separation (VIBEStd), the acquired data were reprocessed including a superresolution algorithm that was optimized for partial Fourier acquisitions (VIBESR). To accelerate theoretically the acquisition process, a more aggressive partial Fourier setting was applied in VIBESR reconstructions practically corresponding to a shorter acquisition for the data included in the retrospective reconstruction. Precontrast, dynamic contrast-enhanced, and postcontrast data sets were processed. Image analysis was performed by 2 radiologists independently in a blinded random order without access to clinical data regarding the following criteria using a Likert scale ranging from 1 to 4 with 4 being the best: noise levels, sharpness and contrast of vessels, sharpness and contrast of organs and lymph nodes, overall image quality, diagnostic confidence, and lesion conspicuity.Wilcoxon signed rank test for paired data was applied to test for significance.

Mean patient age was 61 ± 14 years. Mean acquisition time for the conventional VIBEStd sequence was 15 ± 1 seconds versus theoretical 13 ± 1 seconds of acquired data used for the VIBESR reconstruction. Noise levels were evaluated to be better in VIBESR with a median of 4 (4-4) versus a median of 3 (3-3) in VIBEStd by both readers (P < 0.001). Sharpness and contrast of vessels as well as organs and lymph nodes were also evaluated to be superior in VIBESR compared with VIBEStd with a median of 4 (4-4) versus a median of 3 (3-3) (P < 0.001). Diagnostic confidence was also rated superior in VIBESR with a median of 4 (4-4) versus a median of 3.5 (3-4) in VIBEStd by reader 1 and with a median of 4 (4-4) for VIBESR and a median of 4 (4-4) for VIBEStd by reader 2 (both P < 0.001).

Image enhancement using deep learning-based superresolution tailored to partial Fourier acquisitions of T1-weighted gradient echo imaging of the abdomen provides improved image quality and diagnostic confidence in combination with more aggressive partial Fourier settings leading to shorter scan time.

This review introduces the basic principles of contrast-enhanced magnetic resonance (MR) angiography and details four contrast-enhanced MR angiography sequences for body imaging with extracellular gadolinium-based contrast agents in pediatric patients. Specifically, this review covers (1) respiratory-navigated, cardiac-gated MR angiography; (2) time-resolved MR angiography; (3) conventional MR angiography; and (4) modified spoiled gradient echo variants. We present and discuss indications, technical considerations, sequence optimization, advantages and disadvantages, along with practical tips and illustrative case examples for each sequence.

The 'loss of resistance' technique is used to determine entry into the epidural space, often by a midline needle in the interspinous ligament before the ligamentum flavum. Anatomical explanations for loss of resistance without entry into the epidural space are lacking. This investigation aimed to improve morphometric characterization of the lumbar interspinous ligament by observation and measurement at dissection and from MRI.

Measurements were made on 14 embalmed donor lumbar spines (T12 to S1) imaged with MRI and then dissected along a tilted axial plane aligned with the lumbar interspace.

In 73 interspaces, median (IQR) lumbar interspinous plus supraspinous ligament length was 29.7 mm (25.5-33.4). Posterior width was 9.2 mm (7.7, 11.9), with narrowing in the middle (4.5 mm (3.0, 6.8)) and an anterior width of 7.3 mm (5.7, 9.8).Fat-filled gaps were present within 55 (75%). Of 51 anterior gaps, 49 (67%) were related to the ligamenta flava junction. Median (IQR) gap length and width were 3.5 mm (2.5, 5.1) and 1.1 mm (0.9, 1.7).Detection of gaps with MRI had 100% sensitivity (95% CI 93.5 to 100), 94.4% specificity (72.7, 99.9), 98.2% (90.4, 100) positive predictive value and 100% (80.5, 100) negative predictive value against dissection as the gold standard.

The lumbar interspinous ligament plus supraspinous ligament are biconcave axially. It commonly has fat-filled gaps, particularly anteriorly. These anatomical features may form the anatomical basis for false or equivocal loss of resistance.

Advances in magnetic resonance imaging (MRI) technology now enable the feasible three-dimensional (3D) acquisition of images. With respect to the imaging of musculoskeletal (MSK) tumors, literature is beginning to accumulate on the use of 3D MRI acquisition for tumor detection and characterization. The benefits of 3D MRI, including general advantages, such as decreased acquisition time, isotropic resolution, and increased image quality, are not only inherently useful for tumor imaging, but they also contribute to the feasibility of more specialized tumor-imaging techniques, such as whole-body MRI, and are reviewed here. Disadvantages of 3D acquisition, such as motion artifact and equipment requirements, do exist and are also discussed. Although further study is needed, 3D MRI acquisition will likely prove increasingly useful in the evaluation of patients with tumors of the MSK system.

With its outstanding soft tissue contrast, spatial resolution, and multiplanar capacities, magnetic resonance imaging (MRI) has become a widely used technique. Whole-body MRI (WB-MRI) has been introduced among diagnostic methods for the staging and follow-up assessment in oncologic patients, and international guidelines recommend its use. In nononcologic applications, WB-MRI is as a promising imaging tool in inflammatory diseases, such as seronegative arthritis and inflammatory myopathies. Technological advances have facilitated the introduction of three-dimensional (3D) almost isotropic sequences in MRI examinations covering the whole body. The possibility to reformat 3D images in any plane with equal or almost equal resolution offers comprehensive understanding of the anatomy, easier disease detection and characterization, and finally contributes to correct treatment planning. This article illustrates the basic principles, advantages, and limitations of the 3D approach in WB-MRI examinations and provides a short review of the literature.

CT is the imaging modality of choice for assessment of 3D bony morphology but incurs the penalty of ionizing radiation. Improving the ability of 3D MRI to provide high-resolution images of cortical bone with CT-like bone contrast has been a focus of recent research. The ability of 3D MRI to deliver cortical bone information with similar diagnostic performance to CT would complement assessment of soft tissues and medullary bone from a single MRI examination, simplifying evaluation and obviating radiation exposure from additional CT. This article presents an overview of current 3D MRI approaches for imaging cortical bone with CT-like bone contrast including ultrashort echo time, zero echo time, T1-weighted gradient recalled echo, susceptibility-weighted imaging and deep learning techniques. We also discuss clinical implementation of an optimized stack-of-stars 3D gradient recalled echo pulse sequence (3D-Bone) on commercially available MRI scanners for rendering 3D MRI with CT-like bone contrast in our institutional practice.

There is a strong need for improvements in motion robust T1-weighted abdominal imaging sequences in children to enable high-quality, free-breathing imaging.

To compare imaging time and quality of a radial stack-of-stars, free-breathing T1-weighted gradient echo acquisition (volumetric interpolated breath-hold examination [VIBE]) three-dimensional (3-D) Dixon sequence in sedated pediatric patients undergoing abdominal magnetic resonance imaging (MRI) against conventional Cartesian T1-weighed sequences.

This study was approved by the institutional review board with informed consent obtained from all subjects. Study subjects included 31 pediatric patients (19 male, 12 female; median age: 5 years; interquartile range: 5 years) undergoing abdominal MRI at 3 tesla with a free-breathing T1-weighted radial stack-of-stars 3-D VIBE Dixon prototype sequence, StarVIBE Dixon (radial technique), between October 2018 and June 2019 with previous abdominal MR imaging using conventional Cartesian T1-weighed imaging (traditional technique). MRI component times were recorded as well as the total number of non-contrast T1-weighted sequences. Two radiologists independently rated images for quality using a scale from 1 to 5 according to the following metrics: overall image quality, hepatic edge sharpness, hepatic vessel clarity and respiratory motion robustness. Scores were compared between the groups.

Mean T1-weighted imaging times for all subjects were 3.63 min for radial exams and 8.01 min for traditional exams (P<0.001), and total non-contrast imaging time was 32.7 min vs. 43.9 min (P=0.002). Adjusted mean total MRI time for all subjects was 60.2 min for radial exams and 65.7 min for traditional exams (P=0.387). The mean number of non-contrast T1-weighted sequences performed in radial MRI exams was 1.0 compared to 1.9 (range: 0-6) in traditional exams (P<0.001). StarVIBE Dixon outperformed Cartesian methods in all quality metrics. The mean overall image quality (scale 1-5) was 3.95 for radial exams and 3.31 for traditional exams (P<0.001).

Radial stack-of-stars 3-D VIBE Dixon during free-breathing abdominal MRI in pediatric patients offers improved image quality compared to Cartesian T1-weighted imaging techniques with decreased T1-weighted and total non-contrast imaging time. This has important implications for children undergoing sedation for imaging.

The aim of this study was to investigate the impact of a deep learning-based superresolution reconstruction technique for T1-weighted volume-interpolated breath-hold examination (VIBESR) on image quality in comparison with standard VIBE images (VIBESD).

Between May and August 2020, a total of 46 patients with various abdominal pathologies underwent contrast-enhanced upper abdominal VIBE magnetic resonance imaging (MRI) at 1.5 T. After data acquisition, the precontrast and postcontrast T1-weighted VIBE raw data were processed by a deep learning-based prototype algorithm for deblurring and denoising the images as well as for enhancing their sharpness (VIBESR). In a randomized and blinded manner, 2 radiologists independently analyzed the image data sets using the unprocessed images VIBESD as a standard reference. Outcome measures were as follows: overall image quality, anatomic clarity of organ borders, sharpness of vessels, artifacts, noise, and diagnostic confidence. All ratings were performed on an ordinal 4-point Likert scale. If the MRI examination encompassed a hepatic lesion, the maximum diameter of the largest hepatic lesion was quantified, and lesion sharpness and conspicuity were evaluated on an ordinal 4-point Likert scale. In addition, a post hoc regression analysis for lesion evaluation was computed. Finally, interrater/intrarater agreement was analyzed.

The overall image quality, anatomic clarity of organ borders, and sharpness of vessels in both precontrast and postcontrast images were rated significantly higher in VIBESR than in VIBESD (P < 0.001). Similarly, diagnostic confidence was higher in VIBESR than in VIBESD (P < 0.001). Furthermore, VIBESR images were rated to have significantly less noise and fewer artifacts in comparison with VIBESD (P < 0.001). The interreader agreement was substantial with a Cohen κ of 0.72 for the precontrast analysis and a κ of 0.74 for the postcontrast analysis. A total of 28 hepatic lesions were analyzed. For both readers, lesion sharpness and conspicuity were rated significantly better in VIBESR than in VIBESD in both the precontrast and postcontrast data sets (P < 0.01), which was consistent with the post hoc regression analysis (for every 1-point increase in sharpness/conspicuity, the odds ratio revealed a positive relation with VIBESR of 13-fold to 17-fold in comparison with VIBESD; P < 0.001). In terms of lesion size, there was no significant difference between the precontrast VIBESD and VIBESR or between the postcontrast VIBESD and VIBESR for both readers. Similarly, there was an excellent interreader agreement regarding lesion size (intraclass correlation coefficient, >0.9).

The data-driven superresolution reconstruction (VIBESR) is clinically feasible for precontrast and postcontrast upper abdominal VIBE MRI, providing improved image quality, diagnostic confidence, and lesion conspicuity compared with standard VIBESD images.

The aim of this study was to investigate the impact of a novel edge enhancement and iterative denoising algorithm in 1.5-T T1-weighted dynamic contrast-enhanced (DCE) gradient echo (GRE) magnetic resonance imaging of the abdomen on image quality, noise levels, diagnostic confidence, and lesion detectability.

Fifty patients who underwent a clinically indicated magnetic resonance imaging with DCE imaging of the abdomen between June and August 2020 were included in this retrospective, monocentric, institutional review board-approved study. For DCE imaging, a series of 3 volume interpolated breath-hold examinations (VIBEs) was performed. The raw data of all DCE imaging studies were processed twice, once using standard reconstruction (DCES) and again using an edge enhancement and iterative denoising approach (DCEDE). All imaging studies were randomly reviewed by 2 radiologists independently regarding noise levels, arterial contrast, sharpness of vessels, overall image quality, and diagnostic confidence using a Likert scale ranging from 1 to 4, with 4 being the best. Furthermore, lesion detectability was evaluated using the same ranking system.

All 50 imaging studies were successfully reconstructed with both methods. Interreader agreement (Cohen κ) was substantial to perfect for both readers. Arterial contrast and sharpness of vessels were rated superior by both readers with a median of 4 in DCEDE versus a median of 3 in DCES (P < 0.001). Furthermore, noise levels as well as overall image quality were rated higher with a median of 4 in DCEDE compared with a median of 3 in DCES (P < 0.001). Lesion detectability was evaluated to be superior in DCEDE with a median of 4 versus DCES with a median of 3 (P < 0.001). Consequently, diagnostic confidence was also rated to be superior in DCEDE with a median of 4 versus DCES with a median of 3 (P < 0.001).

Iterative denoising and edge enhancement are feasible in DCE imaging of the abdomen providing superior arterial contrast, noise levels, and overall image quality. Furthermore, lesion detectability and diagnostic confidence were significantly improved using this novel reconstruction method. Further reduction of acquisition time might be possible via reduction of increased noise levels using this presented method.

A technical note is presented on the slab-direction aliasing of 3D imaging, introducing a simple methodology for determining the minimised duration of low flip-angle sinc radiofrequency (RF) excitation pulses, with respect to a required slab profile accuracy. The various interdependent factors affected in modifying an RF pulse duration are considered and analysed in the context of a new metric for quantifying the levels of permitted slab-aliasing. A general framework is presented for the selection of standard sinc RF excitation pulses with system-minimised durations, as well as their analysis and validation, and a demonstration of this methodology is performed for an example requirement and scanner. This methodology enables implementation of standard (vendor-generated) RF pulses with minimised duration for a required application, with high confidence in their operational reliability. Parts of such a methodology may also in theory be extended to more advanced RF pulse designs.

The aim of this study was to assess the reliability of using MRI scans to calculate the Spinal Instability Neoplastic Score (SINS) in patients with metastatic spinal cord compression (MSCC).

A total of 100 patients were retrospectively included in the study. The SINS score was calculated from each patient's MRI and CT scans by two consultant musculoskeletal radiologists (reviewers 1 and 2) and one consultant spinal surgeon (reviewer 3). In order to avoid potential bias in the assessment, MRI scans were reviewed first. Bland-Altman analysis was used to identify the limits of agreement between the SINS scores from the MRI and CT scans for the three reviewers.

The limit of agreement between the SINS score from the MRI and CT scans for the reviewers was -0.11 for reviewer 1 (95% CI 0.82 to -1.04), -0.12 for reviewer 2 (95% CI 1.24 to -1.48), and -0.37 for reviewer 3 (95% CI 2.35 to -3.09). The use of MRI tended to increase the score when compared with that using the CT scan. No patient having their score calculated from MRI scans would have been classified as stable rather than intermediate or unstable when calculated from CT scans, potentially leading to suboptimal care.

We found that MRI scans can be used to calculate the SINS score reliably, compared with the score from CT scans. The main difference between the scores derived from MRI and CT was in defining the type of bony lesion. This could be made easier by knowing the site of the primary tumour when calculating the score, or by using inverted T1-volumetric interpolated breath-hold examination MRI to assess the bone more reliably, similar to using CT. Cite this article: Bone Joint J 2021;103-B(5):971-975.

The aim of this study was to investigate the impact of a novel iterative denoising and image enhancement technique in T1-weighted precontrast and postcontrast volume-interpolated breath-hold examination (VIBE) of the abdomen on image quality, noise levels, and diagnostic confidence without change of acquisition parameters.

Fifty patients were included in this retrospective, monocentric, institutional review board-approved study after clinically indicated magnetic resonance imaging of the abdomen including T1-weighted precontrast and postcontrast imaging. After acquisition of the standard VIBE (VIBES), images were processed with a novel reconstruction algorithm using the same raw data as for VIBES, resulting in a denoised and enhanced dataset (VIBEDE). Two different radiologists evaluated both datasets in a randomized order regarding sharpness of organs as well as vessels, noise levels, artifacts, overall image quality, and diagnostic confidence using a Likert scale ranging from 1 to 4 with 4 being the best. Furthermore, in the presence of focal liver lesions, the largest lesion was measured in the postcontrast dataset, and lesion detectability was analyzed using a Likert scale (1-4).

Precontrast and postcontrast sharpness of organs and sharpness of vessels were rated significantly superior by both readers in VIBEDE with a median of 4 (interquartile range, 0) compared with VIBES with a median of 3 (1) (all P's < 0.0001). Precontrast and postcontrast noise levels were also rated superior by both readers in VIBEDE with a median of 4 (0) compared with VIBES with a median of 3 (1) for precontrast and a median of 3 (0) (median of 3 [1] for reader 2) for postcontrast imaging (all P's < 0.0001).Overall image quality was also rated higher with a median of 4 (0) in VIBEDE versus 3 (1) in VIBES (P < 0.0001). Twenty-seven imaging studies contained liver lesions. There was no difference regarding the number and localization between the readers and between VIBES and VIBEDE. Lesion detectability was rated by both readers significantly better in VIBEDE with a median of 4 (0) compared with a median of 4 (1) for reader 1 and a median of 3 (1) for reader 2 (P = 0.001 for reader 1; P < 0.001 for reader 2). Consequently, diagnostic confidence was also significantly superior in VIBEDE versus VIBES with a median of 4 (0) for both (P = 0.001). Interreader agreement resulted in a Cohen κ of 0.76 for precontrast analysis as well as of 0.76 for postcontrast analysis.

Application of a novel iterative denoising and image enhancement technique in T1-weighted VIBE precontrast and postcontrast imaging of the abdomen is feasible, providing superior image quality, noise levels, and diagnostic confidence.