Cardiac Cine MRI Using a Commercially Available 0.55-T Scanner.

Purpose To compare parameters of left ventricular (LV) and right ventricular (RV) volume and function between a commercially available 0.55-T low-field-strength cardiac cine MRI scanner and a 1.5-T scanner. Materials and Methods In this prospective study, healthy volunteers (May 2022 to July 2022) underwent same-day cine imaging using both scanners (0.55 T, 1.5 T). Volumetric and functional parameters were assessed by two experts. After analyzing the results of a blinded crossover reader study of the healthy volunteers, 20 participants with clinically indicated cardiac MRI were prospectively included (November 2022 to February 2023). In a second blinded expert reading, parameters from clinical 1.5-T scans in these participants were compared with those same-day 0.55-T scans. Results are displayed as Bland-Altman plots. Results Eleven healthy volunteers (mean age: 33 years [95% CI: 27, 40]; four of 11 [36%] female, seven of 11 [64%] male) were included. Very strong mean correlation was observed (r = 0.98 [95% CI: 0.97, 0.98]). Average deviation between MRI systems was 1.6% (95% CI: 0.3, 2.9) for both readers. Twenty participants with clinically indicated cardiac MRI were included (mean age: 55 years [95% CI: 48, 62], six of 20 [30%] female, 14 of 20 [70%] male). Mean correlation was very strong (r = 0.98 [95% CI: 0.97, 0.98]). LV and RV parameters demonstrated an average deviation of 1.1% (95% CI: 0.1, 2.1) between MRI systems. Conclusion Cardiac cine MRI at 0.55 T yielded comparable results for quantitative biventricular volumetric and functional parameters compared with routine imaging at 1.5 T, if acquisition time is doubled. Keywords: Cardiac, Comparative Studies, Heart, Cardiovascular MRI, Cine, Myocardium Supplemental material is available for this article. ©RSNA, 2024.

Diagnosing periprosthetic hip joint infection with new-generation 0.55T MRI.

PURPOSE: To assess the accuracy of 0.55 T MRI in diagnosing periprosthetic joint infection (PJI) in patients with symptomatic total hip arthroplasty (THA). MATERIAL AND METHODS: 0.55 T MRI of patients with THA PJI (Group A) and noninfected THA (Group B), including aseptic loosening (Group C, subgroup of B) performed between May 2021 and July 2023 were analysed retrospectively. Two musculoskeletal fellowship-trained radiologists independently identified MRI bone and soft tissue changes including: marrow oedema, periosteal reaction, osteolysis, joint effusion, capsule oedema and thickening, fluid collections, muscle oedema, bursitis, inguinal adenopathy, and muscle tears. The diagnostic performance of MRI discriminators of PJI was evaluated using Fisher's exact test (p < 0.05) and interrater reliability was determined. 61 MRI scans from 60 THA patients (34 female, median age 68, range 41-93 years) in Group A (n = 9; female 4; median age 69, range 56-82 years), B (n = 51; 30; 67.5, 41-93 years), and C (10; 6; 67; 41-82 years) were included. RESULTS: Capsule oedema (sensitivity 89 %, specificity 92 %,), intramuscular oedema (89 %, 82 %) and joint effusion (89 %, 73 %) were the best performing discriminators for PJI diagnosis (p ≤ 0.001), when viewed individually and had combined 70 % sensitivity and 100 % specificity for PJI diagnosis in parallel testing. For the differentiation between PJI and aseptic loosening, intramuscular oedema (89 %, 80 %) and capsule oedema (89 %, 80 %) were significant discriminators (p ≤ 0.001) with combined 64 % sensitivity and 96 % specificity for PJI. CONCLUSIONS: New generation 0.55 T MRI may aid in the detection of PJI in symptomatic patients. Oedema of the joint capsule, adjacent muscles as well as joint effusion were indicative of the presence of PJI.

Deep Learning Reconstructed New-Generation 0.55 T MRI of the Knee-A Prospective Comparison With Conventional 3 T MRI.

OBJECTIVES: The aim of this study was to compare deep learning reconstructed (DLR) 0.55 T magnetic resonance imaging (MRI) quality, identification, and grading of structural anomalies and reader confidence levels with conventional 3 T knee MRI in patients with knee pain following trauma. MATERIALS AND METHODS: This prospective study of 26 symptomatic patients (5 women) includes 52 paired DLR 0.55 T and conventional 3 T MRI examinations obtained in 1 setting. A novel, commercially available DLR algorithm was employed for 0.55 T image reconstruction. Four board-certified radiologists reviewed all images independently and graded image quality, noted structural anomalies and their respective reporting confidence levels for the presence or absence, as well as grading of bone, cartilage, meniscus, ligament, and tendon lesions. Image quality and reader confidence levels were compared (P < 0.05, significant), and MRI findings were correlated between 0.55 T and 3 T MRI using Cohen kappa (κ). RESULTS: In reader's consensus, good image quality was found for DLR 0.55 T MRI and 3 T MRI (3.8 vs 4.1/5 points, P = 0.06). There was near-perfect agreement between 0.55 T DLR and 3 T MRI regarding the identification of structural anomalies for all readers (each κ ≥ 0.80). Substantial to near-perfection agreement between 0.55 T and 3 T MRI was reported for grading of cartilage (κ = 0.65-0.86) and meniscus lesions (κ = 0.71-1.0). High confidence levels were found for all readers for DLR 0.55 T and 3 T MRI, with 3 readers showing higher confidence levels for reporting cartilage lesions on 3 T MRI. CONCLUSIONS: In conclusion, new-generation 0.55 T DLR MRI provides good image quality, comparable to conventional 3 T MRI, and allows for reliable identification of internal derangement of the knee with high reader confidence.

Advanced deep learning-based image reconstruction in lumbar spine MRI at 0.55 T - Effects on image quality and acquisition time in comparison to conventional deep learning-based reconstruction.

Objectives: To evaluate an optimized deep leaning-based image post-processing technique in lumbar spine MRI at 0.55 T in terms of image quality and image acquisition time. Materials and methods: Lumbar spine imaging was conducted on 18 patients using a 0.55 T MRI scanner, employing conventional (CDLR) and advanced (ADLR) deep learning-based post-processing techniques. Two musculoskeletal radiologists visually evaluated the images using a 5-point Likert scale to assess image quality and resolution. Quantitative assessment in terms of signal intensities (SI) and contrast ratios was performed by region of interest measurements in different body-tissues (vertebral bone, intervertebral disc, spinal cord, cerebrospinal fluid and autochthonous back muscles) to investigate differences between CDLR and ADLR sequences. Results: The images processed with the advanced technique (ADLR) were rated superior to the conventional technique (CDLR) in terms of signal/contrast, resolution, and assessability of the spinal canal and neural foramen. The interrater agreement was moderate for signal/contrast (ICC = 0.68) and good for resolution (ICC = 0.77), but moderate for spinal canal and neuroforaminal assessability (ICC = 0.55). Quantitative assessment showed a higher contrast ratio for fluid-sensitive sequences in the ADLR images. The use of ADLR reduced image acquisition time by 44.4%, from 14:22 min to 07:59 min. Conclusions: Advanced deep learning-based image reconstruction algorithms improve the visually perceived image quality in lumbar spine imaging at 0.55 T while simultaneously allowing to substantially decrease image acquisition times. Clinical relevance: Advanced deep learning-based image post-processing techniques (ADLR) in lumbar spine MRI at 0.55 T significantly improves image quality while reducing image acquisition time.

The learning curve for robotic-assisted transperineal MRI/US fusion-guided prostate biopsy.

Transperineal fusion prostate biopsy has a considerable learning curve (LC). Robotic-assisted transperineal MRI/Ultrasound fusion-guided biopsy (RA-TP-FBx) may have an easier LC due to automatization. We aimed to assess the LC of RA-TP-FBx and analyze its most difficult steps. We prospectively analyzed cases randomized to a biopsy-naïve urology resident, the chief resident, and an expert urologist in RA-TP-FBx (controls). We also analyzed consecutive cases in the LC of the expert. The LC was defined by procedure time, PCa detection rate (including stratification by PI-RADS), entrustable professional activities (EPA) assessment scores, and the NASA task load index. We collectively performed 246 RA-TP-FBx with the Mona Lisa device. Procedure time for residents decreased steeply from maximum 53 min to minimum 10 min, while the mean procedure time for the expert was 9 min (range 17-5 min). PCa detection for PI-RADS-4 lesions was 57% for the naïve resident, 61% for the chief resident and 62% for the expert. There was also no difference in Pca detection for PI-RADS-4 lesions when comparing the first and second half of the experts' biopsies (p = 0.8). Maximum EPA score was registered after 22 cases. Workload steeply declined. Proficient RA-TP-FBx performance appears feasible after 22 cases regardless of previous experience.

Comparing Metal Artifact Severity and Ability to Assess Near-Metal Anatomy Between 0.55 T and 1.5 T MRI in Patients with Metallic Spinal Implants-A Scanner Comparison Study.

RATIONALE AND OBJECTIVES: To compare image quality and metal artifact severity at 0.55 T and 1.5 T MRI in patients with spinal implants following posterior fusion surgery. MATERIALS AND METHODS: 50 consecutive patients (mean age: 69 ±â€¯12 years) who underwent 0.55 T and 1.5 T MRI following posterior fusion surgery of the lumbar or thoracolumbar spine were included. Examinations used metal artifact reduction protocols from clinical routine. Images were rated by two fellowship-trained musculoskeletal radiologists for image quality, ability to assess the spinal canal and the neural foramina, and artifact severity on 5-point Likert scales. Additionally, differences in artifact severity and visibility of near-metal anatomy among implant sizes (1-level vs. 2-level vs. >2-levels) were evaluated. RESULTS: Signal/contrast (mean: 4.0 ±â€¯0.3 [0.55 T] vs. 4.4 ±â€¯0.6 [1.5 T]; p < .001) and resolution (3.8 ±â€¯0.5 vs. 4.2 ±â€¯0.7; p < .001) were rated lower at 0.55 T. The ability to assess the spinal canal (4.4 ±â€¯0.5 vs. 4.2 ±â€¯0.9; p = .69) and the neural foramina (3.8 ±â€¯0.5 vs. 3.8 ±â€¯0.9; p = .19) were however rated equally good with excellent interrater agreement (range: 0.84-0.94). Susceptibility artifacts were rated milder at 0.55 T (1.8 ±â€¯0.5 vs. 3.0 ±â€¯0.6; p < .001). For implant size-based subgroups, the visibility of near-metal anatomy decreased with implant length at 1.5 T, but remained unchanged at 0.55 T. In consequence, the spinal canal and neural foramina could be better assessed at 0.55 T in patients with multi-level implants (4.4 ±â€¯0.5 vs. 3.6 ±â€¯1.1; p < .001). CONCLUSION: Metal artifacts of spinal implants are substantially less pronounced at 0.55 T MRI. When examining patients with multi-level posterior fusion, this translates into a superior ability to assess near-metal anatomy, where 1.5 T MRI reaches diagnostic limitations.

New-Generation 0.55 T MRI of the Knee-Initial Clinical Experience and Comparison With 3 T MRI.

OBJECTIVES: The aim of this study was to compare the detection rate of and reader confidence in 0.55 T knee magnetic resonance imaging (MRI) findings with 3 T knee MRI in patients with acute trauma and knee pain. MATERIALS AND METHODS: In this prospective study, 0.55 T and 3 T knee MRI of 25 symptomatic patients (11 women; median age, 38 years) with suspected internal derangement of the knee was obtained in 1 setting. On the 0.55 T system, a commercially available deep learning image reconstruction algorithm was used (Deep Resolve Gain and Deep Resolve Sharp; Siemens Healthineers), which was not available on the 3 T system. Two board-certified radiologists reviewed all images independently and graded image quality parameters, noted MRI findings and their respective reporting confidence level for the presence or absence, as well as graded the bone, cartilage, meniscus, ligament, and tendon lesions. Image quality and reader confidence levels were compared ( P < 0.05 = significant), and clinical findings were correlated between 0.55 T and 3 T MRI by calculation of the intraclass correlation coefficient (ICC). RESULTS: Image quality was rated higher at 3 T compared with 0.55 T studies (each P ≤ 0.017). Agreement between 0.55 T and 3 T MRI for the detection and grading of bone marrow edema and fractures, ligament and tendon lesions, high-grade meniscus and cartilage lesions, Baker cysts, and joint effusions was perfect for both readers. Overall identification and grading of cartilage and meniscal lesions showed good agreement between high- and low-field MRI (each ICC > 0.76), with lower agreement for low-grade cartilage (ICC = 0.77) and meniscus lesions (ICC = 0.49). There was no difference in readers' confidence levels for reporting lesions of bone, ligaments, tendons, Baker cysts, and joint effusions between 0.55 T and 3 T (each P > 0.157). Reader reporting confidence was higher for cartilage and meniscal lesions at 3 T (each P < 0.041). CONCLUSIONS: New-generation 0.55 T knee MRI, with deep learning-aided image reconstruction, allows for reliable detection and grading of joint lesions in symptomatic patients, but it showed limited accuracy and reader confidence for low-grade cartilage and meniscal lesions in comparison with 3 T MRI.

Radiology weather forecast: A retrospective analysis of predictability of median daily polytrauma-CT occurrence based on weather data.

OBJECTIVES: Resource planning is a crucial component in hospitals, particularly in radiology departments. Since weather conditions are often described to correlate with emergency room visits, we aimed to forecast the amount of polytrauma-CTs using weather information. DESIGN: All polytrauma-CTs between 01/01/2011 and 12/31/2022 (n = 6638) were retrieved from the radiology information system. Local weather data was downloaded from meteoblue.com. The data was normalized and smoothened. Daily polytrauma-CT occurrence was stratified into below median and above median number of daily polytrauma-CTs. Logistic regression and machine learning algorithms (neural network, random forest classifier, support vector machine, gradient boosting classifier) were employed as prediction models. Data from 2012 to 2020 was used for training, data from 2021 to 2022 for validation. RESULTS: More polytrauma-CTs were acquired in summer compared with winter months, demonstrating a seasonal change (median: 2.35; IQR 1.60-3.22 vs. 2.08; IQR 1.36-3.03; p <.001). Temperature (rs = 0.45), sunshine duration (rs = 0.38) and ultraviolet light amount (rs = 0.37) correlated positively, wind velocity (rs = -0.57) and cloudiness (rs = -0.28) correlated negatively with polytrauma-CT occurrence (all p <.001). The logistic regression model for identification of days with above median number of polytrauma-CTs achieved an accuracy of 87 % on training data from 2011 to 2020. When forecasting the years 2021-2022 an accuracy of 65 % was achieved. A neural network and a support vector machine both achieved a validation accuracy of 72 %, whereas all classifiers regarded wind velocity and ultraviolet light amount as the most important parameters. CONCLUSION: It is possible to forecast above or below median daily number of polytrauma-CTs using weather data. CLINCICAL RELEVANCE STATEMENT: Prediction of polytrauma-CT examination volumes may be used to improve resource planning.

TotalSegmentator: Robust Segmentation of 104 Anatomic Structures in CT Images.

Purpose: To present a deep learning segmentation model that can automatically and robustly segment all major anatomic structures on body CT images. Materials and Methods: In this retrospective study, 1204 CT examinations (from 2012, 2016, and 2020) were used to segment 104 anatomic structures (27 organs, 59 bones, 10 muscles, and eight vessels) relevant for use cases such as organ volumetry, disease characterization, and surgical or radiation therapy planning. The CT images were randomly sampled from routine clinical studies and thus represent a real-world dataset (different ages, abnormalities, scanners, body parts, sequences, and sites). The authors trained an nnU-Net segmentation algorithm on this dataset and calculated Dice similarity coefficients to evaluate the model's performance. The trained algorithm was applied to a second dataset of 4004 whole-body CT examinations to investigate age-dependent volume and attenuation changes. Results: The proposed model showed a high Dice score (0.943) on the test set, which included a wide range of clinical data with major abnormalities. The model significantly outperformed another publicly available segmentation model on a separate dataset (Dice score, 0.932 vs 0.871; P < .001). The aging study demonstrated significant correlations between age and volume and mean attenuation for a variety of organ groups (eg, age and aortic volume [rs = 0.64; P < .001]; age and mean attenuation of the autochthonous dorsal musculature [rs = -0.74; P < .001]). Conclusion: The developed model enables robust and accurate segmentation of 104 anatomic structures. The annotated dataset (https://doi.org/10.5281/zenodo.6802613) and toolkit (https://www.github.com/wasserth/TotalSegmentator) are publicly available.Keywords: CT, Segmentation, Neural Networks Supplemental material is available for this article. © RSNA, 2023See also commentary by Sebro and Mongan in this issue.

Assessment of hepatic function employing hepatocyte specific contrast agent concentrations to multifactorially evaluate fibrotic remodeling.

Background: Diffuse parenchymal liver diseases are contributing substantially to global morbidity and represent major causes of deaths worldwide. The aim of our study is to assess whether established hepatic fat and iron quantitation and relaxometry-based quantification of hepatocyte-specific contrast material as surrogate for liver function estimation allows to evaluate liver fibrosis. Methods: Retrospective consecutive study. Seventy-two healthy patients (mean age: 53 years) without known liver disease, 21 patients with temporary elevated liver enzymes (mean: 65 years) and 109 patients with biopsy proven liver fibrosis or cirrhosis (mean: 61 years), who underwent liver magnetic resonance imaging (MRI) with a hepatocyte-specific contrast agent [gadoxetate disodium, gadolinium ethoxybenzyl-diethylenetriaminepentaacetic acid (Gd-EOB-DTPA), 0.25 mmol/mL Primovist, Bayer AG, Leverkusen, Germany] at 1.5 T (n=133) and at 3 T (n=69), were included. Fibrosis was classified using the histopathological meta-analysis of histological data in viral hepatitis (METAVIR) and the clinical Child-Pugh scores. Gd-concentration were quantified using T1 map-based calculations. Gd-concentration mapping was performed by using a Look-Locker approach prior to and 912±159 s after intravenous administration of hepatocyte specific contrast agent. Additionally, parenchymal fat fraction, R2*, bilirubin, gender and age were defined as predicting factors. Diagnostic accuracy was calculated in a monoparametric (linear regression, predictor: Gd-concentration) and multiparametric model (predictors: age, bilirubin level, iron overload, liver fat fraction, Gd concentration in the left and right liver lobe). Results: Mean Gd-concentration in the liver parenchyma was significantly higher for healthy patients ([Gd] =0.51 µmol/L) than for those with liver fibrosis or cirrhosis ([Gd] =0.31 µmol/L; P<0.0001) and with acute liver disease ([Gd] =0.28 µmol/L), though there were no significant differences for the latter two groups. There was a significant moderate negative correlation for the mean Gd-concentration and the METAVIR score (ρ=-0.44, P<0.0001) as well as for the Child-Pugh stage (ρ=-0.35, P<0.0001). There was a significant strong correlation between the bilirubin concentration and the Gd-concentration (ρ=-0.61, P<0.0001). The diagnostic accuracy for the discrimination of healthy patients and patients with known fibrosis or cirrhosis was 0.74 (0.71/0.60 sensitivity/specificity) in a monoparametric and 0.76 (0.85/0.61 sensitivity/specificity) in a machine learning based multiparametric model. Conclusions: T1 mapping-based quantification of hepatic Gd-EOB-DTPA concentrations performed in a multiparametric model shows promising diagnostic accuracy for the detection of fibrotic changes. Liver biopsy might be replaced by imaging examinations.

Machine Learning for Onset Prediction of Patients with Intracerebral Hemorrhage.

OBJECTIVE: Intracerebral hemorrhage (ICH) has a high mortality and long-term morbidity and thus has a significant overall health-economic impact. Outcomes are especially poor if the exact onset is unknown, but reliable imaging-based methods for onset estimation have not been established. We hypothesized that onset prediction of patients with ICH using artificial intelligence (AI) may be more accurate than human readers. MATERIAL AND METHODS: A total of 7421 computed tomography (CT) datasets between January 2007-July 2021 from the University Hospital Basel with confirmed ICH were extracted and an ICH-segmentation algorithm as well as two classifiers (one with radiomics, one with convolutional neural networks) for onset estimation were trained. The classifiers were trained based on the gold standard of 644 datasets with a known onset of >1 and <48 h. The results of the classifiers were compared to the ratings of two radiologists. RESULTS: Both the AI-based classifiers and the radiologists had poor discrimination of the known onsets, with a mean absolute error (MAE) of 9.77 h (95% CI (confidence interval) = 8.52-11.03) for the convolutional neural network (CNN), 9.96 h (8.68-11.32) for the radiomics model, 13.38 h (11.21-15.74) for rater 1 and 11.21 h (9.61-12.90) for rater 2, respectively. The results of the CNN and radiomics model were both not significantly different to the mean of the known onsets (p = 0.705 and p = 0.423). CONCLUSIONS: In our study, the discriminatory power of AI-based classifiers and human readers for onset estimation of patients with ICH was poor. This indicates that accurate AI-based onset estimation of patients with ICH based only on CT-data may be unlikely to change clinical decision making in the near future. Perhaps multimodal AI-based approaches could improve ICH onset prediction and should be considered in future studies.

Chronic stage magnetic resonance imaging findings in patients with shoulder injury related to vaccine administration (SIRVA).

PURPOSE: Identify chronic shoulder MRI findings in patients with known shoulder injury related to vaccine administration (SIRVA). MATERIALS AND METHODS: Two fellowship-trained musculoskeletal radiologists retrospectively reviewed the MRI of nine patients with clinically established SIRVA. MRI was performed at least 4 weeks after vaccination and included intravenous contrast-enhanced sequences. MRI was reviewed for the presence of erosions, tendonitis, capsulitis, synovitis, bone marrow oedema, joint effusion, bursitis, cartilage defects, rotator cuff lesions, and lymphadenopathy. The number and location of focal lesions were recorded. RESULTS: Erosions of the greater tuberosity were present in 8/9 (89%), tendonitis of the infraspinatus muscle tendon in 7/9 (78%), capsulitis, synovitis, and bone marrow oedema in 5/9 (56%) cases, respectively. Effusion was found in three, and subdeltoid bursitis, rotator cuff lesions as well as cartilage defects in one patient, respectively. None of our included subjects showed axillary lymphadenopathy. CONCLUSION: In this case series, greater humeral tuberosity erosions, infraspinatus muscle tendonitis, capsulitis, synovitis, and bone marrow oedema were common MRI findings in chronic SIRVA.

Prospective Assessment of Cerebral Microbleeds with Low-Field Magnetic Resonance Imaging (0.55 Tesla MRI).

PURPOSE: Accurate detection of cerebral microbleeds (CMBs) on susceptibility-weighted (SWI) magnetic resonance imaging (MRI) is crucial for the characterization of many neurological diseases. Low-field MRI offers greater access at lower costs and lower infrastructural requirements, but also reduced susceptibility artifacts. We therefore evaluated the diagnostic performance for the detection of CMBs of a whole-body low-field MRI in a prospective cohort of suspected stroke patients compared to an established 1.5 T MRI. METHODS: A prospective scanner comparison was performed including 27 patients, of whom 3 patients were excluded because the time interval was >1 h between acquisition of the 1.5 T and 0.55 T MRI. All SWI sequences were assessed for the presence, number, and localization of CMBs by two neuroradiologists and additionally underwent a Likert rating with respect to image impression, resolution, noise, contrast, and diagnostic quality. RESULTS: A total of 24 patients with a mean age of 74 years were included (11 female). Both readers detected the same number and localization of microbleeds in all 24 datasets (sensitivity and specificity 100%; interreader reliability Ï° = 1), with CMBs only being observed in 12 patients. Likert ratings of the sequences at both field strengths regarding overall image quality and diagnostic quality did not reveal significant differences between the 0.55 T and 1.5 T sequences (p = 0.942; p = 0.672). For resolution and contrast, the 0.55 T sequences were even significantly superior (p < 0.0001; p < 0.0003), whereas the 1.5 T sequences were significantly superior (p < 0.0001) regarding noise. CONCLUSION: Low-field MRI at 0.55 T may have similar accuracy as 1.5 T scanners for the detection of microbleeds and thus may have great potential as a resource-efficient alternative in the near future.

CNN-based evaluation of bone density improves diagnostic performance to detect osteopenia and osteoporosis in patients with non-contrast chest CT examinations.

PURPOSE: As osteoporosis is still underdiagnosed by clinicians and radiologists, the aim of the present study was to assess the performance of an Artificial intelligence (AI)-based Convolutional Neuronal Network (CNN)-Algorithm for the detection of low bone density on routine non-contrast chest CT in comparison to clinical reports using DEXA scans as reference. METHOD: This retrospective cross-sectional study included patients who underwent non-contrast chest CT and DEXA between April 2018 and June 2018 (n = 109, 19 men, mean age: 67.7 years). CT studies were evaluated for thoracic vertebral bone pathologies using a CNN-Algorithm, which calculates the attenuation profile of the spine. The content of the radiological reports was evaluated for the description of osteoporosis or osteopenia. DEXA was used as the reference standard. To estimate correlation the Spearman test was used and the comparison of the different groups was performed using the Wilcoxon rank sum test. Diagnostic was evaluated by performing a receiver operating characteristic curve analysis. RESULTS: The DEXA examination revealed normal bone density in 42 patients, while 49 patients had osteopenia and 7 osteoporosis. There was a statistically significant correlation between the mean CNN-based attenuation of the thoracic spine and the bone density measured on the DEXA in the hip (r = 0.51, p < 0.001) and lumbar spine (r = 0.34, p = 0.01). The mean attenuation was significantly higher in patients with normal bone density (172 ± 44.5 HU) compared to those with osteopenia or osteoporosis (125.2 ± 33.8 HU), (p < 0.0001). Diagnostic performance in distinguishing normal from abnormal bone density was higher using the CNN-based vertebral attenuation (accuracy 0.75, sensitivity: 0.93, specificity: 0.61) compared to clinical reports (accuracy 0.51, sensitivity: 0.14, specificity: 0.53). CONCLUSION: CNN-based evaluation of bone density may provide additional value over standard clinical reports for the detection of osteopenia and osteoporosis in patients undergoing routine non-contrast chest CT scans. This additional value could improve identification of fracture risk and subsequent treatment.

Visual and quantitative assessment of hip implant-related metal artifacts at low field MRI: a phantom study comparing a 0.55-T system with 1.5-T and 3-T systems.

BACKGROUND: To investigate hip implant-related metal artifacts on a 0.55-T system compared with 1.5-T and 3-T systems. METHODS: Total hip arthroplasty made of three different alloys were evaluated in a water phantom at 0.55, 1.5, and 3 T using routine protocols. Visually assessment (VA) was performed by three readers using a Likert scale from 0 (no artifacts) to 6 (extremely severe artifacts). Quantitative assessment (QA) was performed using the coefficient of variation (CoV) and the fraction of voxels within a threshold of the mean signal intensity compared to an automatically defined region of interest (FVwT). Agreement was evaluated using intra/inter-class correlation coefficient (ICC). RESULTS: Interreader agreement of VA was strong-to-moderate (ICC 0.74-0.82). At all field strengths (0.55-T/1.5-T/3-T), artifacts were assigned a lower score for titanium (Ti) alloys (2.44/2.9/2.7) than for stainless steel (Fe-Cr) (4.1/3.9/5.1) and cobalt-chromium (Co-Cr) alloys (4.1/4.1/5.2) (p < 0.001 for both). Artifacts were lower for 0.55-T and 1.5-T than for 3-T systems, for all implants (p ≤ 0.049). A strong VA-to-QA correlation was found (r = 0.81; p < 0.001); CoV was lower for Ti alloys than for Fe-Cr and Co-Cr alloys at all field strengths. The FVwT showed a negative correlation with VA (-0.68 < r < -0.84; p < 0.001). CONCLUSIONS: Artifact intensity was lowest for Ti alloys at 0.55 T. For other alloys, it was similar at 0.55 T and 1.5 T, higher at 3 T. Despite an inferior gradient system and a larger bore width, the 0.55-T system showed the same artifact intensity of the 1.5-T system.

Image Quality of Lumbar Spine Imaging at 0.55T Low-Field MRI is Comparable to Conventional 1.5T MRI - Initial Observations in Healthy Volunteers.

RATIONALE AND OBJECTIVES: To assess the potential of 0.55T low-field MRI system in lumbar spine imaging with and without the use of additional advanced postprocessing techniques. MATERIALS AND METHODS: The lumbar spine of 14 volunteers (32.9 ± 3.6 years) was imaged both at 0.55T and 1.5T using sequences from clinical routine. On the 0.55T scanner system, additional sequences with simultaneous multi-slice acquisition and artificial intelligence-based postprocessing techniques were acquired. Image quality of all 28 examinations was assessed by three musculoskeletal radiologists with respect to signal/contrast, resolution, and assessability of the spinal canal and neuroforamina using a 5-point Likert scale (1 = non-diagnostic to 5 = perfect quality). Interrater agreement was evaluated with the Intraclass Correlation Coefficient and the Mann-Whitney U test (significance level: p < 0.05). RESULTS: Image quality at 0.55T was rated lower on the 5-point Likert scale compared to 1.5T regarding signal/contrast (mean: 4.16 ± 0.29 vs. 4.54 ± 0.29; p < 0.001), resolution (4.07 ± 0.31 vs. 4.49 ± 0.30; p < 0.001), assessability of the spinal canal (4.28 ± 0.13 vs. 4.73 ± 0.26; p < 0.001) and the neuroforamina (4.14 ± 0.28 vs. 4.70 ± 0.27; p < 0.001). Image quality for the AI-processed sagittal T1 TSE and T2 TSE at 0.55T was also rated slightly lower, but still good to perfect with a concomitant reduction in measurement time. Interrater agreement was good to excellent (range: 0.60-0.91). CONCLUSION: While lumbar spine image quality at 0.55T is perceived inferior to imaging at 1.5T by musculoskeletal radiologists, good overall examination quality was observed with high interrater agreement. Advanced postprocessing techniques may accelerate intrinsically longer acquisition times at 0.55T.

The impact of robotic-assisted transperineal biopsy of the prostate on erectile function.

BACKGROUND: Prostate biopsy represents one of the most frequently performed urologic procedures worldwide and therefore presupposes knowledge on potential effects like on the erectile function, especially in extensive or repeated biopsies. The robotic-assisted biopsy system (Mona Lisa) offers a minimal invasive approach via only two incision points ensuring maximal accuracy combined with protection of the neurovascular bundle of the prostate. OBJECTIVE: Our purpose was to analyse the impact of robotic-assisted transperineal biopsy of the prostate on the erectile function. METHODS: Our prospective study analyses the outcomes of 210 patients, who had undergone minimal-invasive, transperineal robotic-assisted biopsy of the prostate at the University Hospital Basel from January 2020 to March 2022 and provided sufficient data. Of these, 157 (74.8%) were included in final analysis. RESULTS: Mean (range) age, prostate volume, PSA and IIEF-5 score at baseline were 63.8 years (46.1-83.6), 46.4 ml (9-310), 13.2 ng/ml (0.2-561), and 18.8 points (6-25), respectively. EF before and 1 month after intervention was assessed with the IIEF-5 questionnaire for the whole cohort. No significant change of IIEF-5 was observed for the whole cohort with a mean (± SD) decrease of 0.4 (± 3.1) points. Except for patients > 69 years, subgroup analysis revealed no change of IIEF-5 in statistically significant manner for all subgroups. Number of biopsy cores (< 20 and ≥ 20), previous biopsies and active surveillance showed no significant influence. CONCLUSION: Our results suggest that the minimally invasive and highly precise robotic technique can spare the erectile function without limiting the extent of biopsy and without compromising diagnostic accuracy.

Safety profile of robotic-assisted transperineal MRI-US-fusion guided biopsy of the prostate.

Introduction: Robotic-assisted transperineal MRI-US-fusion guided biopsy of the prostate is a novel and highly accurate procedure. The aim of this study was to evaluate the MonaLisa prostate biopsy system in terms of safety, tolerability, and patient-related outcomes. Methods: This prospective study included 228 patients, who had undergone Robotic-assisted transperineal MRI-US-fusion guided biopsy of the prostate at the University Hospital Basel between January 2020 and June 2022. Peri-operative side effects, functional outcomes and patient satisfaction were assessed. Results: Mean pain score on the day of biopsy was 1.3 points on VAS, which remained constant on the day after biopsy. Overall, 32 of 228 patients (14%) developed grade I complications according to Clavien-Dindo classification. No higher-grade complications occurred. Gross haematuria, hematospermia and acute urinary retention occurred in 145/228 (63.6%), 98/228 (43%) and 32/228 (14%) patients, respectively. One patient (0.4%) developed urinary tract infection. Conclusions: Robotic-assisted transperineal MRI-US-fusion guided biopsy of the prostate performed under general anesthesia is a safe and well tolerated procedure. This technique allows to omit perioperative prophylaxis and at the same time minimizes the risk of infectious complications. We attribute the favorable risk profile and tolerability to the minimal invasive approach via two entry points.

More Space, Less Noise-New-generation Low-Field Magnetic Resonance Imaging Systems Can Improve Patient Comfort: A Prospective 0.55T-1.5T-Scanner Comparison.

OBJECTIVES: The objectives of this study were to assess patient comfort when imaged on a newly introduced 0.55T low-field magnetic resonance (MR) scanner system with a wider bore opening compared to a conventional 1.5T MR scanner system. MATERIALS AND METHODS: In this prospective study, fifty patients (mean age: 66.2 ± 17.0 years, 22 females, 28 males) underwent subsequent magnetic resonance imaging (MRI) examinations with matched imaging protocols at 0.55T (MAGNETOM FreeMax, Siemens Healthineers; Erlangen, Germany) and 1.5T (MAGNETOM Avanto Fit, Siemens Healthineers; Erlangen, Germany) on the same day. MRI performed between 05/2021 and 07/2021 was included for analysis. The 0.55T MRI system had a bore opening of 80 cm, while the bore diameter of the 1.5T scanner system was 60 cm. Four patient groups were defined by imaged body regions: (1) cranial or cervical spine MRI using a head/neck coil (n = 27), (2) lumbar or thoracic spine MRI using only the in-table spine coils (n = 10), (3) hip MRI using a large flex coil (n = 8) and (4) upper- or lower-extremity MRI using small flex coils (n = 5). Following the MRI examinations, patients evaluated (1) sense of space, (2) noise level, (3) comfort, (4) coil comfort and (5) overall examination impression on a 5-point Likert-scale (range: 1= "much worse" to 5 = "much better") using a questionnaire. Maximum noise levels of all performed imaging studies were measured in decibels (dB) by a sound level meter placed in the bore center. RESULTS: Sense of space was perceived to be "better" or "much better" by 84% of patients for imaging examinations performed on the 0.55T MRI scanner system (mean score: 4.34 ± 0.75). Additionally, 84% of patients rated noise levels as "better" or "much better" when imaged on the low-field scanner system (mean score: 3.90 ± 0.61). Overall sensation during the imaging examination at 0.55T was rated as "better" or "much better" by 78% of patients (mean score: 3.96 ± 0.70). Quantitative assessment showed significantly reduced maximum noise levels for all 0.55T MRI studies, regardless of body region compared to 1.5T, i.e., brain MRI (83.8 ± 3.6 dB vs. 89.3 ± 5.4 dB; p = 0.04), spine MRI (83.7 ± 3.7 dB vs. 89.4 ± 2.6 dB; p = 0.004) and hip MRI (86.3 ± 5.0 dB vs. 89.1 ± 1.4 dB; p = 0.04). CONCLUSIONS: Patients perceived 0.55T new-generation low-field MRI to be more comfortable than conventional 1.5T MRI, given its larger bore opening and reduced noise levels during image acquisition. Therefore, new concepts regarding bore design and noise level reduction of MR scanner systems may help to reduce patient anxiety and improve well-being when undergoing MR imaging.

Potential of Stroke Imaging Using a New Prototype of Low-Field MRI: A Prospective Direct 0.55 T/1.5 T Scanner Comparison.

Objectives: Ischemic stroke is a leading cause of mortality and acquired disability worldwide and thus plays an enormous health-economic role. Imaging of choice is computed-tomographic (CT) or magnetic resonance imaging (MRI), especially diffusion-weighted (DW) sequences. However, MR imaging is associated with high costs and therefore has a limited availability leading to low-field-MRI techniques increasingly coming into focus. Thus, the aim of our study was to assess the potential of stroke imaging with low-field MRI. Material and Methods: A scanner comparison was performed including 27 patients (17 stroke cohort, 10 control group). For each patient, a brain scan was performed first with a 1.5T scanner and afterwards with a 0.55T scanner. Scan protocols were as identical as possible and optimized. Data analysis was performed in three steps: All DWI/ADC (apparent diffusion coefficient) and FLAIR (fluid attenuated inversion recovery) sequences underwent Likert rating with respect to image impression, resolution, noise, contrast, and diagnostic quality and were evaluated by two radiologists regarding number and localization of DWI and FLAIR lesions in a blinded fashion. Then segmentation of lesion volumes was performed by two other radiologists on DWI/ADC and FLAIR. Results: DWI/ADC lesions could be diagnosed with the same reliability by the most experienced reader in the 0.55T and 1.5T sequences (specificity 100% and sensitivity 92.9%, respectively). False positive findings did not occur. Detection of number/location of FLAIR lesions was mostly equivalent between 0.55T and 1.5T sequences. No significant difference (p = 0.789−0.104) for FLAIR resolution and contrast was observed regarding Likert scaling. For DWI/ADC noise, the 0.55T sequences were significantly superior (p < 0.026). Otherwise, the 1.5T sequences were significantly superior (p < 0.029). There was no significant difference in infarct volume and volume of infarct demarcation between the 0.55T and 1.5T sequences, when detectable. Conclusions: Low-field MRI stroke imaging at 0.55T may not be inferior to scanners with higher field strengths and thus has great potential as a low-cost alternative in future stroke diagnostics. However, there are limitations in the detection of very small infarcts. Further technical developments with follow-up studies must show whether this problem can be solved.