Objectives
The goal of this study was to investigate the precise timeline of respiratory events occurring after the administration of two gadolinium-based contrast agents, gadoxetate disodium and ...gadoterate meglumine.
Materials and methods
This retrospective study examined 497 patients subject to hepatobiliary imaging using the GRASP MRI technique (TR/TE = 4/2 ms; ST = 2.5 mm; 384 × 384 mm). Imaging was performed after administration of gadoxetate (
N
= 338) and gadoterate (
N
= 159). All GRASP datasets were reconstructed using a temporal resolution of 1 s. Four regions-of-interest (ROIs) were placed in the liver dome, the right and left cardiac ventricle, and abdominal aorta detecting liver displacement and increasing vascular signal intensities over time. Changes in hepatic intensity reflected respiratory dynamics in temporal correlation to the vascular contrast bolus.
Results
In total, 216 (67%) and 41 (28%) patients presented with transient respiratory motion after administration of gadoxetate and gadoterate, respectively. The mean duration from start to acme of the respiratory episode was similar (
p
= 0.4) between gadoxetate (6.0 s) and gadoterate (5.6 s). Its mean onset in reference to contrast arrival in the right ventricle differed significantly (
p
< 0.001) between gadoxetate (15.3s) and gadoterate (1.8 s), analogously to peak inspiration timepoint in reference to the aortic enhancement arrival (gadoxetate: 0.9s
after
, gadoterate: 11.2 s
before
aortic enhancement,
p
< 0.001).
Conclusions
The timepoint of occurrence of transient respiratory anomalies associated with gadoxetate disodium and gadoterate meglumine differs significantly between both contrast agents while the duration of the event remains similar.
Key Points
•
Transient respiratory anomalies following the administration of gadoterate meglumine occurred during a time period usually not acquired in MR imaging.
•
Transient respiratory anomalies following the administration of gadoxetate disodium occurred around the initiation of arterial phase imaging.
•
The estimated duration of respiratory events was similar between both contrast agents.
•An analysis of 6683 polytrauma CTs revealed higher number of CT examinations on warmer days with more sunshine and ultraviolet light, less wind and fewer clouds.•Logistic regression analysis of ...weather parameters yielded a 87% accuracy to predict days with above median numbers of Polytrauma-CTs on training data.•Out of multiple machine-learning approaches on validation data, both a neural network (72%) and a support vector machine (72%) demonstrated higher prediction accuracy compared with logistic regression (65%) in a clinical daily routine setting.
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.
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.
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.
It is possible to forecast above or below median daily number of polytrauma-CTs using weather data.
Prediction of polytrauma-CT examination volumes may be used to improve resource planning.
ABSTRACT
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.
Objective
To assess if adding perfusion information from dynamic contrast-enhanced (DCE MRI) acquisition schemes with high spatiotemporal resolution to T2w/DWI sequences as input features for a ...gradient boosting machine (GBM) machine learning (ML) classifier could better classify prostate cancer (PCa) risk groups than T2w/DWI sequences alone.
Materials and methods
One hundred ninety patients (68 ± 9 years) were retrospectively evaluated at 3T MRI for clinical suspicion of PCa. Included were 201 peripheral zone (PZ) PCa lesions. Histopathological confirmation on fusion biopsy was matched with normal prostate parenchyma contralaterally. Biopsy results were grouped into benign tissue and low-, intermediate-, and high-risk groups (Gleason sum score 6, 7, and > 7, respectively). DCE MRI was performed using golden-angle radial sparse MRI. Perfusion maps (K
trans
, K
ep
, V
e
), apparent diffusion coefficient (ADC), and absolute T2w signal intensity were determined and used as input features for building two ML models: GBM with/without perfusion maps. Areas under the receiver operating characteristic curve (AUC) values for correlated models were compared.
Results
For the classification of benign vs. malignant and intermediate- vs. high-grade PCa, perfusion information added relevant information (AUC values 1 vs. 0.953 and 0.909 vs. 0.700,
p
< 0.001 and
p
= 0.038), while no statistically significant effect was found for low- vs. intermediate- and high-grade PCa.
Conclusion
Perfusion information from DCE MRI acquisition schemes with high spatiotemporal resolution to ML classifiers enables a superior risk stratification between benign and malignant and intermediate- and high-risk PCa in the PZ compared with classifiers based on T2w/DWI information alone.
Key Points
• In the recent guidelines, the role of DCE MRI has changed from a mandatory to recommended sequence.
• DCE MRI acquisition schemes with high spatiotemporal resolution (e.g., GRASP) have been shown to improve the diagnostic performance compared with conventional DCE MRI sequences.
• Using perfusion information acquired with GRASP in combination with ML classifiers significantly improved the prediction of benign vs. malignant and intermediate- vs. high-grade peripheral zone prostate cancer compared with non-contrast sequences.
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.
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).
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).
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.
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.
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.
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.
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
two entry points.
To explore the feasibility of a fully automated workflow for whole-body volumetric analyses based on deep reinforcement learning (DRL) and to investigate the influence of contrast-phase (CP) and ...slice thickness (ST) on the calculated organ volume. This retrospective study included 431 multiphasic CT datasets—including three CP and two ST reconstructions for abdominal organs—totaling 10,508 organ volumes (10,344 abdominal organ volumes: liver, spleen, and kidneys, 164 lung volumes). Whole-body organ volumes were determined using multi-scale DRL for 3D anatomical landmark detection and 3D organ segmentation. Total processing time for all volumes and mean calculation time per case were recorded. Repeated measures analyses of variance (ANOVA) were conducted to test for robustness considering CP and ST. The algorithm calculated organ volumes for the liver, spleen, and right and left kidney (mean volumes in milliliter (interquartile range), portal venous CP, 5 mm ST: 1868.6 (1426.9, 2157.8), 350.19 (45.46, 395.26), 186.30 (147.05, 214.99) and 181.91 (143.22, 210.35), respectively), and for the right and left lung (2363.1 (1746.3, 2851.3) and 1950.9 (1335.2, 2414.2)). We found no statistically significant effects of the variable contrast phase or the variable slice thickness on the organ volumes. Mean computational time per case was 10 seconds. The evaluated approach, using state-of-the art DRL, enables a fast processing of substantial amounts irrespective of CP and ST, allowing building up organ-specific volumetric databases. The thus derived volumes may serve as reference for quantitative imaging follow-up.
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