Primary anterior cruciate ligament repair-morphological and quantitative assessment by 7-T MRI and clinical outcome after 1.5 years.

OBJECTIVES: The purpose of this study was to assess morphological and quantitative changes of the anterior cruciate ligament (ACL) and cartilage after ACL repair. METHODS: 7T MRI of the knee was acquired in 31 patients 1.5 years after ACL repair and in 13 controls. Proton density-weighted images with fat saturation (PD-fs) were acquired to assess ACL width, signal intensity, elongation, and fraying. T2/T2* mapping was performed for assessment of ACL and cartilage. Segmentation of the ACL, femoral, and tibial cartilage was carried out at 12 ROIs. The outcome evaluation consisted of the Lysholm Knee Score and International Knee Documentation Committee (IKDC) subjective score and clinical examination. RESULTS: ACL showed a normal signal intensity in 96.8% and an increased width in 76.5% after repair. Fraying occurred in 22.6% without having an impact on the clinical outcome (Lysholm score: 90.39 ± 9.75, p = 0.76 compared to controls). T2 analysis of the ACL revealed no difference between patients and controls (p = 0.74). Compared to controls, assessment of the femoral and tibial cartilage showed a significant increase of T2* times in all ROIs, except at the posterolateral femur. Patients presented a good outcome in clinical examination with a Lysholm score of 87.19 ± 14.89 and IKDC of 80.23 ± 16.84. CONCLUSION: T2 mapping results suggest that the tissue composition of the ACL after repair is similar to that of a native ACL after surgery, whereas the ACL exhibits an increased width. Fraying of the ACL can occur without having any impact on functional outcomes. T2* analysis revealed early degradation at the cartilage. CLINICAL RELEVANCE STATEMENT: MRI represents a noninvasive diagnostic tool for the morphological and compositional assessment of the anterior cruciate ligament after repair, whereas knowledge about post-surgical alterations is crucial for adequate imaging interpretation. KEY POINTS: • There has been renewed interest in repairing the anterior cruciate ligament with a proximally torn ligament. • T2 times of the anterior cruciate ligament do not differ between anterior cruciate ligament repair patients and controls. • T2 mapping may serve as a surrogate for the evaluation of the anterior cruciate ligament after repair.

Impact of velocity- and acceleration-compensated encodings on signal dropout and black-blood state in diffusion-weighted magnetic resonance liver imaging at clinical TEs.

PURPOSE: The study aims to develop easy-to-implement concomitant field-compensated gradient waveforms with varying velocity-weighting (M1) and acceleration-weighting (M2) levels and to evaluate their efficacy in correcting signal dropouts and preserving the black-blood state in liver diffusion-weighted imaging. Additionally, we seek to determine an optimal degree of compensation that minimizes signal dropouts while maintaining blood signal suppression. METHODS: Numerically optimized gradient waveforms were adapted using a novel method that allows for the simultaneous tuning of M1- and M2-weighting by changing only one timing variable. Seven healthy volunteers underwent diffusion-weighted magnetic resonance imaging (DWI) with five diffusion encoding schemes (monopolar, velocity-compensated (M1 = 0), acceleration-compensated (M1 = M2 = 0), 84%-M1-M2-compensated, 67%-M1-M2-compensated) at b-values of 50 and 800 s/mm2 at a constant echo time of 70 ms. Signal dropout correction and apparent diffusion coefficients (ADCs) were quantified using regions of interest in the left and right liver lobe. The blood appearance was evaluated using two five-point Likert scales. RESULTS: Signal dropout was more pronounced in the left lobe (19%-42% less signal than in the right lobe with monopolar scheme) and best corrected by acceleration-compensation (8%-10% less signal than in the right lobe). The black-blood state was best with monopolar encodings and decreased significantly (p < 0.001) with velocity- and/or acceleration-compensation. The partially M1-M2-compensated encoding schemes could restore the black-blood state again. Strongest ADC bias occurred for monopolar encodings (difference between left/right lobe of 0.41 µm2/ms for monopolar vs. < 0.12 µm2/ms for the other encodings). CONCLUSION: All of the diffusion encodings used in this study demonstrated suitability for routine DWI application. The results indicate that a perfect value for the level of M1-M2-compensation does not exist. However, among the examined encodings, the 84%-M1-M2-compensated encodings provided a suitable tradeoff.

Feature-guided deep learning reduces signal loss and increases lesion CNR in diffusion-weighted imaging of the liver.

PURPOSE: This research aims to develop a feature-guided deep learning approach and compare it with an optimized conventional post-processing algorithm in order to enhance the image quality of diffusion-weighted liver images and, in particular, to reduce the pulsation-induced signal loss occurring predominantly in the left liver lobe. METHODS: Data from 40 patients with liver lesions were used. For the conventional approach, the best-suited out of five examined algorithms was chosen. For the deep learning approach, a U-Net was trained. Instead of learning "gold-standard" target images, the network was trained to optimize four image features (lesion CNR, vessel darkness, data consistency, and pulsation artifact reduction), which could be assessed quantitatively using manually drawn ROIs. A quality score was calculated from these four features. As an additional quality assessment, three radiologists rated different features of the resulting images. RESULTS: The conventional approach could substantially increase the lesion CNR and reduce the pulsation-induced signal loss. However, the vessel darkness was reduced. The deep learning approach increased the lesion CNR and reduced the signal loss to a slightly lower extent, but it could additionally increase the vessel darkness. According to the image quality score, the quality of the deep-learning images was higher than that of the images obtained using the conventional approach. The radiologist ratings were mostly consistent with the quantitative scores, but the overall quality ratings differed among the readers. CONCLUSION: Unlike the conventional algorithm, the deep-learning algorithm increased the vessel darkness. Therefore, it may be a viable alternative to conventional algorithms.

Influence of saturation effects on biexponential liver intravoxel incoherent motion.

PURPOSE: Studies on intravoxel incoherent motion (IVIM) imaging in the liver have been carried out with different acquisition protocols. The number of acquired slices and the distances between slices can influence IVIM measurements due to saturation effects, but these effects have often been disregarded. This study investigated differences in biexponential IVIM parameters between two slice settings. METHODS: Fifteen healthy volunteers (21-30 years) were examined at a field strength of 3 T. Diffusion-weighted images of the abdomen were acquired with 16 b values (0-800 s/mm2 ), with four slices for the few slices setting and 24-27 slices for the many slices setting. Regions of interest were manually drawn in the liver. The data were fitted with a monoexponential signal curve and a biexponential IVIM curve, and biexponential IVIM parameters were determined. The dependence on the slice setting was assessed with Student's t test for paired samples (normally distributed IVIM parameters) and the Wilcoxon signed-rank test (non-normally distributed parameters). RESULTS: None of the parameters were significantly different between the settings. For few slices and many slices, respectively, the mean values (SDs) for D $$ D $$ were 1.21 µm 2 / ms $$ 1.21{\upmu \mathrm{m}}^2/\mathrm{ms} $$ ( 0.19 µm 2 / ms $$ 0.19\kern0.3em {\upmu \mathrm{m}}^2/\mathrm{ms} $$ ) and 1.20 µm 2 / ms $$ 1.20{\upmu \mathrm{m}}^2/\mathrm{ms} $$ ( 0.11 µm 2 / ms $$ 0.11\kern0.3em {\upmu \mathrm{m}}^2/\mathrm{ms} $$ ); for f $$ f $$ they were 29.7% (6.2%) and 27.7% (3.6%); and for D * $$ {D}^{\ast } $$ they were 8.76 ⋅ 10 - 2 mm 2 / s $$ 8.76\cdot {10}^{-2}{\mathrm{mm}}^2/\mathrm{s} $$ ( 4.54 ⋅ 10 - 2 mm 2 / s $$ 4.54\cdot {10}^{-2}\kern0.3em {\mathrm{mm}}^2/\mathrm{s} $$ ) and 8.71 ⋅ 10 - 2 mm 2 / s $$ 8.71\cdot {10}^{-2}{\mathrm{mm}}^2/\mathrm{s} $$ ( 4.06 ⋅ 10 - 2 mm 2 / s $$ 4.06\cdot {10}^{-2}\kern0.3em {\mathrm{mm}}^2/\mathrm{s} $$ ). CONCLUSION: Biexponential IVIM parameters in the liver are comparable among IVIM studies that use different slice settings, with mostly negligible saturation effects. However, this may not hold for studies that use much shorter TR.

Reduction of the cardiac pulsation artifact and improvement of lesion conspicuity in flow-compensated diffusion images in the liver-A quantitative evaluation of postprocessing algorithms.

PURPOSE: To enhance image quality of flow-compensated diffusion-weighted liver MRI data by increasing the lesion conspicuity and reducing the cardiac pulsation artifact using postprocessing algorithms. METHODS: Diffusion-weighted image data of 40 patients with liver lesions had been acquired at 1.5 T. These data were postprocessed with 5 different algorithms (weighted averaging, p-mean, percentile, outlier exclusion, and exception set). Four image properties of the postprocessed data were evaluated for optimizing the algorithm parameters. These properties were the lesion to tissue contrast-to-noise ratio (CNR), the reduction of the cardiac pulsation artifact, the data consistency, and the vessel darkness. They were combined into a total quality score ( Q total , $$ {Q}_{\mathrm{total}}, $$ set to 1 for the trace-weighted reference image), which was used to rate the image quality objectively. RESULTS: The weighted averaging algorithm performed best according to the total quality score ( Q total = 1.111 ± 0.067 $$ {Q}_{\mathrm{total}}=1.111\pm 0.067 $$ ). The further ranking was outlier exclusion algorithm ( Q total = 1.086 ± 0.061 $$ {Q}_{\mathrm{total}}=1.086\pm 0.061 $$ ), p-mean algorithm ( Q total = 1.045 ± 0.049 $$ {Q}_{\mathrm{total}}=1.045\pm 0.049 $$ ), percentile algorithm ( Q total = 1.012 ± 0.049 $$ {Q}_{\mathrm{total}}=1.012\pm 0.049 $$ ), and exception set algorithm ( Q total = 0.957 ± 0.027 $$ {Q}_{\mathrm{total}}=0.957\pm 0.027 $$ ). All optimized algorithms except for the exception set algorithm corrected the pulsation artifact and increased the lesion CNR. Changes in Q total $$ {Q}_{\mathrm{total}} $$ were significant for all optimized algorithms except for the percentile algorithm. Liver ADC was significantly reduced (except for the exception set algorithm), particularly in the left lobe. CONCLUSION: Postprocessing algorithms should be used for flow-compensated liver DWI. The proposed weighted averaging algorithm seems to be suited best to increase the image quality of artifact-corrupted flow-compensated diffusion-weighted liver data.

Differences and Similarities in the Pattern of Early Metabolic and Morphologic Response after Induction Chemo-Immunotherapy versus Induction Chemotherapy Alone in Locally Advanced Squamous Cell Head and Neck Cancer.

Background: In head and neck cancer patients, parameters of metabolic and morphologic response of the tumor to single-cycle induction chemotherapy (IC) with docetaxel, cis- or carboplatin are used to decide the further course of treatment. This study investigated the effect of adding a double immune checkpoint blockade (DICB) of tremelimumab and durvalumab to IC on imaging parameters and their significance with regard to tumor cell remission. Methods: Response variables of 53 patients treated with IC+DICB (ICIT) were compared with those of 104 who received IC alone. Three weeks after one cycle, pathologic and, in some cases, clinical and endoscopic primary tumor responses were evaluated and correlated with a change in 18F-FDG PET and CT/MRI-based maximum-standardized uptake values (SUVmax) before (SUVmaxpre), after treatment (SUVmaxpost) and residually (resSUVmax in % of SUVmaxpre), and in maximum tumor diameter (Dmax) before (Dmaxpre) and after treatment (Dmaxpost) and residually (resD). Results: Reduction of SUVmax and Dmax occurred in both groups; values were SUVmaxpre: 14.4, SUVmaxpost: 6.6, Dmaxpre: 30 mm and Dmaxpost: 23 mm for ICIT versus SUVmaxpre: 16.5, SUVmaxpost: 6.4, Dmaxpre: 21 mm, and Dmaxpost: 16 mm for IC alone (all p < 0.05). ResSUVmax was the best predictor of complete response (IC: AUC: 0.77; ICIT: AUC: 0.76). Metabolic responders with resSUVmax ≤ 40% tended to have a higher rate of CR to ICIT (88%; n = 15/17) than to IC (65%; n = 30/46; p = 0.11). Of the metabolic nonresponders (resSUVmax > 80%), 33% (n = 5/15) achieved a clinical CR to ICIT versus 6% (n = 1/15) to IC (p = 0.01). Conclusions: ICIT and IC quickly induce a response and 18F-FDG PET is the more accurate modality for identifying complete remission. The rate of discrepant response, i.e., pCR with metabolic nonresponse after ICIT was >30%.

Deep learning-guided weighted averaging for signal dropout compensation in DWI of the liver.

PURPOSE: To develop an algorithm for the retrospective correction of signal dropout artifacts in abdominal DWI resulting from cardiac motion. METHODS: Given a set of image repetitions for a slice, a locally adaptive weighted averaging is proposed that aims to suppress the contribution of image regions affected by signal dropouts. Corresponding weight maps were estimated by a sliding-window algorithm, which analyzed signal deviations from a patch-wise reference. In order to ensure the computation of a robust reference, repetitions were filtered by a classifier that was trained to detect images corrupted by signal dropouts. The proposed method, named Deep Learning-guided Adaptive Weighted Averaging (DLAWA), was evaluated in terms of dropout suppression capability, bias reduction in the ADC, and noise characteristics. RESULTS: In the case of uniform averaging, motion-related dropouts caused signal attenuation and ADC overestimation in parts of the liver, with the left lobe being affected particularly. Both effects could be substantially mitigated by DLAWA while preventing global penalties with respect to SNR due to local signal suppression. Performing evaluations on patient data, the capability to recover lesions concealed by signal dropouts was demonstrated as well. Further, DLAWA allowed for transparent control of the trade-off between SNR and signal dropout suppression by means of a few hyperparameters. CONCLUSION: This work presents an effective and flexible method for the local compensation of signal dropouts resulting from motion and pulsation. Because DLAWA follows a retrospective approach, no changes to the acquisition are required.

Improved Visualization of Prostate Cancer Using Multichannel Computed Diffusion Images: Combining ADC and DWI.

(1) Background: For the peripheral zone of the prostate, diffusion weighted imaging (DWI) is the most important MRI technique; however, a high b-value image (hbDWI) must always be evaluated in conjunction with an apparent diffusion coefficient (ADC) map. We aimed to unify the important contrast features of both a hbDWI and ADC in one single image, termed multichannel computed diffusion images (mcDI), and evaluate the values of these images in a retrospective clinical study; (2) Methods: Based on the 2D histograms of hbDWI and ADC images of 70 patients with histologically proven prostate cancer (PCa) in the peripheral zone, an algorithm was designed to generate the mcDI. Then, three radiologists evaluated the data of 56 other patients twice in three settings (T2w images +): (1) hbDWI and ADC; (2) mcDI; and (3) mcDI, hbDWI, and ADC. The sensitivity, specificity, and inter-reader variability were evaluated; (3) Results: The overall sensitivity/specificity were 0.91/0.78 (hbDWI + ADC), 0.85/0.88 (mcDI), and 0.97/0.88 (mcDI + hbDWI + ADC). The kappa-values for the inter-reader variability were 0.732 (hbDWI + ADC), 0.800 (mcDI), and 0.853 (mcDI + hbDWI + ADC). (4) Conclusions: By using mcDI, the specificity of the MRI detection of PCa was increased at the expense of the sensitivity. By combining the conventional diffusion data with the mcDI data, both the sensitivity and specificity were improved.

Non-Invasive Characterization of Experimental Bone Metastasis in Obesity Using Multiparametric MRI and PET/CT.

The growth of primary tumors and metastases is associated with excess body fat. In bone metastasis formation, the bone marrow microenvironment, and particularly adipocytes, play a pivotal role as growth mediators of disseminated tumor cells in the bone marrow. The aim of the present study is to non-invasively characterize the pathophysiologic processes in experimental bone metastasis resulting from accelerated tumor progression within adipocyte-rich bone marrow using multimodal imaging from magnetic resonance imaging (MRI) and positron emission tomography/computed tomography (PET/CT). To achieve this, we have employed small animal models after the administration of MDA-MB 231 breast cancer and B16F10 melanoma cells into the bone of nude rats or C57BL/6 mice, respectively. After tumor cell inoculation, ultra-high field MRI and µPET/CT were used to assess functional and metabolic parameters in the bone marrow of control animals (normal diet, ND), following a high-fat diet (HFD), and/or treated with the peroxisome proliferator-activated receptor-gamma (PPARγ) antagonist bisphenol-A-diglycidylether (BADGE), respectively. In the bone marrow of nude rats, dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI), as well as [18F]fluorodeoxyglucose-PET/CT([18F]FDG-PET/CT), was performed 10, 20, and 30 days after tumor cell inoculation, followed by immunohistochemistry. DCE-MRI parameters associated with blood volume, such as area under the curve (AUC), were significantly increased in bone metastases in the HFD group 30 days after tumor cell inoculation as compared to controls (p < 0.05), while the DWI parameter apparent diffusion coefficient (ADC) was not significantly different between the groups. [18F]FDG-PET/CT showed an enhanced glucose metabolism due to increased standardized uptake value (SUV) at day 30 after tumor cell inoculation in animals that received HFD (p < 0.05). BADGE treatment resulted in the inversion of quantitative DCE-MRI and [18F]FDG-PET/CT data, namely a significant decrease in AUC and SUV in HFD-fed animals as compared to ND-fed controls (p < 0.05). Finally, immunohistochemistry and qPCR confirmed the HFD-induced stimulation in vascularization and glucose activity in murine bone metastases. In conclusion, multimodal and multiparametric MRI and [18F]FDG-PET/CT were able to derive quantitative parameters in bone metastases, revealing an increase in vascularization and glucose metabolism following HFD. Thus, non-invasive imaging may serve as a biomarker for assessing the pathophysiology of bone metastasis in obesity, opening novel options for therapy and treatment monitoring by MRI and [18F]FDG-PET/CT.

Flow-compensated diffusion encoding in MRI for improved liver metastasis detection.

Magnetic resonance (MR) diffusion-weighted imaging (DWI) is often used to detect focal liver lesions (FLLs), though DWI image quality can be limited in the left liver lobe owing to the pulsatile motion of the nearby heart. Flow-compensated (FloCo) diffusion encoding has been shown to reduce this pulsation artifact. The purpose of this prospective study was to intra-individually compare DWI of the liver acquired with conventional monopolar and FloCo diffusion encoding for assessing metastatic FLLs in non-cirrhotic patients. Forty patients with known or suspected multiple metastatic FLLs were included and measured at 1.5 T field strength with a conventional (monopolar) and a FloCo diffusion encoding EPI sequence (single refocused; b-values, 50 and 800 s/mm2). Two board-certified radiologists analyzed the DWI images independently. They issued Likert-scale ratings (1 = worst, 5 = best) for pulsation artifact severity and counted the difference of lesions visible at b = 800 s/mm² separately for small and large FLLs (i.e., < 1 cm or > 1 cm) and separately for left and right liver lobe. Differences between the two diffusion encodings were assessed with the Wilcoxon signed-rank test. Both readers found a reduction in pulsation artifact in the liver with FloCo encoding (p < 0.001 for both liver lobes). More small lesions were detected with FloCo diffusion encoding in both liver lobes (left lobe: six and seven additional lesions by readers 1 and 2, respectively; right lobe: five and seven additional lesions for readers 1 and 2, respectively). Both readers found one additional large lesion in the left liver lobe. Thus, flow-compensated diffusion encoding appears more effective than monopolar diffusion encoding for the detection of liver metastases.

Cutting Staff Radiation Exposure and Improving Freedom of Motion during CT Interventions: Comparison of a Novel Workflow Utilizing a Radiation Protection Cabin versus Two Conventional Workflows.

This study aimed to evaluate the radiation exposure to the radiologist and the procedure time of prospectively matched CT interventions implementing three different workflows-the radiologist-(I) leaving the CT room during scanning; (II) wearing a lead apron and staying in the CT room; (III) staying in the CT room in a prototype radiation protection cabin without lead apron while utilizing a wireless remote control and a tablet. We prospectively evaluated the radiologist's radiation exposure utilizing an electronic personal dosimeter, the intervention time, and success in CT interventions matched to the three different workflows. We compared the interventional success, the patient's dose of the interventional scans in each workflow (total mAs and total DLP), the radiologist's personal dose (in µSV), and interventional time. To perform workflow III, a prototype of a radiation protection cabin, with 3 mm lead equivalent walls and a foot switch to operate the doors, was built in the CT examination room. Radiation exposure during the maximum tube output at 120 kV was measured by the local admission officials inside the cabin at the same level as in the technician's control room (below 0.5 µSv/h and 1 mSv/y). Further, to utilize the full potential of this novel workflow, a sterile packed remote control (to move the CT table and to trigger the radiation) and a sterile packed tablet anchored on the CT table (to plan and navigate during the CT intervention) were operated by the radiologist. There were 18 interventions performed in workflow I, 16 in workflow II, and 27 in workflow III. There were no significant differences in the intervention time (workflow I: 23 min ± 12, workflow II: 20 min ± 8, and workflow III: 21 min ± 10, p = 0.71) and the patient's dose (total DLP, p = 0.14). However, the personal dosimeter registered 0.17 ± 0.22 µSv for workflow II, while I and III both documented 0 µSv, displaying significant difference (p < 0.001). All workflows were performed completely and successfully in all cases. The new workflow has the potential to reduce interventional CT radiologists' radiation dose to zero while relieving them from working in a lead apron all day.

Image Quality and Detection of Small Focal Liver Lesions in Diffusion-Weighted Imaging: Comparison of Navigator Tracking and Free-Breathing Acquisition.

OBJECTIVES: The aim of this study was to compare intraindividual diffusion-weighted imaging (DWI) of the liver acquired with free breathing (FB) versus navigator triggering (NT) for assessing small focal liver lesions (FLLs) in noncirrhotic patients. MATERIALS AND METHODS: Patients with known or suspected multiple FLLs were prospectively included, and spin-echo echo-planar DWI with NT and FB acquisition was performed (b-values, 50 and 800 s/mm2 [b50 and b800]). NT and FB DWI sequences with similar acquisitions times were used. Liver and lesion signal-to-noise ratios were measured at b800. The DWI scans were analyzed independently by 2 readers. Liver edge delineation, presence of stair-step artifacts, vessel sharpness, severity of cardiac motion artifacts, overall image quality, and lesion conspicuity were rated with 5-point Likert scales. Small and large FLLs (ie, <1 cm or ≥1 cm) were rated separately for lesion conspicuity. The FLL detectability was estimated by comparing the number of lesions visible with FB to those visible with NT. RESULTS: Forty-three patients were included in the study. The FB acquisition performed better in terms of severity of cardiac motion artifacts. The NT performed better in terms of liver edge delineation and vessel sharpness. Little difference was found for stair-step artifact, overall image quality, and conspicuity of large FLL, whereas the conspicuity of small FLL was better for NT. For small FLL, both readers found more lesions with NT in 11 cases at b800. For large FLL, this effect was much less pronounced (1 case at b800 reported by 1 of the readers). The mean liver and lesion signal-to-noise ratios were 16.8/41.5 and 19.8/38.4 for NT/FB, respectively. CONCLUSIONS: Small FLL detection is better with NT. Large FLL detection by FB and NT is similarly good. We conclude that NT should be used.

Gadolinium-based contrast agents: What we learned from acute adverse events, nephrogenic systemic fibrosis and brain retention. / Gadolinium-haltige Kontrastmittel nach anaphylaktoiden Reaktionen, nephrogener systemischer Fibrose und Hirnretention ­ was haben wir gelernt?

BACKGROUND: Radiologists have been administering gadolinium-based contrast agents (GBCA) in magnetic resonance imaging for several decades, so that there is abundant experience with these agents regarding allergic-like reactions, nephrogenic systemic fibrosis (NSF) and gadolinium retention in the brain. METHODS: This review is based on a selective literature search and reflects the current state of research on acute adverse effects of GBCA, NSF and brain retention of gadolinium. RESULTS: Due to the frequent use of GBCA, data on adverse effects of these compounds are available in large collectives. Allergic-like reactions occurred rarely, whereas severe acute reactions were very rarely observed. Systemic changes in NSF also occur very rarely, although measures to avoid NSF resulted in a significantly reduced incidence of NSF. Due to gadolinium retention in the body after administration of linear MR contrast agents, only macrocyclic preparations are currently used with few exceptions. Clear clinical correlates of gadolinium retention in the brain could not be identified so far. Although the clinical added value of GBCA is undisputed, individual risks associated with the injection of GBCA should be identified and the use of non-contrast enhanced MR techniques should be considered. Alternative contrast agents such as iron oxide nanoparticles are not clinically approved, but are currently undergoing clinical trials. CONCLUSION: GBCA have a very good risk profile with a low rate of adverse effects or systemic manifestations such as NSF. Gadolinium retention in the brain can be minimized by the use of macrocyclic GBCA, although clear clinical correlates due to gadolinium retention in the brain following administration of linear GBCA could not be identified yet. KEY POINTS: · Acute adverse effects are predominantly mild/moderate, rarely severe reactions occur.. · International guidelines resulted in significant reduction of nephrogenic systemic fibrosis.. · Application of macrocyclic contrast agents minimizes gadolinium retention in the brain.. CITATION FORMAT: · Bäuerle T, Saake M, Uder M. Gadolinium-based contrast agents: What we learned from acute adverse events, nephrogenic systemic fibrosis and brain retention. Fortschr Röntgenstr 2021; 193: 1010 - 1018.

Personalized computed tomography - Automated estimation of height and weight of a simulated digital twin using a 3D camera and artificial intelligence. / Personalisierte Computertomografie ­ automatisierte Abschätzung von Größe und Gewicht durch Simulation eines digitalen Zwillings mit einer 3D-Kamera und künstlicher Intelligenz.

PURPOSE: The aim of this study was to develop an algorithm for automated estimation of patient height and weight during computed tomography (CT) and to evaluate its accuracy in everyday clinical practice. MATERIALS AND METHODS: Depth images of 200 patients were recorded with a 3D camera mounted above the patient table of a CT scanner. Reference values were obtained using a calibrated scale and a measuring tape to train a machine learning algorithm that fits a patient avatar into the recorded patient surface data. The resulting algorithm was prospectively used on 101 patients in clinical practice and the results were compared to the reference values and to estimates by the patient himself, the radiographer and the radiologist. The body mass index was calculated from the collected values for each patient using the WHO formula. A tolerance level of 5 kg was defined in order to evaluate the impact on weight-dependent contrast agent dosage in abdominal CT. RESULTS: Differences between values for height, weight and BMI were non-significant over all assessments (p > 0.83). The most accurate values for weight were obtained from the patient information (R²â€Š= 0.99) followed by the automated estimation via 3D camera (R²â€Š= 0.89). Estimates by medical staff were considerably less precise (radiologist: R²â€Š= 0.78, radiographer: R²â€Š= 0.77). A body-weight dependent dosage of contrast agent using the automated estimations matched the dosage using the reference measurements in 65 % of the cases. The dosage based on the medical staff estimates would have matched in 49 % of the cases. CONCLUSION: Automated estimation of height and weight using a digital twin model from 3D camera acquisitions provide a high precision for protocol design in computer tomography. KEY POINTS: · Machine learning can calculate patient-avatars from 3D camera acquisitions.. · Height and weight of the digital twins are comparable to real measurements of the patients.. · Estimations by medical staff are less precise.. · The values can be used for calculation of contrast agent dosage.. CITATION FORMAT: · Geissler F, Heiß R, Kopp M et al. Personalized computed tomography - Automated estimation of height and weight of a simulated digital twin using a 3D camera and artificial intelligence. Fortschr Röntgenstr 2021; 193: 437 - 445.

On the dependence of the cardiac motion artifact on the breathing cycle in liver diffusion-weighted imaging.

PURPOSE: The purpose of this study was to investigate whether the cardiac motion artifact that regularly appears in diffusion-weighted imaging of the left liver lobe might be reduced by acquiring images in inspiration, when the coupling between heart and liver might be minimal. MATERIALS AND METHODS: 43 patients with known or suspected focal liver lesions were examined at 1.5 T with breath hold acquisition, once in inspiration and once in expiration. Data were acquired with a diffusion-weighted echo planar imaging sequence and two b-values (b50 = 50 s/mm² and b800 = 800 s/mm²). The severity of the cardiac motion artifact in the left liver lobe was rated by two experienced radiologists for both b-values with a 5 point Likert scale. Additionally, the normalized signal S(b800)/S(b50) in the left liver lobe was computed. The Wilcoxon signed-rank test was used comparing the scores of the two readers obtained in inspiration and expiration, and to compare the normalized signal in inspiration and expiration. RESULTS: The normalized signal in inspiration was slightly higher than in expiration (0.349±0.077 vs 0.336±0.058), which would indicate a slight reduction of the cardiac motion artifact, but this difference was not significant (p = 0.24). In the qualitative evaluation, the readers did not observe a significant difference for b50 (reader 1: p = 0.61; reader 2: p = 0.18). For b800, reader 1 observed a significant difference of small effect size favouring expiration (p = 0.03 with a difference of mean Likert scores of 0.27), while reader 2 observed no significant difference (p = 0.62). CONCLUSION: Acquiring the data in inspiration does not lead to a markedly reduced cardiac motion artifact in diffusion-weighted imaging of the left liver lobe and is in this regard not to be preferred over acquiring the data in expiration.

Computer-Aided Diagnosis in Multiparametric MRI of the Prostate: An Open-Access Online Tool for Lesion Classification with High Accuracy.

Computer-aided diagnosis (CADx) approaches could help to objectify reporting on prostate mpMRI, but their use in many cases is hampered due to common-built algorithms that are not publicly available. The aim of this study was to develop an open-access CADx algorithm with high accuracy for classification of suspicious lesions in mpMRI of the prostate. This retrospective study was approved by the local ethics commission, with waiver of informed consent. A total of 124 patients with 195 reported lesions were included. All patients received mpMRI of the prostate between 2014 and 2017, and transrectal ultrasound (TRUS)-guided and targeted biopsy within a time period of 30 days. Histopathology of the biopsy cores served as a standard of reference. Acquired imaging parameters included the size of the lesion, signal intensity (T2w images), diffusion restriction, prostate volume, and several dynamic parameters along with the clinical parameters patient age and serum PSA level. Inter-reader agreement of the imaging parameters was assessed by calculating intraclass correlation coefficients. The dataset was stratified into a train set and test set (156 and 39 lesions in 100 and 24 patients, respectively). Using the above parameters, a CADx based on an Extreme Gradient Boosting algorithm was developed on the train set, and tested on the test set. Performance optimization was focused on maximizing the area under the Receiver Operating Characteristic curve (ROCAUC). The algorithm was made publicly available on the internet. The CADx reached an ROCAUC of 0.908 during training, and 0.913 during testing (p = 0.93). Additionally, established rule-in and rule-out criteria allowed classifying 35.8% of the malignant and 49.4% of the benign lesions with error rates of <2%. All imaging parameters featured excellent inter-reader agreement. This study presents an open-access CADx for classification of suspicious lesions in mpMRI of the prostate with high accuracy. Applying the provided rule-in and rule-out criteria might facilitate to further stratify the management of patients at risk.

Single source split filter dual energy: Image quality and liver lesion detection in abdominal CT.

PURPOSE: Aim of this study was to evaluate image quality of single source dual energy CT (SSDE-CT) using split filter technique in oncologic abdominal CT. METHOD: 51 consecutive patients with newly diagnosed breast carcinoma were prospectively enrolled in this study and underwent a staging examination of the abdomen using SSDE-CT (120 kV, split filter technique, 400 ref. mAs). Inline default images (DI) and post-processed virtual monoenergetic images at 40 keV, 50 keV, 60 keV, 70 keV and 80 keV were reconstructed. Objective image quality was evaluated as contrast to noise ratio (CNR) for liver parenchyma, portal vein, spleen, pancreas, aorta and hypoattenuating liver lesions. Subjective image quality was rated on a 5-point scale. Image quality at different keV settings was analyzed in paired t-tests. RESULTS: CNR was highest at 40 keV for vessels (portal vein: 9.0, aorta: 8.8, all p < 0.001) and for upper abdominal organs (spleen: 4.8, all p < 0.001; pancreas: 2.7, all p < 0.01 except p = 0.93 for 50 keV; liver parenchyma: 3.4, all p < 0.01). Highest CNR values for hypoattenuating liver lesions were found at 40 keV (7.7, all p < 0.001). Overall subjective image quality was highest with 80 keV and DI (both 4.8, all p < 0.001). Artifacts were most pronounced at 40 keV. CONCLUSIONS: High image quality can be obtained with SSDE-CT of the abdomen. Lowest monoenergetic reconstructions provide the highest image contrast and should be used for vessel evaluation. The best trade-off between artifacts and parenchymal contrast can be obtained with 80 keV images.

A mixed waveform protocol for reduction of the cardiac motion artifact in black-blood diffusion-weighted imaging of the liver.

OBJECTIVE: Diffusion-weighted imaging (DWI) in the liver suffers from signal loss due to the cardiac motion artifact, especially in the left liver lobe. The purpose of this work was to improve the image quality of liver DWI in terms of cardiac motion artifact reduction and achievement of black-blood images in low b-value images. MATERIAL AND METHODS: Ten healthy volunteers (age 20-31 years) underwent MRI examinations at 1.5 T with a prototype DWI sequence provided by the vendor. Two diffusion encodings (i.e. waveforms), monopolar and flow-compensated, and the b-values 0, 20, 50, 100, 150, 600 and 800 s/mm2 were used. Two Likert scales describing the severity of the pulsation artifact and the quality of the black-blood state were defined and evaluated by two experienced radiologists. Regions of interest (ROIs) were manually drawn in the right and left liver lobe in each slice and combined to a volume of interest (VOI). The mean and coefficient of variation were calculated for each normalized VOI-averaged signal to assess the severity of the cardiac motion artifact. The ADC was calculated using two b-values once for the monopolar data and once with mixed data, using the monopolar data for the small and the flow-compensated data for the high b-value. A Wilcoxon rank sum test was used to compare the Likert scores obtained for monopolar and flow-compensated data. RESULTS: At b-values from 20 to 150 s/mm2, unlike the flow-compensated diffusion encoding, the monopolar encoding yielded black blood in all images with a negligible signal loss due to the cardiac motion artifact. At the b-values 600 and 800 s/mm2, the flow-compensated encoding resulted in a significantly reduced cardiac motion artifact, especially in the left liver lobe, and in a black-blood state. The ADC calculated with monopolar data was significantly higher in the left than in the right liver lobe. CONCLUSION: It is recommendable to use the following mixed waveform protocol: Monopolar diffusion encodings at small b-values and flow-compensated diffusion encodings at high b-values.