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Upcoming experimental and epidemiological data have identified the endogenous non-proteinogenic amino acid L-homoarginine (L-hArg) not only as a novel biomarker for cardiovascular disease but also as being directly involved in the pathogenesis of cardiac dysfunction. The association of low L-hArg levels with adverse cardiovascular events and mortality has proposed the idea of nutritional supplementation to rescue pathways inversely associated with cardiovascular health. Subsequent clinical and experimental studies contributed significantly to our knowledge of potential effects on the cardiorenal axis, acting either as a biomarker or a cardiovascular active agent. In this review article, we provide a comprehensive summary of the L-hArg metabolism, pathophysiological aspects, and current developments in the field of experimental and clinical evidence in favor of protective cardiovascular effects. Establishing a reliable biomarker to identify patients at high risk to die of cardiovascular disease represents one of the main goals for tackling this disease and providing individual therapeutic guidance.

Purpose Non-invasive prediction of the tumour of origin giving rise to brain metastases (BMs) using MRI measurements obtained in radiological routine and elucidating the biological basis by matched histopathological analysis. Methods Preoperative MRI and histological parameters of 95 BM patients (female, 50; mean age 59.6 ± 11.5 years) suffering from different primary tumours were retrospectively analysed. MR features were assessed by region of interest (ROI) measurements of signal intensities on unenhanced T1-, T2-, diffusion-weighted imaging and apparent diffusion coefficient (ADC) normalised to an internal reference ROI. Furthermore, we assessed BM size and oedema as well as cell density, proliferation rate, microvessel density and vessel area as histopathological parameters. Results Applying recursive partitioning conditional inference trees, only histopathological parameters could stratify the primary tumour entities. We identified two distinct BM growth patterns depending on their proliferative status: Ki67high BMs were larger (p = 0.02), showed less peritumoural oedema (p = 0.02) and showed a trend towards higher cell density (p = 0.05). Furthermore, Ki67high BMs were associated with higher DWI signals (p = 0.03) and reduced ADC values (p = 0.004). Vessel density was strongly reduced in Ki67high BM (p p ≤ 0.03 for all features) with SCLCs representing predominantly the Ki67high group, while NSCLCs rather matching with Ki67low features. Conclusion Interpretable and easy to obtain MRI features may not be sufficient to predict directly the primary tumour entity of BM but seem to have the potential to aid differentiating high- and low-proliferative BMs, such as SCLC and NSCLC.

Objectives The purpose of this study was to evaluate the diagnostic accuracy of third-generation dual-source dual-energy CT (DECT) color-coded collagen reconstructions for the assessment of the cruciate ligaments compared to standard grayscale image reconstruction. Methods Patients who underwent third-generation dual-source DECT followed by either 3-T MRI or arthroscopy of the knee joint within 14 days between January 2016 and December 2021 were included in this retrospective study. Five radiologists independently evaluated conventional grayscale DECT for the presence of injury to the cruciate ligaments; after 4 weeks, readers re-evaluated the examinations using grayscale images and color-coded collagen reconstructions. A reference standard for MRI was provided by a consensus reading of two experienced readers and arthroscopy. Sensitivity and specificity were the primary metrics of diagnostic performance. Results Eighty-five patients (mean age, 44 years ± 16; 50 male) with injury to the ACL or PCL (n = 31) were ultimately included. Color-coded collagen reconstructions significantly increased overall sensitivity (94/105 [90%] vs. 67/105 [64%]), specificity (248/320 [78%] vs. 215/320 [67%]), PPV (94/166 [57%] vs. 67/162 [39%]), NPV (248/259 [96%] vs. 215/253 [85%]), and accuracy (342/425 [81%] vs. 282/425 [66%]) for the detection of injury to the anterior cruciate ligament (all parameters, p p p Conclusions DECT-derived color-coded collagen reconstructions yield substantially higher diagnostic accuracy and confidence for assessing the integrity of the cruciate ligaments compared to standard grayscale CT in patients with acute trauma. Key Points • Color-coded collagen reconstructions derived from dual-energy CT yield substantially higher diagnostic accuracy and confidence for the assessment of the cruciate ligaments compared to standard grayscale CT in patients with acute trauma. • Color-coded collagen reconstructions demonstrate good agreement with MRI for the assessment cruciate ligament injury. • Dual-energy CT may serve as a readily available screening approach for patients with acute trauma to the knee when injury to the cruciate ligaments is suspected.

Purpose The radiologists’ workload is increasing, and computational imaging techniques may have the potential to identify visually unequivocal lesions, so that the radiologist can focus on equivocal and critical cases. The purpose of this study was to assess radiomics versus dual-energy CT (DECT) material decomposition to objectively distinguish visually unequivocal abdominal lymphoma and benign lymph nodes. Methods Retrospectively, 72 patients [m, 47; age, 63.5 (27–87) years] with nodal lymphoma (n = 27) or benign abdominal lymph nodes (n = 45) who had contrast-enhanced abdominal DECT between 06/2015 and 07/2019 were included. Three lymph nodes per patient were manually segmented to extract radiomics features and DECT material decomposition values. We used intra-class correlation analysis, Pearson correlation and LASSO to stratify a robust and non-redundant feature subset. Independent train and test data were applied on a pool of four machine learning models. Performance and permutation-based feature importance was assessed to increase the interpretability and allow for comparison of the models. Top performing models were compared by the DeLong test. Results About 38% (19/50) and 36% (8/22) of the train and test set patients had abdominal lymphoma. Clearer entity clusters were seen in t-SNE plots using a combination of DECT and radiomics features compared to DECT features only. Top model performances of AUC = 0.763 (CI = 0.435–0.923) were achieved for the DECT cohort and AUC = 1.000 (CI = 1.000–1.000) for the radiomics feature cohort to stratify visually unequivocal lymphomatous lymph nodes. The performance of the radiomics model was significantly (p = 0.011, DeLong) superior to the DECT model. Conclusions Radiomics may have the potential to objectively stratify visually unequivocal nodal lymphoma versus benign lymph nodes. Radiomics seems superior to spectral DECT material decomposition in this use case. Therefore, artificial intelligence methodologies may not be restricted to centers with DECT equipment.

Objectives: The objective of this work was to evaluate the incremental value of MR angiography over plain radiographs and MRI for the differentiation of aneurysmal bone cysts (ABCs) from unicameral bone cysts (UBCs). Methods: Thirty-six juvenile patients with histologically secured primary ABCs or UBCs were included in this retrospective study. Two radiologists assessed all obtained images in a blinded fashion using a catalog of previously suggested imaging findings. A second readout with supplementary MR angiography images was performed after 8 weeks to prevent observer recall bias. Diagnostic accuracy parameters were calculated for individual imaging findings, and overall diagnostic accuracy and diagnostic confidence were assessed for all readouts. Receiver operating characteristic (ROC) curve comparison was used to determine the incremental value of MR angiography. Results: Of 16 imaging features, only abnormal vascularization in MR angiography provided sufficient diagnostic accuracy for the identification of ABCs. Other imaging features such as fluid–fluid levels and internal septations were insufficient for the differentiation of UBCs from ABCs. Availability of MR angiography images significantly increased diagnostic accuracy (94.4 vs 75.0% and 83.3 vs 69.4%, respectively, p < 0.05) and diagnostic confidence (4.5 vs 3.7, p < 0.05) of reading radiologists. Conclusion: The presence of arterial feeders in MR angiography can accurately discriminate primary ABCs from UBCs and increases the diagnostic accuracy and diagnostic confidence of reporting radiologists. Advances in knowledge: Radiographic differentiation of cystic bone lesions such as ABCs and UBCs remains challenging. We demonstrate that MR angiography provides incremental value and suggest inclusion in standard examination protocols.

D-dimer testing is known to have a high sensitivity at simultaneously low specificity, resulting in nonspecific elevations in a variety of conditions.This retrospective study sought to assess diagnostic and prognostic features of D-dimers in cancer patients referred to the emergency department for suspected pulmonary embolism (PE) and deep vein thrombosis (DVT). In total, 526 patients with a final adjudicated diagnosis of PE (n = 83) and DVT (n = 69) were enrolled, whereas 374 patients served as the comparative group, in which venous thromboembolism (VTE) has been excluded.For the identification of VTE, D-dimers yielded the highest positive predictive value of 96% (95% confidence interval (CI), 85-99) at concentrations of 9.9 mg/L and a negative predictive value of 100% at .6 mg/L (95% CI, 97-100). At the established rule-out cut-off level of .5 mg/L, D-dimers were found to be very sensitive (100%) at a moderate specificity of nearly 65%. Using an optimised cut-off value of 4.9 mg/L increased the specificity to 95% for the detection of life-threatening VTE at the cost of moderate sensitivities (64%). During a median follow-up of 30 months, D-dimers positively correlated with the reoccurrence of VTE (p = .0299) and mortality in both cancer patients with VTE (p .0001) and without VTE (p = .0008).Although D-dimer testing in cancer patients is discouraged by current guidelines, very high concentrations above the 10-fold upper reference limit contain diagnostic and prognostic information and might be helpful in risk assessment, while low concentrations remain useful for ruling out VTE.

This prospective study sought to evaluate potential savings of radiation dose to medical staff using real-time dosimetry coupled with visual radiation dose feedback during angiographic interventions. For this purpose, we analyzed a total of 214 angiographic examinations that consisted of chemoembolizations and several other types of therapeutic interventions. The Unfors RaySafe i2 dosimeter was worn by the interventionalist at chest height over the lead protection. A total of 110 interventions were performed with real-time radiation dosimetry allowing the interventionalist to react upon higher x-ray exposure and 104 examinations served as the comparative group without real-time radiation monitoring. By using the real-time display during interventions, the overall mean operator radiation dose decreased from 3.67 (IQR, 0.95-23.01) to 2.36 μSv (IQR, 0.52-12.66) (-36%; p = 0.032) at simultaneously reduced operator exposure time by 4.5 min (p = 0.071). Dividing interventions into chemoembolizations and other types of therapeutic interventions, radiation dose decreased from 1.31 (IQR, 0.46-3.62) to 0.95 μSv (IQR, 0.53-3.11) and from 24.39 (IQR, 12.14-63.0) to 10.37 μSv (IQR, 0.85-36.84), respectively, using live-screen dosimetry (p ≤ 0.005). Radiation dose reductions were also observed for the participating assistants, indicating that they could also benefit from real-time visual feedback dosimetry during interventions (-30%; p = 0.039). Integration of real-time dosimetry into clinical processes might be useful in reducing occupational radiation exposure time during angiographic interventions. The real-time visual feedback raised the awareness of interventionalists and their assistants to the potential danger of prolonged radiation exposure leading to the adoption of radiation-sparing practices. Therefore, it might create a safer environment for the medical staff by keeping the applied radiation exposure as low as possible.

Whole-body magnetic resonance imaging (MRI) has become increasingly popular in oncology. However, the long acquisition time might hamper its widespread application. We sought to assess and compare free-breathing sequences with conventional breath-hold examinations in whole-body MRI using an automated workflow process. This prospective study consisted of 20 volunteers and six patients with a variety of pathologies who had undergone whole-body 1.5-T MRI that included T1-weighted radial and Dixon volumetric interpolated breath-hold examination sequences. Free-breathing sequences were operated by using an automated user interface. Image quality, diagnostic confidence, and image noise were evaluated by two experienced radiologists. Additionally, signal-to-noise ratio was measured. Diagnostic performance for the overall detection of pathologies was assessed using the area under the receiver operating characteristics curve (AUC). Study participants were asked to rate their examination experiences in a satisfaction survey. MR free-breathing scans were rated as at least equivalent to conventional MR scans in more than 92% of cases, showing high overall diagnostic accuracy (95% [95% CI 92-100]) and performance (AUC 0.971, 95% CI 0.942-0.988; p 0.0001) for the assessment of pathologies at simultaneously reduced examination times (25 ± 2 vs. 32 ± 3 min; p 0.0001). Interrater agreement was excellent for both free-breathing (ϰ = 0.96 [95% CI 0.88-1.00]) and conventional scans (ϰ = 0.93 [95% CI 0.84-1.00]). Qualitative and quantitative assessment for image quality, image noise, and diagnostic confidence did not differ between the two types of MR image acquisition (all p 0.05). Scores for patient satisfaction were significantly better for free-breathing compared with breath-hold examinations (p = 0.0145), including significant correlations for the grade of noise (r = 0.79, p 0.0001), tightness (r = 0.71, p 0.0001), and physical fatigue (r = 0.52, p = 0.0065). In summary, free-breathing whole-body MRI in tandem with an automated user interface yielded similar diagnostic performance at equivalent image quality and shorter acquisition times compared to conventional breath-hold sequences.

To assess the potential of radiomic features in comparison to dual-energy CT (DECT) material decomposition to objectively stratify abdominal lymph node metastases.In this retrospective study, we included 81 patients (m, 57; median age, 65 (interquartile range, 58.7-73.3) years) with either lymph node metastases (n = 36) or benign lymph nodes (n = 45) who underwent contrast-enhanced abdominal DECT between 06/2015-07/2019. All malignant lymph nodes were classified as unequivocal according to RECIST criteria and confirmed by histopathology, PET-CT or follow-up imaging. Three investigators segmented lymph nodes to extract DECT and radiomics features. Intra-class correlation analysis was applied to stratify a robust feature subset with further feature reduction by Pearson correlation analysis and LASSO. Independent training and testing datasets were applied on four different machine learning models. We calculated the performance metrics and permutation-based feature importance values to increase interpretability of the models. DeLong test was used to compare the top performing models.Distance matrices and t-SNE plots revealed clearer clusters using a combination of DECT and radiomic features compared to DECT features only. Feature reduction by LASSO excluded all DECT features of the combined feature cohort. The top performing radiomic features model (AUC = 1.000; F1 = 1.000; precision = 1.000; Random Forest) was significantly superior to the top performing DECT features model (AUC = 0.942; F1 = 0.762; precision = 0.800; Stochastic Gradient Boosting) (DeLong 0.001).Imaging biomarkers have the potential to stratify unequivocal lymph node metastases. Radiomics models were superior to DECT material decomposition and may serve as a support tool to facilitate stratification of abdominal lymph node metastases.

Neben der stetig zunehmenden Arbeitsverdichtung wird die Diagnostik und Patientenbetreuung für MTRA und Radiologen immer komplexer. Als potenziellen Lösungsansatz dieser täglichen Herausforderungen im Gesundheitswesen hat das Thema Künstliche Intelligenz längst Aufmerksamkeit auf sich gezogen und bereits viele Debatten über die Rolle und Verantwortlichkeiten des Radiologen und der MTRA ausgelöst.

Purpose To test the effect of anatomic variants of the prostatic apex overlapping the membranous urethra (Lee type classification), as well as median urethral sphincter length (USL) in preoperative multiparametric magnetic resonance imaging (mpMRI) on the very early continence in open (ORP) and robotic-assisted radical prostatectomy (RARP) patients. Methods In 128 consecutive patients (01/2018–12/2019), USL and the prostatic apex classified according to Lee types A–D in mpMRI prior to ORP or RARP were retrospectively analyzed. Uni- and multivariable logistic regression models were used to identify anatomic characteristics for very early continence rates, defined as urine loss of ≤ 1 g in the PAD-test. Results Of 128 patients with mpMRI prior to surgery, 76 (59.4%) underwent RARP vs. 52 (40.6%) ORP. In total, median USL was 15, 15 and 10 mm in the sagittal, coronal and axial dimensions. After stratification according to very early continence in the PAD-test (≤ 1 g vs. > 1 g), continent patients had significantly more frequently Lee type D (71.4 vs. 54.4%) and C (14.3 vs. 7.6%, p = 0.03). In multivariable logistic regression models, the sagittal median USL (odds ratio [OR] 1.03) and Lee type C (OR: 7.0) and D (OR: 4.9) were independent predictors for achieving very early continence in the PAD-test. Conclusion Patients’ individual anatomical characteristics in mpMRI prior to radical prostatectomy can be used to predict very early continence. Lee type C and D suggest being the most favorable anatomical characteristics. Moreover, longer sagittal median USL in mpMRI seems to improve very early continence rates.

Background: To test the impact of urethral sphincter length (USL) and anatomic variants of prostatic apex (Lee-type classification) in preoperative multiparametric magnet resonance imaging (mpMRI) on mid-term continence in prostate cancer patients treated with radical prostatectomy (RP). Methods: We relied on an institutional tertiary-care database to identify patients who underwent RP between 03/2018 and 12/2019 with preoperative mpMRI and data available on mid-term (>6 months post-surgery) urinary continence, defined as usage 0/1 (-safety) pad/24 h. Univariable and multivariable logistic regression models were fitted to test for predictor status of USL and prostatic apex variants, defined in mpMRI measurements. Results: Of 68 eligible patients, rate of mid-term urinary continence was 81% (n = 55). Median coronal (15.1 vs. 12.5 mm) and sagittal (15.4 vs. 11.1 mm) USL were longer in patients reporting urinary continence in mid-term follow-up (both p < 0.01). No difference was recorded for prostatic apex variants distribution (Lee-type) between continent vs. incontinent patients (p = 0.4). In separate multivariable logistic regression models, coronal (odds ratio (OR): 1.35) and sagittal (OR: 1.67) USL, but not Lee-type, were independent predictors for mid-term continence. Conclusion: USL, but not apex anatomy, in preoperative mpMRI was associated with higher rates of urinary continence at mid-term follow-up.

Aims Changes in metabolism are known to contribute to tumour phenotypes. If and how metabolic alterations in brain tumours contribute to patient outcome is still poorly understood. Epigenetics impact metabolism and mitochondrial function. The aim of this study is a characterisation of metabolic features in molecular subgroups of isocitrate dehydrogenase mutant (IDHmut) and isocitrate dehydrogenase wildtype (IDHwt) gliomas. Methods We employed DNA methylation pattern analyses with a special focus on metabolic genes, large-scale metabolism panel immunohistochemistry (IHC), qPCR-based determination of mitochondrial DNA copy number and immune cell content using IHC and deconvolution of DNA methylation data. We analysed molecularly characterised gliomas (n = 57) for in depth DNA methylation, a cohort of primary and recurrent gliomas (n = 22) for mitochondrial copy number and validated these results in a large glioma cohort (n = 293). Finally, we investigated the potential of metabolic markers in Bevacizumab (Bev)-treated gliomas (n = 29). Results DNA methylation patterns of metabolic genes successfully distinguished the molecular subtypes of IDHmut and IDHwt gliomas. Promoter methylation of lactate dehydrogenase A negatively correlated with protein expression and was associated with IDHmut gliomas. Mitochondrial DNA copy number was increased in IDHmut tumours and did not change in recurrent tumours. Hierarchical clustering based on metabolism panel IHC revealed distinct subclasses of IDHmut and IDHwt gliomas with an impact on patient outcome. Further quantification of these markers allowed for the prediction of survival under anti-angiogenic therapy. Conclusion A mitochondrial signature was associated with increased survival in all analyses, which could indicate tumour subgroups with specific metabolic vulnerabilities.

Objectives To analyze the performance of radiological assessment categories and quantitative computational analysis of apparent diffusion coefficient (ADC) maps using variant machine learning algorithms to differentiate clinically significant versus insignificant prostate cancer (PCa). Methods Retrospectively, 73 patients were included in the study. The patients (mean age, 66.3 ± 7.6 years) were examined with multiparametric MRI (mpMRI) prior to radical prostatectomy (n = 33) or targeted biopsy (n = 40). The index lesion was annotated in MRI ADC and the equivalent histologic slides according to the highest Gleason Grade Group (GrG). Volumes of interest (VOIs) were determined for each lesion and normal-appearing peripheral zone. VOIs were processed by radiomic analysis. For the classification of lesions according to their clinical significance (GrG ≥ 3), principal component (PC) analysis, univariate analysis (UA) with consecutive support vector machines, neural networks, and random forest analysis were performed. Results PC analysis discriminated between benign and malignant prostate tissue. PC evaluation yielded no stratification of PCa lesions according to their clinical significance, but UA revealed differences in clinical assessment categories and radiomic features. We trained three classification models with fifteen feature subsets. We identified a subset of shape features which improved the diagnostic accuracy of the clinical assessment categories (maximum increase in diagnostic accuracy ΔAUC = + 0.05, p Conclusions The impact of radiomic features to differentiate PCa lesions according to their clinical significance remains controversial. It depends on feature selection and the employed machine learning algorithms. It can result in improvement or reduction of diagnostic performance. Key Points • Quantitative imaging features differ between normal and malignant tissue of the peripheral zone in prostate cancer. • Radiomic feature analysis of clinical routine multiparametric MRI has the potential to improve the stratification of clinically significant versus insignificant prostate cancer lesions in the peripheral zone. • Certain combinations of standard multiparametric MRI reporting and assessment categories with feature subsets and machine learning algorithms reduced the diagnostic performance over standard clinical assessment categories alone.

To assess the impact of noise-optimised virtual monoenergetic imaging (VMI+) on image quality and diagnostic evaluation in abdominal dual-energy CT scans with impaired portal-venous contrast.We screened 11,746 patients who underwent portal-venous abdominal dual-energy CT for cancer staging between 08/2014 and 11/2019 and identified those with poor portal-venous contrast.Standard linearly-blended image series and VMI+ image series at 40, 50, and 60 keV were reconstructed. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of abdominal organs and vascular structures were calculated. Image noise, image contrast and overall image quality were rated by three radiologists using 5-point Likert scale.452 of 11,746 (4%) exams were poorly opacified. We excluded 190 cases due to incomplete datasets or multiple exams of the same patient with a final study group of 262. Highest CNR values in all abdominal organs (liver, 6.4 ± 3.0; kidney, 17.4 ± 7.5; spleen, 8.0 ± 3.5) and vascular structures (aorta, 16.0 ± 7.3; intrahepatic vein, 11.3 ± 4.7; portal vein, 15.5 ± 6.7) were measured at 40 keV VMI+ with significantly superior values compared to all other series. In subjective analysis, highest image contrast was seen at 40 keV VMI+ (4.8 ± 0.4), whereas overall image quality peaked at 50 keV VMI+ (4.2 ± 0.5) with significantly superior results compared to all other series (Image reconstruction using VMI+ algorithm at 50 keV significantly improves image contrast and image quality of originally poorly opacified abdominal CT scans and reduces the number of non-diagnostic scans.We validated the impact of VMI+ reconstructions in poorly attenuated DECT studies of the abdomen in a big data cohort.

To identify transjugular intrahepatic portosystemic shunt (TIPS) thrombosis in abdominal CT scans applying quantitative image analysis.We retrospectively screened 184 patients to include 20 patients (male, 8; female, 12; mean age, 60.7 ± 8.87 years) with (case, n = 10) and without (control, n = 10) in-TIPS thrombosis who underwent clinically indicated contrast-enhanced and unenhanced abdominal CT followed by conventional TIPS-angiography between 08/2014 and 06/2020. First, images were scored visually. Second, region of interest (ROI) based quantitative measurements of CT attenuation were performed in the inferior vena cava (IVC), portal vein and in four TIPS locations. Minimum, maximum and average Hounsfield unit (HU) values were used as absolute and relative quantitative features. We analyzed the features with univariate testing.Subjective scores identified in-TIPS thrombosis in contrast-enhanced scans with an accuracy of 0.667 - 0.833. Patients with in-TIPS thrombosis had significantly lower average (p 0.001), minimum (p 0.001) and maximum HU (p = 0.043) in contrast-enhanced images. The in-TIPS / IVC ratio in contrast-enhanced images was significantly lower in patients with in-TIPS thrombosis (p 0.001). No significant differences were found for unenhanced images. Analyzing the visually most suspicious ROI with consecutive calculation of its ratio to the IVC, all patients with a ratio 1 suffered from in-TIPS thrombosis (p 0.001, sensitivity and specificity = 100%).Quantitative analysis of abdominal CT scans facilitates the stratification of in-TIPS thrombosis. In contrast-enhanced scans, an in-TIPS / IVC ratio 1 could non-invasively stratify all patients with in-TIPS thrombosis.

To find out the opinion of radiological inpatient and outpatient medical staff regarding the measures taken in relation to the COVID-19 pandemic during the first and second waves and to identify the measures that are still perceived as needing improvement.We conducted an anonymous online survey among more than 10 000 radiologists/technicians in Germany from January 5 to January 31, 2021. A total of 862 responses (head physicians, n = 225 [inpatient doctors, n = 138; outpatient doctors, n = 84; N/A, n = 3]; radiologic personnel, n = 637 [inpatient doctor, n = 303; outpatient doctor, n = 50; inpatient technician, n = 217; outpatient technician, n = 26; N/A, n = 41]) were received. Questions of approximation, yes/no questions, and Likert scales were used.During the first/second wave, 70 % (86/123)/43 % (45/104) of inpatient and 26 % (17/66)/10 % (5/52) of outpatient head physicians agreed that they received financial support from the authorities but the majority rated the financial support as insufficient. During the first and second wave, 33 % (8/24) and 80 % (16/20) of outpatient technicians agreed that they were adequately provided with personal protective equipment. The perceived lack of personal protective equipment improved for all participants during the second wave. Inpatient [outpatient] technicians perceived an increased workload in the first and second wave: 72 % (142/198) [79 % (19/24)] and 84 % (146/174) [80 % (16/20)].Technicians seem increasingly negatively affected by the COVID-19 pandemic in Germany. Financial support by the competent authorities seems to be in need of improvement.· The accessibility of personal protective equipment resources improved in the second wave.. · In particular, radiology technicians seem increasingly negatively affected by the COVID-19 pandemic.. · Financial and consulting support from the government could be improved..· Bernatz S, Afat S, Othman AE et al. Impact of the COVID-19 Pandemic on Radiology in Inpatient and Outpatient Care in Germany: A Nationwide Survey Regarding the First and Second Wave. Fortschr Röntgenstr 2022; 194: 70 - 82. Das Ziel war, die Meinungen des stationären und ambulanten medizinisch-radiologischen Personals zu den Maßnahmen zu ermitteln, die im Zusammenhang mit der COVID-19-Pandemie während der ersten und zweiten Welle ergriffen wurden. Zusätzlich sollten die Maßnahmen identifiziert werden, die noch als verbesserungsbedürftig angesehen werden. Wir führten eine anonyme, onlinebasierte Umfrage unter mehr als 10 000 Radiolog/innen und medizinisch-technischen Radiologieassistent/innen (MTRA) in Deutschland vom 5.-31. Januar 2021 durch. Insgesamt erhielten wir 862 Antworten (Chefärzt/innen n = 225 (stationär tätige Ärzt/innen n = 138, ambulant tätige Ärzt/innen n = 84, N/A n = 3); radiologisches Personal n = 637 (stationär tätige Ärzt/innen n = 303, ambulant tätige Ärzt/innen n = 50, stationär tätige MTRA n = 217, ambulant tätige MTRA n = 26, N/A n = 41)). Es wurden Schätzfragen, Ja/Nein-Fragen und Likert-ähnliche Skalen verwendet. Während der ersten/zweiten Welle stimmten 70 % (86/123)/43 % (45/104) der stationären und 26 % (17/66)/10 % (5/52) der ambulanten Chefärzt/innen zu, finanzielle Unterstützung von den Behörden erhalten zu haben, aber die Mehrheit bewertete die finanzielle Unterstützung als nicht ausreichend. Während der ersten und zweiten Welle stimmten 33 % (8/24) und 80 % (16/20) der ambulanten MTRA zu, dass sie ausreichend mit persönlicher Schutzausrüstung ausgestattet wurden. Der wahrgenommene Mangel an persönlicher Schutzausrüstung verbesserte sich bei allen Teilnehmern während der zweiten Welle. Stationäre/ambulante MTRA empfanden in der ersten und zweiten Welle eine erhöhte Arbeitsbelastung: 72 % (142/198)/79 % (19/24) und 84 % (146/174)/80 % (16/20). MTRA scheinen von der COVID-19-Pandemie in Deutschland zunehmend negativ betroffen zu sein. Die finanzielle Unterstützung durch die zuständigen Behörden scheint verbesserungsbedürftig zu sein. · Die Verfügbarkeit von persönlicher Schutzausrüstung hat sich in der zweiten Welle verbessert.. · Insbesondere MTAs scheinen zunehmend negativ von der COVID-19-Pandemie betroffen zu sein.. · Die finanzielle und beratende Unterstützung durch die Regierung könnte verbessert werden..

To assess the potential of material decomposition in dual-energy CT (DECT) to differentiate intrahepatic cholangiocarcinoma (iCCA) from hepatocellular carcinoma (HCC).In this retrospective study, we included 94 patients (26 female (27.7 %), median age 64.5 (interquartile range 55.5-74.5) years) with either iCCA or HCC who underwent abdominal contrast-enhanced DECT in arterial phase. To test for differences between iCCA (n = 47) and HCC (n = 47), we evaluated mean attenuation and DECT material density values including iodine density (ID), normalized iodine uptake (NIU), fat fraction, and lesion-to-liver parenchyma ratio. Histopathology served as reference standard for all lesions. We used univariate logistic regression models for the outcome iCCA versus HCC. ROC curve analysis was applied to assess discriminative ability of the model. Model accuracy was evaluated by calculating the Brier score. Youden index was applied to establish thresholds to differentiate between iCCA and HCC.Comparison of quantitative image parameters revealed significant differences between iCCA and HCC for ID (1.6 ± 0.5 mg/ml vs 2.8 ± 0.8 mg/ml, p 0.001), NIU (14.5 ± 4.8 vs 24.8 ± 10.3, p 0.001), attenuation (41.9 ± 10.1 HU vs 47.9 ± 8.9 HU, p = 0.003), and fat fraction (12.0 ± 7.8 % vs 9.0 ± 6.4 %, p = 0.045). ROC curve analysis revealed highest ability to differentiate iCCA from HCC for ID (AUC = 0.93, 95 % CI 0.89-0.98). For ID, an optimal threshold of 2.33 mg/dl was determined to discriminate between iCCA and HCC (sensitivity 89.4 %, specificity 76.6 %).DECT-based iodine quantification can serve as a tool for the differentiation of iCCA and HCC in contrast-enhanced CT. ID yielded the highest diagnostic performance and may assist in clinical routine CT diagnostics.

Our purpose was to analyze the robustness and reproducibility of magnetic resonance imaging (MRI) radiomic features. We constructed a multi-object fruit phantom to perform MRI acquisition as scan-rescan using a 3 Tesla MRI scanner. We applied T2-weighted (T2w) half-Fourier acquisition single-shot turbo spin-echo (HASTE), T2w turbo spin-echo (TSE), T2w fluid-attenuated inversion recovery (FLAIR), T2 map and T1-weighted (T1w) TSE. Images were resampled to isotropic voxels. Fruits were segmented. The workflow was repeated by a second reader and the first reader after a pause of one month. We applied PyRadiomics to extract 107 radiomic features per fruit and sequence from seven feature classes. We calculated concordance correlation coefficients (CCC) and dynamic range (DR) to obtain measurements of feature robustness. Intraclass correlation coefficient (ICC) was calculated to assess intra- and inter-observer reproducibility. We calculated Gini scores to test the pairwise discriminative power specific for the features and MRI sequences. We depict Bland Altmann plots of features with top discriminative power (Mann–Whitney U test). Shape features were the most robust feature class. T2 map was the most robust imaging technique (robust features (rf), n = 84). HASTE sequence led to the least amount of rf (n = 20). Intra-observer ICC was excellent (≥ 0.75) for nearly all features (max–min; 99.1–97.2%). Deterioration of ICC values was seen in the inter-observer analyses (max–min; 88.7–81.1%). Complete robustness across all sequences was found for 8 features. Shape features and T2 map yielded the highest pairwise discriminative performance. Radiomics validity depends on the MRI sequence and feature class. T2 map seems to be the most promising imaging technique with the highest feature robustness, high intra-/inter-observer reproducibility and most promising discriminative power.

While the central nervous system is considered an immunoprivileged site and brain tumors display immunosuppressive features, both innate and adaptive immune responses affect glioblastoma (GBM) growth and treatment resistance. However, the impact of the major immune cell population in gliomas, represented by glioma-associated microglia/macrophages (GAMs), on patients' clinical course is still unclear. Thus, we aimed at assessing the immunohistochemical expression of selected microglia and macrophage markers in 344 gliomas (including gliomas from WHO grade I-IV). Furthermore, we analyzed a cohort of 241 IDH1R132H-non-mutant GBM patients for association of GAM subtypes and patient overall survival. Phenotypical properties of GAMs, isolated from high-grade astrocytomas by CD11b-based magnetic cell sorting, were analyzed by immunocytochemistry, mRNA microarray, qRT-PCR and bioinformatic analyses. A higher amount of CD68-, CD163- and CD206-positive GAMs in the vital tumor core was associated with beneficial patient survival. The mRNA expression profile of GAMs displayed an upregulation of factors that are considered as pro-inflammatory M1 (eg, CCL2, CCL3L3, CCL4, PTGS2) and anti-inflammatory M2 polarization markers (eg, MRC1, LGMN, CD163, IL10, MSR1), the latter rather being associated with phagocytic functions in the GBM microenvironment. In summary, we present evidence that human GBMs contain mixed M1/M2-like polarized GAMs and that the levels of different GAM subpopulations in the tumor core are positively associated with overall survival of patients with IDH1R132H-non-mutant GBMs.

Objective To determine the feasibility and outcome of radical prostatectomy (RP) following neoadjuvant therapy (NAT) in patients with initial inoperable, rectum-infiltrating cT4 prostate cancer (PCa). Methods From 01/2018 to 12/2020, 26 patients with clinical (DRE) or radiographical (mpMRI) suspicion of rectum infiltrating PCa at diagnosis and NAT prior to RP were retrospectively identified from our prospective institutional database. Two patients were still inoperable after NAT. Downsizing was administered for at least 20 weeks and RP was performed after excluding ongoing rectal infiltration. Results At diagnosis, median PSA was 42.5 ng/ml (IQR: 23.0–66.1). Inductive NAT consisted of androgen deprivation therapy (ADT) in combination with chemotherapy (n = 9) or without chemotherapy (n = 14). Median preoperative PSA was 0.93 ng/ml (IQR: 0.24–0.40). Median time from NAT to RP was 6 months (IQR: 5–7). Two patients were still inoperable after NAT. Of 24 patients undergoing RP, abortion of surgery due to inoperability was observed in 2 patients (8.4%), demonstrating a total failure rate of NAT in 4 out of 26 patients (15.4%). One patient suffered a rectal injury with consecutive colostomy (4.2%). No Clavien-Dindo complication Grade IV or V were observed. Urinary continence was achieved in 16 patients (84.2%). Sufficient erection for sexual intercourse was present in 2 patients (10.5%). All patients received adjuvant ADT with or without radiation therapy. Median PSA at 13 months was 0.08 ng/ml (IQR: 0.01–0.74). Conclusion RP of initially rectum infiltrating PCa is feasible and safe after inductive NAT, however complications rates tend to be higher compared to standard RP.

Background: To assess the potential of radiomic features to quantify components of flowing blood to non-invasively predict moderate-to-severe anemia in non-contrast enhanced CT scans. Methods: One hundred patients (median age, 69 years; range, 19–94 years) who received CT scans of the thoracolumbar spine and blood-testing for hemoglobin and hematocrit levels ± 24h between 08/2018 and 11/2019 were retrospectively included. Intraaortic blood was segmented using a spherical volume of interest with consecutive radiomic analysis. Feature selection was performed applying analysis of correlation and collinearity. The final feature set was obtained to differentiate moderate-to-severe anemia. Random forest machine learning was applied and predictive performance was assessed. A decision-tree was obtained to propose a cut-off value of CT Hounsfield units (HU).Results: High correlation with hemoglobin and hematocrit levels was shown for first-order radiomic features (p

OBJECTIVES: To evaluate the potential of a fully automatic artificial intelligence (AI)-driven computed tomography (CT) software prototype to quantify severity of COVID-19 infection on chest CT in relationship with clinical and laboratory data. METHODS: We retrospectively analyzed 50 patients with laboratory confirmed COVID-19 infection who had received chest CT between March and July 2020. Pulmonary opacifications were automatically evaluated by an AI-driven software and correlated with clinical and laboratory parameters using Spearman-Rho and linear regression analysis. We divided the patients into sub cohorts with or without necessity of intensive care unit (ICU) treatment. Sub cohort differences were evaluated employing Wilcoxon-Mann-Whitney-Test. RESULTS: We included 50 CT examinations (mean age, 57.24 years), of whom 24 (48%) had an ICU stay. Extent of COVID-19 like opacities on chest CT showed correlations (all p < 0.001 if not otherwise stated) with occurrence of ICU stay (R = 0.74), length of ICU stay (R = 0.81), lethal outcome (R = 0.56) and length of hospital stay (R = 0.33, p < 0.05). The opacities extent was correlated with laboratory parameters: neutrophil count (NEU) (R = 0.60), lactate dehydrogenase (LDH) (R = 0.60), troponin (TNTHS) (R = 0.55) and c-reactive protein (CRP) (R = 0.51). Differences (p < 0.001) between ICU group and non-ICU group concerned longer length of hospital stay (24.04 vs. 10.92 days), higher opacity score (12.50 vs. 4.96) and severity of laboratory data changes such as c-reactive protein (11.64 vs. 5.07 mg/dl, p < 0.01). CONCLUSIONS: Automatically AI-driven quantification of opacities on chest CT correlates with laboratory and clinical data in patients with confirmed COVID-19 infection and may serve as non-invasive predictive marker for clinical course of COVID-19.

Objective: To investigate the value of standard [digital rectal examination (DRE), PSA] and advanced (mpMRI, prostate biopsy) clinical evaluation for prostate cancer (PCa) detection in contemporary patients with clinical bladder outlet obstruction (BOO) scheduled for Holmium laser enucleation of the prostate (HoLEP). Material and Methods: We retrospectively analyzed 397 patients, who were referred to our tertiary care laser center for HoLEP due to BOO between 11/2017 and 07/2020. Of those, 83 (20.7%) underwent further advanced clinical PCa evaluation with mpMRI and/or prostate biopsy due to elevated PSA and/or lowered PSA ratio and/or suspicious DRE. Logistic regression and binary regression tree models were applied to identify PCa in BOO patients. Results: An mpMRI was conducted in 56 (66%) of 83 patients and revealed PIRADS 4/5 lesions in 14 (25%) patients. Subsequently, a combined systematic randomized and MRI-fusion biopsy was performed in 19 (23%) patients and revealed in PCa detection in four patients (5%). A randomized prostate biopsy was performed in 31 (37%) patients and revealed in PCa detection in three patients (4%). All seven patients (9%) with PCa detection underwent radical prostatectomy with 29% exhibiting non-organ confined disease. Incidental PCa after HoLEP (n = 76) was found in nine patients (12%) with advanced clinical PCa evaluation preoperatively. In univariable logistic regression analyses, PSA, fPSA ratio, and PSA density failed to identify patients with PCa detection. Conversely, patients with a lower International Prostate Symptom Score (IPSS) and PIRADs 4/5 lesion in mpMRI were at higher risk for PCa detection. In multivariable adjusted analyses, PIRADS 4/5 lesions were confirmed as an independent risk factor (OR 9.91, p = 0.04), while IPSS did not reach significance (p = 0.052). Conclusion: In advanced clinical PCa evaluation mpMRI should be considered in patients with elevated total PSA or low fPSA ratio scheduled for BOO treatment with HoLEP. Patients with low IPSS or PIRADS 4/5 lesions in mpMRI are at highest risk for PCa detection. In patients with a history of two or more sets of negative prostate biopsies, advanced clinical PCa evaluation might be omitted.

Higher grade meningiomas tend to recur. We aimed to evaluate protein levels of vascular endothelial growth factor (VEGF)-A with the VEGF-receptors 1-3 and the co-receptors Neuropilin (NRP)-1 and -2 in WHO grade II and III meningiomas to elucidate the rationale for targeted treatments. We investigated 232 specimens of 147 patients suffering from cranial meningioma, including recurrent tumors. Immunohistochemistry for VEGF-A, VEGFR-1-3, and NRP-1/-2 was performed on tissue micro arrays. We applied a semiquantitative score (staining intensity x frequency). VEGF-A, VEGFR-1-3, and NRP-1 were heterogeneously expressed. NRP-2 was mainly absent. We demonstrated a significant increase of VEGF-A levels on tumor cells in WHO grade III meningiomas (p = 0.0098). We found a positive correlation between expression levels of VEGF-A and VEGFR-1 on tumor cells and vessels (p < 0.0001). In addition, there was a positive correlation of VEGF-A and VEGFR-3 expression on tumor vessels (p = 0.0034). VEGFR-2 expression was positively associated with progression-free survival (p = 0.0340). VEGF-A on tumor cells was negatively correlated with overall survival (p = 0.0084). The VEGF-A-driven system of tumor angiogenesis might still present a suitable target for adjuvant therapy in malignant meningioma disease. However, its role in malignant tumor progression may not be as crucial as expected. The value of comprehensive testing of the ligand and all receptors prior to administration of anti-angiogenic therapy needs to be evaluated in clinical trials.

In Europe extracts from Viscum album L., the European white-berry mistletoe, are widely used as a complementary cancer therapy. Viscumins (mistletoe lectins, ML) have been scrutinized as important active components of mistletoe and exhibit a variety of anticancer effects such as stimulation of the immune system, induction of cytotoxicity, reduction of tumor cell motility as well as changes in the expression of genes associated with cancer development and progression. By microarray expression analysis, quantitative RT-PCR and RT-PCR based validation of microarray data we demonstrate for the Viscum album extract Iscador Qu and for the lectins Aviscumine and ML-1 that in glioma cells these drugs differentially modulate the expression of genes involved in the regulation of cell migration and invasion, including processes modulating cell architecture and cell adhesion. A variety of differentially expressed genes in ML treated cells are associated with the transforming growth factor (TGF)-β signaling pathway or are targets of TGF-β. ML treatment downregulated the expression of TGF-β itself, of the TGF-β receptor II (TGFBR2), of the TGF-β intracellular signal transducer protein SMAD2, and of matrix-metalloproteinases (MMP) MMP-2 and MMP-14. Even if the changes in gene expression differ between Aviscumine, Iscador Qu and ML-1, the overall regulation of motility associated gene expression by all drugs showed functional effects since tumor cell motility was reduced in a ML-dependent manner. Therefore, ML containing compounds might provide clinical benefit as adjuvant therapeutics in the treatment of patients with invasively growing tumors such as glioblastomas.

Background Breast cancer (BC) is the most frequent malignant tumor in females and the 2nd most common cause of brain metastasis (BM), that are associated with a fatal prognosis. The increasing incidence from 10% up to 40% is due to more effective treatments of extracerebral sites with improved prognosis and increasing use of MRI in diagnostics. A frequently administered, potent chemotherapeutic group of drugs for BC treatment are taxanes usually used in the adjuvant and metastatic setting, which, however, have been suspected to be associated with a higher incidence of BM. The aim of our study was to experimentally analyze the impact of the taxane docetaxel (DTX) on brain metastasis formation, and to elucidate the underlying molecular mechanism. Methods A monocentric patient cohort was analyzed to determine the association of taxane treatment and BM formation. To identify the specific impact of DTX, a murine brain metastatic model upon intracardial injection of breast cancer cells was conducted. To approach the functional mechanism, dynamic contrast-enhanced MRI and electron microscopy of mice as well as in-vitro transendothelial electrical resistance (TEER) and tracer permeability assays using brain endothelial cells (EC) were carried out. PCR-based, immunohistochemical and immunoblotting analyses with additional RNA sequencing of murine and human ECs were performed to explore the molecular mechanisms by DTX treatment. Results Taxane treatment was associated with an increased rate of BM formation in the patient cohort and the murine metastatic model. Functional studies did not show unequivocal alterations of blood-brain barrier properties upon DTX treatment in-vivo, but in-vitro assays revealed a temporary DTX-related barrier disruption. We found disturbance of tubulin structure and upregulation of tight junction marker claudin-5 in ECs. Furthermore, upregulation of several members of the tubulin family and downregulation of tetraspanin-2 in both, murine and human ECs, was induced. Conclusion In summary, a higher incidence of BM was associated with prior taxane treatment in both a patient cohort and a murine mouse model. We could identify tubulin family members and tetraspanin-2 as potential contributors for the destabilization of the blood-brain barrier. Further analyses are needed to decipher the exact role of those alterations on tumor metastatic processes in the brain.

Simple Summary: Early and accurate diagnosis of breast cancer that has spread to other organs and tissues is crucial, as therapeutic decisions and outcome expectations might change. Computed tomography (CT) is often used to detect breast cancer’s spread, but this method has its weaknesses. The computer-assisted technique “radiomics” extracts grey-level patterns, so-called radiomic features, from medical images, which may reflect underlying biological processes. Our retrospective study therefore evaluated whether breast cancer spread can be predicted by radiomic features derived from iodine maps, an application on a new generation of CT scanners visualizing tissue blood flow. Based on 77 patients with newly diagnosed breast cancer, we found that this approach might indeed predict cancer spread to other organs/tissues. In the future, radiomics may serve as an additional tool for cancer detection and risk assessment. Abstract: Dual-energy CT (DECT) iodine maps enable quantification of iodine concentrations as a marker for tissue vascularization. We investigated whether iodine map radiomic features derived from staging DECT enable prediction of breast cancer metastatic status, and whether textural differ- ences exist between primary breast cancers and metastases. Seventy-seven treatment-naïve patients with biopsy-proven breast cancers were included retrospectively (41 non-metastatic, 36 metastatic). Radiomic features including first-, second-, and higher-order metrics as well as shape descriptors were extracted from volumes of interest on iodine maps. Following principal component analysis, a multilayer perceptron artificial neural network (MLP-NN) was used for classification (70% of cases for training, 30% validation). Histopathology served as reference standard. MLP-NN predicted metastatic status with AUCs of up to 0.94, and accuracies of up to 92.6 in the training and 82.6 in the validation datasets. The separation of primary tumor and metastatic tissue yielded AUCs of up to 0.87, with accuracies of up to 82.8 in the training, and 85.7 in the validation dataset. DECT iodine map-based radiomic signatures may therefore predict metastatic status in breast cancer patients. In addition, microstructural differences between primary and metastatic breast cancer tissue may be reflected by differences in DECT radiomic features.