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Background: Patients with suspected prostate cancer usually undergo transrectal ultrasound-guided (TRUS) systematic biopsy, which can miss relevant prostate cancers and lead to overtreatment., Aims: The aim of this study was to evaluate the detection rate for prostate cancer in MR-guided targeted biopsy (TB) and systematic biopsy (SB) in comparison with mpMRI of the prostate., Methods and Results: Three hundred and eight men who underwent mpMRI due to elevated PSA values between 2015 and 2020 were studied at university hospital Aachen, Germany. MRI-images were divided into cohorts with suspicious findings (PI-RADS ≥ 3) and negative findings (PI-RADS < 3). In patients with PI-RADS ≥ 3 TB combined with SB was performed. A part of this group underwent RP subsequently. In patients with PI-RADS < 3 and clinical suspicion SB was performed. In the PI-RADS ≥ 3 group (n = 197), TB combined with SB was performed in 194 cases. Three cases were lost to follow-up. Biopsy yielded 143 positive biopsies and 51 cases without carcinoma. TB detected 71% (102/143) and SB 98% (140/143) of the overall 143 carcinoma. Overall, 102 carcinomas were detected by TB, hereof 66% (67/102) clinically significant (Gleason ≥ 3+4) and 34% (35/102) clinically insignificant carcinoma (Gleason 3+3). SB detected 140 carcinomas, hereof 64% (90/140) csPCA and 36% (50/140) nsPCA. Forty-one of the overall 143 detected carcinoma were only found by SB, hereof 46% (19/41) csPCA and 54% (22/41) nsPCA. Tumor locations overlapped in 44% (63/143) between TB and SB. In 25% (36/143), SB detected additional tumor foci outside the target lesions. 70/143 patients subsequently underwent RP. The detection of tumor foci was congruent between mpMRI and prostatectomy specimen in 79% (55/70) of cases. Tumor foci were mpMRI occult in 21% (15/70) of cases. In the group with negative mpMRI (n = 111), biopsy was performed in 81 cases. Gleason ≥ 3+4 carcinoma was detected in 7% and Gleason 3+3 in 24% cases., Conclusion: There was a notable number of cases in which SB detected tumor foci that were mpMRI occult and could have been missed by TB alone. Therefore, additional systematic random biopsy is still required. A supplemental random biopsy should be considered depending on the overall clinical suspicion in negative mpMRI., (© 2024 The Authors. Cancer Reports published by Wiley Periodicals LLC.)

Background: So far, typical findings for COVID-19 in computed tomography (CT) have been described as bilateral, multifocal ground glass opacities (GGOs) and consolidations, as well as intralobular and interlobular septal thickening. On the contrary, round consolidations with the halo sign are considered uncommon and are typically found in fungal infections, such as invasive pulmonary aspergillosis. The authors recently observed several patients with COVID-19 pneumonia presenting with round, multifocal consolidations accompanied by a halo sign. As this may indicate alterations of CT morphology based on the virus variant, the aim of this study was to investigate this matter in more detail., Methods: 161 CT scans of patients with confirmed SARS-CoV-2 infection (RT-PCR within 2 days of CT) examined between January 2021 and September 15, 2021 were included. Follow-up examinations, patients with invasive ventilation at the time of CT, and patients with insufficient virus typing for variants of concern (VOC) were excluded. CT scans were assessed for vertical and axial distribution of pulmonary patterns, degree of involvement, uni- vs. bilaterality, reticulations, and other common findings. The mean density of representative lesions was assessed in Hounsfield units. Results were compared using Mann-Whitney U-tests, Student's t-rests, descriptive statistics, and Fisher's exact tests., Results: 75 patients did not meet the inclusion criteria. Therefore, 86/161 CT scans of unique patients were analyzed. PCR VOC testing confirmed manifestation of the Delta-VOC SARS-CoV-2 in 22 patients, 39 patients with Alpha-VOC and the remaining 25 patients with Non-VOC SARS-CoV-2 infections. Three patients with the Delta-VOC demonstrated multiple pulmonary masses or nodules with surrounding halo sign, whereas no patients with either Alpha-VOC (p = 0.043) or non-VOC (p = 0.095) demonstrated these findings. All three patients were admitted to normal wards and had no suspicion of a pulmonary co-infection. Patients with Delta-VOC were less likely to have ground glass opacities compared to Alpha-VOC (7/22 or 31.8 % vs. 4/39 or 10.3 %; p < 0.001), whereas a significant difference has not been observed between Delta-VOC and non-VOC (5/25 or 20 %; p = 0.348). The mean representative density of lesions did not show significant differences between the studied cohorts., Conclusion: In this study 3 out of 22 patients (13.6 %) with Delta-VOC presented with bilateral round pulmonary masses or nodules with surrounding halo signs, which has not been established as a notable imaging pattern in COVID-19 pneumonia yet. Compared to the other cohorts, a lesser percentage of patients with Delta-VOC presented with ground glass opacities. Based on these results Delta-VOC might cause a divergence in CT-morphologic phenotype., Key Points: · Until recently, CT-morphologic signs of COVID-19 pneumonia have been presumed to be uncontroversially understood. Yet, recently the authors observed diverging pulmonary alterations in patients infected with Delta-VOC.. · These imaging alterations included round pulmonary masses or nodules with surrounding halo sign.. · These imaging alterations have not yet been established as typical for COVID-19 pneumonia, yet.. · Based on these results, Delta-VOC could impose a divergence of CT-morphologic phenotype.., Citation Format: · Yüksel C, Sähn M, Kleines M et al. Possible Alterations of Imaging Patterns in Computed Tomography for Delta-VOC of SARS-CoV-2 . Fortschr Röntgenstr 2022; 194: 1229 - 1241., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

Purpose: The psoas major muscle (PMM) volume serves as an opportunistic imaging marker in cross-sectional imaging datasets for various clinical applications. Since manual segmentation is time consuming, two different automated segmentation methods, a generative adversarial network architecture (GAN) and a multi-atlas segmentation (MAS), as well as a combined approach of both, were investigated in terms of accuracy of automated volumetrics in given CT datasets., Materials and Methods: The bilateral PMM was manually segmented by a radiologist in 34 abdominal CT scans, resulting in 68 single 3D muscle segmentations as training data. Three different methods were tested for their ability to generate automated image segmentations: a GAN- and MAS-based approach and a combined approach of both methods (COM). Bilateral PMM volume (PMMV) was calculated in cm 3 by each algorithm for every CT. Results were compared to the corresponding ground truth using the Dice similarity coefficient (DSC), Spearman's correlation coefficient and Wilcoxon signed-rank test., Results: Mean PMMV was 239 ± 7.0 cm 3 and 308 ± 9.6 cm 3 , 306 ± 9.5 cm 3 and 243 ± 7.3 cm 3 for the CNN, MAS and COM, respectively. Compared to the ground truth the CNN and MAS overestimated the PMMV significantly (+ 28.9% and + 28.0%, p < 0.001), while results of the COM were quite accurate (+ 0.7%, p = 0.33). Spearman's correlation coefficients were 0.38, 0.62 and 0.73, and the DSCs were 0.75 [95%CI: 0.56-0.88], 0.73 [95%CI: 0.54-0.85] and 0.82 [95%CI: 0.65-0.90] for the CNN, MAS and COM, respectively., Conclusion: The combined approach was able to efficiently exploit the advantages of both methods (GAN and MAS), resulting in a significantly higher accuracy in PMMV predictions compared to the isolated implementations of both methods. Even with the relatively small set of training data, the segmentation accuracy of this hybrid approach was relatively close to that of the radiologist., (© 2021. The Author(s).)

Purpose: To determine the performance of radiologists with different levels of expertise regarding the differentiation of COVID-19 from other atypical pneumonias. Chest CT to identify patients suffering from COVID-19 has been reported to be limited by its low specificity for distinguishing COVID-19 from other atypical pneumonias ("COVID-19 mimics"). Meanwhile, the understanding of the morphologic patterns of COVID-19 has improved and they appear to be fairly specific., Materials and Methods: Between 02/2020 and 04/2020, 60 patients with COVID-19 pneumonia underwent chest CT in our department. Cases were matched with a comparable control group of 60 patients of similar age, sex, and comorbidities, who underwent chest CT prior to 01/2020 for atypical pneumonia caused by other pathogens. Included were other viral, fungal, and bacterial pathogens. All 120 cases were blinded to patient history and were reviewed independently by two radiologists and two radiology residents. Readers rated the probability of COVID-19 pneumonia according to the COV-RADS classification system. Results were analyzed using Clopper-Pearson 95 % confidence intervals, Youden's Index for test quality criteria, and Fleiss' kappa statistics., Results: Overall, readers were able to correctly identify the presence of COVID-19 pneumonia in 219/240 (sensitivity: 91 %; 95 %-CI; 86.9 %-94.5 %), and to correctly attribute CT findings to COVID-19 mimics in 159/240 ratings (specificity: 66.3 %; 59.9 %-72.2 %), yielding an overall diagnostic accuracy of 78.8 % (378/480; 74.8 %-82.3 %). Individual reader accuracy ranged from 74.2 % (89/120) to 84.2 % (101/120) and did not correlate significantly with reader expertise. Youden's Index was 0.57. Between-reader agreement was moderate (κ = 0.53)., Conclusion: In this enriched cohort, radiologists were able to distinguish COVID-19 from "COVID-19 mimics" with moderate diagnostic accuracy. Accuracy did not correlate with reader expertise., Key Points: · In a scenario of direct comparison (no negative findings), CT allows the differentiation of COVID-19 from other atypical pneumonias ("COVID mimics") with moderate accuracy.. · Reader expertise did not significantly influence these results.. · Despite similar patterns and distributions of pulmonary findings, radiologists were able to estimate the probability of COVID-19 pneumonia using the COV-RADS classification in a standardized manner in the larger proportion of cases.., Citation Format: · Sähn M, Yüksel C, Keil S et al. Accuracy of Chest CT for Differentiating COVID-19 from COVID-19 Mimics. Fortschr Röntgenstr 2021; 193: 1081 - 1091., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

Alterations in bone mineral density (BMD) have been suggested as independent predictors of survival for several diseases. However, little is known about the role of BMD in the context of critical illness and intensive care medicine. We therefore evaluated the prognostic role of BMD in critically ill patients upon admission to an intensive care unit (ICU). Routine computed tomography (CT) scans of 153 patients were used to assess BMD in the first lumbar vertebra. Results were correlated with clinical data and outcomes. While median BMD was comparable between patients with and without sepsis, BMD was lower in patients with pre-existing arterial hypertension or chronic obstructive pulmonary disease. A low BMD upon ICU admission was significantly associated with impaired short-term ICU survival. Moreover, patients with baseline BMD < 122 HU had significantly impaired overall survival. The prognostic relevance of low BMD was confirmed in uni- and multivariate Cox-regression analyses including several clinicopathological parameters. In the present study, we describe a previously unrecognised association of individual BMD with short- and long-term outcomes in critically ill patients. Due to its easy accessibility in routine CT, BMD provides a novel prognostic tool to guide decision making in critically ill patients.

Purpose: To evaluate the feasibility of a novel curved CT-guided biopsy needle prototype with shape memory to access otherwise not accessible biopsy targets., Methods and Materials: A biopsy needle curved by 90° with specific radius was designed. It was manufactured using nitinol to acquire shape memory, encased in a straight guiding trocar to be driven out for access of otherwise inaccessible targets. Fifty CT-guided punctures were conducted in a biopsy phantom and 10 CT-guided punctures in a swine corpse. Biposies from porcine liver and muscle tissue were separately gained using the biopsy device, and histological examination was performed subsequently., Results: Mean time for placement of the trocar and deployment of the inner biopsy needle was ~205 ± 69 and ~93 ± 58 s, respectively, with a mean of ~4.5 ± 1.3 steps to reach adequate biopsy position. Mean distance from the tip of the needle to the target was ~0.7 ± 0.8 mm. CT-guided punctures in the swine corpse took relatively longer and required more biopsy steps (~574 ± 107 and ~380 ± 148 s, 8 ± 2.6 steps). Histology demonstrated appropriate tissue samples in nine out of ten cases (90%)., Conclusions: Targets that were otherwise inaccessible via standard straight needle trajectories could be successfully reached with the curved biopsy needle prototype. Shape memory and preformed size with specific radius of the curved needle simplify the target accessibility with a low risk of injuring adjacent structures.