Background: Endovascular revascularization has established as the first-line therapy of femoropopliteal artery disease. Paclitaxel-coated balloon angioplasty proved to be superior to plain old balloon angioplasty (POBA) regarding prevention of restenosis and need for recurrent revascularization. Over the past years, paclitaxel was the only active drug to inhibit neointimal proliferation which could be processed to an appropriate balloon coating. The purpose of this study is to assess whether efficacy and safety of sirolimus-coated balloon angioplasty is noninferior to paclitaxel-coated balloon angioplasty. Methods: This randomized controlled, single-blinded, multicentre, investigator-initiated noninferiority trial aims to enrol a total of 478 participants with symptomatic femoropopliteal artery disease of Rutherford category 2 to 4 due to de novo stenosis or restenosis. After pre-dilation, participants will be allocated in a 1:1 ratio to either sirolimus- or paclitaxel-coated balloon angioplasty. Post-dilation with the drug-coated balloon (DCB) used or standard balloon is mandatory in case ≥ 50%, and optional in case of ≥ 30% residual diameter stenosis. Bailout stenting with bare-metal nitinol stents should be conducted in case of flow-limiting dissection. Primary noninferiority endpoints are primary patency and the composite of all-cause mortality, major target limb amputation, and clinically driven target lesion revascularization at 12 months. Secondary outcomes are clinical and hemodynamic improvement, change in health-related quality of life, and safety throughout 60 months. Discussion: Although concerns about long-term safety of paclitaxel-coated devices were not confirmed by recent patient-level data analyses, conflicting evidence contributed to a loss of confidence among patients and physicians. Therefore, sirolimus, known for a broader therapeutic range than paclitaxel, may serve as a welcome alternative. This will be justified if noninferiority of sirolimus-coated balloon angioplasty against the current standard of paclitaxel-coated balloon angioplasty can be demonstrated. Trial registration: ClinicalTrials.gov NCT04475783. Registered on 17 July 2020 EUDAMED No. CIV-20-11-035172, DRKS00022452

Background: It is essential to avoid admission of patients with undetected corona virus disease 2019 (COVID-19) to hospitals’ general wards. Even repeated negative reverse transcription polymerase chain reaction (RT-PCR) results do not rule-out COVID-19 with certainty. The study aimed to evaluate a rule-out strategy for COVID-19 using chest computed tomography (CT) in adults being admitted to the emergency department and suspected of COVID-19. Methods: In this prospective, single centre, diagnostic accuracy cohort study, consecutive adults (≥ 18 years) presenting with symptoms consistent with COVID-19 or previous contact to infected individuals, admitted to the emergency department and supposed to be referred to general ward were included in March and April 2020. All participants underwent low-dose chest CT. RT-PCR- and specific antibody tests were used as reference standard. Main outcome measures were sensitivity and specificity of chest CT. Predictive values were calculated based on the theorem of Bayes using Fagan’s nomogram. Results: Of 165 participants (56.4% male, 71 ± 16 years) included in the study, the diagnosis of COVID-19 was confirmed with RT-PCR and AB tests in 13 participants (prevalence 7.9%). Sensitivity and specificity of chest CT were 84.6% (95% confidence interval [CI], 54.6–98.1) and 94.7% (95% CI, 89.9–97.7), respectively. Positive and negative likelihood ratio of chest CT were 16.1 (95% CI, 7.9–32.8) and 0.16 (95% CI, 0.05–0.58) and positive and negative predictive value were 57.9% (95% CI, 40.3–73.7) and 98.6% (95% CI, 95.3–99.6), respectively. Conclusion: At a low prevalence of COVID-19, chest CT could be used as a complement to repeated RT-PCR testing for early COVID-19 exclusion in adults with suspected infection before referral to hospital’s general wards. Trial registration ClinicalTrials.gov: NCT04357938 April 22, 2020.

Objectives: To evaluate the diagnostic accuracy of AI-assisted biparametric MRI (AI-bpMRI) in detecting prostate cancer (PCa) as a possible replacement for multiparametric MRI (mpMRI) depending on readers’ experience. Methods: This fully crossed, multireader multicase, single-centre, consecutive study retrospectively included men with suspected PCa. Three radiologists with different levels of experience independently scored each participant’s biparametric (bp) MRI, mpMRI, and AI-bpMRI according to the PI-RADS V2.1 classification. The AI-assisted image processing was based on a sequential deep learning network. Histopathological findings were used as a reference. The study evaluated the mean areas under the receiver operating characteristic curves (AUCs) using the jackknife method for covariance. AUCs were tested for non-inferiority of AI-bpMRI to mpMRI (non-inferiority margin: −0.05). Results: A total of 105 men (mean age 66 ± 7 years) were evaluated. AI-bpMRI was non-inferior to mpMRI in detecting both Gleason score (GS) ≥ 3 + 4 PCa (AUC difference: 0.03 [95% CI: −0.03, 0.08], p = 0.37) and GS ≥ 3 + 3 PCa (AUC difference: 0.04 [95% CI: −0.01, 0.09], p = 0.14) and was superior to bpMRI in detecting GS ≥ 3 + 3 PCa (AUC difference: 0.07 [95% CI: 0.02, 0.12], p = 0.004). The benefit of AI-bpMRI was greatest for the readers with low or medium experience (AUC difference in detecting GS ≥ 3 + 4 compared to mpMRI: 0.06 [95% CI: −0.03, 0.14], p = 0.19 and 0.06 [95% CI: −0.03, 0.14], p = 0.19, respectively). Conclusions: This study indicates that AI-bpMRI detects PCa with a diagnostic accuracy comparable to that of mpMRI.

Background: In hospitals, it is crucial to rule out coronavirus disease 2019 (COVID-19) timely and reliably. Artificial intelligence (AI) provides sufficient accuracy to identify chest computed tomography (CT) scans with signs of COVID-19. Purpose: To compare the diagnostic accuracy of radiologists with different levels of experience with and without assistance of AI in CT evaluation for COVID-19 pneumonia and to develop an optimized diagnostic pathway. Material and Methods: The retrospective, single-center, comparative case-control study included 160 consecutive participants who had undergone chest CT scan between March 2020 and May 2021 without or with confirmed diagnosis of COVID-19 pneumonia in a ratio of 1:3. Index tests were chest CT evaluation by five radiological senior residents, five junior residents, and an AI software. Based on the diagnostic accuracy in every group and on comparison of groups, a sequential CT assessment pathway was developed. Results: Areas under receiver operating curves were 0.95 (95% confidence interval [CI]=0.88–0.99), 0.96 (95% CI=0.92–1.0), 0.77 (95% CI=0.68–0.86), and 0.95 (95% CI=0.9–1.0) for junior residents, senior residents, AI, and sequential CT assessment, respectively. Proportions of false negatives were 9%, 3%, 17%, and 2%, respectively. With the developed diagnostic pathway, junior residents evaluated all CT scans with the support of AI. Senior residents were only required as second readers in 26% (41/160) of the CT scans. Conclusion: AI can support junior residents with chest CT evaluation for COVID-19 and reduce the workload of senior residents. A review of selected CT scans by senior residents is mandatory.

Summary: Background: The influence of diabetes mellitus (DM) on recurrent in-stent restenosis (ISR) of femoropopliteal arteries remains understudied. We investigated whether DM has an impact on rec...