Purpose To compare digital mammography (DM) plus digital breast tomosynthesis (DBT) versus DM alone for breast cancer screening in the Reggio Emilia Tomosynthesis trial, a two-arm test-and-treat randomized controlled trial. Materials and Methods For this trial, eligible women (45-70 years old) who previously participated in the Reggio Emilia screening program were invited for mammography. Consenting women were randomly assigned 1:1 to undergo DBT+DM or DM (both of which involved two projections and double reading). Women were treated according to the decision at DBT+DM. Sensitivity, recall rate, and positive predictive value (PPV) at baseline were determined; the ratios of these rates for DBT+DM relative to DM alone were determined. Results From March 2014 to March 2016, 9777 women were recruited to the DM+DBT arm of the study, and 9783 women were recruited to the DM arm (mean age, 56.2 vs 56.3 years). Recall was 3.5% in both arms; detection was 4.5 per 1000 (44 of 9783) and 8.6 per 1000 (83 of 9777), respectively (+89%; 95% confidence interval [CI]: 31, 72). PPV of the recall was 13.0% and 24.1%, respectively (P = .0002); 72 of 80 cancers found in the DBT+DM arm and with complete DBT imaging were positive at least at one DBT-alone reading. The greater detection rate for DM+DBT was stronger for ductal carcinoma in situ (+180%, 95% CI: 1, 665); it was notable for small and medium invasive cancers, but not for large ones (+94 [95% CI: 6, 254]; +122 [95% CI: 18, 316]; -12 [95% CI: -68, 141]; for invasive cancers < 10 mm, 10-19 mm, and ≥ 20 mm, respectively). Conclusion DBT+DM depicts 90% more cancers in a population previously screened with DM, with similar recall rates.

BackgroundNeoadjuvant-chemotherapy (NAC) is considered the standard treatment for locally advanced breast carcinomas. Accurate assessment of disease response is fundamental to increase the chances of successful breast-conserving surgery and to avoid local recurrence. The purpose of this study was to compare contrast-enhanced spectral mammography (CESM) and contrast-enhanced-MRI (MRI) in the evaluation of tumor response to NAC.MethodsThis prospective study was approved by the institutional review board and written informed consent was obtained. Fifty-four consenting women with breast cancer and indication of NAC were consecutively enrolled between October 2012 and December 2014. Patients underwent both CESM and MRI before, during and after NAC. MRI was performed first, followed by CESM within 3 days. Response to therapy was evaluated for each patient, comparing the size of the residual lesion measured on CESM and MRI performed after NAC to the pathological response on surgical specimens (gold standard), independently of and blinded to the results of the other test. The agreement between measurements was evaluated using Lin’s coefficient. The agreement between measurements using CESM and MRI was tested at each step of the study, before, during and after NAC. And last of all, the variation in the largest dimension of the tumor on CESM and MRI was assessed according to the parameters set in RECIST 1.1 criteria, focusing on pathological complete response (pCR).ResultsA total of 46 patients (85%) completed the study. CESM predicted pCR better than MRI (Lin’s coefficient 0.81 and 0.59, respectively). Both methods tend to underestimate the real extent of residual tumor (mean 4.1mm in CESM, 7.5mm in MRI). The agreement between measurements using CESM and MRI was 0.96, 0.94 and 0.76 before, during and after NAC respectively. The distinction between responders and non-responders with CESM and MRI was identical for 45/46 patients. In the assessment of CR, sensitivity and specificity were 100% and 84%, respectively, for CESM, and 87% and 60% for MRI.ConclusionCESM and MRI lesion size measurements were highly correlated. CESM seems at least as reliable as MRI in assessing the response to NAC, and may be an alternative if MRI is contraindicated or its availability is limited.

Objective To assess sensitivity/specificity of CT vs RT-PCR for the diagnosis of COVID-19 pneumonia in a prospective Italian cohort of symptomatic patients during the outbreak peak. Methods In this cross-sectional study, we included all consecutive patients who presented to the ER between March 13 and 23 for suspected COVID-19 and underwent CT and RT-PCR within 3 days. Using a structured report, radiologists prospectively classified CTs in highly suggestive, suggestive, and non-suggestive of COVID-19 pneumonia. Ground-glass, consolidation, and visual extension of parenchymal changes were collected. Three different RT-PCR-based reference standard definitions were used. Oxygen saturation level, CRP, LDH, and blood cell counts were collected and compared between CT/RT-PCR classes. Results The study included 696 patients (41.4% women; age 59 ± 15.8 years): 423/454 (93%) patients with highly suggestive CT, 97/ 127 (76%) with suggestive CT, and 31/115 (27%) with non-suggestive CT had positive RT-PCR. CT sensitivity ranged from 73 to 77% and from 90 to 94% for high and low positivity threshold, respectively. Specificity ranged from 79 to 84% for high positivity threshold and was about 58% for low positivity threshold. PPV remained ≥ 90% in all cases. Ground-glass was more frequent in patients with positive RT-PCR in all CT classes. Blood tests were significantly associated with RT-PCR and CT classes. Leukocytes, lymphocytes, neutrophils, and platelets decreased, CRP and LDH increased from non-suggestive to suggestive CT classes. Conclusions During the outbreak peak (in a high-prevalence setting), CT presented high PPV and may be considered a good reference to recognize COVID-19 patients while waiting for RT-PCR confirmation. Key Points • During the epidemic peak, CT showed high positive predictive value and sensitivity for COVID-19 pneumonia when compared with RT-PCR. • Blood tests were significantly associated with RT-PCR and CT classes.

We assessed the impact of chest CT body composition parameters on outcomes and disease severity at hospital presentation of COVID-19 patients, focusing also on the possible mediation of body composition in the relationship between age and death in these patients. Chest CT scans performed at hospital presentation by consecutive COVID-19 patients (02/27/2020-03/13/2020) were retrospectively reviewed to obtain pectoralis muscle density and total, visceral, and intermuscular adipose tissue areas (TAT, VAT, IMAT) at the level of T7-T8 vertebrae. Primary outcomes were: hospitalization, mechanical ventilation (MV) and/or death, death alone. Secondary outcomes were: C-reactive protein (CRP), oxygen saturation (SO2), CT disease extension at hospital presentation. The mediation of body composition in the effect of age on death was explored. Of the 318 patients included in the study (median age 65.7 years, females 37.7%), 205 (64.5%) were hospitalized, 68 (21.4%) needed MV, and 58 (18.2%) died. Increased muscle density was a protective factor while increased TAT, VAT, and IMAT were risk factors for hospitalization and MV/death. All these parameters except TAT had borderline effects on death alone. All parameters were associated with SO2 and extension of lung parenchymal involvement at CT; VAT was associated with CRP. Approximately 3% of the effect of age on death was mediated by decreased muscle density. In conclusion, low muscle quality and ectopic fat accumulation were associated with COVID-19 outcomes, VAT was associated with baseline inflammation. Low muscle quality partly mediated the effect of age on mortality.

The authors confirm the robustness and reproducibility of the eDQE method. As expected, the DR systems performed better than the CR systems due to their superior signal-to-noise transfer characteristics. The results of this study suggest the eDQE method may provide an opportunity to more accurately assess the clinical performance of digital radiographic imaging systems by accounting for factors such as the presence of scatter, use of an antiscatter grid, and magnification and focal spot blurring effects, which are not reflected in conventional DQE measures.

Objective The aims of this study were to develop a multiparametric prognostic model for death in COVID-19 patients and to assess the incremental value of CT disease extension over clinical parameters. Methods Consecutive patients who presented to all five of the emergency rooms of the Reggio Emilia province between February 27 and March 23, 2020, for suspected COVID-19, underwent chest CT, and had a positive swab within 10 days were included in this retrospective study. Age, sex, comorbidities, days from symptom onset, and laboratory data were retrieved from institutional information systems. CT disease extension was visually graded as < 20%, 20–39%, 40–59%, or ≥ 60%. The association between clinical and CT variables with death was estimated with univariable and multivariable Cox proportional hazards models; model performance was assessed using k -fold cross-validation for the area under the ROC curve (cvAUC). Results Of the 866 included patients (median age 59.8, women 39.2%), 93 (10.74%) died. Clinical variables significantly associated with death in multivariable model were age, male sex, HDL cholesterol, dementia, heart failure, vascular diseases, time from symptom onset, neutrophils, LDH, and oxygen saturation level. CT disease extension was also independently associated with death (HR = 7.56, 95% CI = 3.49; 16.38 for ≥ 60% extension). cvAUCs were 0.927 (bootstrap bias-corrected 95% CI = 0.899–0.947) for the clinical model and 0.936 (bootstrap bias-corrected 95% CI = 0.912–0.953) when adding CT extension. Conclusions A prognostic model based on clinical variables is highly accurate in predicting death in COVID-19 patients. Adding CT disease extension to the model scarcely improves its accuracy. Key Points • Early identification of COVID-19 patients at higher risk of disease progression and death is crucial; the role of CT scan in defining prognosis is unclear. • A clinical model based on age, sex, comorbidities, days from symptom onset, and laboratory results was highly accurate in predicting death in COVID-19 patients presenting to the emergency room. • Disease extension assessed with CT was independently associated with death when added to the model but did not produce a valuable increase in accuracy. Supplementary Information The online version contains supplementary material available at 10.1007/s00330-021-07993-9.

Background Laboratory data and computed tomography (CT) have been used during the COVID-19 pandemic, mainly to determine patient prognosis and guide clinical management. The aim of this study was to evaluate the association between CT findings and laboratory data in a cohort of COVID-19 patients. Methods This was an observational cross-sectional study including consecutive patients presenting to the Reggio Emilia (Italy) province emergency rooms for suspected COVID-19 for one month during the outbreak peak, who underwent chest CT scan and laboratory testing at presentation and resulted positive for SARS-CoV-2. Results Included were 866 patients. Total leukocytes, neutrophils, C-reactive protein (CRP), creatinine, AST, ALT and LDH increase with worsening parenchymal involvement; an increase in platelets was appreciable with the highest burden of lung involvement. A decrease in lymphocyte counts paralleled worsening parenchymal extension, along with reduced arterial oxygen partial pressure and saturation. After correcting for parenchymal extension, ground-glass opacities were associated with reduced platelets and increased procalcitonin, consolidation with increased CRP and reduced oxygen saturation. Conclusions Pulmonary lesions induced by SARS-CoV-2 infection were associated with raised inflammatory response, impaired gas exchange and end-organ damage. These data suggest that lung lesions probably exert a central role in COVID-19 pathogenesis and clinical presentation.

8. Novel Coronavirus Pneumonia Emergency Response Epidemiology Team. Vital surveillances: the epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19)-China, 2020. China CDC Weekly. 2020;2: 113-122 [cited 2020 April 24]. http://weekly.chinacdc. cn/en/article/id/e53946e2-c6c4-41e9-9a9b-fea8db1a8f51 9.