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.

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.

The purpose of this study was to perform a complete evaluation of three pieces of clinical digital mammography equipment. Image quality was assessed by performing physical characterization and contrast-detail (CD) analysis. We considered three different FFDM systems: a computed radiography unit (Fuji "FCR 5000 MA") and two flat-panel units, the indirect conversion a-Si based GE "Senographe 2000D" and the direct conversion a-Si based IMS "Giotto Image MD." The physical characterization was estimated by measuring the MTF, NNPS, and DQE of the detectors with no antiscatter grid and over the clinical range of exposures. The CD analysis was performed using a CDMAM 3.4 phantom and custom software designed for automatic computation of the contrast-detail curves. The physical characterization of the three digital systems confirms the excellent MTF properties of the direct conversion flat-panel detector (FPD). We performed a relative standard deviation (RSD) analysis, for investigating the different components of the noise presented by the three systems. It turned out that the two FPDs show a significant additive component, whereas for the CR system the statistical noise is dominant. The multiplicative factor is a minor constituent for all the systems. The two FPDs demonstrate better DQE, with respect to the CR system, for exposures higher than 70 microGy. The CD analysis indicated that the three systems are not statistically different for detail objects with a diameter greater than 0.3 mm. However, the IMS system showed a statistically significant different response for details smaller than 0.3 mm. In this case, the poor response of the a-Se detector could be attributed to its high-frequency noise characteristics, since its MTF, NEQ, and DQE are not inferior to those of the other systems. The CD results were independent of exposure level, within the investigated clinical range. We observed slight variations in the CD results, due to the changes in the visualization parameters (window/level and magnification factor). This suggests that radiologists would benefit from viewing images using varied window/level and magnification.

Reggio Emilia hospital installed Picture Archiving and Communications Systems (PACS) as the final step towards a completely digital clinical environment completing the HIS/EMR and 1,400 web/terminals for patient information access. Financial benefits throughout the hospital were assessed upfront and measured periodically. Key indicators (radiology exam turnaround time, number of radiology procedures performed, inpatients length of stay before and after the PACS implementation, etc.) were analyzed and values were statistically tested to assess workflow and productivity improvements. The hospital went “filmless” in 28 weeks. Between the half of 2004 and the respective period in 2003, overall Radiology Department productivity increased by 12%, TAT improved by more than 60%. Timelier patient care resulted in decreased lengths of stay. Neurology alone experienced a 12% improvement in average patient stay. To quantify the impact of PACS on the average hospital stays and the expected productivity benefits to inpatient productivity were used a “high level” and a “detailed” business model. Annual financial upsides have exceeded $1.9 millions/year. A well-planned PACS deployment simplifies imaging workflow and improves patient care throughout the hospital while delivering substantial financial benefits. Staff buy-in was the key in this process and on-going training and process monitoring are a must.

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.

During a tender we evaluated the image performance of three commercially available active matrix flat panel imagers (AMFPI) for general radiography, one based on direct detection method (Se photoconductor) the other two on indirect detection method (CsI phosphor). Basic image quality parameters (MTF, NNPS, DQE) were evaluated with particular attention to dose and energy dependence. As it is known, presampling modulation transfer function (MTF) of selenium based detector is very high (at 70 kV, 2 cycles/mm, 2.5 microGy, about 0.80). Indirect detection panels exhibit a comparable (lower) resolution (at 70 kV, 2 cycles/mm, 2.5 microGy, MTF is about 0.34 for both the systems analyzed) and a more pronounced energy and dose dependence could also be noted in one of them. As a consequence of the very high resolution, the normalized noise power spectrum (NNPS) of the direct system is substantially flat, very similar to a white noise. Considering that the sensitive layer of all detectors is the same (0.5 mm), the relatively higher NNPS values are related to selenium absorption properties (lower Z respect to CsI:Tl) and detector inherent noise. NNPSs of the other systems, at low frequencies, are comparable but the frequency dependence is significantly different. At 70 kV, 2.5 microGy, 0.5 cycles/mm detective quantum efficiency (DQE) is about 0.35 for the direct detection system, and about the same (0.6) for the indirect ones. The combined effect of additive and multiplicative noise components makes DQE dependence on dose not monotonic. DQE present a maximum for an intermediate exposure. This complex behavior may be useful to characterize the systems in terms of the monodimensional integral over the frequency of DQE (IDQE). Both visual contrast-detail experiment and the direct evaluation of the signal-to-noise ratio confirmed, at least in a qualitative way, the system performances predicted by IDQE.

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.