Contrast-enhanced mammography (CEM) is a relatively new imaging technique that allows morphologic, anatomic and functional imaging of the breast. The aim of our study was to validate contrast-enhanced mammography (CEM) compared to mammography (MMG) and digital breast tomosynthesis (DBT) in daily clinical practice. This retrospective study included 316 consecutive patients who underwent MMG, DBT and CEM at the Centre for Prevention and Diagnosis of Chronic Diseases of Primorsko-goranska County. Two breast radiologists independently analyzed the image data, without available anamnestic information and without the possibility of comparison with previous images, to determine the presence of suspicious lesions and their morphological features according to the established criteria of the Breast Imaging Reporting and Data System (BI-RADS) lexicon. The diagnostic value of MMG, DBT and CEM was assessed by ROC analysis. The interobserver agreement was excellent. CEM showed higher diagnostic accuracy in terms of sensitivity and specificity compared to MMG and DBT, the reporting time for CEM was significantly shorter, and CEM findings resulted in a significantly lower proportion of equivocal findings (BI-RADS 0), suggesting fewer additional procedures. In conclusion, CEM achieves high diagnostic accuracy while maintaining simplicity, reproducibility and applicability in complex clinical settings.

Background: This study aims to evaluate the impact of various weighting factors (WFs) on the quality of weighted average (WA) dual-energy computed tomography (DECT) non-contrast brain images and to determine the optimal WF value. Because they simulate standard CT images, 0.4-WA reconstructions are routinely used. Methods: In the initial phase of the research, quantitative and qualitative analyses of WA DECT images of an anthropomorphic head phantom, utilizing WFs ranging from 0 to 1 in 0.1 increments, were conducted. Based on the phantom study findings, WFs of 0.4, 0.6, and 0.8 were chosen for patient analyses, which were identically carried out on 85 patients who underwent non-contrast head DECT. Three radiologists performed subjective phantom and patient analyses. Results: Quantitative phantom image analysis revealed the best gray-to-white matter contrast-to-noise ratio (CNR) at the highest WFs and minimal noise artifacts at the lowest WF values. However, the WA reconstructions were deemed non-diagnostic by all three readers. Two readers found 0.6-WA patient reconstructions significantly superior to 0.4-WA images (p < 0.001), while reader 1 found them to be equally good (p = 0.871). All readers agreed that 0.8-WA images exhibited the lowest image quality. Conclusions: In conclusion, 0.6-WA reconstructions demonstrated superior image quality over 0.4-WA and are recommended for routine non-contrast brain DECT.

The aim of our study was to establish and compare the diagnostic accuracy and clinical applicability of published chest CT severity scoring systems used for COVID-19 pneumonia assessment and to propose the most efficient CT scoring system with the highest diagnostic performance and the most accurate prediction of disease severity. This retrospective study included 218 patients with PCR-confirmed SARS-CoV-2 infection and chest CT. Two radiologists blindly evaluated CT scans and calculated nine different CT severity scores (CT SSs). The diagnostic validity of CT SSs was tested by ROC analysis. Interobserver agreement was excellent (intraclass correlation coefficient: 0.982–0.995). The predominance of either consolidations or a combination of consolidations and ground-glass opacities (GGOs) was a predictor of more severe disease (both p < 0.005), while GGO prevalence alone was not. Correlation between all CT SSs was high, ranging from 0.848 to 0.971. CT SS 30 had the highest diagnostic accuracy (AUC = 0.805) in discriminating mild from severe COVID-19 disease compared to all the other proposed scoring systems (AUC range 0.755–0.788). In conclusion, CT SS 30 achieved the highest diagnostic accuracy in predicting the severity of COVID-19 disease while maintaining simplicity, reproducibility, and applicability in complex clinical settings.

Tomosynthesis-Guided Vacuum-Assisted Excision of B3 Breast Lesions: Reducing Overtreatment Without Compromising Safety - European Journal of Breast Health

Background: Negative CCTA can effectively exclude significant CAD, eliminating the need for further noninvasive or invasive testing. However, in the presence of severe CAD, the accuracy declines, thus necessitating additional testing. The aim of our study was to evaluate the diagnostic performance of noninvasive cFFR derived from CCTA, compared to ICA in detecting hemodynamically significant stenoses in participants with high CAC scores (>400). Methods: This study included 37 participants suspected of having CAD who underwent CCTA and ICA. CAC was calculated and cFFR analyses were performed using an on-site machine learning-based algorithm. Diagnostic accuracy parameters of CCTA and cFFR were calculated on a per-vessel level. Results: The median total CAC score was 870, with an IQR of 642–1370. Regarding CCTA, sensitivity and specificity for RCA were 60% and 67% with an AUC of 0.639; a LAD of 87% and 50% with an AUC of 0.688; an LCX of 33% and 90% with an AUC of 0.617, respectively. Regarding cFFR, sensitivity and specificity for RCA were 60% and 61% with an AUC of 0.606; a LAD of 75% and 54% with an AUC of 0.647; an LCX of 50% and 77% with an AUC of 0.647. No significant differences between AUCs of coronary CTA and cFFR for each vessel were found. Conclusions: Our results showed poor diagnostic accuracy of CCTA and cFFR in determining significant ischemia-related lesions in participants with high CAC scores when compared to ICA. Based on our results and study limitations we cannot exclude cFFR as a method for determining significant stenoses in people with high CAC. A key issue is accurate and detailed lumen segmentation based on good-quality CCTA images.

Background: Accurate delineation of ductal carcinoma in situ (DCIS) remains a key challenge in surgical planning. Although contrast-enhanced mammography (CEM) improves lesion detection, its clinical role in informing individualized surgical strategies remains unclear. This study evaluated the impact of CEM on preoperative assessment and surgical planning, with particular emphasis on whether its effect varies across patient subgroups. Methods: This multicentre pilot observational cohort study included 102 patients: 51 prospective patients undergoing preoperative CEM and mammography (MMG) and 51 retrospective controls assessed with MMG alone. Imaging-derived lesion size and planned resection volume were compared with pathological size using correlation analysis, intraclass correlation coefficient (ICC), and Bland–Altman methods. Surgical outcomes were assessed, and subgroup analyses explored differences according to CEM enhancement status. Results: CEM showed improved correlation with pathological DCIS size compared with MMG (ρ = 0.54 vs. 0.37), with the strongest agreement in CEM-positive lesions (ρ = 0.67; ICC 0.745). However, its clinical impact was not uniform. At the population level, CEM did not significantly change planned resection volume or surgical thresholds. In contrast, in CEM-positive patients, CEM was associated with larger planned resections, proportional to pathological tumor burden. Reoperation rates were lower in the CEM cohort (5.9% vs. 17.6%), without statistical significance, and margin status was comparable. Conclusions: The impact of CEM on surgical planning in DCIS is heterogeneous and largely confined to patients with enhancing lesions. These findings suggest that the value of CEM may lie in its selective use, where it can refine assessment of disease extent in specific subgroups rather than in routine application. Further studies incorporating predictive approaches are needed to support risk-adapted imaging strategies.