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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.
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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.
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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.
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BACKGROUND: Virtual monoenergetic (VM) dual-energy computed tomography (DE-CT) enables grey-to-white matter contrast-to-noise ratio optimization, potentially increasing ischaemic brain oedema visibility. The aim of this study was to compare the diagnostic accuracy of VM and standard DE-CT reconstructions for early stroke detection. METHODS: Consecutive patients with non-contrast DE-CT of the brain scanned within 12 h of stroke symptom onset were prospectively included in the study. Patients with other significant brain pathology were excluded. Two radiologists jointly evaluated standard and VM reconstructions (from 40 to 190 keV at increments of 10 keV) for early stroke signs on a four-point Likert scale: (a) stroke definitely present, (b) stroke probably present, (c) probably no stroke, and (d) definitely no stroke. Follow-up imaging and clinical data served as the standard of reference. Diagnostic accuracy was evaluated by receiver operating characteristic analysis. RESULTS: Stroke incidence among 184 patients was 76%. In 64 patients follow-up imaging served as the standard of reference: ischemic brain oedema detection was significantly more accurate on VM reconstructions at 80 keV compared with standard DE-CT reconstructions (area under the curve (AUC) = 0.821 vs. AUC = 0.672, p = 0.002). The difference was most prominent within the first 3 h after symptom onset (at 11%, AUC = 0.819 vs. AUC = 0.709, p = 0.17) and in patients with National Institutes of Health Stroke Scale above 16 (at 37.5%, AUC = 1 vs. AUC = 0.625, p = 0.14). CONCLUSION: VM DE-CT reconstructions at 80 keV appear to be the optimal non-contrast CT technique for diagnosing early ischaemic stroke, particularly within the first 3 h after symptom onset and in severely ill patients.