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Objectives To assess the value of myocardial extracellular volume (ECV) derived from contrast-enhanced chest computed tomography (CT) for longitudinal evaluation of cardiotoxicity in patients with breast cancer (BC) treated with anthracycline (AC). Materials and methods A total of 1151 patients with BC treated with anthracyclines, who underwent at least baseline, and first follow-up contrast-enhanced chest CT were evaluated. ECV and left ventricular ejection fraction (LVEF) were measured before (ECV0, LVEF0), during ((ECV1, LVEF1) and (ECV2, LVEF2)), and after (ECV3, LVEF3) AC treatment. ECV values were evaluated at the middle of left ventricular septum on venous phase images. Cancer therapy-related cardiac dysfunction (CTRCD) was recorded. Results Mean baseline LVEF values were 65.85% ± 2.72% and 102 patients developed CTRCD. The mean ECV0 was 26.76% ± 3.03% (N0 = 1151). ECV1, ECV2, and ECV3 (median interval: 61 (IQR, 46–75), 180 (IQR, 170–190), 350 (IQR, 341–360) days from baseline) were 31.32% ± 3.10%, 29.60% ± 3.24%, and 32.05% ± 3.58% (N1 = 1151, N2 = 841, N3 = 511). ECV1, ECV2, and ECV3 were significantly higher than ECV0 (p < 0.001). ECV0 and ECV1 showed no difference between CTRCD (+) and CTRCD (−) group (p1 = 0.150; p2 = 0.216). However, ECV2 and ECV3 showed significant differences between the two groups (p3 < 0.001; p4 < 0.001). Conclusion CT-derived ECV is a potential biomarker for dynamic monitoring AC cardiotoxicity in patients with BC.

Background: Head and neck squamous cell carcinoma (HNSCC) patients with a high tumor grade, lymphovascular invasion (LVI), or perineural invasion (PNI) tend to demonstrate a poor prognosis in clinical series. Thus, the identification of histopathological features, including tumor grade, LVI, and PNI, before treatment could be used to stratify the prognosis of patients with HNSCC. This study aimed to assess whether quantitative parameters derived from pretreatment dual-energy computed tomography (DECT) can predict the histopathological features of patients with HNSCC.Methods: In this study, 72 consecutive patients with pathologically confirmed HNSCC were enrolled and underwent dual-phase (noncontrast-enhanced phase and contrast-enhanced phase) DECT examinations.Normalized iodine concentration (NIC), the slope of the spectral Hounsfield unit curve (λ HU ), and normalized effective atomic number (NZ eff ) were calculated. The attenuation values on 40-140 keV noiseoptimized virtual monoenergetic images [VMIs (+)] in the contrast-enhanced phase were recorded. The diagnostic performance of the quantitative parameters for predicting histopathological features, including tumor grade, LVI, and PNI, was assessed by receiver operating characteristic curves. Results:The NIC, λ HU , NZ eff , and attenuation value on the VMIs (+) at 40 keV (A 40 ) in the grade III group, LVI-positive group, and PNI-positive group were significantly higher than those in the grade I and II groups, the LVI-negative group, and the PNI-negative group (all P values <0.05). A multivariate logistic regression model combining these 4 quantitative parameters improved the diagnostic performance of the model in predicting tumor grade, LVI, and PNI (areas under the curve: 0.969, 0.944, and 0.931, respectively).Conclusions: Quantitative parameters derived from pretreatment DECT, including NIC, λ HU , NZ eff , and A 4,0 were found to be imaging markers for predicting the histopathological characteristics of HNSCC.Combining all these characteristics improved the predictive performance of the model.