Myocardial extracellular volume derived from contrast-enhanced chest computed tomography for longitudinal evaluation of cardiotoxicity in patients with breast cancer treated with anthracyclines.

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.

Longitudinal pericardial adipose tissue changes in patients with breast cancer receiving anthracycline-based chemotherapy: a retrospective cohort study.

Background: Pericardial adipose tissue (PAT) has been associated with adverse cardiac events. In this study, we evaluated changes of PAT in patients with breast cancer during and after anthracycline-based chemotherapy and explored the clinical variables associated with increases in PAT volume at the completion of chemotherapy. Methods: A total of 278 breast cancer patients who were receiving anthracycline-based chemotherapy were retrospectively enrolled. Their PAT volumes were measured using non-contrast chest computed tomography (CT) images from a dedicated workstation. We compared these volumes to their measurements at baseline, during different chemotherapy cycles, at and after chemotherapy completion. We identified the clinical variables associated with increases in PAT volume at chemotherapy completion using logistic regression analyses. Results: At the completion of chemotherapy, PAT volumes were shown to have increased compared to baseline measurements (87.67±45.09 vs. 104.25±47.74 cm3; P=0.00). After 4, 6, and 8 chemotherapy cycles, PAT volumes increased from the baseline measurement by 9.48% [95% confidence interval (CI): -2.30% to 21.27%], 14.75% (95% CI: 4.68% to 24.82%), and 20.02% (95% CI: 11.38% to 28.66%), respectively. Compared to volumes measured at chemotherapy completion (104.25±47.74 cm3), PAT volumes at 6 and 12 months after chemotherapy completion were 105.23±49.27 and 107.56±46.34 cm3, respectively. The differences between chemotherapy completion and follow-up PAT volumes were not statistically significant. A variable associated with an increase in PAT from baseline to chemotherapy completion was the number of chemotherapy cycles (8 vs. 4) [odds ratio (OR) =3.850; 95% CI: 1.751 to 8.488]. Conclusions: Patients with breast cancer who undergo anthracycline-based chemotherapy can experience unfavorable PAT volume increases, which are maintained after the completion of treatment. Patients at risk of increases in PAT volume at chemotherapy completion can be identified based on clinical risk factors and targeted for interventions.

Novel physical performance-based models for activities of daily living disability prediction among Chinese older community population: a nationally representative survey in China.

BACKGROUND: Physical performances including upper and lower limb functions have predictive roles in activities of daily living (ADL) disability, but they have rarely been incorporated into prediction models. This study primarily aimed to develop and validate novel physical performance-based models for ADL disability among Chinese older adults. Comparisons of predictive performance across multiple models were performed, and model simplification was further explored. METHODS: Data were obtained from the China Health and Retirement Longitudinal Study in the 2011 and 2015 waves, containing 2192 older adults over 60 years old. Our models were constructed by logistic regression analysis, using a backward stepwise selection. Model performance was internally validated by discrimination, calibration, and clinical utility. Integrated Discrimination Improvement (IDI) and Net Reclassification Improvement (NRI) were used to assess the incremental benefit of the extended models. Moreover, nomograms were built for visualization. RESULTS: We selected gender, age, smoking, self-report health condition, BMI, depressive symptoms, and cognitive function into the fundamental model (Model 1). Based on Model 1, five novel prediction models were constructed by adding handgrip strength (Model 2), Short Physical Performance Battery (SPPB) (Model 3), gait speed (Model 4), handgrip strength plus SPPB (Model 5), and handgrip strength plus gait speed (Model 6), respectively. Significant improvement in predictive values were observed for all five novel models compared with Model 1 (C-index = 0.693). The lower limb model (Model 3 SPPB model: C-index = 0.731) may play a key role in the prediction of ADL disability, reflecting a comparable predictive value to the comprehensive models combining both upper and lower limbs (Model 5 handgrip strength + SPPB model: C-index = 0.732). When we simplified the lower limb models by replacing SPPB with gait speed, the predictive values attenuated slightly (C-index: Model 3 vs Model 4: 0.731 vs 0.714; Model 5 vs Model 6: 0.732 vs 0.718), but still better than the upper limb model (Model 2 handgrip strength model: C-index = 0.701). CONCLUSIONS: Physical performance-based models, especially lower limb model, provided improved prediction for ADL disability among Chinese older adults, which may help guide the targeted intervention.

Using quantitative parameters derived from pretreatment dual-energy computed tomography to predict histopathologic features in head and neck squamous cell carcinoma.

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 (λHU), and normalized effective atomic number (NZeff) were calculated. The attenuation values on 40-140 keV noise-optimized 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, λHU, NZeff, and attenuation value on the VMIs (+) at 40 keV (A40) 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, λHU, NZeff, and A4,0 were found to be imaging markers for predicting the histopathological characteristics of HNSCC. Combining all these characteristics improved the predictive performance of the model.

Simultaneous multi-slice readout-segmentation of long variable echo-trains for accelerated diffusion-weighted imaging of nasopharyngeal carcinoma: A feasibility and optimization study.

OBJECTIVES: We aimed to evaluate the feasibility of simultaneous multi-slice readout segmentation of long variable echo-trains (SMS-RESOLVE) for diffusion-weighted imaging (DWI) of nasopharyngeal carcinoma (NPC) and determine the optimal acceleration factor of SMS-RESOLVE DWI compared with conventional RESOLVE DWI. MATERIALS AND METHODS: One hundred and five patients with histologically confirmed NPC were enrolled. DWIs including conventional RESOLVE DWI, SMS-RESOLVE DWI with acceleration factors of 2 and 3 (2 × SMS-RESOLVE and 3 × SMS-RESOLVE) were acquired at b-values of 0 and 800 s/mm2. The subjective image quality, including overall image quality, lesion conspicuity, and lesion distortion scores, and objective image quality, including signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and contrast in these three protocols, were assessed and compared. The apparent diffusion coefficients (ADCs) of the primary tumor and right masseter muscle and normalized ADCs in the three protocols were measured and compared. RESULTS: The 2 × SMS-RESOLVE provided comparable image quality and ADCs with a 48.3% reduction in scan time compared with conventional RESOLVE DWI. The 3 × SMS-RESOLVE showed significantly poorer image quality and the highest ADCs with a 56.9% reduction in scan times compared with conventional RESOLVE DWI. CONCLUSION: The SMS-RESOLVE DWI with an acceleration factor of 2 yielded the best compromise between image quality and scan time reduction and could be an alternative to conventional RESOLVE DWI for nasopharyngeal carcinoma.

A web-based dynamic Nomogram for predicting instrumental activities of daily living disability in older adults: a nationally representative survey in China.

BACKGROUND: Instrumental Activities of Daily Living (IADL) disability is a common health burden in aging populations. The identification of high-risk individuals is essential for timely targeted interventions. Although predictors for IADL disability have been well described, studies constructing prediction tools for IADL disability among older adults were not adequately explored. Our study aims to develop and validate a web-based dynamic nomogram for individualized IADL disability prediction in older adults. METHODS: Data were obtained from the China Health and Retirement Longitudinal Study (CHARLS). We included 4791 respondents aged 60 years and over, without IADL disability at baseline in the 2011 to 2013 cohort (training cohort) and 371 respondents in the 2013 to 2015 cohort (validation cohort). Here, we defined IADL disability as needing any help in any items of the Lawton and Brody's scale. A web-based dynamic nomogram was built based on a logistic regression model in the training cohort. We validated the nomogram internally with 1000 bootstrap resamples and externally in the validation cohort. The discrimination and calibration ability of the nomogram was assessed using the concordance index (C-index) and calibration plots, respectively. RESULTS: The nomogram incorporated ten predictors, including age, education level, social activity frequency, drinking frequency, smoking frequency, comorbidity condition, self-report health condition, gait speed, cognitive function, and depressive symptoms. The C-index values in the training and validation cohort were 0.715 (bootstrap-corrected C-index = 0.702) and 0.737, respectively. The internal and external calibration plots for predictions of IADL disability were in excellent agreement. An online web server was built ( https://lilizhang.shinyapps.io/DynNomapp/ ) to facilitate the use of the nomogram. CONCLUSIONS: We developed a dynamic nomogram to evaluate the risk of IADL disability precisely and expediently. The application of this nomogram would be helpful for health care physicians in decision-making.

Optimization of alkaline extraction and bioactivities of polysaccharides from rhizome of Polygonatum odoratum.

The present study is to explore the optimal extraction parameters, antioxidant activity, and antimicrobial activity of alkaline soluble polysaccharides from rhizome of Polygonatum odoratum. The optimal extraction parameters were determined as the following: NaOH concentration (A) 0.3 M, temperature (B) 80 °C, ratio of NaOH to solid (C) 10-fold, and extraction time (D) 4 h, in which ratio of NaOH to solid was a key factor. The order of the factors was ratio of NaOH to solid (fold, C) > extraction temperature (°C, B) > NaOH concentration (M, A) > extraction time (h, D). The monosaccharide compositions of polysaccharides from P. odoratum were rhamnose, mannose, xylose, and arabinose with the molecular ratio of 31.78, 31.89, 11.11, and 1.00, respectively. The reducing power, the 1, 1-diphenyl-2-picryl-hydrazil (DPPH) radical scavenging rate, the hydroxyl radicals scavenging rate, and the inhibition rate to polyunsaturated fatty acid (PUFA) peroxidation of the alkaline soluble polysaccharides from P. odoratum at 1 mg/mL were 9.81%, 52.84%, 19.22%, and 19.42% of ascorbic acid at the same concentration, respectively. They also showed antimicrobial activity against pathogenic bacteria Staphylococcus aureus, Pseudomonas aeruginosa, Bacillus subtilis, and Escherichia coli.