An ultrasonographic monitoring of skin condition in patients receiving radiotherapy for head and neck cancers

Radiodermatitis is one of the commonest side effects of radiotherapy. They are usually assessed by semi‐quantitative clinical scores, which are not validated and may be subject to inter‐observer variability. A few previous studies suggested that high‐frequency ultrasonography (HF‐USG) is useful in the assessment of the acute phase of radiation dermatitis in breast cancer patients. (a) To monitor skin changes by HF‐USG during the course of radiotherapy due to head and neck cancers, and (b) to determine whether there is any connection between skin sonograms and the skin scoring criteria. This prospective, observational study includes patients diagnosed with head and neck cancers, treated with radiotherapy or concomitant chemoradiation. The final analysis includes six patients. In every patient, the HF‐USG as well as dermatological assessment (target lesion score—TLS and CACE v. 4.0) were performed 4×: before, in the middle, day after, and 3 months after radiotherapy. There were significant differences between non‐irradiated skin thickness and thickness of skin with clinically obvious radiodermatitis (TLS grade 1‐4; P < .0001), as well as between irradiated, unchanged skin thickness (TLS grade 0) and thickness of skin with clinically obvious radiodermatitis (TLS grade 1‐4; P = .0002). There was no significant difference between non‐irradiated and irradiated, unchanged skin thickness (TLS grade 0; P = .9318). In four patients, we demonstrated subepidermal low echogenic band (SLEB). HF‐USG can be useful tool to noninvasive and objective assessment of skin changes during radiotherapy.     

论当前疾病预防控制体系面临的主要问题

对当前的疾病预防控制体系和机构面临的体系不健全、政府投入不充分、事业发展不平衡、人才缺失和能力不足、缺乏系统的理论指导、体系的碎片化严重、与社会经济发展的战略衔接不力、机构内部内生动力和活力不足以及体系治理能力不足等问题做了讨论分析,以期进一步分析在健康中国战略和事业单位机构改革等宏观环境变化所带来的机遇以及疾控体系的发展策略和具体措施,促进疾病预防控制事业在改革中谋发展。     

Radiomics model based on preoperative gadoxetic acid-enhanced MRI for predicting liver failure

BACKGROUND Postoperative liver failure is the most severe complication in cirrhotic patients with hepatocellular carcinoma(HCC) after major hepatectomy. Current available clinical indexes predicting postoperative residual liver function are not sufficiently accurate.AIM To determine a radiomics model based on preoperative gadoxetic acid-enhanced magnetic resonance imaging for predicting liver failure in cirrhotic patients with HCC after major hepatectomy.METHODS For this retrospective study, a radiomics-based model was developed based on preoperative hepatobiliary phase gadoxetic acid-enhanced magnetic resonance images in 101 patients with HCC between June 2012 and June 2018. Sixty-one radiomic features were extracted from hepatobiliary phase images and selected by the least absolute shrinkage and selection operator method to construct a radiomics signature. A clinical prediction model, and radiomics-based model incorporating significant clinical indexes and radiomics signature were built using multivariable logistic regression analysis. The integrated radiomics-based model was presented as a radiomics nomogram. The performances of clinical prediction model, radiomics signature, and radiomics-based model for predicting post-operative liver failure were determined using receiver operating characteristics curve, calibration curve, and decision curve analyses.RESULTS Five radiomics features from hepatobiliary phase images were selected to construct the radiomics signature. The clinical prediction model, radiomics signature, and radiomics-based model incorporating indocyanine green clearance rate at 15 min and radiomics signature showed favorable performance for predicting postoperative liver failure(area under the curve: 0.809-0.894). The radiomics-based model achieved the highest performance for predicting liver failure(area under the curve: 0.894; 95%CI: 0.823-0.964). The integrated discrimination improvement analysis showed a significant improvement in the accuracy of liver failure prediction when radiomics signature was added to the clinical prediction model(integrated discrimination improvement = 0.117, P =0.002). The calibration curve and an insignificant Hosmer-Lemeshow test statistic(P = 0.841) demonstrated good calibration of the radiomics-based model. The decision curve analysis showed that patients would benefit more from a radiomics-based prediction model than from a clinical prediction model and radiomics signature alone.CONCLUSION A radiomics-based model of preoperative gadoxetic acid–enhanced MRI can be used to predict liver failure in cirrhotic patients with HCC after major hepatectomy.     

Buscando o motivo da instabilidade hemodinâmica: relato de caso sobre o papel do ultrassom intraoperatório

Background and objectives

A prompt and effective management of trauma patient is necessary. The aim of this case report is to highlight the importance of intraoperative echocardiography as a useful tool in patients suffering from refractory hemodynamic instability no otherwise explained.