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.     

Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.     

Endoscopic ultrasonography and small‐bowel endoscopy: Present and future

Over the last decade, impressive technological advances have occurred in ultrasonography and small‐bowel endoscopy. Nowadays, endoscopic ultrasonography is an essential diagnostic tool and a therapeutic weapon for pancreatobiliary disorders. Capsule endoscopy and device‐assisted enteroscopy have quickly become the reference standard for the diagnosis of small‐bowel luminal diseases, thereby leading to radical changes in diagnostic and therapeutic pathways. We herein provide an up‐to‐date overview of the latest advances in endoscopic ultrasonography and small‐bowel endoscopy, focusing on the emerging paradigms and technological innovations that might improve clinical practice in the near future.     

经食管实时三维超声心动图评价房性心律失常对二尖瓣结构和功能的影响

目的:应用经食管实时三维超声心动图(RT-3D-TEE)技术,探讨房性心律失常对二尖瓣结构和功能的影响.方法:选取2018年6月~2019年6月本院收治的房性心律失常拟行射频消融的患者49例纳入观察组,另外选取21例正常窦性心律者作为对照组,所有患者均行经胸超声心电图(TTE)和经食管实时三维超声心动图(RT-3D-TEE)检查,将两组患者的瓣环投影面积(A2D)、瓣环周长(C3D)、瓣环高度(H)、瓣环前后径(DAP)、瓣环前外侧至后内侧直径(DAIPm)、左室射血分数(LVEF)、左心房前后径(Lad)等参数进行比较,并分别计算对合面积和对合指数,之后采取二项Logistic回归分析或逐步线性回归对各参数及临床因素与对合指数的相关性进行分析.结果:两组患者在LVEF和对合面积方面的比较无明显差异(P>0.05),在A2D、C3D、H、DA、PDAIPm、Lad方面的比较,房性心律失常组患者明显高于正常窦性心律组患者(P<0.05),且观察组患者的对合指数明显降低(P<0.05).将49例观察组患者以不同心律失常类型分为持续性房颤、阵发性房颤、房扑、混合型房性心律失常4个亚组,采用单因素方差分析,发现在LVEF、C3D、Lad、对合指数方面的比较,各亚组间无明显差异(P>0.05).采用二项Logistic回归分析发现,女性是导致对合指数低的危险因素,另外对合指数较低、房性心律失常是导致二尖瓣返流的重要因素.结论:房性心律失常对患者二尖瓣的A2D、C3D、H、DA、PDAIPm、Lad等都会造成较大影响,从而降低对合指数,影响二尖瓣的正常功能,导致二尖瓣返流的发生.     

新生儿肺部超声在早产儿肺部感染评价中的价值

目的 探讨新生儿肺部超声在早产儿肺部感染评价中的价值。 方法 选取肺部感染早产儿80例为观察组，无肺部感染的早产儿80例为对照组，均给予新生儿肺部超声检查，比较2组肺部超声评分、氧合指数、呼吸指数，比较观察组不同病情、预后患儿肺部超声评分、氧合指数、呼吸指数,分析肺部超声评分和氧合指数、呼吸指数的相关性。 结果 观察组肺部超声评分、氧合指数低于对照组，呼吸指数高于对照组，差异有统计学意义（P＜0.05）。观察组极危重患儿肺部超声评分、氧合指数低于危重和非危重患儿，呼吸指数高于危重和非危重患儿，危重患儿肺部超声评分、氧合指数低于非危重患儿，呼吸指数高于非危重患儿，差异有统计学意义（P＜0.05）。肺部超声评分与呼吸指数呈负相关（r=-0.455，P＜0.05），与氧合指数呈正相关（r=0.470，P＜0.05）。观察组死亡患儿肺部超声评分、氧合指数低于存活患儿，呼吸指数高于存活患儿，差异有统计学意义（P＜0.05）。肺部超声评分预测患儿预后的ROC曲线下面积为0.874，高于呼吸指数和氧合指数（P＜0.05），其截断值为20分时，敏感度和特异度为88.50%和75.00%。 结论 新生儿肺部超声在早产儿肺部感染评价中有较好的效果，值得临床使用。     

Impact and Predictors of Noncircular Left Ventricular Outflow Tract Shapes on Estimating Aortic Stenosis Severity by Means of Continuity Equations

Determining aortic stenosis (AS) severity is clinically important. Calculating aortic valve (AV) area by means of the continuity equation assumes a circular left ventricular outflow tract (LVOT). The full impact of this assumption in calculating AV area is unknown. Predictors of noncircular LVOT shape in patients with AS are undefined.In 109 adult patients with AS who underwent multiplanar transesophageal echocardiography, we calculated AV area by means of the standard continuity method and by a modified method involving planimetric LVOT area.We found 54 circular, 37 horizontal-oval, 8 vertical-oval, and 10 irregular LVOTs. Area derived by direct planimetry correlated better with the modified than the standard continuity method (r=0.89 vs r=0.85; both P=0.0001). Valve areas of patients with mild, moderate, or severe AS by planimetry were more often mischaracterized with use of the standard than modified method (29 vs 18; P <0.0001). Horizontal-oval AV area derived by planimetry (1.28 ± 0.55 cm²) was underestimated by the standard method (1.05 ± 0.47 cm²; P=0.001), but not by the modified method. Congenital AV morphology and low cardiac index were the only multivariate predictors of horizontal-oval shape. Low cardiac index was the only predictor of noncircular shape.More than half our patients with AS had noncircular LVOTs. Using the modified method reduces mischaracterizations of AS severity. Congenital AV morphology and low cardiac index predict horizontal-oval or noncircular shape. These data suggest the value of direct LVOT measurement to calculate AS severity in patients who have congenital AV or a low cardiac index.