Atypical Abnormal Pulmonary Vein Drainage with Atrial Septal Defect: Surgical Treatment

Sinus venosus atrial septal defect (SV‐ASD) usually coexists with partial anomalous pulmonary vein connection (PAPVC). It is a difficult diagnosis in transthoracic echocardiography (TTE) due to eccentric position of defects. We present a rare case of atypical anatomical variation in PAPVC, which was never described before. Two right pulmonary veins drained into superior vena cava, which overrode SV‐ASD and interatrial septum, a third pulmonary vein into the right atrium. Complete diagnosis could not be set after TTE, nor transesophageal echocardiography, whereas angio‐CT was finally conclusive. This diagnostic approach allowed the surgical planning.     

Optimal combination of antiangiogenic therapy for hepatocellular carcinoma

The success of sorafenib in prolonging survival of patients with hepatocellular carcinoma (HCC) makes therapeutic inhibition of angiogenesis a component of treatment for HCC. To enhance therapeutic efficacy, overcome drug resistance and reduce toxicity, combination of antiangiogenic agents with chemotherapy, radiotherapy or other targeted agents were evaluated. Nevertheless, the use of antiangiogenic therapy remains suboptimal regarding dosage, schedule and duration of therapy. The issue is further complicated by combination antiangiogenesis to other cytotoxic or biologic agents. There is no way to determine which patients are most likely respond to a given form of antiangiogenic therapy. Activation of alternative pathways associated with disease progression in patients undergoing antiangiogenic therapy has also been recognized. There is increasing importance in identifying, validating and standardizing potential response biomarkers for antiangiogenesis therapy for HCC patients. In this review, biomarkers for antiangiogenesis therapy including systemic, circulating, tissue and imaging ones are summarized. The strength and deficit of circulating and imaging biomarkers were further demonstrated by a series of studies in HCC patients receiving radiotherapy with or without thalidomide.     

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%.     

Stress Testing Versus CT Angiography in Patients With Diabetes and Suspected Coronary Artery Disease

Background

The optimal noninvasive test (NIT) for patients with diabetes and stable symptoms of coronary artery disease (CAD) is unknown.

How accurate is atherosclerosis imaging by coronary computed tomography angiography?

Invasive coronary plaque imaging such as intravascular ultrasound and optical coherence tomography has been widely used to observe culprit or non-culprit coronary atherosclerosis, as well as optimize stent sizing, apposition and deployment. Coronary computed tomographic angiography (CTA) is non-invasively available to assess coronary artery disease (CAD) and has become an appropriate strategy to evaluate patients with suspected CAD. Given recent technologies, semi-automated plaque software is available to identify coronary plaque stenosis, volume and characteristics and potentially allows to be used for the assessment of more details of plaque information, progression and future risk as a surrogate tool of the invasive imaging modalities. This review article aims to focus on various evidence in coronary plaque imaging by coronary CTA and describes how accurate coronary CTA can classify coronary atherosclerosis.     

针刺京骨穴联合推拿治疗背肌筋膜炎临床研究

目的探讨针刺京骨穴联合推拿治疗背肌筋膜炎的临床疗效。方法将2016年10月—2018年10月收治的背肌筋膜炎患者86例纳入研究,采用随机数字表法分组。对照组43例予以推拿治疗,观察组43例予以针刺京骨穴联合推拿治疗。比较2组患者的治疗总有效率、VAS评分及Oswestry功能障碍指数、痊愈所用时间。结果观察组治疗总有效率为95.3%,而对照组仅为81.4%,差异有统计学意义(P<0.05);2组治疗后VAS评分、Oswestry功能障碍指数均有下降,观察组上述指标低于对照组,差异有统计学意义(P<0.05);观察组痊愈所用时间短于对照组,差异有统计学意义(P<0.05)。结论针刺京骨穴联合推拿治疗背肌筋膜炎的临床疗效突出,可缓解背部疼痛、恢复功能活动,并缩短了愈合时间,提高了生活质量,值得一定的临床推广。