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%.     

Development of a Simulation-Based Mastery Learning Curriculum for Breaking Bad News

Introduction

Physician communication impacts patient outcomes. However, communication skills, especially around difficult conversations, remain suboptimal, and there is no clear way to determine the validity of entrustment decisions. The aims of this study were to 1) describe the development of a simulation-based mastery learning (SBML) curriculum for breaking bad news (BBN) conversation skills and 2) set a defensible minimum passing standard (MPS) to ensure uniform skill acquisition among learners.

Quality improvement training for burn care in low-and middle-income countries: A pilot course for nurses

BackgroundThere is an urgent need to empower practitioners to undertake quality improvement (QI) projects in burn services in low-middle income countries (LMICs). We piloted a course aimed to equip nurses working in these environments with the knowledge and skills to undertake such projects.MethodsEight nurses from five burns services across Malawi and Ethiopia took part in this pilot course, which was evaluated using a range of methods, including interviews and focus group discussions.ResultsCourse evaluations reported that interactive activities were successful in supporting participants to devise QI projects. Appropriate online platforms were integral to creating a community of practice and maintaining engagement. Facilitators to a successful QI project were active individuals, supportive leadership, collaboration, effective knowledge sharing and demonstrable advantages of any proposed change. Barriers included: staff attitudes, poor leadership, negative culture towards training, resource limitations, staff rotation and poor access to information to guide practice.ConclusionsThe course demonstrated that by bringing nurses together, through interactive teaching and online forums, a supportive community of practice can be created. Future work will include investigating ways to scale up access to the course so staff can be supported to initiate and lead quality improvement in LMIC burn services.     

Brain impedance variation of directional leads implanted in subthalamic nuclei of Parkinsonian patients

ObjectiveConventional deep brain stimulation (DBS) systems with ring-shaped leads generate spherical electrical fields. In contrast, novel directional leads use segmented electrodes. Aim of this study was to quantify the impedance variations over time in subjects with the directional Cartesia-Boston® system.MethodsImpedance records, programming settings, and clinical data of 11 consecutive Parkinsonian patients implanted with DBS directional leads in two Italian centers (Udine and Vicenza) were retrospectively evaluated. Data were collected before starting stimulation (in the operating room and at days 5 and 40) and after switching stimulation on at the successive follow-up visits (1, 6 and 12 months).ResultsDirectional leads have significantly higher impedance than ring leads. Stimulated contacts had always lower impedance compared to non-stimulated contacts. Before DBS-on, all contacts had higher impedance in the operating room, with an initial decrease five days post-surgery and a subsequent increase at day 40, more evident for directional contacts. The impedance of directional leads increased post-implantation at 1 and 6 months with a plateau at 12 months.ConclusionsThere was a significant difference between the directional and ring leads at baseline (before activation of DBS) and during follow-up (chronic DBS).SignificanceOur study reveals new information about the impedance of segmented electrodes that is useful for patient management during the initial test period, as well as during long-term DBS follow-up.     

益母草中阿魏酸对含益母草中成药质量标准影响的探讨

目的：建立HPLC/TQ-MS测定益母草中阿魏酸含量的方法并测定不同产地益母草中阿魏酸含量，评价益母草中阿魏酸对中成药调经止痛片及新生化颗粒的质量影响，为制定含有益母草并以阿魏酸为定量指标的中成药质量标准提供参考。方法：采用薄层色谱法及UPLC-Q/TOF定性鉴别及分析益母草中阿魏酸，采用HPLC/TQ-MS定量分析10批不同产地益母草中阿魏酸含量。基于定量分析结果及处方用量探讨益母草中阿魏酸含量对其中成药质量标准的影响。结果：薄层鉴别及UPLC-Q/TOF定性分析结果显示，10批不同产地益母草中均含有阿魏酸。HPLC/TQ-MS定量分析结果显示，益母草中阿魏酸含量在0.004 2%~0.006 5%之间。结论：益母草与当归、川芎等含有阿魏酸的药材配伍且其用量较大时，益母草中阿魏酸含量会对其质量评价产生一定的影响。