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%.     

Insulin-like growth factor-1 as predictive factor of difficult laryngoscopy in patients with GH-producing pituitary adenoma: A pilot study

BackgroundGrowth hormone (GH)-producing pituitary tumors account for 10 to 15% of pituitary tumors. The hypersecretion of GH may induce changes in the airway anatomy through the activation of Insulin-like Growth factor 1(IGF-1) pathway. We sought investigate the role IGF-1 as a potential predictive factor of difficult laryngoscopy in patients with GH-producing pituitary adenoma.MethodsThis study was a single center retrospective study. We included 33 patients undergoing transsphenoidal resection of GH-producing pituitary. We recorded demographic data, el-Ganzouri risk index (EGRI) and modified Look-Evaluate-Mallampati-Obstruction-Neck mobility (mLEMON) score, and pituitary hormone plasma levels. We performed ordinal logistic regression to analyze the relationship between IGF-1 and EGRI, mLEMON, and Cormack-Lehane Grade score and a multiple logistic regression to test the capability of EGRI, mLEMON and IGF-1 levels to predict Cormack-Lehane score. Receiver operating curve (ROC), area under the curve (AUC), and cut-off value of IGF-1 were calculated.ResultsOnly 14 (42.8%) and 12 (36.36%) patients showed predictive factors of difficult intubation according to EGRI and mLEMON score, respectively. IGF-1 significantly correlated with Cormack-Lehane (p = 0.005879) but not with mLEMON and EGRI (p = 0.3080 and 0.4146, respectively). In multiple regression model IGF-1 correlated only with Cormack-Lehane grade (p = 0.0089). Area under ROC was 0.8571 and cut-off value of IGF-1 was 186.15 ng/ml.ConclusionHigher IGF-1 levels correlate with the probability of having a higher Cormack-Lehane score; classical bedside scores, such as mLEMON and EGRI, were not able to predict difficult laryngoscopy in our population.     

Proteases and their inhibitors as prognostic factors for high-grade serous ovarian cancer

Ovarian carcinoma is one of the most lethal malignancies, but only very few prognostic biomarkers are known. The degradome, comprising proteases, protease non-proteolytic homologues and inhibitors, have been involved in the prognosis of many cancer types, including ovarian carcinoma. The prognostic significance of the whole degradome family has not been specifically studied in high-grade serous ovarian cancer. A targeted DNA microarray known as the CLIP-CHIP microarray was used to identify potential prognostic factors in ten high-grade serous ovarian cancer women who had early recurrence (<1.6 years) or late/no recurrence after first line surgery and chemotherapy. In women with early recurrence, we identified seven upregulated genes (TMPRSS4, MASP1/3, SPC18, PSMB1, IGFBP2, CFI – encoding Complement Factor I – and MMP9) and one down-regulated gene (ADAM-10). Using immunohistochemistry, we evaluated the prognostic effect of these 8 candidate genes in an independent cohort of 112 high-grade serous ovarian cancer women. Outcomes were progression, defined according to CA-125 criteria, and death. Multivariate Cox proportional hazard regression models were done to estimate the associations between each protein and each outcome. High ADAM-10 expression (intensity of 2–3) was associated with a lower risk of progression (adjusted hazard ratio (HR): 0.51; 95% confidence interval (CI): 0.29-0.87). High complement factor I expression (intensity 2–3) was associated with a higher risk of progression (adjusted HR: 2.30, 95% CI: 1.17–4.53) and death (adjusted HR: 3.42; 95% CI: 1.72–6.79). Overall, we identified the prognostic value of two proteases, ADAM-10 and complement factor I, for high-grade serous ovarian cancer which could have clinical significance.     

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.

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。