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%.     

A comparison in independent nurse prescribing and patient group directions by nurse practitioners in the emergency department: A cross sectional review

AimTo explore nurse prescribing in an emergency department using patient group directions versus independent nurse prescribing.BackgroundPatient group directions allow restricted access to medication in unselected patients using pre-set criteria. Independent nurse prescribing is a flexible method of medication provision. Limited data exists on the application of either method in clinical practice.MethodsExploration of patient group directions and independent nurse prescribing application in an emergency department using 617 nurse practitioners’ clinical notes; 235 and 382 respectively. Patient attendances from 01/07/2009 to 30/06/2010 were randomly sampled. Prescribing frequency; range of medications and diagnoses; independent episode completion and prescribing safety was explored.ResultsStatistical difference exists in prescribing frequency between the independent nurse prescribers (51.6%, n = 197) and patient group directions (32.3%, n = 76). Appropriate medication given by 99.7% (n = 381) of independent nurse prescribers, with 1 contraindicated drug provided. The limitations of patient group directions was highlighted in 11.8% (n = 9) of cases, however all drugs given were appropriate for the diagnosis. No statistical difference in independent episode completion.ConclusionsNurses provide appropriate medication in an emergency department. Patients being managed by nurse prescribers were more likely to receive medication. Further investigation is required to justify this.     

Vaccines and variants: Modelling insights into emerging issues in COVID-19 epidemiology

Mathematical modelling has played a pivotal role in understanding the epidemiology of and guiding public health responses to the ongoing coronavirus disease of 2019 (COVID-19) pandemic. Here, we review the role of epidemiological models in understanding evolving epidemic characteristics, including the effects of vaccination and Variants of Concern (VoC). We highlight ways in which models continue to provide important insights, including (1) calculating the herd immunity threshold and evaluating its limitations; (2) verifying that nascent vaccines can prevent severe disease, infection, and transmission but may be less efficacious against VoC; (3) determining optimal vaccine allocation strategies under efficacy and supply constraints; and (4) determining that VoC are more transmissible and lethal than previously circulating strains, and that immune escape may jeopardize vaccine-induced herd immunity. Finally, we explore how models can help us anticipate and prepare for future stages of COVID-19 epidemiology (and that of other diseases) through forecasts and scenario projections, given current uncertainties and data limitations.     

Optimization of the Parameters for Diffusion Tensor Magnetic Resonance Imaging Data Acquisition for Breast Fiber Tractography at 1.5 T

IntroductionDiffusion tensor MRI has emerged as a promising tool for the analysis of the microscopic properties of tissues. Optimizing image acquisition parameters is essential for producing high-quality DTI. This study aimed to optimize the parameters for DTI data acquisition for breast fiber tractography at 1.5 T.Patients and MethodsA total of 21 healthy volunteers received breast DTI scanning using an ASSET-based EPI technique operated under different parameters including b value, the number of diffusion gradient directions, and spatial resolution. The images were analyzed for signal-to-noise, signal intensity ratio, mean number and length of reconstructive fiber tracts, and fractional anisotropy value.ResultsThe optimal acquisition parameters at 1.5 T for breast DT-MRI fiber tractography were determined as follows: axial 31 direction, b = 600 seconds per mm², matrix 128 × 128 with slice thickness of 3 mm.ConclusionThe optimization of data acquisition parameters could improve the quality of breast DT-MRI images and assist fiber tractography at 1.5 T.     

Understanding Interactions Between Chinese Medicines and Pharmaceutical Drugs in Integrative Healthcare

In the 21 st century,the public are more informed,mainly via the Internet,about health and medical products and have become more knowledgeable about matters relating to their health conditions and well-being in curing and preventing illnesses.They often self-medicate themselves with various health products and over-the-counter(OTC) medicines apart from prescribed pharmaceutical drugs(PD).Some of those non-prescribed products may have doubtful quality control and contain harmful additives or unchecked ingredients;thus their usefulness is in doubt.The increasing popularity world-wide of using Chinese medicines(CM) and related OTC functional products has raised concerns over their concomitant use with PD and the consequential adverse effects.In most cases the alleged causes of adverse effects are linked with herbal sources,although the authorised information on the interactions between CM-PD is not plentiful in the literature.There is an urgent need for such a data base.The future professionals in health and medical care should be knowledgeable or aware of what their patients have been taking or given.In actual practice the patients may receive both treatments intentionally or unintentionally,with or without the awareness of the practitioner.In these situations a reliable database for interactions between CM-PD will be extremely useful for consultation when treatment problems appear or during emergency situations.Their combining of medications may be involved with possible outcomes of adverse reactions or beneficial effects.Such a database will be welcomed by both practitioners of herbal medicines and orthodox medicine practitioners in the emerging trend of integrative medicine.The author has been involved in various research projects of basic and clinical aspects in mainly CM among other herbal and PD.Examples will be given largely on those related to these disciplines as illustrations in this overview.     

“卧”的姿势、时位与禁忌文献研究

养生之诀,以卧为先。通过从"卧"的姿势、时位以及禁忌归纳整理古代养生文献,发现古人所言睡方,应以侧卧为宜,面生气之位而居,四时应晨起于寅卯时,夜卧于戌亥时;卧须有向包括:恒东而卧——万物以生,东西而卧——调补阴阳,四向而卧——以应四季,依季而卧——顺时针卧;卧的禁忌包括:趋避不良环境(勿卧窗脊下,卧处勿当风,卧勿对炉灯),趋避不当行为(卧须闭口,不可言语;卧勿覆首,旦须暖腹;卧勿饱食,亦不可久;卧勿湿头,脚踏勿高)。以此为方,才能获得健康的睡眠,达到养生延寿的效果。     

The relationship between vocal accuracy and variability to the level of compensation to altered auditory feedback

Auditory feedback plays an important role in monitoring vocal output and determining when adjustments are necessary. In this study a group of untrained singers participated in a frequency altered feedback experiment to examine if accuracy at matching a note could predict the degree of compensation to auditory feedback that was shifted in frequency. Participants were presented with a target note and instructed to match the note in pitch and duration. Following the onset of the participants’ vocalizations their vocal pitch was shifted down one semi-tone at a random time during their utterance. This altered auditory feedback was instantaneously presented back to them through headphones. Results indicated that note matching accuracy did not correlate with compensation magnitude, however, a significant correlation was found between baseline variability and compensation magnitude. These results suggest that individuals with a more stable baseline fundamental frequency rely more on feedforward control mechanisms than individuals with more variable vocal production. This increased weighting of feedforward control means they are less sensitive to mismatches between their intended vocal production and auditory feedback.