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%. 相似文献
To investigate primary care physician clinical practice patterns, barriers, and education surrounding pediatric physical activity (PA), and to compare practice patterns by discipline. 相似文献
Although classified by the Joint Monitoring Programme (JMP) as unimproved sanitation facilities, public toilets still play a critical role in eliminating open defecation in informal settlements. We explored perspectives of toilet operators on opportunities and barriers to operation and maintenance (O&M) of public toilets in informal settlements. A cross-sectional study design was used. Up to 20 in-depth interviews were used to obtain data on the experiences of public toilet operators. Thematic content analysis was used.
Ressults show that opportunities for improving O&M include; operation of public toilets is a source of livelihood; operators are knowledgeable on occupational risks, and the community is involvedin sanitation activities. Barriers to effective O&M include; high operation costs, failure to break even and a lack of investments in occupational health Therefore, there is need to recognise the significance of public toilets as a viable alternative to open defecation in areas where ownership of private sanitation facilities is difficult. Failure to observe the health and safety of toilet operators may further compromise O&M. 相似文献
Background and aimPatient decision aids for oncological treatment options, provide information on the effect on recurrence rates and/or survival benefit, and on side-effects and/or burden of different treatment options. However, often uncertainty exists around the probability estimates for recurrence/survival and side-effects which is too relevant to be ignored. Evidence is lacking on the best way to communicate these uncertainties. The aim of this study is to develop a method to incorporate uncertainties in a patient decision aid for breast cancer patients to support their decision on radiotherapy.MethodsFirstly, qualitative interviews were held with patients and health care professionals. Secondly, in the development phase, thinking aloud sessions were organized with four patients and 12 health care professionals, individual and group-wise.ResultsConsensus was reached on a pictograph illustrating the whole range of uncertainty for local recurrence risks, in combination with textual explanation that a more exact personalized risk would be given by their own physician. The pictograph consisted of 100 female icons in a 10 x 10 array. Icons with a stepwise gradient color indicated the uncertainty margin. The prevalence and severity of possible side-effects were explained using verbal labels.ConclusionsWe developed a novel way of visualizing uncertainties in recurrence rates in a patient decision aid. The effect of this way of communicating risk uncertainty is currently being tested in the BRASA study (NCT03375801). 相似文献