Breast cancer, with a high prevalence and survival rate, leads to long-term complications. A major sequel is acute or chronic postoperative pain, and we investigated the possible relationship with ...clinical and psychological variables. Patients undergoing breast surgery filled out the loneliness (ULS-8) and depression (HADS) questionnaires. Patients rated their pain intensity with the Numerical Rating Scale (0-10, NRS) two days, seven days, and six months after surgery. Of 124 patients, the mean age was 45.86 years old, and the pain scores on the second and seventh postoperative days were 5.33 and 3.57, respectively. Sixth-month pain was significantly correlated with the acute scores with a mean of 3.27; and in the multivariate analysis, it was significantly associated with preoperative pain (p-value = 0.007), self-reported loneliness (p-value = 0.010), and adjuvant radiotherapy (p-value = 0.004). In conclusion, loneliness may be a risk factor for postoperative pain in breast surgery.
Burnout, stemming from chronic work stress, is a significant issue in the medical field, especially among radiologists. It leads to compromised patient care and reduced job satisfaction. Addressing ...burnout in radiology is essential for the well-being of radiologists and, in turn, for improving patient care. This study aimed to assess the prevalence and dimensions of burnout among radiology trainees (RTs) and practicing radiologists (PRs).
A systematic review and meta-analysis were conducted in accordance with established guidelines. The search encompassed PubMed, Scopus, Web of Science, and Embase databases up to June 20, 2023. Eligible studies that assessed the rate of burnout syndrome and/or its subscales, including depersonalization (DP), emotional exhaustion (EE), and personal accomplishment (PA), among RTs and/or PRs using the Maslach Burnout Inventory (MBI), were included. Relevant data were extracted and analyzed using R and STATA.
Among the 22 included studies, the pooled rates of positive MBI subscales for RTs and PRs were as follows: 54.7% (95% confidence interval CI: 43.8%-65.1%, I
= 95.2%) for DP, 57.2% (95% CI: 48.7%-65.4%, I
= 92.9%) for EE, and 38.6% (95% CI: 27%-51.7%, I
= 95.5%) for low PA. The pooled rate indicating the presence of at least one positive MBI subscale was 82.9% (95% CI: 79.2%-86.1%, I
= 57.4%). For two or more positive MBI subscales, the pooled rate was 55.5% (95% CI: 49.7%-61.3%, I
= 60.2%), and for three positive MBI subscales, it was 16.7% (95% CI: 11.7%-23.3%, I
= 82.7%).
This study emphasizes a notable prevalence of burnout in the radiology specialty, with 8 of 10 individuals exhibiting positive results in at least one MBI subscale. This highlights the urgent need for interventions and support systems to protect the well-being of both trainees and practitioners and uphold the quality of patient care.
PURPOSEMagnetic resonance imaging (MRI) can reduce the need for unnecessary invasive diagnostic tests by nearly half. In this meta-analysis, we investigated the diagnostic accuracy of intravoxel ...incoherent motion modeling (IVIM) and dynamic contrast-enhanced (DCE) MRI in differentiating benign from malignant breast lesions. METHODWe systematically searched PubMed, EMBASE, and Scopus. We included English articles reporting diagnostic accuracy for both sequences in differentiating benign from malignant breast lesions. Articles were assessed by quality assessment of diagnostic accuracy studies-2 (QUADAS-2) questionnaire. We used a bivariate effects model for standardized mean difference (SMD) analysis and diagnostic test accuracy analysis. RESULTSTen studies with 537 patients and 707 (435 malignant and 272 benign) lesions were included. The D, f, Ktrans, and Kep mean values significantly differ between benign and malignant lesions. The pooled sensitivity (95 % confidence interval) and specificity were 86.2 % (77.9 %-91.7 %) and 70.3 % (56.5 %-81.1 %) for IVIM, and 93.8 % (85.3 %-97.5 %) and 68.1 % (52.7 %-80.4 %) for DCE, respectively. Combined IVIM and DCE depicted the highest area under the curve of 0.94, with a sensitivity and specificity of 91.8 % (82.8 %-96.3 %) and 87.6 % (73.8 %-94.7 %), respectively. CONCLUSIONSCombined IVIM and DCE had the highest diagnostic accuracy, and multiparametric MRI may help reduce unnecessary benign breast biopsy.
Nowadays, manufacturing environments are faced with globalization that urges new necessities for manufacturing systems. These necessities have been considered from different perspectives, and ...Computer Integrated Manufacturing (CIM) is the most popular and effective system. However, considering the rapid rate of manufacturing globalization, traditional and current CIM solutions can be criticized by major deficiencies such as high complexity for resource allocation over the globe, global facility sharing, and the absence of an efficient way to handle lifecycle issues. Recently, Virtual CIM (VCIM) has been introduced as an effective solution to extend the traditional CIM solutions. This paper has investigated recent pieces of research associated with VCIM/CIM field in accordance with the necessity of todays' globalized manufacturing environment. The paper shows the lack of traditional and current CIM/VCIM solutions and, then, proposes an effective solution to cover them. Due to the complexity of designing such systems, this paper exploits Axiomatic Design (AD) theory as a promising tool in this field. This theory is applied to validate the suggested architectural solution and verify its performance and implementational aspects. The implementation of the architectural solution is considered based on ISO standards. Finally, the results approved the feasibility of the suggested solution for manufacturing system and its Implementational aspects.
This comprehensive review explores the role of deep learning (DL) in glioma segmentation using multiparametric magnetic resonance imaging (MRI) data. The study surveys advanced techniques such as ...multiparametric MRI for capturing the complex nature of gliomas. It delves into the integration of DL with MRI, focusing on convolutional neural networks (CNNs) and their remarkable capabilities in tumor segmentation. Clinical applications of DL‐based segmentation are highlighted, including treatment planning, monitoring treatment response, and distinguishing between tumor progression and pseudo‐progression. Furthermore, the review examines the evolution of DL‐based segmentation studies, from early CNN models to recent advancements such as attention mechanisms and transformer models. Challenges in data quality, gradient vanishing, and model interpretability are discussed. The review concludes with insights into future research directions, emphasizing the importance of addressing tumor heterogeneity, integrating genomic data, and ensuring responsible deployment of DL‐driven healthcare technologies. Evidence Level N/A Technical Efficacy Stage 2
This paper studies the behavior of six air pollutants (including PMio, PM2.5, O3, SO2, NO2, and CO) in Tehran over a 6-year time span. In this paper, an iterative procedure based on the univariate ...Box-Jenkins stochastic models is applied to develop the most effective forecasting model for each air pollutant. Applying a number of widely used criteria, the best model for each air pollutant is selected and the results show that the proposed models perform accurately and satisfactorily for both fitting and predicting where the fitted and predicted values are so close to the true values of the related data. Finally, factor analysis is conducted to investigate the relationships between the air pollutants where the results show that four factors account for 93.2704% of the total variance. In this regard, the factor containing PM10 and PM2.5 and the factor containing CO and NO2 are, respectively, the most and the second most affecting factors with the proportion of 43.2594% and 21.6500% of the total variability. Since both of these factors stem from the large-scale use of fossil-fuel vehicles, reducing the number of vehicles or improving the quality of fossil fuels, may increase air quality by 60%.
Natural resources have long played a prominent part in conventional treatments as a parental source due to their multifaceted functions and lesser side effects. The diversity of marine products is a ...significant source of possible bioactive chemical compounds with a wide range of potential medicinal applications. Marine organisms produce natural compounds and new drugs with unique properties are produced from these compounds. A lot of bioactive compounds with medicinal properties are extracted from marine invertebrates, including Peptides, Alkaloids, Terpenoids, Steroids. Thus, it can be concluded that marine ecosystems are endowed with natural resources that have a wide range of medicinal properties, and it is important to examine the therapeutic and pharmacological capabilities of these molecules. So, finding particular inhibitors of the COVID-19 in natural compounds will be extremely important. Natural ingredients, in this light, could be a valuable resource in the progression of COVID-19 therapeutic options. Controlling the immunological response in COVID-19 patients may be possible by addressing the PI3K/Akt pathway and regulating T cell responses. T cell effector activity can be improved by preventing anti-viral exhaustion by suppressing PI3K and Akt during the early anti-viral response. The diversity of marine life is a significant supply of potentially bioactive chemical compounds with a broad range of medicinal uses. In this study, some biologically active compounds from marine organisms capable of inhibiting PI3K/AKT and the possible therapeutic targets from these compounds in viral infection COVID-19 have been addressed.
Background
Glioma grading transformed in World Health Organization (WHO) 2021 CNS tumor classification, integrating molecular markers. However, the impact of this change on radiomics‐based machine ...learning (ML) classifiers remains unexplored.
Purpose
To assess the performance of ML in classifying glioma tumor grades based on various WHO criteria.
Study Type
Retrospective.
Subjects
A neuropathologist regraded gliomas of 237 patients into WHO 2016 and 2021 from 2007 criteria.
Field Strength/Sequence
Multicentric 0.5 to 3 Tesla; pre‐ and post‐contrast T1‐weighted, T2‐weighted, and fluid‐attenuated inversion recovery.
Assessment
Radiomic features were selected using random forest‐recursive feature elimination. The synthetic minority over‐sampling technique (SMOTE) was implemented for data augmentation. Stratified 10‐fold cross‐validation with and without SMOTE was used to evaluate 11 classifiers for 3‐grade (2, 3, and 4; WHO 2016 and 2021) and 2‐grade (low and high grade; WHO 2007 and 2021) classification. Additionally, we developed the models on data randomly divided into training and test sets (mixed‐data analysis), or data divided based on the centers (independent‐data analysis).
Statistical Tests
We assessed ML classifiers using sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve (AUC). Top performances were compared with a t‐test and categorical data with the chi‐square test using a significance level of P < 0.05.
Results
In the mixed‐data analysis, Stacking Classifier without SMOTE achieved the highest accuracy (0.86) and AUC (0.92) in 3‐grade WHO 2021 grouping. The results of WHO 2021 were significantly better than WHO 2016 (P‐value<0.0001). In the 2‐grade analysis, ML achieved 1.00 in all metrics. In the independent‐data analysis, ML classifiers showed strong discrimination between grade 2 and 4, despite lower performance metrics than the mixed analysis.
Data Conclusion
ML algorithms performed better in glioma tumor grading based on WHO 2021 criteria. Nonetheless, the clinical use of ML classifiers needs further investigation.
Level of Evidence
3
Technical Efficacy
Stage 2
Esophageal cancer remains a global challenge due to late diagnoses and limited treatments. Lymph node metastasis (LNM) is crucial for prognosis, yet traditional diagnostics fall short. Integrating ...radiomics and deep learning (DL) with CT imaging for LNM diagnosis could revolutionize prognostic assessment and treatment planning.
A systematic review and meta-analysis were conducted by searching PubMed, Scopus, Web of Science, and Embase up to October 1, 2023. The focus was on studies developing CT-based radiomics and/or DL models for preoperative LNM detection in esophageal cancer. Methodological quality was assessed using the METhodological RadiomICs Score (METRICS).
Twelve studies were reviewed, and seven were included in the meta-analysis, most showing excellent methodological quality. Training sets revealed a pooled AUC of 87 % (95 % CI: 78 %–90 %), and internal validation sets showed an AUC of 85 % (95 % CI: 76 %–89 %), with no significant difference (p = 0.39). Sensitivity and specificity for training sets were 78.7 % and 81.8 %, respectively, with validation sets at 81.2 % and 76.2 %. DL models in training sets showed better diagnostic accuracy than radiomics (p = 0.054), significant after removing outliers (p < 0.01). Incorporating clinical data improved sensitivity in validation sets (p = 0.029). No significant difference was found between models based on CE or non-CE imaging (p = 0.281) or arterial or venous phase imaging (p = 0.927).
Integrating CT-based radiomics and DL improves LNM detection in esophageal cancer. Including clinical data could enhance model performance. Future research should focus on multicenter studies with independent validations to confirm these findings and promote broader clinical adoption.
•CT radiomics and deep learning can guide esophageal cancer treatment planning by lymph node metastasis diagnosis.•Meta-analysis shows high discrimination power with nearly 85 % pooled area under the curve in validation sets.•Deep learning models yield higher specificity than hand-crafted radiomics.•Model trained on radiomics and clinical data had higher sensitivity in validation sets.
It is important to note that prevention of button battery ingestion is the most effective way to reduce its incidence and complications. This is unachievable without providing educational plans for ...parents. Moreover, triage nurses and first-line staff who take the history of patients and physicians should take the history to evaluate the risk of battery ingestion. Plain radiographs can be helpful in this matter, as the presence of "Hallow" and "Steep" signs in the anteroposterior and lateral views, respectively, can help.Key Clinical MessageIt is important to note that prevention of button battery ingestion is the most effective way to reduce its incidence and complications. This is unachievable without providing educational plans for parents. Moreover, triage nurses and first-line staff who take the history of patients and physicians should take the history to evaluate the risk of battery ingestion. Plain radiographs can be helpful in this matter, as the presence of "Hallow" and "Steep" signs in the anteroposterior and lateral views, respectively, can help.Foreign body ingestion is a relatively common occurrence in pediatrics, especially among children 1-3 years of age. Although most cases are benign and managed conservatively, those with high-risk subjects such as button batterie can bring about fatal conditions in the minority of cases. In the present study, the history, diagnostic, and therapeutic procedures of a 13-month-old baby with the final diagnosis of button battery ingestion are presented. The parents ignored the symptoms, suspecting that it was a viral infection. The evaluations showed that a battery was lodged in the middle part of the thoracic esophagus, which was removed by an urgent endoscopic procedure. The patient was under observation and on a nothing-by-mouth diet for a week, receiving nutritional fluid with a nasogastric tube. The necrosis, which was obvious after the removal of the battery, was healing in the second control esophagogastroduodenoscopy performed 1 week after the procedure. The stricture was minimal, and no need for dilation was diagnosed. This case report underscores the importance of a timely diagnosis and removal of these cases. This case underscores the importance of the timely presentation of these cases to health care and the risk of delayed removal, such as necrosis, forming fistula, and perforation of the esophagus. The delay can cause necrosis, fistula, and perforation and might lead to irreversible severe complications and even death.AbstractForeign body ingestion is a relatively common occurrence in pediatrics, especially among children 1-3 years of age. Although most cases are benign and managed conservatively, those with high-risk subjects such as button batterie can bring about fatal conditions in the minority of cases. In the present study, the history, diagnostic, and therapeutic procedures of a 13-month-old baby with the final diagnosis of button battery ingestion are presented. The parents ignored the symptoms, suspecting that it was a viral infection. The evaluations showed that a battery was lodged in the middle part of the thoracic esophagus, which was removed by an urgent endoscopic procedure. The patient was under observation and on a nothing-by-mouth diet for a week, receiving nutritional fluid with a nasogastric tube. The necrosis, which was obvious after the removal of the battery, was healing in the second control esophagogastroduodenoscopy performed 1 week after the procedure. The stricture was minimal, and no need for dilation was diagnosed. This case report underscores the importance of a timely diagnosis and removal of these cases. This case underscores the importance of the timely presentation of these cases to health care and the risk of delayed removal, such as necrosis, forming fistula, and perforation of the esophagus. The delay can cause necrosis, fistula, and perforation and might lead to irreversible severe complications and even death.
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