INTRODUCTION:Hemorrhoidectomy is among the most painful procedures in colorectal surgery. Effective postoperative pain management remains an unmet clinical need. To evaluate the efficacy, duration of analgesia, and safety of CT-guided inferior rectal nerve block (IRNB) for postoperative pain management following hemorrhoidectomy. METHODS:This retrospective study enrolled 69 patients with grade III or IV mixed hemorrhoids undergoing hemorrhoidectomy between April 2024 and March 2026. Patients who elected to receive IRNB were assigned to Group 1 (n = 38); those who declined formed Group 2 (n = 31, standard analgesia). Group 1 received bilateral CT-guided IRNB on postoperative day 1 using a mixture of triamcinolone acetonide, 0.5% bupivacaine HCl, normal saline, and epinephrine. Pain intensity was assessed using the Numerical Rating Scale (NRS, 0-10) at baseline and on postoperative days 1 to 10, 14, and 28. Analgesic use and complications were also recorded. RESULTS:Group 1 showed significantly lower median NRS scores than Group 2 on postoperative day 1 (2 [1-5] vs 5 [4-7]; P < .001), with sustained superiority through day 14 (1 [0-1] vs 2 [0-3]; P < .05). A secondary pain peak occurred in Group 1 on day 4 (4 [2-5]), consider pharmacological attrition and pain rebound. Both groups reached near-complete pain resolution by day 28. Complication rates did not differ significantly between groups. CONCLUSIONS:CT-guided IRNB may provides effective and safe postoperative analgesia following hemorrhoidectomy, with significant pain control over the first 2 postoperative weeks.
PURPOSE:To evaluate the diagnostic outcomes of single-view asymmetries (SVAs) recalled from screening mammography and to explore the association between artificial intelligence (AI) detection and malignancy. METHODS:This REB-approved retrospective single-center study included women recalled for SVAs from screening mammography performed at The Ottawa Hospital between March 1, 2024 and March 31, 2025. SVAs were defined as asymmetries identified on a single mammographic projection. Screening performance metrics were obtained from the EPIC Mammography Quality Standards Act module, and imaging outcomes were reviewed in PACS. Primary outcomes included cancer detection rate (CDR), positive predictive value for recall (PPV1), and positive predictive value for biopsy (PPV3). Following implementation of AI software (Transpara) in September/October 2024, exploratory analyses evaluated associations between AI flag status and malignancy. RESULTS:Among 32 412 screening examinations, 2455 patients (7.6%) were recalled, including 410 patients with 464 SVAs. Five cancers were identified, corresponding to a CDR of 0.16 per 1000 screened patients, significantly lower than the overall screening CDR of 6.08 per 1000 (P < .0001). PPV1 for SVAs was 1.22% (5/410), significantly lower than the overall PPV1 of 8.02% (197/2455) (P < .0001). Twenty-five patients (5.4%) underwent biopsy, yielding a PPV3 of 20%. Overall, 98.8% of recalled SVAs were non-malignant. Following AI implementation, malignancy rates were 0.6% (1/154) among non-flagged SVAs and 2.9% (2/68) among AI-flagged SVAs (P = .17). All malignancies were Stage I at diagnosis. CONCLUSION:SVAs were a common but very low-yield cause of recall in screening mammography. Although exploratory, the low malignancy yield among non-AI-flagged SVAs suggests a potential role for AI as a supportive adjunct in risk stratification and recall decision-making.
PURPOSE:Environmental sustainability is an emerging priority in radiology, yet the impact of deep learning training policies on greenhouse gas emissions remains poorly characterized. This study quantified the effect of training policy on carbon dioxide equivalent (CO2eq) emissions and model performance for chest radiograph classification. METHODS:Anteroposterior chest radiographs (128 907 training, 24 570 validation, 8282 test) were used to train 3 ImageNet-pretrained convolutional neural networks (ResNet-50, DenseNet-121, EfficientNet-B0) for 20 epochs. Three policies were evaluated: (1) retrospective optimal checkpoint selection at the validation loss minimum; (2) prospective early stopping (patience 10 epochs); and (3) fixed 20-epoch training without checkpoint selection. Per-epoch CO2eq emissions, energy, macro-averaged area under the curve (AUC), and carbon efficiency were evaluated. RESULTS:Validation loss reached its minimum at median epoch 2 for ResNet-50 and DenseNet-121 and epoch 4 for EfficientNet-B0. At the retrospective optimum, macro-AUCs ranged from 0.793 to 0.800 and generated 6.2 to 7.9 g CO2eq (37-46 Wh) at the deployed checkpoint. However, producing this model required the full run, generating 30.8 to 49.4 g CO2eq (181-291 Wh) with 78% to 84% of training emissions accruing after the deployed checkpoint. Prospective early stopping had macro-AUCs equivalent to the retrospective optimum (0.793-0.800), with 31% to 38% lower total emissions (21.1-30.9 vs 30.8-49.4 g CO2eq) and 57% to 76% higher carbon efficiency (25.9-37.6 vs 14.7-24.0 AUC/kg CO2eq) compared to fixed-epoch training. CONCLUSIONS:Up to 84% of total training emissions accrued after the optimal checkpoint, with relative savings dependent on the comparator. Prospective early stopping preserved performance, reduced emissions by up to 38%, and improved carbon efficiency by up to 76% versus fixed 20-epoch training.
Global health in radiology has expanded substantially over the past 2 decades. However, much of the field continues to be described through the language of outreach, volunteerism, and bilateral partnerships. While these concepts reflect an important part of how global radiology work has developed, they do not fully capture the wider systems issues that determine whether radiology services can function effectively over time. In practice, radiology services are shaped by workforce training, equipment procurement and maintenance, digital infrastructure, governance, financing, quality improvement, and evaluation. These factors influence whether imaging services are available, reliable, and able to support equitable care. This narrative review examines the development of global health radiology, distinguishes it from related concepts such as public health and international outreach, and synthesises the literature across major areas, including education partnerships, service development, teleradiology, point-of-care ultrasound, low-field magnetic resonance imaging, artificial intelligence, and interventional radiology capacity building. Particular challenges with radiology in global health settings include high equipment and infrastructure requirements, dependence on maintenance and technical support, and the need for sustained training, oversight, and long-term investment. The literature also demonstrates several ongoing limitations, including fragmented initiatives, limited evaluation frameworks, little attention to patient-centred outcome measurement, inequitable partnership models, and insufficient focus on implementation and financing. This review outlines future directions for global health radiology with relevance to equitable partnership design, sustainable funding, implementation, and alignment with broader health-system priorities.
France has seen significant advancements in radiology in recent years, driven by innovations in research and clinical practice. French groups have developed innovative imaging techniques and artificial intelligence applications in the field of diagnostic imaging and interventional radiology. These include a more precise diagnosis of cancer and other diseases, research in dual-energy and photon-counting computed tomography, new applications of artificial intelligence, and advanced treatments in the field of interventional radiology. The objective of this article was to provide an update on selected research initiatives and technological advances that are influencing the field of radiology in France. By underscoring pivotal contributions in the domains of diagnostic imaging, artificial intelligence, and interventional radiology, this article provides a comprehensive overview and underscores the manner in which these innovations are enhancing patient outcomes, increasing diagnostic accuracy, and expanding the potential for minimally invasive therapeutic interventions. As the field continues to evolve, France’s position at the forefront of radiological research ensures that these innovations will play a central role in addressing current healthcare challenges and improving patient care on a global scale.
The objective of the study was to estimate the magnitude, associated factors, and risk-factor population attributable fractions (PAFs) for Diabetes Mellitus (DM) among adults living in Brazilian state capitals, according to sex. This was a cross-sectional study using data from a sample of 32,111 adults aged 18 years or older who participated in the 2019 National Health Survey. Poisson regression and PAFs estimation were used to assess the associated factors and their contributions to prevalent cases of DM, respectively. The prevalence of DM was 7.7% (7.2% in men and 8.0% in women). In the total sample, the Poisson model showed a direct association between DM and female sex, age >60 years, no formal education, physical inactivity during leisure time, self-reported hypercholesterolemia and hypertension, overweight, and obesity. An inverse association was observed for binge drinking. Mixed-race and black race/skin color, as well as leisure-time physical inactivity, were factors associated with DM among women. The PAFs of risk factors that contributed most to prevalent cases of DM, in both sexes, were age >60 years, self-reported hypertension and hypercholesterolemia, and obesity. In conclusion, clinical factors had the highest PAFs for DM and should be the focus of prevention and control policies.
This research analyzed the spatial distribution and the association between environmental factors and childhood overweight (OW), using municipal-level data from the Food and Nutrition Surveillance System (2019) to estimate the prevalence of OW and its magnitude as a public health problem among infants, preschoolers, and school-aged children. The Moran's index for spatial correlation was performed, and generalized linear mixed models for the associations between OW and the micro (prevalence of obesity in women), meso (density of unhealthy businesses/10,000 inhabitants), and macro environment (Sustainable Cities Development Index - IDSC). The respective prevalences were high/very high among infants, preschoolers, and school-aged children in 28%, 75%, and 77% of the cities. The higher the IDSC, the lower the prevalence of OW among infants and preschoolers; among school-aged children, there was a positive association between OW and the micro and meso environment. It is concluded that there are spatial clusters of OW in all macro-regions, with macroenvironmental factors providing protection against OW in children under five years of age, while micro and mesoenvironmental factors pose risk for OW school-aged children.
Corporate Political Activities (CPA) in the commercial private sector present significant obstacles to developing regulatory policies concerning food. This study investigates how associations within the food and communication sectors, which have historically opposed food advertising regulation in Brazil, are organized and what specific CPA they engage in regarding this issue. To achieve this, the websites of these associations were examined, and information on affiliated companies was collected. The evaluation of CPA was conducted using a framework that differentiates between instrumental and discursive activities. The sample comprised seven associations, representing a total of 413 companies, 183 of which belong to the food sector. A total of 179 instances of CPA were identified, including 73 instrumental strategies and 106 discursive strategies. The most frequently employed instrumental strategies included information management and coalition management, while the discursive strategies focused on narratives related to diet and public health concerns. The findings indicate that commercial private sector associations, with a history of opposing food advertising regulation, constitute an organized network that employs CPA to impede regulatory initiatives in Brazil.
PURPOSE:This study evaluates the diagnostic value of CT/MRI-based nodal morphology and three-plane size criteria for identifying pathologically positive (pN+) cervical lymph nodes (LNs) in oral squamous cell carcinoma (OSCC). METHODS:OSCC patients who underwent neck dissection (2020-2021) were included. Preoperative CT/MRI were reviewed by an observer blinded to clinicopathological information. Visible LNs were assessed for morphologic abnormality and size in short-axial (SAD), maximum-axial (MAD), and craniocaudal (CC) diameters. Sensitivity and specificity of each imaging parameter were calculated using pathology as the reference standard. RESULTS:CT/MRI scans from 148 patients were analyzed. Sensitivity/specificity for detecting pN+ LNs were: 56%/76% (abnormal morphology-alone), 57%/72% (morphology ± SAD >1.0 cm), 83%/28% (morphology ± MAD >1.0 cm), 86%/29% (morphology ± CC >1.0 cm), and 88%/24% (morphology ± any-plane >1.0 cm). Among 64 morphologically abnormal LNs, 25, 6, and 5 measured ≤1.0 cm in SAD, MAD, and CC, respectively, with pN+ rates of 16/25 (64%), 4/6 (66.7%), and 3/5 (60%). In morphologically "normal" (homogenous) LNs, sensitivity/specificity for pN+ detection by >1.0 cm size threshold were: 3%/95% (SAD), 62%/36% (MAD), 68%/39% (CC), and 72%/32% (any plane). CONCLUSIONS:Abnormal LN morphology is the most reliable CT/MRI indicator of pN+ disease in OSCC, irrespective of nodal size, although sensitivity remains modest. In morphologically normal LNs, three-plane size assessment, particularly MAD and CC, improves detection of pN+ beyond SAD. These findings support a morphology-first approach to CT/MRI nodal evaluation and inform an exploratory OSCC-specific decision framework incorporating morphology, multi-plane size assessment, and lymphatic drainage patterns.
This study identifies structural changes, changes in the delivery of care, and trends in the use of cesarean sections in teaching hospitals participating in the Apice ON project, which focuses on transforming the teaching and delivery of obstetric and neonatal care towards a humanized, evidence-based approach. A descriptive and exploratory study was conducted using secondary data from the National Registry of Health Establishments, the Hospital Information System, and the Live Birth Information System from before the project (first half of 2017) and near its completion (second half of 2019). The study found progress in the provision of specialized facilities such as-high-risk maternity homes and in-hospital birth centers; an increase in the number of obstetric nurses; a three-percentage-point increase in births assisted by these professionals; an increase in births in low-risk cesarean groups (Robson groups 1 to 4); and a decrease in unclassified births. Overall, however, cesarean section rates remained high, even in the groups where they should be reduced (Robson groups 1, 3, and 5).
The present study aims to analyze the needs of health services after the tailings dam collapse disaster in Brumadinho-MG Brazil from the perspective of managers and professionals. This is a qualitative methodological study, based on 26 interviews guided by a semi-structured script. The data were processed using the content analysis technique, and the interpretation was mediated by the theoretical-methodological framework of hermeneutic anthropology. The study showed that both the process of obtaining compensation and its materialization had a major impact on local health services, both in terms of the emergence of new health demands and the work overload of professionals who had to handle situations beyond their designated jobs, involving porous limits of agreements and negotiations between the population and the company responsible for the disaster. The analysis shows the need to develop and equate strategies that consider the guarantee of rights without compromising the health and quality of life of those affected: those who care and those who are cared for. It is expected that this study's results may support surveillance actions, health care, and future risk management in similar contexts.
Leadership has emerged as a core competency for Canadian radiologists navigating an era of challenges, including the integration of artificial intelligence, regional service consolidation, value-based care, and growing administrative complexity. Yet formal leadership training remains underrepresented in radiology training and in continuing professional development. This article synthesizes contemporary leadership scholarship into a practical framework for radiologist development and is based on the first module of the CAR leadership course. Six interlocking concepts are examined: (1) leadership as an ongoing journey rather than a positional title; (2) authentic, self-aware leadership grounded in the "incomplete leader" model of distributed capabilities; (3) adaptability across leadership styles; (4) team chemistry and cognitive diversity; (5) the first 100 days of a new leadership role; and (6) mentorship as both a developmental obligation and a hedge against burnout. Effective leadership in radiology is learnable, but not by a checklist. It requires interactive education, reflective self-assessment, deliberate construction of complementary teams, intentional onboarding, and a sustained commitment to mentoring the next generation. The Canadian Association of Radiologists, in concert with Canadian Radiology departments and the Canadian Heads of Academic Radiology (CHAR), has taken on the task of formalizing these elements into structured programming that can meet the needs of busy radiologists.
