Canadian Association of Radiologists Journal-Journal De L Association Canadienne Des Radiologistes最新文献

Purpose: Adrenocortical carcinoma (ACC) is a rare condition with a poor and hardly predictable prognosis. This study aims to build and evaluate a preoperative computed tomography (CT)-based score (CT score) using features previously reported as biomarkers in ACC to predict overall survival (OS) in patients with ACC. Methods: A CT score based on preoperative CT examinations combining shape elongation, maximum tumour diameter, and the European Network for the Study of Adrenal Tumors (ENSAT) stage was built using a logistic regression model to predict OS duration in a development cohort of 89 patients with ACC. An optimal cut-off of the CT score was defined and the Kaplan-Meier method was used to assess OS. The CT score was then tested in an external validation cohort of 54 patients wit ACC. The C-index of the CT score for predicting OS was compared to that of ENSAT stage alone. Results: The CT score helped discriminate between patients with poor prognosis and patients with good prognosis in both the validation cohort (54 patients; mean OS, 69.4 months; 95% confidence interval [CI]: 57.4-81.4 months vs mean OS, 75.6 months; 95% CI: 62.9-88.4 months, respectively; P = .022). In the validation cohort the C-index of the CT score was significantly better than that of the ENSAT stage alone (0.62 vs 0.35; P = .002). Conclusion: A CT score combining morphological criteria, radiomics, and ENSAT stage on preoperative CT examinations allows a better prognostic stratification of patients with ACC compared to ENSAT stage alone.

Purpose: This shadow deployment evaluated an externally-developed AI tool to predict disposition using chest X-rays (CXR) in patients with community-acquired pneumonia (CAP) in the Emergency Department (ED). Retrospective and prospective external validations were conducted to assess differences between the 2 evaluations and across subgroups to inform deployment decisions. Methods: The CNN was retrospectively validated (n = 17 689) from November 1, 2020, to June 30, 2021, and prospectively validated on "suspected-CAP" patients (n = 3062) from Jan 1 to Jan 31, 2023. Calibration and standard metrics, including AUC, accuracy, sensitivity, specificity, PPV, and NPV, were calculated. Subgroup analyses were conducted for age, sex, modality, and CXR projection (PA vs AP). Results: The model's AUC was 67% in both validations. The prospective evaluation showed a non-significant increase in sensitivity (65% vs 59%) and PPV (64% vs 63%), while specificity (68% vs 73%) and NPV (69% vs 70%) slightly decreased. NPV was very high for younger patients in the prospective evaluation (95%); PPV was moderately high for older patients (81%). Sensitivity dropped significantly in females under 31 years (50%), and specificity was reduced in females over 86 years (38%). Conclusion: This study showed moderate, consistent performance in both retrospective and prospective validations. While this consistency is encouraging, further direct comparisons are needed to determine whether both validation approaches are necessary in different clinical settings. Subgroup analysis suggests the tool may be helpful to accelerate discharge in younger patients (high NPV) and possibly for admission in older patients (high PPV).

When discussing leadership, multiple questions arise: what does it mean to be an effective leader?; what are the characteristics of a person that make them so?; and are leaders born, or are they made? Organizations need effective leaders at all levels, especially in the constant and rapidly changing landscape that is healthcare provision. Those in senior leadership roles should encourage junior team members to engage in leadership activities appropriate to their level of comfort and expertise. Integrity and principle are also essential leadership characteristics, particularly when faced with making decisions that are difficult, or considered to be "unpopular." Organizations that wish to develop and maintain effective leadership programs must ensure that they balance the needs of the organization with those of the leaders. Adequate space must be made to facilitate leadership activities as well as personal, academic, and clinical duties. Ultimately, leadership takes practice and persistence on the part of the leader themselves, but also on the part of the organization in which they work.

Purpose: Large language models (LLMs) have the potential to support clinical decision-making but often lack training on the latest clinical guidelines. Retrieval-augmented generation (RAG) may enhance guideline adherence by dynamically integrating external information. This study evaluates the performance of two LLMs, GPT-4o and o1-mini, with and without RAG, in adhering to Canadian radiology guidelines for incidental hepatobiliary findings. Methods: A customized RAG architecture was developed to integrate guideline-based recommendations into LLM prompts. Clinical cases were curated and used to prompt models with and without RAG. Primary analyses assessed the rate of guideline adherence with comparisons made between LLMs with and without RAG. Secondary analyses evaluated reading ease, grade level, and response times for generated outputs. Results: A total of 319 clinical cases were evaluated. Adherence rates were 81.7% for GPT-4o without RAG, 97.2% for GPT-4o with RAG, 79.3% for o1-mini without RAG, and 95.1% for o1-mini with RAG. Model performance differed significantly across groups, with RAG-enabled configurations outperforming their non-RAG counterparts (P < .05). RAG-enabled models demonstrated improved reading ease and lower grade level scores; however, all model outputs remained at advanced comprehension levels. Response times for RAG-enabled models increased slightly due to additional retrieval processing but remained clinically acceptable. Conclusions: RAG-enabled LLMs significantly improved adherence to Canadian radiology guidelines for incidental hepatobiliary findings without compromising readability or response times. This approach holds promise for advancing evidence-based care and warrants further validation across broader clinical settings.