In a stretched healthcare system, radiographer preliminary image evaluation in the acute setting can be a means to optimise patient care by reducing error and increasing efficiencies in the patient journey. Radiographers have shown impressive accuracies in the provision of these initial evaluations, however, barriers such as a lack of confidence and increased workloads have been cited as a reason for radiographer reticence in engagement with this practice. With advances in Artificial Intelligence (AI) technology for assistance in clinical decision-making, and indication that this may increase confidence in diagnostic decision-making with reporting radiographers, the author of this editorial wonders what the impact of this technology might be on clinical decision-making by radiographers in the provision of Preliminary Image Evaluation (PIE).

This editorial summarises the evolution and positive impact that radiographer preliminary image evaluation has on patient care. It also highlights the importance of using consistent and clear terminology when referring to when radiographers alert significant pathology to the referring clinical team and radiologists.

Radiology services in New Zealand are under significant pressure. Preliminary image evaluation (PIE) by radiographers can have a significant positive impact on patient care in this constrained environment and should be supported.

This article discusses the role of deep learning (DL) in cancer imaging, focusing on its applications for automatic image segmentation. It highlights two studies that demonstrate how U-Net- and convolutional neural networks–based architectures have improved the speed and accuracy of body composition analysis in CT scans and rectal tumour segmentation in MRI images. While the results are promising, the article stresses the need for further research to address issues like image quality variability across different imaging systems.

A novel automatic segmentation algorithm (named AttSEResUNet) was proposed for rectal cancer in axial T2WI images, which combines residual network with spatial attention and channel attention mechanisms. The AttSEResUNet model outperformed other three models and the segmentation variability of AttSEResUNet was similar to that of the inter-observer.

The automated analysis of body composition using computed tomography (CT) slices plays a crucial role in understanding its relationship with clinical outcomes in colorectal cancer patients. This study aimed to assess the effectiveness of an AI-based model for automatic quantification of body composition from lumbar (L3) region CT slices in colorectal cancer patients.

The use of the BodyFIX system reduced the pelvic tilt variance for gynaecological patients. This form of immobilisation also reduced the need for re-imaging pre-treatment by half, reducing imaging dose to the patients. Approximately 82% of departments who responded to the study survey reported seeing pelvic tilt on pre-treatment imaging indicating that this is an issue worth finding a strategy to combat. The BodyFIX system could result in more accurate and efficient treatment of gynaecological external beam radiotherapy patients.

The purpose of this study was to investigate the regions of the body that cause the most false-positive errors. A longitudinal retrospective clinical audit was conducted to determine the accuracy of radiographer preliminary image evaluations over five years from January 2016 to December 2020. Findings in this study should be used to tailor education specific to radiographer image interpretation.

Lack of adequate time to review imaging has been identified as a key barrier in the implementation of a radiographer preliminary image evaluation (PIE) service. Statistical analysis evidences no significant correlation between average hourly imaging workload and average hourly PIE service accuracy.

External beam radiation therapy using electrons and an internal eye shield is an alternative, relatively underreported technique which can provide similar cosmetic and functional outcomes. This report aimed to describe the process for the use of internal eye shields and the associated clinical outcomes and patient perceptions of the delivery and results of this procedure.

In resource-limited settings, radiology departments often face challenges such as radiologist shortages that impact image interpretation. This qualitative study explores the perceptions of radiographers and radiologists on these challenges and potential solutions. The research identified key themes related to image interpretation pathways, operational challenges and proposed solutions, which include increasing the number of radiologists, enhancing IT support systems, and empowering radiographers to take on interpretation roles through additional training.

This study aimed to explore and describe the experiences of BSc second-year sonography students using simulation-based learning (SBL) as a form of clinical training prior to patient interaction at a University of Technology (UoT) in South Africa. Thematic analysis of the data revealed three themes: (1) Enhancing preparedness for the clinical environment, (2) Limitations of the tissue-equivalent phantom and (3) Suggestions for improving simulation learning.

The aim of this study was to determine what effect regular feedback had on radiographers' performance when performing PIE in ED.  A prospective longitudinal study design was used to analyse PIEs performed by radiographers for 6-months between 2 April and 30 September 2023. The findings of this study recommend participants in a PIE system receive ongoing feedback to provide confidence and support to ensure they can maintain their PIE performance.

Current systems do not record the patient's name and pronouns appropriately, conflate sex and gender and treat sex and gender as a binary concept. This review indicates that current information systems used in medical radiation science and health care settings are inadequate to facilitate inclusive health care for transgender and gender-diverse patients.

This commentary paper addresses cultural safety in the context of the radiation therapy profession and emphasises the importance of highlighting the impact of knowledge and practice gaps. The educational strategies to improve cultural awareness among undergraduate students and qualified Radiation Therapists (RTs) are explored. Curriculum integration and development of initiatives such as workshops and interactive yarning groups are highlighted as pivotal platforms that foster continuous learning in radiation therapy.