Journal of Medical Radiation Sciences最新文献

{"title":"Emotional intelligence evaluation tools used in allied health students: A scoping review","authors":"Debra Lee AssDip (TherMedRad), DipAppSci (MedRadTech), BAppSci (MedRadTech),&nbsp;Tracy Burrows BHSC (N&D), GCTT, PhD,&nbsp;Daphne James AssDip (NucMedTech), GCert (TT), PhD,&nbsp;Ross Wilkinson BPsych, PhD,&nbsp;Yolanda Surjan BAppSci (MedRadTech), GCertHlthProm, MHlthSc (ED), PhD, Fellow (ASMIRT)","doi":"10.1002/jmrs.851","DOIUrl":"10.1002/jmrs.851","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Emotional intelligence (EI) is described as the ability to recognise and understand one's own emotions and the emotions of others, and empathically manage emotional responses. While historically not emphasised in undergraduate allied health sciences training, it is increasingly considered an essential graduate trait. This scoping review synthesises existing research on EI outcomes, specifically in undergraduate allied health professions students.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Method</h3>\u0000 \u0000 <p>Four databases were searched in February 2024 using keywords relating to EI and empathy to identify studies published in English from 1990. Eligible studies needed to include assessment and reported outcomes using validated EI tools in health professions students.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>A total of 163 papers met the inclusion criteria. Many studies employed a cross-sectional design (<i>n</i> = 115). Most studies (<i>n</i> = 135) focused on undergraduate students studying medicine (<i>n</i> = 62), nursing (<i>n</i> = 80) and dentistry (<i>n</i> = 13), with some studies (<i>n</i> = 21) evaluating more than one discipline. Many studies investigated one discipline only (<i>n</i> = 64 for nursing, <i>n</i> = 50 for medicine) using no comparator undergraduate degree. The most common EI models evaluated from this review were ability-based (<i>n</i> = 77), followed by trait-based models (<i>n</i> = 36) and mixed social–emotional competence (<i>n</i> = 35). Ability model evaluations of EI most commonly utilised the Schutte Self-Report Emotional Intelligence Test (SSEIT) (<i>n</i> = 44) and the Mayer–Salovey–Caruso Emotional Intelligence Test (MSCEIT) (<i>n</i> = 24).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Research on EI among undergraduate allied health fields is limited. Existing literature reveals there is some consensus on the importance of EI in healthcare education, but there is considerable variability in how EI is measured. Studies suggest higher levels of EI may correlate with improved student professional skill development in clinical reasoning, empathy and stress management.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"72 2","pages":"177-192"},"PeriodicalIF":1.8,"publicationDate":"2024-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jmrs.851","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142877320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence in radiation therapy treatment planning: A discrete choice experiment.","authors":"Milena Lewandowska, Deborah Street, Jackie Yim, Scott Jones, Rosalie Viney","doi":"10.1002/jmrs.843","DOIUrl":"https://doi.org/10.1002/jmrs.843","url":null,"abstract":"<p><strong>Introduction: </strong>The application of artificial intelligence (AI) in radiation therapy holds promise for addressing challenges, such as healthcare staff shortages, increased efficiency and treatment planning variations. Increased AI adoption has the potential to standardise treatment protocols, enhance quality, improve patient outcomes, and reduce costs. However, drawbacks include impacts on employment and algorithmic biases, making it crucial to navigate trade-offs. A discrete choice experiment (DCE) was undertaken to examine the AI-related characteristics radiation oncology professionals think are most important for adoption in radiation therapy treatment planning.</p><p><strong>Methods: </strong>Radiation oncology professionals completed an online discrete choice experiment to express their preferences about AI systems for radiation therapy planning which were described by five attributes, each with 2-4 levels: accuracy, automation, exploratory ability, compatibility with other systems and impact on workload. The survey also included questions about attitudes to AI. Choices were modelled using mixed logit regression.</p><p><strong>Results: </strong>The survey was completed by 82 respondents. The results showed they preferred AI systems that offer the largest time saving, and that provide explanations of the AI reasoning (both in-depth and basic). They also favoured systems that provide improved contouring precision compared with manual systems. Respondents emphasised the importance of AI systems being cost-effective, while also recognising AI's impact on professional roles, responsibilities, and service delivery.</p><p><strong>Conclusions: </strong>This study provides important information about radiation oncology professionals' priorities for AI in treatment planning. The findings from this study can be used to inform future research on economic evaluations and management perspectives of AI-driven technologies in radiation therapy.</p>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142869302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An evaluation of a checklist in musculoskeletal radiographic image interpretation when using artificial intelligence","authors":"Laura McLaughlin PhD,&nbsp;Sonyia L McFadden PhD,&nbsp;Angelina T Villikudathil PhD,&nbsp;Jonathan McConnell PhD,&nbsp;Ciara Hughes PhD,&nbsp;Raymond Bond PhD,&nbsp;Clare Rainey PhD","doi":"10.1002/jmrs.850","DOIUrl":"10.1002/jmrs.850","url":null,"abstract":"<div>\u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Artificial intelligence (AI) is being used increasingly in image interpretation tasks. Human reliance on technology and bias can cause decision errors. A checklist, used with the AI to mitigate against such biases, may optimise the use of AI technologies and promote good decision hygiene. A checklist to aid radiographic image interpretation for radiographers using AI for image interpretation was formed. This study investigates the effect of a checklist for musculoskeletal (MSK) radiographic image assessment when using AI interpretive assistance.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Radiographers were asked to interpret five MSK examinations with AI feedback. They were then provided with the checklist and asked to reinterpret the same five examinations with the AI feedback (<i>n</i> = 140 interpretations). During the interpretation sessions, participants were asked to provide a diagnosis and a confidence level on the diagnosis provided. Participants were then asked to complete a questionnaire to gain feedback on the use of the checklist.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Fourteen radiographers were recruited. Nine participants found the checklist alongside the AI most useful and five participants found the AI element to be most useful on its own. Five participants found the AI feedback to be useful as it helped to critique the radiographic image interpretation more closely and rethink their own initial diagnosis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The checklist for use with AI in MSK image interpretation contained useful elements to the user, but further developments can be made to enhance its use in clinical practice.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"72 2","pages":"209-216"},"PeriodicalIF":1.8,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jmrs.850","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142872301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A two-stage model for precise identification and Gleason grading of clinically significant prostate cancer: a hybrid approach","authors":"Yuyan Zou MMS,&nbsp;Xuechun Wang PhD,&nbsp;Fen Ma MB,&nbsp;Xulun Liu MMS,&nbsp;Chunyue Jiao MMS,&nbsp;Zhen Kang MD,&nbsp;Jingjing Cui MMS,&nbsp;Yang Zhang MMS,&nbsp;Yan Xie MMS,&nbsp;Lei Chen PhD,&nbsp;Ronghua Tian MMS","doi":"10.1002/jmrs.841","DOIUrl":"10.1002/jmrs.841","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Accurate identification and grading of clinically significant prostate cancer (csPCa, Gleason Score ≥ 7) without invasive procedures remains a significant clinical challenge. This study aims to develop and evaluate a two-stage model designed for precise Gleason grading. The model initially uses radiomics-based multiparametric MRI to identify csPCa and then refines the Gleason grading by integrating clinical indicators and radiomics features.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We retrospectively analysed 399 patients with PI-RADS ≥ 3 lesions, categorising them into non-significant prostate cancer (nsPCa, 263 cases) and csPCa (136 cases, subdivided by GGs). Regions of interest (ROIs) for the prostate and lesions were manually delineated on T2-weighted and apparent diffusion coefficient (ADC) images, followed by the extraction of radiomics features. A two-stage model was developed: the first stage identifies csPCa using radiomics-based MRI, and the second integrates clinical indicators for Gleason grading. Model efficacy was evaluated by sensitivity, specificity, accuracy and area under the curve (AUC), with external validation on 100 patients.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The first-stage model demonstrated excellent diagnostic accuracy for csPCa, achieving AUCs of 0.989, 0.982 and 0.976 in the training, testing and external validation cohorts, respectively. The second-stage model exhibited commendable Gleason grading capabilities, with AUCs of 0.82, 0.844 and 0.83 across the same cohorts. Decision curve analysis supported the clinical applicability of both models.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This study validated the potential of T2W and ADC image radiomics features as biomarkers in distinguishing csPCa. Combining these features with clinical indicators for csPCa Gleason grading provides superior predictive performance and significant clinical benefit.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"72 1","pages":"93-105"},"PeriodicalIF":1.8,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jmrs.841","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142854351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond pink ribbons: The unmet needs of women with breast cancer.","authors":"Laura Feighan, Lesley MacDonald-Wicks, Robin Callister, Yolanda Surjan","doi":"10.1002/jmrs.849","DOIUrl":"https://doi.org/10.1002/jmrs.849","url":null,"abstract":"<p><p>Breast cancer is the most frequently diagnosed cancer worldwide. The treatment options for breast cancer can cause side effects and adversely impact quality of life. Side effects, including fatigue, pain, cognitive changes, and psychosocial complications, can be life altering and continue beyond treatment into survivorship. Traditionally, health professionals focused almost entirely on achieving cancer survival; however, due to significant success in cancer treatment outcomes, most women now live beyond their breast cancer treatment. Consequently, addressing side effects and compromises in quality of life are becoming more important issues to include in a comprehensive approach to breast cancer treatment. For women, these unmet needs may involve body image concerns, sexual dysfunction, and other lifestyle challenges, and may not have previously been given sufficient recognition or priority. It is necessary for us, as oncology healthcare professionals, to modify our delivery of cancer care and ensure that more comprehensive care is provided to women. By addressing women's unmet needs, we can contribute to achieving the United Nations' Sustainable Development Goals regarding improving health and equality. This commentary seeks to emphasise the advantages of providing comprehensive care for women with breast cancer and advocates for cancer care professionals to actively participate in initiating and implementing this care.</p>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142854403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Technique considerations for implementing volumetric-modulated arc therapy for total body irradiation within an Australian tertiary institution","authors":"Gabriella La Macchia BSc, DipMus, MRadTher,&nbsp;Clare Wan BSc, MRadTher,&nbsp;Joshua Dass MPH, MHM, FRANZCR, FRACMA,&nbsp;Mandy Taylor MBBS (Hons), FRANZCR,&nbsp;Gabor Neveri MSc,&nbsp;Malgorzata Skorska PhD","doi":"10.1002/jmrs.844","DOIUrl":"10.1002/jmrs.844","url":null,"abstract":"<p>Over the past decade, our institution delivered conventional total body irradiation (TBI) using Elekta's Monaco treatment planning system (TPS) with an extended SSD field arrangement and 18 megavoltage (MV) energy lateral fields. In 2020, there was a transition to the Eclipse™ treatment planning system and Truebeam® linear accelerators with 6 MV and 10 MV energies. These changes meant that essential components of the existing technique were unavailable for clinical use and a new approach to the institution technique was required to ensure continuation of service. The aim was to implement a volumetric-modulated arc therapy (VMAT) TBI technique using existing infrastructure, the new planning system and treatment hardware to continue providing a TBI service for patients of all ages, including those under general anaesthetic (GA). A multidisciplinary team within the institution was created to evaluate existing literature and to implement a VMAT TBI technique that was feasible within our institution. This article will discuss the resultant technique, the practicalities faced and the radiation therapy pathway within our institution.</p>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"72 1","pages":"165-172"},"PeriodicalIF":1.8,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jmrs.844","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142818315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Collaborative use of a 3D anatomy platform to motivate and enhance anatomy learning in first-year online medical sonography students","authors":"Michelle Fenech PhD, MSc, GDMed US, BApSc (Med Rad Imag),&nbsp;Nadia Mead PhD, MLitt, BA (Hons)","doi":"10.1002/jmrs.848","DOIUrl":"10.1002/jmrs.848","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Sonography students require a deep understanding of structural anatomy, including where structures sit relative to one another. Additionally, they need to learn the complex task of identifying structures on medical images including X-rays, computed tomography, magnetic resonance imaging and ultrasound imaging. Anatomy can be taught online, but learning can be challenging for students. Online three-dimensional (3D) anatomy platforms aid student learning, but research investigating how to use them effectively when teaching is scarce. This project evaluated the impact of incorporating a three-dimensional (3D) online anatomy platform into teaching relative structural anatomy and assist sonography students when learning how to recognise structures on medical images.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Sixty-one first-year sonography students within an articulated undergraduate and postgraduate medical sonography programme in Australia, studying anatomy online participated in this mixed methods study. The impact of using a 3D online anatomy platform on their conceptual 3D anatomy understanding of relative anatomy, development of medical image recognition skills and their learning experience was assessed via a Qualtrics survey.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Students who used this platform collaboratively enhanced their relative anatomy understanding and developed the skill of identifying structures from medical images. The scaffolded use of this platform generated enquiry discussions between teachers and students and made learning anatomy online a social and enjoyable experience.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Collaborative and interactive scaffolded use of 3D online anatomy platforms can motivate and encourage student questions and discussions, enabling social connections and enhancing their learning experience. Student enquiry skills were developed, and the more complex task of identifying structures from medical images was made achievable.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"72 2","pages":"202-208"},"PeriodicalIF":1.8,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jmrs.848","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142818378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pre-operative transcranial Doppler ultrasound assessment of cerebral collateral circulation in children undergoing veno-arterial extracorporeal membrane oxygenation or cardiac surgery.","authors":"Tristan Reddan, Michael Malouf, Prem Venugopal, Jennifer Powell","doi":"10.1002/jmrs.845","DOIUrl":"https://doi.org/10.1002/jmrs.845","url":null,"abstract":"<p><p>Children requiring veno-arterial extracorporeal membrane oxygenation (VA ECMO) or cardiac surgery often undergo cervical cannulation or carotid artery clamping, which can interrupt cerebral circulation. Inadequate collateral flow through the circle of Willis (CoW) may lead to cerebral ischaemia within the vascular territory and/or watershed regions. Pre-cannulation survey of the CoW using transcranial Doppler (TCD) ultrasound may be performed to predict and plan neuroprotection. It is important to note in this article TCD refers to Duplex or colour coded trans-cranial Doppler (TCCD) using radiology-based machines, which is distinct from the more traditional trans-cranial Doppler technique that does not incorporate a B-mode image. This article describes our technique, in use since 2019, to guide surgical approaches and neuroprotective measures when an incomplete CoW is identified. High-end radiology-based ultrasound platforms and various transducers are used to assess brain morphology and haemorrhage through the anterior fontanelle in neonates. TCD is performed with the highest frequency transducer possible, utilising Doppler imaging to visualise cerebral arteries. Manual carotid compression can be used to functionally assess collateral flow when segments appear aplastic or hypoplastic. Potential pitfalls include mistaking the anterior choroidal artery for a hypoplastic posterior communicating artery (PCommA). Since implementing this protocol 5 years ago, no catastrophic infarcts related to cervical cannulation have occurred. This technique provides a practical solution for pre-operative assessment of cerebral collateral circulation in children undergoing VA ECMO or cardiac surgery, allowing for consideration of neuroprotective measures and improving patient safety.</p>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142818313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Continuing Professional Development – Answers","authors":"","doi":"10.1002/jmrs.828","DOIUrl":"10.1002/jmrs.828","url":null,"abstract":"<p>Maximise your Continuing Professional Development (CPD) by reading the selected articles and answer the five questions. Please remember to self-claim your CPD and retain your supporting evidence.</p>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"71 4","pages":"616-617"},"PeriodicalIF":1.8,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11638349/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142818318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying non-clinical outcomes of ultra-hypofractionated breast radiotherapy in Western NSW-A narrative review.","authors":"Faith Yeo, Rachael Beldham-Collins, Paul Roth, Rodney Hammond","doi":"10.1002/jmrs.842","DOIUrl":"https://doi.org/10.1002/jmrs.842","url":null,"abstract":"<p><p>Ultra-Hypofractionated Whole Breast Radiotherapy (U-WBRT) has been proven to be a viable treatment option for breast cancer patients receiving radiation therapy, however, due to its novelty our understanding of its non-clinical benefits is still evolving. With increasing U-WBRT selection during COVID and in rural and regional settings such as the Western New South Wales Local Health District (WNSWLHD), it's important to quantify the savings when compared to other fractionation schedules (e.g. Conventional fractionation (C-WBRT) involving 25 fractions and Moderate hypofractionation (M-WBRT) with 15 fractions.) Using literature sourced from Medline, Embase, Pubmed and reports from relevant websites and organisations this narrative review investigates quantifiable methods of assessing non-clinical benefits of U-WBRT in rural settings according to the triple bottom line philosophy. This review was able to identify a standard set of quantifiable metrics that can compare the non-clinical benefits of various fractionation schedules, with relevance to a rural setting. These include: fractionation trends, financial subsidy, average linear accelerator (Linac) minutes, hospital visits, travel time and distance, Linac energy consumption, travel and Linac carbon emissions. By identifying these metrics, non-clinical benefits between the fractionation schedules can easily be quantified and compared.</p>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142794781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}