Journal of Medical Radiation Sciences最新文献

{"title":"ePortfolios: Enhancing confidence in student radiographers' communication of radiographic anatomy and pathology. A cross-sectional study","authors":"Magdalena Dolic BRadMedImag (Hons),&nbsp;Yaxuan Peng BRadMedImag (Hons),&nbsp;Keshav Dhingra BRadMedImag (Hons),&nbsp;Kristal Lee BRadMedImag (Hons),&nbsp;John McInerney HDipHPE. GCHPE, PGCertIV Leadership and Management, PGCert CT Imaging, PGDip IV cannulation, BSc(Rad) Hons","doi":"10.1002/jmrs.787","DOIUrl":"10.1002/jmrs.787","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>In 2020, the Medical Radiation Practice Board of Australia made several revisions to its professional capabilities. To address this, medical radiation practitioners, including diagnostic radiographers, are required to escalate urgent findings in all radiographic settings. However, the confidence of radiographers in articulating descriptions of radiographic findings varies despite this requirement. This cross-sectional study explores how the implementation of eportfolio affects student self-perceived confidence in identifying and describing radiographic findings in both an academic and a clinical setting.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A Qualtrics survey was distributed to second-year radiography students who had used eportfolios. The survey comprised of four questions using a Likert-scale and one open-ended question. Quantitative data were analysed using the Wilcoxon signed-rank test and qualitative data was thematically assessed.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Overall, 55 of 65 radiographic students (85%) completed the survey. Confidence (strongly agree and agree) decreased from 89% to 74% between academic and clinical environments when identifying abnormalities, and 89% to 73% when describing findings. This finding highlights the challenges students face when in the clinical environment. Wilcoxon signed rank test analysed a statistically significant relation between the two environments (<i>P</i> &lt; 0.05). However, the relationship between identifying and describing skills was not statistically significant (<i>P</i> &gt; 0.05). Following a review of the qualitative data, three recurring themes were identified among responses.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>ePortfolios assist in improving confidence in identification and description of radiographic abnormalities, particularly in an academic setting. The clinical environment presents unique challenges which may limit student clinical performance; however, this requires further investigation.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"71 3","pages":"403-411"},"PeriodicalIF":1.8,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jmrs.787","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140855114","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":"Improved deep learning for automatic localisation and segmentation of rectal cancer on T2-weighted MRI","authors":"Zaixian Zhang PhD,&nbsp;Junqi Han MS,&nbsp;Weina Ji MS,&nbsp;Henan Lou MS,&nbsp;Zhiming Li PhD,&nbsp;Yabin Hu PhD,&nbsp;Mingjia Wang PhD,&nbsp;Baozhu Qi MS,&nbsp;Shunli Liu PhD","doi":"10.1002/jmrs.794","DOIUrl":"10.1002/jmrs.794","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>The automatic segmentation approaches of rectal cancer from magnetic resonance imaging (MRI) are very valuable to relieve physicians from heavy workloads and enhance working efficiency. This study aimed to compare the segmentation accuracy of a proposed model with the other three models and the inter-observer consistency.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A total of 65 patients with rectal cancer who underwent MRI examination were enrolled in our cohort and were randomly divided into a training cohort (<i>n</i> = 45) and a validation cohort (<i>n</i> = 20). Two experienced radiologists independently segmented rectal cancer lesions. A novel segmentation model (AttSEResUNet) was trained on T2WI based on ResUNet and attention mechanisms. The segmentation performance of the AttSEResUNet, U-Net, ResUNet and U-Net with Attention Gate (AttUNet) was compared, using Dice similarity coefficient (DSC), Hausdorff distance (HD), mean distance to agreement (MDA) and Jaccard index. The segmentation variability of automatic segmentation models and inter-observer was also evaluated.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The AttSEResUNet with post-processing showed perfect lesion recognition rate (100%) and false recognition rate (0), and its evaluation metrics outperformed other three models for two independent readers (observer 1: DSC = 0.839 ± 0.112, HD = 9.55 ± 6.68, MDA = 0.556 ± 0.722, Jaccard index = 0.736 ± 0.150; observer 2: DSC = 0.856 ± 0.099, HD = 11.0 ± 10.1, MDA = 0.789 ± 1.07, Jaccard index = 0.673 ± 0.130). The segmentation performance of AttSEResUNet was comparable and similar to manual variability (DSC = 0.857 ± 0.115, HD = 10.0 ± 10.0, MDA = 0.704 ± 1.17, Jaccard index = 0.666 ± 0.139).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Comparing with other three models, the proposed AttSEResUNet model was demonstrated as a more accurate model for contouring the rectal tumours in axial T2WI images, whose variability was similar to that of inter-observer.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"71 4","pages":"509-518"},"PeriodicalIF":1.8,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jmrs.794","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140660443","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":"The importance of quality management systems in nuclear medicine departments","authors":"Kunthi Pathmaraj MSc (Radiation Physics), BSc Applied Science (Medical Radiations), Grad Dip Computer Science","doi":"10.1002/jmrs.793","DOIUrl":"10.1002/jmrs.793","url":null,"abstract":"<p>Quality management systems (QMS) in nuclear medicine is an essential component of the Quality program and is instrumental in the safe delivery of a high standard clinical service. The IAEA QUANUM program is a nuclear medicine specific audit program that can be used to assess the standards of a nuclear medicine department and its service delivery. Regular internal and external audits are encouraged as part of the QMS.\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"71 2","pages":"167-169"},"PeriodicalIF":2.1,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jmrs.793","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140682113","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":"Cut-off value for a normal posterior tibial nerve to diagnose tarsal tunnel syndrome amongst people of different race in Pretoria, South Africa","authors":"Natasha Roos B Tech (Radiography),&nbsp;Tintswalo Brenda Mahlaola M Tech (Radiography),&nbsp;Lynne Hazell PhD (Health Sciences)","doi":"10.1002/jmrs.792","DOIUrl":"10.1002/jmrs.792","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Posterior tibial nerve (PTN) cross-sectional area (CSA) reference values for the diagnosis of tarsal tunnel syndrome (TTS) using ultrasound imaging exist in several countries but not in South Africa (SA). Therefore, the objective was to measure the CSA reference values for PTN in SA.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Ultrasound CSA measurements of PTN in both ankles on 112 participants were performed, the mean measurement was recorded, and the effect of race, age, gender, and body mass index (BMI) were recorded.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In this study, the primary variables age and BMI affect the CSA measurement of the PTN. A positive correlation was found between PTN asymptomatic size and age (<i>r</i> = 0.196, <i>P</i> &lt; 0.05), size and BMI (<i>r</i> = 0.200, <i>P</i> &lt; 0.05). Age (categories) had a mean value of 3.17 for the age group 36–45 years (95% confidence interval (CI) 2.9–3.4). The mean BMI was 30.0 kg/m² (CI 28.57–31.08). As for the asymptomatic PTN, a mean CSA reference value of 0.10 cm² was obtained.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>With increase in age and BMI, a greater PTN measurement will occur. Race appears to be a contributing factor, but further research is needed in this regard. The reference CSA value for normal PTN should be set at 0.10 cm² for all racial groups for a basic musculoskeletal ultrasound exam protocol in South Africa.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"71 3","pages":"396-402"},"PeriodicalIF":1.8,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jmrs.792","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140681619","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 and the future of radiotherapy planning: The Australian radiation therapists prepare to be ready","authors":"Vanessa Panettieri PhD,&nbsp;Giovanna Gagliardi PhD","doi":"10.1002/jmrs.791","DOIUrl":"10.1002/jmrs.791","url":null,"abstract":"<p>The use of artificial intelligence (AI) solutions is rapidly changing the way radiation therapy tasks, traditionally relying on human skills, are approached by enabling fast automation. This evolution represents a paradigm shift in all aspects of the profession, particularly for treatment planning applications, opening up opportunities but also causing concerns for the future of the multidisciplinary team. In Australia, radiation therapists (RTs), largely responsible for both treatment planning and delivery, are discussing the impact of the introduction of AI and the potential developments in the future of their role. As medical physicists, who are part of the multidisciplinary team, in this editorial we reflect on the considerations of RTs, and on the implications of this transition to AI.\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"71 2","pages":"174-176"},"PeriodicalIF":2.1,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jmrs.791","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140679761","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":"Eliciting the views of left breast cancer patients' receiving deep inspiration breath hold radiation therapy to inform the design of multimedia education and improve patient-centred care for prospective patients","authors":"Kathleene Dower BApSc (MRS), MHSM,&nbsp;Georgia K.B. Halkett PhD, FASMIRT, BMedRad(Hons), GAICD,&nbsp;Haryana Dhillon BSc MA (Psych), PhD,&nbsp;Diana Naehrig Dr.Med., FMH RadOnc, MSc CoachPsych, PhD,&nbsp;Moira O'Connor BA (Hons), MSc, PhD","doi":"10.1002/jmrs.790","DOIUrl":"10.1002/jmrs.790","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>The currently accepted best practice radiation treatment for left breast cancer patients is Deep Inspiration Breath Hold (DIBH) where patients hold a deep breath to reduce late cardiac and pulmonary effects from treatment. DIBH can be challenging and induce or exacerbate anxiety in patients due to the perceived pressure to reduce radiation treatment side effects. This study explored the experiences of patients treated with Deep Inspiration Breath Hold Radiation Therapy (DIBH-RT) to improve patient-centred care and inform the design of multimedia educational tools for future patients undergoing DIBH.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This descriptive qualitative study was underpinned by a social constructivist approach to create new educational and patient care approaches based on previous patients' experiences. Semi-structured interviews were conducted with patients who had completed DIBH-RT for breast cancer. Data was analysed with reflexive thematical analysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Twenty-two patients were interviewed with five key themes identified: (1) informational needs, (2) care needs, (3) autonomy, (4) DIBH performance influencers and (5) other centredness. Recommendations were derived from these themes to improve future treatments of DIBH patients. These recommendations revolved around improvements to education, patient-centred care and strategies to improve self-efficacy with breath holding.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Patients offer a wealth of knowledge regarding their lived experiences with treatment which can enhance future patients' experiences if incorporated into their education and care. Eliciting patients' views of their DIBH-RT treatment highlighted the need to improve patient self-efficacy with DIBH through familiarity with their planned treatment from new multimedia education, and foster patient care to enhance their experience.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"71 3","pages":"384-395"},"PeriodicalIF":1.8,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jmrs.790","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140694613","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":"Sponsor Acknowledgement","authors":"","doi":"10.1002/jmrs.765","DOIUrl":"https://doi.org/10.1002/jmrs.765","url":null,"abstract":"","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"71 S1","pages":"1-2"},"PeriodicalIF":2.1,"publicationDate":"2024-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jmrs.765","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140537640","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":"Poster Abstracts","authors":"","doi":"10.1002/jmrs.767","DOIUrl":"https://doi.org/10.1002/jmrs.767","url":null,"abstract":"","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"71 S1","pages":"100-132"},"PeriodicalIF":2.1,"publicationDate":"2024-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jmrs.767","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140537642","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":"Oral Abstracts","authors":"","doi":"10.1002/jmrs.766","DOIUrl":"https://doi.org/10.1002/jmrs.766","url":null,"abstract":"","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"71 S1","pages":"3-99"},"PeriodicalIF":2.1,"publicationDate":"2024-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jmrs.766","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140537641","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":"Breast percent density changes in digital mammography pre- and post-radiotherapy","authors":"Sana Mohammadi MD,&nbsp;Sadegh Ghaderi PhD,&nbsp;Mahdi Mohammadi PhD,&nbsp;Hamid Ghaznavi MSc,&nbsp;Kamal Mohammadian MD","doi":"10.1002/jmrs.788","DOIUrl":"10.1002/jmrs.788","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Breast cancer (BC), the most frequently diagnosed malignancy among women worldwide, presents a public health challenge and affects mortality rates. Breast-conserving therapy (BCT) is a common treatment, but the risk from residual disease necessitates radiotherapy. Digital mammography monitors treatment response by identifying post-operative and radiotherapy tissue alterations, but accurate assessment of mammographic density remains a challenge. This study used OpenBreast to measure percent density (PD), offering insights into changes in mammographic density before and after BCT with radiation therapy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This retrospective analysis included 92 female patients with BC who underwent BCT, chemotherapy, and radiotherapy, excluding those who received hormonal therapy or bilateral BCT. Percent/percentage density measurements were extracted using OpenBreast, an automated software that applies computational techniques to density analyses. Data were analysed at baseline, 3 months, and 15 months post-treatment using standardised mean difference (SMD) with Cohen's <i>d</i>, chi-square, and paired sample <i>t</i>-tests. The predictive power of PD changes for BC was measured based on the receiver operating characteristic (ROC) curve analysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The mean age was 53.2 years. There were no significant differences in PD between the periods. Standardised mean difference analysis revealed no significant changes in the SMD for PD before treatment compared with 3- and 15-months post-treatment. Although PD increased numerically after radiotherapy, ROC analysis revealed optimal sensitivity at 15 months post-treatment for detecting changes in breast density.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This study utilised an automated breast density segmentation tool to assess the changes in mammographic density before and after BC treatment. No significant differences in the density were observed during the short-term follow-up period. However, the results suggest that quantitative density assessment could be valuable for long-term monitoring of treatment effects. The study underscores the necessity for larger and longitudinal studies to accurately measure and validate the effectiveness of quantitative methods in clinical BC management.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"71 3","pages":"375-383"},"PeriodicalIF":1.8,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jmrs.788","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140747585","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}