Jermayne Takapautolo BAppSci (Med Rad Tech) (Hons), Michael Neep BAppSci (Med Rad Tech), MSci, PhD, AFHEA, Deborah Starkey DipAppSc (DiagRad) MAppSc (MedImagTech) MEd (HigherEd) FASMIRT SFHEA
Introduction
Diagnostic errors in the emergency departments can have major implications on patient outcomes. Preliminary Image Evaluation (PIE) is a brief comment written by a radiographer describing an acute or traumatic pathology on a radiograph and can be used to complement referrer's image interpretation in the absence of the radiologist report. Currently, no studies exist that focus their analysis on false-positive (FP) errors in PIE. The purpose of this study was to investigate the regions of the body that cause the most FP errors and recognise other areas in image interpretation that may need additional attention.
Methods
A longitudinal retrospective clinical audit was conducted to determine the accuracy of radiographer PIE's over 5 years from January 2016 to December 2020. PIE's were compared to the radiologist report to assess for diagnostic accuracy. FP and unsure errors were further categorised by anatomical region and age.
Results
Over this period, a sample size of 11,090 PIE audits were included in the study demonstrating an overall PIE accuracy of 87.7%. Foot, ankle and chest regions caused the most FP errors, while ankle, shoulder and elbow caused the most unsure cases. 76% of the unsure cases were negative for any pathology when compared to the radiologist report. The paediatric population accounted for 21.3% of FP cases and 33.6% of unsure cases.
Conclusion
Findings in this study should be used to tailor education specific to radiographer image interpretation. Improving radiography image interpretation skills can assist in improving referrer diagnostic accuracy, thus improving patient outcomes.
导言：急诊科的诊断错误会对患者的治疗效果产生重大影响。影像初步评估（PIE）是由放射技师撰写的简短评论，描述放射照片上的急性或创伤性病理变化，可用于在没有放射医师报告的情况下补充转诊医师的影像解释。目前，还没有研究重点分析 PIE 中的假阳性 (FP) 错误。本研究的目的是调查造成 FP 错误最多的身体部位，并识别图像判读中可能需要额外注意的其他部位：从 2016 年 1 月到 2020 年 12 月的 5 年间，进行了一次纵向回顾性临床审核，以确定放射技师 PIE 的准确性。将 PIE 与放射医师报告进行比较，以评估诊断准确性。根据解剖区域和年龄对FP和不确定错误进行进一步分类：在此期间，共有 11,090 份 PIE 审计样本纳入研究，显示总体 PIE 准确率为 87.7%。足部、踝部和胸部造成的 FP 错误最多，而踝部、肩部和肘部造成的不确定病例最多。与放射科医生的报告相比，76%的不确定病例为阴性。儿科人群占FP病例的21.3%，占不确定病例的33.6%：本研究的结果应用于针对放射技师图像解读的定制教育。提高放射摄影图像判读技能有助于提高转诊医生诊断的准确性，从而改善患者的预后。
{"title":"Analysing false-positive errors when Australian radiographers use preliminary image evaluation","authors":"Jermayne Takapautolo BAppSci (Med Rad Tech) (Hons), Michael Neep BAppSci (Med Rad Tech), MSci, PhD, AFHEA, Deborah Starkey DipAppSc (DiagRad) MAppSc (MedImagTech) MEd (HigherEd) FASMIRT SFHEA","doi":"10.1002/jmrs.809","DOIUrl":"10.1002/jmrs.809","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Diagnostic errors in the emergency departments can have major implications on patient outcomes. Preliminary Image Evaluation (PIE) is a brief comment written by a radiographer describing an acute or traumatic pathology on a radiograph and can be used to complement referrer's image interpretation in the absence of the radiologist report. Currently, no studies exist that focus their analysis on false-positive (FP) errors in PIE. The purpose of this study was to investigate the regions of the body that cause the most FP errors and recognise other areas in image interpretation that may need additional attention.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A longitudinal retrospective clinical audit was conducted to determine the accuracy of radiographer PIE's over 5 years from January 2016 to December 2020. PIE's were compared to the radiologist report to assess for diagnostic accuracy. FP and unsure errors were further categorised by anatomical region and age.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Over this period, a sample size of 11,090 PIE audits were included in the study demonstrating an overall PIE accuracy of 87.7%. Foot, ankle and chest regions caused the most FP errors, while ankle, shoulder and elbow caused the most unsure cases. 76% of the unsure cases were negative for any pathology when compared to the radiologist report. The paediatric population accounted for 21.3% of FP cases and 33.6% of unsure cases.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Findings in this study should be used to tailor education specific to radiographer image interpretation. Improving radiography image interpretation skills can assist in improving referrer diagnostic accuracy, thus improving patient outcomes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"71 4","pages":"540-546"},"PeriodicalIF":1.8,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11638359/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141457427","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}
Christina Malamateniou PhD, MA, BSc (Hons), SFHEA, DIC, MAcadMEd
This is an exciting time to be working in healthcare and medical radiation sciences. This article discusses the potential benefits and risks of new technological interventions for patient benefit and outlines the need for co-production, governance and education to ensure these are used for advancing patients' well-being.
{"title":"Technology-enabled patient care in medical radiation sciences: the two sides of the coin","authors":"Christina Malamateniou PhD, MA, BSc (Hons), SFHEA, DIC, MAcadMEd","doi":"10.1002/jmrs.807","DOIUrl":"10.1002/jmrs.807","url":null,"abstract":"<p>This is an exciting time to be working in healthcare and medical radiation sciences. This article discusses the potential benefits and risks of new technological interventions for patient benefit and outlines the need for co-production, governance and education to ensure these are used for advancing patients' well-being.\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 3","pages":"326-329"},"PeriodicalIF":1.8,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jmrs.807","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141457428","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}
Shimon Prasad BMRS (RT), Linda J. Bell PhD, BAppSc (MRT), FASMIRT, Benjamin Zwan PhD, MSc (Med Phys), BSc (honours), BMath, Florence Ko BAppSc (MRT), Tayla Blackwell BMRS (RT), Kevin Connell BMRS (RT), Cameron Stanton MSc (Res), BMedRadPhys, Meegan Shepherd BAppSc (MRS) RT, MHlthSc (RT), MEdu (HPE), John Atyeo PhD, BSc (Psych), MHlthScEd, BA (Com), AssDipRadTech, Mark Stevens MBBS, BSc (Med), MMED (Pain Mgt), FRANZCR, Marita Morgia MBBS, FRANZCR
Introduction
The aim was to determine which immobilisation device improved inter-fraction reproducibly of pelvic tilt and required the least pre-treatment setup and planning interventions.
Methods
Sixteen patients were retrospectively reviewed, eight immobilised using the BodyFIX system (BodyFIX®, Elekta, Stockholm, Sweden) and eight using the Butterfly Board (BB) (Bionix Radiation Therapy, Toledo, OH, USA). The daily pre-treatment images were reviewed to assess setup variations between each patient and groups for pelvic tilt, pubic symphysis, sacral promontory and the fifth lumbar spine (L5).
Results
Compared with the planning CT, pelvic tilt for most patients was within ±2° using the BodyFIX and ± 4° for the BB. The Butterfly Board had a slightly higher variance both for patient-to-patient (standard deviation of the systematic error) and day-to-day error (standard deviation of the random error). Variance in position between individual patients and the two stabilisation devices were minimal in the anterior–posterior (AP) and superior–inferior (SI) direction for the pubic symphysis, sacral promontory and L5 spine. Re-imaged fractions due to pelvic tilt reduced by about half when BodyFIX was used (39.1% BB, 19.4% BodyFIX). One patient treated with the BB required a re-scan for pelvic tilt. Three patients required a re-scan for body contour variations (two using BodyFIX and one with the BB).
Conclusions
BodyFIX resulted in a more accurate inter-fraction setup and efficient treatment and is used as the standard stabilisation for gynaecological patients at our centre. It reduced the pelvic tilt variance and reduced the need for re-imaging pre-treatment by half.
{"title":"Comparing immobilisation devices in gynaecological external beam radiotherapy: improving inter-fraction reproducibility of pelvic tilt","authors":"Shimon Prasad BMRS (RT), Linda J. Bell PhD, BAppSc (MRT), FASMIRT, Benjamin Zwan PhD, MSc (Med Phys), BSc (honours), BMath, Florence Ko BAppSc (MRT), Tayla Blackwell BMRS (RT), Kevin Connell BMRS (RT), Cameron Stanton MSc (Res), BMedRadPhys, Meegan Shepherd BAppSc (MRS) RT, MHlthSc (RT), MEdu (HPE), John Atyeo PhD, BSc (Psych), MHlthScEd, BA (Com), AssDipRadTech, Mark Stevens MBBS, BSc (Med), MMED (Pain Mgt), FRANZCR, Marita Morgia MBBS, FRANZCR","doi":"10.1002/jmrs.804","DOIUrl":"10.1002/jmrs.804","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>The aim was to determine which immobilisation device improved inter-fraction reproducibly of pelvic tilt and required the least pre-treatment setup and planning interventions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Sixteen patients were retrospectively reviewed, eight immobilised using the BodyFIX system (BodyFIX®, Elekta, Stockholm, Sweden) and eight using the Butterfly Board (BB) (Bionix Radiation Therapy, Toledo, OH, USA). The daily pre-treatment images were reviewed to assess setup variations between each patient and groups for pelvic tilt, pubic symphysis, sacral promontory and the fifth lumbar spine (L5).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Compared with the planning CT, pelvic tilt for most patients was within ±2° using the BodyFIX and ± 4° for the BB. The Butterfly Board had a slightly higher variance both for patient-to-patient (standard deviation of the systematic error) and day-to-day error (standard deviation of the random error). Variance in position between individual patients and the two stabilisation devices were minimal in the anterior–posterior (AP) and superior–inferior (SI) direction for the pubic symphysis, sacral promontory and L5 spine. Re-imaged fractions due to pelvic tilt reduced by about half when BodyFIX was used (39.1% BB, 19.4% BodyFIX). One patient treated with the BB required a re-scan for pelvic tilt. Three patients required a re-scan for body contour variations (two using BodyFIX and one with the BB).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>BodyFIX resulted in a more accurate inter-fraction setup and efficient treatment and is used as the standard stabilisation for gynaecological patients at our centre. It reduced the pelvic tilt variance and reduced the need for re-imaging pre-treatment by half.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"71 4","pages":"529-539"},"PeriodicalIF":1.8,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11638372/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141419510","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}
Sérgio Miravent, Carmen Jiménez, Narciso Barbancho, Manuel Duarte Lobo, Teresa Figueiredo, Carla Gomes, Ion Ratusneac, João Mário Gonçalves, Corina Hasnas, Rui de Almeida
Introduction: Renal Point-of-Care Ultrasound (POCUS) is a screening modality that aids in clinical decision-making for patients with suspected renal colic. This study intends to compare the accuracy and pertinence of sonographic findings obtained by a sonographer in a Basic Emergency Service (BES) with the imaging findings at the Referral Hospital (RH).
Methods: Thirty-one patients suspected of having renal pathology underwent initial sonography screening with POCUS at the BES and were subsequently referred to the RH for additional imaging examinations. The results of both examinations were compared to verify whether the findings from the BES were confirmed by the radiologist in the RH and to ensure that the patient referrals from BES to RH were appropriate.
Results: In our sample, the majority of patients (80%) exhibited varying degrees of pyelocaliceal distension, with nearly half (48%) patients presenting obstructions. A strong association between the sonographic findings in the BES and the RH was found in the variables 'Dilatation of pyelocaliceal system' (V = 0.895; P = 0.00), 'Simple cystic formation' (V = 0.878; P = 0.000), respectively. There was a statistically significant correlation between BES and RH findings, indicating a strong association between these two variables, respectively (k = 0.890; P = 0.000) and (k = 0.870; P = 0.000). There was also a strong statistically significant correlation in the ultrasonographic findings between BES and RH performers (k = 0.890; P = 0.000 and k = 0.870; P = 0.000). In this research, an achieved sensitivity of 96% and a specificity of 85% were demonstrated in the identification of pyelocaliceal dilatation.
Conclusion: Renal POCUS screening successfully detected abnormalities in the urinary system of patients suspected of having renal colic. The sonographic findings at the BES had a good correlation with the complementary imaging results obtained at the RH in Portugal. These results suggest that Radiographers/Sonographers can have an important role in the preliminary assessment of urgent renal pathology in remote areas, contributing to a correct referral and early treatment.
{"title":"Renal screening sonography-A comparative study in a Portuguese basic emergency service.","authors":"Sérgio Miravent, Carmen Jiménez, Narciso Barbancho, Manuel Duarte Lobo, Teresa Figueiredo, Carla Gomes, Ion Ratusneac, João Mário Gonçalves, Corina Hasnas, Rui de Almeida","doi":"10.1002/jmrs.802","DOIUrl":"https://doi.org/10.1002/jmrs.802","url":null,"abstract":"<p><strong>Introduction: </strong>Renal Point-of-Care Ultrasound (POCUS) is a screening modality that aids in clinical decision-making for patients with suspected renal colic. This study intends to compare the accuracy and pertinence of sonographic findings obtained by a sonographer in a Basic Emergency Service (BES) with the imaging findings at the Referral Hospital (RH).</p><p><strong>Methods: </strong>Thirty-one patients suspected of having renal pathology underwent initial sonography screening with POCUS at the BES and were subsequently referred to the RH for additional imaging examinations. The results of both examinations were compared to verify whether the findings from the BES were confirmed by the radiologist in the RH and to ensure that the patient referrals from BES to RH were appropriate.</p><p><strong>Results: </strong>In our sample, the majority of patients (80%) exhibited varying degrees of pyelocaliceal distension, with nearly half (48%) patients presenting obstructions. A strong association between the sonographic findings in the BES and the RH was found in the variables 'Dilatation of pyelocaliceal system' (V = 0.895; P = 0.00), 'Simple cystic formation' (V = 0.878; P = 0.000), respectively. There was a statistically significant correlation between BES and RH findings, indicating a strong association between these two variables, respectively (k = 0.890; P = 0.000) and (k = 0.870; P = 0.000). There was also a strong statistically significant correlation in the ultrasonographic findings between BES and RH performers (k = 0.890; P = 0.000 and k = 0.870; P = 0.000). In this research, an achieved sensitivity of 96% and a specificity of 85% were demonstrated in the identification of pyelocaliceal dilatation.</p><p><strong>Conclusion: </strong>Renal POCUS screening successfully detected abnormalities in the urinary system of patients suspected of having renal colic. The sonographic findings at the BES had a good correlation with the complementary imaging results obtained at the RH in Portugal. These results suggest that Radiographers/Sonographers can have an important role in the preliminary assessment of urgent renal pathology in remote areas, contributing to a correct referral and early treatment.</p>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141419512","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}
Maximise your CPD by reading the following selected article and answer the five questions. Please remember to self-claim your CPD and retain your supporting evidence. Answers will be available via the QR code and published in JMRS – Volume 71, Issue 4, December 2024.
{"title":"Continuing Professional Development - Medical Imaging","authors":"","doi":"10.1002/jmrs.805","DOIUrl":"10.1002/jmrs.805","url":null,"abstract":"<p>Maximise your CPD by reading the following selected article and answer the five questions. Please remember to self-claim your CPD and retain your supporting evidence. Answers will be available via the QR code and published in JMRS – Volume 71, Issue 4, December 2024.</p><p>Scan this QR code to find the answers.</p>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"71 3","pages":"491"},"PeriodicalIF":1.8,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jmrs.805","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141419511","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}
Maximise your CPD by reading the following selected article and answer the five questions. Please remember to self-claim your CPD and retain your supporting evidence. Answers will be available via the QR code and published in JMRS – Volume 71, Issue 4 December 2024.
{"title":"Continuing Professional Development - Radiation Therapy","authors":"","doi":"10.1002/jmrs.799","DOIUrl":"10.1002/jmrs.799","url":null,"abstract":"<p>Maximise your CPD by reading the following selected article and answer the five questions. Please remember to self-claim your CPD and retain your supporting evidence. Answers will be available via the QR code and published in JMRS – Volume 71, Issue 4 December 2024.</p><p>Scan this QR code to find the answers.</p>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"71 2","pages":"319"},"PeriodicalIF":2.1,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jmrs.799","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141296267","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}
Daniel Serra MSc, BSc, Michael J Neep PhD, MSc, BApp Sci(Med Rad Tech), Elaine Ryan PhD, MSc, BSc (Hons), PGDip(IPEM)
Introduction
Reject analysis in digital radiography helps guide the training of staff to reduce patient radiation dose and improve department efficiency. The purpose of this study was to perform a multi-centre, vendor agnostic reject analysis across different room usage types, and to provide benchmarks for comparison.
Methods
Retrospective reject and exposure log data were collected via USB from fixed general X-ray systems across multiple Australian sites, for collation and analysis. The overall reject rate, local reject reference level, absolute and relative reject rates for body part categories, reject rates by room usage types and the reject rate for each reason of rejection were calculated.
Results
Data were collected from 44 X-ray systems, across 11 hospitals. A total of 2,031,713 acquired images and 172,495 rejected images were included. The median reject rate was 9.1%. The local reject reference level (LRRL), set as the 75th percentile of all reject rates, was 10.6%. Median reject rates by room type were emergency (7.4%), inpatients + outpatients (9.6%), outpatients (9.2%), and hybrid (10.1%). The highest absolute reject rates by body part were chest (2.1%) and knee (1.4%). The highest relative rates by body part were knee (18.1%) and pelvis (17.2%). The most frequent reasons for image rejection were patient positioning (76%) and patient motion (7.5%).
Conclusions
The results compare well with previously published data. The range of reject rates highlights the need to analyse typical reject rates in different ways. With analysis feedback to participating sites and the implementation of standardised reject reasons, future analysis should monitor whether reject rates reduce.
介绍：数字放射摄影中的剔除分析有助于指导员工培训，从而减少患者辐射剂量并提高部门效率。本研究的目的是针对不同的房间使用类型进行多中心、不受供应商影响的剔除分析，并提供比较基准：方法：通过 USB 从澳大利亚多个地点的固定普通 X 光系统收集回顾性剔除和曝光日志数据，并进行整理和分析。方法：通过 USB 从澳大利亚多个地点的固定普通 X 光系统收集回顾性剔除率和曝光日志数据，以便进行整理和分析：数据收集自 11 家医院的 44 个 X 光系统。结果：数据收集自 11 家医院的 44 套 X 光系统，共获取 2,031,713 张图像和 172,495 张剔除图像。剔除率中位数为 9.1%。本地剔除参考水平（LRRL）设定为所有剔除率的第 75 百分位数，为 10.6%。按病房类型划分，中位废片率分别为急诊（7.4%）、住院+门诊（9.6%）、门诊（9.2%）和混合型（10.1%）。按身体部位划分，绝对拒收率最高的是胸部（2.1%）和膝部（1.4%）。身体各部位相对拒收率最高的是膝关节（18.1%）和骨盆（17.2%）。图像拒绝的最常见原因是患者的体位（76%）和患者的运动（7.5%）：结论：研究结果与之前公布的数据对比良好。拒收率的范围凸显了以不同方式分析典型拒收率的必要性。通过对参与地点的分析反馈以及标准化拒收原因的实施，未来的分析应能监测拒收率是否降低。
{"title":"Multi-centre digital radiography reject analysis for different clinical room use types: The establishment of local reject reference levels for public hospital departments","authors":"Daniel Serra MSc, BSc, Michael J Neep PhD, MSc, BApp Sci(Med Rad Tech), Elaine Ryan PhD, MSc, BSc (Hons), PGDip(IPEM)","doi":"10.1002/jmrs.796","DOIUrl":"10.1002/jmrs.796","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Reject analysis in digital radiography helps guide the training of staff to reduce patient radiation dose and improve department efficiency. The purpose of this study was to perform a multi-centre, vendor agnostic reject analysis across different room usage types, and to provide benchmarks for comparison.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Retrospective reject and exposure log data were collected via USB from fixed general X-ray systems across multiple Australian sites, for collation and analysis. The overall reject rate, local reject reference level, absolute and relative reject rates for body part categories, reject rates by room usage types and the reject rate for each reason of rejection were calculated.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Data were collected from 44 X-ray systems, across 11 hospitals. A total of 2,031,713 acquired images and 172,495 rejected images were included. The median reject rate was 9.1%. The local reject reference level (LRRL), set as the 75<i>th</i> percentile of all reject rates, was 10.6%. Median reject rates by room type were emergency (7.4%), inpatients + outpatients (9.6%), outpatients (9.2%), and hybrid (10.1%). The highest absolute reject rates by body part were chest (2.1%) and knee (1.4%). The highest relative rates by body part were knee (18.1%) and pelvis (17.2%). The most frequent reasons for image rejection were patient positioning (76%) and patient motion (7.5%).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The results compare well with previously published data. The range of reject rates highlights the need to analyse typical reject rates in different ways. With analysis feedback to participating sites and the implementation of standardised reject reasons, future analysis should monitor whether reject rates reduce.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"71 3","pages":"412-420"},"PeriodicalIF":1.8,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jmrs.796","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141283893","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}
Laura Di Michele GradDipHM, BMedRadSc(DR), SFHEA, Amani Bell PhD, BSc (Hons), GradCertHigherEd, SFHEA, Kate Thomson PhD, GradCertEdStudies (HigherEd), MIH (Dist), BPsych (Hons), FHERDSA, SFHEA, Warren Reed PhD, PGCert TLHE, BSc (Hons)
Evidence-based practice (EBP) has a vital role to play in improving outcomes for patients, organisations and individual practitioners. Unfortunately, within diagnostic radiography, literature consistently demonstrates that positive EBP is not the norm. This editorial discusses a strategy for fostering cultural change within the profession to improve EBP.
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Ke Cao PhD (Melb), Josephine Yeung BPharm (Hons), Yasser Arafat MS (Usyd), FRACS, Jing Qiao MD, Richard Gartrell MS, FRACS, Mobin Master FRANZCR, MBBS, Justin M. C. Yeung DM, FRACS, Paul N. Baird PhD (Lond)
Introduction
This study aimed to evaluate the accuracy of our own artificial intelligence (AI)-generated model to assess automated segmentation and quantification of body composition-derived computed tomography (CT) slices from the lumber (L3) region in colorectal cancer (CRC) patients.
Methods
A total of 541 axial CT slices at the L3 vertebra were retrospectively collected from 319 patients with CRC diagnosed during 2012–2019 at a single Australian tertiary institution, Western Health in Melbourne. A two-dimensional U-Net convolutional network was trained on 338 slices to segment muscle, visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). Manual reading of these same slices of muscle, VAT and SAT was created to serve as ground truth data. The Dice similarity coefficient was used to assess the U-Net-based segmentation performance on both a validation dataset (68 slices) and a test dataset (203 slices). The measurement of cross-sectional area and Hounsfield unit (HU) density of muscle, VAT and SAT were compared between two methods.
Results
The segmentation for muscle, VAT and SAT demonstrated excellent performance for both the validation (Dice similarity coefficients >0.98, respectively) and test (Dice similarity coefficients >0.97, respectively) datasets. There was a strong positive correlation between manual and AI segmentation measurements of body composition for both datasets (Spearman's correlation coefficients: 0.944–0.999, P < 0.001).
Conclusions
Compared to the gold standard, this fully automated segmentation system exhibited a high accuracy for assessing segmentation and quantification of abdominal muscle and adipose tissues of CT slices at the L3 in CRC patients.
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Maximise your CPD by reading the following selected article and answer the five questions. Please remember to self-claim your CPD and retain your supporting evidence. Answers will be available via the QR code and published in JMRS – Volume 71, Issue 4 December 2024.
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