Mark F. McEntee

University College Cork

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Journal of Medical Radiation Sciences (2017)

Ryoko Suzuki Motoko Omura Shoko Takano Kengo Matsui Ashutosh Dixit

This editorial addresses the importance of incident reporting, checklists and a just culture to patient safety.

10.1002/jmrs.2017.64.issue-3

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Radiologists remember mountains better than radiographs, or do they?

Journal of Medical Imaging (2015)

Karla K. Evans Edith M. Marom Myrna C.B. Godoy Diana Palacio Tara Sagebiel

Expertise with encoding material has been shown to aid long-term memory for that material. It is not clear how relevant this expertise is for image memorability (e.g., radiologists' memory for radiographs), and how robust over time. In two studies, we tested scene memory using a standard long-term memory paradigm. One compared the performance of radiologists to naïve observers on two image sets, chest radiographs and everyday scenes, and the other radiologists' memory with immediate as opposed to delayed recognition tests using musculoskeletal radiographs and forest scenes. Radiologists' memory was better than novices for images of expertise but no different for everyday scenes. With the heterogeneity of image sets equated, radiologists' expertise with radiographs afforded them better memory for the musculoskeletal radiographs than forest scenes. Enhanced memory for images of expertise disappeared over time, resulting in chance level performance for both image sets after weeks of delay. Expertise with the material is important for visual memorability but not to the same extent as idiosyncratic detail and variability of the image set. Similar memory decline with time for images of expertise as for everyday scenes further suggests that extended familiarity with an image is not a robust factor for visual memorability.

Everyday Life

10.1117/1.jmi.3.1.011005

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Citations (10)

A review of mammographic positioning image quality criteria for the craniocaudal projection

British Journal of Radiology (2017)

Rhonda-Joy Sweeney Sarah Lewis Peter Hogg Mark F. McEntee

Detection of breast cancer is reliant on optimal breast positioning and the production of quality images. Two projections, the mediolateral oblique and craniocaudal (CC), are routinely performed. Determination of successful positioning and inclusion of all breast tissue is achieved through meeting stated image quality criteria. For the CC view, current image quality criteria are inconsistent. Absence of reliable anatomical markers, other than the nipple, further contribute to difficulties in assessing the quality of CC views. The aim of this paper was to explore published international quality standards to identify and find the origin of any CC positioning criteria which might provide for quantitative assessment. The pectoralis major (pectoral) muscle was identified as a key posterior anatomical structure to establish optimum breast tissue inclusion on mammographic projections. It forms the first two of the three main CC metrics that are frequently reported (1) visualization of the pectoral muscle, (2) measurement of the posterior nipple line and (3) depiction of retroglandular fat. This literature review explores the origin of the three metrics, and discusses three key publications, spanning 1992 to 1994, on which subsequent image quality standards have been based. The evidence base to support published CC metrics is sometimes not specified and more often, the same set of publications are cited, most often without critical evaluation. To conclude, there remains uncertainty if the metrics explored for the CC view support objective evaluation and reproducibility to confirm optimal breast positioning and quality images.

Oblique projection

10.1259/bjr.20170611

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Citations (21)

Strategies for dose reduction with specific clinical indications during computed tomography

Radiography (2020)

Stella Joyce Owen J. O’Connor M. Maher Mark F. McEntee

Increasing integration of computed tomography (CT) into routine patient care has escalated concerns regarding associated radiation exposure. Specific patient cohorts, particularly those with cystic fibrosis (CF) and Crohn's disease, have repeat exposures and thus have an increased risk of high lifetime cumulative effective dose exposures.Thoracic CT is the gold standard imaging method in the diagnosis, assessment and management of pulmonary disease. In the setting of CF, CT demonstrates increased sensitivity compared with pulmonary function tests and chest radiography. Furthermore, in specific cases of Crohn's disease, CT demonstrates diagnostic superiority over magnetic resonance imaging (MRI) for radiological evaluation.Low dose CT protocols have proven beneficial in the evaluation of CF, Crohn's disease and renal calculi, and in the follow up of testicular cancer patients. For individuals with chronic conditions warranting frequent radiological follow up, the focus must continue to be the incorporation of appropriate CT use into patient care. This is of particular importance for the paediatric population who are most susceptible to potential radiation induced malignancy.CT technological developments continue to focus on radiation dose optimisation. This article aims to highlight these advancements, which prioritise the acquisition of diagnostically satisfactory images with the least amount of radiation possible.

Gold standard (test)

10.1016/j.radi.2020.06.012

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Citations (19)

Guidance on good practice in authorship of journal publications

Radiography (2016)

Patrick Brennan Geoffrey Currie Georgia Halkett Peter Hogg L. Holden

Excellence

Publication

10.1016/j.radi.2016.05.004

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Citations (3)

AI implementation in the UK landscape: Knowledge of AI governance, perceived challenges and opportunities, and ways forward for radiographers

Radiography (2024)

Nikolaos Stogiannos Tracy O’Regan Erica Scurr Lia Litosseliti Michael Pogose

IntroductionDespite the rapid increase of AI-enabled applications deployed in clinical practice, many challenges exist around AI implementation, including the clarity of governance frameworks, usability of validation of AI models, and customisation of training for radiographers. This study aimed to explore the perceptions of diagnostic and therapeutic radiographers, with existing theoretical and/or practical knowledge of AI, on issues of relevance to the field, such as AI implementation, including knowledge of AI governance and procurement, perceptions about enablers and challenges and future priorities for AI adoption.MethodsAn online survey was designed and distributed to UK-based qualified radiographers who work in medical imaging and/or radiotherapy and have some previous theoretical and/or practical knowledge of working with AI. Participants were recruited through the researchers' professional networks on social media with support from the AI advisory group of the Society and College of Radiographers. Survey questions related to AI training/education, knowledge of AI governance frameworks, data privacy procedures, AI implementation considerations, and priorities for AI adoption. Descriptive statistics were employed to analyse the data, and chi-square tests were used to explore significant relationships between variables.ResultsIn total, 88 valid responses were received. Most radiographers (56.6 %) had not received any AI-related training. Also, although approximately 63 % of them used an evaluation framework to assess AI models' performance before implementation, many (36.9 %) were still unsure about suitable evaluation methods. Radiographers requested clearer guidance on AI governance, ample time to implement AI in their practice safely, adequate funding, effective leadership, and targeted support from AI champions. AI training, robust governance frameworks, and patient and public involvement were seen as priorities for the successful implementation of AI by radiographers.ConclusionAI implementation is progressing within radiography, but without customised training, clearer governance, key stakeholder engagement and suitable new roles created, it will be hard to harness its benefits and minimise related risks.Implications for practiceThe results of this study highlight some of the priorities and challenges for radiographers in relation to AI adoption, namely the need for developing robust AI governance frameworks and providing optimal AI training.

10.1016/j.radi.2024.01.019

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Citations (10)

Knowledge and practice of computed tomography exposure parameters amongst radiographers in Jordan

Computers in Biology and Medicine (2018)

Mohammad Rawashdeh Mark F. McEntee Maha Zaitoun Mostafa Abdelrahman Patrick Brennan

Bachelor

Demographics

10.1016/j.compbiomed.2018.09.020

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Citations (24)

Radiographers' perspectives on clinical supervision of students in Ireland

Radiography (2023)

Rena Young Mark F. McEntee Deirdre Bennett

10.1016/j.radi.2022.12.009

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Citations (11)

Breast Screen New South Wales Generally Demonstrates Good Radiologic Viewing Conditions

Journal of Digital Imaging (2013)

BaoLin Pauline Soh Warwick Lee Jennifer Diffey Mark F. McEntee Peter Kench

Workstation

Confusion

10.1007/s10278-013-9571-1

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Citations (6)

Indirect detection of pulmonary nodule on low-pass filtered and original x-ray images during limited and unlimited display times

Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (2012)

Mariusz W. Pietrzyk Mark F. McEntee Michael G. Evanoff Patrick Brennan

Aim: This study evaluates the assumption that global impression is created based on low spatial frequency components of posterior-anterior chest radiographs. Background: Expert radiologists precisely and rapidly allocate visual attention on pulmonary nodules chest radiographs. Moreover, the most frequent accurate decisions are produced in the shortest viewing time, thus, the first hundred milliseconds of image perception seems be crucial for correct interpretation. Medical image perception model assumes that during holistic analysis experts extract information based on low spatial frequency (SF) components and creates a mental map of suspicious location for further inspection. The global impression results in flagged regions for detailed inspection with foveal vision. Method: Nine chest experts and nine non-chest radiologists viewed two sets of randomly ordered chest radiographs under 2 timing conditions: (1) 300ms; (2) free search in unlimited time. The same radiographic cases of 25 normal and 25 abnormal digitalized chest films constituted two image sets: low-pass filtered and unfiltered. Subjects were asked to detect nodules and rank confidence level. MRMC ROC DBM analyses were conducted. Results: Experts had improved ROC AUC while high SF components are displayed (p=0.03) or while low SF components were viewed under unlimited time (p=0.02) compared with low SF 300mSec viewings. In contrast, non-chest radiologists showed no significant changes when high SF are displayed under flash conditions compared with free search or while low SF components were viewed under unlimited time compared with flash. Conclusion: The current medical image perception model accurately predicted performance for non-chest radiologists, however chest experts appear to benefit from high SF features during the global impression.

10.1117/12.911639

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