Artificial intelligence and soft skills in radiation oncology: Data versus wisdom

Boon, Ian S; Lim, Jean S; Yap, Moi Hoon; Yong, T.P.T. Au; Boon, Cheng

doi:10.1016/j.jmir.2020.08.011

Cited by 7 publications

(7 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It would also be interesting to think about national or international initiatives offering specific soft skills courses for RO and RTT to fill this gap. This is important because we know that although the various tasks of RO and RTT are becoming more and more automated and artificial intelligence (AI) is in full expansion, the fact remains that patients like human contact with their caregivers and that soft skills like good communication and empathy are the basis of good patient care [ 19 , 20 ].…”

Section: Discussionmentioning

confidence: 99%

Training of radiotherapy professionals: status, content, satisfaction and improvement suggestions in the Greater Region

et al. 2022

View full text Add to dashboard Cite

Background The initial training of Radiation Oncology professionals can vary widely across Europe. The aim of this study was to assess the status and content of the initial training programs currently implemented in the Greater Region: Lorraine (Nancy, France), Saarland (Homburg, Germany), Luxembourg, and Liège (Wallonia, Belgium). Methods A survey was developed to investigate (1) the overall satisfaction, learning objectives, and teaching methods used during initial training programs and (2) the perceptions of the importance of key professional competencies as described by the CanMEDS (a framework that identifies and describes the abilities physicians require to effectively meet the health care needs of the people they serve). In addition, open-ended questions were used to elicit opinions on room for improvement. Participants (N = 38) were physicians (radiation oncologists (RO) seniors and residents) and radiation therapists (RTTs). Results Only 21.1% of the respondents declared having acquired all the competencies required for their professional practice during their initial training. Heterogeneity in teaching methods was noted within professional programs but there is no difference between those from RO and RTT in the teaching of technical and relational skills. Relational skills were not addressed in a range of 39.5–57.9% of respondent’s curricula. More practical lessons were deemed necessary to improve radiotherapy (RT) training programs. Conclusions Radiation oncology professionals expressed the need for more practical teaching, especially in the training of non-technical skills. Regarding the perceived importance of professional aptitudes, radiation oncology professionals highlighted medical and relational skills as the most important competencies.

show abstract

Section: Discussionmentioning

confidence: 99%

Training of radiotherapy professionals: status, content, satisfaction and improvement suggestions in the Greater Region

et al. 2022

View full text Add to dashboard Cite

show abstract

“…AAPM Report Task Group 71 reports on the formalism for calculating monitor units. 1 AAPM Task Group 114 reports on methods and requirements for verification of data for conformal external beam plans. 2 The need for monitor unit verification programs was identified early in the adoption of IMRT treatment planning and delivery techniques.…”

Section: Statement Of the Problem And Tg Chargesmentioning

confidence: 99%

“…48 In MRS applications, smaller signals from the targeted metabolites are weak but of more clinical interest, and thus high magnetic field strengths are typically used to ensure adequate signal-to-noise ratio (SNR). 49 While several common nuclei in the human body are available for spectra acquisition, including 1 H, 13 C, 19 F, and 31 P, 1 H is often chosen for MRS since 1 H exists in a large number of metabolites and 1 H has a high concentration making it easier to detect than the other nuclei. In single voxel spectroscopy (SVS), a single voxel of tissue is chosen for spectrum derivation, and the voxel location is often determined by anatomical MRI guidance.…”

Section: Magnetic Resonance Spectroscopymentioning

confidence: 99%

“…Radiation therapy (RT) has been treating cancer for more than a century and has been adopted globally as an effective cancer management tool. It has been estimated that 50% of patients with cancer should receive RT in order to properly manage their diseases 1,2 . In the past decades, advances in technologies have significantly enhanced the landscape of modern RT.…”

Section: Introductionmentioning

confidence: 99%

“…It has been estimated that 50% of patients with cancer should receive RT in order to properly manage their diseases. 1,2 In the past decades, advances in technologies have significantly enhanced the landscape of modern RT. More specifically, rapid development and utilization of medical imaging, computerized treatment planning, and treatment delivery have enabled RT to evolve to ever increasingly complex forms of treatment delivery from conventional two-dimensional (2D) RT to threedimensional (3D) conformal RT (3D-CRT), intensitymodulated RT (IMRT), volumetric-modulated arc therapy (VMAT), image-guided radiotherapy (IGRT), and stereotactic body radiation therapy (SBRT).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Multi‐parametric MRI (mpMRI) for treatment response assessment of radiation therapy

Wang

Padgett

et al. 2021

Medical Physics

View full text Add to dashboard Cite

Magnetic resonance imaging (MRI) plays an important role in the modern radiation therapy (RT) workflow. In comparison with computed tomography (CT) imaging, which is the dominant imaging modality in RT, MRI possesses excellent soft‐tissue contrast for radiographic evaluation. Based on quantitative models, MRI can be used to assess tissue functional and physiological information. With the developments of scanner design, acquisition strategy, advanced data analysis, and modeling, multiparametric MRI (mpMRI), a combination of morphologic and functional imaging modalities, has been increasingly adopted for disease detection, localization, and characterization. Integration of mpMRI techniques into RT enriches the opportunities to individualize RT. In particular, RT response assessment using mpMRI allows for accurate characterization of both tissue anatomical and biochemical changes to support decision‐making in monotherapy of radiation treatment and/or systematic cancer management. In recent years, accumulating evidence have, indeed, demonstrated the potentials of mpMRI in RT response assessment regarding patient stratification, trial benchmarking, early treatment intervention, and outcome modeling. Clinical application of mpMRI for treatment response assessment in routine radiation oncology workflow, however, is more complex than implementing an additional imaging protocol; mpMRI requires additional focus on optimal study design, practice standardization, and unified statistical reporting strategy to realize its full potential in the context of RT. In this article, the mpMRI theories, including image mechanism, protocol design, and data analysis, will be reviewed with a focus on the radiation oncology field. Representative works will be discussed to demonstrate how mpMRI can be used for RT response assessment. Additionally, issues and limits of current works, as well as challenges and potential future research directions, will also be discussed.

show abstract

Re: Clinical evaluation of a deep-learning-based computer-aided detection system for the detection of pulmonary nodules in a large teaching hospital

et al. 2022

View full text Add to dashboard Cite

Artificial intelligence and soft skills in radiation oncology: Data versus wisdom

Cited by 7 publications

References 9 publications

Training of radiotherapy professionals: status, content, satisfaction and improvement suggestions in the Greater Region

Training of radiotherapy professionals: status, content, satisfaction and improvement suggestions in the Greater Region

Multi‐parametric MRI (mpMRI) for treatment response assessment of radiation therapy

Re: Clinical evaluation of a deep-learning-based computer-aided detection system for the detection of pulmonary nodules in a large teaching hospital

Contact Info

Product

Resources

About