Difference between revisions of "Journal:The current state of knowledge on imaging informatics: A survey among Spanish radiologists"

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==Introduction==
==Introduction==
There is no doubt that the upsurge of [[machine learning]] (ML) and deep learning (DL) algorithms, paired with the high amount of digital data generated in radiology, is changing this medical specialty. ML is already used in different imaging modalities such as CAD (computer-aided design) systems for breast cancer screening on mammography [1] or nodule detection on thoracic CT or radiography. [2] DL algorithms, in particular convolutional networks, are a promising technique for processing medical imaging data not only in tasks like image classification, object detection, segmentation, or registration [3], but also on dose optimization, creation and maintenance of [[biobank]]s, and structured reporting among others. [4]


More than 50,000 articles are returned when the search <tt>“Radiology” AND “Artificial Intelligence” OR “Deep Learning” OR “Machine Learning”</tt> is performed in the PubMed medical research engine, with a “quasi-exponential” slope for the last 10 years. Such is the concern that both the European Society of Radiology (ESR) and the Radiological Society of North America (RSNA) have their own specialized internet portals dedicated to [[artificial intelligence]] (AI) [5, 6], and the latter has even published a peer-reviewed journal fully dedicated to it. [7]


For this reason, there is growing concern among radiologists about the future of the profession. Some believe that radiologists will become obsolete in a few years, and others, such as the aforementioned societies [4, 8], have a more conservative stance in which AI will enhance the role of the radiologist and turn the job from volume-based to value-based. [9] Regardless of particular opinions, the irruption of AI in the radiological field, as well as its progressive integration into clinical practice, will bring a radical change in radiology as we currently know it.


The aim of this study is to evaluate general knowledge and concerns about trends on imaging informatics among radiologists currently working in Spain (both residents and attending physicians). All those respondents who had completed residency at the time of the survey are referred to as "attending physicians" throughout the text.
==Methods==
An online survey using [https://forms.gle/Ha8Rbm9yEG2ZCmq29 Google Forms] was designed by the authors, composed of 20 questions related to the level of knowledge about trending terminology and technologies according to the most recent and relevant literature [4, 8, 10], the need for a regulated academic training, and concerns about the implications of the widespread use of these technologies in the clinical setting, both ethics- and workforce-related. A summary of the survey is displayed in Table 1.
{|
| STYLE="vertical-align:top;"|
{| class="wikitable" border="1" cellpadding="5" cellspacing="0" width="80%"
|-
  | style="background-color:white; padding-left:10px; padding-right:10px;" colspan="4"|'''Table 1.''' Questions about the state of knowledge on imaging informatics and concerns, translated to English; AP = attending physician.
|-
  ! style="padding-left:10px; padding-right:10px;" colspan="4"|Demographic information
|-
  | style="background-color:white; padding-left:10px; padding-right:10px;" colspan="2"|Region of the country
  | style="background-color:white; padding-left:10px; padding-right:10px;" colspan="2"|17 options
|-
  | style="background-color:white; padding-left:10px; padding-right:10px;" colspan="2" rowspan="3"|Gender
  | style="background-color:white; padding-left:10px; padding-right:10px;" colspan="2"|Male
|-
  | style="background-color:white; padding-left:10px; padding-right:10px;" colspan="2"|Female
|-
  | style="background-color:white; padding-left:10px; padding-right:10px;" colspan="2"|I'd rather not say
|-
  | style="background-color:white; padding-left:10px; padding-right:10px;" colspan="2" rowspan="2"|Are you a resident or attending physician (AP)?
  | style="background-color:white; padding-left:10px; padding-right:10px;" colspan="2"|Resident physician
|-
  | style="background-color:white; padding-left:10px; padding-right:10px;" colspan="2"|Attending physician
|-
  | style="background-color:white; padding-left:10px; padding-right:10px;" colspan="2"|''Only for residents''
  | style="background-color:white; padding-left:10px; padding-right:10px;" colspan="2"|''Only for AP''
|-
  | style="background-color:white; padding-left:10px; padding-right:10px;" rowspan="5"|Which year of your residency are you currently in?
  | style="background-color:white; padding-left:10px; padding-right:10px;"|R1
  | style="background-color:white; padding-left:10px; padding-right:10px;" rowspan="5"|What is your work setting?
  | style="background-color:white; padding-left:10px; padding-right:10px;"|Only public health care
|-
  | style="background-color:white; padding-left:10px; padding-right:10px;"|R2
  | style="background-color:white; padding-left:10px; padding-right:10px;"|Only private health care
|-
  | style="background-color:white; padding-left:10px; padding-right:10px;"|R3
  | style="background-color:white; padding-left:10px; padding-right:10px;"|Both, mainly public health care
|-
  | style="background-color:white; padding-left:10px; padding-right:10px;"|R4
  | style="background-color:white; padding-left:10px; padding-right:10px;"|Both, mainly private health care
|-
  | style="background-color:white; padding-left:10px; padding-right:10px;"|
  | style="background-color:white; padding-left:10px; padding-right:10px;"|Other (explain)
|-
  | style="background-color:white; padding-left:10px; padding-right:10px;" rowspan="6"|Upon finishing your residency, in which setting do you wish to practice your specialty?
  | style="background-color:white; padding-left:10px; padding-right:10px;"|I haven't decided yet
  | style="background-color:white; padding-left:10px; padding-right:10px;" rowspan="6"|Without taking your residency into consideration, how many years of professional experience do you currently have?
  | style="background-color:white; padding-left:10px; padding-right:10px;"|0–5
|-
  | style="background-color:white; padding-left:10px; padding-right:10px;"|Both, mainly in public health care
  | style="background-color:white; padding-left:10px; padding-right:10px;"|6–10
|-
  | style="background-color:white; padding-left:10px; padding-right:10px;"|Only public health care
  | style="background-color:white; padding-left:10px; padding-right:10px;"|11–20
|-
  | style="background-color:white; padding-left:10px; padding-right:10px;"|Only private health care
  | style="background-color:white; padding-left:10px; padding-right:10px;"|21–30
|-
  | style="background-color:white; padding-left:10px; padding-right:10px;"|Both, mainly in private health care
  | style="background-color:white; padding-left:10px; padding-right:10px;"|> 30
|-
  | style="background-color:white; padding-left:10px; padding-right:10px;"|Other (explain)
  | style="background-color:white; padding-left:10px; padding-right:10px;"|
|-
|}
|}





Revision as of 19:56, 8 March 2022

Full article title The current state of knowledge on imaging informatics: A survey among Spanish radiologists
Journal Insights into Imaging
Author(s) Eiroa, Daniel; Antolín, Andreu; Ascanio, Mónica F.d.C.; Ortiz, Violeta P.; Escobar, Manuel; Roson, Nuria
Author affiliation(s) Hospital Universitario Valle de Hebrón, Hospital Universitario Nuestra Señora de Candelaria
Primary contact Email: danieldomingo dot eiroa dot idi at gencat dot cat
Year published 2022
Volume and issue 13
Page(s) 34
DOI 10.1186/s13244-022-01164-0
ISSN 1869-4101
Distribution license Creative Commons Attribution 4.0 International
Website https://insightsimaging.springeropen.com/articles/10.1186/s13244-022-01164-0
Download https://insightsimaging.springeropen.com/track/pdf/10.1186/s13244-022-01164-0.pdf (PDF)

Abstract

Background: There is growing concern about the impact of artificial intelligence (AI) on radiology and the future of the profession. The aim of this study is to evaluate general knowledge and concerns about trends on imaging informatics among radiologists working in Spain (residents and attending physicians). For this purpose, an online survey among radiologists working in Spain was conducted with questions related to knowledge about terminology and technologies, need for a regulated academic training on AI, and concerns about the implications of the use of these technologies.

Results: A total of 223 radiologists answered the survey, of whom 76.7% were attending physicians and 23.3% residents. General terms such as "AI" and "algorithm" had been heard of or read in at least 75.8% and 57.4% of the cases, respectively, while more specific terms were scarcely known. All the respondents considered that they should pursue academic training in medical informatics and new technologies, and 92.9% of them reckoned this preparation should be incorporated in the training program of the specialty. Patient safety was found to be the main concern for 54.2% of the respondents. Job loss was not seen as a peril by 45.7% of the participants.

Conclusions: Although there is a lack of knowledge about AI among Spanish radiologists, there is a will to explore such topics and a general belief that radiologists should be trained in these matters. Based on the results, a consensus is needed to change the current training curriculum to better prepare future radiologists.

Key points: Spanish radiologists desire to delve deeper into imaging informatics. Patient safety and adaptation to new technologies are the main concerns. A change on radiology education is needed to include artificial intelligence.

Keywords: artificial intelligence, medical informatics, medical education, surveys and questionnaires, radiology

Introduction

There is no doubt that the upsurge of machine learning (ML) and deep learning (DL) algorithms, paired with the high amount of digital data generated in radiology, is changing this medical specialty. ML is already used in different imaging modalities such as CAD (computer-aided design) systems for breast cancer screening on mammography [1] or nodule detection on thoracic CT or radiography. [2] DL algorithms, in particular convolutional networks, are a promising technique for processing medical imaging data not only in tasks like image classification, object detection, segmentation, or registration [3], but also on dose optimization, creation and maintenance of biobanks, and structured reporting among others. [4]

More than 50,000 articles are returned when the search “Radiology” AND “Artificial Intelligence” OR “Deep Learning” OR “Machine Learning” is performed in the PubMed medical research engine, with a “quasi-exponential” slope for the last 10 years. Such is the concern that both the European Society of Radiology (ESR) and the Radiological Society of North America (RSNA) have their own specialized internet portals dedicated to artificial intelligence (AI) [5, 6], and the latter has even published a peer-reviewed journal fully dedicated to it. [7]

For this reason, there is growing concern among radiologists about the future of the profession. Some believe that radiologists will become obsolete in a few years, and others, such as the aforementioned societies [4, 8], have a more conservative stance in which AI will enhance the role of the radiologist and turn the job from volume-based to value-based. [9] Regardless of particular opinions, the irruption of AI in the radiological field, as well as its progressive integration into clinical practice, will bring a radical change in radiology as we currently know it.

The aim of this study is to evaluate general knowledge and concerns about trends on imaging informatics among radiologists currently working in Spain (both residents and attending physicians). All those respondents who had completed residency at the time of the survey are referred to as "attending physicians" throughout the text.

Methods

An online survey using Google Forms was designed by the authors, composed of 20 questions related to the level of knowledge about trending terminology and technologies according to the most recent and relevant literature [4, 8, 10], the need for a regulated academic training, and concerns about the implications of the widespread use of these technologies in the clinical setting, both ethics- and workforce-related. A summary of the survey is displayed in Table 1.


Table 1. Questions about the state of knowledge on imaging informatics and concerns, translated to English; AP = attending physician.
Demographic information
Region of the country 17 options
Gender Male
Female
I'd rather not say
Are you a resident or attending physician (AP)? Resident physician
Attending physician
Only for residents Only for AP
Which year of your residency are you currently in? R1 What is your work setting? Only public health care
R2 Only private health care
R3 Both, mainly public health care
R4 Both, mainly private health care
Other (explain)
Upon finishing your residency, in which setting do you wish to practice your specialty? I haven't decided yet Without taking your residency into consideration, how many years of professional experience do you currently have? 0–5
Both, mainly in public health care 6–10
Only public health care 11–20
Only private health care 21–30
Both, mainly in private health care > 30
Other (explain)


References