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Virtual Clinical Trials in Medical Imaging System Evaluation and Optimisation

Barufaldi, Bruno ; Maidment, Andrew D A ; Dustler, Magnus LU ; Axelsson, Rebecca LU ; Tomic, Hanna LU ; Zackrisson, Sophia LU ; Tingberg, Anders LU and Bakic, Predrag R LU (2021) In Radiation Protection Dosimetry 195(3-4). p.363-371
Abstract

Virtual clinical trials (VCTs) can be used to evaluate and optimise medical imaging systems. VCTs are based on computer simulations of human anatomy, imaging modalities and image interpretation. OpenVCT is an open-source framework for conducting VCTs of medical imaging, with a particular focus on breast imaging. The aim of this paper was to evaluate the OpenVCT framework in two tasks involving digital breast tomosynthesis (DBT). First, VCTs were used to perform a detailed comparison of virtual and clinical reading studies for the detection of lesions in digital mammography and DBT. Then, the framework was expanded to include mechanical imaging (MI) and was used to optimise the novel combination of simultaneous DBT and MI. The first... (More)

Virtual clinical trials (VCTs) can be used to evaluate and optimise medical imaging systems. VCTs are based on computer simulations of human anatomy, imaging modalities and image interpretation. OpenVCT is an open-source framework for conducting VCTs of medical imaging, with a particular focus on breast imaging. The aim of this paper was to evaluate the OpenVCT framework in two tasks involving digital breast tomosynthesis (DBT). First, VCTs were used to perform a detailed comparison of virtual and clinical reading studies for the detection of lesions in digital mammography and DBT. Then, the framework was expanded to include mechanical imaging (MI) and was used to optimise the novel combination of simultaneous DBT and MI. The first experiments showed close agreement between the clinical and the virtual study, confirming that VCTs can predict changes in performance of DBT accurately. Work in simultaneous DBT and MI system has demonstrated that the system can be optimised in terms of the DBT image quality. We are currently working to expand the OpenVCT software to simulate MI acquisition more accurately and to include models of tumour growth. Based on our experience to date, we envision a future in which VCTs have an important role in medical imaging, including support for more imaging modalities, use with rare diseases and a role in training and testing artificial intelligence (AI) systems.

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author
; ; ; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Radiation Protection Dosimetry
volume
195
issue
3-4
article number
ncab080
pages
363 - 371
publisher
Oxford University Press
external identifiers
  • scopus:85112546134
  • pmid:34144597
ISSN
1742-3406
DOI
10.1093/rpd/ncab080
project
Simultaneous Digital Breast Tomosynthesis and Mechanical Imaging
language
English
LU publication?
yes
id
6881ca8e-d546-48dc-9a9b-8939664c76e4
date added to LUP
2021-09-27 16:18:27
date last changed
2024-04-20 11:55:35
@article{6881ca8e-d546-48dc-9a9b-8939664c76e4,
  abstract     = {{<p>Virtual clinical trials (VCTs) can be used to evaluate and optimise medical imaging systems. VCTs are based on computer simulations of human anatomy, imaging modalities and image interpretation. OpenVCT is an open-source framework for conducting VCTs of medical imaging, with a particular focus on breast imaging. The aim of this paper was to evaluate the OpenVCT framework in two tasks involving digital breast tomosynthesis (DBT). First, VCTs were used to perform a detailed comparison of virtual and clinical reading studies for the detection of lesions in digital mammography and DBT. Then, the framework was expanded to include mechanical imaging (MI) and was used to optimise the novel combination of simultaneous DBT and MI. The first experiments showed close agreement between the clinical and the virtual study, confirming that VCTs can predict changes in performance of DBT accurately. Work in simultaneous DBT and MI system has demonstrated that the system can be optimised in terms of the DBT image quality. We are currently working to expand the OpenVCT software to simulate MI acquisition more accurately and to include models of tumour growth. Based on our experience to date, we envision a future in which VCTs have an important role in medical imaging, including support for more imaging modalities, use with rare diseases and a role in training and testing artificial intelligence (AI) systems.</p>}},
  author       = {{Barufaldi, Bruno and Maidment, Andrew D A and Dustler, Magnus and Axelsson, Rebecca and Tomic, Hanna and Zackrisson, Sophia and Tingberg, Anders and Bakic, Predrag R}},
  issn         = {{1742-3406}},
  language     = {{eng}},
  number       = {{3-4}},
  pages        = {{363--371}},
  publisher    = {{Oxford University Press}},
  series       = {{Radiation Protection Dosimetry}},
  title        = {{Virtual Clinical Trials in Medical Imaging System Evaluation and Optimisation}},
  url          = {{http://dx.doi.org/10.1093/rpd/ncab080}},
  doi          = {{10.1093/rpd/ncab080}},
  volume       = {{195}},
  year         = {{2021}},
}