Assessment of a tumour growth model for virtual clinical trials of breast cancer screening

Tomic, Hanna; Bjerkén, Anna; Hellgren, Gustav; Johnson, Kristin; Förnvik, Daniel; Zackrisson, Sophia; Tingberg, Anders; Dustler, Magnus; Bakić, Predrag R.

doi:10.1117/12.2576131

Cited by 5 publications

(5 citation statements)

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“…An aspect that can increase the realism of VCTs investigating breast screening is the incorporation of tumour growth models, potentially with the aim of evaluating screening programme efficiency and the ability of a modality to detect interval cancers. While this is a very broad field (Edelman et al 2010, Jeanquartier et al 2016, specific applications relevant to VCTs have begun (Sengupta et al 2021, Tomic et al 2021. In the model developed by Sengupta et al (2021), pressure fields determined from adjacent anatomical structures govern tumour growth by allowing the lesion to develop in a given directions.…”

Section: Lesion Modellingmentioning

confidence: 99%

“…Changing pressure maps generated anisotropic lesions that were seen in clinical cases. The aim of the study by Tomic et al (2021) was to develop set of growing tumours to evaluate multiple screening rounds with growing tumours. A fit to the probability distribution for tumour volume doubling times (TVDT) was applied to clinical data and used to generate growing tumours in 30 virtual breasts.…”

Section: Lesion Modellingmentioning

confidence: 99%

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Performance evaluation of digital breast tomosynthesis systems: comparison of current virtual clinical trial methods

Marshall¹,

Bosmans²

2022

Phys. Med. Biol.

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Virtual clinical trials (VCT) have been developed by a number of groups to study breast imaging applications, with the focus on digital breast tomosynthesis (DBT) imaging. In this review, the main components of these simulation platforms are compared, along with the validation steps, a number of practical applications and some of the limitations associated with this method. VCT platforms simulate, up to a certain level of detail, the main components of the imaging chain: the x-ray beam, system geometry including the antiscatter grid and the x-ray detector. In building VCT platforms, groups use a number of techniques, including x-ray spectrum modelling, Monte Carlo (MC) simulation for x-ray imaging and scatter estimation, ray tracing, breast phantom models and modelling of the detector. The incorporation of different anthropomorphic breast models is described, together with the lesions needed to simulate clinical studies and to study detection performance. A step by step comparison highlights the need for transparency when describing the simulation frameworks. Current simulation bottlenecks include resolution and memory constraints when generating high resolution breast phantoms, difficulties in accessing/applying relevant, vendor specific image processing and reconstruction methods, while the imaging tasks considered are generally detection tasks without search, evaluated by computational observers. A number of applications are described along with some future avenues for research.

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Section: Lesion Modellingmentioning

confidence: 99%

Section: Lesion Modellingmentioning

confidence: 99%

Performance evaluation of digital breast tomosynthesis systems: comparison of current virtual clinical trial methods

Marshall¹,

Bosmans²

2022

Phys. Med. Biol.

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“…The OpenVCT framework was used to simulate 30 breasts, with one spherical tumour in each breast ( 45 ) . Tumour growth was modelled by increasing the tumour volume exponentially over time according to the tumour volume doubling time (TVDT) ( 46 , 47 ) .…”

Section: Study Ii: Vcts For System Optimisationmentioning

confidence: 99%

“…The sizes measured by the radiologist were 12.2 and 7.6 mm, respectively, corresponding to a TVDT of 356 d (18 d or 4.8% lower than the ground truth). Analysing all 30 simulated breasts, no significant difference was seen between the estimated and ground-truth TVDTs, with a median difference of 12 d (4%) ( p > 0.5 using the Kolmogorov–Smirnov test) ( 45 ) .…”

Section: Study Ii: Vcts For System Optimisationmentioning

confidence: 99%

Virtual Clinical Trials in Medical Imaging System Evaluation and Optimisation

Barufaldi

Maidment

Dustler

et al. 2021

Radiation Protection Dosimetry

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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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“…This article is based on a modified and expanded version of the SPIE Proceedings paper 115954Q. 51 S.Z. has received speaker fees and travel support from Siemens Healthcare AG.…”

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confidence: 99%

Development and evaluation of a method for tumor growth simulation in virtual clinical trials of breast cancer screening

et al. 2022

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. Purpose Image-based analysis of breast tumor growth rate may optimize breast cancer screening and diagnosis by suggesting optimal screening intervals and guide the clinical discussion regarding personalized screening based on tumor aggressiveness. Simulation-based virtual clinical trials (VCTs) can be used to evaluate and optimize medical imaging systems and design clinical trials. This study aimed to simulate tumor growth over multiple screening rounds. Approach This study evaluates a preliminary method for simulating tumor growth. Clinical data on tumor volume doubling time (TVDT) was used to fit a probability distribution (“clinical fit”) of TVDTs. Simulated tumors with TVDTs sampled from the clinical fit were inserted into 30 virtual breasts (“simulated cohort”) and used to simulate mammograms. Based on the TVDT, two successive screening rounds were simulated for each virtual breast. TVDTs from clinical and simulated mammograms were compared. Tumor sizes in the simulated mammograms were measured by a radiologist in three repeated sessions to estimate TVDT. Results The mean TVDT was 297 days (standard deviation, SD, 169 days) in the clinical fit and 322 days (SD, 217 days) in the simulated cohort. The mean estimated TVDT was 340 days (SD, 287 days). No significant difference was found between the estimated TVDTs from simulated mammograms and clinical TVDT values ( ). No significant difference ( ) was observed in the reproducibility of the tumor size measurements between the two screening rounds. Conclusions The proposed method for tumor growth simulation has demonstrated close agreement with clinical results, supporting potential use in VCTs of temporal breast imaging.

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Assessment of a tumour growth model for virtual clinical trials of breast cancer screening

Cited by 5 publications

References 0 publications

Performance evaluation of digital breast tomosynthesis systems: comparison of current virtual clinical trial methods

Performance evaluation of digital breast tomosynthesis systems: comparison of current virtual clinical trial methods

Virtual Clinical Trials in Medical Imaging System Evaluation and Optimisation

Development and evaluation of a method for tumor growth simulation in virtual clinical trials of breast cancer screening

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