Simulation of spiculated breast lesions

Elangovan, Premkumar; Alrehily, F.; Rs, Pinto; Rashidnasab, Alaleh; Dance, David R.; Young, Kenneth C.; Wells, Kevin

doi:10.1117/12.2216227

Cited by 9 publications

(6 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The number of images rated equally good in both 2D and DBT were 60.4% for simulated and 86% for real images. This is a significant improvement on the previous observer study results 10 conducted with simulated lesions without adding blending effects as shown in Table 1. …”

Section: Resultssupporting

confidence: 65%

“…The width of the spicule observed in the DBT stack was also measured at several key points. A 3D horn structure could then be fitted using an empirically observed power law 10 to model the change in width with distance from the lesion core Figure 1d. Then random distortions were applied to the cones to reduce the geometric appearance.…”

Section: Generating Biologically-inspired Spiculated Massesmentioning

confidence: 99%

See 1 more Smart Citation

Design and validation of biologically inspired spiculated breast lesion models utilizing structural tissue distortion

Schmidt

Chen

et al. 2018

Medical Imaging 2018: Physics of Medical Imaging

Self Cite

View full text Add to dashboard Cite

The use of conventional clinical trials to optimise technology and techniques in breast cancer screening carries with it issues of dose, high cost and delay. This has motivated the development of Virtual Clinical Trials (VCTs) as an alternative in-silico assessment paradigm. However, such an approach requires a set of modelling tools that can realistically represent the key biological and technical components within the imaging chain. The OPTIMAM image simulation toolbox provides a complete validated end-to-end solution for VCTs, wherein commonly-found regular and irregular lesions can be successfully and realistically simulated. As spiculated lesions are the second most common form of solid mass we report on our latest developments to produce realistic spiculated lesion models, with particular application in Alternative Forced Choice trials. We make use of sets of spicules drawn using manually annotated landmarks and interpolated by a fitted 3D spline for each spicule. Once combined with a solid core, these are inserted into 2D and tomosynthesis image segments and blended using a combination of elongation, rotational alignment with background, spicule twisting and core radial contraction effects. A mixture of real and simulated images (86 2D and 86 DBT images) with spiculated lesions were presented to an experienced radiologist in an observer study. The latest observer study results demonstrated that 88.4% of simulated images of lesions in 2D and 67.4% of simulated lesions in DBT were rated as definitely or probably real on a six-point scale. This presents a significant improvement on our previous work which did not employ any background blending algorithms to simulate spiculated lesions in clinical images.

show abstract

Section: Resultssupporting

confidence: 65%

Section: Generating Biologically-inspired Spiculated Massesmentioning

confidence: 99%

Design and validation of biologically inspired spiculated breast lesion models utilizing structural tissue distortion

Schmidt

Chen

et al. 2018

Medical Imaging 2018: Physics of Medical Imaging

Self Cite

View full text Add to dashboard Cite

show abstract

“…The spicules were modeled following a technique by Elangovan et al (2016). In their research, the authors detailed a method for generating spiculated lesions, which involved creating a central mass through a diffusionlimited algorithm and then attaching a set of spicules to the surface of this mass generated using patient data.…”

Section: Addition Of Spiculationsmentioning

confidence: 99%

In situ tumor model for longitudinal in silico imaging trials

Sengupta,

Lago,

Badano

2024

Phys. Med. Biol.

View full text Add to dashboard Cite

Objective: In this article, we introduce a computational model for simulating the growth of breast cancerlesions accounting for the stiffness of surrounding anatomical structures.Approach: In our model, ligaments are classified as the most rigid structures while the softer parts of thebreast are occupied by fat and glandular tissues As a result of these variations in tissue elasticity, the rapidlyproliferating tumor cells are met with differential resistance. It is found that these cells are likely to circumventstiffer terrains such as ligaments, instead electing to proliferate preferentially within the more yielding confines ofthe breast’s soft topography. By manipulating the interstitial tumor pressure in direct proportion to the elasticconstants of the tissues surrounding the tumor, this model thus creates the potential for realizing a databaseof unique lesion morphology sculpted by the distinctive topography of each local anatomical infrastructure.We modeled the growth of simulated lesions within volumes extracted from fatty breast models, developed byGraff et al., with a resolution of 50 μm generated with the open-source and readily available VICTRE (VirtualImaging Clinical Trials for Regulatory Evaluation) imaging pipeline. To visualize and validate the realism ofthe lesion models, we leveraged the imaging component of the VICTRE pipeline, which replicates the SiemensMammomat Inspiration mammography system in a digital format. This system was instrumental in generatingdigital mammogram (DM) images for each breast model containing the simulated lesions.Results: By utilizing the DM images, we were able to effectively illustrate the imaging characteristics of thelesions as they integrated with the anatomical backgrounds.Significance: The lesion growth model will facilitate and enhance longitudinal in silico trials investigating theprogression of breast cancer.

show abstract

“…The features extracted from real masses are then used to generate digital models. Elangovan et al (2016b) extended the DLA model to simulate spiculated lesions by using features, in terms of spicule length, width, curvature and distribution, extracted from patient DBT images containing spiculated lesions. These features were used as a guide to simulate realistic spicules which were then attached to the surface of a DLA mass resulting in models as shown in figure 8(a).…”

Section: Statistical Models Based On Characteristics Of Real Lesionsmentioning

confidence: 99%

The creation of breast lesion models for mammographic virtual clinical trials: a topical review

et al. 2023

View full text Add to dashboard Cite

Simulated breast lesion models, including microcalcification clusters and masses, have been used in several studies. Realistic lesions are required for virtual clinical trials (VCT) to be representative of clinical performance. Lesions can be obtained using mathematical methods or patient data. Various approaches exist to embed these lesions into breast structures to create cancer cases. This article provides a review of the literature available on the development of lesion models, simulation methods to insert these lesions into background structures and their applications.

show abstract

Simulation of spiculated breast lesions

Cited by 9 publications

References 8 publications

Design and validation of biologically inspired spiculated breast lesion models utilizing structural tissue distortion

Design and validation of biologically inspired spiculated breast lesion models utilizing structural tissue distortion

In situ tumor model for longitudinal in silico imaging trials

The creation of breast lesion models for mammographic virtual clinical trials: a topical review

Contact Info

Product

Resources

About