Methodology to simulate temporal changes in breast tumors and parenchyma using Perlin noise
(2025) Medical Imaging 2025: Physics of Medical Imaging 13405.- Abstract
Simulating temporal changes in breast tissue has been challenging, despite advancement in virtual clinical trials. This study aims to enable virtual trials over time, motivated by interest in the effect of tissue involution on tumor visibility. We present a framework for creating 3D voxel-based breast phantoms and lesions using in-house Perlin Noise-based algorithm. The framework consists of three modules “Population Creator”, “Phantom Creator” and “Lesion Creator”. Population Creator generates a population based on characteristics from real clinical cases. Phantom and Lesion Creator enable selection of breast shape, size, density, and lesion shape and size. Perlin Noise parameters are selected to match the appearance of different... (More)
Simulating temporal changes in breast tissue has been challenging, despite advancement in virtual clinical trials. This study aims to enable virtual trials over time, motivated by interest in the effect of tissue involution on tumor visibility. We present a framework for creating 3D voxel-based breast phantoms and lesions using in-house Perlin Noise-based algorithm. The framework consists of three modules “Population Creator”, “Phantom Creator” and “Lesion Creator”. Population Creator generates a population based on characteristics from real clinical cases. Phantom and Lesion Creator enable selection of breast shape, size, density, and lesion shape and size. Perlin Noise parameters are selected to match the appearance of different tissue types. We used open-source software to reconstruct digital breast tomosynthesis images. Alternative software can be used for other imaging modalities. We illustrate the use of the framework to simulate temporal changes in the breast. First, assuming that the average volumetric breast density is 10.7% at 57 years of age and decreases exponentially over time, we create the phantom at the start and the end of the screening program (40 and 74 years, respectively, in Sweden). The breast density was calculated as 16.0% and 7.2%, respectively. Second, we show a simulated lesion at different time points, assuming a tumour volume doubling time of 282 days. We present a simulation framework for temporal changes in breast anatomy. We illustrate two applications which support the use of virtual clinical trials over time.
(Less)
- author
- Tomic, Hanna
LU
; Timberg, Pontus
LU
; Markbo, John Henry
LU
; Zackrisson, Sophia
LU
; Tingberg, Anders
LU
; Dustler, Magnus LU
and Bakic, Predrag R. LU
- organization
-
- Diagnostic Radiology, (Lund)
- Radiology Diagnostics, Malmö (research group)
- Medical Radiation Physics, Malmö (research group)
- LUCC: Lund University Cancer Centre
- Medical Radiation Physics, Lund
- Department of Translational Medicine
- EpiHealth: Epidemiology for Health
- LTH Profile Area: Photon Science and Technology
- LU Profile Area: Light and Materials
- publishing date
- 2025
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- breast density, Breast phantoms, breast tumors, computer simulation, temporal changes in anatomy, virtual clinical trials
- host publication
- Progress in Biomedical Optics and Imaging - Proceedings of SPIE
- editor
- Sabol, John M. ; Li, Ke and Abbaszadeh, Shiva
- volume
- 13405
- article number
- 134050O
- publisher
- SPIE
- conference name
- Medical Imaging 2025: Physics of Medical Imaging
- conference location
- San Diego, United States
- conference dates
- 2025-02-17 - 2025-02-21
- external identifiers
-
- scopus:105004581648
- ISBN
- 9781510685888
- DOI
- 10.1117/12.3047185
- language
- English
- LU publication?
- yes
- id
- d9130121-a8ca-4190-a09b-59d39003cd3f
- date added to LUP
- 2025-09-22 16:09:28
- date last changed
- 2025-09-22 16:09:28
@inproceedings{d9130121-a8ca-4190-a09b-59d39003cd3f, abstract = {{<p>Simulating temporal changes in breast tissue has been challenging, despite advancement in virtual clinical trials. This study aims to enable virtual trials over time, motivated by interest in the effect of tissue involution on tumor visibility. We present a framework for creating 3D voxel-based breast phantoms and lesions using in-house Perlin Noise-based algorithm. The framework consists of three modules “Population Creator”, “Phantom Creator” and “Lesion Creator”. Population Creator generates a population based on characteristics from real clinical cases. Phantom and Lesion Creator enable selection of breast shape, size, density, and lesion shape and size. Perlin Noise parameters are selected to match the appearance of different tissue types. We used open-source software to reconstruct digital breast tomosynthesis images. Alternative software can be used for other imaging modalities. We illustrate the use of the framework to simulate temporal changes in the breast. First, assuming that the average volumetric breast density is 10.7% at 57 years of age and decreases exponentially over time, we create the phantom at the start and the end of the screening program (40 and 74 years, respectively, in Sweden). The breast density was calculated as 16.0% and 7.2%, respectively. Second, we show a simulated lesion at different time points, assuming a tumour volume doubling time of 282 days. We present a simulation framework for temporal changes in breast anatomy. We illustrate two applications which support the use of virtual clinical trials over time.</p>}}, author = {{Tomic, Hanna and Timberg, Pontus and Markbo, John Henry and Zackrisson, Sophia and Tingberg, Anders and Dustler, Magnus and Bakic, Predrag R.}}, booktitle = {{Progress in Biomedical Optics and Imaging - Proceedings of SPIE}}, editor = {{Sabol, John M. and Li, Ke and Abbaszadeh, Shiva}}, isbn = {{9781510685888}}, keywords = {{breast density; Breast phantoms; breast tumors; computer simulation; temporal changes in anatomy; virtual clinical trials}}, language = {{eng}}, publisher = {{SPIE}}, title = {{Methodology to simulate temporal changes in breast tumors and parenchyma using Perlin noise}}, url = {{http://dx.doi.org/10.1117/12.3047185}}, doi = {{10.1117/12.3047185}}, volume = {{13405}}, year = {{2025}}, }