Computer simulations of case difficulty in digital breast tomosynthesis using virtual clinical trials
(2022) In Medical Physics 49(4). p.2220-2232- Abstract
Purpose: Virtual clinical trials (VCTs) require computer simulations of representative patients and images to evaluate and compare changes in performance of imaging technologies. The simulated images are usually interpreted by model observers whose performance depends upon the selection of imaging cases used in training evaluation models. This work proposes an efficient method to simulate and calibrate soft tissue lesions, which matches the detectability threshold of virtual and human readings. Methods: Anthropomorphic breast phantoms were used to evaluate the simulation of four mass models (I–IV) that vary in shape and composition of soft tissue. Ellipsoidal (I) and spiculated (II–IV) masses were simulated using composite voxels with... (More)
Purpose: Virtual clinical trials (VCTs) require computer simulations of representative patients and images to evaluate and compare changes in performance of imaging technologies. The simulated images are usually interpreted by model observers whose performance depends upon the selection of imaging cases used in training evaluation models. This work proposes an efficient method to simulate and calibrate soft tissue lesions, which matches the detectability threshold of virtual and human readings. Methods: Anthropomorphic breast phantoms were used to evaluate the simulation of four mass models (I–IV) that vary in shape and composition of soft tissue. Ellipsoidal (I) and spiculated (II–IV) masses were simulated using composite voxels with partial volumes. Digital breast tomosynthesis projections and reconstructions of a clinical system were simulated. Channelized Hotelling observers (CHOs) were evaluated using reconstructed slices of masses that varied in shape, composition, and density of surrounded tissue. The detectability threshold of each mass model was evaluated using receiver operating characteristic (ROC) curves calculated with the CHO's scores. Results: The area under the curve (AUC) of each calibrated mass model were within the 95% confidence interval (mean AUC [95% CI]) reported in a previous reader study (0.93 [0.89, 0.97]). The mean AUC [95% CI] obtained were 0.94 [0.93, 0.96], 0.92 [0.90, 0.93], 0.92 [0.90, 0.94], 0.93 [0.92, 0.95] for models I to IV, respectively. The mean AUC results varied substantially as a function of shape, composition, and density of surrounded tissue. Conclusions: For successful VCTs, lesions composed of soft tissue should be calibrated to simulate imaging cases that match the case difficulty predicted by human readers. Lesion composition, shape, and size are parameters that should be carefully selected to calibrate VCTs.
(Less)
- author
- Barufaldi, Bruno ; Vent, Trevor Lewis ; Bakic, Predrag Radomir LU and Maidment, Andrew Douglas Arnould
- organization
- publishing date
- 2022-04
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- anthropomorphic breast phantom, digital breast tomosynthesis, virtual clinical trials
- in
- Medical Physics
- volume
- 49
- issue
- 4
- pages
- 13 pages
- publisher
- American Association of Physicists in Medicine
- external identifiers
-
- scopus:85125587777
- pmid:35212403
- ISSN
- 0094-2405
- DOI
- 10.1002/mp.15553
- language
- English
- LU publication?
- yes
- id
- 3b6866f7-66e6-41bf-b9f1-cbfb8f299b38
- date added to LUP
- 2022-04-26 15:23:39
- date last changed
- 2024-06-14 14:51:19
@article{3b6866f7-66e6-41bf-b9f1-cbfb8f299b38,
abstract = {{<p>Purpose: Virtual clinical trials (VCTs) require computer simulations of representative patients and images to evaluate and compare changes in performance of imaging technologies. The simulated images are usually interpreted by model observers whose performance depends upon the selection of imaging cases used in training evaluation models. This work proposes an efficient method to simulate and calibrate soft tissue lesions, which matches the detectability threshold of virtual and human readings. Methods: Anthropomorphic breast phantoms were used to evaluate the simulation of four mass models (I–IV) that vary in shape and composition of soft tissue. Ellipsoidal (I) and spiculated (II–IV) masses were simulated using composite voxels with partial volumes. Digital breast tomosynthesis projections and reconstructions of a clinical system were simulated. Channelized Hotelling observers (CHOs) were evaluated using reconstructed slices of masses that varied in shape, composition, and density of surrounded tissue. The detectability threshold of each mass model was evaluated using receiver operating characteristic (ROC) curves calculated with the CHO's scores. Results: The area under the curve (AUC) of each calibrated mass model were within the 95% confidence interval (mean AUC [95% CI]) reported in a previous reader study (0.93 [0.89, 0.97]). The mean AUC [95% CI] obtained were 0.94 [0.93, 0.96], 0.92 [0.90, 0.93], 0.92 [0.90, 0.94], 0.93 [0.92, 0.95] for models I to IV, respectively. The mean AUC results varied substantially as a function of shape, composition, and density of surrounded tissue. Conclusions: For successful VCTs, lesions composed of soft tissue should be calibrated to simulate imaging cases that match the case difficulty predicted by human readers. Lesion composition, shape, and size are parameters that should be carefully selected to calibrate VCTs.</p>}},
author = {{Barufaldi, Bruno and Vent, Trevor Lewis and Bakic, Predrag Radomir and Maidment, Andrew Douglas Arnould}},
issn = {{0094-2405}},
keywords = {{anthropomorphic breast phantom; digital breast tomosynthesis; virtual clinical trials}},
language = {{eng}},
number = {{4}},
pages = {{2220--2232}},
publisher = {{American Association of Physicists in Medicine}},
series = {{Medical Physics}},
title = {{Computer simulations of case difficulty in digital breast tomosynthesis using virtual clinical trials}},
url = {{http://dx.doi.org/10.1002/mp.15553}},
doi = {{10.1002/mp.15553}},
volume = {{49}},
year = {{2022}},
}