Physical and digital phantoms for 2D and 3D x-ray breast imaging: Review on the state-of-the-art and future prospects

Sarno, Antonio; Valero, Chiara; Tucciariello, Raffaele M.; Dukov, Nikolay; Costa, Paulo Roberto; Tomal, Alessandra

doi:10.1016/j.radphyschem.2022.110715

Cited by 15 publications

(12 citation statements)

References 117 publications

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“…Recent years have witnessed a growing academic interest in virtual clinical trials (VCTs) of breast x-ray imaging (Glick and Ikejimba 2018, Abadi et al 2020, Bliznakova 2020, Marshall and Bosmans 2022, Sarno et al 2023. A critical component of VCTs is the breast phantom, which plays a pivotal role in both breast imaging and dosimetry.…”

Section: Introductionmentioning

confidence: 99%

THUBreast: an open-source breast phantom generation software for x-ray imaging and dosimetry

Wang,

Liu,

et al. 2024

Phys. Med. Biol.

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Objective: Establishing realistic phantoms of human anatomy is a continuing concern within virtual clinical trials (VCTs) of breast X-ray imaging. However, little attention has been paid to glandular distribution within these phantoms. The principal objective of this study was to develop breast phantoms considering the clinical glandular distribution.Approach: This research introduces an innovative method for integrating glandular distribution information into breast phantoms. We have developed an open-source software, THUBreast, which generates breast phantoms that accurately replicate both the structural texture and glandular distribution, two crucial elements in breast X-ray imaging and dosimetry. To validate the efficacy of THUBreast, we assembled three groups of breast phantoms (THUBreast, patient-based, homogeneous) for irradiation simulation and calculated the power-law exponents (β) and mean glandular dose (D_g), indicators of texture realism and radiation risk, respectively, utilizing MC-GPU.Main results: Upon the computation of the D_g for the THUBreast phantoms, it was found to be in agreement with that absorbed by the phantoms based on patients, with an average deviation of 4%. The estimates of average D_g thus obtained were on average 23% less than those computed for the homogeneous phantoms. It was observed that the homogeneous phantoms did overestimate the average D_g by 30% when compared to the phantoms based on patients. The mean value of β for the images of THUBreast phantoms was found to be 2.92±0.08, which shows a commendable agreement with the findings of prior investigations.Significance: It is evidently clear from the results that THUBreast phantoms have a preliminary good performance in both imaging and dosimetry in terms of indicators of texture realism and glandular dose. THUBreast represents a further step towards developing a powerful toolkit for comprehensive evaluation of image quality and radiation risk.

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Section: Introductionmentioning

confidence: 99%

THUBreast: an open-source breast phantom generation software for x-ray imaging and dosimetry

Wang,

Liu,

et al. 2024

Phys. Med. Biol.

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“…Although many digital phantoms have been developed for brain [24,25], breast [26][27][28], whole body human [29,30], etc., these phantoms are mostly derived from and applicable to X-ray imaging, X-ray computed tomography (CT), or MRI. To our best knowledge, there are only a few existing pelvic digital phantoms [31], and there is a notable scarcity of prostate digital phantom.…”

Section: Introductionmentioning

confidence: 99%

Realistic digital phantoms for prostate ultrasound and photoacoustic imaging

Wu,

Enders,

Williams

et al. 2024

Medical Imaging 2024: Ultrasonic Imaging and Tomography

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In this work, we introduce the first realistic digital phantoms for prostate ultrasound and photoacoustic (PA) imaging in the male pelvic region. Our model encompasses surrounding tissues or organs around the prostate, including fat, bones (including femoral heads), muscles, urinary bladder, rectum, anal canal, penile bulb, neurovascular bundles, and seminal vesicles. Each digital phantom set contains five parameters: speed of sound, density, acoustic attenuation, optical absorption, and reduced optical scattering. The anatomical structures were derived from open-source computed tomography (CT) and magnetic resonance imaging (MRI) data from the Gold Atlas Project. The acoustic parameters, including the speed of sound and attenuation of the prostate, were obtained from an ex vivo prostate study utilizing the QTscan ultrasound tomography (UST) platform at the National Institutes of Health. All other parameters were acquired from the literature. By employing atlas data from four pelvises and UST images of 62 ex vivo prostate specimens, we generated 248 sets of digital phantoms. Additionally, we demonstrate a practical application, showcasing the identification of the effective insonification window for prostate UST. The developed digital phantoms are made open source and can be found at https://github.com/ywu115/Prostate-digital-phantoms. They can be leveraged for imaging device design, image formation studies, image reconstruction validation, and diagnostic and treatment planning for numerous prostate studies using ultrasound and PA imaging. Since the digital phantoms cover the entire male pelvic region, they can potentially be extended to other applications, such as bladder cancer imaging, cyst detection in seminal vesicles, hernias, and treatment planning for point-of-care ultrasound.

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“…At the today state-of-the art, there is large availability of digital models of the breast for VCT. These present different degrees of realisms and are derived either from clinical patient data or mathematical models [9,10]; similarly, also databases of simulated lesions have been developed [11]. As regard to the simulation of the imaging apparatuses, several authors have proposed analytical calculations based on raytracing algorithms coupled with post-processing algorithms for the inclusion of poissonin noise and scatter Compton contribution [3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

A Model for a Linear a-Se Detector in Simulated X-Ray Breast Imaging With Monte Carlo Software

Sarno,

Tucciariello,

Fantacci

et al. 2024

IEEE Trans. Radiat. Plasma Med. Sci.

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In-silico clinical trials with digital patient models and simulated devices are an alternative to expensive and long clinical trials on patient population for testing x-ray breast imaging apparatuses. In this work, we simulated a linear-response a-Se detector as an x-ray absorber, neglecting some physical processes such as electro-hole tracking and thermal noise. In order to tune characteristics of the simulated images toward those of the clinical scanners, the detector response curve, modulation transfer function (MTF) and normalized noise power spectrum (NNPS) were measured on a clinical mammographic unit. The same tests were replicated in-silico via a custom-made Monte Carlo code in order to define a suitable model to modify simulated images and to have realistic pixel values, noise and spatial resolution. The proposed approach resulted to restore the slope and the magnitude of the NNPS in simulated images toward curves evaluated on a clinical scanner. Similarly, the proposed strategy for tuning noise and spatial resolution in simulated images led to a contrast to noise ratio (CNR) evaluated on a custom-made phantom which differed from those in measured images less than 16% in absolute value.

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Physical and digital phantoms for 2D and 3D x-ray breast imaging: Review on the state-of-the-art and future prospects

Cited by 15 publications

References 117 publications

THUBreast: an open-source breast phantom generation software for x-ray imaging and dosimetry

THUBreast: an open-source breast phantom generation software for x-ray imaging and dosimetry

Realistic digital phantoms for prostate ultrasound and photoacoustic imaging

A Model for a Linear a-Se Detector in Simulated X-Ray Breast Imaging With Monte Carlo Software

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