Антропоморфные фантомы молочной железы для лучевой диагностики: научный обзор

Обложка

Цитировать

Полный текст

Аннотация

Фантомы молочной железы применяются для разработки, валидации и усовершенствования методов лучевой диагностики. В визуализации молочной железы антропоморфные модели используются для валидации, оценки и оптимизации новых методов диагностики заболеваний молочной железы, а также для контроля качества диагностических систем, совершенствования клинических протоколов и алгоритмов реконструкции изображений. Ключевым требованием к фантомам для решения этих задач является реалистичная имитация органа.

В обзоре описаны существующие на настоящий момент варианты фантомов молочной железы для лучевой диагностики и процесса их создания.

Поиск литературы, соответствующей теме обзора, производился в базах данных PubMed, eLibrary, а также в поисковой системе Google Scholar. Всего в обзор включено 72 статьи и 13 тезисов материалов конференций.

Все виды фантомов молочной железы можно разделить на два вида: вычислительные и физические. Вычислительные, в свою очередь, подразделяются на группы в зависимости от типа первичных данных: на основе математических моделей, из образцов тканей, с использований изображений медицинской визуализации молочной железы пациентки. Физические фантомы классифицируются в зависимости от способа изготовления: литья, 3D-печати или послойного формирования с использованием контрастных веществ. Основными преимуществами вычислительных фантомов являются универсальность, эффективность, точность и безопасность, а также возможность генерировать большие объёмы виртуальных данных. Физические фантомы позволяют получать наиболее реалистичные диагностические изображения без участия пациентов и проводить неограниченное число лучевых исследований.

Об авторах

Юрий Александрович Васильев

Научно-практический клинический центр диагностики и телемедицинских технологий

Email: VasilevYA1@zdrav.mos.ru
ORCID iD: 0000-0002-5283-5961
SPIN-код: 4458-5608

канд. мед. наук

Россия, Москва

Ольга Васильевна Омелянская

Научно-практический клинический центр диагностики и телемедицинских технологий

Email: OmelyanskayaOV@zdrav.mos.ru
ORCID iD: 0000-0002-0245-4431
SPIN-код: 8948-6152
Россия, Москва

Анастасия Александровна Насибуллина

Научно-практический клинический центр диагностики и телемедицинских технологий

Автор, ответственный за переписку.
Email: NasibullinaAA@zdrav.mos.ru
ORCID iD: 0000-0003-1695-7731
SPIN-код: 2482-3372
Россия, Москва

Денис Владимирович Леонов

Научно-практический клинический центр диагностики и телемедицинских технологий

Email: LeonovDV2@zdrav.mos.ru
ORCID iD: 0000-0003-0916-6552
SPIN-код: 5510-4075

канд. техн. наук

Россия, Москва

Юлия Владиславовна Булгакова

Научно-практический клинический центр диагностики и телемедицинских технологий

Email: BulgakovaYV@zdrav.mos.ru
ORCID iD: 0000-0002-1627-6568
SPIN-код: 8945-6205
Россия, Москва

Дина Альфредовна Ахмедзянова

Научно-практический клинический центр диагностики и телемедицинских технологий

Email: AkhmedzyanovaDA@zdrav.mos.ru
ORCID iD: 0000-0001-7705-9754
SPIN-код: 6983-5991
Россия, Москва

Юлия Федоровна Шумская

Научно-практический клинический центр диагностики и телемедицинских технологий

Email: shumskayayf@zdrav.mos.ru
ORCID iD: 0000-0002-8521-4045
SPIN-код: 3164-5518
Россия, Москва

Роман Владимирович Решетников

Научно-практический клинический центр диагностики и телемедицинских технологий

Email: r.reshetnikov@npcmr.ru
ORCID iD: 0000-0002-9661-0254
SPIN-код: 8592-0558

канд. ф.-м. наук

Россия, Москва

Список литературы

  1. Leonov D., Venidiktova D., Costa-Júnior J.F.S., et al. Development of an anatomical breast phantom from polyvinyl chloride plastisol with lesions of various shape, elasticity and echogenicity for teaching ultrasound examination // International Journal of Computer Assisted Radiology and Surgery. 2023. doi: 10.1007/s11548-023-02911-4
  2. Nuzov N.B., Bhusal B., Henry K.R., et al. True location of deep brain stimulation electrodes differs from what is seen on postoperative magnetic resonance images: An anthropomorphic phantom study // Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. 2022. P. 1863–1866. doi: 10.1109/EMBC48229.2022.9871619
  3. Cannella R., Shahait M., Furlan A.A., et al. Efficacy of single-source rapid kV-switching dual-energy CT for characterization of non-uric acid renal stones: a prospective ex vivo study using anthropomorphic phantom // Abdominal Radiology. 2020. Vol. 45, N 4. P. 1092–1099. doi: 10.1007/s00261-019-02164-3
  4. Kramer R., Zankl M., Williams G., Drexler G., et al. The calculation of dose from external photon exposures using reference human phantoms and Monte Carlo methods. 1982.
  5. Васильев Ю.А., Тыров И.А., Владзимирский А.В., и др. Двойной просмотр результатов маммографии с применением технологий искусственного интеллекта: новая модель организации массовых профилактических исследований // Digital Diagnostics. 2023. Т. 4, № 2. C. 93–104. doi: 10.17816/DD3214236.
  6. Cockmartin L., Bosmans H., Marshall N.W. Comparative power law analysis of structured breast phantom and patient images in digital mammography and breast tomosynthesis // Med Phys. 2013. Vol. 40, № 8. P. 81920.
  7. Ma A.K.W., Gunn S., Darambara D.G. Introducing DeBRa: a detailed breast model for radiological studies // Physics in medicine and biology. 2009. Vol. 54, N 14. P. 4533–4545. doi: 10.1088/0031-9155/54/14/010
  8. Chen B., Shorey J., Saunders R.S., et al. An Anthropomorphic Breast Model for Breast Imaging Simulation and Optimization // Academic radiology. 2011. Vol. 18, N 5. P. 536–546. doi: 10.1016/j.acra.2010.11.009
  9. Elangovan P., Mackenzie A., Dance D.R., et al. Design and validation of realistic breast models for use in multiple alternative forced choice virtual clinical trials // Physics in medicine and biology. 2017. Vol. 62, N 7. P. 2778–2794. doi: 10.1088/1361-6560/aa622c
  10. Bliznakova K., Suryanarayanan S., Karellas A., Pallikarakis N. Evaluation of an improved algorithm for producing realistic 3D breast software phantoms: Application for mammography // Medical Physics. 2010. Vol. 37, N 11. P. 5604–5617. doi: 10.1118/1.3491812
  11. O’Connor J.M., Das M., Dider C., Mahd M., Glick S.J. Generation of voxelized breast phantoms from surgical mastectomy specimens // Medical Physics. 2013. Vol. 40, N 4. doi: 10.1118/1.4795758
  12. Lau B.A., Reiser I., Nishikawa R.M. A statistically defined anthropomorphic software breast phantom // Medical Physics. 2012. Vol. 39, N 6. P. 3375–3385. doi: 10.1118/1.4718576
  13. Sarno A., Mettivier G., di Franco F., et al. Dataset of patient-derived digital breast phantoms for in silico studies in breast computed tomography, digital breast tomosynthesis, and digital mammography // Medical Physics. 2021. Vol. 48, N 5. P. 2682–2693. doi: 10.1002/mp.14826
  14. Li C.M., Segars W.P., Tourassi G.D., Boone J.M., Dobbins J.T. Methodology for generating a 3D computerized breast phantom from empirical data // Medical Physics. 2009. Vol. 36, N 7. P. 3122–3131. doi: 10.1118/1.3140588
  15. Bliznakova K., Bliznakov Z., Bravou V., Kolitsi Z., Pallikarakis N. A three-dimensional breast software phantom for mammography simulation // Physics in medicine and biology. 2003. Vol. 48, N 22. P. 3699–3719. doi: 10.1088/0031-9155/48/22/006
  16. Bakic P.R., Albert M., Brzakovic D., Maidment A.D. Mammogram synthesis using a 3D simulation. I. Breast tissue model and image acquisition simulation // Medical Physics. 2002. Vol. 29, N 9. P. 2131–2139. doi: 10.1118/1.1501143
  17. Bakic P.R., Albert M., Brzakovic D., Maidment A.D. Mammogram synthesis using a 3D simulation. II. Evaluation of synthetic mammogram texture // Medical Physics. 2002. Vol. 29, N 9. P. 2140–2151. doi: 10.1118/1.1501144
  18. Bakic P.R., Albert M., Brzakovic D., Maidment A.D. Mammogram synthesis using a three-dimensional simulation. III. Modeling and evaluation of the breast ductal network // Medical Physics. 2003. Vol. 30, N 7. P. 1914–1925. doi: 10.1118/1.1586453
  19. Pokrajac D.D., Maidment A.D.A., Bakic P.R. Optimized generation of high resolution breast anthropomorphic software phantoms // Medical Physics. 2012. Vol. 39, N 4. P. 2290–2302. doi: 10.1118/1.3697523
  20. Chen F., Pokrajac D., Shi X., et al. Partial volume simulation in software breast phantoms // Medical Imaging 2012: Physics of Medical Imaging. 2012. doi: 10.1117/12.912242
  21. Graff C.G. A new, open-source, multi-modality digital breast phantom // Proceedings of the SPIE. 2016. Vol. 9783. doi: 10.1117/12.2216312
  22. Ikejimba L.C., Salad J., Graff C.G., et al. A four-alternative forced choice (4AFC) methodology for evaluating microcalcification detection in clinical full-field digital mammography (FFDM) and digital breast tomosynthesis (DBT) systems using an inkjet-printed anthropomorphic phantom // Medical Physics. 2019. Vol. 46, N 9. P. 3883–3892. doi: 10.1002/mp.13629
  23. Imran A.-A.-Z., Bakic P.R., Pokrajac D.D. Spatial distribution of adipose compartments size, shape and orientation in a CT breast image of a mastectomy specimen // 2015 IEEE Signal Processing in Medicine and Biology Symposium (SPMB). 2015. P. 1–2. doi: 10.1109/SPMB.2015.7405460
  24. Imran A.-A.-Z., Pokrajac D.D., Maidment A.D.A., Bakic P.R. Estimation of adipose compartment volumes in CT images of a mastectomy specimen // Proceedings of the SPIE. 2016. Vol. 9783. doi: 10.1117/12.2217175
  25. Hoeschen C., Fill U., Zankl M., et al. A high-resolution voxel phantom of the breast for dose calculations in mammography // Radiation protection dosimetry. 2005. Vol. 114, N 1–3. P. 406–409. doi: 10.1093/rpd/nch558
  26. Hsu C.M., Palmeri M.L., Segars W.P., Veress A.I., Dobbins J.T. An analysis of the mechanical parameters used for finite element compression of a high-resolution 3D breast phantom // Medical Physics. 2011. Vol. 38, N 10. P. 5756–5770. doi: 10.1118/1.3637500
  27. Hsu C.M.L., Palmeri M.L., Segars W.P., Veress A.I., Dobbins J.T. Generation of a suite of 3D computer-generated breast phantoms from a limited set of human subject data // Medical Physics. 2013. Vol. 40, N 4. doi: 10.1118/1.4794924
  28. Huang S.Y., Boone J.M., Yang K., et al. The characterization of breast anatomical metrics using dedicated breast CT // Medical Physics. 2011. Vol. 38, N 4. P. 2180–2191. doi: 10.1118/1.3567147
  29. Segars W.P., Veress A.I., Wells J.R., et al. Population of 100 realistic, patient-based computerized breast phantoms for multi-modality imaging research // Proceedings of the SPIE. 2014. Vol. 9033. doi: 10.1117/12.2043868
  30. Erickson D.W., Wells J.R., Sturgeon G.M., et al. Population of 224 realistic human subject-based computational breast phantoms // Medical Physics. 2015. Vol. 43, N 1. P. 23–32. doi: 10.1118/1.4937597
  31. Sarno A., Mettivier G., Di Lillo F., et al. Homogeneous vs. patient specific breast models for Monte Carlo evaluation of mean glandular dose in mammography // Physica Medica. 2018. Vol. 51. P. 56–63. doi: 10.1016/j.ejmp.2018.04.392
  32. Ivanov D., Bliznakova K., Buliev I., et al. Suitability of low density materials for 3D printing of physical breast phantoms // Physics in medicine and biology. 2018. Vol. 63, N 17. doi: 10.1088/1361-6560/aad315
  33. Santos J.C., Almeida C.D., Iwahara A., Peixoto J.E. Characterization and applicability of low-density materials for making 3D physical anthropomorphic breast phantoms // Radiation Physics and Chemistry. 2019. Vol. 164. doi: 10.1016/j.radphyschem.2019.108361
  34. Esposito G., Mettivier G., Bliznakova K., et al. Investigation of the refractive index decrement of 3D printing materials for manufacturing breast phantoms for phase contrast imaging // Physics in medicine and biology. 2019. Vol. 64, N 7. doi: 10.1088/1361-6560/ab0670
  35. Bliznakova K., Buliev I., Bliznakov Z. Anthropomorphic Phantoms in Image Quality and Patient Dose Optimization. Philadelphia : IOP Publishing, 2018. doi: 10.1088/2053-2563/aae197
  36. Hernandez A.M., Seibert J.A., Nosratieh A., Boone J.M. Generation and analysis of clinically relevant breast imaging x-ray spectra // Medical Physics. 2017. Vol. 44, N 6. P. 2148–2160. doi: 10.1002/mp.12222
  37. Dukov N.T., Feradov F.N., Gospodinova G.D., Bliznakova K.S. An Approach for Printing Tissue-mimicking Abnormalities Dedicated to Applications in Breast Imaging // 2019 IEEE XXVIII International Scientific Conference Electronics (ET). 2019. P. 1–4. doi: 10.1109/ET.2019.8878587
  38. Mäder U., Martin F., Karin B., Stephan S. Concept to extend anthropomorphic breast phantoms for 2D digital mammography with movable lesions at variable reproducible positions // 15th International Workshop on Breast Imaging (IWBI2020). 2020. doi: 10.1117/12.2560619
  39. Okoh F.O., Kabir N.A., Mohd F.M.Y., Siti N.A.A. Measurement of mass attenuation coefficient of polyvinyl alcohol (PVAL) as breast tissue equivalent material in the photon energy range of 16.61–25.26 keV // Journal of Physics: Conference Series. 2020. Vol. 1535, N 1. doi: 10.1088/1742-6596/1535/1/012051
  40. Mainprize J.G., Mawdsley G.E., Carton A.-K., et al. Full-size anthropomorphic phantom for 2D and 3D breast x-ray imaging // Proceedings of the SPIE. 2020. Vol. 11513. P. 17. doi: 10.1117/12.2560358
  41. Filippou V., Tsoumpas C. Recent advances on the development of phantoms using 3D printing for imaging with CT, MRI, PET, SPECT, and ultrasound // Medical Physics. 2018. Vol. 45, N 9. P. e740–e760. doi: 10.1002/mp.13058
  42. di Franco F., Mettivier G., Sarno A., Varallo A., Russo P. Manufacturing of physical breast phantoms with 3D printing technology for X-ray breast imaging // 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). 2019. P. 1–5. doi: 10.1109/NSS/MIC42101.2019.9059986
  43. Sage J., Fezzani K.L., Fitton I., et al. Experimental evaluation of seven quality control phantoms for digital breast tomosynthesis // Physica Medica. 2019. Vol. 57. P. 137–144. doi: 10.1016/j.ejmp.2018.12.031
  44. Freed M., Badal A., Jennings R.J., et al. X-ray properties of an anthropomorphic breast phantom for MRI and x-ray imaging // Physics in medicine and biology. 2011. Vol. 56, N 12. P. 3513–3533. doi: 10.1088/0031-9155/56/12/005
  45. Ruvio G., Solimene R., Cuccaro A., et al. Multimodal Breast Phantoms for Microwave, Ultrasound, Mammography, Magnetic Resonance and Computed Tomography Imaging // Sensors. 2020. Vol. 20, N 8. P. 2400. doi: 10.3390/s20082400
  46. Baldelli P., Phelan N., Egan G. Investigation of the effect of anode/filter materials on the dose and image quality of a digital mammography system based on an amorphous selenium flat panel detector // Br J Radiol. 2010. Vol. 83, N 988. P. 290–295. doi: 10.1259/bjr/60404532
  47. Park S., Jennings R., Liu H., Badano A., Myers K. A statistical, task-based evaluation method for three-dimensional x-ray breast imaging systems using variable-background phantoms // Medical Physics. 2010. Vol. 37, N 12. P. 6253–6270. doi: 10.1118/1.3488910
  48. Taibi A., Fabbri S., Baldelli P., et al. Dual-energy imaging in full-field digital mammography: a phantom study // Physics in medicine and biology. 2003. Vol. 48, N 13. P. 1945–1956. doi: 10.1088/0031-9155/48/13/307
  49. Cockmartin L., Marshall N., Bosmans H. Design and Evaluation of a Phantom with Structured Background for Digital Mammography and Breast Tomosynthesis. In: Maidment A.D.A., Bakic P.R., Gavenonis S., editors. Breast Imaging. IWDM 2012. Lecture Notes in Computer Science, vol 7361. Berlin : Springer, 2012. doi: 10.1007/978-3-642-31271-7_83
  50. Baneva Y., Bliznakova K., Cockmartin L., et al. Evaluation of a breast software model for 2D and 3D X-ray imaging studies of the breast // Physica Medica. 2017. Vol. 41. P. 78–86. doi: 10.1016/j.ejmp.2017.04.024
  51. Bliznakova K. Development of breast software phantom dedicated for research and educational purposes // RAD Association Journal. 2017. Vol. 2, N 1. P. 14–19. doi: 10.21175/RadJ.2017.01.004
  52. Marinov S., Carton A.-K., Cockmartin L., et al. Evaluation of the visual realism of breast texture phantoms in digital mammography // Proc. SPIE 11513, 15th International Workshop on Breast Imaging (IWBI2020). 2020. doi: 10.1117/12.2564124
  53. Feradov F., Marinov S., Bliznakova K. Physical Breast Phantom Dedicated for Mammography Studies. In: Henriques J., Neves N., de Carvalho P., editors. XV Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019. MEDICON 2019. IFMBE Proceedings, vol 76. Springer, 2020. P. 344–352. doi: 10.1007/978-3-030-31635-8_41
  54. Bliznakova K., Mettivier G., Russo P., Bliznakov Zh. Validation of a software platform for 2D and 3D phase contrast imaging: preliminary subjective evaluation // 15th International Workshop on Breast Imaging (IWBI2020). 2020. P. 97. doi: 10.1117/12.2564356
  55. Bliznakova K., Mettivier G., Russo P., et al. A software platform for phase contrast x-ray breast imaging research // Comput Biol Med. 2015. Vol. 61. P. 62–74. doi: 10.1016/j.compbiomed.2015.03.017
  56. Petrov D., Marshall N.W., Young K.C., Bosmans H. Systematic approach to a channelized Hotelling model observer implementation for a physical phantom containing mass-like lesions: Application to digital breast tomosynthesis // Physica Medica. 2019. Vol. 58. P. 8–20. doi: 10.1016/j.ejmp.2018.12.033
  57. Mettivier G., Bliznakova K., Sechopoulos I., et al. Evaluation of the BreastSimulator Software Platform for Breast Tomography: Preliminary Results // Physics in Medicine and Biology. 2016. Vol. 62, N 16. P. 145–151. doi: 10.1088/1361-6560/aa6ca3
  58. Salomon E., Semturs F., Unger E., et al. Equivalent breast thickness and dose sensitivity of a next iteration 3D structured breast phantom with lesion models // Medical Imaging 2020: Physics of Medical Imaging. 2020. doi: 10.1117/12.2548956
  59. Carton A.-K., Bakic P., Ullberg C., Derand H., Maidment A.D. Development of a physical 3D anthropomorphic breast phantom // Medical Physics. 2011. Vol. 38, N 2. P. 891–896. doi: 10.1118/1.3533896
  60. Mainprize J.G., Carton A.-K., Klausz R., et al. Development of a physical 3D anthropomorphic breast texture model using selective laser sintering rapid prototype printing // Medical Imaging 2018: Physics of Medical Imaging. 2018. P. 9. doi: 10.1117/12.2560358
  61. Li Z., Desolneux A., Muller S., Carton A.-K. A Novel 3D Stochastic Solid Breast Texture Model for X-Ray Breast Imaging. In: Tingberg A., Lång K., Timberg P., editors. Breast Imaging. IWDM 2016. Lecture Notes in Computer Science, vol 9699. Springer, 2016. P. 660–667. doi: 10.1007/978-3-319-41546-8_822016
  62. Prionas N.D., Burkett G.W., McKenney S.E., et al. Development of a patient-specific two-compartment anthropomorphic breast phantom // Physics in medicine and biology. 2012. Vol. 57, N 13. P. 4293–4307. doi: 10.1088/0031-9155/57/13/4293
  63. Badal A., Clark M., Ghammraoui B. Reproducing two-dimensional mammograms with three-dimensional printed phantoms // Journal of Medical Imaging. 2018. Vol. 5, N 3. doi: 10.1117/1.JMI.5.3.033501
  64. Schopphoven S., Cavael P., Bock K., Fiebich M., Mäder U. Breast phantoms for 2D digital mammography with realistic anatomical structures and attenuation characteristics based on clinical images using 3D printing // Physics in medicine and biology. 2019. Vol. 64, N 21. doi: 10.1088/1361-6560/ab3f6a
  65. Clark M., Ghammraoui B., Badal A. Reproducing 2D breast mammography images with 3D printed phantoms // Medical Imaging 2016: Physics of Medical Imaging. 2016. Vol. 9783. doi: 10.1117/12.2217215
  66. Okkalidis N. A novel 3D printing method for accurate anatomy replication in patient-specific phantoms // Medical Physics. 2018. Vol. 45, N 10. P. 4600–4606. doi: 10.1002/mp.13154
  67. Daskalov S., Okkalidis N., Boone J.M., et al. Anthropomorphic Physical Breast Phantom Based on Patient Breast CT Data: Preliminary Results. In: Henriques J., Neves N., de Carvalho P., editors. XV Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019. MEDICON 2019. IFMBE Proceedings, vol 76. Springer, 2020. P. 367–374. doi: 10.1007/978-3-030-31635-8_442020
  68. Kiarashi N., Nolte A.C., Sturgeon G.M., et al. Development of realistic physical breast phantoms matched to virtual breast phantoms based on human subject data // Medical Physics. 2015. Vol. 42, N 7. P. 4116–4126. doi: 10.1118/1.4919771
  69. Lindfors K.K., Boone J.M., Nelson T.R., et al. Dedicated Breast CT: Initial Clinical Experience // Radiology. 2008. Vol. 246, N 3. P. 725–733. doi: 10.1148/radiol.2463070410
  70. Burgess A.E., Judy P.F. Signal detection in power-law noise: effect of spectrum exponents // Journal of the Optical Society of America A. 2007. Vol. 24, N 12. P. B52–B60. doi: 10.1364/JOSAA.24.000B52
  71. Burgess A.E., Jacobson F.L., Judy P.F. Human observer detection experiments with mammograms and power-law noise // Medical Physics. 2001. Vol. 28, N 4. P. 419–437. doi: 10.1118/1.1355308
  72. Rossman A.H., Catenacci M., Zhao C., et al. Three-dimensionally-printed anthropomorphic physical phantom for mammography and digital breast tomosynthesis with custom materials, lesions, and uniform quality control region // Journal of Medical Imaging. 2019. Vol. 6, N 2. doi: 10.1117/1.JMI.6.2.021604
  73. Mettivier G., Sarno A., Boone J.M., et al. Virtual clinical trials in 3D and 2D breast imaging with digital phantoms derived from clinical breast CT scans // Medical Imaging 2020: Physics of Medical Imaging. 2020. doi: 10.1117/12.2548224
  74. Mettivier G., Sarno A, di Franco F., et al. The Napoli-Varna-Davis project for virtual clinical trials in X-ray breast imaging // 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). 2019. P. 1–5. doi: 10.1109/NSS/MIC42101.2019.9059828
  75. Ikejimba L.C., Graff C.G., Rosenthal S., et al. A novel physical anthropomorphic breast phantom for 2D and 3D x-ray imaging // Medical Physics. 2017. Vol. 44, N 2. P. 407–416. doi: 10.1002/mp.12062
  76. Mei K., Geagan M., Roshkovan L., et al. Three-dimensional printing of patient-specific lung phantoms for CT imaging: Emulating lung tissue with accurate attenuation profiles and textures // Medical Physics. 2022. Vol. 49, N 2. P. 825–835. doi: 10.1002/mp.15407
  77. Ionita C.N., Mokin M., Varble N., et al. Challenges and limitations of patient-specific vascular phantom fabrication using 3D Polyjet printing // Proceedings of SPIE--the International Society for Optical Engineering. doi: 10.1117/12.2042266
  78. Theodorakou C., Horrocks J.A., Marshall N.W., Speller R.D. A novel method for producing x-ray test objects and phantoms // Physics in medicine and biology. 2004. Vol. 49, N 8. P. 1423–1438. doi: 10.1088/0031-9155/49/8/004
  79. Sikaria D., Musinsky S., Sturgeon G.M., et al. Second generation anthropomorphic physical phantom for mammography and DBT: Incorporating voxelized 3D printing and inkjet printing of iodinated lesion inserts. Proc. SPIE 9783, Medical Imaging 2016: Physics of Medical Imaging. 2016. doi: 10.1117/12.2217667
  80. Jahnke P., Limberg F.R., Gerbl A., et al. Radiopaque Three-dimensional Printing: A Method to Create Realistic CT Phantoms // Radiology. 2017. Vol. 282, N 2. P. 569–575. doi: 10.1148/radiol.2016152710
  81. de Sisternes L., Brankov J.G., Zysk A.M., et al. A computational model to generate simulated three-dimensional breast masses // Medical Physics. 2015. Vol. 42, N 2. P. 1098–1118. doi: 10.1118/1.4905232
  82. SUN NUCLEAR. BR3D BREAST IMAGING PHANTOM [Internet] [дата обращения 01.01.2023]. Доступ по ссылке: https://www.cirsinc.com/products/mammography/br3d-breast-imaging-phantom/
  83. Piccolomini E.L., Morotti E. A Model-Based Optimization Framework for Iterative Digital Breast Tomosynthesis Image Reconstruction // Journal of imaging. 2021. Vol. 7, N 2. P. 36. doi: 10.3390/jimaging7020036
  84. Cavicchioli R., Hu J.C., Loli Piccolomini E., Morotti E., Zanni L. GPU acceleration of a model-based iterative method for Digital Breast Tomosynthesis // Scientific reports. 2020. Vol. 10, N 1. P. 43. doi: 10.1038/s41598-019-56920-y
  85. Gomi T., Kijima Y., Kobayashi T., Koibuchi Y. Evaluation of a Generative Adversarial Network to Improve Image Quality and Reduce Radiation-Dose during Digital Breast Tomosynthesis // Diagnostics. 2022. Vol. 12, N 2. P. 495. doi: 10.3390/diagnostics1202049586.
  86. Cockmartin L., Bosmans H., Marshall N.W. Establishing a quality control protocol for dual-energy based contrast-enhanced digital mammography // Proceedings of the SPIE. 2021. Vol. 11595. doi: 10.1117/12.2581816
  87. Marimón E., Marsden P.A., Nait-Charif H., Díaz O. A semi-empirical model for scatter field reduction in digital mammography // Physics in medicine and biology. 2021. Vol. 66, N 4. doi: 10.1088/1361-6560/abd231
  88. Silver E.H., Shulman S.D., Rehani M.M. Innovative monochromatic x-ray source for high-quality and low-dose medical imaging // Medical Physics. 2021. Vol. 48, N 3. P. 1064–1078. doi: 10.1002/mp.14677

Дополнительные файлы

Доп. файлы
Действие
1. JATS XML
Скачать
2. Рис. 1. Типы плотности ткани молочной железы согласно классификации BI-RADS. Для каждого изображения верхняя часть — краниокаудальная проекция, нижняя часть — медиолатеральная проекция.

Скачать (284KB)
Метаданные
3. Рис. 2. Схема строения вычислительного фантома молочной железы.

Скачать (176KB)
Метаданные
4. Рис. 3. BR3D Breast Imaging Phantom [82].

Скачать (191KB)
Метаданные
5. Рис. 4. Модель 011A производителя CIRS.

Скачать (139KB)
Метаданные

© Эко-вектор, 2023

Creative Commons License
Эта статья доступна по лицензии Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Данный сайт использует cookie-файлы

Продолжая использовать наш сайт, вы даете согласие на обработку файлов cookie, которые обеспечивают правильную работу сайта.

О куки-файлах