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Review

Advances in automatic delineation of target volume and cardiac substructure in breast cancer radiotherapy (Review)

  • Authors:
    • Jingjing Shen
    • Peihua Gu
    • Yun Wang
    • Zhongming Wang
  • View Affiliations / Copyright

    Affiliations: School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200438, P.R. China, Department of Oncology and Radiotherapy, Shidong Hospital Affiliated to University of Shanghai for Science and Technology, Shanghai 200438, P.R. China
  • Article Number: 110
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    Published online on: February 2, 2023
       https://doi.org/10.3892/ol.2023.13697
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Abstract

Postoperative adjuvant radiotherapy plays an important role in the treatment of patients with breast cancer. With the continuous development of radiotherapeutic technologies, the requirements for radiotherapeutic accuracy are increasingly high. The accuracy of target volume and organ at risk delineation significantly affects the effect of radiotherapy. Automatic delineation software has been continuously developed for the automatic delineation of target areas and organs at risk. Automatic segmentation based on an atlas and deep learning is a hot topic in current clinical research. Automatic delineation can not only reduce the workload and delineation times, but also establish a uniform delineation standard and reduce inter‑observer and intra‑observer differences. In patients with breast cancer, especially in patients who undergo left breast radiotherapy, the protection of the heart is particularly important. Treating the whole heart as an organ at risk cannot meet the clinical needs, and it is necessary to limit the dose to specific cardiac substructures. The present review discusses the importance of automatic delineation of target volume and cardiac substructure in radiotherapy for patients with breast cancer.
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1 

Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A and Bray F: Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 71:209–249. 2021. View Article : Google Scholar : PubMed/NCBI

2 

Christiansen P, Carstensen SL, Ejlertsen B, Kroman N, Offersen B, Bodilsen A and Jensen MB: Breast conserving surgery versus mastectomy: Overall and relative survival-a population based study by the Danish breast cancer cooperative group (DBCG). Acta Oncol. 57:19–25. 2018. View Article : Google Scholar : PubMed/NCBI

3 

Corradini S, Reitz D, Pazos M, Schönecker S, Braun M, Harbeck N, Matuschek C, Bölke E, Ganswindt U, Alongi F, et al: Mastectomy or breast-conserving therapy for early breast cancer in real-life clinical practice: Outcome comparison of 7565 cases. Cancers (Basel). 11:1602019. View Article : Google Scholar : PubMed/NCBI

4 

van Maaren MC, de Munck L, de Bock GH, Jobsen JJ, van Dalen T, Linn SC, Poortmans P, Strobbe LJA and Siesling S: 10 Year survival after breast-conserving surgery plus radiotherapy compared with mastectomy in early breast cancer in the Netherlands: A population-based study. Lancet Oncol. 17:1158–1170. 2016. View Article : Google Scholar : PubMed/NCBI

5 

Darby SC, Ewertz M, McGale P, Bennet AM, Blom-Goldman U, Brønnum D, Correa C, Cutter D, Gagliardi G, Gigante B, et al: Risk of ischemic heart disease in women after radiotherapy for breast cancer. N Engl J Med. 368:987–998. 2013. View Article : Google Scholar : PubMed/NCBI

6 

Brownlee Z, Garg R, Listo M, Zavitsanos P, Wazer DE and Huber KE: Late complications of radiation therapy for breast cancer: Evolution in techniques and risk over time. Gland Surg. 7:371–378. 2018. View Article : Google Scholar : PubMed/NCBI

7 

Poortmans PM, Weltens C, Fortpied C, Kirkove C, Peignaux-Casasnovas K, Budach V, van der Leij F, Vonk E, Weidner N, Rivera S, et al: Internal mammary and medial supraclavicular lymph node chain irradiation in stage I–III breast cancer (EORTC 22922/10925): 15-Year results of a randomised, phase 3 trial. Lancet Oncol. 21:1602–1610. 2020. View Article : Google Scholar : PubMed/NCBI

8 

Thorsen LB, Offersen BV, Danø H, Berg M, Jensen I, Pedersen AN, Zimmermann SJ, Brodersen HJ, Overgaard M and Overgaard J: DBCG-IMN: A population-based cohort study on the effect of internal mammary node irradiation in early node-positive breast cancer. J Clin Oncol. 34:314–320. 2016. View Article : Google Scholar : PubMed/NCBI

9 

Wang X, Luo J, Jin K, Chen X, Zhang L, Meng J, Zhang X, Zhang Z, Shao Z, Bazan JG, et al: Internal mammary node irradiation improves 8-year survival in breast cancer patients: Results from a retrospective cohort study in real-world setting. Breast Cancer. 27:252–260. 2020. View Article : Google Scholar : PubMed/NCBI

10 

Vinod SK, Jameson MG, Min M and Holloway LC: Uncertainties in volume delineation in radiation oncology: A systematic review and recommendations for future studies. Radiother Oncol. 121:169–179. 2016. View Article : Google Scholar : PubMed/NCBI

11 

Li XA, Tai A, Arthur DW, Buchholz TA, Macdonald S, Marks LB, Moran JM, Pierce LJ, Rabinovitch R, Taghian A, et al: Variability of target and normal structure delineation for breast cancer radiotherapy: An RTOG multi-institutional and multiobserver study. Int J Radiat Oncol Biol Phys. 73:944–951. 2009. View Article : Google Scholar : PubMed/NCBI

12 

Lim JY and Leech M: Use of auto-segmentation in the delineation of target volumes and organs at risk in head and neck. Acta Oncol. 55:799–806. 2016. View Article : Google Scholar : PubMed/NCBI

13 

Reed VK, Woodward WA, Zhang L, Strom EA, Perkins GH, Tereffe W, Oh JL, Yu TK, Bedrosian I, Whitman GJ, et al: Automatic segmentation of whole breast using atlas approach and deformable image registration. Int J Radiat Oncol Biol Phys. 73:1493–1500. 2009. View Article : Google Scholar : PubMed/NCBI

14 

Fontanilla HP, Woodward WA, Lindberg ME, Zhang L, Sharp HJ, Strom EA, Salehpour M, Buchholz TA and Dong L: Automating RTOG-defined target volumes for postmastectomy radiation therapy. Pract Radiat Oncol. 1:97–104. 2011. View Article : Google Scholar : PubMed/NCBI

15 

Bell LR, Dowling JA, Pogson EM, Metcalfe P and Holloway L: Atlas-based segmentation technique incorporating inter-observer delineation uncertainty for whole breast. J Phys Conf Ser. 777:0120022017. View Article : Google Scholar

16 

Eldesoky AR, Yates ES, Nyeng TB, Thomsen MS, Nielsen HM, Poortmans P, Kirkove C, Krause M, Kamby C, Mjaaland I, et al: Internal and external validation of an ESTRO delineation guideline-dependent automated segmentation tool for loco-regional radiation therapy of early breast cancer. Radiother Oncol. 121:424–430. 2016. View Article : Google Scholar : PubMed/NCBI

17 

Offersen BV, Boersma LJ, Kirkove C, Hol S, Aznar MC, Biete Sola A, Kirova YM, Pignol JP, Remouchamps V, Verhoeven K, et al: ESTRO consensus guideline on target volume delineation for elective radiation therapy of early stage breast cancer. Radiother Oncol. 114:3–10. 2015. View Article : Google Scholar : PubMed/NCBI

18 

Ciardo D, Gerardi MA, Vigorito S, Morra A, Dell'acqua V, Diaz FJ, Cattani F, Zaffino P, Ricotti R, Spadea MF, et al: Atlas-based segmentation in breast cancer radiotherapy: Evaluation of specific and generic-purpose atlases. Breast. 32:44–52. 2017. View Article : Google Scholar : PubMed/NCBI

19 

Gao Y, Hou Y, Pan X, Wang L, Li L and Xia YX: Research progress on the whole breast radiotherapy in prone position after breast-conserving surgery for early breast cancer. Chin J Radiol Health. 31:373–378. 3852022.

20 

Dipasquale G, Wang X, Chatelain-Fontanella V, Vinh-Hung V and Miralbell R: Automatic segmentation of breast in prone position: Correlation of similarity indexes and breast pendulousness with dose/volume parameters. Radiother Oncol. 120:124–127. 2016. View Article : Google Scholar : PubMed/NCBI

21 

Stross WC, Herchko SM and Vallow LA: Atlas based segmentation in prone breast cancer radiation therapy. Med Dosim. 45:298–301. 2020. View Article : Google Scholar : PubMed/NCBI

22 

Wang X, Miralbell R, Fargier-Bochaton O, Bulling S, Vallée JP and Dipasquale G: Atlas sampling for prone breast automatic segmentation of organs at risk: The importance of patients' body mass index and breast cup size for an optimized contouring of the heart and the coronary vessels. Technol Cancer Res Treat. 19:15330338209206242020.PubMed/NCBI

23 

Msika R, Tkatchenko N, Robilliard M, Fourquet A and Kirova Y: Evaluation of a software for automatic delineation of the mammary gland and organs at risk in patients treated for breast cancer in lateral position. Cancer Radiother. 24:799–804. 2020. View Article : Google Scholar : PubMed/NCBI

24 

Leonardi MC, Pepa M, Gugliandolo SG, Luraschi R, Vigorito S, Rojas DP, La Porta MR, Cante D, Petrucci E, Marino L, et al: Geometric contour variation in clinical target volume of axillary lymph nodes in breast cancer radiotherapy: An AIRO multi-institutional study. Br J Radiol. 94:202011772021. View Article : Google Scholar : PubMed/NCBI

25 

Dong X, Lei Y, Wang T, Thomas M, Tang L, Curran WJ, Liu T and Yang X: Automatic multiorgan segmentation in thorax CT images using U-net-GAN. Med Phys. 46:2157–2168. 2019. View Article : Google Scholar : PubMed/NCBI

26 

Fu Y, Lei Y, Wang T, Curran WJ, Liu T and Yang X: A review of deep learning based methods for medical image multi-organ segmentation. Phys Med. 85:107–122. 2021. View Article : Google Scholar : PubMed/NCBI

27 

Wang T, Lei Y, Fu Y, Curran WJ, Liu T and Yang X: Machine learning in quantitative PET imaging. arXiv preprint arXiv. 2001.06597. 2020.

28 

Sahiner B, Pezeshk A, Hadjiiski LM, Wang X, Drukker K, Cha KH, Summers RM and Giger ML: Deep learning in medical imaging and radiation therapyc. Med Phys. 46:e1–e36. 2019. View Article : Google Scholar : PubMed/NCBI

29 

Szegedy C, Liu W, Jia Y, Sermanet P, Reed S, Anguelov D, Erhan D, Vanhoucke V and Rabinovich A: Going Deeper with Convolutions. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 1–9. 2015.

30 

LeCun Y, Bengio Y and Hinton G: Deep learning. Nature. 521:436–444. 2015. View Article : Google Scholar : PubMed/NCBI

31 

Ronneberger O, Fischer P and Brox T: U-net: Convolutional networks for biomedical image segmentation. International conference on medical image computing and computer-assisted intervention. 234–241. 2015.

32 

He K, Zhang X, Ren S and Sun J: Deep residual learning for image recognition. Proceedings of the IEEE conference on computer vision and pattern recognition. 770–778. 2016.PubMed/NCBI

33 

Men K, Zhang T, Chen X, Chen B, Tang Y, Wang S, Li Y and Dai J: Fully automatic and robust segmentation of the clinical target volume for radiotherapy of breast cancer using big data and deep learning. Phys Med. 50:13–19. 2018. View Article : Google Scholar : PubMed/NCBI

34 

Men K, Dai J and Li Y: Automatic segmentation of the clinical target volume and organs at risk in the planning CT for rectal cancer using deep dilated convolutional neural networks. Med Phys. 44:6377–6389. 2017. View Article : Google Scholar : PubMed/NCBI

35 

Men K, Chen X, Zhang Y, Zhang T, Dai J, Yi J and Li Y: Deep deconvolutional neural network for target segmentation of nasopharyngeal cancer in planning computed tomography images. Front Oncol. 7:3152017. View Article : Google Scholar : PubMed/NCBI

36 

Zhou T, Dong Y and Huo B: U-Net and its applications in medical image segmentation: A review. J Image Graph. 26:2058–2077. 2021.

37 

Siddique N, Sidike P, Elkin CP and Devabhaktuni V: U-net and its variants for medical image segmentation: A review of theory and applications. IEEE Access. 9:82031–82057. 2021. View Article : Google Scholar : PubMed/NCBI

38 

Liu Z, Liu F, Chen W, Tao Y, Liu X, Zhang F, Shen J, Guan H, Zhen H, Wang S, et al: Automatic segmentation of clinical target volume and organs-at-risk for breast conservative radiotherapy using a convolutional neural network. Cancer Manag Res. 13:8209–8217. 2021. View Article : Google Scholar : PubMed/NCBI

39 

Schreier J, Attanasi F and Laaksonen H: A full-image deep segmenter for CT images in breast cancer radiotherapy treatment. Front Oncol. 9:6772019. View Article : Google Scholar : PubMed/NCBI

40 

Balagopal A, Kazemifar S, Nguyen D, Lin MH, Hannan R, Owrangi A and Jiang S: Fully automated organ segmentation in male pelvic CT images. Phys Med Biol. 63:2450152018. View Article : Google Scholar : PubMed/NCBI

41 

Zhou X, Yamada K, Kojima T, Takayama R, Wang S, Zhou X, Hara T and Fujita H: Performance evaluation of 2D and 3D deep learning approaches for automatic segmentation of multiple organs on CT images. Medical Imaging 2018: Computer-Aided Diagnosis. 10575:520–525. 2018.

42 

Chung SY, Chang JS, Choi MS, Chang Y, Choi BS, Chun J, Keum KC, Kim JS and Kim YB: Clinical feasibility of deep learning-based auto-segmentation of target volumes and organs-at-risk in breast cancer patients after breast-conserving surgery. Radiat Oncol. 16:442021. View Article : Google Scholar : PubMed/NCBI

43 

Byun HK, Chang JS, Choi MS, Chun J, Jung J, Jeong C, Kim JS, Chang Y, Chung SY, Lee S and Kim YB: Evaluation of deep learning-based autosegmentation in breast cancer radiotherapy. Radiat Oncol. 16:2032021. View Article : Google Scholar : PubMed/NCBI

44 

Oya M, Sugimoto S, Sasai K and Yokoyama K: Investigation of clinical target volume segmentation for whole breast irradiation using three-dimensional convolutional neural networks with gradient-weighted class activation mapping. Radiol Phys Technol. 14:238–247. 2021. View Article : Google Scholar : PubMed/NCBI

45 

Almberg SS, Lervåg C, Frengen J, Eidem M, Abramova TM, Nordstrand CS, Alsaker MD, Tøndel H, Raj SX and Wanderås AD: Training, validation, and clinical implementation of a deep-learning segmentation model for radiotherapy of loco-regional breast cancer. Radiother Oncol. 173:62–68. 2022. View Article : Google Scholar : PubMed/NCBI

46 

Liu Z, Liu F, Chen W, Liu X, Hou X, Shen J, Guan H, Zhen H, Wang S, Chen Q, et al: Automatic segmentation of clinical target volumes for post-modified radical mastectomy radiotherapy using convolutional neural networks. Front Oncol. 10:5813472021. View Article : Google Scholar : PubMed/NCBI

47 

Hu Y, Guo Y, Wang Y, Yu J, Li J, Zhou S and Chang C: Automatic tumor segmentation in breast ultrasound images using a dilated fully convolutional network combined with an active contour model. Med Phys. 46:215–228. 2019. View Article : Google Scholar : PubMed/NCBI

48 

Qi X, Hu J, Zhang L, Bai S and Yi Z: Automated segmentation of the clinical target volume in the planning CT for breast cancer using deep neural networks. IEEE Trans Cybern. 52:3446–3456. 2022. View Article : Google Scholar : PubMed/NCBI

49 

Sherer MV, Lin D, Elguindi S, Duke S, Tan LT, Cacicedo J, Dahele M and Gillespie EF: Metrics to evaluate the performance of auto-segmentation for radiation treatment planning: A critical review. Radiother Oncol. 160:185–191. 2021. View Article : Google Scholar : PubMed/NCBI

50 

Simões R, Wortel G, Wiersma TG, Janssen TM, van der Heide UA and Remeijer P: Geometrical and dosimetric evaluation of breast target volume auto-contouring. Phys Imaging Radiat Oncol. 12:38–43. 2019. View Article : Google Scholar : PubMed/NCBI

51 

van den Bogaard VA, Ta BD, van der Schaaf A, Bouma AB, Middag AM, Bantema-Joppe EJ, van Dijk LV, van Dijk-Peters FB, Marteijn LA, de Bock GH, et al: Validation and modification of a prediction model for acute cardiac events in patients with breast cancer treated with radiotherapy based on three-dimensional dose distributions to cardiac substructures. J Clin Oncol. 35:1171–1178. 2017. View Article : Google Scholar : PubMed/NCBI

52 

Jacobse JN, Duane FK, Boekel NB, Schaapveld M, Hauptmann M, Hooning MJ, Seynaeve CM, Baaijens MHA, Gietema JA, Darby SC, et al: Radiation dose-response for risk of myocardial infarction in breast cancer survivors. Int J Radiat Oncol Biol Phys. 103:595–604. 2019. View Article : Google Scholar : PubMed/NCBI

53 

Wennstig AK, Garmo H, Isacsson U, Gagliardi G, Rintelä N, Lagerqvist B, Holmberg L, Blomqvist C, Sund M and Nilsson G: The relationship between radiation doses to coronary arteries and location of coronary stenosis requiring intervention in breast cancer survivors. Radiat Oncol. 14:402019. View Article : Google Scholar : PubMed/NCBI

54 

Piroth MD, Baumann R, Budach W, Dunst J, Feyer P, Fietkau R, Haase W, Harms W, Hehr T, Krug D, et al: Heart toxicity from breast cancer radiotherapy: Current findings, assessment, and prevention. Strahlenther Onkol. 195:1–12. 2019. View Article : Google Scholar : PubMed/NCBI

55 

Jacob S, Camilleri J, Derreumaux S, Walker V, Lairez O, Lapeyre M, Bruguière E, Pathak A, Bernier MO, Laurier D, et al: Is mean heart dose a relevant surrogate parameter of left ventricle and coronary arteries exposure during breast cancer radiotherapy: A dosimetric evaluation based on individually-determined radiation dose (BACCARAT study). Radiat Oncol. 14:292019. View Article : Google Scholar : PubMed/NCBI

56 

Taylor C, McGale P, Brønnum D, Correa C, Cutter D, Duane FK, Gigante B, Jensen MB, Lorenzen E, Rahimi K, et al: Cardiac structure injury after radiotherapy for breast cancer: Cross-sectional study with individual patient data. J Clin Oncol. 36:2288–2296. 2018. View Article : Google Scholar : PubMed/NCBI

57 

Naimi Z, Moujahed R, Neji H, Yahyaoui J, Hamdoun A, Bohli M and Kochbati L: Cardiac substructures exposure in left-sided breast cancer radiotherapy: Is the mean heart dose a reliable predictor of cardiac toxicity? Cancer Radiother. 25:229–236. 2021. View Article : Google Scholar : PubMed/NCBI

58 

Munshi A, Khataniar N, Sarkar B, Bera ML and Mohanti BK: Spatial orientation of coronary arteries and its implication for breast and thoracic radiotherapy-proposing ‘coronary strip’ as a new organ at risk. Strahlenther Onkol. 194:711–718. 2018. View Article : Google Scholar : PubMed/NCBI

59 

van den Bogaard VAB, van Dijk LV, Vliegenthart R, Sijtsema NM, Langendijk JA, Maduro JH and Crijns APG: Development and evaluation of an auto-segmentation tool for the left anterior descending coronary artery of breast cancer patients based on anatomical landmarks. Radiother Oncol. 136:15–20. 2019. View Article : Google Scholar : PubMed/NCBI

60 

Kaderka R, Gillespie EF, Mundt RC, Bryant AK, Sanudo-Thomas CB, Harrison AL, Wouters EL, Moiseenko V, Moore KL, Atwood TF and Murphy JD: Geometric and dosimetric evaluation of atlas based auto-segmentation of cardiac structures in breast cancer patients. Radiother Oncol. 131:215–220. 2019. View Article : Google Scholar : PubMed/NCBI

61 

Jung JW and Lee C, Mosher EG, Mille MM, Yeom YS, Jones EC, Choi M and Lee C: Automatic segmentation of cardiac structures for breast cancer radiotherapy. Phys Imaging Radiat Oncol. 12:44–48. 2019. View Article : Google Scholar : PubMed/NCBI

62 

Bekelman JE, Lu H, Pugh S, Baker K, Berg CD, Berrington de González A, Braunstein LZ, Bosch W, Chauhan C, Ellenberg S, et al: Pragmatic randomised clinical trial of proton versus photon therapy for patients with non-metastatic breast cancer: The radiotherapy comparative effectiveness (RadComp) consortium trial protocol. BMJ Open. 9:e0255562019. View Article : Google Scholar : PubMed/NCBI

63 

Jung JW, Mille MM, Ky B, Kenworthy W, Lee C, Yeom YS, Kwag A, Bosch W, MacDonald S, Cahlon O, et al: Application of an automatic segmentation method for evaluating cardiac structure doses received by breast radiotherapy patients. Phys Imaging Radiat Oncol. 19:138–144. 2021. View Article : Google Scholar : PubMed/NCBI

64 

Milo MLH, Nyeng TB, Lorenzen EL, Hoffmann L, Møller DS and Offersen BV: Atlas-based auto-segmentation for delineating the heart and cardiac substructures in breast cancer radiation therapy. Acta Oncol. 61:247–254. 2022. View Article : Google Scholar : PubMed/NCBI

65 

Tan W, Liu D, Xue C, Xu J, Li B, Chen Z, Hu D and Wang X: Anterior myocardial territory may replace the heart as organ at risk in intensity-modulated radiotherapy for left-sided breast cancer. Int J Radiat Oncol Biol Phys. 82:1689–1697. 2012. View Article : Google Scholar : PubMed/NCBI

66 

Stockinger M, Karle H, Rennau H, Sebb S, Wolf U, Remmele J, Bührdel S, Bartkowiak D, Blettner M, Schmidberger H and Wollschläger D: Heart atlas for retrospective cardiac dosimetry: a multi-institutional study on interobserver contouring variations and their dosimetric impact. Radiat Oncol. 16:2412021. View Article : Google Scholar : PubMed/NCBI

67 

Loap P, Tkatchenko N, Nicolas E, Fourquet A and Kirova Y: Optimization and auto-segmentation of a high risk cardiac zone for heart sparing in breast cancer radiotherapy. Radiother Oncol. 153:146–154. 2020. View Article : Google Scholar : PubMed/NCBI

68 

Loap P, De Marzi L, Kirov K, Servois V, Fourquet A, Khoubeyb A and Kirova Y: Development of simplified auto-segmentable functional cardiac atlas. Pract Radiat Oncol. 12:533–538. 2022. View Article : Google Scholar : PubMed/NCBI

69 

Choi MS, Choi BS, Chung SY, Kim N, Chun J, Kim YB, Chang JS and Kim JS: Clinical evaluation of atlas- and deep learning-based automatic segmentation of multiple organs and clinical target volumes for breast cancer. Radiother Oncol. 153:139–145. 2020. View Article : Google Scholar : PubMed/NCBI

70 

van den Oever LB, Spoor DS, Crijns APG, Vliegenthart R, Oudkerk M, Veldhuis RNJ, de Bock GH and van Ooijen PMA: Automatic cardiac structure contouring for small datasets with cascaded deep learning models. J Med Syst. 46:222022. View Article : Google Scholar : PubMed/NCBI

71 

Jin X, Thomas MA, Dise J, Kavanaugh J, Hilliard J, Zoberi I, Robinson CG and Hugo GD: Robustness of deep learning segmentation of cardiac substructures in noncontrast computed tomography for breast cancer radiotherapy. Med Phys. 48:7172–7188. 2021. View Article : Google Scholar : PubMed/NCBI

72 

Harms J, Lei Y, Tian S, McCall NS, Higgins KA, Bradley JD, Curran WJ, Liu T and Yang X: Automatic delineation of cardiac substructures using a region-based fully convolutional network. Med Phys. 48:2867–2876. 2021. View Article : Google Scholar : PubMed/NCBI

73 

Momin S, Lei Y, McCall NS, Zhang J, Roper J, Harms J, Tian S, Lloyd MS, Liu T, Bradley JD, et al: Mutual enhancing learning-based automatic segmentation of CT cardiac substructure. Phys Med Biol. 67:10.1088/1361–6560/ac692d. 2022. View Article : Google Scholar : PubMed/NCBI

74 

Morris ED, Ghanem AI, Dong M, Pantelic MV, Walker EM and Glide-Hurst CK: Cardiac substructure segmentation with deep learning for improved cardiac sparing. Med Phys. 47:576–586. 2020. View Article : Google Scholar : PubMed/NCBI

75 

Bruns S, Wolterink JM, Takx RAP, van Hamersvelt RW, Suchá D, Viergever MA, Leiner T and Išgum I: Deep learning from dual-energy information for whole-heart segmentation in dual-energy and single-energy non-contrast-enhanced cardiac CT. Med Phys. 47:5048–5060. 2020. View Article : Google Scholar : PubMed/NCBI

76 

van Velzen SGM, Bruns S, Wolterink JM, Leiner T, Viergever MA, Verkooijen HM and Išgum I: AI-based quantification of planned radiation therapy dose to cardiac structures and coronary arteries in patients with breast cancer. Int J Radiat Oncol Biol Phys. 112:611–620. 2022. View Article : Google Scholar : PubMed/NCBI

77 

Chun J, Chang JS, Oh C, Park I, Choi MS, Hong CS, Kim H, Yang G, Moon JY, Chung SY, et al: Synthetic contrast-enhanced computed tomography generation using a deep convolutional neural network for cardiac substructure delineation in breast cancer radiation therapy: A feasibility study. Radiat Oncol. 17:832022. View Article : Google Scholar : PubMed/NCBI

78 

Shen J, Zhang F, Di M, Shen J, Wang S, Chen Q, Chen Y, Liu Z, Lian X, Ma J, et al: Clinical target volume automatic segmentation based on lymph node stations for lung cancer with bulky lump lymph nodes. Thorac Cancer. 13:2897–2903. 2022. View Article : Google Scholar : PubMed/NCBI

79 

Cardenas CE, Beadle BM, Garden AS, Skinner HD, Yang J, Rhee DJ, McCarroll RE, Netherton TJ, Gay SS, Zhang L and Court LE: Generating high-quality lymph node clinical target volumes for head and neck cancer radiation therapy using a fully automated deep learning-based approach. Int J Radiat Oncol Biol Phys. 109:801–812. 2021. View Article : Google Scholar : PubMed/NCBI

80 

Jin D, Guo D, Ge J, Ye X and Lu L: Towards automated organs at risk and target volumes contouring: Defining precision radiation therapy in the modern era. J Natl Cancer Cent. 2:306–313. 2022. View Article : Google Scholar

81 

Xu H, Arsene Henry A, Robillard M, Amessis M and Kirova YM: The use of new delineation tool ‘MIRADA’ at the level of regional lymph nodes, step-by-step development and first results for early-stage breast cancer patients. Br J Radiol. 91:201800952018. View Article : Google Scholar : PubMed/NCBI

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Copy and paste a formatted citation
Spandidos Publications style
Shen J, Gu P, Wang Y and Wang Z: Advances in automatic delineation of target volume and cardiac substructure in breast cancer radiotherapy (Review). Oncol Lett 25: 110, 2023.
APA
Shen, J., Gu, P., Wang, Y., & Wang, Z. (2023). Advances in automatic delineation of target volume and cardiac substructure in breast cancer radiotherapy (Review). Oncology Letters, 25, 110. https://doi.org/10.3892/ol.2023.13697
MLA
Shen, J., Gu, P., Wang, Y., Wang, Z."Advances in automatic delineation of target volume and cardiac substructure in breast cancer radiotherapy (Review)". Oncology Letters 25.3 (2023): 110.
Chicago
Shen, J., Gu, P., Wang, Y., Wang, Z."Advances in automatic delineation of target volume and cardiac substructure in breast cancer radiotherapy (Review)". Oncology Letters 25, no. 3 (2023): 110. https://doi.org/10.3892/ol.2023.13697
Copy and paste a formatted citation
x
Spandidos Publications style
Shen J, Gu P, Wang Y and Wang Z: Advances in automatic delineation of target volume and cardiac substructure in breast cancer radiotherapy (Review). Oncol Lett 25: 110, 2023.
APA
Shen, J., Gu, P., Wang, Y., & Wang, Z. (2023). Advances in automatic delineation of target volume and cardiac substructure in breast cancer radiotherapy (Review). Oncology Letters, 25, 110. https://doi.org/10.3892/ol.2023.13697
MLA
Shen, J., Gu, P., Wang, Y., Wang, Z."Advances in automatic delineation of target volume and cardiac substructure in breast cancer radiotherapy (Review)". Oncology Letters 25.3 (2023): 110.
Chicago
Shen, J., Gu, P., Wang, Y., Wang, Z."Advances in automatic delineation of target volume and cardiac substructure in breast cancer radiotherapy (Review)". Oncology Letters 25, no. 3 (2023): 110. https://doi.org/10.3892/ol.2023.13697
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