{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T22:09:27Z","timestamp":1740175767497,"version":"3.37.3"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2020,10,13]],"date-time":"2020-10-13T00:00:00Z","timestamp":1602547200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2020,10,13]],"date-time":"2020-10-13T00:00:00Z","timestamp":1602547200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61401242"],"award-info":[{"award-number":["61401242"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Complex Intell. Syst."],"published-print":{"date-parts":[[2023,6]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The model and algorithm of intensity-modulated radiotherapy (IMRT) are updated increasingly quickly, but the hardware upgrade of primary hospitals often lags behind. The new generation of intelligent precise radiotherapy platforms provides users with intelligent medical consortium services using big data, artificial intelligence and industrial Internet of Things technology. This technology can ensure that under the real-time guidance of a professional medical consortium, primary hospitals can realize rapid large-scale reverse planning design and can more accurately consider many factors of postprocessing. Although large-scale healthcare systems, such as volumetric-modulated arc therapy and other accurate radiotherapy technologies, have developed rapidly, the development of step-and-shoot-mode IMRT technology is still very important for developing countries. For software, in addition to the conformity of the dose distribution, the modulation speed, convenience and stability of the later dose delivery should also be considered in inverse planning. Therefore, this paper analyzes the main problems in conventional IMRT inverse planning, including the smoothing of the fluence map, the selection of the gantry angle and the dose leakage of tongue\u2013groove effects. To address these issues, a novel Intelligent IoT-based large-scale inverse planning strategy with the key factors of the postmodulation is developed, and a detailed flow chart is also provided. The scheme consists of two steps. The first step is to obtain a relatively optimal combination of gantry angles by considering the dose distribution requirements and constraints and the modulation requirements and constraints. The second step is to optimize the intensity map, to smooth the map based on prior knowledge according to the determined angles, and to obtain the final modulation scheme according to the relevant objectives and constraints of the map decomposition (leaf sequencing). In an experiment, we calculate and validate the clinical head and neck case. Because of the special gantry angle selection, the angle combination is optimized from the initial equivalent distribution to adapt to the target area and protect the nontarget area. The value of the objective function varies greatly after the optimization, especially in the target area, and the target value decreases by approximately 10%. On this basis, we smooth the fluence map by a partial differential equation with prior knowledge and a minimization of the total number of monitor units. It is also shown from the objective function value that the target value is essentially unchanged for the target area, while for the nontarget area, the value decreases by 16%, which is very impressive.<\/jats:p>","DOI":"10.1007\/s40747-020-00207-7","type":"journal-article","created":{"date-parts":[[2020,10,13]],"date-time":"2020-10-13T08:06:56Z","timestamp":1602576416000},"page":"2613-2627","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Intelligent IoT-based large-scale inverse planning system considering postmodulation factors"],"prefix":"10.1007","volume":"9","author":[{"given":"Yihua","family":"Lan","sequence":"first","affiliation":[]},{"given":"Fang","family":"Li","sequence":"additional","affiliation":[]},{"given":"Zijun","family":"Li","sequence":"additional","affiliation":[]},{"given":"Binglei","family":"Yue","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1772-0763","authenticated-orcid":false,"given":"Yin","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,10,13]]},"reference":[{"issue":"4","key":"207_CR1","doi-asserted-by":"publisher","first-page":"411","DOI":"10.3233\/ICA-190605","volume":"26","author":"S-H Wang","year":"2019","unstructured":"Wang S-H, Zhang Y-D, Yang M, Liu B, Ramirez J, Gorriz JM (2019) Unilateral sensorineural hearing loss identification based on double-density dual-tree complex wavelet transform and multinomial logistic regression. Integr Comput Aided Eng 26(4):411\u2013426","journal-title":"Integr Comput Aided Eng"},{"key":"207_CR2","doi-asserted-by":"publisher","first-page":"S563","DOI":"10.1016\/S0167-8140(18)31318-5","volume":"127","author":"R DeRoover","year":"2018","unstructured":"DeRoover R, Crijns W, Poels K, Nulens A, Vanstraelen B, Haustermans K, Depuydt T (2018) PO-1008: Commissioning of IMRT\/VMAT on the novel Varian Halcyon. Radiother Oncol. 127:S563. https:\/\/doi.org\/10.1016\/S0167-8140(18)31318-5","journal-title":"Radiother Oncol."},{"issue":"11","key":"207_CR3","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1002\/acm2.12747","volume":"20","author":"H Kim","year":"2019","unstructured":"Kim H, Huq MS, Lalonde R, Houser CJ, Beriwal S, Heron DE (2019) Early clinical experience with varian halcyon v2 linear accelerator: dual-isocenter IMRT planning and delivery with portal dosimetry for gynecological cancer treatments. J Appl Clin Med Phys 20(11):111\u2013120","journal-title":"J Appl Clin Med Phys"},{"issue":"11","key":"207_CR4","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1002\/acm2.12749","volume":"20","author":"X Ray","year":"2019","unstructured":"Ray X, Bojechko C, Moore KL (2019) Evaluating the sensitivity of halcyons automatic transit image acquisition for treatment error detection: a phantom study using static IMRT. J Appl Clin Med Phys 20(11):131\u2013143","journal-title":"J Appl Clin Med Phys"},{"key":"207_CR5","doi-asserted-by":"publisher","first-page":"422","DOI":"10.3389\/fnins.2019.00422","volume":"13","author":"S Wang","year":"2019","unstructured":"Wang S, Tang C, Sun J, Zhang Y (2019) Cerebral micro-bleeding detection based on densely connected neural network. Front Neurosci 13:422","journal-title":"Front Neurosci"},{"key":"207_CR6","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1016\/j.ejmp.2019.11.015","volume":"68","author":"T Jarema","year":"2019","unstructured":"Jarema T, Aland T (2019) Using the iterative kv CBCT reconstruction on the varian halcyon linear accelerator for radiation therapy planning for pelvis patients. Phys Med 68:112\u2013116","journal-title":"Phys Med"},{"key":"207_CR7","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1016\/j.ejmp.2018.09.030","volume":"56","author":"D Nguyen","year":"2018","unstructured":"Nguyen D, Pietri FJ, Sporea C, Khodri M (2018) 17 patient quality assurance of the new halcyon linear accelerator (varian). Phys Med 56:10\u201311","journal-title":"Phys Med"},{"issue":"3","key":"207_CR8","doi-asserted-by":"publisher","first-page":"665","DOI":"10.1007\/s00521-018-3924-0","volume":"32","author":"S-H Wang","year":"2020","unstructured":"Wang S-H, Muhammad K, Hong J, Sangaiah AK, Zhang Y-D (2020) Alcoholism identification via convolutional neural network based on parametric relu, dropout, and batch normalization. Neural Comput Appl 32(3):665\u2013680","journal-title":"Neural Comput Appl"},{"key":"207_CR9","doi-asserted-by":"publisher","unstructured":"Mukhtar R, Butt S, Rafaye MA, Iqbal K, Mazhar S, Sadaf T (2020) An institutional review: dosimetry comparison between simultaneous integrated boost IMRT and VMAT for prostate cancer. J Radiother Pract. 1\u201311. https:\/\/doi.org\/10.1017\/S1460396920000370","DOI":"10.1017\/S1460396920000370"},{"issue":"1","key":"207_CR10","doi-asserted-by":"publisher","first-page":"300","DOI":"10.21037\/tcr.2019.12.75","volume":"9","author":"J Qian","year":"2020","unstructured":"Qian J, Yang Y, Xing P, Wang C, Tian Y, Lu X (2020) Differences in lower cranial nerve complications predicted by the NTCP model between rtog and reduced-volume IMRT planning in radiotherapy for nasopharyngeal carcinoma. Transl Cancer Res 9(1):300\u2013308","journal-title":"Transl Cancer Res"},{"issue":"31","key":"207_CR11","doi-asserted-by":"publisher","first-page":"e7685","DOI":"10.1097\/md.0000000000007685","volume":"96","author":"D Xu","year":"2017","unstructured":"Xu D, Li G, Li H, Jia F (2017) Comparison of IMRT versus 3D-CRT in the treatment of esophagus cancer: A systematic review and metaanalysis. Medicine 96(31):e7685. https:\/\/doi.org\/10.1097\/md.0000000000007685","journal-title":"Medicine"},{"issue":"5","key":"207_CR12","doi-asserted-by":"publisher","first-page":"629","DOI":"10.1080\/0284186X.2017.1400686","volume":"57","author":"SK Ahmed","year":"2018","unstructured":"Ahmed SK, Kruse JJ, Bradley TB, Beltran CJ, Laack NNI (2018) Clinical efficacy and safety of a highly conformal, supine, hybrid forward and inverse planned intensity modulated radiation therapy technique for craniospinal irradiation. Acta Oncol 57(5):629\u2013636","journal-title":"Acta Oncol"},{"issue":"2","key":"207_CR13","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1002\/mp.12058","volume":"44","author":"H Wang","year":"2017","unstructured":"Wang H, Dong P, Liu H, Xing L (2017) Development of an autonomous treatment planning strategy for radiation therapy with effective use of population-based prior data. Med Phys 44(2):389\u2013396","journal-title":"Med Phys"},{"issue":"7","key":"207_CR14","doi-asserted-by":"publisher","first-page":"2875","DOI":"10.1002\/mp.12930","volume":"45","author":"A Babier","year":"2018","unstructured":"Babier A, Boutilier JJ, McNiven AL, Chan TC (2018) Knowledge-based automated planning for oropharyngeal cancer. Med Phys 45(7):2875\u20132883","journal-title":"Med Phys"},{"key":"207_CR15","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1016\/j.oraloncology.2017.01.005","volume":"67","author":"M Rastogi","year":"2017","unstructured":"Rastogi M, Sapru S, Gupta P, Gandhi AK, Mishra SP, Srivastava AK, Khurana R, Hadi R, Sahni K, Farzana S (2017) Prospective evaluation of intensity modulated radiation therapy with simultaneous integrated boost (IMRT-SIB) in head and neck squamous cell carcinoma in patients not suitable for chemo-radiotherapy. Oral Oncol 67:10\u201316","journal-title":"Oral Oncol"},{"key":"207_CR16","doi-asserted-by":"publisher","first-page":"S1125","DOI":"10.1016\/S0167-8140(18)32364-8","volume":"127","author":"MA Gonzalez","year":"2018","unstructured":"Gonzalez MA, Maldonado X, Fa X, Planas J, Celma A, Pons A, Ruiz M, Mateos J, P\u00e9rez B, Alvarenga F et al (2018) Ep-2055: comparison of two correction protocols for IGRT in prostate cancer patients treated with IMRT. Radiother Oncol 127:S1125\u2013S1126","journal-title":"Radiother Oncol"},{"issue":"3","key":"207_CR17","doi-asserted-by":"publisher","first-page":"606","DOI":"10.1016\/j.ijrobp.2017.11.036","volume":"100","author":"JJ Caudell","year":"2018","unstructured":"Caudell JJ, Ward MC, Riaz N, Zakem SJ, Awan MJ, Dunlap NE, Isrow D, Hassanzadeh C, Vargo JA, Heron DE et al (2018) Volume, dose, and fractionation considerations for IMRT-based reirradiation in head and neck cancer: a multi-institution analysis. Int J Radiat Oncol Biol Phys 100(3):606\u2013617","journal-title":"Int J Radiat Oncol Biol Phys"},{"issue":"3","key":"207_CR18","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1016\/j.meddos.2015.05.003","volume":"40","author":"P-C Tu","year":"2015","unstructured":"Tu P-C, Lin C-H, Lee H-Y, Shaw S, Wu C-J (2015) Dosimetric comparison of whole breast irradiation with hybrid IMRT and inverse-fields IMRT. Med Dosim 40(3):262\u20137","journal-title":"Med Dosim"},{"issue":"9","key":"207_CR19","doi-asserted-by":"publisher","first-page":"3599","DOI":"10.1088\/1361-6560\/aa602b","volume":"62","author":"S Penfold","year":"2017","unstructured":"Penfold S, Zalas R, Casiraghi M, Brooke M, Censor Y, Schulte R (2017) Sparsity constrained split feasibility for dose-volume constraints in inverse planning of intensity-modulated photon or proton therapy. Phys Med Biol 62(9):3599","journal-title":"Phys Med Biol"},{"issue":"2","key":"207_CR20","doi-asserted-by":"publisher","first-page":"025028","DOI":"10.1088\/1361-6560\/aa9c96","volume":"63","author":"A Hagan","year":"2018","unstructured":"Hagan A, Sawant A, Folkerts M, Modiri A (2018) Multi-gpu configuration of 4d intensity modulated radiation therapy inverse planning using global optimization. Phys Med Biol 63(2):025028","journal-title":"Phys Med Biol"},{"issue":"4","key":"207_CR21","doi-asserted-by":"publisher","first-page":"1391","DOI":"10.1002\/mp.12838","volume":"45","author":"C Stambaugh","year":"2018","unstructured":"Stambaugh C, Ezzell G (2018) A clinically relevant IMRT QA workflow: design and validation. Med Phys 45(4):1391\u20131399","journal-title":"Med Phys"},{"issue":"6","key":"207_CR22","doi-asserted-by":"publisher","first-page":"2672","DOI":"10.1002\/mp.12890","volume":"45","author":"Y Interian","year":"2018","unstructured":"Interian Y, Rideout V, Kearney VP, Gennatas E, Morin O, Cheung J, Solberg T, Valdes G (2018) Deep nets vs expert designed features in medical physics: an IMRT QA case study. Med Phys 45(6):2672\u20132680","journal-title":"Med Phys"},{"issue":"18","key":"207_CR23","doi-asserted-by":"publisher","first-page":"185015","DOI":"10.1088\/1361-6560\/aadb3a","volume":"63","author":"H Liu","year":"2018","unstructured":"Liu H, Chen Y, Lu B (2018) A new inverse planning formalism with explicit DVH constraints and kurtosis-based dosimetric criteria. Phys Med Biol 63(18):185015","journal-title":"Phys Med Biol"},{"issue":"10","key":"207_CR24","doi-asserted-by":"publisher","first-page":"105004","DOI":"10.1088\/1361-6560\/aabd14","volume":"63","author":"A Babier","year":"2018","unstructured":"Babier A, Boutilier JJ, Sharpe MB, McNiven AL, Chan TC (2018) Inverse optimization of objective function weights for treatment planning using clinical dose-volume histograms. Phys Med Biol 63(10):105004","journal-title":"Phys Med Biol"},{"issue":"1","key":"207_CR25","doi-asserted-by":"publisher","first-page":"382","DOI":"10.1002\/mp.12665","volume":"45","author":"S Hashimoto","year":"2018","unstructured":"Hashimoto S, Fujita Y, Katayose T, Mizuno H, Saitoh H, Karasawa K (2018) Field-size correction factors of a radiophotoluminescent glass dosimeter for small-field and intensity-modulated radiation therapy beams. Med Phys 45(1):382\u2013390","journal-title":"Med Phys"},{"issue":"4","key":"207_CR26","doi-asserted-by":"publisher","first-page":"045015","DOI":"10.1088\/1361-6560\/aaa94f","volume":"63","author":"D Oconnor","year":"2018","unstructured":"Oconnor D, Yu V, Nguyen D, Ruan D, Sheng K (2018) Fraction-variant beam orientation optimization for non-coplanar IMRT. Phys Med Biol 63(4):045015","journal-title":"Phys Med Biol"},{"key":"207_CR27","doi-asserted-by":"publisher","unstructured":"Andreozzi JM, Mooney KE, BrAuza P, Curcuru A, Gladstone DJ, Pogue BW, Green O (2018) Remote cherenkov imaging-based quality assurance of a magnetic resonance image-guided radiotherapy system. Med Phys 45(6):2647\u20132659. https:\/\/doi.org\/10.1002\/mp.12919","DOI":"10.1002\/mp.12919"},{"issue":"4","key":"207_CR28","doi-asserted-by":"publisher","first-page":"1246","DOI":"10.1002\/mp.12165","volume":"44","author":"X Liu","year":"2017","unstructured":"Liu X, Pelizzari C, Belcher AH, Grelewicz Z, Wiersma RD (2017) Use of proximal operator graph solver for radiation therapy inverse treatment planning. Med Phys 44(4):1246\u20131256","journal-title":"Med Phys"},{"issue":"13","key":"207_CR29","doi-asserted-by":"publisher","first-page":"135024","DOI":"10.1088\/1361-6560\/aac8b4","volume":"63","author":"L Yuan","year":"2018","unstructured":"Yuan L, Zhu W, Ge Y, Jiang Y, Sheng Y, Yin F-F, Wu QJ (2018) Lung IMRT planning with automatic determination of beam angle configurations. Phys Med Biol 63(13):135024","journal-title":"Phys Med Biol"},{"issue":"9","key":"207_CR30","doi-asserted-by":"publisher","first-page":"4452","DOI":"10.1002\/mp.12410","volume":"44","author":"CV Guthier","year":"2017","unstructured":"Guthier CV, Damato AL, Viswanathan AN, Hesser JW, Cormack RA (2017) A fast multitarget inverse treatment planning strategy optimizing dosimetric measures for high-dose-rate (HDR) brachytherapy. Med Phys 44(9):4452\u20134462","journal-title":"Med Phys"},{"issue":"2\u20133","key":"207_CR31","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1016\/j.tcs.2005.05.020","volume":"344","author":"M Dorigo","year":"2005","unstructured":"Dorigo M, Blum C (2005) Ant colony optimization theory: a survey. Theor Comput Sci 344(2\u20133):243\u2013278","journal-title":"Theor Comput Sci"}],"container-title":["Complex &amp; Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-020-00207-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s40747-020-00207-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-020-00207-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,9]],"date-time":"2023-06-09T17:23:44Z","timestamp":1686331424000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s40747-020-00207-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,13]]},"references-count":31,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2023,6]]}},"alternative-id":["207"],"URL":"https:\/\/doi.org\/10.1007\/s40747-020-00207-7","relation":{},"ISSN":["2199-4536","2198-6053"],"issn-type":[{"type":"print","value":"2199-4536"},{"type":"electronic","value":"2198-6053"}],"subject":[],"published":{"date-parts":[[2020,10,13]]},"assertion":[{"value":"30 July 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 September 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 October 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"On behalf of all authors, the corresponding author states that there is no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}