{
    "created": "2021-07-01 01:53:13",
    "updated": "2026-06-20 14:43:47",
    "id": "a70c97a0-1575-4cdd-9e83-5441406b6560",
    "version": 4,
    "ds_topic": null,
    "title_cn": "基于肿瘤百分剂量覆盖度、正常组织和危及器官的容积剂量等为参数的评判模型",
    "title_en": "A evaluation model was based on the percentage dose coverage of tumor, volume dose of normal tissue and organs at risk",
    "ds_abstract": "<p>&emsp;&emsp;该文档是对于粒子治疗中的重要参数的一份评判模型，该模型的建立充分考虑肿瘤百分剂量覆盖度、正常组织和危及器官的容积剂量等参数，评估治疗计划的优劣性和治疗的有效性，给出评判结果，以供医生和药剂师选择和修改治疗计划。</p>",
    "ds_source": "<p>&emsp;&emsp;本研究建立了光子、碳离子和其他粒子联合治疗，以肿瘤百分剂量覆盖度、正常组织和危及器官的容积剂量等作为参数的评判模型。并建立端到端的基于深度学习的方法来预测放疗计划的三维剂量分布，实现了上述的评判模型。通过自主开发端到端的卷积神经网络和结构图像的预处理算法等，使模型取得较准确的预测效果。该模型既可用于光子或碳离子或多粒子联合放疗计划预测。预测的剂量可直接应用于计算肿瘤控制概率和正常组织并发症概率，如对鼻咽癌调强放疗后甲状腺功能减退发生概率的预测。</p>",
    "ds_process_way": "<p>&emsp;&emsp;本研究建立了光子、碳离子和其他粒子联合治疗，以肿瘤百分剂量覆盖度、正常组织和危及器官的容积剂量等作为参数的评判模型。并建立端到端的基于深度学习的方法来预测放疗计划的三维剂量分布，实现了上述的评判模型。</p>",
    "ds_quality": "<p>&emsp;&emsp;数据来源于临床试验，数据质量良好。</p>",
    "ds_acq_start_time": "2017-07-01 00:00:00",
    "ds_acq_end_time": "2019-12-31 00:00:00",
    "ds_acq_place": "甘肃兰州",
    "ds_acq_lon_east": null,
    "ds_acq_lat_south": null,
    "ds_acq_lon_west": null,
    "ds_acq_lat_north": null,
    "ds_acq_alt_low": null,
    "ds_acq_alt_high": null,
    "ds_share_type": "apply-access",
    "ds_total_size": 17109669,
    "ds_files_count": 2,
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    "ds_coordinate": "无",
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    "ds_thumbnail": "a70c97a0-1575-4cdd-9e83-5441406b6560.png",
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    "ds_ref_way": "肖国青，基于肿瘤百分剂量覆盖度、正常组织和危及器官的容积剂量等为参数的评判模型，国家冰川冻土沙漠科学数据中心(http://www.ncdc.ac.cn/)，2021，doi：10.12072/ncdc.IMP.db2509.2022",
    "paper_ref_way": "",
    "ds_ref_instruction": "",
    "ds_from_station": null,
    "organization_id": "9971252d-7beb-4464-bc08-bdcc5a1d7dd1",
    "ds_serv_man": "敏玉芳",
    "ds_serv_phone": "0931-4967596",
    "ds_serv_mail": "ncdc@lzb.ac.cn",
    "doi_value": "",
    "subject_codes": [],
    "quality_level": 3,
    "publish_time": "2022-08-26 17:35:00",
    "last_updated": "2022-12-03 02:10:09",
    "protected": false,
    "protected_to": null,
    "lang": "zh",
    "cstr": "11738.11.ncdc.IMP.db2509.2022",
    "i18n": {
        "en": {
            "title": "A evaluation model was based on the percentage dose coverage of tumor, volume dose of normal tissue and organs at risk",
            "ds_format": "",
            "ds_source": "<pre><code>\n</code></pre>\n<p>&emsp; In this study, we established the evaluation model of the combined treatment of photons, carbon ions and other particles, with the percentage dose coverage of tumor, the volume dose of normal tissues and organs at risk as parameters. An end-to-end method based on deep learning is established to predict the three-dimensional dose distribution of radiotherapy plan, and the above evaluation model is realized. Through the self-developed end-to-end convolution neural network and the preprocessing algorithm of structural images, the model can achieve more accurate prediction results. The model can be used for the prediction of photon or carbon ion or multi particle combined radiotherapy plan. The predicted dose can be directly used to calculate the probability of tumor control and the probability of normal tissue complications, such as the probability of hypothyroidism after intensity-modulated radiotherapy for nasopharyngeal carcinoma</ p>",
            "ds_quality": "<pre><code>\n</code></pre>\n<p>&emsp; The data are from clinical trials, and the data quality is good</ p>",
            "ds_ref_way": "",
            "ds_abstract": "<pre><code>\n</code></pre>\n<p>  This document is an evaluation model for important parameters in particle therapy. The model is established by fully considering such parameters as tumor percentage dose coverage, volume dose of normal tissue and dangerous organs, evaluating the advantages and disadvantages of treatment plan and the effectiveness of treatment, and giving the evaluation results for doctors and pharmacists to select and modify treatment plans</p>",
            "ds_time_res": "",
            "ds_acq_place": "Lanzhou, Gansu",
            "ds_space_res": "",
            "ds_projection": "",
            "ds_process_way": "<pre><code>\n</code></pre>\n<p>&emsp;In this study, we established the evaluation model of the combined treatment of photons, carbon ions and other particles, with the percentage dose coverage of tumor, the volume dose of normal tissues and organs at risk as parameters. An end-to-end method based on deep learning is established to predict the three-dimensional dose distribution of radiotherapy plan, and the above evaluation model is realized</ p>",
            "ds_ref_instruction": "                    "
        }
    },
    "submit_center_id": "ncdc",
    "data_level": 0,
    "recommendation_value": 0,
    "license_type": "https://creativecommons.org/licenses/by/4.0/",
    "doi_reg_from": "reg_local",
    "cstr_reg_from": "reg_local",
    "doi_not_reg_reason": null,
    "cstr_not_reg_reason": null,
    "is_paper_in_submitting": false,
    "belong_to_nieer": false,
    "ds_topic_tags": [
        "百分剂量",
        "容积剂量",
        "评判模型"
    ],
    "ds_subject_tags": [],
    "ds_class_tags": [],
    "ds_locus_tags": [
        "兰州",
        "甘肃省"
    ],
    "ds_time_tags": [
        2017,
        2018,
        2019
    ],
    "ds_contributors": [
        {
            "true_name": "肖国青",
            "email": "xiaogq@impcas.ac.cn",
            "work_for": "中国科学院近代物理研究所",
            "country": "中国"
        }
    ],
    "ds_meta_authors": [
        {
            "true_name": "申国盛",
            "email": "sgs2005@impcas.ac.cn",
            "work_for": "中国科学院近代物理研究所",
            "country": "中国"
        }
    ],
    "ds_managers": [
        {
            "true_name": "肖国青",
            "email": "xiaogq@impcas.ac.cn",
            "work_for": "中国科学院近代物理研究所",
            "country": "中国"
        }
    ],
    "category": "其他"
}