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基于CT影像组学的宫颈癌单纯放疗后急性血液毒性预测的初步研究

Preliminary study on the prediction of acute hematologic toxicity in cervical cancer patients after radiotherapy alone based on CT radiomics

  • 摘要: 宫颈癌是女性中发病率和死亡率位居第四的癌症,是最常见的妇科恶性肿瘤1, 2。外照射放射治疗(External beam radiation therapy, EBRT)是宫颈癌治疗中主要的治疗手段之一3, 4。在包括髂骨、骶骨、股骨近端和下腰椎等骨盆区域,集中了人体超过一半的活性造血骨髓(Bone marrow, BM)而EBRT使这些危及器官不可避免受到照射5。骨盆照射不仅通过直接损伤放射敏感的骨髓干细胞影响骨髓功能,还可能通过辐射损伤诱导生长因子的异常释放,导致骨髓微环境的改变,而个体间异质性(如骨髓的放射敏感性和造血储备能力)在HT发生和发展中的具有关键作用6。HT限制了患者对治疗的耐受性,引起EBRT计划中断,等效生物剂量降低,进而削弱肿瘤克隆源性细胞杀灭效应,会影响对肿瘤的控制,每延迟1天治疗时间,局部疾病控制率减少约1%7。目前对于HT的预测工具较少,因此,寻找准确有效的预测方法评估HT风险,并针对高危患者进行危及器保护和早期临床干预,可减少HT的发生,具有重要的临床意义。影像组学提供了一种基于影像数据研究组织异质性的科学工具,通过从医学影像中提取高通量定量特征,能够反映组织的表型特性,这些特性与其生物学行为和潜在异质性密切相关8, 9。在本研究中,我们基于宫颈癌患者放疗前的CT影像组学特征整合剂量学参数,探索并建立预测急性HT的多模态预测模型,为临床提前干预与治疗方案优化提供科学依据。

     

    Abstract: s: Objective This study aims to construct a predictive model for acute hematologic toxicity (HT) in cervical cancer patients undergoing radiotherapy alone by utilizing CT radiomic features prior to treatment, combined with clinical and dosimetric characteristics.Methods We retrospectively analyzed data from 82 cervical cancer patients treated with radiotherapy alone at Affiliated Hospital of Jiangnan University (June 2022–March 2025). Patients were divided into training and test sets (8: 2 ratio), with ≥grade 2 HT as the endpoint. Clinical features and dosimetric parameters of pelvic structures (lumbosacral spine, lower pelvis, ilium, and overall pelvis) were collected. A total of 1, 046 radiomic features were extracted from the entire pelvic structure using PyRadiomics. First, a Clinical-dose model was constructed based on 56 clinical/dosimetric features after Z-score normalization, Spearman correlation analysis (>0.9), and LASSO regression with K-nearest neighbor (KNN) machine learning via 5-fold cross-validation. A Radiomics model was then developed using the same methodology. Finally, a Hybrid model integrating both feature sets was established. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC).Results Of the patients, 48.8% (40/82) developed ≥grade 2 HT. Univariate analysis found that V20 in the lumbosacral spine was significantly associated with the development of grade ≥2 HT (P<0.05). The radiomics prediction model achieved an AUC of 0.802 (95% CI: 0.702-0.902) in the training set and 0.703 (95% CI: 0.425-0.981) in the test set15. The clinical-dose model demonstrated AUC values of 0.750 (95% CI: 0.634-0.866) in the training set and 0.633 (95% CI: 0.362-0.904) in the test set25. The hybrid model outperformed both, with AUCs of 0.861 (95% CI: 0.778-0.944) in the training set and 0.781 (95% CI: 0.550-1.000) in the test set.Conclusion Pre-radiotherapy CT radiomic features combined with dosimetric characteristics can predict the occurrence of acute hematologic toxicity in cervical cancer patients, potentially aiding in early clinical intervention.

     

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