首页|基于18F-PSMA-1007 PET/CT影像组学模型在前列腺癌与前列腺增生鉴别诊断中的价值

基于18F-PSMA-1007 PET/CT影像组学模型在前列腺癌与前列腺增生鉴别诊断中的价值

扫码查看
目的 评估前列腺特异膜抗原(PSMA)PET/CT影像组学模型对前列腺癌和前列腺增生(BPH)鉴别诊断的价值.方法 回顾性收集2020年5月至2022年9月在西安交通大学第一附属医院行前列腺穿刺活组织检查和18F-PSMA-1007 PET/CT显像的50例前列腺癌[年龄(70.0±8.8)岁]和25例BPH患者[年龄(66.9±9.4)岁]的资料,采用随机种子数按7∶3分为训练集(n=53)和测试集(n=22).基于PET/CT配准图像勾画前列腺ROI,提取PET和CT影像组学特征,使用最大相关最小冗余(mRMR)和最小绝对收缩和选择算子(LASSO)算法进行特征筛选.采用logistic回归分别构建PET和PET/CT影像组学模型.通过ROC曲线评价模型的诊断效能,并与游离前列腺特异抗原(fPSA)/总前列腺特异性抗原(tPSA)比值、PET常规代谢参数以及前列腺癌分子成像标准化评估(PROMISE)等指标和参数进行比较(Delong检验).结果 PET影像组学模型共纳入7个特征,PET/CT影像组学模型分别纳入3个CT特征和4个PET特征.训练集、测试集中PET和PET/CT影像组学模型 AUC 分别为 0.941、0.914 和 0.965、0.914,均高于 fPSA/tPSA(0.719 和 0.710)、SUVmax(0.748 和 0.800)、SUV 峰值(SUVpeak;0.722 和 0.771)、肿瘤代谢体积(MTV;0.640 和 0.595)、病灶总摄取值(TLU;0.525 和 0.476)以及 PROMISE(0.644 和 0.667)的 AUC[训练集 z 值:-6.26~-3.13,均P<0.01;测试集 z 值:-3.16~-1.08,P>0.05(fPSA/tPSA、SUVmax、SUVpeak)或 P<0.05(MTV、TLU、PROMISA)].PET和PET/CT影像组学模型在测试集中鉴别诊断的准确性、灵敏度和特异性分别为86.36%(19/22)、13/15、6/7和90.91%(20/22)、15/15、5/7.结论 相较于临床指标和PET常规参数,基于PSMA PET/CT的影像组学模型可进一步提高对前列腺癌和BPH鉴别诊断的效能.
Value of 18F-PSMA-1007 PET/CT-based radiomics model for differential diagnosis between prostate cancer and benign prostatic hyperplasia
Objective To evaluate the value of prostate specific membrane antigen(PSMA)PET/CT-based radiomics models in differentiation between prostate cancer and benign prostatic hyperplasia(BPH).Methods Data from 50 patients with prostate cancer(age:(70.0±8.8)years)and 25 patients with BPH(age:(66.9±9.4)years)who underwent 18F-PSMA-1007 PET/CT imaging and prostate biopsy in the First Affiliated Hospital of Xi'an Jiaotong University from May 2020 to September 2022 were retro-spectively collected.Patients were divided into the training set(n=53)and test set(n=22)in the ratio of 7∶3 by using random seed number.The RO Is were delineated based on PET and CT images,and radiomics features were extracted respectively.Feature selection was performed using the minimum redundancy and maximum relevance(mRMR)and the least absolute shrinkage and selection operator(LASSO)algorithm.PET and PET/CT radiomics models were generated using logistic regression.ROC curve analysis was em-ployed for model evaluation.In addition,comparisons of the 2 radiomics models with parameters including the ratio of free prostate specific antigen(fPSA)/total prostate specific antigen(tPSA),PET metabolic pa-rameters,as well as prostate cancer molecular imaging standardize evaluation(PROMISE)were conducted(Delong test).Results A total of 7 features were included in the PET radiomics model,and 3 CT-based features and 4 PET-based features were included in the PET/CT radiomics model.The AUCs of PET and PET/CT radiomics models in the training set and test set were 0.941,0.914 and 0.965,0.914,respective-ly,which were higher than those of fPSA/tPSA(0.719 and 0.710),SUVmax(0.748 and 0.800),peak of SUV(SUVpeak,0.722 and 0.771),metabolic tumor volume(MTV,0.640 and 0.595),total lesion uptake(TLU,0.525 and 0.476)and PROMISE(0.644 and 0.667)[z values for the training set:from-6.26 to-3.13,all P<0.01;z values for the test set:from-3.16 to-1.08,P>0.05(fPSA/tPSA,SUVmax,SUVpeak)or P<0.05(MTV,TLU,PROMISE)].The differential diagnostic accuracy,sensitivity and specificity of PET and PET/CT radiomics models in the test set were 86.36%(19/22),13/15,6/7 and 90.91%(20/22),15/15,5/7,respectively.Conclusion Compared with the clinical and PET parameters,PSMA PET/CT-based radiomics model can further improve the efficiency of differential diagnosis between prostate cancer and BPH.

Prostatic neoplasmsProstatic hyperplasiaProstate-specific membrane antigenRa-diomicsPositron-emission tomographyTomography,X-ray computed

罗量、常儒玺、李运轩、高俊刚、刘翔、段小艺

展开 >

西安交通大学第一附属医院PET/CT室,西安 710061

前列腺肿瘤 前列腺增生 前列腺特异膜抗原 影像组学 正电子发射断层显像术 体层摄影术,X线计算机

2024

中华核医学与分子影像杂志
中华医学会

中华核医学与分子影像杂志

CSTPCD北大核心
影响因子:1.107
ISSN:2095-2848
年,卷(期):2024.44(2)
  • 18