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单指数、双指数和拉伸指数信号模型在评估喉和下咽鳞状细胞癌(LHSCC)患者放化疗后预后和生存风险中的应用。

Utility of mono-exponential, bi-exponential, and stretched exponential signal models of intravoxel incoherent motion (IVIM) to predict prognosis and survival risk in laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC) patients after chemoradiotherapy.

机构信息

Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.

Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, 518116, China.

出版信息

Jpn J Radiol. 2023 Jul;41(7):712-722. doi: 10.1007/s11604-023-01399-x. Epub 2023 Feb 27.

DOI:10.1007/s11604-023-01399-x
PMID:36847996
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10313558/
Abstract

PURPOSE

To investigate the predictive power of mono-exponential, bi-exponential, and stretched exponential signal models of intravoxel incoherent motion (IVIM) in prognosis and survival risk of laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC) patients after chemoradiotherapy.

MATERIALS AND METHODS

Forty-five patients with laryngeal or hypopharyngeal squamous cell carcinoma were retrospectively enrolled. All patients had undergone pretreatment IVIM examination, subsequently, mean apparent diffusion coefficient (ADCmean), maximum ADC (ADCmax), minimum ADC (ADCmin) and ADCrange (ADCmax - ADCmean) by mono-exponential model, true diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f) by bi-exponential model, distributed diffusion coefficient (DDC), and diffusion heterogeneity index (α) by stretched exponential model were measured. Survival data were collected for 5 years.

RESULTS

Thirty-one cases were in the treatment failure group and fourteen cases were in the local control group. Significantly lower ADCmean, ADCmax, ADCmin, D, f, and higher D* values were observed in the treatment failure group than in the local control group (p < 0.05). D* had the greatest AUC of 0.802, with sensitivity and specificity of 77.4 and 85.7% when D* was 38.85 × 10 mm/s. Kaplan-Meier survival analysis showed that the curves of N stage, ADCmean, ADCmax, ADCmin, D, D*, f, DDC, and α values were significant. Multivariate Cox regression analysis showed ADCmean and D* were independently correlated with progression-free survival (PFS) (hazard ratio [HR] = 0.125, p = 0.001; HR = 1.008, p = 0.002, respectively).

CONCLUSION

The pretreatment parameters of mono-exponential and bi-exponential models were significantly correlated with prognosis of LHSCC, ADCmean and D* values were independent factors for survival risk prediction.

摘要

目的

探讨单指数、双指数和拉伸指数信号模型在喉和下咽鳞状细胞癌(LHSCC)患者放化疗后预后和生存风险预测中的预测能力。

材料与方法

回顾性纳入 45 例喉或下咽鳞状细胞癌患者。所有患者均行治疗前 IVIM 检查,随后测量单指数模型的平均表观扩散系数(ADCmean)、最大 ADC(ADCmax)、最小 ADC(ADCmin)和 ADC 范围(ADCmax-ADCmean),双指数模型的真扩散系数(D)、伪扩散系数(D*)、灌注分数(f),拉伸指数模型的分布扩散系数(DDC)和扩散异质性指数(α)。收集 5 年的生存数据。

结果

31 例为治疗失败组,14 例为局部控制组。治疗失败组的 ADCmean、ADCmax、ADCmin、D、f 和 D值明显低于局部控制组(p<0.05)。当 D为 38.85×10mm/s 时,D的 AUC 最大为 0.802,灵敏度和特异性分别为 77.4%和 85.7%。Kaplan-Meier 生存分析显示,N 分期、ADCmean、ADCmax、ADCmin、D、D、f、DDC 和α值的曲线有显著差异。多变量 Cox 回归分析显示,ADCmean 和 D*与无进展生存期(PFS)独立相关(风险比[HR]分别为 0.125,p=0.001;HR 为 1.008,p=0.002)。

结论

单指数和双指数模型的治疗前参数与 LHSCC 的预后显著相关,ADCmean 和 D*值是生存风险预测的独立因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52d6/10313558/77694879c7bb/11604_2023_1399_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52d6/10313558/e6fd5891f6b2/11604_2023_1399_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52d6/10313558/b114386fdfcb/11604_2023_1399_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52d6/10313558/f4942d83fa07/11604_2023_1399_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52d6/10313558/77694879c7bb/11604_2023_1399_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52d6/10313558/e6fd5891f6b2/11604_2023_1399_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52d6/10313558/b114386fdfcb/11604_2023_1399_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52d6/10313558/f4942d83fa07/11604_2023_1399_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52d6/10313558/77694879c7bb/11604_2023_1399_Fig4_HTML.jpg

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