Correlation of texture feature analysis with bone marrow infiltration in initial staging of patients with lymphoma using (18)F-fluorodeoxyglucose positron emission tomography combined with computed tomography.
Correlation of texture feature analysis with bone marrow infiltration in initial staging of patients with lymphoma using (18)F-fluorodeoxyglucose positron emission tomography combined with computed tomography.
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DOI：
10.5114/pjr.2020.99833
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发表时间：
2020
影响因子：
1.2
通讯作者：
El-Bahnasawy HH
中科院分区：
文献类型：
--
作者：
Kenawy MA;Khalil MM;Abdelgawad MH;El-Bahnasawy HH
探讨与其他常规PET指标相比，氟-18-氟脱氧葡萄糖（18 F-FDG）正电子发射断层扫描-计算机断层扫描（PET/CT）的放射组学特征是否与骨髓浸润（BMI）相关。44例患者（病理证实为淋巴瘤疾病）接受了分期18F-FDG PET/CT扫描。原发性肿瘤半自动或手动分割，阈值标准化摄取值（SUV）为3。从8种不同的纹理中提取了73个特征。斯皮尔曼相关性用于检验特征与常规定量指标（如SUV、代谢肿瘤体积和总病变糖酵解）的相关性。使用受试者工作特征（ROC）曲线推导每个研究参数的特异性和灵敏度（包括95%置信区间[CI]）。单变量和多变量分析用于确定与BMI相关的独立预测因子。对于强相关性和中等相关性，常规PET指标和特征之间的正相关性范围在0.50和0.97之间（33个显著关联特征），负相关性范围在-0.52到-0.97之间（3个显著关联特征）。ROC曲线分析显示，高强度长时间强调4 bin、高强度大区域强调64 bin、长时间强调（LRE）64 bin、大区域强调64 bin、最大频谱8 bin、忙碌64 bin、代码相似性32和64 bin是BMI在其他特征中的显著判别因素（曲线下面积> 0.682，p < 0.05）。纹理特征的单变量分析表明，代码相似性和长期强调（均为64箱）是骨髓受累的显著预测因子。多变量分析显示，LRE（64 bin，p = 0.031）的比值比为1.022，95% CI为（1.002-1.043），是骨髓受累的独立变量。18F-FDG PET/CT放射组学特征与使用18F-FDG PET/CT诊断为淋巴瘤的患者的BMI视觉评估具有协同作用。进一步评估长期重点是非常必要的。
To explore whether radiomic features of fluorine-18-fluorodeoxyglucose (18F-FDG) positron emission tomo-graphy–computed tomography (PET/CT) has association with bone marrow infiltration (BMI) in comparison to other conventional PET metrics. Forty-four patients (with pathologically proven lymphoma disease) underwent staging 18F-FDG PET/CT scan. Primary tumour was semi-automatically or manually segmented with a threshold standardised uptake value (SUV) of 3. A total of 73 features were extracted from eight different textures. Spearman correlation was used to test the correlation of features with conventional quantitative metrics such as SUV, metabolic tumour volume, and total lesion glycolysis. Specificity and sensitivity (including 95% confidence intervals [CI]) for each of the studied parameters were derived using receiver operative characteristic (ROC) curves. Univariate and multivariate analyses were used to identify independent predictors associated with BMI. Correlation between conventional PET metrics and features ranged between 0.50 and 0.97 for positive correlation (33 significant association features) and ranged from –0.52 to –0.97 for inverse correlation (three significant association features) for both strong and moderate correlations. Analysis of ROC curves showed that high-intensity long-run emphasis 4 bin, high-intensity large zone emphasis 64 bin, long-run emphasis (LRE) 64 bin, large-zone emphasis 64 bin, max spectrum 8 bin, busyness 64 bin, and code similarity 32 and 64 bin were significant discriminators of BMI among other features (area under curve > 0.682, p < 0.05). Univariate analyses of texture features showed that code similarity and long-run emphasis (both 64 bin) were significant predictors of bone marrow involvement. Multivariate analyses revealed that LRE (64 bin, p = 0.031) with an odds ratio of 1.022 and 95% CI of (1.002–1.043) were independent variables for bone marrow involvement. 18F-FDG PET/CT radiomic features are synergistic to visual assessment of BMI in patients diagnosed with lymphoma using 18F-FDG PET/CT. Further assessment of long-run emphasis is highly warranted.
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