Nuclear Medicine Department, Gui de Chauliac University Hospital, 80, Avenue Augustin Fliche, 34295, Montpellier Cedex 5, France.
Haematology Department, Saint Eloi University Hospital, 80, Avenue Augustin Fliche, 34295, Montpellier Cedex 5, France.
Med Phys. 2017 Sep;44(9):4608-4619. doi: 10.1002/mp.12349. Epub 2017 Aug 2.
We investigated whether metabolic, textural, and morphological tumoral indices evaluated on baseline PET-CT were predictive of early metabolic response on interim PET-CT in a cohort of patients with bulky Hodgkin and non-Hodgkin malignant lymphomas.
This retrospective study included 57 patients referred for initial PET-CT examination. In-house dedicated software was used to delineate tumor contours using a fixed 30% threshold of SUV max and then to compute tumoral metabolic parameters (SUV max, mean, peak, standard deviation, skewness and kurtosis, metabolic tumoral volume (MTV), total lesion glycolysis, and area under the curve of the cumulative histogram), textural parameters (Moran's and Geary's indices, energy, entropy, contrast, correlation derived from the gray-level co-occurrence matrix, area under the curve of the power spectral density, auto-correlation distance, and granularity), and shape parameters (surface, asphericity, convexity, surfacic extension, and 2D and 3D fractal dimensions). Early metabolic response was assessed on interim PET-CT using the Deauville 5-point scale and patients were ranked according to the Lugano classification as complete or not complete metabolic responders. The impact of the segmentation method (alternate threshold at 41%) and image resolution (Gaussian postsmoothing of 3, 5, and 7 mm) was investigated. The association of the proposed parameters with early response was assessed in univariate and multivariate analyses. Their added predictive value was explored using supervised classification by support vector machines (SVM). We evaluated in leave-one-out cross-validation three SVMs admitting as input features (a) MTV, (b) MTV + histological type, and (c) MTV + histology + relevant texture/shape indices.
Features associated with complete metabolic response were low MTV (P = 0.01), low TLG (P = 0.003), high power spectral density AUC (P = 0.007), high surfacic extension (P = 0.006), low 2D fractal dimension (P = 0.007), and low 3D fractal dimension (P = 0.003). The prognostic value of these metrics was optimal with the 30% segmentation threshold and overall was progressively altered with decreasing image resolution. In cross-validation, the SVM accounting for texture and shape achieved the highest predictive value with ROC AUC of 0.82 and 80% accuracy (compared with 0.68 and 61% for MTV, and 0.65 and 68% for MTV + histology).
The combination of usual prognostic factors with appropriately chosen textural and shape parameters evaluated on baseline PET-CT improves the prediction of early metabolic response in bulky lymphoma.
我们研究了基线 PET-CT 上评估的代谢、纹理和形态肿瘤学指标是否可以预测大肿块霍奇金和非霍奇金恶性淋巴瘤患者的中期 PET-CT 上的早期代谢反应。
这项回顾性研究纳入了 57 名接受初始 PET-CT 检查的患者。使用内部专用软件，使用 SUV max 的固定 30%阈值来描绘肿瘤轮廓，然后计算肿瘤代谢参数（SUV max、平均值、峰值、标准差、偏度和峰度、代谢肿瘤体积（MTV）、总病变糖酵解和累积直方图曲线下面积）、纹理参数（Moran 和 Geary 指数、能量、熵、对比度，来自灰度共生矩阵的相关性，功率谱密度曲线下面积、自相关距离和粒度）和形状参数（表面积、非球形度、凸度、表面积扩展以及二维和三维分形维数）。中期 PET-CT 上使用 Deauville 5 分制评估早期代谢反应，根据 Lugano 分类将患者分为完全或不完全代谢反应者。研究了分割方法（41%的交替阈值）和图像分辨率（3、5 和 7 毫米的高斯平滑）的影响。在单变量和多变量分析中评估了这些参数与早期反应的相关性。使用支持向量机（SVM）进行监督分类来探索它们的附加预测价值。我们在留一法交叉验证中评估了三个 SVM，它们将 MTV、MTV+组织学类型和 MTV+组织学+相关纹理/形状指数作为输入特征。
与完全代谢反应相关的特征是低 MTV（P=0.01）、低 TLG（P=0.003）、高功率谱密度 AUC（P=0.007）、高表面积扩展（P=0.006）、低二维分形维数（P=0.007）和低三维分形维数（P=0.003）。这些指标的预后价值在 30%分割阈值下最佳，并且随着图像分辨率的降低而逐渐改变。在交叉验证中，考虑纹理和形状的 SVM 达到了最高的预测值，ROC AUC 为 0.82 和 80%的准确率（与 MTV 的 0.68 和 61%和 MTV+组织学的 0.65 和 68%相比）。
在基线 PET-CT 上评估常用预后因素与适当选择的纹理和形状参数相结合，可以提高大肿块淋巴瘤早期代谢反应的预测。
