Abenavoli Elisabetta M, Linguanti Flavia, Anichini Matilde, Miele Vittorio, Mungai Francesco, Palazzo Marianna, Nassi Luca, Puccini Benedetta, Romano Ilaria, Sordi Benedetta, Sciagrà Roberto, Simontacchi Gabriele, Vannucchi Alessandro M, Berti Valentina
Nuclear Medicine Unit, Department of Experimental and Clinical Biomedical Sciences 'Mario Serio', University of Florence, Florence, Italy.
Department of Radiology, Azienda Ospedaliero Universitaria Careggi, Florence, Italy.
Hematol Oncol. 2024 Mar;42(2):e3261. doi: 10.1002/hon.3261.
To recognize patients at high risk of refractory disease, the identification of novel prognostic parameters improving stratification of newly diagnosed Hodgkin Lymphoma (HL) is still needed. This study investigates the potential value of metabolic and texture features, extracted from baseline 18F-FDG Positron Emission Tomography/Computed Tomography (PET) and Contrast-Enhanced Computed Tomography scan (CECT), together with clinical data, in predicting first-line therapy refractoriness (R) of classical HL (cHL) with mediastinal bulk involvement. We reviewed 69 cHL patients who underwent staging PET and CECT. Lesion segmentation and texture parameter extraction were performed using the freeware software LIFEx 6.3. The prognostic significance of clinical and imaging features was evaluated in relation to the development of refractory disease. Receiver operating characteristic curve, Cox proportional hazard regression and Kaplan-Meier analyses were performed to examine the potential independent predictors and to evaluate their prognostic value. Among clinical characteristics, only stage according to the German Hodgkin Group (GHSG) classification system significantly differed between R and not-R. Among CECT variables, only parameters derived from second order matrices (gray-level co-occurrence matrix (GLCM) and gray-level run length matrix (GLRLM) demonstrated significant prognostic power. Among PET variables, SUVmean, several variables derived from first (histograms, shape), and second order analyses (GLCM, GLRLM, NGLDM) exhibited significant predictive power. Such variables obtained accuracies greater than 70% at receiver operating characteristic analysis and their PFS curves resulted statistically significant in predicting refractoriness. At multivariate analysis, only HISTO_EntropyPET extracted from PET (HISTO_Entropy ) and GHSG stage resulted as significant independent predictors. Their combination identified 4 patient groups with significantly different PFS curves, with worst prognosis in patients with higher HISTO_Entropy values, regardless of the stage. Imaging radiomics may provide a reference for prognostic evaluation of patients with mediastinal bulky cHL. The best prognostic value in the prediction of R versus not-R disease was reached by combining HISTO_Entropy with GHSG stage.
为了识别难治性疾病的高危患者,仍需要确定能够改善新诊断霍奇金淋巴瘤(HL)分层的新的预后参数。本研究调查了从基线18F-FDG正电子发射断层扫描/计算机断层扫描(PET)和对比增强计算机断层扫描(CECT)中提取的代谢和纹理特征以及临床数据,对伴有纵隔肿块的经典HL(cHL)一线治疗难治性(R)的预测价值。我们回顾了69例接受分期PET和CECT检查的cHL患者。使用免费软件LIFEx 6.3进行病变分割和纹理参数提取。评估临床和影像特征与难治性疾病发生的预后意义。进行受试者工作特征曲线、Cox比例风险回归和Kaplan-Meier分析,以检查潜在的独立预测因素并评估其预后价值。在临床特征中,只有根据德国霍奇金淋巴瘤研究组(GHSG)分类系统的分期在R组和非R组之间存在显著差异。在CECT变量中,只有从二阶矩阵(灰度共生矩阵(GLCM)和灰度游程长度矩阵(GLRLM))导出的参数显示出显著的预后能力。在PET变量中,SUVmean、几个从一阶(直方图、形状)和二阶分析(GLCM、GLRLM、邻域灰度差矩阵(NGLDM))导出的变量表现出显著的预测能力。这些变量在受试者工作特征分析中获得了大于70%的准确率,并且它们的无进展生存期(PFS)曲线在预测难治性方面具有统计学意义。在多变量分析中,只有从PET中提取的HISTO_EntropyPET(HISTO_Entropy)和GHSG分期是显著的独立预测因素。它们的组合确定了4个PFS曲线显著不同的患者组,无论分期如何,HISTO_Entropy值较高的患者预后最差。影像组学可为伴有纵隔大肿块的cHL患者的预后评估提供参考。通过将HISTO_Entropy与GHSG分期相结合,在预测R组与非R组疾病方面达到了最佳预后价值。