Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India.
Department of Radio Diagnosis, All India Institute of Medical Sciences, New Delhi, India.
NMR Biomed. 2021 Feb;34(2):e4426. doi: 10.1002/nbm.4426. Epub 2020 Oct 20.
The efficacy of MRI-based statistical texture analysis (TA) in predicting chemotherapy response among patients with osteosarcoma was assessed. Forty patients (male: female = 31:9; age = 17.2 ± 5.7 years) with biopsy-proven osteosarcoma were analyzed in this prospective study. Patients were scheduled for three cycles of neoadjuvant chemotherapy (NACT) and diffusion-weighted MRI acquisition at three time points: at baseline (t0), after the first NACT (t1) and after the third NACT (t2) using a 1.5 T scanner. Eight patients (nonsurvivors) died during NACT while 34 patients (survivors) completed the NACT regimen followed by surgery. Histopathological evaluation was performed in the resected tumor to assess NACT response (responder [≤50% viable tumor] and nonresponder [>50% viable tumor]) and revealed nonresponder: responder = 20:12. Apparent diffusion coefficient (ADC) and intravoxel incoherent motion (IVIM) parameters, diffusion coefficient (D), perfusion coefficient (D*) and perfusion fraction (f) were evaluated. A total of 25 textural features were evaluated on ADC, D, D* and f parametric maps and structural T1-weighted (T1W) and T2-weighted (T2W) images in the entire tumor volume using 3D TA methods gray-level cooccurrence matrix (GLCM), neighborhood gray-tone-difference matrix (NGTDM) and run-length matrix (RLM). Receiver-operating-characteristic curve analysis was performed on the selected textural feature set to assess the role of TA features (a) as marker(s) of tumor aggressiveness leading to mortality at baseline and (b) in predicting the NACT response among survivors in the course of treatment. Findings showed that the NGTDM features coarseness, busyness and strength quantifying tumor heterogeneity in D, D* and f maps and T1W and T2W images were useful markers of tumor aggressiveness in identifying the nonsurvivor group (area-under-the-curve [AUC] = 0.82-0.88) at baseline. The GLCM features contrast and correlation, NGTDM features contrast and complexity and RLM feature short-run-low-gray-level-emphasis quantifying homogeneity/terogeneity in tumor were effective markers for predicting chemotherapeutic response using D (AUC = 0.80), D* (AUC = 0.80) and T2W (AUC = 0.70) at t0, and D* (AUC = 0.80) and f (AUC = 0.70) at t1. 3D statistical TA features might be useful as imaging-based markers for characterizing tumor aggressiveness and predicting chemotherapeutic response in patients with osteosarcoma.
本研究旨在评估基于 MRI 的统计纹理分析（TA）在预测骨肉瘤患者化疗反应中的疗效。本前瞻性研究纳入了 40 名经活检证实的骨肉瘤患者（男：女=31：9；年龄=17.2±5.7 岁）。患者接受了三个周期的新辅助化疗（NACT），并在三个时间点进行扩散加权 MRI 采集：基线（t0）、第一次 NACT 后（t1）和第三次 NACT 后（t2），使用 1.5T 扫描仪。8 名患者（死亡组）在 NACT 期间死亡，34 名患者（存活组）完成了 NACT 方案，随后进行了手术。对切除的肿瘤进行组织病理学评估，以评估 NACT 反应（应答者[≤50%存活肿瘤]和非应答者[>50%存活肿瘤]），结果显示非应答者：应答者=20：12。评估了表观扩散系数（ADC）和体素内不相干运动（IVIM）参数、扩散系数（D）、灌注系数（D*）和灌注分数（f）。使用 3D TA 方法灰度共生矩阵（GLCM）、邻域灰度差矩阵（NGTDM）和游程长度矩阵（RLM），在整个肿瘤体积的 ADC、D、D和 f 参数图以及结构 T1 加权（T1W）和 T2 加权（T2W）图像上评估了总共 25 个纹理特征。对选定的纹理特征集进行受试者工作特征曲线分析，以评估 TA 特征（a）作为导致基线时死亡的肿瘤侵袭性标志物的作用，以及（b）在治疗过程中预测幸存者 NACT 反应的作用。结果表明，D、D、f 图和 T1W、T2W 图像中 NGTDM 特征粗糙度、繁忙度和强度定量评估肿瘤异质性，是基线时识别非存活组的有用标志物（曲线下面积[AUC]=0.82-0.88）。GLCM 特征对比度和相关性、NGTDM 特征对比度和复杂性以及 RLM 特征短运行低灰度强调定量评估肿瘤的均匀性/异质性，是使用 D（AUC=0.80）、D*（AUC=0.80）和 T2W（AUC=0.70）在 t0 时预测化疗反应以及 D*（AUC=0.80）和 f（AUC=0.70）在 t1 时预测化疗反应的有效标志物。3D 统计 TA 特征可能是一种有用的影像学标志物，可用于表征骨肉瘤患者的肿瘤侵袭性和预测化疗反应。
