From the Division of Nuclear Medicine, Department of Radiology.
Department of Radiation Oncology, University of Washington School of Medicine, Seattle, WA.
Clin Nucl Med. 2021 Nov 1;46(11):861-871. doi: 10.1097/RLU.0000000000003774.
We evaluated the reliability of 18F-FDG PET imaging biomarkers to classify early response status across observers, scanners, and reconstruction algorithms in support of biologically adaptive radiation therapy for locally advanced non-small cell lung cancer.
Thirty-one patients with unresectable locally advanced non-small cell lung cancer were prospectively enrolled on a phase 2 trial (NCT02773238) and underwent 18F-FDG PET on GE Discovery STE (DSTE) or GE Discovery MI (DMI) PET/CT systems at baseline and during the third week external beam radiation therapy regimens. All PET scans were reconstructed using OSEM; GE-DMI scans were also reconstructed with BSREM-TOF (block sequential regularized expectation maximization reconstruction algorithm incorporating time of flight). Primary tumors were contoured by 3 observers using semiautomatic gradient-based segmentation. SUVmax, SUVmean, SUVpeak, MTV (metabolic tumor volume), and total lesion glycolysis were correlated with midtherapy multidisciplinary clinical response assessment. Dice similarity of contours and response classification areas under the curve were evaluated across observers, scanners, and reconstruction algorithms. LASSO logistic regression models were trained on DSTE PET patient data and independently tested on DMI PET patient data.
Interobserver variability of PET contours was low for both OSEM and BSREM-TOF reconstructions; intraobserver variability between reconstructions was slightly higher. ΔSUVpeak was the most robust response predictor across observers and image reconstructions. LASSO models consistently selected ΔSUVpeak and ΔMTV as response predictors. Response classification models achieved high cross-validated performance on the DSTE cohort and more variable testing performance on the DMI cohort.
The variability FDG PET lesion contours and imaging biomarkers was relatively low across observers, scanners, and reconstructions. Objective midtreatment PET response assessment may lead to improved precision of biologically adaptive radiation therapy.
我们评估了 18F-FDG PET 成像生物标志物在跨观察者、扫描仪和重建算法分类早期反应状态的可靠性,以支持局部晚期非小细胞肺癌的生物适应性放射治疗。
31 名无法切除的局部晚期非小细胞肺癌患者前瞻性地参加了一项 2 期试验(NCT02773238),并在基线和外照射放射治疗期间在 GE Discovery STE(DSTE)或 GE Discovery MI(DMI)PET/CT 系统上进行 18F-FDG PET。所有 PET 扫描均使用 OSEM 重建;GE-DMI 扫描也使用 BSREM-TOF(包含飞行时间的块顺序正则化期望最大化重建算法)重建。3 名观察者使用半自动基于梯度的分割对原发性肿瘤进行轮廓勾画。SUVmax、SUVmean、SUVpeak、MTV(代谢肿瘤体积)和总病变糖酵解与治疗中期多学科临床反应评估相关。评估了不同观察者、扫描仪和重建算法的轮廓和响应分类曲线下面积的 Dice 相似性。在 DSTE PET 患者数据上训练 LASSO 逻辑回归模型,并在 DMI PET 患者数据上进行独立测试。
OSEM 和 BSREM-TOF 重建的 PET 轮廓的观察者间变异性均较低;重建之间的观察者内变异性稍高。ΔSUVpeak 是所有观察者和图像重建中最稳健的反应预测因子。LASSO 模型一致选择 ΔSUVpeak 和 ΔMTV 作为反应预测因子。响应分类模型在 DSTE 队列中具有较高的交叉验证性能,在 DMI 队列中具有更可变的测试性能。
在观察者、扫描仪和重建中,FDG PET 病变轮廓和成像生物标志物的变异性相对较低。客观的治疗中期 PET 反应评估可能会提高生物适应性放射治疗的精度。