Fatima Kashuf, Dasgupta Archya, DiCenzo Daniel, Kolios Christopher, Quiaoit Karina, Saifuddin Murtuza, Sandhu Michael, Bhardwaj Divya, Karam Irene, Poon Ian, Husain Zain, Sannachi Lakshmanan, Czarnota Gregory J
Physical Sciences, Sunnybrook Research Institute, Toronto, Canada.
Department of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, Canada.
Clin Transl Radiat Oncol. 2021 Mar 12;28:62-70. doi: 10.1016/j.ctro.2021.03.002. eCollection 2021 May.
This study investigated the use of quantitative ultrasound (QUS) obtained during radical radiotherapy (RT) as a radiomics biomarker for predicting recurrence in patients with node-positive head-neck squamous cell carcinoma (HNSCC).
Fifty-one patients with HNSCC were treated with RT (70 Gy/33 fractions) (±concurrent chemotherapy) were included. QUS Data acquisition involved scanning an index neck node with a clinical ultrasound device. Radiofrequency data were collected before starting RT, and after weeks 1, and 4. From this data, 31 spectral and related-texture features were determined for each time and delta (difference) features were computed. Patients were categorized into two groups based on clinical outcomes (recurrence or non-recurrence). Three machine learning classifiers were used for the development of a radiomics model. Features were selected using a forward sequential selection method and validated using leave-one-out cross-validation.
The median follow up for the entire group was 38 months (range 7-64 months). The disease sites involved neck masses in patients with oropharynx (39), larynx (5), carcinoma unknown primary (5), and hypopharynx carcinoma (2). Concurrent chemotherapy and cetuximab were used in 41 and 1 patient(s), respectively. Recurrence was seen in 17 patients. At week 1 of RT, the support vector machine classifier resulted in the best performance, with accuracy and area under the curve (AUC) of 80% and 0.75, respectively. The accuracy and AUC improved to 82% and 0.81, respectively, at week 4 of treatment.
QUS Delta-radiomics can predict higher risk of recurrence with reasonable accuracy in HNSCC.Clinical trial registration: clinicaltrials.gov.in identifier NCT03908684.
本研究探讨在根治性放射治疗（RT）期间获得的定量超声（QUS）作为一种放射组学生物标志物，用于预测颈部淋巴结阳性的头颈部鳞状细胞癌（HNSCC）患者复发的情况。
纳入51例接受RT（70 Gy/33次分割）（±同步化疗）治疗的HNSCC患者。QUS数据采集包括使用临床超声设备扫描颈部索引淋巴结。在开始RT前、第1周和第4周后收集射频数据。从这些数据中，每次确定31个频谱和相关纹理特征，并计算差值（差异）特征。根据临床结局（复发或未复发）将患者分为两组。使用三种机器学习分类器开发放射组学模型。采用向前序贯选择方法选择特征，并使用留一法交叉验证进行验证。
整个组的中位随访时间为38个月（范围7 - 64个月）。疾病部位包括口咽癌患者的颈部肿块（39例）、喉癌（5例）、原发灶不明癌（5例）和下咽癌（2例）。分别有41例和1例患者使用了同步化疗和西妥昔单抗。17例患者出现复发。在RT第1周时，支持向量机分类器表现最佳，准确率和曲线下面积（AUC）分别为80%和0.75。在治疗第4周时，准确率和AUC分别提高到82%和0.81。
QUS放射组学差值能够以合理的准确率预测HNSCC患者较高的复发风险。临床试验注册：clinicaltrials.gov.in标识符NCT03908684。
