■本研究调查了在根治性放疗(RT)期间获得的定量超声(QUS)作为影像组学生物标志物在预测淋巴结阳性头颈部鳞状细胞癌(HNSCC)患者复发中的应用。
■51例HNSCC患者接受RT(70Gy/33分)(±同步化疗)治疗。QUS数据采集涉及使用临床超声设备扫描索引颈淋巴结。在开始RT之前收集射频数据,在第1周和第4周之后。从这些数据来看,每次确定31个光谱和相关纹理特征,并计算δ(差异)特征。根据临床结果(复发或非复发)将患者分为两组。三个机器学习分类器用于开发放射组学模型。使用正向顺序选择方法选择特征,并使用留一交叉验证进行验证。
■全组的中位随访时间为38个月(范围7-64个月)。疾病部位涉及口咽患者的颈部肿块(39),喉(5),原发癌未知(5),和下咽癌(2)。同时化疗和西妥昔单抗用于41例和1例患者,分别。17例患者复发。在RT的第1周,支持向量机分类器产生最佳性能,准确度和曲线下面积(AUC)分别为80%和0.75。准确度和AUC分别提高到82%和0.81,在治疗的第4周。
■QUSDelta-放射组学可以在HNSCC中以合理的准确性预测更高的复发风险。临床试验注册:clinicaltrials.gov.在标识符NCT03908684中。
OBJECTIVE: 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).
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: QUS Delta-radiomics can predict higher risk of recurrence with reasonable accuracy in HNSCC.Clinical trial registration: clinicaltrials.gov.in identifier NCT03908684.