The prognostic value of location and size change of pathological lymph nodes evaluated on CT-scan following radiotherapy in head and neck cancer

Role of primary tumor volume and metastatic lymph node volume in response to curative effect of definitive radiotherapy for locally advanced head and neck cancer

BACKGROUND

Studies have shown mixed results concerning the role of primary tumor volume (TV) and metastatic lymph node (NV) volume in response to the curative effect of definitive radiotherapy for locally advanced head and neck squamous cell carcinoma (LAHNSCC).

OBJECTIVE

We aimed to evaluate the impact of TV and NV on the efficacy of radical radiotherapy in LAHNSCC patients, with the goal of guiding individualized therapy.

PATIENTS AND METHODS

Patients with LAHNSCC who received radical radiation therapy and were reexamined within 6 months post-therapy from January 2012 to December 2021 were selected. The volumes of the primary tumors and metastatic lymph nodes were calculated by software and then were divided into a large TV group vs small TV group and a large NV group vs small NV group according to the relationship with the median. Additionally, patients who received concurrent chemoradiotherapy (CCRT) or not were divided into the CCRT group and the radiotherapy (RT) group. Patients with lymph node metastasis were divided into node concurrent chemotherapy (N-CCRT) group and a node metastatic chemotherapy (N-RT) group according to whether they received concurrent chemotherapy or not. The volume shrinkage rate (VSR), objective response rate (ORR), local control rate (LCR) and overall survival (OS) were recorded and analyzed.

RESULTS

96 patients were included in the primary tumor volume group, and 73 patients were included in the metastatic lymph node group. Receiver operating characteristic (ROC) curves were constructed for objective remission (OR) endpoints, and a volume threshold was defined for TV and NV patients. The threshold primary tumor volume was 32.45 cm3, and the threshold metastatic lymph node volume was 6.05 cm3.The primary TV shrinkage rates of the small TV and the large TV groups were basically the same, P = 0.801. Similarly, the ORR and LCR were not significantly different between the small TV group and the large TV group (PORR = 0.118, PLCR = 0.315). Additionally, the TV shrinkage rate did not significantly differ between the CCRT group and the RT group, P = 0.133. Additionally, there was no significant difference in ORR or LCR in CCRT group (PORR = 0.057, PLCR = 0.088). However, the metastatic lymph node volume shrinkage rate in the small NV group was significantly greater than that in the large NV group (P = 0.001). The ORR and LCR of the small NV subgroup were significantly greater than those of the large NV subgroup (PORR = 0.002, PLCR = 0.037). Moreover, compared with that of the N-RT group, the NV shrinkage rate of the N-CCRT group was 84.10 ± s3.11%, and the shrinkage rate was 70.76 ± s5.77% (P = 0.047). For the ORR and LCR, the N-CCRT group and N-RT group were significantly different (PORR = 0.030, PLCR = 0.037). The median OS of the whole group was 26 months. However, neither TV/NV nor concurrent chemotherapy seemed to influence OS.

CONCLUSION

Primary tumor volume is not a prognostic factor for the response to curative effect radiotherapy in LAHNSCC patients. Nevertheless, metastatic lymph nodes are a prognostic factor for the response to curative effect radiotherapy in LAHNSCC patients. Patients with smaller lymph nodes have better local control.

Exploratory ensemble interpretable model for predicting local failure in head and neck cancer: the additive benefit of CT and intra-treatment cone-beam computed tomography features

BACKGROUND

Local failure (LF) following chemoradiation (CRT) for head and neck cancer is associated with poor overall survival. If machine learning techniques could stratify patients at risk of treatment failure based on baseline and intra-treatment imaging, such a model could facilitate response-adapted approaches to escalate, de-escalate, or switch therapy.

METHODS

A 1:2 retrospective case control cohort of patients treated at a single institution with definitive radiotherapy for head and neck cancer who failed locally, in-field at a primary or nodal structure were included. Radiomic features were extracted from baseline CT and CBCT scans at fractions 1 and 21 (delta) of radiotherapy with PyRadiomics and were selected for by: reproducibility (intra-class correlation coefficients ≥0.95), redundancy [maximum relevance and minimum redundancy (mRMR)], and informativeness [recursive feature elimination (RFE)]. Separate models predicting LF of primaries or nodes were created using the explainable boosting machine (EBM) classifier with 5-fold cross-validation for (I) clinical only, (II) radiomic only (CT1 and delta features), and (III) fused models (clinical + radiomic). Twenty-five iterations were performed, and predicted scores were averaged with a parallel ensemble design. Receiver operating characteristic curves were compared between models with paired-samples t-tests.

RESULTS

The fused ensemble model for primaries (using clinical, CT1, and delta features) achieved an AUC of 0.871 with a sensitivity of 78.3% and specificity of 90.9% at the maximum Youden J statistic. The fused ensemble model trended towards improvement when compared to the clinical only ensemble model (AUC =0.788, P=0.134) but reached significance when compared to the radiomic ensemble model (AUC =0.770, P=0.017). The fused ensemble model for nodes achieved an AUC of 0.910 with a sensitivity of 100.0% and specificity of 68.0%, which also trended towards improvement when compared to the clinical model (AUC =0.865, P=0.080).

CONCLUSIONS

The fused ensemble EBM model achieved high discriminatory ability at predicting LF for head and neck cancer in independent primary and nodal structures. Although an additive benefit of delta radiomics over clinical factors could not be proven, the results trended towards improvement with the fused ensemble model, which are promising and worthy of prospective investigation in a larger cohort.

Supraclavicular lymph node recurrence after radical surgery: is epidermal growth factor receptor a predictive marker?

The aim of this study was to evaluate the rare postoperative supraclavicular metastasis originating from oral squamous cell carcinoma (OSCC) and to discuss epidermal growth factor receptor (EGFR) as a potential predictive marker. Tumour specimens of OSCC patients divided into three groups were included: supraclavicular metastasis (n = 8), conventional cervical metastasis (n = 28), no metastasis (n = 48). Basic information and EGFR expression were compared among these groups and the data were analysed to identify potentially related risk factors for supraclavicular metastasis. In the supraclavicular metastasis group (n = 8), all primary tumours were T1-T2 and located in the tongue and buccal region; five of eight cases were pathologically N0. The median interval from the primary tumour resection to the development of supraclavicular metastases was 21.5 months. All related deaths (5/8) occurred within 2 years. In the supraclavicular metastasis group, EGFR expression was highest in the supraclavicular metastases, followed by cervical lymph nodes, and was lowest in the primary tumours (P = 0.39). In contrast, in the conventional metastasis group and the N0 group, EGFR expression was higher in the primary tumours than in the lymph nodes (P < 0.01). Supraclavicular metastasis of OSCC is infrequent and associated with a poor prognosis. EGFR might predict the occurrence of supraclavicular metastasis.