Characteristics and kinetics of cervical lymph node regression after radiation therapy for human papillomavirus-associated oropharyngeal carcinoma: Quantitative image analysis of post-radiotherapy response

Tang, Chad; Fuller, Clifton D.; Garden, Adam S.; Awan, Musaddiq J.; Colen, Rivka R.; Morrison, William H.; Frank, Steven J.; Beadle, Beth M.; Phan, Jack; Zafereo, Mark; Weber, Randal S.; Rosenthal, David I.; Gunn, G. Brandon

doi:10.1016/j.oraloncology.2014.11.001

Cited by 14 publications

(8 citation statements)

References 25 publications

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“…(1,2) Using daily or weekly 3D image guidance, HPV-positive oropharyngeal tumors often demonstrate a complete radiologic response shortly after completing definitive radiation therapy. (3) However, the pre-treatment identification of radiosensitive tumors and host factors associated with radiosensitivity remains a fragmented story for other tumor types.…”

Section: Introductionmentioning

confidence: 99%

Tumour radiosensitivity is associated with immune activation in solid tumours

Ström

Harrison

Giuliano

et al. 2017

European Journal of Cancer

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Purpose Our goal was to determine whether tumor radiosensitivity is associated with activation of the immune system across all tumor types as measured by two gene expression signatures (GES). Methods We identified 10,240 genomically profiled distinct solid primary tumors with gene expression analysis available from an institutional de-identified database. Two separate GES were included in the analysis, the radiosensitivity index (RSI) GES (a 10-gene GES as a measure of radiosensitivity), and the 12-chemokine (12-CK) signature (a 12-gene GES as a measure of immune activation). We tested whether the RSI and 12-CK were associated with each other across all tumor samples, and in an exploratory analysis, their prognostic significance in predicting distant metastasis-free survival (DMFS) among a well-characterized, independent cohort of 282 early-stage breast cancer cases treated with surgery and post-operative radiation alone without systemic therapy. The lower the RSI score, the higher the tumor radiosensitivity; whereas, the higher the 12-CK score the higher the immune activation. Results Using an RSI cut-point of ≤0.3745, RSI-low tumors (n=4,291, 41.9%) had a significantly higher median 12-CK GES value (0.54 [range −0.136,1.095]) compared with RSI-high tumors (−0.17 [−0.82,0.42]; p<0.001) across all tumor samples, indicating that radiosensitivity is associated with immune activation. In an exploratory analysis of early stage breast cancer cases, a multivariable model with patient age, RSI and 12-CK provided a strong composite model for DMFS (p=0.02), with RSI (HR 0.63 [95%CI 0.36,1.09]) and 12-CK (HR 0.66 [0.41,1.04]) each providing comparable contributions. Conclusions Tumor radiosensitivity is associated with immune activation as measured by two GES.

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Section: Introductionmentioning

confidence: 99%

Tumour radiosensitivity is associated with immune activation in solid tumours

Ström

Harrison

Giuliano

et al. 2017

European Journal of Cancer

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“…The seemingly weaker informativeness of delta texture features may be due to the (I) inherent artifacts of CBCT scans and metal artifacts from dental implants that could interfere with accurate quantification of texture features and (II) the inherent heterogeneity of both primary and nodal structures in this dataset making broad changes in texture features over time difficult to interpret. Prior retrospective CT studies evaluating the evolution of morphology of nodes following CRT have shown that baseline hypodensity/fat sub-volume component, volume/size, and HU standard deviation were associated with response/regression following therapy (45).…”

Section: Discussionmentioning

confidence: 99%

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

Morgan¹,

Wang²,

Dohopolski³

et al. 2021

Quant Imaging Med Surg

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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.

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“…HPV-OPC status is of importance since it has unique histopathological characteristics, distinct epidemiology and improved response to CRT. Differing patterns of lymph node response have been noted in the HPV-OPC population, with a greater initial involution but then a more prolonged and inconsistent reduction in size, particularly in the presence of low-density lymph nodes on CT [24][25][26].…”

Section: Discussionmentioning

confidence: 99%

MRI in head and neck cancer following chemoradiotherapy: what is the optimal delay to demonstrate maximal response?

2021

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Objectives To investigate the optimal timing for post-chemoradiotherapy (CRT) reference magnetic resonance imaging (MRI) in head and neck cancer, so as to demonstrate a maximal treatment response. To assess whether this differs in human papillomavirus–related oropharyngeal cancer (HPV-OPC) and whether the MRI timing impacts on the ability to predict treatment success. Methods Following ethical approval and informed consent, 45 patients (40 male, mean age 59.7 ± 7.9 years, 33 HPV-OPC) with stage 3 and 4 HNSCC underwent pre-treatment, 6- and 12-week post-CRT MRIs in this prospective cohort study. Primary tumour (n = 39) size, T2w morphology and diffusion weight imaging (DWI) scores, together with nodal (n = 42) size and necrotic/cystic change, were recorded. Interval imaging changes were analysed for all patients and according to HPV-OPC status. MRI descriptors and their interval changes were also compared with 2-year progression-free survival (PFS). Results All MRI descriptors significantly changed between pre-treatment and 6-week post-treatment MRI studies (p < .001). Primary tumour and nodal volume decreased between 6- and 12-week studies; however, interval changes in linear dimensions were only evident for HPV-OPC lymph nodes. Nodal necrosis scores also evolved after 6 weeks but other descriptors were stable. The 6-week nodal necrosis score and the 6- and 12-week nodal volume were predictive of 2-year PFS. Conclusion Apart from HPV-OPC patients with nodal disease, the 6-week post-CRT MRI demonstrates maximal reduction in the linear dimensions of head and neck cancer; however, a later reference study should be considered if volumetric analysis is applied. Key Points • This study provides guidance on when early post-treatment imaging should be performed in head and neck cancer following chemoradiotherapy, in order to aid subsequent detection of recurrent tumour. • Lymph nodes in HPV-related oropharyngeal cancer patients clearly reduced in size from 6 to 12 weeks post-treatment. However, other lymph node disease and all primary tumours showed only a minor reduction in size beyond 6 weeks, and this required a detailed volumetric analysis for demonstration. • Timing of the reference MRI following chemoradiotherapy for head and neck cancer depends on whether the patient has HPV-related oropharyngeal cancer and whether there is nodal disease. MRI as early as 6 weeks post-treatment may be performed unless volumetric analysis is routinely performed.

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Characteristics and kinetics of cervical lymph node regression after radiation therapy for human papillomavirus-associated oropharyngeal carcinoma: Quantitative image analysis of post-radiotherapy response

Cited by 14 publications

References 25 publications

Tumour radiosensitivity is associated with immune activation in solid tumours

Tumour radiosensitivity is associated with immune activation in solid tumours

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

MRI in head and neck cancer following chemoradiotherapy: what is the optimal delay to demonstrate maximal response?

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