Influence of lymph nodal status on primary tumor control probability in head and neck cancer

1984 ◽  
Vol 10 ◽  
pp. 199
Author(s):  
T.J. Wall ◽  
L.J. Peters
Keyword(s):  
Head And Neck Cancer ◽  
Head And Neck ◽  
Neck Cancer ◽  
Primary Tumor ◽  
Nodal Status ◽  
Tumor Control ◽  
Tumor Control Probability

scholarly journals Automated Non-Coplanar VMAT for Dose Escalation in Recurrent Head and Neck Cancer Patients

Cancers ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1910
Author(s):  
Kaley Woods ◽  
Robert K. Chin ◽  
Kiri A. Cook ◽  
Ke Sheng ◽  
Amar U. Kishan ◽  
...  
Keyword(s):  
Head And Neck Cancer ◽  
Head And Neck ◽  
Neck Cancer ◽  
Dose Escalation ◽  
Volumetric Modulated Arc Therapy ◽  
Normal Tissue Complication Probability ◽  
Tumor Control ◽  
Tumor Control Probability ◽  
Increased Risk ◽  
Recurrent Head

This study evaluates the potential for tumor dose escalation in recurrent head and neck cancer (rHNC) patients with automated non-coplanar volumetric modulated arc therapy (VMAT) stereotactic body radiation therapy (SBRT) planning (HyperArc). Twenty rHNC patients are planned with conventional VMAT SBRT to 40 Gy while minimizing organ-at-risk (OAR) doses. They are then re-planned with the HyperArc technique to match these minimal OAR doses while escalating the target dose as high as possible. Then, we compare the dosimetry, tumor control probability (TCP), and normal tissue complication probability (NTCP) for the two plan types. Our results show that the HyperArc technique significantly increases the mean planning target volume (PTV) and gross tumor volume (GTV) doses by 10.8 ± 4.4 Gy (25%) and 11.5 ± 5.1 Gy (26%) on average, respectively. There are no clinically significant differences in OAR doses, with maximum dose differences of <2 Gy on average. The average TCP is 23% (± 21%) higher for HyperArc than conventional plans, with no significant differences in NTCP for the brainstem, cord, mandible, or larynx. HyperArc can achieve significant tumor dose escalation while maintaining minimal OAR doses in the head and neck—potentially enabling improved local control for rHNC SBRT patients without increased risk of treatment-related toxicities.

scholarly journals Prospective Evaluation of a Tumor Control Probability Model Based on Dynamic 18F-FMISO PET for Head and Neck Cancer Radiotherapy

2019 ◽  
Vol 60 (12) ◽  
pp. 1698-1704 ◽  
Author(s):  
Daniela Thorwarth ◽  
Stefan Welz ◽  
David Mönnich ◽  
Christina Pfannenberg ◽  
Konstantin Nikolaou ◽  
...  
Keyword(s):  
Head And Neck Cancer ◽  
Head And Neck ◽  
Neck Cancer ◽  
Probability Model ◽  
Tumor Control ◽  
Tumor Control Probability ◽  
Prospective Evaluation ◽  
Cancer Radiotherapy ◽  
Model Based

scholarly journals Combined CT radiomics of primary tumor and metastatic lymph nodes improves prediction of loco-regional control in head and neck cancer

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Marta Bogowicz ◽  
Stephanie Tanadini-Lang ◽  
Matthias Guckenberger ◽  
Oliver Riesterer
Keyword(s):  
Head And Neck Cancer ◽  
Lymph Nodes ◽  
Head And Neck ◽  
Neck Cancer ◽  
Primary Tumor ◽  
Mixed Model ◽  
Cox Model ◽  
Tumor Control ◽  
Regional Control ◽  
Selection Operator

Abstract Loco-regional control (LRC) is a major clinical endpoint after definitive radiochemotherapy (RCT) of head and neck cancer (HNC). Radiomics has been shown a promising biomarker in cancer research, however closer related to primary tumor control than composite endpoints. Radiomics studies often focus on the analysis of primary tumor (PT). We hypothesize that the combination of PT and lymph nodes (LN) radiomics better predicts LRC in HNC treated with RCT. Radiomics analysis was performed in CT images of 128 patients using Z-Rad implementation (training n = 77, validation n = 51). 285 features were extracted from PT and involved LN. Features were preselected with the maximum relevance minimum redundancy method and the multivariate Cox model was trained using least absolute shrinkage and selection operator. The mixed model was based on the combination of PT and LN radiomics, whereas the PT model included only the PT features. The mixed model showed significantly higher performance than the PT model (p < 0.01), c-index of 0.67 and 0.63, respectively; and better risk group stratification. The clinical nodal status was not a significant predictor in the combination with PT radiomics. This study shows that the LRC can be better predicted by expansion of radiomics analysis with LN features.

scholarly journals Adaptive radiotherapy for head and neck cancer

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Enis Tinjak ◽  
Velda Smajlbegović ◽  
Adnan Beganović ◽  
Mirjana Ristanić ◽  
Halil Ćorović ◽  
...  
Keyword(s):  
Radiation Therapy ◽  
Head And Neck Cancer ◽  
Head And Neck ◽  
Neck Cancer ◽  
Locally Advanced ◽  
Adaptive Radiotherapy ◽  
Tumor Control ◽  
Parotid Glands ◽  
Image Guided Radiotherapy ◽  
The Impact

Introduction: Radiation therapy has long played an integral role in the manage¬ment of locally advanced head and neck cancer (HNC), both for organ preservation and to improve tumor control in the postoperative setting. The aim of this research is to investigate the effects of adaptive radiotherapy on dosimetric, clinical, and toxicity outcomes for patients with head and neck cancer undergoing radiation therapy treatment. Many sources have reported volume reductions in the primary target, nodal volumes, and parotid glands over treatment, which may result in unintended dosimetric changes affecting the side effect profile and even efficacy of the treatment. Adaptive radiotherapy (ART) is an interesting treatment paradigm that has been developed to directly adjust to these changes.Material and methods: This research contains the results of 15 studies, including clinical trials, randomized prospective and retrospective studies. The researches analyze the impact of radiation therapy on changes in tumor volume and the relationship with planned radiation dose delivery, as well as the possibility of using adaptive radiotherapy in response to identified changes. Also, medical articles and abstracts that are closely related to the title of adaptive radiotherapy were researched.Results: The application of ART significantly improved the quality of life of patients with head and neck cancer, as well as two-year locoregional control of the disease. The average time to apply ART is the middle of the treatment course approximately 17 to 20 fractions of the treatment.Conclusion: Based on systematic review of the literature, evidence based changes in target volumes and dose reduction at OAR, adaptive radiotherapy is recommended treatment for most of the patients with head and neck cancer with the support of image-guided radiotherapy.

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