18F-FDG-PET/CT-based treatment planning for definitive (chemo)radiotherapy in patients with head and neck squamous cell carcinoma improves regional control and survival

Bosch, Sven van den; Doornaert, P.; Dijkema, Tim; Zwijnenburg, Ellen M.; Verhoef, Lia C.G.; Hoeben, Bianca A.W.; Kasperts, N.; Smid, Ernst J.; Terhaard, Chris H.J.; Kaanders, Johannes H.A.M.

doi:10.1016/j.radonc.2019.07.025

Cited by 27 publications

(25 citation statements)

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“…However, local recurrences still occur in some cases when radiotherapy has not been given because of negative PET after chemotherapy. This is particularly confirmed in a number of studies for early stages [204][205][206][207][208]. The data on FDG-PET-guided radiotherapy in HL is now secure for intermediate and advanced stages.…”

Section: The Utility Of Pet For Therapy Stratification In the Combined Modality Settingmentioning

confidence: 63%

Value of PET imaging for radiation therapy

et al. 2021

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This comprehensive review written by experts in their field gives an overview on the current status of incorporating positron emission tomography (PET) into radiation treatment planning. Moreover, it highlights ongoing studies for treatment individualisation and per-treatment tumour response monitoring for various primary tumours. Novel tracers and image analysis methods are discussed. The authors believe this contribution to be of crucial value for experts in the field as well as for policy makers deciding on the reimbursement of this powerful imaging modality.

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Section: The Utility Of Pet For Therapy Stratification In the Combined Modality Settingmentioning

confidence: 63%

Value of PET imaging for radiation therapy

et al. 2021

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“…Many cancer types spread though the lymphatic system and metastasize in regional lymph nodes 3 – 8 . Sufficiently large metastases can be identified using computed tomography (CT), magnetic resonance imaging (MRI), or positron emission tomography (PET) 9 – 11 . However, current in-vivo imaging techniques are not able to detect microscopic metastases, which would require pathological examination of the tissue 12 , 13 .…”

Section: Introductionmentioning

confidence: 99%

A hidden Markov model for lymphatic tumor progression in the head and neck

Ludwig

Pouymayou

Balermpas

et al. 2021

Sci Rep

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Currently, elective clinical target volume (CTV-N) definition for head and neck squamous cell carcinoma (HNSCC) is mostly based on the prevalence of nodal involvement for a given tumor location. In this work, we propose a probabilistic model for lymphatic metastatic spread that can quantify the risk of microscopic involvement in lymph node levels (LNL) given the location of macroscopic metastases and T-category. This may allow for further personalized CTV-N definition based on an individual patient’s state of disease. We model the patient's state of metastatic lymphatic progression as a collection of hidden binary random variables that indicate the involvement of LNLs. In addition, each LNL is associated with observed binary random variables that indicate whether macroscopic metastases are detected. A hidden Markov model (HMM) is used to compute the probabilities of transitions between states over time. The underlying graph of the HMM represents the anatomy of the lymphatic drainage system. Learning of the transition probabilities is done via Markov chain Monte Carlo sampling and is based on a dataset of HNSCC patients in whom involvement of individual LNLs was reported. The model is demonstrated for ipsilateral metastatic spread in oropharyngeal HNSCC patients. We demonstrate the model's capability to quantify the risk of microscopic involvement in levels III and IV, depending on whether macroscopic metastases are observed in the upstream levels II and III, and depending on T-category. In conclusion, the statistical model of lymphatic progression may inform future, more personalized, guidelines on which LNL to include in the elective CTV. However, larger multi-institutional datasets for model parameter learning are required for that.

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“…Multimodal FDG-PET/CT and PET/MRI data have been shown by various studies to improve RT planning in different aspects, such as better patient selection and precision in target delineation [58,193,[209][210][211][212][213][214][215]. Inclusion of PET/CT or PET/MRI data into radiation dose planning requires dedicated acquisition protocols [216][217][218][219][220] to ensure reproducible manual or automatic contouring of tumour regions [210,[221][222][223].…”

Section: Pet/ct Pet/mri and Radiomics In Radiotherapy Planningmentioning

confidence: 99%

“…Imaging biomarkers measured with hypoxia tracers such as [ 18 F]FMISO and [ 18 F]FAZA but also with routine [ 18 F]FDG have been shown to be prognostic for outcome after radiotherapy [43,46,48,209,[252][253][254][255][256]. Consequently, radiation treatment adaptation by means of PET-guided dose escalation or de-escalation to account for individual radiation sensitivities in tumour sub-regions, so-called dose painting, seems attractive and might enable for increased tumour control rates and/or reduced toxicity [51,252,257].…”

Section: Pet-based Dose Paintingmentioning

confidence: 99%