Dataset Information

FMISO-Based Adaptive Radiotherapy in Head and Neck Cancer.

ABSTRACT: Concurrent chemoradiotherapy represents one of the most used strategies in the curative treatment of patients with head and neck (HNC) cancer. Locoregional failure is the predominant recurrence pattern. Tumor hypoxia belongs to the main cause of treatment failure. Positron emission tomography (PET) using hypoxia radiotracers has been studied extensively and has proven its feasibility and reproducibility to detect tumor hypoxia. A number of studies confirmed that the uptake of FMISO in the recurrent region is significantly higher than that in the non-recurrent region. The escalation of dose to hypoxic tumors may improve outcomes. The technical feasibility of optimizing radiotherapeutic plans has been well documented. To define the hypoxic tumour volume, there are two main approaches: dose painting by contour (DPBC) or by number (DPBN) based on PET images. Despite amazing technological advances, precision in target coverage, and surrounding tissue sparring, radiation oncology is still not considered a targeted treatment if the "one dose fits all" approach is used. Using FMISO and other hypoxia tracers may be an important step for individualizing radiation treatment and together with future radiomic principles and a possible genome-based adjusting dose, will move radiation oncology into the precise and personalized era.

SUBMITTER: Dolezel M

PROVIDER: S-EPMC9410424 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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FMISO-Based Adaptive Radiotherapy in Head and Neck Cancer.

Dolezel Martin M Slavik Marek M Blazek Tomas T Kazda Tomas T Koranda Pavel P Veverkova Lucia L Burkon Petr P Cvek Jakub J

Journal of personalized medicine 20220729 8

Concurrent chemoradiotherapy represents one of the most used strategies in the curative treatment of patients with head and neck (HNC) cancer. Locoregional failure is the predominant recurrence pattern. Tumor hypoxia belongs to the main cause of treatment failure. Positron emission tomography (PET) using hypoxia radiotracers has been studied extensively and has proven its feasibility and reproducibility to detect tumor hypoxia. A number of studies confirmed that the uptake of FMISO in the recurr ...[more]

PMID: 36013194

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Project description:No clear criteria have yet been established to guide decision-making for patient selection and the optimal timing of adaptive radiotherapy (ART) based on image-guided radiotherapy (IGRT). We have developed a novel protocol—the Best for Adaptive Radiotherapy (B-ART) protocol—to guide patient selection for ART. The aim of the present study is to describe this protocol, to evaluate its validity in patients with head and neck (HN) cancer, and to identify the anatomical and clinical predictors of the need for replanning. We retrospectively evaluated 82 patients with HN cancer who underwent helical tomotherapy (HT) and subsequently required replanning due to soft tissue changes upon daily MVCT. Under the proposed criteria, patients with anatomical changes >3 mm on three to four consecutive scans are candidates for ART. We compared the volumes on the initial CT scan (iCT) and the replanning CT (rCT) scan for the clinical target volumes (CTV1, referring to primary tumor or tumor bed and CTV2, metastatic lymph nodes) and for the parotid glands (PG) and body contour (B-body). The patients were stratified by primary tumor localization, clinical stage, and treatment scheme. The main reasons for replanning were: (1) a planning target volume (PTV) outside the body contour (n = 70; 85.4%), (2) PG shrinkage (n = 69; 84.1%), (3) B-body deviations (n = 69; 84.1%), and (4) setup deviations (n = 40; 48.8%). The replanning decision was made, on average, during the fourth week of treatment (n = 47; 57.3%). The mean reductions in the size of the right and left PG volumes were 6.31 cc (20.9%) and 5.98 cc (20.5%), respectively (p < 0.001). The reduction in PG volume was ≥30% in 30 patients (36.6%). The volume reduction in all of the anatomical structures was statistically significant. Four variables—advanced stage disease (T3−T4), chemoradiation, increased weight loss, and oropharyngeal localization—were significantly associated with the need for ART. The B-ART protocol provides clear criteria to eliminate random errors, and to allow for an early response to relevant changes in target volumes.

Project description:PurposeOptimal head-and-neck cancer (HNC) treatment planning requires accurate and feasible planning goals to meet dosimetric constraints and generate robust online adaptive treatment plans. A new x-ray-based adaptive radiotherapy (ART) treatment planning system (TPS) version 2.0 emulator includes novel methods to drive the planning process including the revised intelligent optimization engine algorithm (IOE2). HNC is among the most challenging and complex sites and heavily depends on planner skill and experience to successfully generate a reference plan. Therefore, we evaluate the new TPS performance via conventionally accepted planning strategies with/without artificial intelligence (AI) and knowledge-based planning (KBP).MethodsOur institution has a pre-clinical release of the Varian Ethos2.0 TPS emulator which includes several changes that may affect current planning strategies. Twenty definitive and post-operative HNC patients were retrospectively selected with a two or three-level simultaneous integrated boost (SIB) dosing scheme. Patients were replanned in the emulator using population-based, KBP-guided with/without human intervention and AI-guided planning goals. These planning strategies were compared both dosimetrically and for plan deliverability.ResultsAll strategies generally demonstrated acceptable plan quality with KBP- and AI-guided goals offering enhanced dosimetric sparing in organs-at-risk (OAR). The average contralateral parotid gland mean dose was 20.0 ± 6.1 Gy (p < 0.001) for population-based and 15.0 ± 6.1 Gy (p = n.s.) for KBP-with human intervention versus 15.1 ± 7.4 Gy for clinical plans. Target coverage, minimum dose, and plan hotspot were acceptable in all cases. KBP-enabled strategy demonstrated higher modulation and faster optimization time than both population-based and AI-guided strategies.ConclusionSimply entering population, automatic KBP-enabled or AI-generated planning goals into the new Ethos2.0 TPS produced dosimetrically compliant plans, with AI-guided goals demonstrating the most OAR sparing. Several of these approaches are easy to translate to other treatment sites and will help lower the barrier to entry for x-ray-based online-ART.

Dataset Information

FMISO-Based Adaptive Radiotherapy in Head and Neck Cancer.

Publications

FMISO-Based Adaptive Radiotherapy in Head and Neck Cancer.

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