Purpose/Objective Locoregional recurrence (LRR) represents a significant burden in cancer-related deaths, impacting 15-50% of patients treated for head-and-neck cancer (HNC) [1]. Accurately classifying the location of, and the dose delivered to, the failure site is a crucial step towards understanding the causes of LRR. The aim of this study is to classify and analyse patterns of loco-regional failure after radiotherapy treatment, for HNC patients, in the Cambridge VoxTox study. This classification methodology builds upon previous work done by Mohamed et al [2] by incorporating the radiotherapy dose-field, instead of CTV volumes, as the primary basis for investigating patterns of locoregional failure. Material/Methods Eighteen patients with evidence of local and/or locoregional failure following image-guided intensity-modulated radiotherapy (IMRT) for HNC were identified. Three patients were excluded from the analysis due to incomplete data. The relapse gross tumour volume (rGTV) and clinical target volumes (CTVs) were manually delineated on each patient's relapse diagnostic CT (rCT) by radiation oncologists. The thyroid cartilage (TC) was delineated by experienced HNC clinicians as a comparative organ at risk (OAR) on both the planning CT (pCT) and relapse diagnostic CT (rCT). The pCT was co-registered with the rCT using deformable image registration (DIR) to obtain the transform for spatial mapping between the two CT scans. The accuracy of the DIR for each patient was quantified using the target registration error (TRE) of the centroid of the thyroid cartilage (TC). The final cohort TRE was calculated as the absolute distance between centroid of TC on the pCT and centroid of TC mapped from the rCT to the pCT, averaged across all LRR patients included in the analysis. The clinically prescribed dose to the high-risk region (CTV1), intermediate-risk region (CTV2) and low-risk region (CTV3) was obtained from the patient's radiotherapy plan. A dosimetric structure set was then created by delineating structures that encapsulate regions receiving 95% of the dose clinically prescribed to these high-risk, intermediate-risk and low-risk CTVs. The rGTV was then spatially mapped onto the pCT and compared with each of the 95% dose structures using centroid and volume-based criteria. The failure was then classified into one of five categories, dependent on these criteria: A (central high dose), B (peripheral high dose), C (central elective dose), D (peripheral elective dose), and E (extraneous dose) [2]. Clinical patient variables were used to search for associations between treatment type and LRR classifications. Results In total, 15 recurrences were identified and classified using DIR methods. The cohort DIR TRE was evaluated as 4.5 mm. Of the 15 LRR, 9 were identified as Type A (central high dose), 1 as Type B (peripheral high dose), 1 as Type C (central elective dose), and 4 as Type E (extraneous dose). Among the 9 high-risk Type A failures, 8 received 65 Gy in 30 fractions with bilateral neck irradiation, and 1 received post-operative doses of 60 Gy in 30 with unilateral neck. The most common Type A primary site was oropharynx (67%). All Type E patients had primary surgery to the primary tumour volume; none underwent bilateral neck irradiation. Three Type E patients received post-operative doses (60 Gy in 30) to oral cavity or salivary gland, and one received a comorbidity-adjusted protocol of 50 Gy in 20. Oral cavity was the primary site for 75% of Type E patients. In previous work by Mohamed et al [2], no type E patients were classified, as patients who received adjuvant RT following definitive surgery were excluded from the analysis. Conclusion The majority of HNC LRRs in the VoxTox study originate within the high-dose volumes (Type A), with the majority receiving a maximal treatment dose of 65 Gy in 30 fractions. Type A, high-dose, classifications are suggestive of radiobiological resistance to treatment dose. Patients recurring in the extraneous dose regions (Type E), all received primary surgery with unilateral or no neck irradiation. The VoxTox study is a small dataset and presents a preliminary exploration of LRR classifications. However, exploration in large datasets is crucial for investigating relationships between LRR failure patterns and clinical variables. As a result, work on a larger local validation dataset from Cambridge University Hospitals is ongoing.

Background: The irradiation of sub-regions of the parotid has been linked to xerostomia development in patients with head and neck cancer (HNC). In this study, we compared the xerostomia classification performance of radiomics features calculated on clinically relevant and de novo sub-regions of the parotid glands of HNC patients.Material and Methods: All patients (N = 117) were treated with TomoTherapy in 30-35 fractions of 2-2.167 Gy per fraction with daily mega-voltage-CT (MVCT) acquisition for image-guidance purposes. Radiomics features (N = 123) were extracted from daily MVCTs for the whole parotid gland and nine sub-regions. The changes in feature values after each complete week of treatment were considered as predictors of xerostomia (CTCAEv4.03, grade >= 2) at 6 and 12 months. Combinations of predictors were generated following the removal of statistically redundant information and stepwise selection. The classification performance of the logistic regression models was evaluated on train and test sets of patients using the Area Under the Curve (AUC) associated with the different sub-regions at each week of treatment and benchmarked with the performance of models solely using dose and toxicity at baseline.Results: In this study, radiomics-based models predicted xerostomia better than standard clinical predictors. Models combining dose to the parotid and xerostomia scores at baseline yielded an AUC(test) of 0.63 and 0.61 for xerostomia prediction at 6 and 12 months after radiotherapy while models based on radiomics features extracted from the whole parotid yielded a maximum AUC(test) of 0.67 and 0.75, respectively. Overall, across sub-regions, maximum AUC(test) was 0.76 and 0.80 for xerostomia prediction at 6 and 12 months. Within the first two weeks of treatment, the cranial part of the parotid systematically yielded the highest AUC(test).Conclusion: Our results indicate that variations of radiomics features calculated on sub-regions of the parotid glands can lead to earlier and improved prediction of xerostomia in HNC patients.

Background: This study was designed to identify common genetic susceptibility and shared genetic variants associated with acute radiation-induced toxicity across 4 cancer types (prostate, head and neck, breast, and lung).Methods: A genome-wide association study meta-analysis was performed using 19 cohorts totaling 12 042 patients. Acute standardized total average toxicity (STATacute) was modelled using a generalized linear regression model for additive effect of genetic variants, adjusted for demographic and clinical covariates (rSTATacute). Linkage disequilibrium score regression estimated shared single-nucleotide variation (SNV-formerly SNP)-based heritability of rSTATacute in all patients and for each cancer type.Results: Shared SNV-based heritability of STATacute among all cancer types was estimated at 10% (SE = 0.02) and was higher for prostate (17%, SE = 0.07), head and neck (27%, SE = 0.09), and breast (16%, SE = 0.09) cancers. We identified 130 suggestive associated SNVs with rSTATacute (5.0 x 10-8 < P < 1.0 x 10-5) across 25 genomic regions. rs142667902 showed the strongest association (effect allele A; effect size -0.17; P = 1.7 x 10-7), which is located near DPPA4, encoding a protein involved in pluripotency in stem cells, which are essential for repair of radiation-induced tissue injury. Gene-set enrichment analysis identified 'RNA splicing via endonucleolytic cleavage and ligation' (P = 5.1 x 10-6, P = .079 corrected) as the top gene set associated with rSTATacute among all patients. In silico gene expression analysis showed that the genes associated with rSTATacute were statistically significantly up-regulated in skin (not sun exposed P = .004 corrected; sun exposed P = .026 corrected).Conclusions: There is shared SNV-based heritability for acute radiation-induced toxicity across and within individual cancer sites. Future meta-genome-wide association studies among large radiation therapy patient cohorts are worthwhile to identify the common causal variants for acute radiotoxicity across cancer types.

Background and purpose: We aimed to the genetic components and susceptibility variants associated with acute radiation-induced toxicities (RITs) in patients with head and neck cancer (HNC). Materials and methods: We performed the largest meta-GWAS of seven European cohorts (n = 4,042). Patients were scored weekly during radiotherapy for acute RITs including dysphagia, mucositis, and xerostomia. We analyzed the effect of variants on the average burden (measured as area under curve, AUC) per each RIT, and standardized total average acute toxicity (STATacute) score using a multivariate linear regression. We tested suggestive variants (p < 1.0x10-5) in discovery set (three cohorts; n = 2,640) in a replication set (four cohorts; n = 1,402). We meta-analysed all cohorts to calculate RITs specific SNPbased heritability, and effect of polygenic risk scores (PRSs), and genetic correlations among RITS. Results: From 393 suggestive SNPs identified in discovery set; 37 were nominally significant (preplication < 0.05) in replication set, but none reached genome-wide significance (pcombined < 5 x 10-8). Insilico functional analyses identified "3'-5'-exoribonuclease activity" (FDR = 1.6e-10) for dysphagia, "inositol phosphate-mediated signalling" for mucositis (FDR = 2.20e-09), and "drug catabolic process" for STATacute (FDR = 3.57e-12) as the most enriched pathways by the RIT specific suggestive genes. The SNP-based heritability (+/- standard error) was 29 +/- 0.08 % for dysphagia, 9 +/- 0.12 % (mucositis) and 27 +/- 0.09 % (STATacute). Positive genetic correlation was rg = 0.65 (p = 0.048) between dysphagia and STATacute. PRSs explained limited variation of dysphagia (3 %), mucositis (2.5 %), and STATacute (0.4 %). Conclusion: In HNC patients, acute RITs are modestly heritable, sharing 10 % genetic susceptibility, when PRS explains < 3 % of their variance. We identified numerus suggestive SNPs, which remain to be repli-cated in larger studies. (c) 2022 The Author(s). Published by Elsevier B.V. Radiotherapy and Oncology 176 (2022) 138-148 This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Background and purpose: The images acquired during radiotherapy for image-guidance purposes could be used to monitor patient-specific response to irradiation and improve treatment personalisation. We investigated whether the kinetics of radiomics features from daily mega-voltage CT image-guidance scans (MVCT) improve prediction of moderate-to-severe xerostomia compared to dose/volume parameters in radiotherapy of head-and-neck cancer (HNC). Materials and Methods: All included HNC patients (N = 117) received 30 or more fractions of radiotherapy with daily MVCTs. Radiomics features were calculated on the contra-lateral parotid glands of daily MVCTs. Their variations over time after each complete week of treatment were used to predict moderate-to-severe xerostomia (CTCAEv4.03 grade >= 2) at 6, 12 and 24 months post-radiotherapy. After dimensionality reduction, backward/ forward selection was used to generate combinations of predictors. Three types of logistic regression model were generated for each follow-up time: 1) a pre-treatment reference model using dose/volume parameters, 2) a combination of dose/volume and radiomics-based predictors, and 3) radiomics-based predictors. The models were internally validated by cross-validation and bootstrapping and their performance evaluated using Area Under the Curve (AUC) on separate training and testing sets. Results: Moderate-to-severe xerostomia was reported by 46 %, 33 % and 26 % of the patients at 6, 12 and 24 months respectively. The selected models using radiomics-based features extracted at or before mid-treatment outperformed the dose-based models with an AUCtrain/AUCtest of 0.70/0.69, 0.76/0.74, 0.86/0.86 at 6, 12 and 24 months, respectively. Conclusion: Our results suggest that radiomics features calculated on MVCTs from the first half of the radio-therapy course improve prediction of moderate-to-severe xerostomia in HNC patients compared to a dose-based pre-treatment model.

Background and purpose: While core to the scientific approach, reproducibility of experimental results is challenging in radiomics studies. A recent publication identified radiomics features that are predictive of late irradiation-induced toxicity in head and neck cancer (HNC) patients. In this study, we assessed the generalisability of these findings. Materials and Methods: The procedure described in the publication in question was applied to a cohort of 109 HNC patients treated with 50–70 Gy in 20–35 fractions using helical radiotherapy although there were inherent differences between the two patient populations and methodologies. On each slice of the planning CT with delineated parotid and submandibular glands, the imaging features that were previously identified as predictive of moderate-to-severe xerostomia and sticky saliva 12 months post radiotherapy (Xer12m and SS12m) were calculated. Specifically, Short Run Emphasis (SRE) and maximum CT intensity (maxHU) were evaluated for improvement in prediction of Xer12m and SS12m respectively, compared to models solely using baseline toxicity and mean dose to the salivary glands. Results: None of the associations previously identified as statistically significant and involving radiomics features in univariate or multivariate models could be reproduced on our cohort. Conclusion: The discrepancies observed between the results of the two studies delineate limits to the generalisability of the previously reported findings. This may be explained by the differences in the approaches, in particular the imaging characteristics and subsequent methodological implementation. This highlights the importance of external validation, high quality reporting guidelines and standardisation protocols to ensure generalisability, replication and ultimately clinical implementation.

Background and Purpose Associations between dose and rectal toxicity in prostate radiotherapy are generally poorly understood. Evaluating spatial dose distributions to the rectal wall (RW) may lead to improvements in dose-toxicity modelling by incorporating geometric information, masked by dose-volume histograms. Furthermore, predictive power may be strengthened by incorporating the effects of interfraction motion into delivered dose calculations. Here we interrogate 3D dose distributions for patients with and without toxicity to identify rectal subregions at risk (SRR), and compare the discriminatory ability of planned and delivered dose. Material and Methods Daily delivered dose to the rectum was calculated using image guidance scans, and accumulated at the voxel level using biomechanical finite element modelling. SRRs were statistically determined for rectal bleeding, proctitis, faecal incontinence and stool frequency from a training set (n = 139), and tested on a validation set (n = 47). Results SRR patterns differed per endpoint. Analysing dose to SRRs improved discriminative ability with respect to the full RW for three of four endpoints. Training set AUC and OR analysis produced stronger toxicity associations from accumulated dose than planned dose. For rectal bleeding in particular, accumulated dose to the SRR (AUC 0.76) improved upon dose-toxicity associations derived from planned dose to the RW (AUC 0.63). However, validation results could not be considered significant. Conclusions Voxel-level analysis of dose to the RW revealed SRRs associated with rectal toxicity, suggesting non-homogeneous intra-organ radiosensitivity. Incorporating spatial features of accumulated delivered dose improved dose-toxicity associations. This may be an important tool for adaptive radiotherapy in the future.

ConclusionA NTCP model based on delivered dose to SRR0.01 and HTN was generated and validated for RB.External validation would be desirable.FEA provides a more anatomically representative tool for dose accumulation than planar homogeneous expansion.Improved toxicity prediction based on delivered dose could be useful for decision making in adaptive RT.

Background and purpose: The impact of weight loss and anatomical change during head and neck (H&N) radiotherapy on spinal cord dosimetry is poorly understood, limiting evidence-based adaptive management strategies. Materials and methods: 133 H&N patients treated with daily mega-voltage CT image-guidance (MVCT-IG) on TomoTherapy, were selected. Elastix software was used to deform planning scan SC contours to MVCT-IG scans, and accumulate dose. Planned (D-p) and delivered (D-A) spinal cord D20%, (SCD2%) were compared. Univariate relationships between neck irradiation strategy (unilateral vs bilateral), T-stage, N stage, weight loss, and changes in lateral separation (LND) and CT slice surface area (SSA) at Cl and the superior thyroid notch (TN), and Delta SCD2% [(D-A-D-p) D2%] were examined. Results: The mean value for (D-A-D-p) D-2%, was-0.07 Gy (95%CI-0.28 to 0.14, range-5.7 Gy to 3.8 Gy), and the mean absolute difference between D-p and D-A (independent of difference direction) was 0.9 Gy (95%CI 0.76-1.04 Gy). Neck treatment strategy (p = 0.39) and T-stage (p = 0.56) did not affect Delta SCD2%. Borderline significance (p = 0.09) was seen for higher N-stage (N2-3) and higher Delta SCD2%. Mean reductions in anatomical metrics were substantial: weight loss 6.8 kg; C1LND 12.9 mm; C1SSA 12.1 cm2; TNLND 5.3 mm; TNSSA 11.2 cm(2), but no relationship between weight loss or anatomical change and Delta SCD2% was observed (all r(2) < 0.1). Conclusions: Differences between delivered and planned spinal cord D-2%, are small in patients treated with daily 1G. Even patients experiencing substantial weight loss or anatomical change during treatment do not require adaptive replanning for spinal cord safety. (C) 2018 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

L’Hermitte’s sign (LS) after chemoradiotherapy for head and neck cancer appears related to higher spinal cord doses. IMRT plans limit spinal cord dose, but the incidence of LS remains high.

ESTRO 36 _______________________________________________________________________________________________ transformation parameters, we created 'voxel histories' for the spinal cord relative to the planning CT, and calculated delivered dose.Maximum planned and delivered spinal cord dose (D2%) were then compared. ResultsA summary of auto-contouring algorithm performance is shown in Table 1.Auto-contouring performance appeared comparable to manual segmentation, and we proceeded to calculate delivered dose.These results are shown in Figure 1 (A-C).Fig. 1A shows a waterfall plot of planned D2% minus delivered D2% for each patient.Mean spinal cord D2% was 35.96Gy (planned) and 36.01Gy(delivered), and the mean absolute difference between planned and delivered dose was 1.1Gy (3% of mean planned D2%).Differences between planned and delivered dose were plotted as a histogram, which appears to be normally distributed around the mean difference (Fig 1B).The mean difference (µ, -0.05) and standard deviation (σ, 1.448) were used to approximate a normal distribution to this data -as shown in Fig. 1C.Using this model, a z statistic can be calculated for a chosen difference (e.g.Prob. of delivered D2% being 4Gy higher than planned is 2.5%). ConclusionDifferences between planned and delivered D2% to the spinal cord in patients receiving daily IG are small in HNC patients treated with daily IG on TomoTherapy.Our model permits computation of clinically meaningful differences in context, but differences in spinal cord dose mandating ART should be a rare event.

The VoxTox research programme has applied expertise from the physical sciences to the problem of radiotherapy toxicity, bringing together expertise from engineering, mathematics, high energy physics (including the Large Hadron Collider), medical physics and radiation oncology. In our initial cohort of 109 men treated with curative radiotherapy for prostate cancer, daily image guidance computed tomography (CT) scans have been used to calculate delivered dose to the rectum, as distinct from planned dose, using an automated approach. Clinical toxicity data have been collected, allowing us to address the hypothesis that delivered dose provides a better predictor of toxicity than planned dose.