Development and multicenter validation of a multiparametric imaging model to predict treatment response in rectal cancer.

OBJECTIVES: To develop and validate a multiparametric model to predict neoadjuvant treatment response in rectal cancer at baseline using a heterogeneous multicenter MRI dataset. METHODS: Baseline staging MRIs (T2W (T2-weighted)-MRI, diffusion-weighted imaging (DWI) / apparent diffusion coefficient (ADC)) of 509 patients (9 centres) treated with neoadjuvant chemoradiotherapy (CRT) were collected. Response was defined as (1) complete versus incomplete response, or (2) good (Mandard tumor regression grade (TRG) 1-2) versus poor response (TRG3-5). Prediction models were developed using combinations of the following variable groups: (1) Non-imaging: age/sex/tumor-location/tumor-morphology/CRT-surgery interval (2) Basic staging: cT-stage/cN-stage/mesorectal fascia involvement, derived from (2a) original staging reports, or (2b) expert re-evaluation (3) Advanced staging: variables from 2b combined with cTN-substaging/invasion depth/extramural vascular invasion/tumor length (4) Quantitative imaging: tumour volume + first-order histogram features (from T2W-MRI and DWI/ADC) Models were developed with data from 6 centers (n = 412) using logistic regression with the Least Absolute Shrinkage and Selector Operator (LASSO) feature selection, internally validated using repeated (n = 100) random hold-out validation, and externally validated using data from 3 centers (n = 97). RESULTS: After external validation, the best model (including non-imaging and advanced staging variables) achieved an area under the curve of 0.60 (95%CI=0.48-0.72) to predict complete response and 0.65 (95%CI=0.53-0.76) to predict a good response. Quantitative variables did not improve model performance. Basic staging variables consistently achieved lower performance compared to advanced staging variables. CONCLUSIONS: Overall model performance was moderate. Best results were obtained using advanced staging variables, highlighting the importance of good-quality staging according to current guidelines. Quantitative imaging features had no added value (in this heterogeneous dataset). CLINICAL RELEVANCE STATEMENT: Predicting tumour response at baseline could aid in tailoring neoadjuvant therapies for rectal cancer. This study shows that image-based prediction models are promising, though are negatively affected by variations in staging quality and MRI acquisition, urging the need for harmonization. KEY POINTS: This multicenter study combining clinical information and features derived from MRI rendered disappointing performance to predict response to neoadjuvant treatment in rectal cancer. Best results were obtained with the combination of clinical baseline information and state-of-the-art image-based staging variables, highlighting the importance of good quality staging according to current guidelines and staging templates. No added value was found for quantitative imaging features in this multicenter retrospective study. This is likely related to acquisition variations, which is a major problem for feature reproducibility and thus model generalizability.

Sources of variation in multicenter rectal MRI data and their effect on radiomics feature reproducibility.

OBJECTIVES: To investigate sources of variation in a multicenter rectal cancer MRI dataset focusing on hardware and image acquisition, segmentation methodology, and radiomics feature extraction software. METHODS: T2W and DWI/ADC MRIs from 649 rectal cancer patients were retrospectively acquired in 9 centers. Fifty-two imaging features (14 first-order/6 shape/32 higher-order) were extracted from each scan using whole-volume (expert/non-expert) and single-slice segmentations using two different software packages (PyRadiomics/CapTk). Influence of hardware, acquisition, and patient-intrinsic factors (age/gender/cTN-stage) on ADC was assessed using linear regression. Feature reproducibility was assessed between segmentation methods and software packages using the intraclass correlation coefficient. RESULTS: Image features differed significantly (p < 0.001) between centers with more substantial variations in ADC compared to T2W-MRI. In total, 64.3% of the variation in mean ADC was explained by differences in hardware and acquisition, compared to 0.4% by patient-intrinsic factors. Feature reproducibility between expert and non-expert segmentations was good to excellent (median ICC 0.89-0.90). Reproducibility for single-slice versus whole-volume segmentations was substantially poorer (median ICC 0.40-0.58). Between software packages, reproducibility was good to excellent (median ICC 0.99) for most features (first-order/shape/GLCM/GLRLM) but poor for higher-order (GLSZM/NGTDM) features (median ICC 0.00-0.41). CONCLUSIONS: Significant variations are present in multicenter MRI data, particularly related to differences in hardware and acquisition, which will likely negatively influence subsequent analysis if not corrected for. Segmentation variations had a minor impact when using whole volume segmentations. Between software packages, higher-order features were less reproducible and caution is warranted when implementing these in prediction models. KEY POINTS: • Features derived from T2W-MRI and in particular ADC differ significantly between centers when performing multicenter data analysis. • Variations in ADC are mainly (> 60%) caused by hardware and image acquisition differences and less so (< 1%) by patient- or tumor-intrinsic variations. • Features derived using different image segmentations (expert/non-expert) were reproducible, provided that whole-volume segmentations were used. When using different feature extraction software packages with similar settings, higher-order features were less reproducible.

Studying local tumour heterogeneity on MRI and FDG-PET/CT to predict response to neoadjuvant chemoradiotherapy in rectal cancer.

OBJECTIVE: To investigate whether quantifying local tumour heterogeneity has added benefit compared to global tumour features to predict response to chemoradiotherapy using pre-treatment multiparametric PET and MRI data. METHODS: Sixty-one locally advanced rectal cancer patients treated with chemoradiotherapy and staged at baseline with MRI and FDG-PET/CT were retrospectively analyzed. Whole-tumour volumes were segmented on the MRI and PET/CT scans from which global tumour features (T2Wvolume/T2Wentropy/ADCmean/SUVmean/TLG/CTmean-HU) and local texture features (histogram features derived from local entropy/mean/standard deviation maps) were calculated. These respective feature sets were combined with clinical baseline parameters (e.g. age/gender/TN-stage) to build multivariable prediction models to predict a good (Mandard TRG1-2) versus poor (Mandard TRG3-5) response to chemoradiotherapy. Leave-one-out cross-validation (LOOCV) with bootstrapping was performed to estimate performance in an 'independent' dataset. RESULTS: When using only imaging features, local texture features showed an AUC = 0.81 versus AUC = 0.74 for global tumour features. After internal cross-validation (LOOCV), AUC to predict a good response was the highest for the combination of clinical baseline variables + global tumour features (AUC = 0.83), compared to AUC = 0.79 for baseline + local texture and AUC = 0.76 for all combined (baseline + global + local texture). CONCLUSION: In imaging-based prediction models, local texture analysis has potential added value compared to global tumour features to predict response. However, when combined with clinical baseline parameters such as cTN-stage, the added value of local texture analysis appears to be limited. The overall performance to predict response when combining baseline variables with quantitative imaging parameters is promising and warrants further research. KEY POINTS: • Quantification of local tumour texture on pre-therapy FDG-PET/CT and MRI has potential added value compared to global tumour features to predict response to chemoradiotherapy in rectal cancer. • However, when combined with clinical baseline parameters such as cTN-stage, the added value of local texture over global tumour features is limited. • Predictive performance of our optimal model-combining clinical baseline variables with global quantitative tumour features-was encouraging (AUC 0.83), warranting further research in this direction on a larger scale.

Bias correction for estimates from linear excess relative risk models in small case-control studies.

Epidemiologic studies conducted to quantify the impact of radiation dose d on an outcome typically model the hazard ratio (HR) for association using a linear term, HR(d)=1+ßd , via a linear excess relative risk (ERR) model, based on biological considerations. To study associations of risk of a second cancer with radiation treatment for a first cancer, several nested case-control designs to estimate ß have been proposed that use refined doses received by different locations in the organ of interest. Here we first evaluated the small sample bias in maximum likelihood estimates of ß for the linear ERR model using location-specific radiation doses in simulations. As we found substantial upward bias for studies of realistic sample sizes (more than 50% relative bias for studies with 75 cases), we also proposed and investigated several approaches to correct this bias. We studied first and second order jackknife bias corrections and we derived a modified set of score functions under retrospective case-control sampling, from which we directly obtained bias-corrected estimates. In simulations based on doses from a study of stomach cancer among testicular cancer survivors and synthetically generated data, neither the first nor second order jackknife bias correction performed well. Estimates based on the modified score equations corrected the bias much better, albeit not completely, and were numerically much more stable.

Pre-treatment prediction of early response to chemoradiotherapy by quantitative analysis of baseline staging FDG-PET/CT and MRI in locally advanced cervical cancer.

BACKGROUND: Early prediction of response to concurrent chemoradiotherapy (cCRT) could aid to further optimize treatment regimens for locally advanced cervical cancer (LACC) in the future. PURPOSE: To explore whether quantitative parameters from baseline (pre-therapy) magnetic resonance imaging (MRI) and FDG-PET/computed tomography (CT) have potential as predictors of early response to cCRT. MATERIAL AND METHODS: Forty-six patients with LACC undergoing cCRT after staging with FDG-PET/CT and MRI were retrospectively analyzed. Primary tumor volumes were delineated on FDG-PET/CT, T2-weighted (T2W)-MRI and diffusion-weighted MRI (DWI) to extract the following quantitative parameters: T2W volume; T2W signalmean; DWI volume; ADCmean; ADCSD; MTV42%; and SUVmax. Outcome was the early treatment response, defined as the residual tumor volume on MRI 3-4 weeks after start of external beam radiotherapy with chemotherapy (before the start of brachytherapy): patients with a residual tumor volume <10 cm3 were classified as early responders. Imaging parameters were analyzed together with FIGO stage to assess their performance to predict early response, using multivariable logistic regression analysis with bi-directional variable selection. Leave-one-out cross-validation with bootstrapping was used to simulate performance in a new, independent dataset. RESULTS: T2W volume (OR 0.94, P = 0.003) and SUVmax (OR 1.15, P = 0.18) were identified as independent predictors in multivariable analysis, rendering a model with an AUC of 0.82 in the original dataset, and AUC of 0.68 (95% CI 0.41-0.81) from cross-validation. CONCLUSION: Although the predictive performance achieved in this small exploratory dataset was limited, these preliminary data suggest that parameters from baseline MRI and FDG-PET/CT (in particular pre-therapy tumor volume) may contribute to prediction of early response to cCRT in cervical cancer.

Value of combined multiparametric MRI and FDG-PET/CT to identify well-responding rectal cancer patients before the start of neoadjuvant chemoradiation.

OBJECTIVES: To explore the value of multiparametric MRI combined with FDG-PET/CT to identify well-responding rectal cancer patients before the start of neoadjuvant chemoradiation. METHODS: Sixty-one locally advanced rectal cancer patients who underwent a baseline FDG-PET/CT and MRI (T2W + DWI) and received long-course neoadjuvant chemoradiotherapy were retrospectively analysed. Tumours were delineated on MRI and PET/CT from which the following quantitative parameters were calculated: T2W volume and entropy, ADC mean and entropy, CT density (mean-HU), SUV maximum and mean, metabolic tumour volume (MTV42%) and total lesion glycolysis (TLG). These features, together with sex, age, mrTN-stage ("baseline parameters") and the CRT-surgery interval were analysed using multivariable stepwise logistic regression. Outcome was a good (TRG 1-2) versus poor histopathological response. Performance (AUC) to predict response was compared for different combinations of baseline ± quantitative imaging parameters and performance in an 'independent' dataset was estimated using bootstrapped leave-one-out cross-validation (LOOCV). RESULTS: The optimal multivariable prediction model consisted of a combination of baseline + quantitative imaging parameters and included mrT-stage (OR 0.004, p < 0.001), T2W-signal entropy (OR 7.81, p = 0.0079) and T2W volume (OR 1.028, p = 0.0389) as the selected predictors. AUC in the study dataset was 0.88 and 0.83 after LOOCV. No PET/CT features were selected as predictors. CONCLUSIONS: A multivariable model incorporating mrT-stage and quantitative parameters from baseline MRI can aid in identifying well-responding patients before the start of treatment. Addition of FDG-PET/CT is not beneficial. KEY POINTS: • A multivariable model incorporating the mrT-stage and quantitative features derived from baseline MRI can aid in identifying well-responding patients before the start of neoadjuvant chemoradiotherapy. • mrT-stage was the strongest predictor in the model and was complemented by the tumour volume and signal entropy calculated from T2W-MRI. • Adding quantitative features derived from pre-treatment PET/CT or DWI did not contribute to the model's predictive performance.

Integrated versus separate reading of F-18 FDG-PET/CT and MRI for abdominal malignancies - effect on staging outcomes and diagnostic confidence.

OBJECTIVE: Abdominal cancer patients increasingly undergo multimodality imaging. This study evaluates effects of integrated reading of PET/CT and abdominal MRI on staging outcomes and diagnostic confidence compared to "routine" separate reading. METHODS: In total, N = 201 patients who underwent abdominal MRI and whole-body F-18 FDG-PET/CT within 14 days were retrospectively analyzed. Original MRI and PET/CT reports were retrieved and reported findings translated into a 5-point confidence score (1 = definitely benign to 5 = definitely malignant) for 7 standardized regions (primary tumor/regional lymph nodes/distant lymph nodes/liver/lung/bone/peritoneum) per patient. Two-reader teams (radiologist + nuclear medicine physician) then performed integrated reading of the images using the same scoring system. RESULTS: Integrated reading led to discrepant findings in 59 of 201 (29%) of patients, with potential clinical impact in 25 of 201 (12%). Equivocal scores decreased from 5.7% (PET/CT) and 5.4% (MRI) to 3.2% (p = 0.05 and p = 0.14). Compared to the original PET/CT reports, integrated reading led to increased diagnostic confidence in 8.9% versus decreased confidence in 6.6% (p = 0.26). Compared with the original MRI reports, an increase in confidence occurred in 9.6% versus a decrease in 6.9% (p = 0.18). The effect on diagnostic confidence was most pronounced in lymph nodes (p = 0.08 vs. MRI), cervical cancer (p = 0.03 vs. MRI), and recurrent disease staging (p = 0.06 vs. PET/CT). CONCLUSIONS: Integrated PET/CT+MRI reading alters staging outcomes in a substantial proportion of cases with potential clinical impact in ± 1 out of 9 patients. It can also have a small positive effect on diagnostic confidence, particularly in lymph nodes and cervical cancer, and in post-treatment settings. These findings support further collaboration between radiology and nuclear medicine disciplines. KEY POINTS: • Increasing numbers of patients undergo multimodality imaging consisting of both MRI and PET/CT for staging of abdominal malignancies. • Integrated reading of FDG-PET/CT and abdominal MR images by a team, consisting of a radiologist and a nuclear medicine physician, can alter staging outcomes compared to separate reporting of the exams in a substantial proportion of cases and with potential clinical impact in ± 1 out of 9 patients. • Integrated PET/CT+MRI reading can have a small positive effect on diagnostic confidence.

Association of Radiation and Procarbazine Dose With Risk of Colorectal Cancer Among Survivors of Hodgkin Lymphoma.

Importance: Hodgkin lymphoma (HL) survivors have higher rates of colorectal cancer, which may be associated with subdiaphragmatic radiation therapy and/or alkylating chemotherapy. Although radiation dose-response associations with breast, lung, stomach, pancreatic, and esophageal cancer after HL have been demonstrated, the association of radiation therapy with colorectal cancer remains unclear. Objective: To quantify the rate of colorectal cancer according to radiation dose to the large bowel and procarbazine dose among HL survivors. Design, Setting, and Participants: A nested case-control study examined 5-year HL survivors at 5 hospital centers in the Netherlands. Participants had been diagnosed with HL in 1964 to 2000, when they were 15 to 50 years of age, and were followed for a median of approximately 26 years. Survivors of HL who developed colorectal cancer and survivors who were selected as controls were individually matched on sex, age at HL diagnosis, and date of HL diagnosis. Data were analyzed from July 2021 to October 2022. Exposures: Mean radiation doses to the large bowel were estimated by reconstructing individual radiation therapy treatments on representative computed tomography data sets. Main Outcomes and Measures: Excess rate ratios (ERRs) were modeled to evaluate the excess risk associated with each 1-gray increase in radiation dose, and potential effect modification by procarbazine was explored. Results: The study population included 316 participants (mean [SD] age at HL diagnosis, 33.0 [9.8] years; 221 [69.9%] men), 78 of whom were HL survivors who developed colorectal cancer (cases) and 238 who did not (controls). The median (IQR) interval between HL and colorectal cancer was 25.7 (18.2-31.6) years. Increased colorectal cancer rates were seen for patients who received subdiaphragmatic radiation therapy (rate ratio [RR], 2.4; 95% CI, 1.4-4.1) and those who received more than 8.4 g/m2 procarbazine (RR, 2.5; 95% CI, 1.3-5.0). Overall, colorectal cancer rate increased linearly with mean radiation dose to the whole large bowel and dose to the affected bowel segment. The association between radiation dose and colorectal cancer rate became stronger with increasing procarbazine dose: the ERR per gray to the whole bowel was 3.5% (95% CI, 0.4%-12.6%) for patients who did not receive procarbazine, and increased 1.2-fold (95% CI, 1.1-1.3) for each 1-g/m2 increase in procarbazine dose. Conclusions and Relevance: This nested case-control study of 5-year HL survivors found a dose-response association between radiation therapy and colorectal cancer risk, and modification of this association by procarbazine. These findings may enable individualized colorectal cancer risk estimations, identification of high-risk survivors for subsequent screening, and optimization of treatment strategies.

ADC Values of Cytologically Benign and Cytologically Malignant 18 F-FDG PET-Positive Lymph Nodes of Head and Neck Squamous Cell Carcinoma.

Nodal staging (N-staging) in head and neck squamous cell carcinoma (HNSCC) is essential for treatment planning and prognosis. 18F-fluordeoxyglucose positron emission tomography (FDG-PET) has high performance for N-staging, although the distinction between cytologically malignant and reactive PET-positive nodes, and consequently, the selection of nodes for ultrasound-guided fine needle aspiration cytology (USgFNAC), is challenging. Diffusion-weighted magnetic resonance imaging (DW-MRI) can help to detect nodal metastases. We aim to investigate the potential of the apparent diffusion coefficient (ADC) as a metric to distinguish between cytologically reactive and malignant PET-positive nodes in order to improve node selection criteria for USgFNAC. PET-CT, real-time image-fused USgFNAC and DW-MRI to calculate ADC were available for 78 patients offered for routine N-staging. For 167 FDG-positive nodes, differences in the ADC between cytologically benign and malignant PET-positive nodes were evaluated, and both were compared to the ADC values of PET-negative reference nodes. Analyses were also performed in subsets of nodes regarding HPV status. A mild negative correlation between SUVmax and ADC was found. No significant differences in ADC values were observed between cytologically malignant and benign PET-positive nodes overall. Within the subset of non-HPV-related nodes, ADCb0-200-1000 was significantly lower in cytologically malignant PET-positive nodes when compared to benign PET-positive nodes. ADCb0-1000 and ADCb0-200-1000 were significantly lower (p = 0.018, 0.016, resp.) in PET-negative reference nodes than in PET-positive nodes. ADC was significantly higher in PET-negative reference nodes than in PET-positive nodes. The non-HPV-related subgroup showed significantly (p = 0.03) lower ADC values in cytologically malignant than in cytologically benign PET-positive nodes, which should help inform the node selection procedure for puncture.

Radiotherapy-Related Dose and Irradiated Volume Effects on Breast Cancer Risk Among Hodgkin Lymphoma Survivors.

BACKGROUND: Breast cancer (BC) risk is increased among Hodgkin lymphoma (HL) survivors treated with chest radiotherapy. Case-control studies showed a linear radiation dose-response relationship for estimated dose to the breast tumor location. However, these relative risks cannot be used for absolute risk prediction of BC anywhere in the breasts. Furthermore, the independent and joint effects of radiation dose and irradiated volumes are unclear. Therefore, we examined the effects of mean breast dose and various dose-volume parameters on BC risk in HL patients. METHODS: We conducted a nested case-control study of BC among 5-year HL survivors (173 case patients, 464 matched control patients). Dose-volume histograms were obtained from reconstructed voxel-based 3-dimensional dose distributions. Summary parameters of dose-volume histograms were studied next to mean and median breast dose, Gini index, and the new dose metric mean absolute difference of dose, using categorical and linear excess odds ratio (EOR) models. Interactions between dose-volume parameters and mean dose were also examined. RESULTS: Statistically significant linear dose-response relationships were observed for mean breast dose (EOR per Gy = 0.19, 95% confidence interval [CI] = 0.05 to 1.06) and median dose (EOR/Gy = 0.06, 95% CI = 0.02 to 0.19), with no statistically significant curvature. All metrics except Gini and mean absolute difference were positively correlated with each other. These metrics all showed similar patterns of dose-response that were no longer statistically significant when adjusting for mean dose. No statistically significant modification of the effect of mean dose was observed. CONCLUSION: Mean breast dose predicts subsequent BC risk in long-term HL survivors.

Value of Assessing Peripheral Vascularization with Micro-Flow Imaging, Resistive Index and Absent Hilum Sign as Predictor for Malignancy in Lymph Nodes in Head and Neck Squamous Cell Carcinoma.

Ultrasound-guided fine needle aspiration cytology (USgFNAC) is commonly used for nodal staging in head and neck squamous cell cancer (HNSCC). Peripheral vascularity is a described feature for node metastasis. Micro-flow imaging (MFI) is a new sensitive technique to evaluate micro-vascularization. Our goal is to assess the additional value of MFI to detect malignancy in lymph nodes. A total of 102 patients with HNSCC were included prospectively. USgFNAC was performed with the Philips eL18-4 transducer. Cytological results served as a reference standard to evaluate the prediction of cytological malignancy depending on ultrasound features such as resistive index (RI), absence of fatty hilum sign, and peripheral vascularization. Results were obtained for all US examinations and for the subgroup of clinically node-negative neck (cN0). USgFNAC was performed in 211 nodes. Peripheral vascularization had a positive predictive value (PPV) of 83% (cN0: 50%) and the absence of a fatty hilum had a PPV of 82% (cN0 50%) The combination of peripheral vascularization and absent fatty hilum had a PPV of 94% (cN0: 72%). RI (threshold: 0.705) had a PPV of 61% (cN0: RI-threshold 0.615, PPV 20%), whereas the PPV of short axis diameter (threshold of 6.5mm) was 59% for all patients and 19% in cN0 necks (threshold of 4 mm). Peripheral vascularization assessed by MFI and absent hilum has a high predictive value for cytological malignancy in neck metastases. Next to size, both features should be used as additional selection criteria for USgFNAC.

Locoregional CT staging of colon cancer: does a learning curve exist?

PURPOSE: To evaluate the learning curve for locoreginal staging of colon cancer in radiologist trainees. METHODS: Eighty-eight cases of colon cancer CT were included in this retrospective study. Four senior radiology residents staged the CTs according to TNM classification. Two out of four radiologists received feedback after reading every 20 cases. Radiologic staging was compared with pathologic staging and the learning curve, diagnostic performance, reader confidence and reading time were evaluated and compared between the two groups (feedback vs. no feedback). Generalized estimating equations logistic regression, QICu statistic, ANOVA and t test/Mann-Whitney test were utilized. RESULTS: Radiologists demonstrated a significant increase in their performance to distinguish between ≤ T2 and ≥ T3 and reached an inflection point at 38 cases, with a significant association with increased number of cases reviewed (P < 0.001). Sensitivity (P < 0.001), specificity (P = 0.030) and NPV (P = 0.002) demonstrated significant associations with increased experience. The overall reader's confidence was significantly higher in the group which received feedback (P < 0.001). There was no significant improvement in performance nor in reader's confidence for N staging (N0 vs. ≥ N1) for all readers. Reading time decreased with experience and showed a significant negative association with experience (P < 0.001). CONCLUSION: Diagnostic performance of senior radiology trainees in differentiating between T2 and T3 colon cancer on CTs improved with increased experience. In contrast, evaluation of lymph node involvement did not improve with more experience. Feedback had no significant effect on improvement of diagnostic performances.

Dose-volume effects of breast cancer radiation therapy on the risk of second oesophageal cancer.

PURPOSE: To investigate the relationship between oesophagus dose-volume distribution and long-term risk of oesophageal cancer after radiation therapy for breast cancer. MATERIALS AND METHODS: In a case-control study nested within a cohort of 289,748 ≥5-year survivors of female breast cancer treated in 1943-2003 in five countries, doses to the second primary cancer (DSPC) and individual dose-volume histograms (DVH) to the entire oesophagus were reconstructed for 252 oesophageal cancer cases and 488 matched controls (median follow-up time: 13, range: 5-37 years). Using conditional logistic regression, we estimated excess odds ratios (EOR) of oesophageal cancer associated with DVH metrics. We also investigated whether DVH metrics confounded or modified DSPC-related -risk estimates. RESULTS: Among the DVH metrics evaluated, median dose (Dmedian) to the entire oesophagus had the best statistical performance for estimating risk of all histological types combined (EOR/Gy = 0.071, 95% confidence interval [CI]: 0.018 to 0.206). For squamous cell carcinoma, the most common subtype, the EOR/Gy for Dmedian increased by 31% (95% CI: 3% to 205%) for each increment of 10% of V30 (p = 0.02). Adjusting for DVH metrics did not materially change the EOR/Gy for DSPC, but there was a borderline significant positive interaction between DSPC and V30 (p = 0.07). CONCLUSION: This first study investigating the relationship between oesophagus dose-volume distribution and oesophageal cancer risk showed an increased risk per Gy for Dmedian with larger volumes irradiated at high doses. While current techniques allows better oesophagus sparing, constraints applied to Dmedian and V30 could potentially further reduce the risk of oesophageal cancer.