The carbon footprint of external beam radiotherapy and its impact in health technology assessment.

Background: The major drivers of carbon dioxide (CO2eq) emissions of external beam radiation therapy (EBRT) are not well known and limit our ability to initiate mitigation strategies. Material and methods: We describe the carbon footprint of four typical centers. We explore direct EBRT associated factors such as the impact of fractionation and use of MRI-LINAC, as well as indirect factors (e.g. patient rides). Treatment strategy related CO2eq emissions are included in a health technology assessment analysis that takes into account CO2eq emissions. Results: A typical EBRT treatment emits from 185 kgCO2eq to 2066 kgCO2eq. CO2eq emissions are mostly driven by (i) accelerator acquisition and maintenance (37.8 %), (ii) patients and workers rides (32.7 %), (iii) drugs and medical devices (7.3 %), (iv) direct energy consumption (6.1 %), and (v) building and bunker construction (5.6 %) with a substantial heterogeneity among centers. Hypofractionation has a strong impact to mitigate emissions. MRI-LINAC is associated with a substantial increase in CO2eq emissions per fraction and requires ultra hypofractionation in 5 fractions to achieve a similar carbon footprint compared to 20 fractions treatment schemes. The expected limited small increase in toxicities due to hypofractionation (when existing) are in the same range as avoided detrimental effects to future people's health thanks to CO2eq mitigation. Conclusion: Carbon footprint of EBRT is not neglectable and could be mitigated. When safely feasible, hypofractionation is one of the main factors to decrease this impact. Taking into account CO2eq emissions has a substantial impact on the health technology assessment of EBRT, favoring hypofractionated regimens.

Efficacy and toxicity following salvage high-dose-rate brachytherapy for locally recurrent prostate cancer after radiotherapy.

INTRODUCTION: The management of local relapse after prostate cancer radiotherapy is frequently based on androgen deprivation therapy. The aim of the study was to report Gustave Roussy's experience with salvage prostate brachytherapy. PATIENTS AND METHODS: All cases of localized prostate cancer presenting in an irradiated area who received salvage high dose rate (HDR) brachytherapy from 2013 to 2020 were retrospectively reviewed. RESULTS: A total of 64 patients were included. Median follow up was 30.5 months. Median initial EBRT dose was 70 Gy [Q1-Q3: 70 - 74]. Median PSA at brachytherapy was 6.8 ng/mL [Q1-Q3: 4.4 - 8.7] with a median interval between first and salvage irradiation of 10 years [Q1-Q3: 6.9 - 12.6]. The modality of the first irradiation was an exclusive EBRT in 73% of the cases, mostly with a 3D technique (82%). Dose prescription was two fractions of 12 Gy or 13 Gy associated with androgen deprivation therapy for 63% of the patients. About 23% of the patients were castrate-resistant. Disease free survival at 2 years was 58% in the whole population and 66% in hormone sensitive patients. The only factors associated with disease free survival on multivariate analysis was a high-risk disease at initial diagnosis (HR = 3.59, IC95 [1.75; 7.39], p = 0.0005). Grade 3 urinary and rectal toxicities occurred in 1.5% and 1.5% of the patients, respectively. CONCLUSION: HDR salvage brachytherapy seems to be a safe option for patients presenting with an isolated local relapse of prostate cancer.

The complexity of tumor shape, spiculatedness, correlates with tumor radiomic shape features.

Radiomics extracts high-throughput quantitative data from medical images to contribute to precision medicine. Radiomic shape features have been shown to correlate with patient outcomes. However, how radiomic shape features vary in function of tumor complexity and tumor volume, as well as with method used for meshing and voxel resampling, remains unknown. The aims of this study are to create tumor models with varying degrees of complexity, or spiculatedness, and evaluate their relationship with quantitatively extracted shape features. Twenty-eight tumor models were mathematically created using spherical harmonics with the spiculatedness degree d being increased by increments of 3 (d = 11 to d = 92). Models were 3D printed with identical bases of 5 cm, imaged with a CT scanner with two different slice thicknesses, and semi-automatically delineated. Resampling of the resulting masks on a 1 × 1 × 1 mm3 grid was performed, and the voxel size of each model was then calculated to eliminate volume differences. Four MATLAB-based algorithms (isosurface (M1), isosurface filter (M2), isosurface remeshing (M3), and boundary (M4)) were used to extract nine 3D features (Volume, Surface area, Surface-to-volume, Compactness1, Compactness2, Compactness3, Spherical Disproportion, Sphericity and Fractional Concavity). To quantify the impact of 3D printing, acquisition, segmentation and meshing, features were computed directly from the stereolithography (STL) file format that was used for 3D printing, and compared to those computed. Changes in feature values between 0.6 and 2 mm slice acquisitions were also compared. Spearman's rank-order correlation coefficients were computed to determine the relationship of each shape feature with spiculatedness for each of the four meshing algorithms. Percent changes were calculated between shape features extracted from the original and resampled contoured images to evaluate the influence of spatial resampling. Finally, the percent change in shape features when the volume was changed from 25% to 150% of their original volume was quantified for three distinct tumor models and compared to the percent change observed when modifying the spiculatedness of the model from d = 11 to d = 92. Values extracted using isosurface remeshing method are the closest to the STL reference ones, with mean differences less than 10.8% (Compactness2) for all features. Seven of the eight features had strong significant correlations with tumor model complexity irrespective of the meshing algorithm (r > 0.98, p < 10-4), with fractional concavity having the lowest correlation coefficient (r = 0.83, p < 10-4, M2). Comparisons of features extracted from the 0.6 and 2 mm slice thicknesses showed that mean differences were from 2.1% (Compactness3) to 12.7% (Compactness2) for the isosurface remeshing method. Resampling on a 1 × 1 × 1 mm3 grid resulted in between 1.3% (Compactness3) to 9.5% (Fractional Concavity) mean changes in feature values. Compactness2, Compactness3, Spherical Disproportion, Sphericity and Fractional Concavity were the features least affected by volume changes. Compactness1 had a 90.4% change with volume, which was greater than the change between the least and most spiculated models. This is the first methodological study that directly demonstrates the relationship of tumor spiculatedness with radiomic shape features, that also produced 3D tumor models, which may serve as reference phantoms for future radiomic studies. Surface Area, Surface-to-volume, and Spherical Disproportion had direct relationships with spiculatedness while the three formulas for Compactness, Sphericity and Fractional Concavity had inverse relationships. The features Compactness2, Compactness3, Spherical Disproportion, and Sphericity should be prioritized as these have minimal variations with volume changes, slice thickness and resampling.