End-to-end framework for automated collection of large multicentre radiotherapy datasets demonstrated in a Danish Breast Cancer Group cohort.

Large Digital Imaging and Communications in Medicine (DICOM) datasets are key to support research and the development of machine learning technology in radiotherapy (RT). However, the tools for multi-centre data collection, curation and standardisation are not readily available. Automated batch DICOM export solutions were demonstrated for a multicentre setup. A Python solution, Collaborative DICOM analysis for RT (CORDIAL-RT) was developed for curation, standardisation, and analysis of the collected data. The setup was demonstrated in the DBCG RT-Nation study, where 86% (n = 7748) of treatments in the inclusion period were collected and quality assured, supporting the applicability of the end-to-end framework.

Interfractional dose accumulation for MR-guided liver SBRT: Variation among algorithms is highly patient- and fraction-dependent.

BACKGROUND AND PURPOSE: Daily plan adaptations could take the dose delivered in previous fractions into account. Due to high dose delivered per fraction, low number of fractions, steep dose gradients, and large interfractional organ deformations, this might be particularly important for liver SBRT. This study investigates inter-algorithm variation of interfractional dose accumulation for MR-guided liver SBRT. MATERIALS AND METHODS: We assessed 27 consecutive MR-guided liver SBRT treatments of 67.5 Gy in three (n = 15) or 50 Gy in five fractions (n = 12), both prescribed to the GTV. We calculated fraction doses on daily patient anatomy, warped these doses to the simulation MRI using seven different algorithms, and accumulated the warped doses. Thus, we obtained differences in planned doses and warped or accumulated doses for each algorithm. This enabled us to calculate the inter-algorithm variations in warped doses per fraction and in accumulated doses per treatment course. RESULTS: The four intensity-based algorithms were more consistent with planned PTV dose than affine or contour-based algorithms. The mean (range) variation of the dose difference for PTV D95% due to dose warping by these intensity-based algorithms was 10.4 percentage points (0.3 to 43.7) between fractions and 8.6 (0.3 to 24.9) between accumulated treatment doses. As seen by these ranges, the variation was very dependent on the patient and the fraction being analyzed. Nevertheless, no correlations between patient or plan characteristics on the one hand and inter-algorithm dose warping variation on the other hand was found. CONCLUSION: Inter-algorithm dose accumulation variation is highly patient- and fraction-dependent for MR-guided liver SBRT. We advise against trusting a single algorithm for dose accumulation in liver SBRT.

Quality assessment of delineation and dose planning of early breast cancer patients included in the randomized Skagen Trial 1.

BACKGROUND AND PURPOSE: To report on a Quality assessment (QA) of Skagen Trial 1, exploring hypofractionation for breast cancer patients with indication for regional nodal radiotherapy. MATERIAL AND METHODS: Deviations from protocol regarding target volume delineations and dose parameters (Dmin, Dmax, D98%, D95% and D2%) from randomly selected dose plans were assessed. Target volume delineation according to ESTRO guidelines was obtained through atlas based automated segmentation and centrally approved as gold standard (GS). Dice similarity scores (DSC) with original delineations were measured. Dose parameters measured in the two delineations were reported to assess their dosimetric outcome. RESULTS: Assessment included 88 plans from 12 centres in 4 countries. DSC showed high agreement in contouring, 99% and 96% of the patients had a complete delineation of target volumes and organs at risk. No deviations in the dosimetric outcome were found in 76% of the patients, 82% and 95% of the patients had successful coverage of breast/chestwall and CTVn_L2-4-interpectoral. Dosimetric outcomes of original delineation and GS were comparable. CONCLUSIONS: QA showed high protocol compliance and adequate dose coverage in most patients. Inter-observer variability in contouring was low. Dose parameters were in harmony with protocol regardless original or GS segmentation.

Two barriers or not? Dynamic force spectroscopy on the integrin α7ß1 invasin complex.

Dynamic force spectroscopy was used to test force-induced dissociation of the complex between the integrin α7ß1 and the bacterial protein invasin. Both proteins were used in truncated forms comprising the respective binding sites. Using the biomembrane force-probe, the bond system was exposed to 14 different loading rates ranging from 18 pN/s to 5.3 nN/s. At each rate, bond rupture spectra were collected. Median forces ranged from 8 to 72 pN. These showed two linear regimes when plotted against the logarithm of the force-loading rate. However, a statistical analysis of the full rupture force spectra including the detection limits of the setup showed that all measured data are well described by dissociation over a single barrier.

Cholesterol and sphingomyelin drive ligand-independent T-cell antigen receptor nanoclustering.

The T-cell antigen receptor (TCR) exists in monomeric and nanoclustered forms independently of antigen binding. Although the clustering is involved in the regulation of T-cell sensitivity, it is unknown how the TCR nanoclusters form. We show that cholesterol is required for TCR nanoclustering in T cells and that this clustering enhances the avidity but not the affinity of the TCR-antigen interaction. Investigating the mechanism of the nanoclustering, we found that radioactive photocholesterol specifically binds to the TCRß chain in vivo. In order to reduce the complexity of cellular membranes, we used a synthetic biology approach and reconstituted the TCR in liposomes of defined lipid composition. Both cholesterol and sphingomyelin were required for the formation of TCR dimers in phosphatidylcholine-containing large unilamellar vesicles. Further, the TCR was localized in the liquid disordered phase in giant unilamellar vesicles. We propose a model in which cholesterol and sphingomyelin binding to the TCRß chain causes TCR dimerization. The lipid-induced TCR nanoclustering enhances the avidity to antigen and thus might be involved in enhanced sensitivity of memory compared with naive T cells. Our work contributes to the understanding of the function of specific nonannular lipid-membrane protein interactions.

Mechanically enforced bond dissociation reports synergistic influence of Mn2+ and Mg2+ on the interaction between integrin α7ß1 and invasin.

Integrins require the divalent ions magnesium and manganese for ligand recognition. Here we mechanically enforced bond dissociation to explore the influence of these ions on the mechanical strength of the specific bond between α(7) ß(1) integrin and its pathologically relevant ligand invasin. Upon addition of these cations to the measurement buffer, we observe a pronounced increase in the force necessary to separate integrin and invasin coated beads. Both ions were found to work synergistically. With free invasin in the measurement buffer we furthermore observe that competitive blocking of binding sites overrides the increase in binding strength of individual beads. We show that this is due to a very strong dependence of bond affinity on divalent ions. Our study illustrates the importance of divalent ions for the regulation of force transmission by integrin ligand bonds on the molecular level.