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Biomedical subjects

Ana Vega

Publications and source records attributed to Ana Vega.

2 recordsLinked to original sources

Updated ENIGMA recommendations for reporting germline variants in cancer susceptibility genes and their translation into twenty languages.

Genetic testing for cancer susceptibility underpins precision cancer prevention and care. Gaps in the healthcare providers' genetic literacy and an ambiguous lexicon for variant description may hinder proper delivery and clinical application of consistently trustworthy test results. The Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) international consortium supports controlled terminology and recommends a framework for reporting germline variants in cancer susceptibility genes, using breast cancer as an exemplar. Moving forward towards terminological coherence across disciplines and borders, the ENIGMA Clinical Working Group launched a multinational effort to release consortium-approved translations of the published recommendations. The herein reported Vocabulary Translation Project offered an opportunity to reappraise and align the reference text to the recent BRCA1 and BRCA2 specifications to the American College of Medical Genetics and Genomics/Association for Molecular Pathology rules by the ENIGMA Variant Curation Expert Panel and to highlight country-specific differences in breast cancer risk assessment and management. The updated recommendations and their 20 translations are now provided as easy to handle documents, covering 11 of the most widely spoken languages in the world. They will contribute to minimised erroneous inferences, more informed decision-making, improved health outcomes and equity in the use of genetic testing for cancer predisposition and in translational oncology.

Humans

Technical note: reconstructing dose distributions from manually planned electron boosts in breast radiotherapy.

PURPOSE: In breast radiotherapy, delivery of manually-calculated electron boosts limits retrospective dose-response analyses as dose distribution is unavailable. This work evaluates the feasibility of reconstructing dose distributions from manually planned electron boosts in breast-conserving radiotherapy. METHODS: Only 72 out of 198 breast cancer patients had complete stored dose distributions from sequential electron boosts in the REQUITE study. Arbitrary data from 70/72 patients were used to develop and validate dose reconstruction method. Twenty patients were used to determine optimal parameters for Monte-Carlo-based (MC) electron dose reconstruction on RayStation (v.11B-R), considering CT-calibration curve, MC-history number, andcalculation grid resolution. Remaining 50 patients were used to quantify dose reconstruction accuracy. The similarity between reconstructed and stored dose was evaluated using 3D-gamma index and dosimetric parameters extracted from breast and tumour bed contours. Dose difference location was evaluated using dose-location histogram. RESULTS: Calculation grid resolution significantly impacted electron dose distribution (p&#xa0;<&#xa0;0.01), where the finest grid (0.15&#xa0;cm) showed highest similarity to stored doses. CT-calibration curve and MC-history number had a negligible influence on dose reconstruction. Dosimetric difference between reconstructed and stored doses was&#xa0;<&#xa0;1&#xa0;Gy for breast and tumour bed. Reconstructed dose was achieved&#xa0;>&#xa0;90% gamma passing rate in the validation set. However, around 2.5&#xa0;Gy dose differences were observed at the skin and tissue interface regions. CONCLUSIONS: Retrospective electron boost dose reconstruction is feasible with acceptable accuracy, and could increase data completeness in large cohort studies. Caution is advised when assessing dose near tissue interface and further validation is needed outside the REQUITE dataset.

Electrons