Dosimetric Evaluation of Cardiac Structures on Left Breast Cancer Radiotherapy: Impact of Movement, Dose Calculation Algorithm and Treatment Technique
Bibliographic record
Abstract
Background: Breast cancer is the most frequently diagnosed and leading cause of cancer-related deaths among females. The treatment of breast cancer with radiotherapy, albeit effective, has been shown to be toxic to the heart, resulting in an elevated risk of cardiovascular disease and associated fatalities. Methods: In this study, we evaluated the impact of respiratory movement, treatment plans and dose calculation algorithm on the dose delivered to the heart and its substructures during left breast radiotherapy over a cohort of 10 patients. We did this through three image sets, four different treatment plans and the employment of three algorithms on the same treatment plan. The dose parameters were then employed to estimate the impact on the 9-year excess cumulative risk for acute cardiac events by applying the model proposed by Darby. Results: The left ventricle was the structure most irradiated. Due to the lack of four-dimensional computed tomography (4DCT), we used a set of images called phase-average CT that correspond to the average of the images from the respiratory cycle (exhale, exhale 50%, inhale, inhale 50%). When considering these images, nearly 10% of the heart received more than 5 Gy and doses were on average 27% higher when compared to free breathing images. Deep inspiration breath-hold plans reduced cardiac dose for nine out of 10 patients and reduced mean heart dose in about 50% when compared to reference plans. We also found that the implementation of deep inspiration breath-hold would reduce the relative lifetime risk of ischemic heart disease to 10%, in comparison to 21% from the reference plan. Conclusion: Our findings illustrate the importance of a more accurate determination of the dose and its consideration in cardiologists' consultation, a factor often overlooked during clinical examination. They also motivate the evaluation of the dose to the heart substructures to derive new heart dose constraints, and a more mindful and individualized clinical practice depending on the treatment employed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".