RESUMEN
Objective: To explore the advantages of dosimetry and the treatment efficiency of tangent-arc technology in deep inspiration breath-hold radiotherapy for breast cancer. Methods: Forty patients with left-sided breast cancer who were treated in our hospital from May 2020 to June 2021 were randomly selected and divided into two groups. The first group's plan was a continuous semi-arc that started at 145° ( ± 5°) and stopped at 325° ( ± 5°). The other group's plan, defined as the tangent-arc plan, had two arcs: the first arc started at 145° ( ± 5°) and stopped at 85° ( ± 5°), and the second arc started at 25° ( ± 5°) and stopped at 325° ( ± 5°). We compared the target dose, dose in organs at risk (OARs), and treatment time between the two groups. Results: The target dose was similar between the continuous semiarc and tangent-arc groups. The V5 of the right lung was significantly different between the two groups (Dif 5.52, 95% confidence interval 1.92-9.13, t=3.10, P=0.004), with the patients in the continuous semi-arc and tangent-arc groups having lung V5 values of (9.16 ± 1.62)%, and (3.64 ± 0.73)%, respectively. The maximum dose to the spinal cord was (1835.88 ± 222.17) cGy in the continuous semi-arc group and (599.42 ± 153.91) cGy in the tangent-arc group, yielding a significant difference between the two groups (Dif 1236.46, 95% confidence interval 689.32-1783.6, t=4.57, P<0.001). The treatment times was (311.70 ± 60.45) s for patients in the continuous semi-arc group and (254.66 ± 40.73) s for patients in the tangent-arc group, and there was a significant difference in the mean number of treatment times between the two groups (Dif 57.04, 95% confidence interval 24.05-90.03, t=3.5, P=0.001). Conclusion: Both the continuous semi-arc and tangent-arc plans met the clinical prescription dose requirements. The OARs received less radiation with the tangent-arc plan than the continuous semi-arc plan, especially for the lung (measured as V5) and the spinal cord (measured as the maximum dose). Tangent-arc plan took significantly less time than the continuous semi-arc, which can greatly improve treatment efficiency. Therefore, tangent-arc plans are superior continuous semi-arc plans for all cases.
RESUMEN
Objective: In individuals with stage IB1-IIA2 cervical cancer (CC) who received postoperative radiotherapy ± chemotherapy (PORT/CRT), the interaction between sarcopenia and malnutrition remains elusive, let alone employing a nomogram model based on radiomic features of psoas extracted at the level of the third lumbar vertebra (L3). This study was set to develop a radiomics-based nomogram model to predict malnutrition as per the Patient-Generated Subjective Global Assessment (PG-SGA) for individuals with CC. Methods: In total, 120 individuals with CC underwent computed tomography (CT) scans before PORT/CRT. The radiomic features of psoas at L3 were obtained from non-enhanced CT images. Identification of the optimal features and construction of the rad-score formula were conducted utilizing the least absolute shrinkage and selection operator (LASSO) logistic regression to predict malnutrition in the training dataset (radiomic model). Identification of the major clinical factors in the clinical model was performed by means of binary logistic regression analysis. The radiomics-based nomogram was further developed by integrating radiomic signatures and clinical risk factors (combined model). The receiver operating characteristic (ROC) curves and decision curves analysis (DCA) were employed for the evaluation and comparison of the three models in terms of their predictive performance. Results: Twelve radiomic features in total were chosen, and the rad-score was determined with the help of the non-zero coefficient from LASSO regression. Multivariate analysis revealed that besides rad-score, age and Eastern Cooperative Oncology Group performance status could independently predict malnutrition. As per the data of this analysis, a nomogram prediction model was constructed. The area under the ROC curves (AUC) values of the radiomic and clinical models were 0.778 and 0.847 for the training and 0.776 and 0.776 for the validation sets, respectively. An increase in the AUC was observed up to 0.972 and 0.805 in the training and validation sets, respectively, in the combined model. DCA also confirmed the clinical benefit of the combined model. Conclusion: This radiomics-based nomogram model depicted potential for use as a marker for predicting malnutrition in stage IB1-IIA2 CC patients who underwent PORT/CRT and required further investigation with a large sample size.