Introduction: The exact location of the original tumor should be known for a targeted increase in the dose to the tumor bed after breast cancer surgery. Therefore, at our site, we perform CT examinations of patients in the radiation position before breast cancer surgery.
Methods: Preoperative native CT scans were performed in the patients in the planning position for radiotherapy; these data were fused with standard planning CT for boost irradiation. We evaluated whether the tumor was accurately identifiable in preoperative CT scans. We also contoured one irradiation volume in the standard planning CT scans and the other in the fusion CT scans with preoperative examination, and compared these volumes.
Results: Out of the total number of 554 patients, we were able to identify the exact location of the breast tumor in 463 cases (83.6 %). In a group of 50 randomly selected patients, the clinical target volume for the boost dose to the postlumpectomy cavity was changed in 20 patients (40%) - decreased in 9 cases (18%) and increased in 11 cases (22%).
Conclusion: As shown by the results of our study, preoperative CT in the planning position can be used in patients with confirmed breast cancer. This method allows us to more accurately locate the tumor bed and thus more accurately draw the target volume for boost irradiation. We confirmed that preoperative CT had an impact on the size of the target volume.
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http://dx.doi.org/10.33699/PIS.2021.100.6.278-284 | DOI Listing |
Pharm Dev Technol
January 2025
Department of Pharmacy, School of Chemistry and Chemical Engineering, Liaoning Normal University, Dalian 116029, China.
In this paper, the pH-sensitive targeting functional material NGR-poly(2-ethyl-2-oxazoline)-cholesteryl methyl carbonate (NGR-PEtOz-CHMC, NPC) modified quercetin (QUE) liposomes (NPC-QUE-L) was constructed. The structure of NPC was confirmed by infrared spectroscopy (IR) and nuclear magnetic resonance hydrogen spectrum (H-NMR). Pharmacokinetic results showed that the accumulation of QUE in plasma of the NPC-QUE-L group was 1.
View Article and Find Full Text PDFJ Med Econ
January 2025
UNESCO-TWAS, The World Academy of Sciences, Trieste, Italy.
Aim: Dynamic cancer control is a current health system priority, yet methods for achieving it are lacking. This study aims to review the application of system dynamics modeling (SDM) on cancer control and evaluate the research quality.
Methods: Articles were searched in PubMed, Web of Science, and Scopus from the inception of the study to November 15th, 2023.
Int J Surg
January 2025
Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China.
Detection of biomarkers of breast cancer incurs additional costs and tissue burden. We propose a deep learning-based algorithm (BBMIL) to predict classical biomarkers, immunotherapy-associated gene signatures, and prognosis-associated subtypes directly from hematoxylin and eosin stained histopathology images. BBMIL showed the best performance among comparative algorithms on the prediction of classical biomarkers, immunotherapy related gene signatures, and subtypes.
View Article and Find Full Text PDFInt J Gen Med
December 2024
Department of Thyroid and Breast Surgery, Quzhou People's Hospital, Quzhou, 324000, People's Republic of China.
Objective: This study aims to demonstrate the impact of sarcopenia on the prognosis of early breast cancer and its role in early multimodal intervention.
Methods: The clinical data of patients (n=285) subjected to chemotherapy for early-stage breast cancer diagnosed pathologically between January 1, 2016, and December 31, 2020, in our hospital were retrospectively analyzed. Accordingly, the recruited subjects were divided into sarcopenia (n=85) and non-sarcopenia (n=200) groups according to CT diagnosis correlating with single-factor and multifactorial logistic regression analyses.
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