MR tomographic evaluation of the effectiveness of neoadjuvant chemotherapy for breast cancer based on pharmacokinetic numerical analysis of tumor uptake of paramagnetic contrast in intravenous contrast enhancement
Background . In clinical practice, MRI pathophysiological and pharmacokinetic models with calculations of contrast transport indicators are unacceptably little used. Aim of the study . To propose a pharmacokinetic technique for the quantitative assessment of primary tumors and metastases, the effectiveness of breast cancer chemotherapy (BC), from dynamic contrast enhancement MRI. Material and methods . 18 patients were included who underwent neoadjuvant chemotherapy (NACHT) in four cycles for breast cancer T1-3N0-1M0, followed by radical surgical removal of the tumor. According to the results of a three — year follow-up, patients with a relapse — free course (n = 11) formed group 1, and seven patients with detected metastatic lesions (3 in the liver, 2 in the lungs, 2 in the brain) — group 2. For the initial 120–180 s of MRI with contrast after the injection of a paramagnetic, the simplification is valid for concentrations in tumor and blood and for tranfer coefficient: d{СОПУХОЛЬ(t)} / dt = ККр-Оп * СКРОВЬ (t) , from which it is obvious: ККр-Оп = (СОПУХОЛЬ(Т)) / (∫CКРОВЬ(t) dt), which was used in all calculations of the contrast transfer constant. Gadobutrol contrast is 0.1M/10 kg of body weight, TR = 5.5–6 ms, TE = 2.5 ms. Results . If, after the first cycle of NACHT, the ККр-Оп of the primary breast cancer is < 0.22 ml/min/g of tissue, the probability of subsequent relapse-free course = 0.78. Similarly, a decrease in the KCr-Op Ккр-Оп of the sentinel lymph node after the first cycle of NAHT < 0.08 ml/min/g of tissue with a probability of 0.75 predicts a relapse-free course. Conclusion. The proposed method for calculating the ККр-Оп transfer coefficient allows obtaining additional diagnostic and prognostic information in patients with local and locally advanced forms of breast cancer.
Authors
- W. Yu. Ussov (ORCID: https://orcid.org/0000-0001-7978-5514)
- А. Л. Чернышова (ORCID: https://orcid.org/0000-0002-8194-2811)
- Zh. Zh. Anashbaev (ORCID: https://orcid.org/0000-0003-3169-0326)
- V. Yu. Babikov (ORCID: https://orcid.org/0000-0002-9175-0290)
- A. М. Chernyavskiy (ORCID: https://orcid.org/0000-0001-9818-8678)
- N. V. Denisova (ORCID: https://orcid.org/0000-0001-9374-1753)
- Н. Никитин (ORCID: https://orcid.org/0000-0001-5643-9109)
- Е. Кобелев (ORCID: https://orcid.org/0000-0002-5901-2271)
- С. М. Минин (ORCID: https://orcid.org/0000-0001-6626-6408)
- N. A. Tarabanovskaya (ORCID: https://orcid.org/0000-0003-1630-4466)
- L. V. Bashkirov (ORCID: https://orcid.org/0000-0002-1042-1947)
- E. N. Nogina
- I. A. Kosarev
Institutions
- Russian Academy of Sciences (RU)
- Novosibirsk State University (RU)
- Tomsk National Research Medical Center (RU)
- Institute of Theoretical and Applied Mechanics (RU)
- Meshalkin National Medical Research Center (RU)
- Tomsk Cancer Research Institute (RU)
- Institute of Pharmacology (CZ)
Publication Details
- Journal
- Translational Medicine
- Published
- 2024-11-10
- DOI
- https://doi.org/10.18705/2311-4495-2024-11-5-428-444
- Primary Topic
- MRI in cancer diagnosis
- Type
- article
- Field-Weighted Citation Impact
- 0.00