Kenneth M Tichauer, Priscilla Machado, Ji-Bin Liu, A S Chalmika Sarathchandra, Maria Stanczak, Walter K Kraft, Flemming Forsberg
{"title":"乳腺淋巴造影中巨噬细胞对 Sonazoid 的摄取率在健康对照组中高度一致。","authors":"Kenneth M Tichauer, Priscilla Machado, Ji-Bin Liu, A S Chalmika Sarathchandra, Maria Stanczak, Walter K Kraft, Flemming Forsberg","doi":"10.1088/1361-6560/ad7f1c","DOIUrl":null,"url":null,"abstract":"<p><p>Subcutaneous microbubble administration in connection with contrast enhanced ultrasound (CEUS) imaging is showing promise as a noninvasive and sensitive way to detect tumor draining sentinel lymph nodes (SLNs) in patients with breast cancer. Moreover, there is potential to harness the results from these approaches to directly estimate cancer burden, since some microbubble formulas, such as the Sonazoid used in this study, are rapidly phagocytosed by macrophages, and the macrophage concentration in a lymph node is inversely related to the cancer burden. This work presents a mathematical model that can approximate a rate constant governing macrophage uptake of Sonazoid,<i>k<sub>i</sub></i>, given dynamic CEUS Sonazoid imaging data. Twelve healthy women were injected with 1.0 ml of Sonazoid in an upper-outer quadrant of one of their breasts and SLNs were imaged in each patient immediately after injection, and then at 0.25, 0.5, 1, 2, 4, 6, and 24 h after injection. The mathematical model developed was fit to the dynamic CEUS data from each subject resulting in a mean ± sd of 0.006 ± 0.005 h<sup>-1</sup>and 0.4 ± 0.1 h<sup>-1</sup>for relative lymphatic flow (<i>EF<sub>l</sub></i>) and<i>k<sub>i</sub></i>, respectively. Furthermore, the roughly 25% sd of the<i>k<sub>i</sub></i>measurement was similar to the sd that would be expected from realistic noise simulations for a stable 0.4 h<sup>-1</sup>value of<i>k<sub>i</sub></i>, suggesting that macrophage concentration is highly consistent among cancer-free SLNs. These results, along with the significantly smaller variance in<i>k<sub>i</sub></i>measurement observed compared to relative lymphatic flow suggest that<i>k<sub>i</sub></i>may be a more precise and promising approach of estimating macrophage abundance, and inversely cancer burden. Future studies comparing tumor-free to tumor-bearing nodes are planned to verify this hypothesis.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":null,"pages":null},"PeriodicalIF":3.3000,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Macrophage uptake rate of Sonazoid in breast lymphosonography is highly conserved in healthy controls.\",\"authors\":\"Kenneth M Tichauer, Priscilla Machado, Ji-Bin Liu, A S Chalmika Sarathchandra, Maria Stanczak, Walter K Kraft, Flemming Forsberg\",\"doi\":\"10.1088/1361-6560/ad7f1c\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Subcutaneous microbubble administration in connection with contrast enhanced ultrasound (CEUS) imaging is showing promise as a noninvasive and sensitive way to detect tumor draining sentinel lymph nodes (SLNs) in patients with breast cancer. Moreover, there is potential to harness the results from these approaches to directly estimate cancer burden, since some microbubble formulas, such as the Sonazoid used in this study, are rapidly phagocytosed by macrophages, and the macrophage concentration in a lymph node is inversely related to the cancer burden. This work presents a mathematical model that can approximate a rate constant governing macrophage uptake of Sonazoid,<i>k<sub>i</sub></i>, given dynamic CEUS Sonazoid imaging data. Twelve healthy women were injected with 1.0 ml of Sonazoid in an upper-outer quadrant of one of their breasts and SLNs were imaged in each patient immediately after injection, and then at 0.25, 0.5, 1, 2, 4, 6, and 24 h after injection. The mathematical model developed was fit to the dynamic CEUS data from each subject resulting in a mean ± sd of 0.006 ± 0.005 h<sup>-1</sup>and 0.4 ± 0.1 h<sup>-1</sup>for relative lymphatic flow (<i>EF<sub>l</sub></i>) and<i>k<sub>i</sub></i>, respectively. Furthermore, the roughly 25% sd of the<i>k<sub>i</sub></i>measurement was similar to the sd that would be expected from realistic noise simulations for a stable 0.4 h<sup>-1</sup>value of<i>k<sub>i</sub></i>, suggesting that macrophage concentration is highly consistent among cancer-free SLNs. These results, along with the significantly smaller variance in<i>k<sub>i</sub></i>measurement observed compared to relative lymphatic flow suggest that<i>k<sub>i</sub></i>may be a more precise and promising approach of estimating macrophage abundance, and inversely cancer burden. Future studies comparing tumor-free to tumor-bearing nodes are planned to verify this hypothesis.</p>\",\"PeriodicalId\":20185,\"journal\":{\"name\":\"Physics in medicine and biology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2024-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Physics in medicine and biology\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1088/1361-6560/ad7f1c\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, BIOMEDICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physics in medicine and biology","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1088/1361-6560/ad7f1c","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
Macrophage uptake rate of Sonazoid in breast lymphosonography is highly conserved in healthy controls.
Subcutaneous microbubble administration in connection with contrast enhanced ultrasound (CEUS) imaging is showing promise as a noninvasive and sensitive way to detect tumor draining sentinel lymph nodes (SLNs) in patients with breast cancer. Moreover, there is potential to harness the results from these approaches to directly estimate cancer burden, since some microbubble formulas, such as the Sonazoid used in this study, are rapidly phagocytosed by macrophages, and the macrophage concentration in a lymph node is inversely related to the cancer burden. This work presents a mathematical model that can approximate a rate constant governing macrophage uptake of Sonazoid,ki, given dynamic CEUS Sonazoid imaging data. Twelve healthy women were injected with 1.0 ml of Sonazoid in an upper-outer quadrant of one of their breasts and SLNs were imaged in each patient immediately after injection, and then at 0.25, 0.5, 1, 2, 4, 6, and 24 h after injection. The mathematical model developed was fit to the dynamic CEUS data from each subject resulting in a mean ± sd of 0.006 ± 0.005 h-1and 0.4 ± 0.1 h-1for relative lymphatic flow (EFl) andki, respectively. Furthermore, the roughly 25% sd of thekimeasurement was similar to the sd that would be expected from realistic noise simulations for a stable 0.4 h-1value ofki, suggesting that macrophage concentration is highly consistent among cancer-free SLNs. These results, along with the significantly smaller variance inkimeasurement observed compared to relative lymphatic flow suggest thatkimay be a more precise and promising approach of estimating macrophage abundance, and inversely cancer burden. Future studies comparing tumor-free to tumor-bearing nodes are planned to verify this hypothesis.
期刊介绍:
The development and application of theoretical, computational and experimental physics to medicine, physiology and biology. Topics covered are: therapy physics (including ionizing and non-ionizing radiation); biomedical imaging (e.g. x-ray, magnetic resonance, ultrasound, optical and nuclear imaging); image-guided interventions; image reconstruction and analysis (including kinetic modelling); artificial intelligence in biomedical physics and analysis; nanoparticles in imaging and therapy; radiobiology; radiation protection and patient dose monitoring; radiation dosimetry