High and low frequency subharmonic imaging of angiogenesis in a murine breast cancer model
Bibliographic record
Abstract
Angiogenesis is an important physiological process where new blood vessels are formed from already existing blood vessels unlike vasculogenesis, which involves formation of blood vessels de novo. It plays an essential role in growth of tumors and development of metastasis. This process involves activation, migration and proliferation of endothelial cells and is regulated by specific growth factors. Ultrasound is an ideal imaging modality that enables scanning in real-time with the help of ultrasound contrast agents. When the gas-filled, shell stabilized microbubbles of ultrasound contrast agents are insonified by an ultrasound beam, they exhibit nonlinear scattering and emit harmonic components of the fundamental signal in the received echoes. Utilizing the subharmonic component emitted at half of the fundamental frequency (f0/2) provides an improved contrast to tissue ratio for ultrasound imaging of tumor angiogenesis. This project compares quantifiable measures of tumor vascularity obtained from contrast-enhanced high frequency (HF) and low frequency (LF) subharmonic ultrasound imaging (SHI) to 3 immunohistochemical markers of angiogenesis in a murine breast cancer model. Nineteen athymic, nude, female rats were implanted with 5x106 breast cancer cells (MDA-MB-231) in the mammary fat pad. The contrast agent Definity (Lantheus Medical Imaging, N Billerica, MA) was injected in a tail vein (dose: 200 [mu]l/kg) and low frequency pulse-inversion SHI was performed with a modified Sonix RP scanner (Ultrasonix Imaging, Richmond, BC, Canada) using a L9-4 linear array (transmitting at 8 MHz and receiving at 4 MHz in SHI mode) followed by high frequency imaging with a micro-ultrasound scanner, Vevo 2100 (Visual Sonics, Toronto, ON, Canada) using a MS-250 linear array transducer transmitting and receiving at 24 MHz in Nonlinear Contrast mode. The radiofrequency image data was filtered using an IIR Butterworth bandpass filter (11-13MHz) to isolate the subharmonic signal (from linear tissue and bubble signals). After the experiments, specimens were stained for endothelial cells (CD31), vascular endothelial growth factor (VEGF) and cyclooxygenase-2 (COX-2). Fractional tumor vascularity was calculated as contrast enhanced pixels over tumor area for SHI digital images, while the relative area stained over the tumor was calculated from specimens. Results were compared on per ROI basis using linear regression analysis. Out of 19 rats, 16 showed tumor growth (84%) and 11 of them were successfully imaged. HF SHI demonstrated better resolution but weaker signals than LF SHI. The strongest correlation determined by linear regression in this breast cancer model was between HF SHI and percent area stained with VEGF (r = 0.38; p=0.034), while there was a trend towards significance for HF SHI vs. CD31 and for LF SHI vs. COX-2 (r~0.31; 0.07
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".