Abstract 4235: Functional assessment of mouse tumor microenvironment following sunitinib treatment using an integrated micro-ultrasound and photoacoustic system
Bibliographic record
Abstract
Abstract The development of novel cancer therapies could benefit significantly from the introduction of new functional imaging methods that allow non-invasive longitudinal assessment of tumor response to therapy. We have developed and tested a new instrument in which photoacoustic (PA) imaging is combined with co-registered micro-ultrasound (µUS). The new system allows tumor oxygenation and hemoglobin data derived from PA imaging to be combined with blood volume and perfusion data derived from contrast µUS and be observed during the course of therapy. Using this system, we assessed changes in the tumor microenvironment following treatment with an anti-angiogenic drug, sunitinib (Pfizer, USA). Human metastatic breast cancer cells (231/LM2-4) were surgically implanted in the mammary fat pads of 4 control and 7 treated female nude SCID mice and were allowed to grow for 10 days prior to initiation of experimental treatment, which consisted of either 4 consecutive daily gavage doses of 120mg/kg sunitinib, or control vehicle. Imaging was performed, using the VevoLAZR (VisualSonics, Canada) integrated µUS/PA system, prior to and following treatment. Tumor volume was quantified with 3D ultrasound imaging using a 40MHz frequency probe. Indices of relative blood volume and perfusion were quantified with non-linear contrast imaging using a 21MHz probe during a 50uL (2x109/mL) intravenous bolus injection of microbubbles (MicroMarker, VisualSonics). Blood oxygen saturation, relative tissue oxygen saturation, and hemoglobin concentration were measured with photoacoustic imaging using an integrated photoacoustic probe with 21MHz ultrasound frequency and tuneable 680-970nm laser optics. Following treatment, we observed significant (p<.05) suppression in tumor growth (-35%) decrease in blood volume (-91%), perfusion (-86%), relative tissue oxygen saturation (-60%), and hemoglobin concentration (-40%) in the sunitinib- relative to control-treated mice. When comparing pre- and post-treatment within the control group, there were increases in tumor volume (+120%), however, interestingly, there were also decreases in perfusion (-52%), blood volume (-22%) and relative tissue oxygen saturation (-31%). When comparing contrast µUS and PA data, there was a strong, moderate, and weaker correlations between relative tissue oxygen saturation and perfusion (R2 = 0.722), relative tissue oxygenation and blood volume (R2 = 0.576), and blood volume and hemoglobin concentration (R2 = 0.294) respectively. This study demonstrates the ability of an integrated PA and µUS imaging system to provide quantitative functional assessment of a preclinical breast cancer model following treatment with sunitinib. The degree to which quantitative correlates such as these are indicative of useful therapeutic response and of prognostic value remain to be investigated. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4235. doi:1538-7445.AM2012-4235
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".