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Record W2333542667 · doi:10.1158/1538-7445.am2012-4338

Abstract 4338: Monitoring radiation response in tumor vasculature using intravital photoacoustic imaging in a murine window chamber model <i>in vivo</i>

2012· article· en· W2333542667 on OpenAlexaff
John Sun, Azusa Maeda, Shawn Stapleton, Yonghong Chen, Andrew Heinmiller, Dave Bate, Theresa McGrath, Andrew Needles, Catherine Theodoropoulos, Ralph S. DaCosta

Bibliographic record

VenueCancer Research · 2012
Typearticle
Languageen
FieldEngineering
TopicPhotoacoustic and Ultrasonic Imaging
Canadian institutionsUniversity of TorontoFujiFilm VisualSonics (Canada)University Health NetworkIllumisonics (Canada)
Fundersnot available
KeywordsIn vivoBiomedical engineeringPreclinical imagingVascularityTumor hypoxiaMaterials scienceIntravital microscopyUltrasoundEx vivoOxygen saturationImaging phantomNuclear medicineChemistryPathologyRadiation therapyMedicineOxygenSurgeryRadiologyBiology

Abstract

fetched live from OpenAlex

Abstract VisualSonics has recently developed a preclinical photoacoustic (PA) imaging system called the VevoLAZR that combines the sensitivity of optical imaging and the high resolution of micro-ultrasound. The system incorporates a 40 MHz (centre frequency) ultrasound transducer linear array probe (LZ550) and a tuneable 680-970 nm nanosecond pulsed-laser. We used this system to study in vivo changes in tumor oxygen saturation and haemoglobin density caused by exposure to radiation therapy (RT). For this, DsRed-Me180 human cervical tumors were grown in a nude mouse dorsal skinfold window chamber model until they reached 2.5 mm in diameter. Specifically, we investigated the system's sensitivity and dynamic range to measure relative changes in oxygen saturation in tumor and surrounding healthy tissues 10 days after treatment. Tumors (∼2.5 mm diameter) were focally irradiated with a single dose of 30 Gy using a small animal microirradiator (XRAD225, Precision XRay Inc., North Branford, CT). To measure the dynamic range and stability of our setup for measuring oxygen saturation in vivo, we altered the anesthetised animal's inhaled oxygen from 100% to 7% for 1 min during PA imaging. This test showed that blood oxygen saturation in the healthy dorsal skinfold tissue decreased from 82% to 8% and confirmed the linearity of the measurement technique. Furthermore, we compared vascular morphology obtained by photoacoustic imaging and intravital fluorescent microscopy using FITC-Dextran (2 MDa, injected 20 mins prior). This comparison showed good correlation and confirms that PA imaging can provide important structural information of vascularity. Photoacoustic imaging was performed before and 10 days after irradiation to assess changes in tumour volume, relative blood oxygen saturation, relative tissue oxygen saturation, and relative hemoglobin density. Ten days after irradiation, PA imaging showed that the tumour volume increased from 5.7 to 14.2 mm3, relative blood oxygen saturation decreased from 75.3 to 48.2%, relative tissue oxygen saturation decreased from 40.7 to 0.1%, and hemoglobin density decreased from 18457 to 3253 a.u. These data illustrate the capability of PA imaging to simultaneously measure multiple radiobiological response metrics from a single imaging scan. Pilot results demonstrate: i) the compatibility of the VisualSonics small animal VevoLAZR photoacoustic imaging system with intravital murine tumor models, ii) the sensitivity of the system to detect RT-induced changes in tumor vascular oxygen saturation non-invasively, in real time and in vivo, and iii) a new preclinical application of PA imaging for longitudinal monitoring of tumor response to RT in vivo. 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 4338. doi:1538-7445.AM2012-4338

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.033
GPT teacher head0.337
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2012
Admission routes1
Has abstractyes

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