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bioRxiv · 10.1101/823245

The impact of respiratory gating on improving volume measurement of murine lung tumors in micro-CT imaging

Abstract

Small animal imaging has become essential in evaluating new cancer therapies as they are translated from the preclinical to clinical domain. However, preclinical imaging faces unique challenges that emphasize the gap between mouse and man. One example is the difference in breathing patterns and breath-holding ability, which can dramatically affect tumor burden assessment in lung tissue. As part of a co-clinical trial studying immunotherapy and radiotherapy in sarcomas, we are using micro-CT of the lungs to detect and measure metastases as a metric of disease progression. To effectively utilize metastatic disease detection as a metric of progression, we have addressed the impact of respiratory gating during micro-CT acquisition on improving lung tumor detection and volume quantitation. Accuracy and precision of lung tumor measurements with and without respiratory gating were studied by performing experiments with in vivo images, simulations, and a pocket phantom. When performing test-retest studies in vivo, the variance in volume calculations was 5.9% in gated images and 15.8% in non-gated images, compared to 2.9% in post-mortem images. Sensitivity of detection was examined in images with simulated tumors, demonstrating that reliable sensitivity (true positive rate (TPR) [≥] 90%) was achievable down to 1.0 mm3 lesions with respiratory gating, but was limited to [≥] 8.0 mm3 in non-gated images. Finally, a clinically-inspired \"pocket phantom\" was used during in vivo mouse scanning to aid in refining and assessing the gating protocols. Application of respiratory gating techniques reduced variance of repeated volume measurements and significantly improved the accuracy of tumor volume quantitation in vivo.

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BibTeXRIS

Blocker, S. J., Holbrook, M. D., Mowery, Y. M., Sullivan, D. C., Badea, C.. 2019-10-29. The impact of respiratory gating on improving volume measurement of murine lung tumors in micro-CT imaging. https://doi.org/10.1101/823245

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