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Developing and Evaluating the Fidelity of Patient Specific Kidney Emulating Phantoms for Image-guided Intervention Applications. | LitMetric

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Article Abstract

Patient specific organ and tissue mimicking phantoms are used routinely to develop and assess new image-guided intervention tools and techniques in laboratory settings, enabling scientists to maintain acceptable anatomical relevance, while avoiding animal studies when the developed technology is still in its infancy. Gelatin phantoms, specifically, offer a cost-effective and readily available alternative to the traditional manufacturing of anatomical phantoms, and also provide the necessary versatility to mimic various stiffness properties specific to various organs or tissues. In this study, we describe the protocol to develop patient specific anthropomorphic gelatin kidney phantoms and we also assess the faithfulness of the developed phantoms against the patient specific CT images and corresponding virtual anatomical models used to generate the phantoms. We built the gelatin phantoms by first using additive manufacturing to generate a kidney mold based on patient specific CT images, into which the gelatin was poured. We then evaluated the fidelity of the phantoms (i.e., children) against the virtual kidney model generated from the patient specific CT image (i.e., parent) by comparing it to the surface model of the mold and gelatin phantoms (i.e., children) following their CT imaging post-manufacturing using various registration metrics. Our experiments showed a 0.58 ± 0.48 mm surface-to-surface distance between the phantoms and mold models following landmark-based registration, and 0.52 ± 0.40 mm surface-to-surface distance between the phantoms and the mold model following iterative closest point (ICP) registration. These experiments confirm that the described protocol provides a reliable, fast, and cost-effective method for manufacturing faithful patient specific organ emulating gelatin phantoms and can be applied or extended to other image-guided intervention applications.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10134787PMC
http://dx.doi.org/10.1117/12.2655603DOI Listing

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