Diffusible iodine‐based contrast‐enhanced computed tomography (diceCT): an emerging tool for rapid, high‐resolution, 3‐D imaging of metazoan soft tissues

Abstract

Morphologists have historically had to rely on destructive procedures to visualize the three‐dimensional (3‐D) anatomy of animals. More recently, however, non‐destructive techniques have come to the forefront. These include X‐ray computed tomography (CT), which has been used most commonly to examine the mineralized, hard‐tissue anatomy of living and fossil metazoans. One relatively new and potentially transformative aspect of current CT‐based research is the use of chemical agents to render visible, and differentiate between, soft‐tissue structures in X‐ray images. Specifically, iodine has emerged as one of the most widely used of these contrast agents among animal morphologists due to its ease of handling, cost effectiveness, and differential affinities for major types of soft tissues. The rapid adoption of iodine‐based contrast agents has resulted in a proliferation of distinct specimen preparations and scanning parameter choices, as well as an increasing variety of imaging hardware and software preferences. Here we provide a critical review of the recent contributions to iodine‐based, contrast‐enhanced CT research to enable researchers just beginning to employ contrast enhancement to make sense of this complex new landscape of methodologies. We provide a detailed summary of recent case studies, assess factors that govern success at each step of the specimen storage, preparation, and imaging processes, and make recommendations for standardizing both techniques and reporting practices. Finally, we discuss potential cutting‐edge applications of diffusible iodine‐based contrast‐enhanced computed tomography (diceCT) and the issues that must still be overcome to facilitate the broader adoption of diceCT going forward.

Joint histology inAlligator mississippiensischallenges the identification of synovial joints in fossil archosaurs and inferences of cranial kinesis

“…New advances, including easier access to higherresolution X-ray tomography, synchrotron tomography and new contrast agents for soft tissues (e.g. DiceCT [34]) will help advance our understanding of cranial joint structure and evolution.…”

The Utility of DiceCT Imaging for High-Throughput Comparative Neuroanatomical Studies

“…Here, we have built on the guidelines presented by Gignac et al [2016] by taking an exploratory approach to optimizing diceCT for neuroanatomical visualizations across three primary methodological steps leading to successful data collection: (1) specimen preservation, (2) iodine staining, and (3) µCT imaging. We have also collated details of these steps from diceCT studies with already published neuroanatomical visualizations (31 publications in total; see online suppl.…”

“…Moreover, diceCT is particularly useful for visualizing central and peripheral nervous tissues because it allows for clear differentiation between myelinated and nonmyelinated structures [de Crespigny et al, 2008;Gignac and Kley, 2014]. This means that subtle tracts of white matter can be readily identified from surrounding gray matter within the brain [Gignac and Kley, 2014;Gignac et al, 2016] (Fig. 1-4; online suppl.…”

“…We discuss our experiences in preserving, staining, and µCT scanning more than 1,000 specimens in order to highlight the power of diceCT for capturing neuroanatomical details and the extent to which these can be rendered into 3D neuroanatomical models. Our goal is to outline how to begin using diceCT imaging for creating rich datasets as a neuroanatomy-specific supplement to the more generalized review provided by Gignac et al [2016]. We do not anticipate that diceCT will replace standard histological approaches or 3D imaging modalities that have already become well-established methods throughout the neuroscience community.…”

“…In 2015, various successful protocols for iodine-enhanced µCT imaging were formalized as "diceCT" by the Austin Working Group . To date, diceCT has been applied successfully to at least 12 classes of metazoans and has permitted the visualization of whole bodies and more restricted regions of interest across a 10,000-fold range in specimen sizes [see review in Gignac et al, 2016].…”