From 2D slices to a 3D model: Training students in digital microanatomy analysis techniques through a 3D printed neuron project

The reconstruction of two‐dimensional (2D) slices to three‐dimensional (3D) digital anatomical models requires technical skills and software that are becoming increasingly important to the modern anatomist, but these skills are rarely taught in undergraduate science classrooms. Furthermore, learning opportunities that allow students to simultaneously explore anatomy in both 2D and 3D space are increasingly valuable. This report describes a novel learning activity that trains students to digitally trace a serially imaged neuron from a confocal stack and to model that neuron in 3D space for 3D printing. By engaging students in the production of a 3D digital model, this learning activity is designed to provide students a novel way to enhance their understanding of the content, including didactic knowledge of neuron morphology, technical research skills in image analysis, and career exploration of neuroanatomy research. Moreover, students engage with microanatomy in a way that starts in 2D but results in a 3D object they can see, touch, and keep. This discursive article presents the learning activity, including videos, instructional guides, and learning objectives designed to engage students on all six levels of Bloom's Taxonomy. Furthermore, this work is a proof of principle modeling workflow that is approachable, inexpensive, achievable, and adaptable to cell types in other organ systems. This work is designed to motivate the expansion of 3D printing technology into microanatomy and neuroanatomy education.


INTRODUC TI ON
The microanatomy of the nervous system is a complex network of cells with intricate design and cytoarchitecture.Since the work of Santiago Ramón y Cajal at the turn of the 20th century, great efforts have been made by anatomists and neuroscientists to characterize these cells and relate their complex structure to their function. 1Although remarkable, illustrations of neuronal architecture over the last century, from Cajal's prodigious drawings to modern textbook figures, typically portray 2D structure but not 3D relationships.Cellular 3D morphology is important in the teaching of microanatomy but can be particularly difficult to visualize based on 2D slices.
The development and evaluation of novel teaching tools to help students with 3D spatial reasoning continues to be an area of active research and innovation in the anatomy education literature. 2,3ysical models are a time-honored kinesthetic teaching tool among anatomy educators to help students visualize and learn spatial relationships and practice anatomical reasoning.5][6][7][8] However, the quality and translatability of these studies varies. 7,9Moreover, the cost of commercially available physical models can be prohibitive for some institutions; they are not customizable and typically have lower fidelity to "real" human anatomy.
The first step prior to creating a 3D printed anatomical model is the generation of a digital 3D object file.This is often done using imaging data from computed tomography (CT) or magnetic resonance imaging (MRI) 16,[33][34][35][36] or tomographic images of milled section structures. 37The transformation of 2D slices to 3D digital models requires technical skills in image analysis and 3D computer graphics software programs.With the explosion of real-time 3D virtual anatomy and 3D printing, proficiency in such programs is becoming increasingly important to the modern anatomist.
However, formal training in such skills is typically reserved for computer animation majors, and these skills are rarely taught to undergraduate biomedical students.Furthermore, learning opportunities that allow students to simultaneously explore anatomy in both 2D and 3D space are increasingly valuable to the neuroscience and anatomy classroom. 38,39e overarching goal of this project was to create a simple and inexpensive learning activity that engages students in the process of creating 3D digital models from 2D anatomical datasets at the microanatomy scale.A neuron, which is a complex 3D morphological structure, was used as the example structure for the video-based learning activity that guided students through the image analysis and 3D modeling steps.The final product made by each student is a 3D object file.The object file can be posted on a learning management system, or it can be 3D printed to result in a tangible model the student can keep.Presented below is a description of the learning activity, including videos, instructional guides, and learning objectives.

Development of 3D modeling workflow
The first step was to develop a novel, easy-to-follow workflow to teach students how to digitally trace a neuron from a confocal image stack and to create a 3D digital microanatomical model (Figure 1 where it can be thickened, smoothed, and edited with artifacts removed.In this step, the model can be scaled to a size compatible with a designated 3D printer and saved as an OBJ or STL file. Further processing to convert the above files to 3D printable files depends on the specific type/brand/model of 3D printer used at each institution.If an in-house 3D printer is not available on campus, online 3D printing services (such as Sculpteo) can be used.
• Video S6 (20:08): This is an optional tutorial that teaches students how to make morphological measurements of their neuron including soma diameter, dendritic field diameter, and total dendritic length.

Learning objectives
This activity was piloted among learners (advanced high school and

Unique aspects of the learning activity
The novel learning activity presented here was designed to teach students how to create a 3D digital model of a neuron from a 2D F I G U R E 1 Student workflow for tracing and 3D printing a neuron.Written student consent was acquired for the use of this photograph for publication.image stack of neuronal tissue.The activity is unique in that students can engage in microanatomical learning in a way that starts in only two dimensions on a microscopic scale but results in a 3D object that they can see, feel, and touch.Another unique feature is that students are able to work with real raw datasets from a confocal microscope, unlike other learning activities that require students to download pre-designed 3D object files from websites like www.neuro morpho.org or www.thing iverse.com (i.e., Refs.[45,46]).
Finally, the learning activity presented here is unique in its accessi- The concept of how 3D structures can be digitally sliced into 2D and then reconstructed again into 3D models is foundational to the modern anatomist, particularly since the profound impact of the US Library of Medicine's Visible Human Project in the mid-nineties. 47rthermore, agility with 3D imaging and modeling software is a skill high in demand in science and technology industries, and increasingly important to healthcare fields.As a result, some health professional programs have recently developed and implemented 3D printing electives for students in PT, MD, and dental programs. 48,491][52] As such, educators have advocated for the development of makerspaces in schools and libraries to support STEM activities that utilize 3D printing, and this trend has surged recently in academic libraries. 53Similarly, undergraduate research experiences help students "think like a scientist" and increase students' probability of indicating plans to enroll in STEM graduate programs. 54,55rly exposure to the value of research is an important strategy for increasing student interest in and attitude toward research careers 56 and is a mission important to the National Institutes of Health and the National Science Foundation. 57In light of these reports, one of the goals of this learning activity is to offer students a taste of what a "real neuroscience researcher" might do on a daily basis by allowing them to work with real confocal images of neuronal tissue and engaging them with industry-standard 3D image analysis and modeling tools.Neuron tracing through confocal image stacks in ImageJ is a skill relevant to a wide range of research fields in neuroscience but is particularly important to cellular neurobiology, 58 and a simple search in the PubMed database with the terms "ImageJ" and "Neuron" will yield over 20,000 results. 59arly all students that started the activity were able to complete the project.Overall, the feedback from students was positive.
In every class and every year this activity was implemented, students shared with the instructors that they found the activity rewarding, and expressed satisfaction in creating a tangible product they could keep.In fact, many students took pictures of themselves with their 3D printed neuron and shared the photos with family and friends through email, text, or social media.Anecdotally, it seemed as though students already comfortable with digital software were able to complete the task more quickly.Furthermore, students would often talk about the project, work in groups after class to troubleshoot and debrief from various aspects of the project.Students often reported on course evaluations that this activity was their favorite part of the course.Students also reported an increase in confidence in Blender and ImageJ software.

Limitations
A limitation of the video-based learning format is the rapid pace of software updates, which will require the instructional videos to be updated frequently.Future users of the learning activity will likely find advancements in the 3D modeling protocol due to the rapid pace of technological advancement in image analysis, 3D modeling, and 3D printing.For this reason, a troubleshooting guide was created (Video S2) to aid students encountering problems with the software in the future.Finally, it is important to note this activity does not explicitly teach the technical aspects of 3D printing including the variety of types/brands/models of 3D printers, g-code, print materials, or how to troubleshoot a malfunctioning 3D printer.

Future directions
This learning activity was designed to help students achieve learning goals on multiple levels including didactic knowledge about neuron morphology, technical skills in industry-standard image processing, analysis and modeling tools, and career exposure in neuroscience research.Overall, this learning activity is approachable, inexpensive, achievable, and adaptable.Teaching students the evolution of 3D structure to 2D image slices to a 3D model is generalizable to many biomedical fields beyond cellular neuroscience.Future studies should evaluate the learning activity among targeted learners to test the hypothesis that this learning activity enhances didactic knowledge of neuronal morphology and increases student confidence with industry-standard 3D imaging and modeling tools.Furthermore, this work is a proof of principle of a modeling workflow that is approachable, inexpensive, achievable, and adaptable to cell types of other organ systems.Thus, there is a rich opportunity to expand 3D printing technology into the field of microanatomy and neuroanatomy education.

ACK N OWLED G M ENTS
Special thanks to the University of Akron MakerStudio for their time and assistance with 3D printing, especially Maria Hawkins and Christopher Wertenberger, for their technical support and thoughtful consideration of student needs.Thanks also to Shilo Smith for assistance with literature searches.

FU N D I N G I N FO R M ATI O N
National Eye Institute; Grant number: R15EY026255.

CO N FLI C T O F I NTER E S T S TATEM ENT
There are no conflicts of interest.

R E FE R E N C E S
).A priority for the learning activity was to use free open-source software that any student could access.Six instructional videos were developed along with written instructions (Video S1) that walked students step-by-step through the project with the following [embedded] videos that total to 1 hour and 48 minutes of instruction (Figure 1): • Video S1: Intro (12:46): This video introduces students to the goals of the project.It teaches students the morphological parts of a typical neuron including soma, dendrites, dendritic spines, axon, axon terminal.The video also introduces the morphologic diversity of neurons in the nervous system, using the retina as an example, and modern methods of imaging neurons in a research laboratory.Finally, this video explains confocal imaging and what is a confocal "stack"; it explains how a 3D microanatomical structure, such as the neuron, can be digitally sliced into 2D images that can then be reconstructed digitally (minute 11:16-12:46).• Video S2: Downloading Software (5:47): This video instructs students how to download the free software required to complete the project including ImageJ (FIJI) Simple Neurite Tracer Plugin 40 and Blender. 41It also instructs students how to download an image stack of a neuron from properly labeled tissue from the Cell Image Library. 42A large variety of cell images are available from the Cell Image Library, and any neuron can be traced if the dendrites are stained or dialyzed with dye.The image stack used in this project was a melanopsin retinal ganglion cell from the mouse retina dialyzed with green fluorescent dye from the mouse retina as described in previous work by Stabio and colleagues 43 (14 stacks at 0.5 μm totaling 7 μm in z-depth), available from the Cell Image Library.The use of this free online repository is a practical solution for students who do not have access to tissue, fluorescent dyes, or a confocal microscope.• Video S3: Tracing Dendrites from a Z-Stack (30:49): This video teaches students how to trace dendrites with a semi-automated method using the Simple Neurite Tracer (SNT) plugin in ImageJ.The video instructs students how to trace the soma so that it can be "filled out" in the next step.• Video S4: Filling the neuron (12:45): This video teaches students how to use the "fill out" tool in SNT using a threshold to set pixel intensity values.Students are instructed to examine the traced neuron for any breaks and retrace or edit the pixel intensity.• Video S5: Smoothing in Blender (25:59): This video teaches students how to import the traced neuron object file into Blender early undergraduate) in an introductory undergraduate-level neuroscience course offered seven times over the course of 3 years.The goal of the project was to build student motivation and confidence in multiple areas, including didactic knowledge, image analysis skills, and 3D printing of neurons.Students were presented with an overview of the project at the beginning of the course, and students who completed the project by the end of the course either received extra credit equivalent to one weekly quiz, or a special notation in their course performance report.This learning activity was designed to integrate didactic knowledge and research skills and to help students achieve learning objectives on all six levels of Bloom's Revised Taxonomy as follows 44 : • To describe the structure and function of a neuron.(Bloom's Level 1: Remember) • To identify the parts of a typical neuron (Bloom's Level 2: Understand) • To demonstrate technical skills in industry-standard research tools including morphological analysis and 3D modeling software programs.(Bloom's Level 3: Apply) • To examine and measure the 3D morphology of a neuron at the micron scale (Bloom's Level 4: Analyze) • To value STEM career activities by role-playing what a "real neuroscience researcher" might do daily in the lab (Bloom's level 5: Evaluate) • To create a 3D model of a real neuron that can be 3D printed (Bloom's Level 6: Create) bility and adaptability.It uses all free open-source software and can be adapted to a wide range of courses (i.e., biology, neuroscience, histology, or research methods course) at advanced high school or undergraduate level.It can be adapted to in person (in a computer laboratory) or remote/virtual learning environment (on a student's home computer).The benefits of technical skills training in the undergraduate curriculum.
As mentioned above, the learning activity in this study used free open educational software programs that required only basic computer knowledge to install and operate.The learning activity also used open-source confocal image stacks that have been loaded by researchers to an online repository for sharing (www.celli magel ibrary.org), where other types of neurons and glial cells can be traced and 3D printed.These features increase the accessibility of the learning activity for institutions that do not have access to the equipment or funds to acquire high-resolution image stacks from neural tissue.Thus, the only potential cost for future students is to 3D print.Small printers are commercially available for relatively low cost (~$200-$300 in 2023) and one roll of filament (~$20 in 2023).Many colleges and universities have 3D printers available in the library for faculty and students to use free of charge.Nevertheless, the availability of a 3D printer and cost of filament are important considerations when implementing this learning activity at other institutions and can vary.