Effectiveness of 3D-printed models prepared from radiological data for anatomy education: A meta-analysis and trial sequential analysis of 22 randomized, controlled, crossover trials

Adil Asghar; Shagufta Naaz; Apurba Patra; Kumar S Ravi; Laxman Khanal

doi:10.4103/jehp.jehp_199_22

Previous article Browse articles Next article

ORIGINAL ARTICLE

J Edu Health Promot 2022, 11:353

Effectiveness of 3D-printed models prepared from radiological data for anatomy education: A meta-analysis and trial sequential analysis of 22 randomized, controlled, crossover trials

Adil Asghar¹, Shagufta Naaz², Apurba Patra³, Kumar S Ravi⁴, Laxman Khanal⁵
¹ Department of Anatomy, All India Institute of Medical Sciences, Patna, Bihar, India
² Department of Anaesthesiology, All India Institute of Medical Sciences, Patna, Bihar, India
³ Department of Anatomy, All India Institute of Medical Sciences, Bathinda, Punjab, India
⁴ Department of Anatomy, All India Institute of Medical Sciences Rishikesh, Uttarakhand, India
⁵ Department of Anatomy, BP Koirala Institute of Health Sciences, Nepal

Date of Submission	07-Feb-2022
Date of Acceptance	06-Jul-2022
Date of Web Publication	31-Oct-2022

Correspondence Address:
Dr. Adil Asghar
Department of Anatomy, All India Institute of Medical Sciences, Patna, Bihar
India

Source of Support: None, Conflict of Interest: None

Check

DOI: 10.4103/jehp.jehp_199_22

Abstract

BACKGROUND: Many academicians suggested the supplementary use of 3D-printed models reconstructed from radiological images for optimal anatomy education. 3D-printed model is newer technology available to us. The purpose of this systematic review was to capture the usefulness or effectiveness of this newer technology in anatomy education.
MATERIALS AND METHODS: Twenty-two studies met the inclusion and exclusion criteria for quantitative synthesis. The included studies were sub-grouped according to the interventions and participants. No restrictions were applied based on geographical location, language and publication years. Randomized, controlled trial, cross-sectional and cross-over designs were included. The effect size of each intervention in both participants was computed as a standardized mean difference (SMD).
RESULTS: Twenty-two randomized, controlled trials were included for quantitative estimation of effect size of knowledge acquisition as standardized mean difference in 1435 participants. The pooled effect size for 3D-printed model was 0.77 (0.45–1.09, 95% CI, P < 0.0001) with 86% heterogeneity. The accuracy score was measured in only three studies and estimated effect size was 2.81 (1.08–4.54, 95% CI, P = 0.001) with 92% heterogeneity. The satisfaction score was examined by questionnaire in 6 studies. The estimated effect size was 2.00 (0.69–3.32, 95% CI, P = 0.003) with significant heterogeneity.
CONCLUSION: The participants exposed to the 3D-printed model performed better than participants who used traditional methodologies. Thus, the 3D-printed model is a potential tool for anatomy education.

Keywords: Cognition, goals, immersion, motivation, printing, reaction time, spatial navigation, three-dimensional, tomography, X-Ray computed

How to cite this article:
Asghar A, Naaz S, Patra A, Ravi KS, Khanal L. Effectiveness of 3D-printed models prepared from radiological data for anatomy education: A meta-analysis and trial sequential analysis of 22 randomized, controlled, crossover trials. J Edu Health Promot 2022;11:353

How to cite this URL:
Asghar A, Naaz S, Patra A, Ravi KS, Khanal L. Effectiveness of 3D-printed models prepared from radiological data for anatomy education: A meta-analysis and trial sequential analysis of 22 randomized, controlled, crossover trials. J Edu Health Promot [serial online] 2022 [cited 2023 Jun 6];11:353. Available from: https://www.jehp.net//text.asp?2022/11/1/353/360018

Introduction

Anatomy is the cornerstone of medical education along with clinical practices for medical and allied health students. The acquisition of anatomical knowledge is mainly concerned with identifying and finding relations of any organ or structure.^[1] Medical students or residents need spatial orientation and visualization of human body structures for clinical teaching or practice, other than their functions. Students often find topics difficult because of complex spatial relations.^[2] Cadaveric dissection or wet cadaveric prosection is the yardstick for anatomy teaching, which is traditionally employed as a normal educational framework to assist students in learning anatomical structure, three-dimensional (3D) orientation, and gaining practical skills.^[3],[4] A lot of money, time, and expertise are utilized during the preparation, maintenance, and disposal of cadaveric specimens. An expressive or meaningful collection of these specimens would be expensive to manage and afford for every medical school. Plastinated specimens became a popular and dependable alternative.^[5] Casting and molding-based plastic models were less realistic and were only suited for teaching elementary anatomy.^[6]

Further advancement with the availability of 3D printers made it feasible to make cost-effective, high-quality copies of human anatomical organs and body parts in a wide variety of textures and colors from 3D-reconstructed images of computerized tomography (CT) scan or magnetic resonance imaging (MRI) scan.^[7] Several researchers have experimented with this additive technology to create anatomical models using CT or MRI images.^[6],[8] Anatomy teachers also have opportunities to develop 3D-printed models (3DPMs) from radiological scans of patients on case basis.^[9] It is highly customized and extraordinarily detailed, which was impossible earlier in the molded physical model. Such models have very minute details, equivalent to dissected cadaveric specimens. Their handling has improved students' visuospatial consciousness, tactile sensation, and decreased cognitive load.^[10] Students can also learn the pathological anatomy of any structure they often miss in cadaveric dissection.^[11] Many trials have been conducted in the past to assess its actual benefits among learners.

Medical students preferred novel 3DPMs as learning tools and expressed their idea and argued with their favorable comments on increasing engagements, orientation and recognition of diverse anatomical details of the structure.^[4],[7],[12] Additionally, they enumerated several benefits of using 3DPMs, for example, color labeling, ease of handling, less fear of damaging the structure, and fewer psychological inhibitions while engaging with the 3DPM [Figure 1]. It was difficult to grasp 3D relationships and build mental representations using static 2D pictures, as opposed to 3DPMs, which could be held in all directions and rotated.^{[6],[7],[8],[10]}

Figure 1: 3D-printed model of skull from CT data prepared at the 3D printing lab (department of anatomy). It is accurate and allows for easy handling. Multiple copies of the same model (partly or even single bone) can be prepared along with the colored region of interest

Click here to view

When students were tested for anatomical knowledge between 3DPMs and standard cadaveric materials, the 3DPM group performed better than the cadaveric group.^{[13],[14],[15]} However, the results of the research were limited by a number of factors, such as a small sample size and a focus on relatively easy anatomical topics.^{[14],[16],[17]} Many researchers outlined the benefits and educational value of these models; however, these innovative tools had not yet been widely implemented in anatomical education.^[6],[7],[13] Many empirical investigations revealed the potential and superiority of 3DPMs above the traditional approach in terms of effective learning and performance. There was a need for further evidence before these approaches could be widely adopted in conventional medical education.

Stakeholders believe 3DPMs can provide a valuable contribution to anatomy education. To test our hypothesis in this context, we explored the learner's benefit based on the available data in published literatures. Could it support the idea that 3DPM is a supplementary tool in anatomy education based on the critical evaluation of published literature? The current systematic review was conducted to evaluate its effectiveness and impact on anatomy teaching comprehensively. The review also glanced at the mechanisms behind its efficacy and assimilation into modern curricula based on learning principles, as well as the attributes that drive its utility.

Materials and Methods

Study design and setting

Population: Undergraduate and residents of medical or allied health courses where anatomy is taught as a subject.

Intervention: 3DPM prepared from radiological data.

Comparator: Traditional method like textbook, atlas, PowerPoint slides and chalk-board teaching.

Outcome: Kirkpatrick's model of educational outcomes [Figure 2] is utilized as an evaluation framework for classifying and analyzing results of an educational intervention (3DPM model).^[18] In this model, postinterventional changes in learners are captured in the form of reaction (learner experience), learning (changes in attitude, knowledge, and skill), behavior (shift in practice and application of learning), and results (changes in practice or application at the level of organization). Here, we captured only the first two main outcomes:

Figure 2: Kirkpatrick model of educational outcomes evaluation (Kirkpatrick 2016)

Click here to view

Learning (Level 2): Knowledge by changes in test score or accuracy. It also corresponds to level 1 of Miller's pyramid.^[19]
Learner's experience (Level 1): Changes in learner's satisfaction, confidence level, utility, and engagement by test completion time.

[Figure 2] shows the Kirkpatrick model of educational outcomes evaluation.^[18]

Inclusion criteria

Population: Students or residents of health professional courses.
Studies addressing the impact or effectiveness of 3DPM as an intervention in surgical and radiological anatomy along with patho-anatomy.
Randomized controlled trials (parallel or cross-over), prospective and retrospective observational studies were included if the 3D anatomy tool was used as an intervention.
The 3DPM prepared from radiological images as anatomy education tools on student or resident learning were included.
The radiological images used for creating 3D models should be computerized tomography (CT) scan, magnetic resonance imaging (MRI), ultrasonography, and positron emission tomography (PET) scan.
The comparator would be the traditional approaches, including textbooks, two-dimensional (2D) images or atlas, lecture notes, tutorial notes, 2D illustrations, PowerPoint slides, and text-focused resources.
The outcomes measured were (a) factual knowledge, spatial orientation measured by test score or accuracy (Kirkpatrick level 2 and Miller's knowledge and applied frame work), (b) the reaction of participant, for example, the satisfaction score, response time, usefulness, confidence (Kirkpatrick level 1) (Kirkpatrick 2016).
English language manuscripts.

Exclusion criteria

Population: Faculty or non-academic trainee.
Following interventions were excluded: Physical plastic model, clay model, plaster of Paris model, plastinated model, and mounted cadaveric viscera.
Commercially procured 3DPM model.
Descriptive studies or narrative meta.
Studies related to planning and making 3D models.
3D model studies dealing with bioengineering and developing implants.
Non-English language manuscript.
Surgical planning, diagnosis, simulation
Presurgical training.
Patient education.
The outcome as a preference or choice or acceptance.

Study selection

The search strategy collected relevant studies from electronic databases like ERIC, OECD, PubMed, Google Scholar, Scopus, and EMBASE. The MeSH terms and their synonyms were used to search for studies. The search strategy is mentioned here (“3D printed” OR “3D printing” OR “3D printed” OR “3-D printing” OR “3-dimensional printed” OR “3-dimensional printing” OR “three-dimensional printed” OR “three- dimensional printing”) AND “anatomy” AND (“education” OR “teaching” OR “learning”). Other sources like online anatomy and medical education journals, the hard copies of anatomy and medical or dental education journals were also searched. The searched items were transferred to Rayyan QCRI app to shortlist the studies based on inclusion and exclusion criteria. Two reviewers used the inclusion and exclusion criteria to shortlist the studies independently. The duplicated items from different search strategies were removed. The third reviewer provided input during conflicting opinions of the first two reviewers. The protocol was prospectively registered in PROSPERO (CRD42021249906).

Methodological quality assessment

This review employed the risk of bias assessment by Medical Education Research Study Quality Instrument (MERSQI).^[20] Risk of bias was assessed by observing the studies for random sequence generation and allocation concealment, blinding of investigator and participant, blinding of outcome assessment, and selective reporting. Each item was categorized into low risk, unclear, and high risk of bias. Two independent reviewers executed the risk of bias assessment.

Data extraction and analysis

The full texts of included studies were assessed for author, publication year, DOI number, country, institution, journal, type of research, participants, intervention, sample size, outcomes of the intervention, and items of risk bias assessment of MERSQI. The extracted data were mapped for synthesizing the qualitative and quantitative shreds of evidence. The original author was contacted via email for missing data. Test score, time of completion of test, satisfaction score, and sample size of the control and intervention groups were recorded. These data recorded were expressed as mean and standard deviation or median and interquartile range. The median and interquartile range were converted to mean and standard deviation, respectively, by the appropriate formulae.

The heterogeneity statistics were measured with Cochrane Q, tau square, and i² statistics. If heterogeneity was more than 50%, the random effect model was used; otherwise, the fixed-effect model was used for effect size estimation. Subgroups were created to deal with heterogeneity. The effect size of each study was computed as a standardized mean difference (SMD) because of variable scale of assessment in pretest and posttest. Then SMD of each study was combined into meta-analysis by inverse variance method to get pooled effect size. Then final i² statistics, Cochrane Q, and Z-score were calculated. The sensitivity analysis was conducted leaving out each study, and cumulative analysis was executed by adding each study in sequence. We were not able to reduce heterogeneity during the data analysis. The cumulative alpha error (α = 0.05) of included studies and high heterogeneity might shift the Z-curve of the pooled effect size during random effect model of meta-analysis. Trial Sequential Analysis (TSA) version 0.9 (Copenhagen Trial Unit, Denmark) was utilized to calculate pooled estimates after adjusting the threshold for statistical significance (α = 0.05 and β = 0.2) to overcome the above errors and to estimate the required information size (RIS). TSA monitoring borders were set at a 95% confidence interval and cumulative Z-curve was evaluated sequentially after the addition of included studies.

Results

Characteristics of included studies

The search strategy resulted in 7539 items from all digital sources and 217 items from other sources. Seventeen hundred fifty-three were found to be nonduplicate items, leaving 6003 things. The titles and abstracts of items of 341 were shortlisted from 1753 items in Rayyan QCRI app, and finally keeping 106 items, the rest of the articles were excluded in the screening phase. The full texts of 106 studies were assessed, and 84 were excluded from review due to different reasons, for example, inadequate outcome or missing data, etc., [Figure 3]. A total of 22 studies were included in the review and quantitative analysis. Of the 22 studies included in the review, 10 were from Asia, 4 from Europe, and 8 from North America. None of the studies were reported from Australia, Africa, and South America [Table 1] and [Table 2]. Fourteen studies dealt with undergraduate students of medical, dental, and allied health sciences, whereas 8 studies dealt with residents and interns [Table 1] and [Table 2].^{[12],[13],[14],[15],[16],[17],[21],[22],[23],[24],[25],[26],[27],[28],[29],[30],[31],[32],[33],[34],[35],[36]}

Figure 3: PRISMA flow diagram of search strategy

Click here to view

Table 1: MERSQI tool used for quality assessment for included studies

Click here to view

Table 2: The characteristics of included studies in systematic review and meta-analysis

Click here to view

Effect of interventions

Factual knowledge and spatial orientation (Kirkpatrick level 2): Both outcomes were tested either by test score or accuracy in the studies.

a. Based on knowledge score: Twenty-two randomized, controlled trials studied the effectiveness of 3DPM in 1435 participants. The 3DPM group had 722 participants and 2D or tradition group had 713 participants in all trials. The pooled effect size (SMD) of 3DPM was 0.77 (0.45–1.09, 95% CI, P < 0.0001) with 86% heterogeneity [Figure 4]. Subgroups were created based on population and intervention.

Figure 4: The forest plot; pooled effect size of changes in test score in 3DPM group with reference to 2D or traditional method

Click here to view

Fourteen studies were included in the undergraduate subgroup. The estimated pooled effect size among the undergraduate students was 0.97 (0.57–1.37, 95%CI, P < 0.001) with 88% heterogeneity among studies. A total of 9 studies were included in the resident subgroup. The pooled effect size (knowledge score) was 0.45 (−0.07 to 0.97, 95% CI, P = 0.09) with 83% heterogeneity [Figure 4]. 3DPM of the musculoskeletal and nervous systems were more effective, but the same were not established for cardiac and gastro-intestinal models. The effect size for musculoskeletal intervention was 0.86 (0.50–1.22, 95%CI, P < 0.001) with 76% heterogeneity. For nervous system 3DPM intervention, the pooled effect size was 1.06 (0.59–1.53, 95% CI, P < 0.001) without any heterogeneity [Figure 5]. Subgroup group analysis did not appear fruitful in reducing the heterogeneity, and trial sequence analysis was considered for evaluation of impact of associated heterogeneity on pooled effect size (cumulative Z-curve).

Figure 5: Forest plot evaluating the change in test score based on subgroup of intervention

Click here to view

In trial sequence analysis was implemented to follow the cumulative Z-curve (blue line) and heterogeneity-adjusted cumulative Z-curve (green line) to assess the impact of existing heterogeneity [Figure 6]a. Both lines ran in significant zone beyond (2SD) and indicated that the 3DPM intervention was significantly effective in undergraduate population. The estimated RIS was 734 which was already achieved. No further trial is needed to evaluate the benefits of 3DPM in anatomy education for undergraduates. For residents, cumulative Z-curve (blue line) just crossed the boundary of insignificant zone, but green line (heterogeneity adjusted Z-curve) was still within the boundary of insignificant zone as shown in [Figure 6]b. Thus, the pooled effect size for residents was insignificant and RIS was yet to be achieved (n = 893). So, further studies need to be conducted to compute final effect size.

Figure 6: (a) Trial Sequence Analysis (TSA) of 3D printed model among students' population. Cumulative Z-curves (blue color) and penalized cumulative Z-curve (green color). RIS = 734. Total sample size crossed the RIS (n = 734). Thus, 3DPM is superior to 2D or traditional method or drawing. No further trials are needed. (b) Trial Sequence Analysis (TSA) of 3D-printed model among residents' population. Cumulative Z-curves (blue color) and penalized cumulative Z-curve (green color); RIS = 893. The total sample size did not cross the RIS (n = 893). It is not superior to 2D or traditional models or drawings as green line falls within monitoring boundary. Further trials are needed for confirmation

Click here to view

b. Accuracy: Only two studies dealt with accuracy scores based on the corrected items. The effect size estimated for the 3DPM (represented as SMD) was found to be 2.81 (1.08–4.54, 95% CI, P = 0.001) with 92% heterogeneity [Figure 7]. Both blue and green lines ran in the significant zone in TSA. Thus, it played a significant role in improving the accuracy of the test.

Figure 7: Forest plot evaluating shift in accuracy in 3DPM group with reference to 2D tradition method

Click here to view

Student's or resident's reaction (Kirkpatrick level 1)

Satisfaction

[Figure 8]

Figure 8: Forest plot of pooled effect size evaluating change in satisfaction score of 3D printed model with reference to 2D or traditiongl method

Click here to view

Test completion time

[Figure 9]

Figure 9: Forest plot of pooled effect size of mean difference of completion time of 3D-printed models with reference to 2D or traditional method

Click here to view

Utility

[Figure 10]

Figure 10: Forest plot of pooled effect size of proportion of subjects felt useful with 3D-printed models with reference to 2D or tradition method

Click here to view

Confidence Level

The confidence level was reported by only 4 studies. The effect size of the confidence level was computed as SMD, which was 0.48 (−0.27 to 1.23, 95% CI, P = 0.21) [Figure 11]. No significant difference of confidence level was observed in participants of the 3DPM group over the traditional group. TSA result had similar findings but RIS was not achieved.

Figure 11: Forest plot of pooled effect size (SMD) confidence level rated by subjects on a Likert scale in 3D-printed models with reference to 2D or traditional method

Click here to view

Publication bias

On examination of the funnel plot of the primary outcome, authors have found no publication bias. All studies were symmetrically arranged on both sides of no effect line. Therefore, no missing studies were expected on the evaluation of the plot of SE (SMD) and SMD.

Discussion

Summary of findings

The goal of the study was to examine the benefits and suitability of 3DPM and its comparison with traditional methods for anatomy learning. The current review focused on Kirkpatrick level 2 or Miller's knowledge and applied knowledge framework since it is most relevant to the first-year medical, allied health students and trainee residents. According to the findings of these studies, health science students who learnt using it outperformed than students who learned using traditional methods in post-test scores with moderate-to-large effect size. Such findings could not be established for trainee residents due to heterogeneity in the study population and methodologies; these need further studies. Both knowledge and skill domains were tested in residents which could be another possible reason for indifference. Moreover, students and residents may not experience similar difficulties in recognizing them in the clinical scenario because of the complexity of structure.^[14] However, in terms of accuracy and satisfaction level, 3DPM is not significantly inferior to traditional. Between the two methods (3DPM vs 2D/traditional), there was no difference in completion or response time. It is superior to traditional methods for short-term retention (based on test score). However, its superiority above traditional models was not established for long-term retention due to paucity of available data. 3DPM is an effective tool for learning anatomy of musculoskeletal and central nervous systems as shown in the current study, but the same could not be established for cardiovascular and peripheral nervous systems because both are difficult to contextualize in 3DPM (like in angiogram, elastography or diffusion tensor imaging). The differentiation of blood vessels and peripheral nerves and their course are difficult to examine in cross-sectional images and 3DPM (which is produced from volume rendering of cross-sectional images).

Yammine and Violato evaluated the effectiveness of physical models (plaster of Paris, or plastic or clay models) in anatomical education. They included 8 studies in their meta-analysis and computed the effect estimates of overall knowledge as an outcome (factual and spatial knowledge acquisition). The effect estimate was 0.73 (0.353–1.119, 95% CI, i² = 84.7%, P = 0.0002).^[2] Ye et al.,^[9] conducted subgroup analysis based on organ system for 3DPM, claimed superiority of 3DPM for the brain, musculoskeletal, abdominal and trunk muscles except for heart model. Their analysis also captured similarly high heterogeneity (60%–89%). Fleming et al. conducted a meta-analysis evaluation of 3DPM among medical students involving 4 studies having 124 participants in the 3D-printed group and 129 in the traditional control group. They computed the effect size (SMD) which was 0.54 (0.29–0.79, 95% CI) without heterogeneity. Furthermore, Fleming et al.,^[11] in 2020, calculated the pooled estimate from studies involving resident physicians (N = 228 participants). The effect size of the 3DPM for resident physicians was 0.15 (−0.32 to 0.62, 95% CI, P = 0.53) with significant heterogeneity. We captured similar results and higher heterogeneity.

Effectiveness of 3DPM models: Possible mechanism based on learning theory

According to Jansen et al.,^[37] tangible visualizations of structure have several advantages over on-screen or 2D image visualizations, as it allows for more active perception, leverages nonvisual senses such as touch, integrates with the physical world, and harnesses the interplay between vision and touch to facilitate cognition. Khot et al.^[38] turned heart CT data into 3D-printed heart model and evaluated students' engagement. The participants stated that the constructs served as a reward and allowed them to reflect their previous learning experiences. According to goal-setting theory, such rewards are vital in retaining interest in any activity, and reward-based therapies push healthy behaviour change (as extra effort in learning, engagement, and reflection) in students' learning.

Representational insight is the ability to perceive and mentally depict a relationship between a structure and its surroundings.^[39],[40] The multi-material and multicolored nature of 3DPM enable them to learn deeper characteristics of structure beyond the simple identification and discrimination. It helped participants to contextualize the structure, create the mental image, and retrieve the information which assists them to apply it in different situations.^[7] Students agreed that 3D models will act as a tool of mental rotation and spatial ability to boost their own and peers' understanding, awareness, and motivation.^[41] Previous research has shown that participating in learning activities with peers promotes motivation, enjoyment,^[39],[40] intensity,^[42] and out-of-school participation.^[43]

3DPM are an important aspect of the case-based learning process. Actively incorporating such models into the learning environment would be a better strategy.^[44] According to Romanek and Lynch, the core principle of case-based or object-based learning is that appealing with an object or model helps the students' learning. It has been suggested that interlocking the sense of touch with visual perception might aid with memory retention.^[45] In constructivist approach, students' understanding and knowledge are formed via interaction (team work with discussion and debates). Two-dimensional visualizations have the ability only to engage learners at superficial level via passive transmission of information.^[46] They do not foster higher order thinking (analysis, synthesis, and assessment) and immersion like in 3D models or cadaveric dissection.^[47] Fear, anxiety and discomfort may lower the level of immersion with cadaveric materials. Students had less psychological distress when dealing with 3DPM compared to wet materials due to odorlessness, and dryness.^[13]

Implication of 3DPM in modern curriculum

Thinking, doing, feeling, and reflecting are the processes of learning (Kolb's Cycle). The textual material, presentations, movies, and models are used to introduce new concepts (abstract conceptualization).^[48] In the “thinking” phase of the lesson plan, students' identify structure shown in 3DPM. In order to develop a 3D concept, students should be encouraged to handle printed models and participate in self-directed small group discussions (8–10 students with team leader) employing their understanding and concepts. Participants were encouraged to share their findings with their peers while touching the models. The instructor acted as a facilitator and created core information before moving on to the high-level (problem solving), utilizing “think-pair-share” cooperative learning methodologies. Finally, students are given time and encouraged to write down major concepts and theories in their own words as reflection. As a result, learners may feel more confident by integrating these innovative technologies into their formal anatomy curriculum.

3DPMs have been widely used in surgical oncology, plastic surgery, dental surgery, neurosurgery, and as a guide for orthopedic surgery. It reduces the surgeon's stress and operative time, blood loss, and infection rates.^[49] Like cadaveric samples, they have high anatomical and physical rationality and could be used as a training model.^[50] Patient data could be used for printing 3DPM according to the needs of the clinical scenario or even could be customized according to the learning outcomes and students' needs.^[51] Students would find every new customized model as interesting and challenging which could be a stimulus for self-directed or peer-mediated learning. They would develop a problem-solving attitude and empathy for patients.^[52] These could be a resource for clinical simulation, surgical training, and studying rare diseases.

Disadvantages of 3DPM

Practically, like every technology, it has disadvantages that must be considered. As Khot et al. pointed out, too much data might make a model less comprehensible, while too little data can lead the model to lose its intended purpose.^[53] Distraction is another problem, and students may find it difficult to manage the content.^{[54],[55],[56]} Other shortcomings are adaptability, cost, and environmental hazard. Even teachers and mentors are also not acquainted with this technology. But the adaptability issues will gradually vanish with an acquaintance. Its cost, maintenance, and printing materials are still very costly and beyond the reach of developing countries. As of now, it is only available in premier institutes, but its cost will decline in the near future. The printing materials are not bio-degradable and can not be recycled, so it can pose an environmental challenge in the coming days. The dust material coming out during printing and cleaning may pose as a health hazard for the end-user and technicians. Printing time and expenditure fluctuate according to the model of the 3D printer and the printing material, which are other potential challenges.

Limitations and recommendations

The potential limitation of this study was the lack of data from the larger geographical areas (Africa, Australia & South America). The language was another possible limitation because the English manuscripts were more represented than other languages. An adequate number of manuscripts in other languages could not be found even after an extensive search. Observed heterogeneity is possibly due to inadequate standardization of content of teaching material, and questionnaires. These could be the possible pitfalls even after adequate validation. Although the present study provides the heterogeneity-adjusted effect size of both interventions, the confidence interval of effect size would be narrowed and devoid of heterogeneity if these factors are adequately standardized. Another limitation is the validity of different assessment methods used in the included studies. The most common method of assessment was questionnaire-based closed-ended items. The difficulty and discriminatory indexes and covariance among the items could also be a possible limitation. Multi-arm RCTs or cross-over trials could be conducted in the future to differentiate the effectiveness of 3DPM from other multimodal tools (prosection, cadaveric dissection, or simulating cadavers) of anatomy education. The intent of acquiring anatomical knowledge before the introduction to the official anatomy course, reservation on the complexity of learning topic based on comments of faculties or anecdotal comments of senior students may introduce bias. The most significant feature of 3DPM is adequate haptic feedback, which is highly reliant on the mechanical properties of the printing materials (adequate elastic modulus and tensile strength), type of printers, processing software, and cost. The absence of established techniques for evaluating macro- and microstructure of 3D-printed models was an obvious restriction. Thus future research should focus on standardized methods for evaluating 3D-printed models.

The present study measured heterogeneity-adjusted effect estimates of knowledge acquisition. The pooled estimates calculated from high-quality cross-over studies made it robust and novel. Determining the long-term retention of anatomical knowledge and the behavioral elements associated with clinical skills and patient care may be the subject of future research. The same set of test items was used for both the pre- and posttests to guarantee that both tests were of equal quality and complexity to determine whether or not there was a change. Appropriate steps should be taken to minimize recall bias and carryover effects. The carryover effects must be eliminated by keeping the washout period, using different learning topics, and blinding the participants on the learning objectives.

Conclusion

Despite the above limitations, the current study demonstrates that 3DPM tool is superior to traditional or conventional methods of anatomy teaching and are providing better factual knowledge and satisfaction to the learners. Therefore, 3DPM could be a potential solution for newly established medical institutions and other institutions having fewer numbers of cadavers. The present review advocates its appropriate use as students' learning resources. The curriculum could be supplemented with this newer technology under guidance for undergraduate students who have limited knowledge and spatial orientation of any structures.

Acknowledgment

The study was registered with PROSPERO: International prospective register of systematic reviews, managed by the National Institute of Health Research, University of York, Centre for Reviews and Dissemination. Registration number: CRD42021249906 dated 21/05/2021.

Ethical statement

Authors have declared that “APA codes of ethics (2017) 1.01 to 10.10. were followed.” The data or images from humans or animals were not utilized in this manuscript.

Authors contributions

Adil Asghar: Conceptualization, Search strategies, Statistical analysis, Manuscript Preparation.

Shagufta Naaz: Risk of Bias, Statistical Analysis, Manuscript preparation, Manuscript editing.

Apurba Patra: Literature search, Collection of literature, Shortlisting of manuscripts,

Kumar Satish Ravi: Literature search, Collection of literature, Shortlisting of manuscripts.

Laxman Khanal: Literature search, Shortlisting of manuscripts, Risk of bias, Manuscript Preparation.

PROSPERO: CRD42021249906.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

References

1.	Sugand K, Abrahams P, Khurana A. The anatomy of anatomy: A review for its modernization. Anat Sci Educ 2010;3:83-93.
2.	Yammine K, Violato C. A meta-analysis of the educational effectiveness of three-dimensional visualization technologies in teaching anatomy. Anat Sci Educ 2015;8:525-38.
3.	Biasutto SN, Ignacio Caussa L, Esteban Criado del Río L. Teaching anatomy: Cadavers vs. computers? Ann Anat 2006;188:187-90.
4.	Chytas D, Piagkou M, Salmas M, Johnson EO. Is cadaveric dissection the “gold standard” for neuroanatomy education? Anat Sci Educ 2020;13:804-5.
5.	Fruhstorfer BH, Palmer J, Brydges S, Abrahams PH. The use of plastinated prosections for teaching anatomy-The view of medical students on the value of this learning resource. Clin Anat 2011;24:246-52.
6.	McMenamin PG, Quayle MR, McHenry CR, Adams JW. The production of anatomical teaching resources using three-dimensional (3D) printing technology: 3D printing in anatomy education. Anat Sci Educ 2014;7:479-86.
7.	Mogali SR, Yeong WY, Tan HKJ, Tan GJS, Abrahams PH, Zary N, et al. Evaluation by medical students of the educational value of multi-material and multi-colored three-dimensional printed models of the upper limb for anatomical education: 3D printed upper limb in anatomical education. Anat Sci Educ 2018;11:54-64.
8.	Radzi S, Tan HKJ, Tan GJS, Yeong WY, Ferenczi MA, Low-Beer N, et al. Development of a three-dimensional printed heart from computed tomography images of a plastinated specimen for learning anatomy. Anat Cell Biol 2020;53:48-57.
9.	Ye Z, Dun A, Jiang H, Nie C, Zhao S, Wang T, et al. The role of 3D printed models in the teaching of human anatomy: A systematic review and meta-analysis. BMC Med Educ 2020;20:335.
10.	Garas M, Vaccarezza M, Newland G, McVay-Doornbusch K, Hasani J. 3D-Printed specimens as a valuable tool in anatomy education: A pilot study. Ann Anat 2018;219:57-64.
11.	Fleming C, Sadaghiani MS, Stellon MA, Javan R. Effectiveness of three-dimensionally printed models in anatomy education for medical students and resident physicians: Systematic review and meta-analysis. J Am Coll Radiol 2020;17:1220-9.
12.	Chen Y, Qian C, Shen R, Wu D, Bian L, Qu H, et al. 3D printing technology improves medical interns' understanding of anatomy of gastrocolic trunk. J Surg Educ 2020;77:1279-84.
13.	Chen S, Pan Z, Wu Y, Gu Z, Li M, Liang Z, et al. The role of three-dimensional printed models of skull in anatomy education: A randomized controlled trail. Sci Rep 2017;7:575.
14.	Smith CF, Tollemache N, Covill D, Johnston M. Take away body parts! An investigation into the use of 3D-printed anatomical models in undergraduate anatomy education. Anat Sci Educ 2018;11:44-53.
15.	Tanner JA, Jethwa B, Jackson J, Bartanuszova M, King TS, Bhattacharya A, et al. A three-dimensional print model of the pterygopalatine fossa significantly enhances the learning experience. Anat Sci Educ 2020;13:568-80.
16.	Li Z, Li Z, Xu R, Li M, Li J, Liu Y, et al. Three-dimensional printing models improve understanding of spinal fracture—A randomized controlled study in China. Sci Rep 2015;5:11570. doi: 10.1038/srep11570.
17.	Yi X, Ding C, Xu H, Huang T, Kang D, Wang D. Three-dimensional printed models in anatomy education of the ventricular system: A randomized controlled study. World Neurosurg 2019;125:e891-901.
18.	Kirkpatrick JD, Kirkpatrick WK. Kirkpatrick's Four Levels of Training Evaluation. Association for Talent Development; Alexandria, Virginia: ATD publisher 2016.
19.	Williams BW, Byrne PD, Welindt D, Williams MV. Miller's pyramid and core competency assessment: A study in relationship construct validity. J Contin Educ Health Prof 2016;36:295-9.
20.	Smith RP, Learman LA. A plea for MERSQI: The medical education research study quality instrument. Obstet Gynecol 2017;130:686-90.
21.	AlAli AB, Griffin MF, Calonge WM, Butler PE. Evaluating the use of cleft lip and palate 3D-printed models as a teaching aid. J Surg Educ 2018;75:200-8.
22.	Awan O, Dako F, Akhter T, Hava S, Shaikh F, Ali S, et al. Utilizing audience response to foster evidence-based learning in a pilot study: Does It really work? Cureus; 10:e3799. doi: 10.7759/cureus. 3799.
23.	Bangeas P, Drevelegas K, Agorastou C, Tzounis Lazaros, Chorti A, Paramythiotis D. Three-dimensional printing as an educational tool in colorectal surgery. Front Biosci (Elite Ed) 2019;11:29-37.
24.	Bohl MA, Zhou JJ, Mooney MA, Repp GJ, Cavallo C, Nakaji P, et al. The barrow biomimetic spine: Effect of a 3-dimensional-printed spinal osteotomy model on performance of spinal osteotomies by medical students and interns. J Spine Surg 2019;5:58-65.
25.	Cai B, Rajendran K, Bay BH, Lee J, Yen C-C. The effects of a functional three-dimensional (3D) printed knee joint simulator in improving anatomical spatial knowledge. Anat Sci Educ 2019;12:610-8.
26.	Chedid VG, Kamath AA, Knudsen JM, Frimannsdottir K, Yost KJ, Geske JR, et al. Three-dimensional-printed liver model helps learners identify hepatic subsegments: A randomized-controlled cross-over trial. Am J Gastroenterol 2020;115:1906-10.
27.	Guitarte Vidaurre A, Hadeed K, Dulac Y, Karsenty C, Acar P. Usefulness of 3D printed models of congenital heart diseases as educational tools for medical students. Arch Cardiovasc Dis Suppl 2019;11:e329.
28.	Jones TW, Seckeler MD. Use of 3D models of vascular rings and slings to improve resident education. Congenit Heart Dis 2017;12:578-82.
29.	Hojo D, Murono K, Nozawa H, Kawai K, Hata K, Tanaka T, et al. Utility of a three-dimensional printed pelvic model for lateral pelvic lymph node dissection. Int J Colorectal Dis 2020;35:905-10.
30.	Loke Y-H, Harahsheh AS, Krieger A, Olivieri LJ. Usage of 3D models of tetralogy of Fallot for medical education: Impact on learning congenital heart disease. BMC Med Educ 2017;17:54.
31.	Low CM, Morris JM, Matsumoto JS, Stokken JK, O'Brien EK, Choby G. Use of 3D-printed and 2D-illustrated international frontal sinus anatomy classification anatomic models for resident education. Otolaryngol Head Neck Surg 2019;161:705-13.
32.	Wang C, Daniel BK, Asil M, Khwaounjoo P, Cakmak YO. A randomised control trial and comparative analysis of multi-dimensional learning tools in anatomy. Sci Rep 2020;10:6120.
33.	White SC, Sedler J, Jones TW, Seckeler M. Utility of three-dimensional models in resident education on simple and complex intracardiac congenital heart defects. Congenit Heart Dis 2018;13:1045-9.
34.	Wu A-M, Wang K, Wang J-S, Chen C-H, Yang X-D, Ni W-F, et al. The addition of 3D printed models to enhance the teaching and learning of bone spatial anatomy and fractures for undergraduate students: A randomized controlled study. Ann Transl Med 2018;6:403. doi: 10.21037/atm. 2018.09.59.
35.	Lin Q-S, Lin Y-X, Wu X-Y, Yao P-S, Chen P, Kang D-Z. Utility of 3-dimensional-printed models in enhancing the learning curve of surgery of tuberculum sellae meningioma. World Neurosurg 2018;113:e222-31.
36.	Su W, Xiao Y, He S, Huang P, Deng X. Three-dimensional printing models in congenital heart disease education for medical students: A controlled comparative study. BMC Med Educ 2018;18:178.
37.	Jansen Y, Dragicevic P, Fekete J-D. Evaluating the efficiency of physical visualizations. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. Paris France: ACM; 2013. p. 2593-602.Available from: https://dl.acm.org/doi/10.1145/24706540.2481359. [Last accessed on 2021 Dec 04].
38.	Khot RA. Exploring material representations of physical activity. In: Proceedings of the 2014 Companion Publication on Designing Interactive Systems-DIS Companion '14. Vancouver, BC, Canada: ACM Press; 2014. p. 177-80. Available from: http://dl.acm.org/citation.cfm?doid=2598784.2598792. [Last accessed on 2021 Dec 04].
39.	Jago R, Page AS, Cooper AR. Friends and physical activity during the transition from primary to secondary school. Med Sci Sports Exer 2012;44:111-7.
40.	Salvy S-J, de la Haye K, Bowker JC, Hermans RCJ. Influence of peers and friends on children's and adolescents' eating and activity behaviors. Physiol Behav 2012;106:369-78.
41.	Salvy S-J, Roemmich JN, Bowker JC, Romero ND, Stadler PJ, Epstein LH. Effect of peers and friends on youth physical activity and motivation to be physically active. J Pediatr Psychol 2008;34:217-25.
42.	Barkley JE, Salvy S-J, Sanders GJ, Dey S, Von Carlowitz K-P, Williamson ML. Peer influence and physical activity behavior in young children: An experimental study. J Phys Activity Health 2014;11:404-9.
43.	Pearce M, Page AS, Griffin TP, Cooper AR. Who children spend time with after school: Associations with objectively recorded indoor and outdoor physical activity. Int J Behav Nutr Phys Act 2014;11:45. doi: 10.1186/1479-5868-11-45.
44.	Chatterjee HJ, Hannan L. Engaging the Senses: Object-Based Learning in Higher Education. London; New York: Routledge; 2016. Available from: https://www.taylorfrancis.com/books/e/9781315579641. [Last accessed on 2021 Dec 04].
45.	Romanek D, Lynch B. Touch in Museums: Policy and Practice in Object Handling. first. Routledge: Taylor Francis; 2008. Available from: https://www.taylorfrancis.com/books/9781003135616. [Last accessed on 2021 Dec 04].
46.	Biggs JB, Tang CS. Teaching for Quality Learning at University: What the Student Does. 4^th ed. Maidenhead, England New York, NY: McGraw-Hill, Society for Research into Higher Education & Open University Press; 2011.
47.	Bonwell CC, Eison JA. Active Learning: Creating Excitement in the Classroom. Washington, DC: School of Education and Human Development, George Washington University; 1991.
48.	Kolb DA, Rubin IM, McIntyre JM. Organizational Psychology: Readings on Human Behavior in Organizations. Prentice Hall; 1984.
49.	Bai J, Wang Y, Zhang P, Liu M, Wang P, Wang J, et al. Efficacy and safety of 3D print-assisted surgery for the treatment of pilon fractures: A meta-analysis of randomized controlled trials. J Orthop Surg Res 2018;13:283.
50.	Kong X, Nie L, Zhang H, Wang Z, Ye Q, Tang L, et al. Do Three-dimensional visualization and three-dimensional printing improve hepatic segment anatomy teaching? A randomized controlled study. J Surg Educ 2016;73:264-9.
51.	Langridge B, Momin S, Coumbe B, Woin E, Griffin M, Butler P. Systematic review of the use of 3-dimensional printing in surgical teaching and assessment. J Surg Educ 2018;75:209-21.
52.	Ratka A. Empathy and the development of affective skills. AJPE 2018;82:7192. doi: 10.5688/ajpe7192.
53.	Khot Z, Quinlan K, Norman GR, Wainman B. The relative effectiveness of computer-based and traditional resources for education in anatomy. Anat Sci Educ 2013;6:211-5.
54.	Fried CB. In-class laptop use and its effects on student learning. Comput Educ 2008;50:906-14.
55.	Abarghouie MH, Omid A, Ghadami A. Effects of virtual and lecture-based instruction on learning, content retention, and satisfaction from these instruction methods among surgical technology students: A comparative study. J Educ Health Promot 2020;9:296. doi: 10.4103/jehp.jehp_634_19.
56.	Rajprasath R, Kumar VD, Murugan M, Goriparthi BP, Devi R. Evaluating the effectiveness of integrating radiological and cross-sectional anatomy in first-year medical students–A randomized, crossover study. J Educ Health Promot 2020;9:16. doi: 10.4103/jehp.jehp_325_19.