Citations

ABSTRACT Following the introduction of meta‐analytic methodology into anatomical research, anatomical meta‐analyses have increased substantially. However, extremely high statistical heterogeneity is frequently observed in these studies, while its implications remain insufficiently discussed within anatomical research. The present study investigated the current state and patterns of heterogeneity in anatomical meta‐analyses and explored the interpretive implications of heterogeneity in anatomical evidence synthesis. A PubMed search was performed on May 21, 2026, using the title‐based search strategy: ((meta‐analysis[Title]) OR (meta analysis[Title])) AND (anatomy[Title]). Anatomical meta‐analyses focused on human structural anatomy were included. Reported I 2 values were extracted and descriptively analyzed by overall distribution and anatomical category. A total of 132 studies were identified, of which 61 anatomical meta‐analyses with analyzable heterogeneity data were included. The mean reported I 2 value was 95.27% (range 41%–100%), with a median I 2 of 98.77%. Most studies demonstrated extreme heterogeneity, with 86.9% reporting I 2 values exceeding 90%. Category‐specific analysis demonstrated consistently elevated heterogeneity across anatomical systems, including skeletal structures (mean I 2 = 99%), peripheral nerves (mean I 2 = 95%), and vascular anatomy studies (mean I 2 = 94.56%). Despite this, pooled prevalence estimates were frequently reported with highly precise numerical values and narrow confidence intervals. Extreme statistical heterogeneity is highly prevalent across anatomical meta‐analyses and appears to represent a widespread characteristic of anatomical synthesis research rather than an isolated statistical phenomenon. Although such heterogeneity likely reflects genuine biological and methodological variability, pooled anatomical estimates should be interpreted with caution, particularly when highly precise numerical estimates are reported despite substantial interstudy inconsistency. These findings highlight the importance of transparent heterogeneity reporting and anatomically stratified approaches in future anatomical meta‐analyses.

ABSTRACT The term “clinical anatomy” is widely used in education and research, yet its conceptual boundaries continue to be interpreted in various ways. Prior consensus‐based efforts have emphasized integration, collaboration, and clinical relevance as central features of the field and have provided an important foundation for interdisciplinary engagement. At the same time, ongoing changes in academic structure, medical education, and interdisciplinary biomedical science raise important questions regarding how clinical anatomy can sustain its scientific identity and long‐term relevance. Building upon prior discussions, this article argues that the continued maturation of clinical anatomy depends on the integration of conceptual frameworks with the sustained production of rigorous, reproducible, and clinically meaningful scholarly contributions. Historical and contemporary examples alike demonstrate that the influence of clinical anatomy has been shaped through contributions that directly advanced clinical science and practice. Accordingly, continued emphasis on methodological rigor, reproducibility, clinically meaningful contribution, and educational accountability may be essential to the field's future development and relevance.

ABSTRACT Although ablation of the greater splanchnic nerve is now being used to treat some patients with heart failure, the anatomical relationships between this nerve and the adjacent posterior intercostal veins used for the procedure are not well elucidated. Therefore, the present anatomical study was performed. The anatomy and relationships of the right GSN and the azygos vein were investigated in 50 adult anatomical donors. In the supine position, the anterior wall of the thorax was removed, and the relationship between the azygos vein and its tributaries and the overlying GSN was observed and documented with quantitation of the distances between these structures. At the T7, T8, and T9 vertebral levels, the mean distance between the GSN and the azygos vein was 3.05, 2.35, and 1.62 cm, respectively. We found that the closest distance between the GSN and the azygos vein was at the T9 vertebral level, with a mean distance of 1.62 cm. Therefore, for the shortest distance between vein and GSN, this level should also be considered for ablation level. Such additional anatomical data can help improve patient outcomes and decrease the complication rates of this procedure.

Since its introduction into medical terminology by Lord Henry Cohen in 1941, the term “neurapraxia” has become established in the neurological and neurosurgical lexicon, although it is often misused or misspelled. It denotes a transient dysfunction of a peripheral nerve, as distinct from axonotmesis and neurotmesis, which describe more significant structural injuries to a peripheral nerve. To expand our understanding of neurapraxia, it is necessary to examine the phenomenon in both temporal and spatial contexts. This study examines neurapraxia in: (A) Time—(1) the origins of the term neurapraxia and (2) the time-course of a neurapraxic injury and its recovery, and (B) Space—(3) the microstructure of a neurapraxic injury and (4) the locations of neurapraxic injuries within the peripheral nervous system. We demonstrate that the term neurapraxia encompasses both a temporal and a spatial definition. In time, it applies to transient peripheral nerve palsy, from which recovery occurs before there is sufficient time for axonal regeneration, typically within a few weeks. In space, there is a histopathological change limited to localized demyelination in nerves lined by epineurium and myelinated by Schwann cells. Nerves distal to the spine qualify as nerves to which the term neurapraxia can apply; however, cranial nerves and spinal nerve roots (including cauda equina) are inconsistent with this owing to the variability in myelinating cells along their course (oligodendroglia proximally, i.e., central glial segment), the absence of an epineurial covering, and exposure to cerebrospinal fluid.

ABSTRACT At the 42nd Annual Meeting of the American Association of Clinical Anatomists (AACA) in Bellevue, Washington, June 2025, two inaugural events—the Clinical Anatomy Fireside Chat (CAFC) and the Clinical Anatomy Symposium: Head and Neck 2025 (CAS)—fostered rich dialogue on the evolving role and operational definition of clinical anatomy. Experts from various clinical and anatomical disciplines explored the meaning of clinical anatomy, highlighting the absence of a universal definition despite its frequent use in education and research. Through these interdisciplinary discussions, a consensus emerged: clinical anatomy is not defined solely by the possession of clinical credentials but by the integration of anatomical knowledge and clinical relevance, achieved most effectively through collaboration. Clinical anatomy education and research require different depths of clinical knowledge depending on the audience and objective, and meaningful collaboration can bridge gaps in expertise. The symposium further illustrated that high‐quality clinical anatomy emerges from mutual respect and reciprocal insight between clinicians and anatomists. This article presents a consensus statement developed by AACA representatives and invited speakers, affirming that collaboration is not only foundational to the practice of clinical anatomy but also fundamental to its definition. These conclusions aim to guide future educational models, research strategies, and interdisciplinary partnerships in the field of clinical anatomy.

ABSTRACT Determining an appropriate sample size in human cadaveric studies remains a long‐standing and unresolved challenge. Unlike other basic science fields, anatomical research is constrained by factors such as limited human donor availability, cultural considerations, and ethical restrictions. Despite these limitations, researchers are often asked to justify sample sizes, yet no standardized guidelines currently exist. To quantitatively assess sample sizes in recent human cadaveric studies and propose evidence‐based recommendations for future research, a PubMed search was conducted on February 26, 2024, using the term human cadaveric study . The articles published in 2023 and 2024 were screened, yielding 770 eligible studies. Data extracted included the total sample size, number of classified groups, and journal impact factor (IF). Descriptive statistics, linear regression, and correlation analyses were performed. Continuous variables were summarized using medians and interquartile ranges (IQR). The median sample size was 11.5 (IQR: 7–20), and 47.9% of studies used 10 or fewer specimens. The median number of classified groups was 3 (IQR: 2–4). Linear regression showed that studies dividing specimens into 2–6 groups often failed to meet the recommended sample size per group based on regression modeling. No significant correlation was found between sample size and journal IF ( r = −0.062, p = 0.115). Most cadaveric studies rely on small sample sizes due to inherent constraints, yet many still attempt a subgroup analysis without sufficient statistical power. Although flexibility is essential in anatomical research, we recommend a minimum total sample size of 10 for basic studies and at least five samples per group for those involving classification. Cadaveric sample size alone does not predict journal impact, highlighting the importance of methodological rigor over quantity.

ABSTRACTMost discussions about discrimination and bias in anatomical research papers have been limited to terminology relating to race/ethnicity and gender/sex. However, as editors of anatomical journals, the authors of this article have frequently observed broader instances of potential discrimination and bias within anatomical research. These often stem from differences among authors' backgrounds, traditions, cultures, religions, provenance/origins, and workplace affiliations. In view of the limited discourse on this topic, we seek in this article to establish a consensus among editors of anatomical journals and to propose new Guidelines Against Discrimination and Bias in Anatomical Research Papers (GDBARP). We have identified multiple factors that can contribute to discrimination and bias, underscoring the need for greater awareness and proactive measures. It is imperative in anatomical research to respect authors, reviewers, and editors regardless of their background, culture, traditions, sex, ethnicity, language, religion, or ethical perspectives.

ABSTRACT Anatomy education is a cornerstone of medical training and relies on cadaveric dissection and 2D illustrations. Technological advancements and integrated curricula have reduced the focus on detailed anatomy and challenged educators to engage Generation Z learners with interactive, tech‐driven methods. Advanced imaging and artificial intelligence (AI) offer a solution, providing virtual dissection simulations and personalized learning tools that mimic 3D anatomy and adapt to individual student needs. Machine learning, a subset of AI, enhances this process by enabling predictive analytics, adaptive feedback, and tailored learning pathways based on performance data, significantly improving anatomical comprehension. Despite its benefits, AI integration raises concerns about over‐reliance on technology, biases, and diminished human interaction in training. This review examines AI's transformative potential in anatomy education while emphasizing the need for balanced implementation and ethical oversight. A systematic review following PRISMA guidelines was conducted, utilizing PubMed and backward citation searches. The search yielded 56 studies, with 47 additional articles from citations, resulting in 61 included studies. These explored AI applications such as virtual dissection simulations, machine learning algorithms for adaptive feedback, and gamified learning experiences, which were shown to enhance engagement, personalize learning, and improve anatomical understanding. Concerns about over‐reliance on AI and the loss of human interaction were also raised. AI has the potential to enhance anatomy education, but careful consideration of ethical and practical implications is essential. A balanced approach combining traditional methods with AI and robust oversight is crucial for effective integration.