The prevalence of the azygos lobe: A meta‐analysis of 1,033,083 subjects

Yurasakpong, Laphatrada; Yammine, Kaissar; Limpanuparb, Taweetham; Janta, Sirorat; Chaiyamoon, Arada; Kruepunga, Nutmethee; Meemon, Krai; Suwannakhan, Athikhun

doi:10.1002/ca.23737

Cited by 20 publications

(19 citation statements)

References 63 publications

(47 reference statements)

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“…In this study, we took advantage of an open‐access COVID‐19 CT dataset to study the prevalences of six well‐known thoracic anatomical variants in the thorax. We found that the AL was present in 0.8% of COVID‐19 patients, more than twice the global prevalence (Yurasakpong et al, 2021 ). However, this finding alone is not sufficient to demonstrate that individuals with an AL are more predisposed to COVID‐19 infection than others; the finding could be due to the use of different imaging modalities.…”

Section: Discussionmentioning

confidence: 64%

“…However, this finding alone is not sufficient to demonstrate that individuals with an AL are more predisposed to COVID‐19 infection than others; the finding could be due to the use of different imaging modalities. In our previous work, we found that most studies used X‐ray to diagnose an AL, and the prevalence of AL obtained from X‐ray studies (2.6%) was significantly lower than that from CT studies (6.7%) (Yurasakpong et al, 2021 ), suggesting that radiographs are less sensitive in detecting the AL. The TB was present in only two patients, a prevalence of 0.2%, which is five times less common than the global average of 1.0% (Wong et al, 2021 ).…”

Section: Discussionmentioning

confidence: 90%

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Anatomical variants identified on chest computed tomography of 1000+ COVID‐19 patients from an open‐access dataset

et al. 2022

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Chest computed tomography (CT) has been the preferred imaging modality during the pandemic owing to its sensitivity in detecting COVID‐19 infections. Recently, a large number of COVID‐19 imaging datasets have been deposited in public databases, leading to rapid advances in COVID‐19 research. However, the application of these datasets beyond COVID‐19‐related research has been little explored. The authors believe that they could be used in anatomical research to elucidate the link between anatomy and disease and to study disease‐related alterations to normal anatomy. Therefore, the present study was designed to investigate the prevalence of six well‐known anatomical variants in the thorax using open‐access CT images obtained from over 1000 Iranian COVID‐19 patients aged between 6 and 89 years (60.9% male and 39.1% female). In brief, we found that the azygos lobe, tracheal bronchus, and cardiac bronchus were present in 0.8%, 0.2%, and 0% of the patients, respectively. Variations of the sternum, including sternal foramen, episternal ossicles, and sternalis muscle, were observed in 9.6%, 2.9%, and 1.5%, respectively. We believe anatomists could benefit from using open‐access datasets as raw materials for research because these datasets are freely accessible and are abundant, though further research is needed to evaluate the uses of other datasets from different body regions and imaging modalities. Radiologists should also be aware of these common anatomical variants when examining lung CTs, especially since the use of this imaging modality has increased during the pandemic.

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Section: Discussionmentioning

confidence: 64%

Section: Discussionmentioning

confidence: 90%

Anatomical variants identified on chest computed tomography of 1000+ COVID‐19 patients from an open‐access dataset

et al. 2022

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“…In this article, we introduced the CATAM rubric and used it to critically appraise a recently published anatomical MA (Kacprzyk et al, 2020). There have been other anatomical MAs recently published (Aldabe et al, 2019; Bellier et al, 2020; Berthaume & Bull, 2021; Cheruiyot et al, 2021; Dreher et al, 2018; Graves et al, 2017; Harvie et al, 2019; Koziej et al, 2020; Morelli et al, 2019; Nallikuzhy et al, 2018; Roberts et al, 2021; Sirico et al, 2019; Solewski et al, 2021; Stefura et al, 2018; Tomaszewska et al, 2018; Tomaszewska et al, 2018; Tomaszewski et al, 2017; Tomaszewski et al, 2017; Vikse et al, 2016a, 2016b; Whitley et al, 2020; Yammine, 2013, 2014b, 2014c, 2014d; Yammine et al, 2015; Yurasakpong et al, 2021). We believe that the running paper that we used is an exemplary anatomical MA (Kacprzyk et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…Including the sample size allows the reader to quickly compare sample sizes between different MAs of the same topic (if previous ones have been published). For two recent examples of anatomical MAs that reported their sample sizes in the titles, see the papers by Kacprzyk et al (2020) and Yurasakpong et al (2021). The running paper title meets our aforementioned criteria because it states that it is a MA and also describes the purpose of the study, which is to analyze the “variations and morphometric features” of the vermiform appendix (Kacprzyk et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

The Critical Appraisal Tool for Anatomical Meta‐analysis: A framework for critically appraising anatomical meta‐analyses

et al. 2022

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The hallmark of evidence‐based medicine is the meta‐analysis (MA). For much of its rich history, the field of anatomy has been dominated by descriptive, cadaveric studies. In the last two decades, quantitative measurements and statistical analyses have frequently accompanied such studies. These studies have directly led to the publication of anatomical MAs, which have ushered in the exciting field of evidence‐based anatomy. Although critical appraisal tools exist for clinical MAs, none of them are specifically tailored for anatomical MAs. Therefore, the purpose of this article is to provide a framework by which clinical anatomists and others can critically appraise anatomical MAs using the Critical Appraisal Tool for Anatomical Meta‐analysis (CATAM). Using a running example from a recently published MA, we show how to use the CATAM rubric in a step‐by‐step fashion. Each scored section of the CATAM rubric is summated into a total score (maximum 50 points). This score is then referenced to a conversion chart, which assigns a qualitative value to the MA in a range from “very good” to “poor.” Future studies can investigate the interrater reliability of the instrument, and possibly subject the CATAM rubric to a Delphi panel. As anatomical MAs become more commonplace at surgical grand rounds and journal clubs in academic medical centers throughout the world, we hope that the CATAM rubric can help facilitate meaningful discussions about the quality and clinical relevance of anatomical MAs.

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“…However, a recent study [20] documented a very high prevalence of the stellate type at 25%, although it is worth noting that only 24 skulls were investigated. Overestimation caused by small sample size is known as the small-study effect [21], which reiterates that appropriate sample size is crucial when performing anatomical studies. Another factor which leads to higher heterogeneity between studies is inter-observer variability.…”

Section: Discussionmentioning

confidence: 99%

Classification and Morphometric Features of Pterion in Thai Population with Potential Sex Prediction

et al. 2021

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Background and Objectives: The landmark for neurosurgical approaches to access brain lesion is the pterion. The aim of the present study is to classify and examine the prevalence of all types of pterion variations and perform morphometric measurements from previously defined anthropological landmarks. Materials and methods: One-hundred and twenty-four Thai dried skulls were investigated. Classification and morphometric measurement of the pterion was performed. Machine learning models were also used to interpret the morphometric findings with respect to sex and age estimation. Results: Spheno-parietal type was the most common type (62.1%), followed by epipteric (11.7%), fronto-temporal (5.2%) and stellate (1.2%). Complete synostosis of the pterion suture was present in 18.5% and was only present in males. While most morphometric measurements were similar between males and females, the distances from the pterion center to the mastoid process and to the external occipital protuberance were longer in males. Random forest algorithm could predict sex with 80.7% accuracy (root mean square error = 0.38) when the pterion morphometric data were provided. Correlational analysis indicated that the distances from the pterion center to the anterior aspect of the frontozygomatic suture and to the zygomatic angle were positively correlated with age, which may serve as basis for age estimation in the future. Conclusions: Further studies are needed to explore the use of machine learning in anatomical studies and morphometry-based sex and age estimation. Thorough understanding of the anatomy of the pterion is clinically useful when planning pterional craniotomy, particularly when the position of the pterion may change with age.

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The prevalence of the azygos lobe: A meta‐analysis of 1,033,083 subjects

Cited by 20 publications

References 63 publications

Anatomical variants identified on chest computed tomography of 1000+ COVID‐19 patients from an open‐access dataset

Anatomical variants identified on chest computed tomography of 1000+ COVID‐19 patients from an open‐access dataset

The Critical Appraisal Tool for Anatomical Meta‐analysis: A framework for critically appraising anatomical meta‐analyses

Classification and Morphometric Features of Pterion in Thai Population with Potential Sex Prediction

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