Introduction: Preoperative computed tomography (CT) evaluation of patients with nonsyndromic craniosynostosis (NSC) has focused on the bony cranial vault while ignoring the surrounding soft tissues. In this study, we posit that novel CT-derived temporal muscle and temporal fat pad morphomics (tissue thickness, area, and volume) can be used to calculate temporal morphomic indices (TMIs), which are unique to each NSC subtype (metopic, coronal, and sagittal) and divergent from normal individuals.
Methods: High-throughput image analysis was used to reconstruct the 3-dimensional anatomy and quantify a TMI. These steps were completed in a semiautomated method using algorithms programmed in MATLAB v13.0. Differences in TMI across various craniosynostosis subtypes were assessed using Wilcoxon nonparametric tests for both patients with NSC and a control cohort of patients with trauma.
Results: Using preoperative CT images, we evaluated 117 children with NSC from the University of Michigan Health System and 50 age-matched control patients between 1999 and 2011. Results indicate significant differences in TMI among the normal and NSC groups, with normal patients having significantly higher TMI values than patients with metopic, sagittal, and coronal synostosis. In addition, significant differences were found to exist between each craniosynostosis category.
Conclusions: Patients with craniosynostosis demonstrate diminished temporalis muscle and overlying fat pad volume and thickness compared with control patients. The unique changes in temporal morphomics presented in this article demonstrate not only that the bony calvaria is affected by craniosynostosis but also that there exist quantifiable aberrations in the temporalis muscle and temporal fat pad. The methodologies described offer a novel methodology to use pre-existing CT scans to glean additional preoperative information on the soft tissue characteristics of patients with craniosynostosis.
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http://dx.doi.org/10.1097/SAP.0b013e31826caf8d | DOI Listing |
JNCI Cancer Spectr
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Department of Epidemiology and Biostatistics, University of California, Irvine, CA, USA.
Background: Obesity, classified by body mass index (BMI), is associated with higher postmenopausal breast cancer (BCa) risk. Yet, the associations between abdominal visceral (VAT) and subcutaneous adipose tissue (SAT) with BCa are unclear.
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J Cosmet Dermatol
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Department of Dermatology, The Second Affiliated Hospital of Jiaxing University, Jiaxing, Zhejiang, People's Republic of China.
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J Biomed Opt
January 2025
Texas A&M University, Department of Biomedical Engineering, College Station, Texas, United States.
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January 2025
National Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Center, Beijing, China.
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