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This study analyzed imaging data from 192 skeletally matured patients… Both cone-beam computed tomography and 3dMD photographs…
3dMDhead images were obtained preoperatively and postoperatively at 3 weeks, 3 months, 1 year, and 2 years. Head circumference, cephalic index, scaphocephalic index (SCI), frontal bossing index (FBI), occipital bullet index (OBI), and vertex narrowing index (VNI) were measured automatically using the 3dMDvultus Craniometrics Calculator.
3dMD images of cleft patients were captured under standardized conditions between 2016 and 2022 and maintained in the database of the Amalia Cleft Palate and Craniofacial Unit of the Radboudumc, Nijmegen, the Netherlands.
An objective plagiocephaly head-shape assessment system aligning with physician-made clinical diagnoses.
These findings may offer further insight to clinicians, educators, and caregivers into the social challenges faced by cleft individuals.
408 patients born between 1991 and 2019, with diagnosed non-syndromic sagittal synostosis, whom underwent FBR, ESC, or SAC in Erasmus MC Sophia Children’s Hospital, and had at least one post-operative 3dMDhead photogrammetry image taken before the age of six, were considered for this study.
Date: October 2024. Source: 3DBodyTech Conference, Lugano, Switzerland. Presenters: Rami R HALLAC, UT Southwestern Medical Center and Children’s Health, Dallas TX, USA, and Chris LANE, 3dMD. Rami R HALLAC Background: Dr. Hallac is an imaging scientist at Children’s Health and an associate professor at UT Southwestern Medical Center. Utilizing 3D imaging, modelling and printing, Dr.…
We collected and assessed 3dMDface images of 115 consecutive patients who underwent primary repair between 2017 and 2019. 3dMD images were taken preoperatively, immediately postoperatively and at a first and second follow-up interval, occurring at an average year of 0.6 and 5.3 years, respectively.
SHAPE reads in a patient’s 3D photogram, automatically places a set of craniofacial landmarks, allows for their manual confirmation and correction, and automatically computes both a series of standard clinical craniofacial measurements and machine learning-based metrics of head development prior to building an analysis report for upload to the patient’s electronic medical record.