Radiation-free 3D head shape and volume evaluation after endoscopically assisted strip craniectomy followed by helmet therapy for trigonocephaly

Jong, Guido de; Tolhuisen, Manon L.; Meulstee, Jene W.; Heijden, Ferdinand van der; Lindert, Erik van; Borstlap, W.A.; Maal, T.J.J.; Delye, Hans

doi:10.1016/j.jcms.2017.02.007

Cited by 15 publications

(20 citation statements)

References 20 publications

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“…Prior to data sampling, each 3D stereophotograph was manually positioned in the sella turcica-nasion orientation using the age specific computed cranial focal point 5 , 35 . Subsequently, data sampling was performed to ensure a standardized representation of each 3D stereophotograph.…”

Section: Methodsmentioning

confidence: 99%

Combining deep learning with 3D stereophotogrammetry for craniosynostosis diagnosis

Jong

Bijlsma

Meulstee

et al. 2020

Sci Rep

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Craniosynostosis is a condition in which cranial sutures fuse prematurely, causing problems in normal brain and skull growth in infants. To limit the extent of cosmetic and functional problems, swift diagnosis is needed. The goal of this study is to investigate if a deep learning algorithm is capable of correctly classifying the head shape of infants as either healthy controls, or as one of the following three craniosynostosis subtypes; scaphocephaly, trigonocephaly or anterior plagiocephaly. In order to acquire cranial shape data, 3D stereophotographs were made during routine pre-operative appointments of scaphocephaly (n = 76), trigonocephaly (n = 40) and anterior plagiocephaly (n = 27) patients. 3D Stereophotographs of healthy infants (n = 53) were made between the age of 3–6 months. The cranial shape data was sampled and a deep learning network was used to classify the cranial shape data as either: healthy control, scaphocephaly patient, trigonocephaly patient or anterior plagiocephaly patient. For the training and testing of the deep learning network, a stratified tenfold cross validation was used. During testing 195 out of 196 3D stereophotographs (99.5%) were correctly classified. This study shows that trained deep learning algorithms, based on 3D stereophotographs, can discriminate between craniosynostosis subtypes and healthy controls with high accuracy.

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Section: Methodsmentioning

confidence: 99%

Combining deep learning with 3D stereophotogrammetry for craniosynostosis diagnosis

Jong

Bijlsma

Meulstee

et al. 2020

Sci Rep

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“…Three-dimensional photography as an alternative to radiation-based techniques is a well-established method, which reliably allows assessment of volumetric and linear dimensions. [24][25][26][27][28][29] To avoid unnecessary radiation exposure and its inherit risks, 30,31 all radiation-based investigations to assess nonsyndromic children, such as CT or radiography, were abandoned in our center more than a decade ago.…”

Section: Discussionmentioning

confidence: 99%

Quantitative and qualitative comparison of morphometric outcomes after endoscopic and conventional correction of sagittal and metopic craniosynostosis versus control groups

Schulz

Liebe-Püschel

Seelbach

et al. 2021

Neurosurgical Focus

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OBJECTIVE Surgical correction for sagittal and metopic craniosynostosis (SCS and MCS) aims to alter the abnormal cranial shape to resemble that of the normal population. The achieved correction can be assessed by morphometric parameters. The purpose of the presented study was to compare craniometric parameters of control groups to those same parameters after endoscopic and conventional (open) correction. METHODS The authors identified 4 groups of children undergoing surgical treatment for either SCS or MCS, with either endoscopic (SCS, n = 17; MCS, n = 16) or conventional (SCS, n = 29; MCS, n = 18) correction. In addition, normal control groups of nonaffected children who were 6 (n = 30) and 24 (n = 18) months old were evaluated. For all groups, several craniometric indices calculated from 3D photographs were compared for quantitative analysis. For qualitative comparison, averages of all 3D photographs were generated for all groups and superimposed to visualize relative changes. RESULTS For children with SCS, the cephalic index and coronal circumference index significantly differed preoperatively from those of the 6-month normal controls. The respective postoperative values were similar to those of the 24-month normal controls after both endoscopic and conventional correction. Similarly, for children with MCS, indices for circumference and diagonal dimension that were significantly different preoperatively became nonsignificantly different from those of 24-month normal controls after both endoscopic and conventional correction. The qualitative evaluation of superimposed average 3D head shapes confirmed changes toward normal controls after both treatment modalities for SCS and MCS. However, in SCS, the volume gain, especially in the biparietal area, was more noticeable after endoscopic correction, while in MCS, relative volume gain of the bilateral forehead was more pronounced after conventional correction. The average 3D head shapes matched more homogeneously with the average of normal controls after endoscopic correction for SCS and after conventional correction for MCS. CONCLUSIONS This quantitative analysis confirms that the performed surgical techniques of endoscopic and conventional correction of SCS and MCS alter the head shape toward those of normal controls. However, in a qualitative evaluation, the average head shape after endoscopic technique for SCS and conventional correction for MCS appears to be closer to that of normal controls than after the alternative technique. This study reports on morphometric outcomes after craniosynostosis correction. Only an assessment of the whole multiplicity of outcome parameters based on multicenter data acquisition will allow conclusions of superiority of one surgical technique.

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“…We defined the origin of the trimmed 3D mesh as the center of mass by averaging all vertices, similar to the published computed cranial focal point. 24 Point zero of the measurement plane (P.0) was created where the y-axis intersects with the measurement plane.…”

Section: Landmarkingmentioning

confidence: 99%

Correction of trigonocephaly after endoscopic strip craniectomy with postoperative helmet orthosis therapy: a 3D stereophotogrammetric study

Elawadly

Smith

Borghi

et al. 2022

Journal of Neurosurgery: Pediatrics

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OBJECTIVE Endoscopic strip craniectomy with postoperative helmet orthosis therapy (ESCH) has emerged as a less invasive alternative to fronto-orbital remodeling for correction of trigonocephaly. However, there is no standardized objective method for monitoring morphological changes following ESCH. Such a method should be reproducible and avoid the use of ionizing radiation and general anesthesia for diagnostic imaging. The authors analyzed a number of metrics measured using 3D stereophotogrammetry (3DSPG) following ESCH, an imaging alternative that is free of ionizing radiation and can be performed on awake children. METHODS 3DSPG images obtained at two time points (perisurgical and 1-year follow-up [FU]) of children with metopic synostosis who had undergone ESCH were analyzed and compared to 3DSPG images of age-matched control children without craniofacial anomalies. In total, 9 parameters were measured, the frontal angle and anteroposterior volume in addition to 7 novel parameters: anteroposterior area ratio, anteroposterior width ratios 1 and 2, and right and left anteroposterior diagonal ratios 30 and 60. RESULTS Six eligible patients were identified in the operated group, and 15 children were in the control group. All 9 parameters differed significantly between perisurgical and age-matched controls, as well as from perisurgical to FU scans. Comparison of FU scans of metopic synostosis patients who underwent surgery to scans of age-matched controls without metopic synostosis revealed that all parameters were statistically identical, with the exception of the right anteroposterior diagonal ratio 30, which was not fully corrected in the treated patients. The left anterior part of the head showed the most change in surface area maps. CONCLUSIONS In this pilot study, ESCH showed satisfactory results at 1 year, with improvements in all measured parameters compared to perisurgical results and normalization of 8 of 9 parameters compared to an age-matched control group. The results indicate that these parameters may be useful for craniofacial units for monitoring changes in head shape after ESCH for trigonocephaly and that 3DSPG, which avoids the use of anesthesia and ionizing radiation, is a satisfactory monitoring method.

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Radiation-free 3D head shape and volume evaluation after endoscopically assisted strip craniectomy followed by helmet therapy for trigonocephaly

Cited by 15 publications

References 20 publications

Combining deep learning with 3D stereophotogrammetry for craniosynostosis diagnosis

Combining deep learning with 3D stereophotogrammetry for craniosynostosis diagnosis

Quantitative and qualitative comparison of morphometric outcomes after endoscopic and conventional correction of sagittal and metopic craniosynostosis versus control groups

Correction of trigonocephaly after endoscopic strip craniectomy with postoperative helmet orthosis therapy: a 3D stereophotogrammetric study

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