Dataset Information

Objective analysis of facial bone fracture CT images using curvature measurement in a surface mesh model.

ABSTRACT: The human facial skeleton consists of multiple segments and causes difficulty during analytic processes. We developed image analysis software to quantify the amount of injury and validate the smooth curvature of the surface after facial bone reduction surgery. Three-dimensional computed tomography images of facial bone were obtained from 40 patients who had undergone open reduction surgery to treat unilateral zygomaticomaxillary fractures. Analytic software was developed based on the discrete curvature of a triangular mesh model. The discrete curvature values were compared before and after surgery using two regions of interest. For the inferior orbital rim, the weighted average of curvature changed from 0.543 ± 0.034 to 0.458 ± 0.042. For the anterior maxilla, the weighted average of curvature changed from 0.596 ± 0.02 to 0.481 ± 0.031, showing a significant decrement (P < 0.05). The curvature was further compared with the unaffected side using the Bray-Curtis similarity index (BCSI). The BCSI of the inferior orbital rim changed from 0.802 ± 0.041 to 0.904 ± 0.015, and that for the anterior maxilla changed from 0.797 ± 0.029 to 0.84 ± 0.025, demonstrating increased similarity (P < 0.05). In computational biology, adequate analytic software is crucial. The newly developed software demonstrated significant differentiation between pre- and postoperative curvature values. Modification of formulas and software will lead to further advancements.

SUBMITTER: Kim J

PROVIDER: S-EPMC9894972 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Objective analysis of facial bone fracture CT images using curvature measurement in a surface mesh model.

Kim Jeenam J Seo Chaneol C Yoo Jung Hwan JH Choi Seung Hoon SH Ko Kwang Yeon KY Choi Hyung Jin HJ Lee Ki Hyun KH Choi Hyungon H Shin Donghyeok D Kim HyungSeok H Lee Myung Chul MC

Scientific reports 20230202 1

The human facial skeleton consists of multiple segments and causes difficulty during analytic processes. We developed image analysis software to quantify the amount of injury and validate the smooth curvature of the surface after facial bone reduction surgery. Three-dimensional computed tomography images of facial bone were obtained from 40 patients who had undergone open reduction surgery to treat unilateral zygomaticomaxillary fractures. Analytic software was developed based on the discrete cu ...[more]

PMID: 36732582

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Project description:BackgroundVariation in imaging protocol, patient positioning, and the presence of artifacts can vary image quality in CT images used for radiotherapy planning. Automated methods for spatial resolution (SR) estimation exist but require further investigation and validation for wider adoption.PurposeTo validated previously existing algorithm for SR estimation and introduce improvements that make it robust to patient positioning, CT protocol, site, and artifacts.MethodA reference algorithm based on the previous gold standard was recreated and modified to improve robustness. The algorithms were tested on three different datasets: (1) a cylindrical ACR CT QC phantom scanned using a Siemens SOMATOM Definition Edge scanner and reconstructed using 61 different kernels, (2) a set of anthropomorphic phantoms scanned with the presence of artifacts common to clinical acquisitions such as blankets and immobilization devices, and (3) a clinical patient dataset of head and neck (HN) CT scans (nine patients) and spine/pelvis (10 patients). The robustness of both algorithms was tested on the clinical patient data.ResultsOver the range of tested kernels, both algorithms were accurate when the ground truth MTF f50 was within the range 0.2-0.7 mm-1 in the cylindrical phantom datasets with an RMS error of 10.3% and 3.8% for the reference and modified versions of the algorithm, respectively, as compared to the ground truth. In the anthropomorphic phantom datasets the reference algorithm showed an 8.4% and 30.0% difference from ground truth for the Pelvic and HN phantoms, respectively, while the modified algorithm showed 4.9% and 3.9% percent difference from ground truth. In the clinical dataset the reference algorithm estimated a mean f50 value of 0.21 ± 0.03 mm-1 and 0.25 ± 0.03 mm-1 for pelvis/spine while the reference algorithm estimated mean of 0.28 ± 0.02 and 0.29 ± 0.01 mm-1 for HN and pelvis/spine, respectively, as compared to the ground truth found to be 0.28 mm-1 on the cylindrical phantom.ConclusionThe SR algorithm was validated cylindrical/anthropomorphic phantoms and clinical CT scans. Further modifications were tested and showed improved accuracy in more challenging CT acquisitions.

Project description:ImportanceRepeated bone mineral density (BMD) testing to screen for osteoporosis requires resources. For patient counseling and optimal resource use, it is important for clinicians to know whether repeated BMD measurement (compared with baseline BMD measurement alone) improves the ability to discriminate between postmenopausal women who will and will not experience a fracture.ObjectiveTo assess whether a second BMD measurement approximately 3 years after the initial assessment is associated with improved ability to estimate fracture risk beyond the baseline BMD measurement alone.Design, setting, and participantsThe Women's Health Initiative is a prospective observational study. Participants in the present cohort study included 7419 women with a mean (SD) follow-up of 12.1 (3.4) years between 1993 and 2010 at 3 US clinical centers. Data analysis was conducted between May 2019 and December 2019.Main outcomes and measuresIncident major osteoporotic fracture (ie, hip, clinical spine, forearm, or shoulder fracture), hip fracture, baseline BMD, and absolute change in BMD were assessed. The area under the receiver operating characteristic curve (AU-ROC) for baseline BMD, absolute change in BMD, and the combination of baseline BMD and change in BMD were calculated to assess incident fracture risk discrimination during follow-up.ResultsOf 7419 participants, the mean (SD) age at baseline was 66.1 (7.2) years, the mean (SD) body mass index was 28.7 (6.0), and 1720 (23%) were nonwhite individuals. During the study follow-up (mean [SD] 9.0 [3.5] years after the second BMD measurement), 139 women (1.9%) experienced hip fractures, and 732 women (9.9%) experienced major osteoporotic fracture. In discriminating between women who experience hip fractures and those who do not, AU-ROC values were 0.71 (95% CI, 0.67-0.75) for baseline total hip BMD, 0.61 (95% CI, 0.56-0.65) for change in total hip BMD, and 0.73 (95% CI, 0.69-0.77) for the combination of baseline total hip BMD and change in total hip BMD. Femoral neck and lumbar spine BMD values had similar discrimination for hip fracture. For discrimination of major osteoporotic fracture, AU-ROC values were 0.61 (95% CI, 0.59-0.63) for baseline total hip BMD, 0.53 (95% CI, 0.51-0.55) for change in total hip BMD, and 0.61 (95% CI, 0.59-0.63) for the combination of baseline total hip BMD and change in total hip BMD. Femoral neck and lumbar spine BMD values had similar ability to discriminate between women who experienced major osteoporotic fracture and those who did not. Associations between change in bone density and fracture risk did not differ by subgroup, including diabetes, age, race/ethnicity, body mass index, or baseline BMD T score.Conclusions and relevanceThe findings of this study suggest that a second BMD assessment approximately 3 years after the initial measurement was not associated with improved discrimination between women who did and did not experience subsequent hip fracture or major osteoporotic fracture beyond the baseline BMD value alone and should not routinely be performed.

Dataset Information

Objective analysis of facial bone fracture CT images using curvature measurement in a surface mesh model.

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Objective analysis of facial bone fracture CT images using curvature measurement in a surface mesh model.

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