Features and networks of the mandible on computed tomography
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ABSTRACT:
SUBMITTER: Pham T
PROVIDER: S-EPMC10791540 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:ObjectivesData on normal mandibular development in the infant is lacking though essential to understand normal growth patterns and to discriminate abnormal growth. The aim of this study was to provide normal linear measurements of the mandible using computed tomography performed in infants from 0 to 2 years of age.Material and methods3D voxel software was used to calculate mandibular body length, mandibular ramus length, bicondylar width, bigonial width and the gonial angle. Intra- and inter-rater reliability was assessed for these measurements. They were found to be sufficient for all distances; intra-class correlation coefficients were all above 0.9. Regression analysis for growth modelling was performed.ResultsIn this multi-centre retrospective study, 109 CT scans were found eligible that were performed for various reasons (e.g. trauma, craniosynostosis, craniofacial abscesses). Craniosynostosis patients had larger mandibular measurements compared to non-craniosynostosis patients and were therefore excluded. Fifty-one CT scans were analysed.ConclusionsAnalysis showed that the mandible increases more in size vertically (the mandibular ramus) than horizontally (the mandibular body). Most of the mandibular growth occurs in the first 6 months.Clinical relevanceThese growth models provide insight into normal mandibular development in the first 2 years of life. This reference data facilitates discrimination between normal and abnormal mandibular growth.
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Project description:BackgroundSMARCA4-deficient non-small cell lung carcinoma (SD-NSCLC) is a relatively rare tumor, which occurs in 5-10% of NSCLC. Based on World Health Organization thoracic tumor classification system, SMARCA4-deficient undifferentiated tumor (SD-UT) is recognized as a separate entity from SD-NSCLC. Differentiation between SD-NSCLC and SD-UT is often difficult due to shared biological continuum, but often required for choosing appropriate treatment regimen. Therefore, the aim of our study was to identify the clinicopathologic, computed tomography (CT), and positron emission tomography (PET)-CT imaging features of SD-NSCLC.MethodsNine patients of pathologically confirmed SD-NSCLC were included in our analysis. We reviewed electronic medical records for clinical information, demographic features, CT, and PET-CT imaging features were analyzed.ResultsSmoking history and male predominance are observed in all patients with SD-NSCLC (n=9). On CT, SD-NSCLC appeared as relatively well-defined masses with lobulated contour (n=8) and peripheral location (n=7). Invasion of adjacent pleura or chest wall (n=7) were frequently observed, regardless of small tumor size. Four cases showed lymph node metastases. Among nine patients, three patients showed multiple bone metastases, and one patient showed lung-to-lung metastases.ConclusionsIn patient with SD-NSCLC, there was tendency for male smokers, peripheral location and invasion of adjacent pleural or chest wall invasion regardless of small tumor size, when compared to SD-UT.
| S-EPMC11009581 | biostudies-literature
Project description:BackgroundComputed tomography (CT) findings of dogs with discospondylitis have not been widely described despite increased availability of this imaging modality.ObjectivesDescribe the CT features of discospondylitis in a population of clinically affected dogs with discospondylitis diagnosed by magnetic resonance imaging (MRI).AnimalsForty-one dogs (63 affected discs) with MRI-identified discospondylitis presented to a single referral hospital between 2012 and 2022.MethodsRetrospective, single center, descriptive case series with analysis of MRI-identified discospondylitis sites and concomitant CT imaging. Computed tomographic features of MRI-affected sites including intervertebral disc space (IVDS), endplates, vertebral body, epidural space and paraspinal tissues were described.ResultsThe most frequently found changes were: (1) endplate involvement (87.3%) most frequently bilateral (94.5%), with erosion (61.9%) and multifocal osteolysis (67.3%); (2) periosteal proliferation adjacent to the IVDS (73%) and spondylosis (66.7%); and (3) vertebral body involvement (66.7%) involving one-third of the vertebra (85.7%) with multifocal osteolysis (73.5%). Other less prevalent features included an abnormal IVDS (narrowed or collapsed), sclerosis of the adjacent vertebral body or endplates, presence of disseminated idiopathic skeletal hyperostosis or vacuum artifact.Conclusions and clinical importanceWe determined that bilateral endplate erosion and periosteal proliferation were very common in dogs with discospondylitis. Careful evaluation of CT in all 3 planes (dorsal, sagittal, transverse) is necessary to identify an affected IVDS. These described CT features can aid in the diagnosis of discospondylitis in dogs but equivocal cases might still require MRI.
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Project description:Image-based algorithmic software segmentation is an increasingly important topic in many medical fields. Algorithmic segmentation is used for medical three-dimensional visualization, diagnosis or treatment support, especially in complex medical cases. However, accessible medical databases are limited, and valid medical ground truth databases for the evaluation of algorithms are rare and usually comprise only a few images. Inaccuracy or invalidity of medical ground truth data and image-based artefacts also limit the creation of such databases, which is especially relevant for CT data sets of the maxillomandibular complex. This contribution provides a unique and accessible data set of the complete mandible, including 20 valid ground truth segmentation models originating from 10 CT scans from clinical practice without artefacts or faulty slices. From each CT scan, two 3D ground truth models were created by clinical experts through independent manual slice-by-slice segmentation, and the models were statistically compared to prove their validity. These data could be used to conduct serial image studies of the human mandible, evaluating segmentation algorithms and developing adequate image tools.
| S-EPMC6350631 | biostudies-literature
Project description:BackgroundComputed tomography (CT) offers detailed cross-sectional images of internal anatomy for disease detection but carries a risk of solid cancer or blood malignancies due to exposure to X-ray radiation. This study aimed to develop a new method to quickly predict patient-specific organ doses from CT examinations by training neural networks (NNs) based on radiomics features.MethodsCT Digital Imaging and Communications in Medicine (DICOM) image data were exported to DeepViewer, a clinical autosegmentation software, to segment the regions of interest (ROIs) for patient organs. Radiomics feature extraction was performed based on the selected CT data and ROIs. Reference organ doses were computed using Monte Carlo (MC) simulations. Patient-specific organ doses were predicted by training a NN model based on radiomics features and reference doses. For the dose prediction performance, the relative root mean squared error (RRMSE), mean absolute percentage error (MAPE), and coefficient of determination (R2) were evaluated on the test sets. The robustness of the NN model was evaluated via the random rearrangement of patient samples in the training and test sets.ResultsThe maximal difference between the reference and predicted doses was less than 1 mGy for all investigated organs. The range of MAPE was 1.68% to 5.2% for head organs, 11.42% to 15.2% for chest organs, and 5.0% to 8.0% for abdominal organs; the maximal R2 values were 0.93, 0.86, and 0.89 for the head, chest, and abdominal organs, respectively.ConclusionsThe radiomics feature-based NN model can achieve accurate prediction of patient-specific organ doses at a high speed of less than 1 second using a single central processing unit, which supports its use as a user-friendly online clinical application.
| S-EPMC11485356 | biostudies-literature
Project description:ObjectivesNon-contrast computed tomography (NCCT) markers are robust predictors of parenchymal hematoma expansion in intracerebral hemorrhage (ICH). We investigated whether NCCT features can also identify ICH patients at risk of intraventricular hemorrhage (IVH) growth.MethodsPatients with acute spontaneous ICH admitted at four tertiary centers in Germany and Italy were retrospectively included from January 2017 to June 2020. NCCT markers were rated by two investigators for heterogeneous density, hypodensity, black hole sign, swirl sign, blend sign, fluid level, island sign, satellite sign, and irregular shape. ICH and IVH volumes were semi-manually segmented. IVH growth was defined as IVH expansion > 1 mL (eIVH) or any delayed IVH (dIVH) on follow-up imaging. Predictors of eIVH and dIVH were explored with multivariable logistic regression. Hypothesized moderators and mediators were independently assessed in PROCESS macro models.ResultsA total of 731 patients were included, of whom 185 (25.31%) suffered from IVH growth, 130 (17.78%) had eIVH, and 55 (7.52%) had dIVH. Irregular shape was significantly associated with IVH growth (OR 1.68; 95%CI [1.16-2.44]; p = 0.006). In the subgroup analysis stratified by the IVH growth type, hypodensities were significantly associated with eIVH (OR 2.06; 95%CI [1.48-2.64]; p = 0.015), whereas irregular shape (OR 2.72; 95%CI [1.91-3.53]; p = 0.016) in dIVH. The association between NCCT markers and IVH growth was not mediated by parenchymal hematoma expansion.ConclusionsNCCT features identified ICH patients at a high risk of IVH growth. Our findings suggest the possibility to stratify the risk of IVH growth with baseline NCCT and might inform ongoing and future studies.Clinical relevance statementNon-contrast CT features identified ICH patients at a high risk of intraventricular hemorrhage growth with subtype-specific differences. Our findings may assist in the risk stratification of intraventricular hemorrhage growth with baseline CT and might inform ongoing and future clinical studies.Key points• NCCT features identified ICH patients at a high risk of IVH growth with subtype-specific differences. • The effect of NCCT features was not moderated by time and location or indirectly mediated by hematoma expansion. • Our findings may assist in the risk stratification of IVH growth with baseline NCCT and might inform ongoing and future studies.
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Project description: Not available
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Project description:The present study aimed to describe the computed tomography (CT) imaging features of ovarian Brenner tumor for diagnostic accuracy and disease understanding. The CT imaging features of 9 cases of ovarian Brenner tumor confirmed by surgery and pathology were retrospectively analyzed and compared. Of the 9 cases of ovarian Brenner tumor, 3 were right located and 6 were left located with clear borders; 7 with round or oval shapes, while 2 were with irregular and lobulated morphology; 5 solid lesions presented with multiple scattered calcification shadows inside with moderate enhancement, while 3 cystic lesions were presented with mixed solid and cystic composition, and significant enhancement was identified in the solid component, but not in the cystic component. Furthermore, papillary projections inside and mild nodular enhancement were observed in one case of cystic lesion. The pathological analysis demonstrated that an epithelium nest composed the tumors with urothelial like cells and fibrous matrix. Of the 9 cases, 5 epithelial nests exhibited adeno-like cystic lumen without cell mitosis phase. All cases were diagnosed with benign ovarian Brenner tumor. Specific CT imaging features of ovarian Brenner tumor can be identified and pathological examinations are required for diagnosis confirmation.
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Project description:Variability in the x-ray tube current used in computed tomography may affect quantitative features extracted from the images. To investigate these effects, we scanned the Credence Cartridge Radiomics phantom 12 times, varying the tube current from 25 to 300 mA∙s while keeping the other acquisition parameters constant. For each of the scans, we extracted 48 radiomic features from the categories of intensity histogram (n = 10), gray-level run length matrix (n = 11), gray-level co-occurrence matrix (n = 22), and neighborhood gray tone difference matrix (n = 5). To gauge the size of the tube current effects, we scaled the features by the coefficient of variation of the corresponding features extracted from images of non-small cell lung cancer tumors. Variations in the tube current had more effect on features extracted from homogeneous materials (acrylic, sycamore wood) than from materials with more tissue-like textures (cork, rubber particles). Thirty-eight of the 48 features extracted from acrylic were affected by current reductions compared with only 2 of the 48 features extracted from rubber particles. These results indicate that variable x-ray tube current is unlikely to have a large effect on radiomic features extracted from computed tomography images of textured objects such as tumors.
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Project description:Plant vascular systems in the stem connect roots with aerial organs to move solutes containing minerals, nutrients as well as signaling molecules, and therefore, they play pivotal roles in plant growth and development. However, stem vascular systems, especially in crop species, have been poorly described since they are deeply embedded in the tissue. Here we describe a protocol to utilize micro-computed tomography (micro-CT) scanning to visualize vascular networks in the maize stem. The protocol covers sample fixation and staining with contrasting reagents, data acquisition using micro-CT, reconstructing three-dimensional (3D) models of stem inner structures and extraction of vascular networks from the model. This protocol can be easily applied to various types of species and organs/tissues.
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