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Defining Orientation of the Foot in WBCT using Hounsfield Units Analysis: Do Soft Tissues Skew the Measurements?
Research Type:
Level 4 – Case series
Introduction/Purpose:
Defining orientation axes of the foot typically requires full segmentation of bones from volumetric data, followed by geometric primitive fitting (GPF) or principal component analysis (PCA). This is either a time or computation heavy task. This study aimed to determine whether soft tissue weight influences the overall foot orientation in DICOM datasets using a simplified approach that involves selecting a region of interest and applying Hounsfield Unit (HU) thresholding. We hypothesized that, given the relatively even distribution and lower density of soft tissues, their inclusion would not significantly impact foot orientation.
Methods:
In this retrospective cross-sectional study, 14 feet from 7 individuals were analyzed using bilateral cone-beam weight-bearing CT (WBCT) scans. Cases with surgical metalwork were excluded. DICOM volumes were processed in 3D Slicer software. Each foot was isolated by defining a region of interest below the ankle joint line. Two segmentation thresholds were applied: one for bone and soft tissue (-500 to 3000 HU) and one for bone only (500 to 3000 HU). Segments were analyzed for volume, mean HU values, centroid position, Oriented Bounding Box (OBB) dimensions, and first PCA coordinates. Statistical analysis included unpaired Student’s t-tests, with significance set at p< 0.05. Statistical analysis was performed with EasyMedStat.
Results:
The vertical centroid coordinate was significantly lower in bone and soft tissue segments (-1159.53 ± 5.26) compared to bone only (-1162.12 ± 2.5), p< 0.001. Segment volumes were significantly larger when soft tissues were included (807.46 ± 145.29 vs. 61.62 ± 30.63, p< 0.001). Mean HU values were significantly lower in the bone and soft tissue segments (74.25 ± 59.21) compared to bone only (742.6 ± 45.2), p< 0.001. Significant differences were observed in OBB dimensions, with increased diameters in the bone and soft tissue segments (OBB diamx: 101.57 ± 14.9 vs. 83.18 ± 9.18, p< 0.001; OBB diamy: 116.1 ± 17.2 vs. 95.48 ± 8.79, p< 0.001). Centroid shifts, increased volume, and altered HU values highlight the impact of soft tissue inclusion on morphological assessment.
Conclusion:
Our main finding was that axial orientation of the foot volume was not affected by different levels of thresholding to include or not the soft tissues. However, the centroid was drawn more plantar with soft tissues. Thus, it would not be possible to reproducibly orientate the volume using HU thresholding other than to fix the sagittal plane. The limitations of this study are a small population without major deformities and the exclusion of metal implants. Future research should investigate deformed feet and explore whether upper HU thresholding can yield similar results in the presence of metal implants.
Journal Article
Your Chi-Square Test Is Statistically Significant: Now What?
Applied researchers have employed chi-square tests for more than one hundred years. This paper addresses the question of how one should follow a statistically significant chi-square test result in order to determine the source of that result. Four approaches were evaluated: calculating residuals, comparing cells, ransacking, and partitioning. Data from two recent journal articles were used to illustrate these approaches. A call is made for greater consideration of foundational techniques such as the chi-square tests.
Journal Article
TP1-3 Final phase of recruitment and statistics analysis plan for Dex-CSDH trial
ObjectivesReview recruitment progression and statistical analysis plan for Dex-CSDH trial.DesignA UK multi-centre, randomised, double-blind, placebo-controlled trial of dexamethasone versus placebo for CSDH.SubjectsSymptomatic, adult CSDH patients admitted to a participating neurosurgical unit.MethodsTrial participants receive a 2 week course of dexamethasone in addition to standard care, including surgery. The primary outcome measure is the modified Rankin Scale (mRS) at 6 months. An mRS of 0–3 requires the patient to be independently mobile and we have considered this a favourable outcome, with scores 4–6 (non-mobile) as unfavourable. The primary analysis will be performed on an intention-to-treat basis, estimating the absolute difference between the two treatment arms in the proportions achieving a favourable outcome. Secondary analysis will be done with an ordinal analysis of mRS scores and proportional odds logistic regression of the original mRS score adjusting for baseline covariates (age, GCS).Results629/750 patients (84%) have been recruited to the Dex-CSDH trial which is on-going as of 20-06-2018. Recruitment progress and follow-up at time of presentation will be reviewed alongside full statistical analysis plan.ConclusionsThe Dex-CSDH trial is drawing close to target following excellent recruitment across 22 UK centres. Transparent communication of the statistical analysis plan is essential prior to unblinding of the data. Up-to-date recruitment and primary endpoint completion rates will also be reviewed.
Journal Article
Key management ratios : the 100+ ratios every manager needs to know
Business ratios are the figures that provide management with targets and standards for their organisation. From earnings per share and cash flow to return on investment and sales to fixed assets ratios, this book guides managers through the key ratios at the heart of business practice.
Book
IDDF2025-ABS-0003 Value of systemic immunoinflammatory index, nutritional risk index, and triglyceride glucose index in predicting the condition and prognosis of patients with hyperlipidemic acute pancreatitis
BackgroundTo investigate the function and prognosis of pancreatitis in patients with hyperlipidemic acute pancreatitis based on the systemic immunoinflammatory index (SII), nutritional risk index (NRI), and triglyceride glucose index (TyG).MethodsA total of 300 hypertriglyceridemic acute pancreatitis (HTGAP) patients admitted to the General Hospital of Ningxia Medical University from January 2022 to June 2023 were selected and divided into the mild acute pancreatitis group (MAP group), moderately severe acute pancreatitis group (MSAP group), and severe acute pancreatitis group (SAP group) based on the disease severity. The SII, NRI, and TyG in the three sets of data were recorded and compared, and the value of SII, NRI, and TyG in predicting the occurrence of HTGAP was analyzed through the receiver operating characteristic (ROC) curve.ResultsThe SII and TyG in the SAP group (3259.4±2795.8, 4.5±1.1) were higher than those in the MSAP group (2563.7±1614.1, 4.3±0.8) and the MAP group (1991.1±1566.8, 4.1±0.8), and the differences were statistically significant (P<0.005). The area under the ROC curve of SII, NRI, and TyG combined to predict SAP occurrence was 0.705 (95% confidence interval, 0.632–0.778), the sensitivity and specificity were 70.8%and 66%, and the combination of the three could better predict the occurrence of HTGAP.ConclusionsSII, NRI, and TyG are related to the severity of HTGAP, and the combination of the three can better predict the occurrence of SAP.
Journal Article
The Oxford handbook of functional data analysis
\"As technology progresses, we are able to handle larger and larger datasets. At the same time, monitoring devices such as electronic equipment and sensors (for registering images, temperature, etc.) have become more and more sophisticated. This high-tech revolution offers the opportunity to observe phenomena in an increasingly accurate way by producing statistical units sampled over a finer and finer grid, with the measurement points so close that the data can be considered as observations varying over a continuum. Such continuous (or functional) data may occur in biomechanics (e.g. human movements), chemometrics (e.g. spectrometric curves), econometrics (e.g. the stock market index), geophysics (e.g. spatio-temporal events such as El Nino or time series of satellite images), or medicine (electro-cardiograms/electro-encephalograms). It is well known that standard multivariate statistical analyses fail with functional data. However, the great potential for applications has encouraged new methodologies able to extract relevant information from functional datasets. This Handbook aims to present a state of the art exploration of this high-tech field, by gathering together most of major advances in this area. Leading international experts have contributed to this volume with each chapter giving the key original ideas and comprehensive bibliographical information. The main statistical topics (classification, inference, factor-based analysis, regression modelling, resampling methods, time series, random processes) are covered in the setting of functional data. The twin challenges of the subject are the practical issues of implementing new methodologies and the theoretical techniques needed to expand the mathematical foundations and toolbox. The volume therefore mixes practical, methodological and theoretical aspects of the subject, sometimes within the same chapter. As a consequence, this book should appeal to a wide audience of engineers, practitioners and graduate students, as well as academic researchers, not only in statistics and probability but also in the numerous related application areas\"-- Provided by publisher.
Book
P255 Value of systemic immunoinflammatory index, and triglyceride glucose index in predicting the prognosis of patients with hyperlipidemic acute pancreatitis
ObjectiveTo investigate the function and prognosis of pancreatitis in patients with hyperlipidemic acute pancreatitis based on the systemic immunoinflammatory index (SII), nutritional risk index (NRI), and triglyceride glucose index (TyG).MethodsA total of 300 hypertriglyceridemic acute pancreatitis (HTGAP) patients admitted to the General Hospital of Ningxia Medical University from January 2022 to June 2023 were selected and divided into the mild acute pancreatitis group (MAP group), moderately severe acute pancreatitis group (MSAP group), and severe acute pancreatitis group (SAP group) based on the disease severity. The SII, NRI, and TyG in the three sets of data were recorded and compared, and the value of SII, NRI, and TyG in predicting the occurrence of HTGAP was analyzed through the receiver operating characteristic (ROC) curve.ResultsThe SII and TyG in the SAP group (3259.4±2795.8, 4.5±1.1) were higher than those in the MSAP group (2563.7±1614.1, 4.3±0.8) and the MAP group (1991.1±1566.8, 4.1±0.8), and the differences were statistically significant (P<0.005). The area under ROC curve of SII, NRI, and TyG combined to predict SAP occurrence was 0.705 (95% confidence interval, 0.632–0.778), the sensitivity and specificity were 70.8%and 66%, and the combination of the three could better predict the occurrence of HTGAP.ConclusionSII, NRI, and TyG are related to the severity of HTGAP, and the combination of the three can better predict the occurrence of SAP.
Journal Article