Diagnostic Performance and Additional Value of Elastosonography in Focal Breast Lesions: Statistical Correlation between Size-Dependant Strain Index Measurements, Multimodality-BI-RADS Score, and Histopathology in a Clinical Routine Setting

Objective. To evaluate the diagnostic benefit of real-time elastography (RTE) in clinical routine. Strain indices (SI) for benign and malignant tumors were assessed. Methods. 100 patients with 110 focal breast lesions were retrieved. Patients had mammography (MG), ultrasound (US), and, if necessary, MRI. RTE was conducted after ultrasound. Lesions were assessed with BI-RADS for mammography and ultrasound. Diagnosis was established with histology or follow-up. Results. SI for BI-RADS 2 was 1.71 ± 0.86. Higher SI (2.21 ± 1.96) was observed for BI-RADS 3 lesions. SI of BI-RADS 4 and 5 lesions were significantly higher (16.92 ± 20.89) and (19.54 ± 10.41). 31 malignant tumors exhibited an average SI of 16.13 ± 14.67; SI of benign lesions was 5.29 ± 11.87 (P value <0.0001). ROC analysis threshold was >3.8 for malignant disease. Sensitivity of sonography was 90.3% (specificity 78.5%). RTE showed a sensitivity of 87.1% (specificity 79.7%). Accuracy of all modalities combined was 96.8%. In BI-RADS 3 lesions RTE was able to detect all malignant lesions (sensitivity 100%, specificity 92.9%, and accuracy 93.9%). Conclusions. RTE increased sensitivity and specificity for breast cancer detection when used in combination with ultrasound.

Kernel density correlation based non-rigid point set matching for statistical model-based 2D/3D reconstruction

This paper presents a kernel density correlation based nonrigid point set matching method and shows its application in statistical model based 2D/3D reconstruction of a scaled, patient-specific model from an un-calibrated x-ray radiograph. In this method, both the reference point set and the floating point set are first represented using kernel density estimates. A correlation measure between these two kernel density estimates is then optimized to find a displacement field such that the floating point set is moved to the reference point set. Regularizations based on the overall deformation energy and the motion smoothness energy are used to constraint the displacement field for a robust point set matching. Incorporating this non-rigid point set matching method into a statistical model based 2D/3D reconstruction framework, we can reconstruct a scaled, patient-specific model from noisy edge points that are extracted directly from the x-ray radiograph by an edge detector. Our experiment conducted on datasets of two patients and six cadavers demonstrates a mean reconstruction error of 1.9 mm

Correlation properties of spontaneous motor activity in healthy infants: a new computer-assisted method to evaluate neurological maturation

Qualitative assessment of spontaneous motor activity in early infancy is widely used in clinical practice. It enables the description of maturational changes of motor behavior in both healthy infants and infants who are at risk for later neurological impairment. These assessments are, however, time-consuming and are dependent upon professional experience. Therefore, a simple physiological method that describes the complex behavior of spontaneous movements (SMs) in infants would be helpful. In this methodological study, we aimed to determine whether time series of motor acceleration measurements at 40-44 weeks and 50-55 weeks gestational age in healthy infants exhibit fractal-like properties and if this self-affinity of the acceleration signal is sensitive to maturation. Healthy motor state was ensured by General Movement assessment. We assessed statistical persistence in the acceleration time series by calculating the scaling exponent α via detrended fluctuation analysis of the time series. In hand trajectories of SMs in infants we found a mean α value of 1.198 (95 % CI 1.167-1.230) at 40-44 weeks. Alpha changed significantly (p = 0.001) at 50-55 weeks to a mean of 1.102 (1.055-1.149). Complementary multilevel regression analysis confirmed a decreasing trend of α with increasing age. Statistical persistence of fluctuation in hand trajectories of SMs is sensitive to neurological maturation and can be characterized by a simple parameter α in an automated and observer-independent fashion. Future studies including children at risk for neurological impairment should evaluate whether this method could be used as an early clinical screening tool for later neurological compromise.

Correlation between the area of increased autofluorescence surrounding geographic atrophy and disease progression in patients with AMD

PURPOSE: To test the hypothesis that the extension of areas with increased fundus autofluorescence (FAF) outside atrophic patches correlates with the rate of spread of geographic atrophy (GA) over time in eyes with age-related macular degeneration (AMD). METHODS: The database of the multicenter longitudinal natural history Fundus Autofluorescence in AMD (FAM) Study was reviewed for patients with GA recruited through the end of August 2003, with follow-up examinations within at least 1 year. Only eyes with sufficient image quality and with diffuse patterns of increased FAF surrounding atrophy were chosen. In standardized digital FAF images (excitation, 488 nm; emission, >500 nm), total size and spread of GA was measured. The convex hull (CH) of increased FAF as the minimum polygon encompassing the entire area of increased FAF surrounding the central atrophic patches was quantified at baseline. Statistical analysis was performed with the Spearman's rank correlation coefficient (rho). RESULTS: Thirty-nine eyes of 32 patients were included (median age, 75.0 years; interquartile range [IQR], 67.8-78.9); median follow-up, 1.87 years; IQR, 1.43-3.37). At baseline, the median total size of atrophy was 7.04 mm2 (IQR, 4.20-9.88). The median size of the CH was 21.47 mm2 (IQR, 15.19-28.26). The median rate of GA progression was 1.72 mm2 per year (IQR, 1.10-2.83). The area of increased FAF around the atrophy (difference between the CH and the total GA size at baseline) showed a positive correlation with GA enlargement over time (rho=0.60; P=0.0002). CONCLUSIONS: FAF characteristics that are not identified by fundus photography or fluorescein angiography may serve as a prognostic determinant in advanced atrophic AMD. As the FAF signal originates from lipofuscin (LF) in postmitotic RPE cells and since increased FAF indicates excessive LF accumulation, these findings would underscore the pathophysiological role of RPE-LF in AMD pathogenesis.

Correlation of bone defect dimensions with healing outcome one year after apical surgery

This clinical study prospectively evaluated the healing outcome 1 year after apical surgery in relation to bony crypt dimensions measured intraoperatively. The study cohort included 183 teeth in an equal number of patients. For statistical analysis, results were dichotomized (healed versus non-healed cases). The overall success rate was 83% (healed cases). Healing outcome was not significantly related to the level and height of the facial bone plate. In contrast, a significant difference was found for the mean size of the bony crypt when healed cases (395 mm(3)) were compared with non-healed cases (554 mm(3)). In addition, healed cases had a significantly shorter mean distance (4.30 mm) from the facial bone surface to the root canal (horizontal access) compared with non-healed cases (5.13 mm). With logistic regression, however, the only parameter found to be significantly related to healing outcome was the length of the access window to the bony crypt.

Statistical evaluation of time-dependent metabolite concentrations: estimation of post-mortem intervals based on in situ 1H-MRS of the brain

Knowledge of the time interval from death (post-mortem interval, PMI) has an enormous legal, criminological and psychological impact. Aiming to find an objective method for the determination of PMIs in forensic medicine, 1H-MR spectroscopy (1H-MRS) was used in a sheep head model to follow changes in brain metabolite concentrations after death. Following the characterization of newly observed metabolites (Ith et al., Magn. Reson. Med. 2002; 5: 915-920), the full set of acquired spectra was analyzed statistically to provide a quantitative estimation of PMIs with their respective confidence limits. In a first step, analytical mathematical functions are proposed to describe the time courses of 10 metabolites in the decomposing brain up to 3 weeks post-mortem. Subsequently, the inverted functions are used to predict PMIs based on the measured metabolite concentrations. Individual PMIs calculated from five different metabolites are then pooled, being weighted by their inverse variances. The predicted PMIs from all individual examinations in the sheep model are compared with known true times. In addition, four human cases with forensically estimated PMIs are compared with predictions based on single in situ MRS measurements. Interpretation of the individual sheep examinations gave a good correlation up to 250 h post-mortem, demonstrating that the predicted PMIs are consistent with the data used to generate the model. Comparison of the estimated PMIs with the forensically determined PMIs in the four human cases shows an adequate correlation. Current PMI estimations based on forensic methods typically suffer from uncertainties in the order of days to weeks without mathematically defined confidence information. In turn, a single 1H-MRS measurement of brain tissue in situ results in PMIs with defined and favorable confidence intervals in the range of hours, thus offering a quantitative and objective method for the determination of PMIs.

Traumatic extra-axial hemorrhage: correlation of postmortem MSCT, MRI, and forensic-pathological findings

PURPOSE: To evaluate the diagnostic accuracy of in situ postmortem multislice computed tomography (MSCT) and magnetic resonance imaging (MRI) in the detection of primary traumatic extra-axial hemorrhage. MATERIALS AND METHODS: Thirty forensic neurotrauma cases and 10 nontraumatic controls who underwent both in situ postmortem cranial MSCT and MR imaging before autopsy were retrospectively reviewed. Both imaging modalities were analyzed in view of their accuracy, sensitivity, and specificity concerning the detection of extra-axial hemorrhage. Statistical significance was calculated using the McNemar test. kappa values for interobserver agreement were calculated for extra-axial hemorrhage types and to quantify the agreement between both modalities as well as MRI, CT, and forensics, respectively. RESULTS: Analysis of the detection of hemorrhagic localizations showed an accuracy, sensitivity, and specificity of 89%, 82%, and 92% using CT, and 90%, 83%, and 94% using MRI, respectively. MRI was more sensitive than CT in the detection of subarachnoid hemorrhagic localizations (P = 0.001), whereas no significant difference resulted from the detection of epidural and subdural hemorrhagic findings (P = 0.248 and P = 0.104, respectively). Interobserver agreement for all extra-axial hemorrhage types was substantial (CT kappa = 0.76; MRI kappa = 0.77). The agreement of both modalitites was almost perfect (readers 1 and 2 kappa = 0.88). CONCLUSION: CT and MRI are of comparable potential as forensic diagnostic tools for traumatic extra-axial hemorrhage. Not only of forensic, but also of clinical interest is the observation that most thin blood layers escape the radiological evaluation.

Strangulation signs: initial correlation of MRI, MSCT, and forensic neck findings

PURPOSE: To evaluate multislice spiral computed tomography (MSCT) and magnetic resonance imaging (MRI) findings in hanging and manual strangulation cases and compare them with forensic autopsy results. MATERIALS AND METHODS: Postmortem MSCT and MRI of nine persons who died from hanging or manual strangulation were performed. The neck findings were compared with those discovered during forensic autopsy. In addition, two living patients underwent imaging and clinical examination following severe manual strangulation and near-hanging, respectively. For evaluation, the findings were divided into "primary" (strangulation mark and subcutaneous desiccation (i.e., soft-tissue thinning as a result of tissue fluids being driven out by mechanical compression) in hanging, and subcutaneous and intramuscular hemorrhage in manual strangulation) and "collateral" signs. The Wilcoxon two-tailed test was used for statistical analysis of the lymph node and salivary gland findings. RESULTS: In hanging, the primary and most frequent collateral signs were revealed by imaging. In manual strangulation, the primary findings were accurately depicted, with the exception of one slight hemorrhage. Apart from a vocal cord hemorrhage, all frequent collateral signs could be diagnosed radiologically. Traumatic lymph node hemorrhage (P = 0.031) was found in all of the manual strangulation cases. CONCLUSION: MSCT and MRI revealed strangulation signs concordantly with forensic pathology findings. Imaging offers a great potential for the forensic examination of lesions due to strangulation in both clinical and postmortem settings.

Statistical analysis of multichannel scalp field data

High density spatial and temporal sampling of EEG data enhances the quality of results of electrophysiological experiments. Because EEG sources typically produce widespread electric fields (see Chapter 3) and operate at frequencies well below the sampling rate, increasing the number of electrodes and time samples will not necessarily increase the number of observed processes, but mainly increase the accuracy of the representation of these processes. This is namely the case when inverse solutions are computed. As a consequence, increasing the sampling in space and time increases the redundancy of the data (in space, because electrodes are correlated due to volume conduction, and time, because neighboring time points are correlated), while the degrees of freedom of the data change only little. This has to be taken into account when statistical inferences are to be made from the data. However, in many ERP studies, the intrinsic correlation structure of the data has been disregarded. Often, some electrodes or groups of electrodes are a priori selected as the analysis entity and considered as repeated (within subject) measures that are analyzed using standard univariate statistics. The increased spatial resolution obtained with more electrodes is thus poorly represented by the resulting statistics. In addition, the assumptions made (e.g. in terms of what constitutes a repeated measure) are not supported by what we know about the properties of EEG data. From the point of view of physics (see Chapter 3), the natural “atomic” analysis entity of EEG and ERP data is the scalp electric field

Are clustering effects accounted for in statistical analysis in leading dental specialty journals?

OBJECTIVES In dental research multiple site observations within patients or taken at various time intervals are commonplace. These clustered observations are not independent; statistical analysis should be amended accordingly. This study aimed to assess whether adjustment for clustering effects during statistical analysis was undertaken in five specialty dental journals. METHODS Thirty recent consecutive issues of Orthodontics (OJ), Periodontology (PJ), Endodontology (EJ), Maxillofacial (MJ) and Paediatric Dentristry (PDJ) journals were hand searched. Articles requiring adjustment accounting for clustering effects were identified and statistical techniques used were scrutinized. RESULTS Of 559 studies considered to have inherent clustering effects, adjustment for this was made in the statistical analysis in 223 (39.1%). Studies published in the Periodontology specialty accounted for clustering effects in the statistical analysis more often than articles published in other journals (OJ vs. PJ: OR=0.21, 95% CI: 0.12, 0.37, p<0.001; MJ vs. PJ: OR=0.02, 95% CI: 0.00, 0.07, p<0.001; PDJ vs. PJ: OR=0.14, 95% CI: 0.07, 0.28, p<0.001; EJ vs. PJ: OR=0.11, 95% CI: 0.06, 0.22, p<0.001). A positive correlation was found between increasing prevalence of clustering effects in individual specialty journals and correct statistical handling of clustering (r=0.89). CONCLUSIONS The majority of studies in 5 dental specialty journals (60.9%) examined failed to account for clustering effects in statistical analysis where indicated, raising the possibility of inappropriate decreases in p-values and the risk of inappropriate inferences.

Fast Prediction of Femoral Biomechanics Using Supervised Machine Learning and Statistical Shape Modeling

Finite element (FE) analysis is an important computational tool in biomechanics. However, its adoption into clinical practice has been hampered by its computational complexity and required high technical competences for clinicians. In this paper we propose a supervised learning approach to predict the outcome of the FE analysis. We demonstrate our approach on clinical CT and X-ray femur images for FE predictions ( FEP), with features extracted, respectively, from a statistical shape model and from 2D-based morphometric and density information. Using leave-one-out experiments and sensitivity analysis, comprising a database of 89 clinical cases, our method is capable of predicting the distribution of stress values for a walking loading condition with an average correlation coefficient of 0.984 and 0.976, for CT and X-ray images, respectively. These findings suggest that supervised learning approaches have the potential to leverage the clinical integration of mechanical simulations for the treatment of musculoskeletal conditions.