Human intervertebral disc stiffness correlates better with the Otsu threshold computed from axial T2 map of its posterior annulus fibrosus than with clinical classifications

Degeneration of the intervertebral disc, sometimes associated with low back pain and abnormal spinal motions, represents a major health issue with high costs. A non-invasive degeneration assessment via qualitative or quantitative MRI (magnetic resonance imaging) is possible, yet, no relation between mechanical properties and T2 maps of the intervertebral disc (IVD) has been considered, albeit T2 relaxation time values quantify the degree of degeneration. Therefore, MRI scans and mechanical tests were performed on 14 human lumbar intervertebral segments freed from posterior elements and all soft tissues excluding the IVD. Degeneration was evaluated in each specimen using morphological criteria, qualitative T2 weighted images and quantitative axial T2 map data and stiffness was calculated from the load-deflection curves of in vitro compression, torsion, lateral bending and flexion/extension tests. In addition to mean T2, the OTSU threshold of T2 (TOTSU), a robust and automatic histogram-based method that computes the optimal threshold maximizing the distinction of two classes of values, was calculated for anterior, posterior, left and right regions of each annulus fibrosus (AF). While mean T2 and degeneration schemes were not related to the IVDs' mechanical properties, TOTSU computed in the posterior AF correlated significantly with those classifications as well as with all stiffness values. TOTSU should therefore be included in future degeneration grading schemes.

Robust Proximal Femur Segmentation in Conventional X-Ray Images via Random Forest Regression on Multi-resolution Gradient Features

In this paper, we propose a fully automatic, robust approach for segmenting proximal femur in conventional X-ray images. Our method is based on hierarchical landmark detection by random forest regression, where the detection results of 22 global landmarks are used to do the spatial normalization, and the detection results of the 59 local landmarks serve as the image cue for instantiation of a statistical shape model of the proximal femur. To detect landmarks in both levels, we use multi-resolution HoG (Histogram of Oriented Gradients) as features which can achieve better accuracy and robustness. The efficacy of the present method is demonstrated by experiments conducted on 150 clinical x-ray images. It was found that the present method could achieve an average point-to-curve error of 2.0 mm and that the present method was robust to low image contrast, noise and occlusions caused by implants.

Improved detection of amnestic MCI by means of discriminative vector quantization of single-trial cognitive ERP responses

Cognitive event-related potentials (ERPs) are widely employed in the study of dementive disorders. The morphology of averaged response is known to be under the influence of neurodegenerative processes and exploited for diagnostic purposes. This work is built over the idea that there is additional information in the dynamics of single-trial responses. We introduce a novel way to detect mild cognitive impairment (MCI) from the recordings of auditory ERP responses. Using single trial responses from a cohort of 25 amnestic MCI patients and a group of age-matched controls, we suggest a descriptor capable of encapsulating single-trial (ST) response dynamics for the benefit of early diagnosis. A customized vector quantization (VQ) scheme is first employed to summarize the overall set of ST-responses by means of a small-sized codebook of brain waves that is semantically organized. Each ST-response is then treated as a trajectory that can be encoded as a sequence of code vectors. A subject's set of responses is consequently represented as a histogram of activated code vectors. Discriminating MCI patients from healthy controls is based on the deduced response profiles and carried out by means of a standard machine learning procedure. The novel response representation was found to improve significantly MCI detection with respect to the standard alternative representation obtained via ensemble averaging (13% in terms of sensitivity and 6% in terms of specificity). Hence, the role of cognitive ERPs as biomarker for MCI can be enhanced by adopting the delicate description of our VQ scheme.

Characterization of microcirculation in multiple sclerosis lesions by dynamic texture parameter analysis (DTPA)

OBJECTIVE Texture analysis is an alternative method to quantitatively assess MR-images. In this study, we introduce dynamic texture parameter analysis (DTPA), a novel technique to investigate the temporal evolution of texture parameters using dynamic susceptibility contrast enhanced (DSCE) imaging. Here, we aim to introduce the method and its application on enhancing lesions (EL), non-enhancing lesions (NEL) and normal appearing white matter (NAWM) in multiple sclerosis (MS). METHODS We investigated 18 patients with MS and clinical isolated syndrome (CIS), according to the 2010 McDonald's criteria using DSCE imaging at different field strengths (1.5 and 3 Tesla). Tissues of interest (TOIs) were defined within 27 EL, 29 NEL and 37 NAWM areas after normalization and eight histogram-based texture parameter maps (TPMs) were computed. TPMs quantify the heterogeneity of the TOI. For every TOI, the average, variance, skewness, kurtosis and variance-of-the-variance statistical parameters were calculated. These TOI parameters were further analyzed using one-way ANOVA followed by multiple Wilcoxon sum rank testing corrected for multiple comparisons. RESULTS Tissue- and time-dependent differences were observed in the dynamics of computed texture parameters. Sixteen parameters discriminated between EL, NEL and NAWM (pAVG = 0.0005). Significant differences in the DTPA texture maps were found during inflow (52 parameters), outflow (40 parameters) and reperfusion (62 parameters). The strongest discriminators among the TPMs were observed in the variance-related parameters, while skewness and kurtosis TPMs were in general less sensitive to detect differences between the tissues. CONCLUSION DTPA of DSCE image time series revealed characteristic time responses for ELs, NELs and NAWM. This may be further used for a refined quantitative grading of MS lesions during their evolution from acute to chronic state. DTPA discriminates lesions beyond features of enhancement or T2-hypersignal, on a numeric scale allowing for a more subtle grading of MS-lesions.

Assessment of Collimator Jaw Optimization in Reducing Normal Tissue Irradiation with Intensity Modulated Radiation Therapy

Purpose: To evaluate normal tissue dose reduction in step-and-shoot intensity-modulated radiation therapy (IMRT) on the Varian 2100 platform by tracking the multileaf collimator (MLC) apertures with the accelerator jaws. Methods: Clinical radiation treatment plans for 10 thoracic, 3 pediatric and 3 head and neck patients were converted to plans with the jaws tracking each segment’s MLC apertures. Each segment was then renormalized to account for the change in collimator scatter to obtain target coverage within 1% of that in the original plan. The new plans were compared to the original plans in a commercial radiation treatment planning system (TPS). Reduction in normal tissue dose was evaluated in the new plan by using the parameters V5, V10, and V20 in the cumulative dose-volume histogram for the following structures: total lung minus GTV (gross target volume), heart, esophagus, spinal cord, liver, parotids, and brainstem. In order to validate the accuracy of our beam model, MLC transmission measurements were made and compared to those predicted by the TPS. Results: The greatest change between the original plan and new plan occurred at lower dose levels. The reduction in V20 was never more than 6.3% and was typically less than 1% for all patients. The reduction in V5 was 16.7% maximum and was typically less than 3% for all patients. The variation in normal tissue dose reduction was not predictable, and we found no clear parameters that indicated which patients would benefit most from jaw tracking. Our TPS model of MLC transmission agreed with measurements with absolute transmission differences of less than 0.1 % and thus uncertainties in the model did not contribute significantly to the uncertainty in the dose determination. Conclusion: The amount of dose reduction achieved by collimating the jaws around each MLC aperture in step-and-shoot IMRT does not appear to be clinically significant.

Improving the accuracy of radiation pneumonitis dose response models

The prognosis for lung cancer patients remains poor. Five year survival rates have been reported to be 15%. Studies have shown that dose escalation to the tumor can lead to better local control and subsequently better overall survival. However, dose to lung tumor is limited by normal tissue toxicity. The most prevalent thoracic toxicity is radiation pneumonitis. In order to determine a safe dose that can be delivered to the healthy lung, researchers have turned to mathematical models predicting the rate of radiation pneumonitis. However, these models rely on simple metrics based on the dose-volume histogram and are not yet accurate enough to be used for dose escalation trials. The purpose of this work was to improve the fit of predictive risk models for radiation pneumonitis and to show the dosimetric benefit of using the models to guide patient treatment planning. The study was divided into 3 specific aims. The first two specifics aims were focused on improving the fit of the predictive model. In Specific Aim 1 we incorporated information about the spatial location of the lung dose distribution into a predictive model. In Specific Aim 2 we incorporated ventilation-based functional information into a predictive pneumonitis model. In the third specific aim a proof of principle virtual simulation was performed where a model-determined limit was used to scale the prescription dose. The data showed that for our patient cohort, the fit of the model to the data was not improved by incorporating spatial information. Although we were not able to achieve a significant improvement in model fit using pre-treatment ventilation, we show some promising results indicating that ventilation imaging can provide useful information about lung function in lung cancer patients. The virtual simulation trial demonstrated that using a personalized lung dose limit derived from a predictive model will result in a different prescription than what was achieved with the clinically used plan; thus demonstrating the utility of a normal tissue toxicity model in personalizing the prescription dose.

A dosimetric study of radionuclide therapy for bone marrow ablation

In a phase I clinical trial, six multiple myeloma patients, who were non-responsive to conventional therapy and were scheduled for bone marrow transplantation, received Holmium-166 ($\sp{166}$Ho) labeled to a bone seeking agent, DOTMP (1,4,7,10-tetraazacyclododecane-1,4,7,10-tetramethylene-phosphonic acid), for the purpose of bone marrow ablation. The specific aims of my research within this protocol were to evaluate the toxicity and efficacy of $\sp{166}$Ho DOTMP by quantifying the in vivo pharmacokinetics and radiation dosimetry, and by correlating these results to the biologic response observed. The reproducibility of pharmacokinetics from multiple injections of $\sp{166}$Ho DOTMP administered to these myeloma patients was demonstrated from both blood and whole body retention. The skeletal concentration of $\sp{166}$Ho DOTMP was heterogenous in all six patients: high in the ribs, pelvis, and lumbar vertebrae regions, and relatively low in the femurs, arms, and head.^ A novel technique was developed to calculate the radiation dose to the bone marrow in each skeletal ROI, and was applied to all six $\sp{166}$Ho DOTMP patients. Radiation dose estimates for the bone marrow calculated using the standard MIRD "S" factors were compared with the average values derived from the heterogenous distribution of activity in the skeleton (i.e., the regional technique). The results from the two techniques were significantly different; the average of the dose estimates from the regional technique were typically 30% greater. Furthermore, the regional technique provided a range of radiation doses for the entire marrow volume, while the MIRD "S" factors only provided a single value. Dose volume histogram analysis of data from the regional technique indicated a range of dose estimates that varied by a factor of 10 between the high dose and low dose regions. Finally, the observed clinical response of cells and abnormal proteins measured in bone marrow aspirates and peripheral blood samples were compared with radiation dose estimates for the bone marrow calculated from the standard and regional technique. The results showed the regional technique values correlated more closely to several clinical response parameters. (Abstract shortened by UMI.) ^

A case of EDTA-dependent pseudothrombocytopenia: simple recognition of an underdiagnosed and misleading phenomenon

1. BMC Clin Pathol. 2014 May 1;14:19. doi: 10.1186/1472-6890-14-19. eCollection 2014. A case of EDTA-dependent pseudothrombocytopenia: simple recognition of an underdiagnosed and misleading phenomenon. Nagler M, Keller P, Siegrist D, Alberio L. Author information: Department of Hematology and Central Hematology Laboratory, Inselspital University Hospital and University of Berne, CH-3010 Berne, Switzerland. BACKGROUND: EDTA-dependent pseudothrombocytopenia (EDTA-PTCP) is a common laboratory phenomenon with a prevalence ranging from 0.1-2% in hospitalized patients to 15-17% in outpatients evaluated for isolated thrombocytopenia. Despite its harmlessness, EDTA-PTCP frequently leads to time-consuming, costly and even invasive diagnostic investigations. EDTA-PTCP is often overlooked because blood smears are not evaluated visually in routine practice and histograms as well as warning flags of hematology analyzers are not interpreted correctly. Nonetheless, EDTA-PTCP may be diagnosed easily even by general practitioners without any experiences in blood film examinations. This is the first report illustrating the typical patterns of a platelet (PLT) and white blood cell (WBC) histograms of hematology analyzers. CASE PRESENTATION: A 37-year-old female patient of Caucasian origin was referred with suspected acute leukemia and the crew of the emergency unit arranged extensive investigations for work-up. However, examination of EDTA blood sample revealed atypical lymphocytes and an isolated thrombocytopenia together with typical patterns of WBC and PLT histograms: a serrated curve of the platelet histogram and a peculiar peak on the left side of the WBC histogram. EDTA-PTCP was confirmed by a normal platelet count when examining citrated blood. CONCLUSION: Awareness of typical PLT and WBC patterns may alert to the presence of EDTA-PTCP in routine laboratory practice helping to avoid unnecessary investigations and over-treatment. PMCID: PMC4012027 PMID: 24808761 [PubMed]

Neuropsychological long-term sequelae after posterior fossa tumour resection during childhood

The importance of the cerebellum for non‐motor functions is becoming more and more evident. The influence on cognitive functions from acquired cerebellar lesions during childhood, however, is not well known. We present follow‐up data from 24 patients, who were operated upon during childhood for benign cerebellar tumours. The benign histology of these tumours required neither radiotherapy nor chemotherapy. Post‐operatively, these children were of normal intelligence with a mean IQ of 99.1, performance intelligence quotient (PIQ) of 101.3 and verbal intelligence quotient (VIQ) of 96.8. However, 57% of patients showed abnormalities in subtesting. In addition, more extensive neuropsychological testing revealed significant problems for attention, memory, processing speed and interference. Visuo‐constructive problems were marked for copying the Rey figure, but less pronounced for recall of the figure. Verbal fluency was more affected than design fluency. Behavioural deficits could be detected in 33% of patients. Attention deficit problems were marked in 12.5%, whereas others demonstrated psychiatric symptoms such as mutism, addiction problems, anorexia, uncontrolled temper tantrums and phobia. Age at tumour operation and size of tumour had no influence on outcome. Vermis involvement was related to an increase in neuropsychological and psychiatric problems. The observation that patients with left‐sided cerebellar tumours were more affected than patients with right‐sided tumours is probably also influenced by a more pronounced vermian involvement in the former group. In summary, this study confirms the importance of the cerebellum for cognitive development and points to the necessity of careful follow‐up for these children to provide them with the necessary help to achieve full integration into professional life.

Quality Assessment and Enhancement Method for high-resolution Fourier-Domain OCT Imaging of Retina Laser Lesions

We present an image quality assessment and enhancement method for high-resolution Fourier-Domain OCT imaging like in sub-threshold retina therapy. A Maximum-Likelihood deconvolution algorithm as well as a histogram-based quality assessment method are evaluated.

Copula calibration

We propose notions of calibration for probabilistic forecasts of general multivariate quantities. Probabilistic copula calibration is a natural analogue of probabilistic calibration in the univariate setting. It can be assessed empirically by checking for the uniformity of the copula probability integral transform (CopPIT), which is invariant under coordinate permutations and coordinatewise strictly monotone transformations of the predictive distribution and the outcome. The CopPIT histogram can be interpreted as a generalization and variant of the multivariate rank histogram, which has been used to check the calibration of ensemble forecasts. Climatological copula calibration is an analogue of marginal calibration in the univariate setting. Methods and tools are illustrated in a simulation study and applied to compare raw numerical model and statistically postprocessed ensemble forecasts of bivariate wind vectors.

Combination of MRI and dynamic FET PET for initial glioma grading

AIM MRI and PET with 18F-fluoro-ethyl-tyrosine (FET) have been increasingly used to evaluate patients with gliomas. Our purpose was to assess the additive value of MR spectroscopy (MRS), diffusion imaging and dynamic FET-PET for glioma grading. PATIENTS, METHODS 38 patients (42 ± 15 aged, F/M: 0.46) with untreated histologically proven brain gliomas were included. All underwent conventional MRI, MRS, diffusion sequences, and FET-PET within 3±4 weeks. Performances of tumour FET time-activity-curve, early-to-middle SUVmax ratio, choline / creatine ratio and ADC histogram distribution pattern for gliomas grading were assessed, as compared to histology. Combination of these parameters and respective odds were also evaluated. RESULTS Tumour time-activity-curve reached the best accuracy (67%) when taken alone to distinguish between low and high-grade gliomas, followed by ADC histogram analysis (65%). Combination of time-activity-curve and ADC histogram analysis improved the sensitivity from 67% to 86% and the specificity from 63-67% to 100% (p < 0.008). On multivariate logistic regression analysis, negative slope of the tumour FET time-activity-curve however remains the best predictor of high-grade glioma (odds 7.6, SE 6.8, p = 0.022). CONCLUSION Combination of dynamic FET-PET and diffusion MRI reached good performance for gliomas grading. The use of FET-PET/MR may be highly relevant in the initial assessment of primary brain tumours.

Metabolic inflexibility and insulin resistance in obese adolescents with non-alcoholic fatty liver disease.

BACKGROUND Non-alcoholic fatty liver disease (NAFLD) is a comorbidity of childhood obesity. OBJECTIVE We examined whole-body substrate metabolism and metabolic characteristics in obese adolescents with vs. without NAFLD. SUBJECTS Twelve obese (BMI ≥ 95th percentile) adolescents with and without NAFLD [intrahepatic triglyceride (IHTG) ≥5.0% vs. <5.0%] were pair-matched for race, gender, age and % body fat. METHODS Insulin sensitivity (IS) was assessed by a 3-h hyperinsulinemic-euglycemic clamp and whole-body substrate oxidation by indirect calorimetry during fasting and insulin-stimulated conditions. RESULTS Adolescents with NAFLD had increased (p < 0.05) abdominal fat, lipids, and liver enzymes compared with those without NAFLD. Fasting glucose concentration was not different between groups, but fasting insulin concentration was higher (p < 0.05) in the NAFLD group compared with those without. Fasting hepatic glucose production and hepatic IS did not differ (p > 0.1) between groups. Adolescents with NAFLD had higher (p < 0.05) fasting glucose oxidation and a tendency for lower fat oxidation. Adolescents with NAFLD had lower (p < 0.05) insulin-stimulated glucose disposal and lower peripheral IS compared with those without NAFLD. Although respiratory quotient (RQ) increased significantly from fasting to insulin-stimulated conditions in both groups (main effect, p < 0.001), the increase in RQ was lower in adolescents with NAFLD vs. those without (interaction, p = 0.037). CONCLUSION NAFLD in obese adolescents is associated with adverse cardiometabolic profile, peripheral insulin resistance and metabolic inflexibility.

Classification of interstitial lung disease patterns using local DCT features and random forest.

Over the last decade, a plethora of computer-aided diagnosis (CAD) systems have been proposed aiming to improve the accuracy of the physicians in the diagnosis of interstitial lung diseases (ILD). In this study, we propose a scheme for the classification of HRCT image patches with ILD abnormalities as a basic component towards the quantification of the various ILD patterns in the lung. The feature extraction method relies on local spectral analysis using a DCT-based filter bank. After convolving the image with the filter bank, q-quantiles are computed for describing the distribution of local frequencies that characterize image texture. Then, the gray-level histogram values of the original image are added forming the final feature vector. The classification of the already described patches is done by a random forest (RF) classifier. The experimental results prove the superior performance and efficiency of the proposed approach compared against the state-of-the-art.

Fully automatic segmentation of AP pelvis X-rays via random forest regression with efficient feature selection and hierarchical sparse shape composition

In clinical practice, traditional X-ray radiography is widely used, and knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic approach for landmark detection and shape segmentation of both pelvis and femur in conventional AP X-ray images. Our approach is based on the framework of landmark detection via Random Forest (RF) regression and shape regularization via hierarchical sparse shape composition. We propose a visual feature FL-HoG (Flexible- Level Histogram of Oriented Gradients) and a feature selection algorithm based on trace radio optimization to improve the robustness and the efficacy of RF-based landmark detection. The landmark detection result is then used in a hierarchical sparse shape composition framework for shape regularization. Finally, the extracted shape contour is fine-tuned by a post-processing step based on low level image features. The experimental results demonstrate that our feature selection algorithm reduces the feature dimension in a factor of 40 and improves both training and test efficiency. Further experiments conducted on 436 clinical AP pelvis X-rays show that our approach achieves an average point-to-curve error around 1.2 mm for femur and 1.9 mm for pelvis.