Comparison of Methods to Estimate Splenic Volume in Myelofibrosis Trials

Primary myelofibrosis (PM) is a chronic blood cancer which increases burden on the spleen to produce blood cells and results in palpable splenomegaly. In the clinic, splenomegaly is classified based on the distance between the spleen's lowest point and the left costal margin, however, this method is highly subjective and depends on the subject's position and respiration. Imaging techniques have the potential to provide accurate, reliable, and reproducible measurements of splenic volume (SV). In clinical trials assessing therapy response, an accepted imaging-based endpoint is ≥35% reduction in SV at week 24 from baseline as measured by Magnetic Resonance Imaging (MRI) or Computer Tomography (CT). A ≥25% increase in SV is typically considered progression. The most accurate method for volume assessment is manual segmentation, since the entire spleen boundary can be utilized for the volume calculation. This study compared two other volume estimation methods: ellipsoid method and a model proposed by Bezerra et al (AJR Am J Roentgenol. 2005). We compared the methods' performance in assessing treatment response or progression based on SV change from baseline to week 24. Imaging data from 30 participants were used in this study, predominantly acquired using MRI modality; CT was used as an alternative, when MRI was contraindicated. Scans from two timepoints per participant were used: baseline and 24 weeks after start of treatment. For the manual segmentation method, preliminary regions of interest were manually outlined on every imaging slice by an experienced imaging analyst and then reviewed by a trained radiologist. SV was derived by multiplying the number of voxels contained in the spleen outlined by the voxel size of the scan. For the ellipsoid method, maximum width (W) and orthogonal thickness (T) were measured on the axial images. Length (L) was measured by multiplying the number of slices containing spleen by the slice interval. Ellipsoid volume was calculated as follows: V = W * T * L * π / 6 For the length-estimated SV based on the Bezerra et al model, spleen length was utilized as shown: V = (L - 5.8006) / 0.0126 For each of the three methods, percent change in SV was calculated from baseline to week 24. Pearson's correlation coefficient and Bland Altman analysis were implemented for comparison of methods to manual segmentation. Sensitivity and specificity analysis was performed to determine the accuracy of each method to predict response or progression. The manual segmentation volume was significantly correlated with both the ellipsoid method (r(58) = 0.94, p < 0.0001) and the length-estimated method (r(58) = 0.89, p < 0.0001). When assessing percent changes from baseline to week 24 using manual segmentation, 4 of the participants achieved splenic response and 4 progressed with 25% increase in SV. However, analysis using ellipsoid method yielded 3 responding and 2 progressing participants. Finally, analysis with length-estimated volume yielded no responding or progressing participants. This data is also illustrated in Table 1, which shows the sensitivity and specificity results. Figure 1 illustrates Bland-Altman plots, suggesting that ellipsoid method provides a more accurate estimation of the change in SV compared to length-estimated volume. Furthermore, we found that the inaccuracy with length-estimated volume increases with larger spleens (not shown). Change in spleen volume contributes to the primary/ secondary endpoints in large multi-center clinical trials for myelofibrosis, so it is imperative that the methods used to measure SV are consistent across imaging sites. The current standard for assessing SV is the manual segmentation method because it provides the most comprehensive measurement of spleen size however, this process is burdensome, time consuming, and requires specific training. The ellipsoid and length-estimated methods were strongly correlated with the manual segmentation method; however, they were not as sensitive when determining treatment response or progression. The length-estimated method had the least level of agreement with manual segmentation. The ellipsoid method may be a better alternative; however, it is important to use one method consistently across all visits for a study participant. Additional work is required to test performance of methods on a larger cohort, as well as assess automated segmentation algorithms that may reduce the burden of manual tracing. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Stability for a Class of State Constrained Impulsive Nonlinear Systems: Barrier Lyapunov Functions Method

This paper studies the problem for a class of state constrained impulsive nonlinear systems. Firstly, we establish two sufficient conditions for the stability of invariant sets of state constrained hybrid systems. Secondly, we construct the symmetric and asymmetric barrier Lyapunov functions, respectively. A feedback method is presented to solve the stabilization problem of constrained hybrid systems. Introduce the auxiliary matrix, combining with inductive method and linear matrix inequality theory, some sufficient conditions are obtained to ensure stability for state constrained hybrid dynamical networks by the attractive ellipsoid method approach. Finally, one example with simulations is given to validate the effectiveness of the proposed criteria.

Correlation of Haematoma Volume with Early Outcome in Surgically Treated Spontaneous Primary Supratentorial Intra-Cerebral Haematomas

Introduction: Spontaneous intracerebral hemorrhage (ICH) comprises 10-15% of all strokes. Aim: To assess the relationship between the haematoma volume and early surgical outcome of patients with spontaneous primary supratentorial intracerebral hemorrhage by Glasgow Outcome Scale at the 30th post ictus day. Methods: This prospective study was done from April 2014 to March 2016 in Department of Neurosurgery, Combined Military Hospital (CMH), Dhaka. Forty seven cases were selected by set down criteria. Glasgow Coma Scale (GCS) score was recorded on admission, haematoma volume was calculated from the CT scan immediately after admission by Modified Ellipsoid Method and the surgical outcome of ICH patients was determined by Glasgow Outcome Scale (GOS) by face to face interview or by structured interview over phone at their 30th post ictus day. Correlation between the haematoma volume and the surgical outcome of ICH was done by Chi-square test. Again the correlations of three variables (haematoma volume, admission GCS and ICH score) with GOS was compared by Spearman’s correlation coefficient test. Results: Patients with haematoma volume of 30cc or more were found to have worst outcome. Conclusion: Relationship between haematoma volume and surgical outcome was found statistically very significant. Risk stratification of the patients with spontaneous primary supratentorial intracerebral hematomas basing on hematoma volume may be used to improve standardization of treatment protocols and clinical research studies. JAFMC Bangladesh. Vol 15, No 1 (June) 2020: 46-49

Optimal design of an asymmetrical parallel mechanism

Aiming at the aircraft composite skin grinding, a Three-DOF Asymmetrical Mechanism (TAM) is proposed to replace manual grinding. Considering asymmetrical characteristics of the TAM, the linear superposition principle is adopted to derive the total stiffness matrix of the mechanism. The driving force curves of numerical calculation and simulation are almost coincident; thus the correctness of the dynamic model is verified. The global kinematics condition number index is established with the velocity ellipsoid method. Similarly, the global stiffness performance evaluation index is constructed according to the stiffness ellipsoid method. Moreover, a new global acceleration dexterity index is proposed to overcome the limitations of the dynamics ellipsoid method. Based on the above models and performance indices, a new optimization method is proposed which combines both single and multi-objective optimization. Among the method, the multi-objective optimization is carried out with normalized weighted sum algorithm and genetic algorithm. This optimization method can not only improve the convergence speed, but also balance the weight of different performance indices. After optimization, the kinematics, stiffness and dynamics performance are significantly improved by contrast with the initial performance atlas. Therefore, the results indicate the effectiveness of the multi-objective optimization method.