Morphological Reconstruction Improves Microvessel Mapping in Super-Resolution Ultrasound.

Generation of super-resolution (SR) ultrasound (US) images, created from the successive localization of individual microbubbles in the circulation, has enabled the visualization of microvascular structure and flow at a level of detail that was not possible previously. Despite rapid progress, tradeoffs between spatial and temporal resolution may challenge the translation of this promising technology to the clinic. To temper these tradeoffs, we propose a method based on morphological image reconstruction. This method can extract from ultrafast contrast-enhanced US (CEUS) images hundreds of microbubble peaks per image (312-by-180 pixels) with intensity values varying by an order of magnitude. Specifically, it offers a fourfold increase in the number of peaks detected per frame, requires on the order of 100 ms for processing, and is robust to additive electronic noise (down to 3.6-dB CNR in CEUS images). By integrating this method to an SR framework, we demonstrate a sixfold improvement in spatial resolution, when compared with CEUS, in imaging chicken embryo microvessels. This method that is computationally efficient and, thus, scalable to large data sets may augment the abilities of SR-US in imaging microvascular structure and function.

A Feature Sampling Strategy for Analysis of High Dimensional Genomic Data.

With the development of high throughput technology, it has become feasible and common to profile tens of thousands of gene activities simultaneously. These genomic data typically have sample size of hundreds or fewer, which is much less than the feature size (number of genes). In addition, the genes, in particular the ones from the same pathway, are often highly correlated. These issues impose a great challenge for selecting meaningful genes from a large number of (correlated) candidates in many genomic studies. Quite a few methods have been proposed to attack this challenge. Among them, regularization-based techniques, e.g., lasso, become much more appealing, because they can do model fitting and variable selection at the same time. However, the lasso regression has its known limitations. One is that the number of genes selected by the lasso couldn't exceed the number of samples. Another limitation is that, if causal genes are highly correlated, the lasso tends to select only one or few genes from them. Biologists, however, desire to identify them all. To overcome these limitations, we present here a novel, robust, and stable variable selection method. Through simulation studies and a real application to the transcriptome data, we demonstrate the superiority of the proposed method in selecting highly correlated causal genes. We also provide some theoretical justifications for this feature sampling strategy based on the mean and variance analyses.

Sparse Sliced Inverse Regression Via Lasso.

For multiple index models, it has recently been shown that the sliced inverse regression (SIR) is consistent for estimating the sufficient dimension reduction (SDR) space if and only if ρ = lim p n = 0 , where p is the dimension and n is the sample size. Thus, when p is of the same or a higher order of n, additional assumptions such as sparsity must be imposed in order to ensure consistency for SIR. By constructing artificial response variables made up from top eigenvectors of the estimated conditional covariance matrix, we introduce a simple Lasso regression method to obtain an estimate of the SDR space. The resulting algorithm, Lasso-SIR, is shown to be consistent and achieve the optimal convergence rate under certain sparsity conditions when p is of order o(n 2 λ 2), where λ is the generalized signal-to-noise ratio. We also demonstrate the superior performance of Lasso-SIR compared with existing approaches via extensive numerical studies and several real data examples.

Determining Candidate Single Nucleotide Polymorphisms in Acquired Laryngotracheal Stenosis.

OBJECTIVES/HYPOTHESIS: Despite wide adoption of strategies to prevent injury from prolonged intubation and tracheotomy, acquired laryngotracheal stenosis (ALTS) has not disappeared. ALTS' persistence may be due to patient factors that confer unique susceptibility for some. We sought to identify genetic markers in genes associated with wound healing that could be associated with ALTS. STUDY DESIGN: Case-control study. METHODS: One hundred thirty-eight patients were recruited, 53 patients with ALTS and 85 control patients who underwent intubation or tracheotomy without evidence of ALTS. The patients' DNA was isolated from whole blood. Custom primers were designed, and the TaqMan assay employing allele-specific polymerase chain reaction was used to interrogate single nucleotide polymorphisms (SNPs) rs1799750, rs522616, rs2276109, rs2569190, rs1800469, and rs1024611 of candidate wound healing genes MMP1, MMP3, MMP12, CD14, TGFß1, and MCP1, respectively. A logistic regression model was used to examine the association of candidate gene polymorphisms with the presence or absence of ALTS. RESULTS: All 138 patients were successfully genotyped. No significant association was found between candidate SNPs and development of ALTS in the overall group. However, subgroup analysis within each ethnicity identified SNPs that are associated with ALTS depending upon the ethnic background. CONCLUSIONS: Patient factors such as variations in wound healing due to functional SNPs may shed light on the development of ALTS. There may be a difference in susceptibility to developing ALTS in different ethnic backgrounds. These preliminary findings need to be corroborated in larger population studies. LEVEL OF EVIDENCE: 3b. Laryngoscope, 128:E111-E116, 2018.

Sample size determination for a three-arm equivalence trial of Poisson and negative binomial responses.

Assessing equivalence or similarity has drawn much attention recently as many drug products have lost or will lose their patents in the next few years, especially certain best-selling biologics. To claim equivalence between the test treatment and the reference treatment when assay sensitivity is well established from historical data, one has to demonstrate both superiority of the test treatment over placebo and equivalence between the test treatment and the reference treatment. Thus, there is urgency for practitioners to derive a practical way to calculate sample size for a three-arm equivalence trial. The primary endpoints of a clinical trial may not always be continuous, but may be discrete. In this paper, the authors derive power function and discuss sample size requirement for a three-arm equivalence trial with Poisson and negative binomial clinical endpoints. In addition, the authors examine the effect of the dispersion parameter on the power and the sample size by varying its coefficient from small to large. In extensive numerical studies, the authors demonstrate that required sample size heavily depends on the dispersion parameter. Therefore, misusing a Poisson model for negative binomial data may easily lose power up to 20%, depending on the value of the dispersion parameter.

Sample size determination for a three-arm equivalence trial of normally distributed responses.

The equivalence assessment is often conducted through a three-arm clinical trial (namely, test, reference, and placebo) and it usually consists of three tests. The first two tests are to demonstrate the superiority of the test and the reference treatment to the placebo, and they are followed by an equivalence test between the test treatment and the reference treatment. When the response variable is continuous, equivalence is commonly defined in terms of mean difference, mean ratio, or ratio of mean differences, that is, the mean difference of the test and the placebo to the mean difference of the reference and the placebo. These equivalence tests can be performed with both a hypothesis-testing approach and a confidence-interval approach. The advantage of applying the equivalence test by ratio of mean differences is that it can test both superiority of the test treatment over placebo and equivalence between the test and the reference simultaneously through a single hypothesis. In this article, we derive the test statistics and the power function for the ratio of mean differences hypothesis and solve the required sample size for a three-arm clinical trial. Examples of required sample size are given in this article, and are compared with the required sample size by the traditional mean difference equivalence test. After a careful examination, we suggest increasing the power of the ratio of mean differences approach by appropriately adjusting the lower limit of the equivalence interval.

Translational genomics of acquired laryngotracheal stenosis.

OBJECTIVES/HYPOTHESIS: Acquired laryngotracheal stenosis (ALTS) results from abnormal mucosal wound healing after laryngeal and/or tracheal injury. Patients with ALTS often present late after significant reduction of the airway lumen and onset of symptoms. Motivated by the need for earlier detection of affected patients, we sought to investigate genetic markers for ALTS that would identify susceptible patients. STUDY DESIGN: Pilot Case-Control Study. METHODS: Seventy-six patients were recruited, 40 patients with ALTS and 36 control patients with airway injury but without ALTS. DNA was isolated from whole blood and formalin-fixed paraffin-embedded specimens from patients. Custom primers were designed and the TaqMan assay employing allele-specific polymerase chain reaction was used to interrogate single nucleotide polymorphisms (SNPs): rs2569190, rs1799750, and rs1800469 located in candidate genes CD14, matrix metalloproteinase-1 (MMP-1), and transforming growth factor-ß1 (TGF-ß1), respectively. A logistic regression model was used to examine the association of candidate gene polymorphisms with the presence or absence of ALTS. RESULTS: All 76 patients were successfully genotyped at the three loci of interest by optimizing the genotyping protocol. MMP-1 SNP rs1799750 was most significantly associated with development of ALTS (P = 0.005). CONCLUSION: Identification of SNPs associated with development of ALTS will provide new experimental targets to study wound healing in human subjects. The association found in the current study between ALTS and SNP rs1799750 is being validated in a larger population examining an expanded set of relevant SNPs. Identifying patients with genetic susceptibility to ALTS and poor wound healing in the upper airway will be useful for management of patients after upper-airway injury.