Predicting mortality in moderate-severe TBI patients without early withdrawal of life-sustaining treatments including ICU complications: The MYSTIC-score.

PURPOSE: To develop and internally validate the MortalitY in Moderate-Severe TBI plus ICU Complications (MYSTIC)-Score to predict in-hospital mortality of msTBI patients without early (<24 h) withdrawal-of-life-sustaining treatments. METHODS: We analyzed data from a Neuro-Trauma Intensive Care Unit prospectively collected between 11/2009-5/2019. Consecutive adult msTBI patients were included if Glasgow Coma Scale≤12, and neither died nor had withdrawal-of-life-sustaining treatments within 24 h of admission (n = 485). Using univariate and multivariable logistic regression in a random-split cohort approach (2/3 derivation;1/3 validation), we identified independent predictors of in-hospital mortality while adjusting for validated predictors of mortality (IMPACT-variables). We constructed the MYSTIC-Score and examined discrimination and calibration. RESULTS: The MYSTIC-Score included the ICU complications brain edema, herniation, systemic inflammatory response syndrome, sepsis, acute kidney injury, cardiac arrest, and urinary tract infection. In the derivation cohort(n = 324), discrimination and calibration were excellent (area-under-the-receiver-operating-curve [AUC-ROC] = 0.95;Hosmer-Lemeshow p-value = 0.09, with p > 0.05 indicating good calibration). Internal validation revealed an AUC-ROC = 0.93 and Hosmer-Lemeshow-p-value = 0.76 (n = 161). CONCLUSIONS: Certain ICU complications are independent predictors of in-hospital mortality and strengthen outcome prediction in msTBI when combined with validated admission predictors of mortality. However, external validation is needed to determine robustness and practical applicability of our model given the high potential for residual confounders.

Treatment of Osteoarthritis With Low-level Laser Therapy, Acupuncture, and Herbal Therapy: A Case Report.

Osteoarthritis is a challenging diagnosis to navigate and treat. Management options range from nonpharmacological agents to surgical repair. No specific combination of therapies has yet been identified for optimal management although a variety of therapeutic options have been studied. This case report details the use of low-level laser therapy, acupuncture, and herbal medicine in a 64-y-old female with radiographically confirmed osteoarthritis. Near-complete resolution of her symptoms was associated with the multiple therapies outlined in this case report.

Cell-Based High Content Analysis of Cell Proliferation and Apoptosis.

High content imaging-based cell cycle analysis allows multiplexing of various parameters including DNA content, DNA synthesis, cell proliferation, and other cell cycle markers such as phosho-histone H3. 5'-Ethynyl-2'-deoxyuridine (EdU) incorporation is a thymidine analog that provides a sensitive method for the detection of DNA synthesis in proliferating cells that is a more convenient method than the traditional BrdU detection by antibody. Caspase 3 is activated in programmed cell death induced by both intrinsic (mitochondrial) and extrinsic factors (death ligand). Cell cycle and apoptosis are common parameters studied in the phenotypic analysis of compound toxicity and anti-cancer drugs. In this chapter, we describe methods for the detection of s-phase cell cycle progression by EdU incorporation, and caspase 3 activation using the CellEvent caspase 3/7 detection reagent.

Integrated spatiotemporal analysis for automatic contrast agent inflow detection on angiography and fluoroscopy during transcatheter aortic valve implantation.

PURPOSE: In this paper, the authors propose an integrated spatial and temporal analysis for automatic detection of contrast agent inflow at the aortic root on fluoroscopic and angiographic sequences during transcatheter aortic valve implantation procedures as a means to automatically trigger registration of 3D aortic models. METHODS: The proposed contrast agent inflow detection method is based on a contrast feature curve, calculated using histogram analysis and a likelihood ratio test. Several image preprocessing steps are performed to enhance the properties of the contrast feature curve. For sequences with a dominant peak on its contrast feature curve, a cascaded classifier is then applied to differentiate the contrast-enhanced aorta from contrast-enhanced balloons. Finally, a multilayer classifier based on sparse Gabor features is used to recognize sequences containing a faint contrast-enhanced aorta. RESULTS: The algorithm was evaluated using 105 sequences consisting of more than 12,000 frames, and achieved a detection accuracy of 99.1% (100% sensitivity and 98.5% specificity). The computation time for a typical sequence of 150 frames was ≈ 1 s on a single-core Dell PC with a 1 GHz Intel Xeon processor and 2 GB of RAM. CONCLUSIONS: The authors developed a novel, automatic method for contrast agent inflow detection on x-ray sequences. With the achieved efficiency and accuracy, the proposed method is potentially feasible for clinical use as it facilitates a seamless workflow in utilizing patient-specific 3D models to provide anatomical details during transcatheter aortic valve implantation procedures.

Learning the manifold of quality ultrasound acquisition.

Ultrasound acquisition is a challenging task that requires simultaneous adjustment of several acquisition parameters (the depth, the focus, the frequency and its operation mode). If the acquisition parameters are not properly chosen, the resulting image will have a poor quality and will degrade the patient diagnosis and treatment workflow. Several hardware-based systems for autotuning the acquisition parameters have been previously proposed, but these solutions were largely abandoned because they failed to properly account for tissue inhomogeneity and other patient-specific characteristics. Consequently, in routine practice the clinician either uses population-based parameter presets or manually adjusts the acquisition parameters for each patient during the scan. In this paper, we revisit the problem of autotuning the acquisition parameters by taking a completely novel approach and producing a solution based on image analytics. Our solution is inspired by the autofocus capability of conventional digital cameras, but is significantly more challenging because the number of acquisition parameters is large and the determination of "good quality" images is more difficult to assess. Surprisingly, we show that the set of acquisition parameters which produce images that are favored by clinicians comprise a 1D manifold, allowing for a real-time optimization to maximize image quality. We demonstrate our method for acquisition parameter autotuning on several live patients, showing that our system can start with a poor initial set of parameters and automatically optimize the parameters to produce high quality images.

Using a visual discrimination model for the detection of compression artifacts in virtual pathology images.

A major issue in telepathology is the extremely large and growing size of digitized "virtual" slides, which can require several gigabytes of storage and cause significant delays in data transmission for remote image interpretation and interactive visualization by pathologists. Compression can reduce this massive amount of virtual slide data, but reversible (lossless) methods limit data reduction to less than 50%, while lossy compression can degrade image quality and diagnostic accuracy. "Visually lossless" compression offers the potential for using higher compression levels without noticeable artifacts, but requires a rate-control strategy that adapts to image content and loss visibility. We investigated the utility of a visual discrimination model (VDM) and other distortion metrics for predicting JPEG 2000 bit rates corresponding to visually lossless compression of virtual slides for breast biopsy specimens. Threshold bit rates were determined experimentally with human observers for a variety of tissue regions cropped from virtual slides. For test images compressed to their visually lossless thresholds, just-noticeable difference (JND) metrics computed by the VDM were nearly constant at the 95th percentile level or higher, and were significantly less variable than peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) metrics. Our results suggest that VDM metrics could be used to guide the compression of virtual slides to achieve visually lossless compression while providing 5-12 times the data reduction of reversible methods.

Differential response to zinc-induced apoptosis in benign prostate hyperplasia and prostate cancer cells.

Zinc concentrations in the prostate are uniquely high but are dramatically decreased with prostate cancer. Studies have suggested that increasing zinc in the prostate may be a potential therapeutic strategy. The goal of this study was to evaluate the antiproliferative effects of zinc in prostate cancer cells (PC-3) and noncancerous benign prostate hyperplasia (BPH) cells (BPH-1) and to define possible mechanisms. PC-3 and BPH-1 cells were treated with zinc (0-250 microM) for 24 and 48 h, and cell growth and viability were examined. Apoptosis was assessed by phosphatidylserine externalization, caspase activation and protein expression of B-cell CLL/lymphoma 2 (Bcl-2)-associated X protein (BAX):Bcl-2. BPH-1 cells were more sensitive to the antiproliferative effects of zinc compared to PC-3. The response to zinc in PC-3 and BPH-1 cells differed as evidenced by opposing effects on Bcl-2:BAX expression. Additionally, different effects on the nuclear expression and activity of the p65 subunit of nuclear factor kappa B were observed in response to zinc between the two cell types. The differential response to zinc in PC-3 and BPH-1 cells suggests that zinc may serve an important role in regulating cell growth and apoptosis in prostate cancer and hyperplasia cells.

Alpha-tocopherol modulates genes involved in hepatic xenobiotic pathways in mice.

Hepatic proteins involved in xenobiotic pathways (Phases I, II and III) are responsible for the metabolism and disposition of endogenous and exogenous compounds including dietary phytochemicals. To test the hypothesis that elevated alpha-tocopherol intakes alter gene expression of hepatic xenobiotic pathways, mice were fed diets supplemented with either 1000 IU (+E) or 35 IU (E) all-rac-alpha-tocopheryl acetate for 4 months; liver RNA was isolated, and gene expression was determined using both whole genome microarray and real-time quantitative polymerase chain reaction analyses. Hepatic alpha-tocopherol (173+/-18 vs. 21+/-1 nmol/g, mean+/-S.E.) and its metabolite (2,5,7,8-tetramethyl-2-(2'-carboxyethyl)-6-hydroxychroman, 0.232+/-0.046 vs. 0.031+/-0.019 nmol/g) concentrations were approximately eightfold higher following the +E dietary treatment. In +E relative to E mice, gene expression of Phase I enzymes, P450 oxidoreductase and cytochrome P450 3a11 increased 1.6- and 4.0-fold, respectively; two Phase II genes, sulfotransferase 2a and glutathione S-transferase mu 3, increased 10.8- and 1.9-fold respectively, and a Phase III biliary transporter, Abcb1a, doubled. Thus, consumption of high-level dietary alpha-tocopherol simultaneously coordinated Phase I, II and III gene expression. These data demonstrate that increased hepatic alpha-tocopherol modulates its own concentrations through increasing xenobiotic metabolism, a process that may alter metabolism of other foreign compounds, such as therapeutic drugs and phytochemicals, in humans.

Zinc deficiency alters DNA damage response genes in normal human prostate epithelial cells.

Zinc is an essential trace element for human health and is a critical component of many proteins and transcription factors involved in DNA damage response and repair. The prostate is known to accumulate high levels of zinc, but levels are markedly decreased with cancer development. We hypothesized that zinc plays a critical role in maintaining DNA integrity in the prostate and zinc deficiency would lead to increased DNA damage and altered DNA damage response mechanisms. To test this hypothesis, the goal of this study was to determine the effects of zinc deficiency on DNA damage and DNA repair mechanisms by examining changes in global gene expression and transcription factor binding abilities in normal prostate epithelial cells (PrEC). Increased single-strand DNA breaks (Comet assay) were observed in PrEC grown in zinc-deficient media compared with cells grown in zinc-adequate media for 7 d. Using Affymetrix HG-U133A gene chips, differential expression of genes involved in cell cycle, apoptosis, transcription, and DNA damage response and repair were identified with low cellular zinc. Among genes involved in DNA damage response and repair, tumor protein p73, MRE11 meiotic recombination 11 homolog A, X-ray repair complementing defective repair in Chinese hamster cells 4, and breast cancer 2, early onset were down-regulated and TP53 was up-regulated. Additionally, western blotting showed increased nuclear p53 protein expression with zinc deficiency. Despite increased p53 gene and nuclear protein expression, there was no significant change in p53 binding activity. Zinc deficiency also induced an increase in binding activity of transcription factors involved in regulating cell proliferation and apoptosis. Thus, zinc deficiency may compromise DNA integrity in the prostate by impairing the function of zinc-containing proteins.

A region based algorithm for vessel detection in retinal images.

Accurate retinal blood vessel detection offers a great opportunity to predict and detect the stages of various ocular and systemic diseases, such as glaucoma, hypertension and congestive heart failure, since the change in width of blood vessels in retina has been reported as an independent and significant prospective risk factor for such diseases. In large-population studies of disease control and prevention, there exists an overwhelming need for an automatic tool that can reliably and accurately identify and measure retinal vessel diameters. To address requirements in this clinical setting, a vessel detection algorithm is proposed to quantitatively measure the salient properties of retinal vessel and combine the measurements by Bayesian decision to generate a confidence value for each detected vessel segment. The salient properties of vessels provide an alternative approach for retinal vessel detection at a level higher than detection at the pixel level. Experiments show superior detection performance than currently published results using a publicly available data set. More importantly, the proposed algorithm provides the confidence measurement that can be used as an objective criterion to select reliable vessel segments for diameter measurement.