A computer-assisted system for handheld whole-breast ultrasonography.

PURPOSE: Breast ultrasonography (US) presents an alternative to mammography in young asymptomatic individuals and a complementary examination in screening of women with dense breasts. Handheld US is the standard-of-care, yet when used in whole-breast examination, no effort has been devoted to monitoring breast coverage and missed regions, which is the purpose of this study. METHODS: We introduce a computer-aided system assisting radiologists and US technologists in covering the whole breast with minimum alteration to the standard workflow. The proposed system comprises a standard US device, proprietary electromagnetic 3D tracking technology and software that combines US visual and tracking data to estimate a probe trajectory, total time spent in different breast segments, and a map of missed regions. A case study, which involved four radiologists (two junior and two senior) performing whole-breast ultrasound in 75 asymptomatic patients, was conducted to test the importance and relevance of the system. RESULTS: The mean process time per breast was [Formula: see text], with no statistically significant difference between the left and the right sides, and slightly longer examination time of junior radiologists. The process time density shows that central parts of the breast have better coverage compared to the periphery. Within the central part, missed regions of minimum detectable size of [Formula: see text] occur in [Formula: see text] of examinations, and non-negligible [Formula: see text] regions occur in [Formula: see text] of cases. CONCLUSION: The results of the case study indicate that missed regions are present in handheld whole-breast US, which renders the proposed system for tracking the probe position during examination a valuable tool for monitoring coverage.

Propagation Kinetics of Isoprene-Glycidyl Methacrylate Copolymerizations Investigated via PLP-SEC.

Pulsed-laser polymerization combined with polymer analysis by NMR and size-exclusion chromatography is used to study the radical copolymerization kinetics of isoprene (IP) with glycidyl methacrylate (GMA). The copolymer is characterized by a close-to-alternating microstructure, with the addition of IP leading to a significant decrease in the composition-averaged propagation rate coefficient. A rigorous fitting strategy is developed to fit a mixed penultimate model to the data, with the selectivity of the IP, but not the GMA, macroradical dependent on the penultimate unit.

The Effect of Hydrogen Bonding on Radical Semi-Batch Copolymerization of Butyl Acrylate and 2-Hydroxyethyl Acrylate.

The radical copolymerization of butyl acrylate (BA) and 2-hydroxyethyl acrylate (HEA) was investigated under batch and semi-batch operations, with a focus on the influence of hydrogen-bonding on acrylate backbiting. The effect of hydrogen bonding on HEA to BA relative incorporation rates during copolymerization, previously seen in low-conversion kinetic studies, was also observed under high-conversion semi-batch conditions. However, overall reaction rates (as indicated by free monomer concentrations), polymer molar masses, and branching levels did not vary as copolymer HEA content was increased from 0 to 40 wt % in the semi-batch system. In contrast, introduction of a H-bonding solvent, n-pentanol, led to an observable decrease in branching levels, and branching levels were also reduced in batch (co)polymerizations with HEA. These differences can be attributed to the low levels of unreacted HEA in the starved-feed semi-batch system.

Automated Analysis of Microscopic Images of Isolated Pancreatic Islets.

Clinical islet transplantation programs rely on the capacities of individual centers to quantify isolated islets. Current computer-assisted methods require input from human operators. Here we describe two machine learning algorithms for islet quantification: the trainable islet algorithm (TIA) and the nontrainable purity algorithm (NPA). These algorithms automatically segment pancreatic islets and exocrine tissue on microscopic images in order to count individual islets and calculate islet volume and purity. References for islet counts and volumes were generated by the fully manual segmentation (FMS) method, which was validated against the internal DNA standard. References for islet purity were generated via the expert visual assessment (EVA) method, which was validated against the FMS method. The TIA is intended to automatically evaluate micrographs of isolated islets from future donors after being trained on micrographs from a limited number of past donors. Its training ability was first evaluated on 46 images from four donors. The pixel-to-pixel comparison, binary statistics, and islet DNA concentration indicated that the TIA was successfully trained, regardless of the color differences of the original images. Next, the TIA trained on the four donors was validated on an additional 36 images from nine independent donors. The TIA was fast (67 s/image), correlated very well with the FMS method (R2=1.00 and 0.92 for islet volume and islet count, respectively), and had small REs (0.06 and 0.07 for islet volume and islet count, respectively). Validation of the NPA against the EVA method using 70 images from 12 donors revealed that the NPA had a reasonable speed (69 s/image), had an acceptable RE (0.14), and correlated well with the EVA method (R2=0.88). Our results demonstrate that a fully automated analysis of clinical-grade micrographs of isolated pancreatic islets is feasible. The algorithms described herein will be freely available as a Fiji platform plugin.

A transgenic minipig model of Huntington's Disease.

BACKGROUND: Some promising treatments for Huntington's disease (HD) may require pre-clinical testing in large animals. Minipig is a suitable species because of its large gyrencephalic brain and long lifespan. OBJECTIVE: To generate HD transgenic (TgHD) minipigs encoding huntingtin (HTT)1-548 under the control of human HTT promoter. METHODS: Transgenesis was achieved by lentiviral infection of porcine embryos. PCR assessment of gene transfer, observations of behavior, and postmortem biochemical and immunohistochemical studies were conducted. RESULTS: One copy of the human HTT transgene encoding 124 glutamines integrated into chromosome 1 q24-q25 and successful germ line transmission occurred through successive generations (F0, F1, F2 and F3 generations). No developmental or gross motor deficits were noted up to 40 months of age. Mutant HTT mRNA and protein fragment were detected in brain and peripheral tissues. No aggregate formation in brain up to 16 months was seen by AGERA and filter retardation or by immunostaining. DARPP32 labeling in WT and TgHD minipig neostriatum was patchy. Analysis of 16 month old sibling pairs showed reduced intensity of DARPP32 immunoreactivity in neostriatal TgHD neurons compared to those of WT. Compared to WT, TgHD boars by one year had reduced fertility and fewer spermatozoa per ejaculate. In vitro analysis revealed a significant decline in the number of WT minipig oocytes penetrated by TgHD spermatozoa. CONCLUSIONS: The findings demonstrate successful establishment of a transgenic model of HD in minipig that should be valuable for testing long term safety of HD therapeutics. The emergence of HD-like phenotypes in the TgHD minipigs will require more study.