Ontology-guided segmentation and object identification for developmental mouse lung immunofluorescent images.

BACKGROUND: Immunofluorescent confocal microscopy uses labeled antibodies as probes against specific macromolecules to discriminate between multiple cell types. For images of the developmental mouse lung, these cells are themselves organized into densely packed higher-level anatomical structures. These types of images can be challenging to segment automatically for several reasons, including the relevance of biomedical context, dependence on the specific set of probes used, prohibitive cost of generating labeled training data, as well as the complexity and dense packing of anatomical structures in the image. The use of an application ontology helps surmount these challenges by combining image data with its metadata to provide a meaningful biological context, modeled after how a human expert would make use of contextual information to identify histological structures, that constrains and simplifies the process of segmentation and object identification. RESULTS: We propose an innovative approach for the semi-supervised analysis of complex and densely packed anatomical structures from immunofluorescent images that utilizes an application ontology to provide a simplified context for image segmentation and object identification. We describe how the logical organization of biological facts in the form of an ontology can provide useful constraints that facilitate automatic processing of complex images. We demonstrate the results of ontology-guided segmentation and object identification in mouse developmental lung images from the Bioinformatics REsource ATlas for the Healthy lung database of the Molecular Atlas of Lung Development (LungMAP1) program CONCLUSION: We describe a novel ontology-guided approach to segmentation and classification of complex immunofluorescence images of the developing mouse lung. The ontology is used to automatically generate constraints for each image based on its biomedical context, which facilitates image segmentation and classification.

Rapid Molecular Diagnostics to Inform Empiric Use of Ceftazidime/Avibactam and Ceftolozane/Tazobactam Against Pseudomonas aeruginosa: PRIMERS IV.

BACKGROUND: Overcoming ß-lactam resistance in pathogens such as Pseudomonas aeruginosa is a major clinical challenge. Rapid molecular diagnostics (RMDs) have the potential to inform selection of empiric therapy in patients infected by P. aeruginosa. METHODS: In this study, we used a heterogeneous collection of 197 P. aeruginosa that included multidrug-resistant isolates to determine whether 2 representative RMDs (Acuitas Resistome test and VERIGENE gram-negative blood culture test) could identify susceptibility to 2 newer ß-lactam/ß-lactamase inhibitor (BL-BLI) combinations, ceftazidime/avibactam (CZA) and ceftolozane/tazobactam (TOL/TAZO). RESULTS: We found that the studied RMD platforms were able to correctly identify BL-BLI susceptibility (susceptibility sensitivity, 100%; 95% confidence interval [CI], 97%, 100%) for both BLs-BLIs. However, their ability to detect resistance to these BLs-BLIs was lower (resistance sensitivity, 66%; 95% CI, 52%, 78% for TOL/TAZO and 33%; 95% CI, 20%, 49% for CZA). CONCLUSIONS: The diagnostic platforms studied showed the most potential in scenarios where a resistance gene was detected or in scenarios where a resistance gene was not detected and the prevalence of resistance to TOL/TAZO or CZA is known to be low. Clinicians need to be mindful of the benefits and risks that result from empiric treatment decisions that are based on resistance gene detection in P. aeruginosa, acknowledging that such decisions are impacted by the prevalence of resistance, which varies temporally and geographically.

Informing Antibiotic Treatment Decisions: Evaluating Rapid Molecular Diagnostics To Identify Susceptibility and Resistance to Carbapenems against Acinetobacter spp. in PRIMERS III.

The widespread dissemination of carbapenem-resistant Acinetobacter spp. has created significant therapeutic challenges. At present, rapid molecular diagnostics (RMDs) that can identify this phenotype are not commercially available. Two RMD platforms, PCR combined with electrospray ionization mass spectrometry (PCR/ESI-MS) and molecular beacons (MB), for detecting genes conferring resistance/susceptibility to carbapenems in Acinetobacter spp. were evaluated. An archived collection of 200 clinical Acinetobacter sp. isolates was tested. Predictive values for susceptibility and resistance were estimated as a function of susceptibility prevalence and were based on the absence or presence of beta-lactamase (bla) NDM, VIM, IMP, KPC, and OXA carbapenemase genes (e.g., blaOXA-23, blaOXA-24/40, and blaOXA-58 found in this study) against the reference standard of MIC determinations. According to the interpretation of MICs, 49% (n = 98) of the isolates were carbapenem resistant (as defined by either resistance or intermediate resistance to imipenem). The susceptibility sensitivities (95% confidence interval [CI]) for imipenem were 82% (74%, 89%) and 92% (85%, 97%) for PCR/ESI-MS and MB, respectively. Resistance sensitivities (95% CI) for imipenem were 95% (88%, 98%) and 88% (80%, 94%) for PCR/ESI-MS and MB, respectively. PRIMERS III establishes that RMDs can discriminate between carbapenem resistance and susceptibility in Acinetobacter spp. In the context of a known prevalence of resistance, SPVs and RPVs can inform clinicians regarding the best choice for empiric antimicrobial therapy against this multidrug-resistant pathogen.

Rapid Molecular Diagnostics, Antibiotic Treatment Decisions, and Developing Approaches to Inform Empiric Therapy: PRIMERS I and II.

BACKGROUND: Rapid molecular diagnostic (RMD) platforms may lead to better antibiotic use. Our objective was to develop analytical strategies to enhance the interpretation of RMDs for clinicians. METHODS: We compared the performance characteristics of 4 RMD platforms for detecting resistance against ß-lactams in 72 highly resistant isolates of Escherichia coli and Klebsiella pneumoniae (PRIMERS I). Subsequently, 2 platforms were used in a blinded study in which a heterogeneous collection of 196 isolates of E. coli and K. pneumoniae (PRIMERS II) were examined. We evaluated the genotypic results as predictors of resistance or susceptibility against ß-lactam antibiotics. We designed analytical strategies and graphical representations of platform performance, including discrimination summary plots and susceptibility and resistance predictive values, that are readily interpretable by practitioners to inform decision-making. RESULTS: In PRIMERS I, the 4 RMD platforms detected ß-lactamase (bla) genes and identified susceptibility or resistance in >95% of cases. In PRIMERS II, the 2 platforms identified susceptibility against extended-spectrum cephalosporins and carbapenems in >90% of cases; however, against piperacillin/tazobactam, susceptibility was identified in <80% of cases. Applying the analytical strategies to a population with 15% prevalence of ceftazidime-resistance and 5% imipenem-resistance, RMD platforms predicted susceptibility in >95% of cases, while prediction of resistance was 69%-73% for ceftazidime and 41%-50% for imipenem. CONCLUSIONS: RMD platforms can help inform empiric ß-lactam therapy in cases where bla genes are not detected and the prevalence of resistance is known. Our analysis is a first step in bridging the gap between RMDs and empiric treatment decisions.