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Applicability of digital analysis and imaging technology in neuropathology assessment.

ABSTRACT: Alzheimer's disease (AD) is a progressive neurological disorder that affects more than 30 million people worldwide. While various dementia-related losses in cognitive functioning are its hallmark clinical symptoms, ultimate diagnosis is based on manual neuropathological assessments using various schemas, including Braak staging, CERAD (Consortium to Establish a Registry for Alzheimer's Disease) and Thal phase scoring. Since these scoring systems are based on subjective assessment, there is inevitably some degree of variation between readers, which could affect ultimate neuropathology diagnosis. Here, we report a pilot study investigating the applicability of computer-driven image analysis for characterizing neuropathological features, as well as its potential to supplement or even replace manually derived ratings commonly performed in medical settings. In this work, we quantitatively measured amyloid beta (A?) plaque in various brain regions from 34 patients using a robust digital quantification algorithm. We next verified these digitally derived measures to the manually derived pathology ratings using correlation and ordinal logistic regression methods, while also investigating the association with other AD-related neuropathology scoring schema commonly used at autopsy, such as Braak and CERAD. In addition to successfully verifying our digital measurements of A? plaques with respective categorical measurements, we found significant correlations with most AD-related scoring schemas. Our results demonstrate the potential for digital analysis to be adapted to more complex staining procedures commonly used in neuropathological diagnosis. As the efficiency of scanning and digital analysis of histology images increases, we believe that the basis of our semi-automatic approach may better standardize quantification of neuropathological changes and AD diagnosis, ultimately leading to a more comprehensive understanding of neurological disorders and more efficient patient care.

SUBMITTER: Dunn WD

PROVIDER: S-EPMC5452679 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Applicability of digital analysis and imaging technology in neuropathology assessment.

Dunn William D WD Gearing Marla M Park Yuna Y Zhang Lifan L Hanfelt John J Glass Jonathan D JD Gutman David A DA

Neuropathology : official journal of the Japanese Society of Neuropathology 20151118 3

Alzheimer's disease (AD) is a progressive neurological disorder that affects more than 30 million people worldwide. While various dementia-related losses in cognitive functioning are its hallmark clinical symptoms, ultimate diagnosis is based on manual neuropathological assessments using various schemas, including Braak staging, CERAD (Consortium to Establish a Registry for Alzheimer's Disease) and Thal phase scoring. Since these scoring systems are based on subjective assessment, there is inevi ...[more]

PMID: 26577803

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Project description:A rapidly increasing flow of genomic data requires the development of efficient methods for obtaining its compact representation. Feature extraction facilitates classification, clustering and model analysis for testing and refining biological hypotheses. "Shotgun" metagenome is an analytically challenging type of genomic data - containing sequences of all genes from the totality of a complex microbial community. Recently, researchers started to analyze metagenomes using reference-free methods based on the analysis of oligonucleotides (k-mers) frequency spectrum previously applied to isolated genomes. However, little is known about their correlation with the existing approaches for metagenomic feature extraction, as well as the limits of applicability. Here we evaluated a metagenomic pairwise dissimilarity measure based on short k-mer spectrum using the example of human gut microbiota, a biomedically significant object of study.We developed a method for calculating pairwise dissimilarity (beta-diversity) of "shotgun" metagenomes based on short k-mer spectra (5 ? k ? 11). The method was validated on simulated metagenomes and further applied to a large collection of human gut metagenomes from the populations of the world (n=281). The k-mer spectrum-based measure was found to behave similarly to one based on mapping to a reference gene catalog, but different from one using a genome catalog. This difference turned out to be associated with a significant presence of viral reads in a number of metagenomes. Simulations showed limited impact of bacterial genetic variability as well as sequencing errors on k-mer spectra. Specific differences between the datasets from individual populations were identified.Our approach allows rapid estimation of pairwise dissimilarity between metagenomes. Though we applied this technique to gut microbiota, it should be useful for arbitrary metagenomes, even metagenomes with novel microbiota. Dissimilarity measure based on k-mer spectrum provides a wider perspective in comparison with the ones based on the alignment against reference sequence sets. It helps not to miss possible outstanding features of metagenomic composition, particularly related to the presence of an unknown bacteria, virus or eukaryote, as well as to technical artifacts (sample contamination, reads of non-biological origin, etc.) at the early stages of bioinformatic analysis. Our method is complementary to reference-based approaches and can be easily integrated into metagenomic analysis pipelines.

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Project description:PurposeThis pilot study developed and evaluated the feasibility, usability, and perceived satisfaction with an end-user mobile medical application and provider web portal. The two interfaces allowed for remote monitoring, provided daily guidance in the management of hypertension and diarrhea, and allowed for rapid management of adverse events during a clinical trial of olaparib and cediranib.Patients and methodseCO (eCediranib/Olaparib) was designed for patient self-reported, real-time management of hypertension and diarrhea using remote monitoring. eCO links to a Bluetooth-enabled blood pressure (BP) monitor and transmits data to a secure provider web portal. eCO use was assessed for suitability, usability, and satisfaction after 4 weeks using a 17-item questionnaire. Metrics regarding patient-reported BP and diarrhea events were analyzed.ResultsSixteen patients enrolled in the pilot. A total of 98.2% of expected BP values were reported: 94.2% via Bluetooth and 5.8% entered manually. Twelve patients experienced 21 BP events (systolic BP > 140 and/or diastolic BP > 90 mmHg on two consecutive readings); data from cycle 1 were comparable to the study database. Thirteen patients reported diarrhea (more than one stool per 24 hours over baseline) categorized as grade 1 or 2, which was comparable to the study database. Survey analysis showed that patients had statistically significant, positive responses to the use of the eCO application. Patients indicated eCO use made them feel more involved in their care and better connected to their health care team. The only aspect of the application that did not show a statistically significant positive response was the process of reporting diarrhea.ConclusionThe eCO application was designed to assist in managing acute treatment-related events most often associated with treatment discontinuation, need for drug holidays, or dose interruption. Hypertension and diarrhea events reported via eCO allowed rapid provider response and a positive overall patient experience.

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Applicability of digital analysis and imaging technology in neuropathology assessment.

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Applicability of digital analysis and imaging technology in neuropathology assessment.

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