Dataset Information

A robust co-localisation measurement utilising z-stack image intensity similarities for biological studies.

ABSTRACT: BACKGROUND: Co-localisation is a widely used measurement in immunohistochemical analysis to determine if fluorescently labelled biological entities, such as cells, proteins or molecules share a same location. However the measurement of co-localisation is challenging due to the complex nature of such fluorescent images, especially when multiple focal planes are captured. The current state-of-art co-localisation measurements of 3-dimensional (3D) image stacks are biased by noise and cross-overs from non-consecutive planes. METHOD: In this study, we have developed Co-localisation Intensity Coefficients (CICs) and Co-localisation Binary Coefficients (CBCs), which uses rich z-stack data from neighbouring focal planes to identify similarities between image intensities of two and potentially more fluorescently-labelled biological entities. This was developed using z-stack images from murine organotypic slice cultures from central nervous system tissue, and two sets of pseudo-data. A large amount of non-specific cross-over situations are excluded using this method. This proposed method is also proven to be robust in recognising co-localisations even when images are polluted with a range of noises. RESULTS: The proposed CBCs and CICs produce robust co-localisation measurements which are easy to interpret, resilient to noise and capable of removing a large amount of false positivity, such as non-specific cross-overs. Performance of this method of measurement is significantly more accurate than existing measurements, as determined statistically using pseudo datasets of known values. This method provides an important and reliable tool for fluorescent 3D neurobiological studies, and will benefit other biological studies which measure fluorescence co-localisation in 3D.

SUBMITTER: Wang Y

PROVIDER: S-EPMC3281864 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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A robust co-localisation measurement utilising z-stack image intensity similarities for biological studies.

Wang Yinhai Y Ledgerwood Craig C Grills Claire C Fitzgerald Denise C DC Hamilton Peter W PW

PloS one 20120217 2

<h4>Background</h4>Co-localisation is a widely used measurement in immunohistochemical analysis to determine if fluorescently labelled biological entities, such as cells, proteins or molecules share a same location. However the measurement of co-localisation is challenging due to the complex nature of such fluorescent images, especially when multiple focal planes are captured. The current state-of-art co-localisation measurements of 3-dimensional (3D) image stacks are biased by noise and cross-o ...[more]

PMID: 22363456

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Project description:PURPOSE:To investigate the consequences of residual setup error on target dose distribution using various image registration strategies for breast cancer treated with intensity-modulated proton therapy (IMPT). MATERIALS AND METHODS:Among 11 post-lumpectomy patients who received IMPT, 44 dose distributions were computed. For each patient, the original plan (Plan-O) and three verification plans were calculated using different alignments: bony anatomy (VPlan-B), breast tissue (VPlan-T), and skin (VPlan-S). The target coverage were evaluated for each alignment technique. Additionally, 2 subvolumes-BreastNearSkin (1-cm rim of anterior CTV) and BreastNearCW (1-cm rim of posterior CTV)-were created to help localize CTV underdosing. Furthermore, we divided the setup error into the posture error and breast error. Patients with a large posture error and those with good posture setup but a large breast error were identified to evaluate the effect of posture error and breast error. RESULTS:For Plan-O, VPlan-B, VPlan-T, and VPlan-S, respectively, the median (interquartile range) breast CTV D95 was 95.7%(94.7-96.3%), 95.1% (93.9-95.7%), 95.2% (94.8-95.6%), and 95.2% (94.9-95.7%); BreastNearCW D95 was 96.9% (95.6-97.3%), 94.8% (93.5-97.0%), 95.6% (94.8-97.0%), 95.6% (94.8-97.1%); and BreastNearSkin D95 was 94.1% (92.7-94.4%), 93.6% (92.2-94.5%), 93.5% (92.4-94.5%), and 94.4% (92.2-94.5%) of the prescription dose. 4/11 patients had ?1% decrease in breast CTV D95, 1 of whom developed breast edema while the other 3 all had a?>?2o posture error. The CTV D95 variation was within 1% for the patients with good posture setup but >2o breast error. CONCLUSION:Acceptable target coverage was achieved with all three alignment strategies. Breast tissue and skin alignment maintained the breast target coverage marginally better than bony alignment, with which the posterior CTV along the chest wall is the predominant area affected by under-dosing. For target dose distribution, posture error appears more influential than breast error.

Dataset Information

A robust co-localisation measurement utilising z-stack image intensity similarities for biological studies.

Publications

A robust co-localisation measurement utilising z-stack image intensity similarities for biological studies.

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