Evidence map›Paper›PMID 18510512›Full record

ArticleJournal of anatomy2008

Quantification of diverse subcellular immunohistochemical markers with clinicobiological relevancies: validation of a new computer-assisted image analysis procedure.

Marylène Lejeune, Joaquín Jaén, Lluis Pons, Carlos López, Maria-Teresa Salvadó, Ramón Bosch, Marcial García, Patricia Escrivà, Jordi Baucells, Xavier Cugat and 1 more

Abstract readComparative StudyValidation Study
In one paragraph

Article in Journal of anatomy, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed.

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  18. Automated analysis of immunohistochemistry images identifies candidate location biomarkers for cancers.Proceedings of the National Academy of Sciences of the United States of America · 2014
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Marylène LejeuneDepartment of Pathology, Hospital de Tortosa Verge de la Cinta, Tortosa, Spain. mlejeune.htvc.ics@gencat.net
Joaquín Jaén
Lluis Pons
Carlos López
Maria-Teresa Salvadó
Ramón Bosch
Marcial García
Patricia Escrivà
Jordi Baucells
Xavier Cugat
Tomás Alvaro

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tissue microarray technology and immunohistochemical techniques have become a routine and indispensable tool for current anatomical pathology diagnosis. However, manual quantification by eye is relatively slow and subjective, and the use of digital image analysis software to extract information of immunostained specimens is an area of ongoing research, especially when the immunohistochemical signals have different localization in the cells (nuclear, membrane, cytoplasm). To minimize critical aspects of manual quantitative data acquisition, we generated semi-automated image-processing steps for the quantification of individual stained cells with immunohistochemical staining of different subcellular location. The precision of these macros was evaluated in 196 digital colour images of different Hodgkin lymphoma biopsies stained for different nuclear (Ki67, p53), cytoplasmic (TIA-1, CD68) and membrane markers (CD4, CD8, CD56, HLA-Dr). Semi-automated counts were compared to those obtained manually by three separate observers. Paired t-tests demonstrated significant differences between intra- and inter-observer measurements, with more substantial variability when the cellular density of the digital images was > 100 positive cells/image. Overall, variability was more pronounced for intra-observer than for inter-observer comparisons, especially for cytoplasmic and membrane staining patterns (P < 0.0001 and P = 0.050). The comparison between the semi-automated and manual microscopic measurement methods indicates significantly lower variability in the results yielded by the former method. Our semi-automated computerized method eliminates the major causes of observer variability and may be considered a valid alternative to manual microscopic quantification for diagnostic, prognostic and therapeutic purposes.

Indexed as

Image Processing, Computer-AssistedImmunohistochemistryPattern Recognition, AutomatedAntigensAntigens, CDAntigens, Differentiation, MyelomonocyticBiomarkers, TumorCD4 AntigensCD56 AntigenCD68 MoleculeCD8 AntigensHLA-DR AntigensHodgkin DiseaseHumansKi-67 AntigenObserver VariationAntigensAntigens, CDAntigens, Differentiation, MyelomonocyticBiomarkers, TumorCD4 AntigensCD56 AntigenCD68 antigen, humanCD68 MoleculeCD8 AntigensHLA-DR AntigensKi-67 AntigenPoly(A)-Binding ProteinsT-Cell Intracellular Antigen-1TIA1 protein, humanTumor Suppressor Protein p53

Identifiers

PMID18510512
PMCPMC2423408

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.