Evidence map›Paper›PMID 26186251›Full record

ArticleApplied immunohistochemistry & molecular morphology : AIMM2016

Image-guided Coring for Large-scale Studies in Molecular Pathology.

Laleh Montaser-Kouhsari, Nicholas W Knoblauch, Eun-Yeong Oh, Gabrielle Baker, Stephen Christensen, Aditi Hazra, Rulla M Tamimi, Andrew H Beck

Open access · hybridAbstract read
In one paragraph

Article in Applied immunohistochemistry & molecular morphology : AIMM, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 33% of its field
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

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
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

8 authors at 2 institutions in 1 country.

Laleh Montaser-Kouhsari*Department of Pathology and Cancer Research Institute, Beth Israel Deaconess Medical Center †Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
Nicholas W Knoblauch
Eun-Yeong Oh
Gabrielle Baker
Stephen Christensen
Aditi Hazra
Rulla M Tamimi
Andrew H Beck
Brigham and Women's Hospital · USHarvard University · US

Funding

Statistical MethodsP01CA087969 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI ROSNER, BERNARD A · 2000 to 2019
$77.8M
Tissue and Pathology CoreP50CA168504 · NCI · DANA-FARBER CANCER INST · PI MYLES A BROWN · 2013 to 2026
$30.1M
Long Term Multidisciplinary Study of Cancer in Women: The Nurses Health StudyUM1CA186107 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI ELIASSEN, A. HEATHER, STAMPFER, MEIR · 2014 to 2023
$22.3M
Epidemiologic StudiesU19CA148065 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI AHSAN, HABIBUL, BRUGGE, JOAN SIEFERT · 2010 to 2014
$10.6M
INFORMATICS METHODS AND MODELS FOR COMPUTATIONAL PATHOLOGYK22LM011931 · NLM · BETH ISRAEL DEACONESS MEDICAL CENTER · PI BECK, ANDREW H · 2014 to 2016
$476k
NCI NIH HHS P01 CA087969NCI NIH HHS P50 CA168504NCI NIH HHS U19 CA148065NCI NIH HHS UM1 CA186107NLM NIH HHS K22 LM011931
6 · The paper itself

Abstract

Sampling of formalin-fixed paraffin-embedded (FFPE) tissue blocks is a critical initial step in molecular pathology. Image-guided coring (IGC) is a new method for using digital pathology images to guide tissue block coring for molecular analyses. The goal of our study is to evaluate the use of IGC for both tissue-based and nucleic acid-based projects in molecular pathology. First, we used IGC to construct a tissue microarray (TMA); second, we used IGC for FFPE block sampling followed by RNA extraction; and third, we assessed the correlation between nuclear counts quantitated from the IGC images and RNA yields. We used IGC to construct a TMA containing 198 normal and breast cancer cores. Histopathologic analysis showed high accuracy for obtaining tumor and normal breast tissue. Next, we used IGC to obtain normal and tumor breast samples before RNA extraction. We selected a random subset of tumor and normal samples to perform computational image analysis to quantify nuclear density, and we built regression models to estimate RNA yields from nuclear count, age of the block, and core diameter. Number of nuclei and core diameter were the strongest predictors of RNA yields in both normal and tumor tissue. IGC is an effective method for sampling FFPE tissue blocks for TMA construction and nucleic acid extraction. We identify significant associations between quantitative nuclear counts obtained from IGC images and RNA yields, suggesting that the integration of computational image analysis with IGC may be an effective approach for tumor sampling in large-scale molecular studies.

Indexed as

Pathology, MolecularHumansParaffin Embedding

Identifiers

PMID26186251
PMCPMC4715808
OpenAlexW2334021449

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.