Evidence map›Paper›PMID 34750471›Full record

ArticleScientific reports2021

Developing diagnostic assessment of breast lumpectomy tissues using radiomic and optical signatures.

Samuel S Streeter, Brady Hunt, Rebecca A Zuurbier, Wendy A Wells, Keith D Paulsen, Brian W Pogue

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 29% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. 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

6 authors at 2 institutions in 1 country.

Samuel S StreeterThayer School of Engineering, Dartmouth College, 14 Engineering Dr., Hanover, NH, 03755, USA. Samuel.S.Streeter.TH@Dartmouth.edu.
Brady HuntThayer School of Engineering, Dartmouth College, 14 Engineering Dr., Hanover, NH, 03755, USA.
Rebecca A ZuurbierDepartment of Radiology, Dartmouth-Hitchcock Medical Center, 1 Medical Center Dr., Lebanon, NH, 03756, USA.
Wendy A WellsDepartment of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical Center, 1 Medical Center Dr., Lebanon, NH, 03756, USA.
Keith D PaulsenThayer School of Engineering, Dartmouth College, 14 Engineering Dr., Hanover, NH, 03755, USA.
Brian W PogueThayer School of Engineering, Dartmouth College, 14 Engineering Dr., Hanover, NH, 03755, USA.
Dartmouth College · USDartmouth–Hitchcock Medical Center · US

Funding

Optical Scatter Imaging System for Surgical Specimen Margin Assessment during Breast Conserving SurgeryR01CA192803 · NCI · DARTMOUTH COLLEGE · PI PAULSEN, KEITH D., POGUE, BRIAN WILLIAM · 2015 to 2019
$2.7M
Breast-conserving surgery resection margin assessment using optical light active line scanningF31CA257340 · NCI · DARTMOUTH COLLEGE · PI STREETER, SAMUEL STEWART · 2021 to 2022
$68k
NCI NIH HHS F31 CA257340NCI NIH HHS R01 CA192803NCI NIH HHS R01CA192803
6 · The paper itself

Abstract

High positive margin rates in oncologic breast-conserving surgery are a pressing clinical problem. Volumetric X-ray scanning is emerging as a powerful ex vivo specimen imaging technique for analyzing resection margins, but X-rays lack contrast between non-malignant and malignant fibrous tissues. In this study, combined micro-CT and wide-field optical image radiomics were developed to classify malignancy of breast cancer tissues, demonstrating that X-ray/optical radiomics improve malignancy classification. Ninety-two standardized features were extracted from co-registered micro-CT and optical spatial frequency domain imaging samples extracted from 54 breast tumors exhibiting seven tissue subtypes confirmed by microscopic histological analysis. Multimodal feature sets improved classification performance versus micro-CT alone when adipose samples were included (AUC = 0.88 vs. 0.90; p-value = 3.65e-11) and excluded, focusing the classification task on exclusively non-malignant fibrous versus malignant tissues (AUC = 0.78 vs. 0.85; p-value = 9.33e-14). Extending the radiomics approach to high-dimensional optical data-termed "optomics" in this study-offers a promising optical image analysis technique for cancer detection. Radiomic feature data and classification source code are publicly available.

Indexed as

Adipose TissueBreast NeoplasmsFemaleHumansIn Vitro TechniquesMargins of ExcisionMastectomy, SegmentalMultimodal ImagingOptical ImagingOptical PhenomenaStochastic ProcessesX-Ray Microtomography

Identifiers

PMID34750471
PMCPMC8575781
OpenAlexW3213445676

What OpenQuestion holds

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LicenceCC BY
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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.