Evidence map›Paper›PMID 23729641›Full record

ArticleCancer research2013

Application of Raman spectroscopy to identify microcalcifications and underlying breast lesions at stereotactic core needle biopsy.

Ishan Barman, Narahara Chari Dingari, Anushree Saha, Sasha McGee, Luis H Galindo, Wendy Liu, Donna Plecha, Nina Klein, Ramachandra Rao Dasari, Maryann Fitzmaurice

Open access · hybridAbstract read
In one paragraph

Article in Cancer research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
13.5field-weighted citation impact, top 1% 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

34 citing papers in PubMed, 1 synthesis or guideline pooled it, 92 citations in OpenAlex.

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  14. Molecular fingerprint of precancerous lesions in breast atypical hyperplasia.The Journal of international medical research · 2020
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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

10 authors at 3 institutions in 1 country.

Ishan BarmanG.R. Harrison Spectroscopy Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
Narahara Chari Dingari
Anushree Saha
Sasha McGee
Luis H Galindo
Wendy Liu
Donna Plecha
Nina Klein
Ramachandra Rao Dasari
Maryann Fitzmaurice
Massachusetts Institute of Technology · USCase Western Reserve University · USUniversity Hospitals Case Medical Center · US

Funding

Wide-Field Short-Wave Infrared (SWIR) multiphoton (MP) tissue imagingP41EB015871 · NIBIB · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI SO, PETER T. · 2012 to 2021
$11.3M
Raman Spectroscopy for Guidance of Stereotactic Breast Biopsies for MicrocalcificR01CA140288 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI FITZMAURICE, MARYANN · 2009 to 2011
$1.0M
NCI NIH HHS R01 CA140288NCI NIH HHS R01-CA140288NIBIB NIH HHS 9P41EB015871-26A1NIBIB NIH HHS P41 EB015871
6 · The paper itself

Abstract

Microcalcifications are a feature of diagnostic significance on a mammogram and a target for stereotactic breast needle biopsy. Here, we report development of a Raman spectroscopy technique to simultaneously identify microcalcification status and diagnose the underlying breast lesion, in real-time, during stereotactic core needle biopsy procedures. Raman spectra were obtained ex vivo from 146 tissue sites from fresh stereotactic breast needle biopsy tissue cores from 33 patients, including 50 normal tissue sites, 77 lesions with microcalcifications, and 19 lesions without microcalcifications, using a compact clinical system. The Raman spectra were modeled on the basis of the breast tissue components, and a support vector machine framework was used to develop a single-step diagnostic algorithm to distinguish normal tissue, fibrocystic change (FCC), fibroadenoma, and breast cancer, in the absence and presence of microcalcifications. This algorithm was subjected to leave-one-site-out cross-validation, yielding a positive predictive value, negative predictive value, sensitivity, and specificity of 100%, 95.6%, 62.5%, and 100% for diagnosis of breast cancer (with or without microcalcifications) and an overall accuracy of 82.2% for classification into specific categories of normal tissue, FCC, fibroadenoma, or breast cancer (with and without microcalcifications). Notably, the majority of breast cancers diagnosed are ductal carcinoma in situ (DCIS), the most common lesion associated with microcalcifications, which could not be diagnosed using previous Raman algorithm(s). Our study shows the potential of Raman spectroscopy to concomitantly detect microcalcifications and diagnose associated lesions, including DCIS, and thus provide real-time feedback to radiologists during such biopsy procedures, reducing nondiagnostic and false-negative biopsies.

Indexed as

AdultAgedAlgorithmsBiopsy, NeedleBreast DiseasesBreast NeoplasmsCalcinosisFemaleHumansMiddle AgedRadiographySpectrum Analysis, RamanStereotaxic Techniques

Identifiers

PMID23729641
PMCPMC3754785
OpenAlexW1986297321

What OpenQuestion holds

Textmetadata
LicenceTDM
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.