Evidence map›Paper›PMID 29446263›Full record

ArticleJournal of biomedical optics2018

Pulsed terahertz imaging of breast cancer in freshly excised murine tumors.

Tyler Bowman, Tanny Chavez, Kamrul Khan, Jingxian Wu, Avishek Chakraborty, Narasimhan Rajaram, Keith Bailey, Magda El-Shenawee

Abstract read
In one paragraph

Article in Journal of biomedical optics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
–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

23 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Biomedical application of terahertz imaging technology: a narrative review.Quantitative imaging in medicine and surgery · 2023
    Review
  5. Review
  6. Article
  7. Visual Enhancement and Semantic Segmentation of Murine Tissue Scans with Pulsed THz Spectroscopy.Proceedings. IEEE International Conference on Semantic Computing · 2023
    Article
  8. Review
  9. Article
  10. Article
  11. Terahertz Imaging for Breast Cancer Detection.Sensors (Basel, Switzerland) · 2021
    Review
  12. Article
  13. Article
  14. Frontiers in genetics · 2021
    Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Terahertz tomographic imaging of freshly excised human breast tissues.Journal of medical imaging (Bellingham, Wash.) · 2019
    Article
  20. 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.

Tyler BowmanUniversity of Arkansas, Bell Engineering Center, Department of Electrical Engineering, Fayetteville,, United States.
Tanny ChavezUniversity of Arkansas, Bell Engineering Center, Department of Electrical Engineering, Fayetteville,, United States.
Kamrul KhanUniversity of Arkansas, Science and Engineering Building, Department of Mathematical Sciences, Fayet, United States.
Jingxian WuUniversity of Arkansas, Bell Engineering Center, Department of Electrical Engineering, Fayetteville,, United States.
Avishek ChakrabortyUniversity of Arkansas, Science and Engineering Building, Department of Mathematical Sciences, Fayet, United States.
Narasimhan RajaramUniversity of Arkansas, Bell Engineering Center, Department of Biomedical Engineering, Fayetteville,, United States.
Keith BaileyOklahoma State University, Oklahoma Animal Disease Diagnostic Laboratory, Stillwater, Oklahoma, United States.
Magda El-ShenaweeUniversity of Arkansas, Bell Engineering Center, Department of Electrical Engineering, Fayetteville,, United States.

Funding

Terahertz Imaging for Margin Assessment of Three Dimensional Breast Cancer TumorsR15CA208798 · NCI · UNIVERSITY OF ARKANSAS AT FAYETTEVILLE · PI EL-SHENAWEE, MAGDA · 2017 to 2021
$849k
NCI NIH HHS R15 CA208798
6 · The paper itself

Abstract

This paper investigates terahertz (THz) imaging and classification of freshly excised murine xenograft breast cancer tumors. These tumors are grown via injection of E0771 breast adenocarcinoma cells into the flank of mice maintained on high-fat diet. Within 1 h of excision, the tumor and adjacent tissues are imaged using a pulsed THz system in the reflection mode. The THz images are classified using a statistical Bayesian mixture model with unsupervised and supervised approaches. Correlation with digitized pathology images is conducted using classification images assigned by a modal class decision rule. The corresponding receiver operating characteristic curves are obtained based on the classification results. A total of 13 tumor samples obtained from 9 tumors are investigated. The results show good correlation of THz images with pathology results in all samples of cancer and fat tissues. For tumor samples of cancer, fat, and muscle tissues, THz images show reasonable correlation with pathology where the primary challenge lies in the overlapping dielectric properties of cancer and muscle tissues. The use of a supervised regression approach shows improvement in the classification images although not consistently in all tissue regions. Advancing THz imaging of breast tumors from mice and the development of accurate statistical models will ultimately progress the technique for the assessment of human breast tumor margins.

Indexed as

AlgorithmsAnimalsBreast NeoplasmsCell Line, TumorFemaleHumansImage Interpretation, Computer-AssistedMammary Neoplasms, ExperimentalMiceModels, StatisticalTerahertz Imagingbiomedical opticsbreast cancermedical imagingmicemorphingstatistical modelingterahertz

Identifiers

PMID29446263
PMCPMC5812433

What OpenQuestion holds

Textmetadata
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.