Evidence map›Paper›PMID 25558431›Full record

ArticleJournal of clinical imaging science2014

Dedicated Breast CT: Feasibility for Monitoring Neoadjuvant Chemotherapy Treatment.

Srinivasan Vedantham, Avice M O'Connell, Linxi Shi, Andrew Karellas, Alissa J Huston, Kristin A Skinner

Abstract read
In one paragraph

Article in Journal of clinical imaging science, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
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  12. Cone-beam breast computed tomography using ultra-fast image reconstruction with constrained, total-variation minimization for suppression of artifacts.Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) · 2020
    Article
  13. Article
  14. Emerging Breast Imaging Technologies on the Horizon.Seminars in ultrasound, CT, and MR · 2018
    Article
  15. Review
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  17. 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.

Srinivasan VedanthamDepartment of Radiology, University of Massachusetts Medical School, Worcester, Massachusetts, USA.
Avice M O'ConnellDepartment of Imaging Sciences, University of Rochester Medical Center, Rochester, New York, USA.
Linxi ShiDepartment of Radiology, University of Massachusetts Medical School, Worcester, Massachusetts, USA.
Andrew KarellasDepartment of Radiology, University of Massachusetts Medical School, Worcester, Massachusetts, USA.
Alissa J HustonDepartment of Medicine, Divisions of Hematology/Oncology, University of Rochester Medical Center, Rochester, New York, USA.
Kristin A SkinnerDepartment of Surgery, University of Rochester Medical Center, Rochester, New York, USA.

Funding

Quantitative breast cancer risk index from routine 3-D imagingR21CA176470 · NCI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI VEDANTHAM, SRINIVASAN · 2013 to 2014
$394k
NCI NIH HHS R21 CA176470
6 · The paper itself

Abstract

objectivesIn this prospective pilot study, the feasibility of non-contrast dedicated breast computed tomography (bCT) to determine primary tumor volume and monitor its changes during neoadjuvant chemotherapy (NAC) treatment was investigated. MATERIALS AND

methodsEleven women who underwent NAC were imaged with a clinical prototype dedicated bCT system at three time points - pre-, mid-, and post-treatment. The study radiologist marked the boundary of the primary tumor from which the tumor volume was quantified. An automated algorithm was developed to quantify the primary tumor volume for comparison with radiologist's segmentation. The correlation between pre-treatment tumor volumes from bCT and MRI, and the correlation and concordance in tumor size between post-treatment bCT and pathology were determined.

resultsTumor volumes from automated and radiologist's segmentations were correlated (Pearson's r = 0.935, P < 0.001) and were not different over all time points [P = 0.808, repeated measures analysis of variance (ANOVA)]. Pre-treatment tumor volumes from MRI and bCT were correlated (r = 0.905, P < 0.001). Tumor size from post-treatment bCT was correlated with pathology (r = 0.987, P = 0.002) for invasive ductal carcinoma larger than 5 mm and the maximum difference in tumor size was 0.57 cm. The presence of biopsy clip (3 mm) limited the ability to accurately measure tumors smaller than 5 mm. All study participants were pathologically assessed to be responders, with three subjects experiencing complete pathologic response for invasive cancer and the reminder experiencing partial response. Compared to pre-treatment tumor volume, there was a statistically significant (P = 0.0003, paired t-test) reduction in tumor volume at mid-treatment observed with bCT, with an average tumor volume reduction of 47%.

conclusionsThis pilot study suggests that dedicated non-contrast bCT has the potential to serve as an expedient imaging tool for monitoring tumor volume changes during NAC. Larger studies are needed in future.

Indexed as

Breastdedicated breast CTneoadjuvant chemotherapytomographytumor size

Identifiers

PMID25558431
PMCPMC4278089

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.