Evidence map›Paper›PMID 38975057›Full record

ArticleJournal of clinical imaging science2024

Next-generation digital chest tomosynthesis.

Christopher Gange, Jamie Ku, Babina Gosangi, Jianqiang Liu, Manat Maolinbay

Abstract read
In one paragraph

Article in Journal of clinical imaging science, 2024. 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
–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

3 citing papers in PubMed.

  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

5 authors.

Christopher GangeDepartment of Radiology and Biomedical Imaging, Yale University, New Haven, Connecticut, United States.
Jamie KuProduct Development, Aixscan Inc., Sunnyvale, California, United States.
Babina GosangiDepartment of Radiology and Biomedical Imaging, Yale University, New Haven, Connecticut, United States.
Jianqiang LiuProduct Development, Aixscan Inc., Sunnyvale, California, United States.
Manat MaolinbayProduct Development, Aixscan Inc., Sunnyvale, California, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The objective of this study was to demonstrate the performance characteristics and potential utility of a novel tomosynthesis device as applied to imaging the chest, specifically relating to lung nodules. The imaging characteristics and quality of a novel digital tomosynthesis prototype system was assessed by scanning, a healthy volunteer, and an andromorphic lung phantom with different configurations of simulated pulmonary nodules. The adequacy of nodule detection on the phantoms was rated by chest radiologists using a standardized scale. Results from using this tomosynthesis device demonstrate in plane resolution of 16lp/cm, with estimated effective radiation doses of 90% less than low dose CT. Nodule detection was adequate across various anatomic locations on a phantom. These proof-of-concept tests showed this novel tomosynthesis device can detect lung nodules with low radiation dose to the patient. This technique has potential as an alternative to low dose chest CT for lung nodule screening and tracking.

Indexed as

Chest radiographyLung nodulesMedical imagingTomosynthesis

Identifiers

PMID38975057
PMCPMC11225395

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.