Evidence map›Paper›PMID 32419896›Full record

ArticleRadiology case reports2020

Preoperative assessment of lung nodules and lobar function by spectral detector computed tomography.

Amit Gupta, Elias George Kikano, Aekta Gupta, Christopher Di Felice, Robert Gilkeson, Kai Roman Laukamp

Open access · goldAbstract readCase Reports
PubMed Full text at PMC Publisher
In one paragraph

Article in Radiology case reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 62% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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 2 countries.

Amit GuptaDepartment of Radiology, University Hospitals Cleveland Medical Center/Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106, USA.
Elias George KikanoDepartment of Radiology, University Hospitals Cleveland Medical Center/Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106, USA.
Aekta GuptaDepartment of Radiology, University Hospitals Cleveland Medical Center/Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106, USA.
Christopher Di FeliceDepartment of Pulmonary, Critical Care and Sleep Medicine, University Hospitals Cleveland Medical Center/Case Western Reserve University, Cleveland, OH, USA.
Robert GilkesonDepartment of Radiology, University Hospitals Cleveland Medical Center/Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106, USA.
Kai Roman LaukampDepartment of Radiology, University Hospitals Cleveland Medical Center/Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106, USA.
University Hospitals of Cleveland · USUniversity Hospital Cologne · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Conventional computed tomography (CT) plays an important role in detection of lung nodules. However, further characterization is usually limited requiring additional imaging and invasive work up. Spectral Detector CT (SDCT) is an upcoming novel modality that not only allows morphological evaluation but also provides insight into prediction of malignant behavior of lung nodules. Additional quantification capabilities available from the same scan make it a more comprehensive imaging option in oncology patients. This is a first case report demonstrating the potential of single SDCT to provide necessary information for lung cancer diagnosis and preoperative planning, comparable to standard of care imaging.

Indexed as

Dual energy CTPresurgical planningPulmonary nodulesSpectral detector CT

Identifiers

PMID32419896
PMCPMC7214771
OpenAlexW3022399614

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.