Evidence map›Paper›PMID 33059184›Full record

ArticleClinical imaging2021

Percutaneous computed tomography guided biopsy of sub-solid pulmonary nodules: differentiating solid from ground glass components at the time of biopsy.

Darragh Halpenny, Krishna Das, Etay Ziv, Andrew Plodkowski, Junting Zheng, Marinela Capanu, Natasha Rekhtman, Joseph Montecalvo, Stephen B Solomon, Michelle S Ginsberg

Open access · greenAbstract read
In one paragraph

Article in Clinical imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 22% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. [Expert Consensus for Thermal Ablation of Pulmonary Subsolid Nodules (2021 Edition)].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2021
    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

10 authors at 1 institution in 1 country.

Darragh HalpennyDepartment of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, United States of America. Electronic address: halpennd@mskcc.org.
Krishna DasDepartment of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, United States of America.
Etay ZivDepartment of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, United States of America.
Andrew PlodkowskiDepartment of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, United States of America.
Junting ZhengDepartment of Biostatistics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, United States of America.
Marinela CapanuDepartment of Biostatistics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, United States of America.
Natasha RekhtmanDepartment of Pathology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, United States of America.
Joseph MontecalvoDepartment of Pathology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, United States of America.
Stephen B SolomonDepartment of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, United States of America.
Michelle S GinsbergDepartment of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, United States of America.
Memorial Sloan Kettering Cancer Center · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

introductionThis study assessed (i) the ability to identify the solid components of part-solid nodules (PSN) during computed tomography (CT) guided lung biopsy (CTGLB), (ii) the ability of CTGLB to assess the invasive nature of a nodule on pathology. MATERIALS AND

methodsSixty-nine nodules were studied in 68 patients who underwent CTGLB between 1/1/2014 and 10/31/2015. Diagnostic CT images and CTGLB images were reviewed. On diagnostic CT images, nodules were classified as ground glass nodules (GGN) or PSNs. Nodule size, location, and percentage of solid component were recorded. At the time of biopsy, the ability to visualize the solid component of a PSN, depth of lesion from skin, and ability to identify the needle within the solid component were recorded.

resultsThere were 42 (61%) part-solid nodules and 27 (39%) GGNs. During biopsy, it was possible to differentiate the solid from the ground glass components in 35 (83%) PSNs. Fifty-nine (86%) nodules were neoplastic based on biopsy pathology (all non-small cell lung carcinoma). Thirty-nine (66%) were resected. In all cases biopsy pathology and surgical pathology agreed regarding the presence of lung carcinoma. In 6 (15%) cases biopsy pathology demonstrated purely lepidic growth but had some non-lepidic growth on surgical pathology, including 2 cases with acinar growth as a dominant pattern.

conclusionIn most patients, the solid and ground glass components of a PSN were distinguishable when performing a CTGLB. In a minority of patients, discrepancy was noted between biopsy pathology and surgical pathology regarding the invasive nature of a nodule.

Indexed as

AdenocarcinomaLung NeoplasmsSolitary Pulmonary NoduleHumansRetrospective StudiesTimeTomography, X-Ray ComputedComputed tomographyLung adenocarcinomaLung nodulePart solid lung nodulePercutaneous lung biopsy

Identifiers

PMID33059184
PMCPMC8863104
OpenAlexW3045273036

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.