Evidence map›Paper›PMID 33439318›Full record

ArticleEuropean radiology2021

CT quantification of the heterogeneity of fibrosis boundaries in idiopathic pulmonary fibrosis.

Junghoan Park, Julip Jung, Soon Ho Yoon, Helen Hong, Hyungjin Kim, Heekyung Kim, Jeong-Hwa Yoon, Jin Mo Goo

Open access · bronzeAbstract read
In one paragraph

Article in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.1field-weighted citation impact, top 13% 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

6 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Observational
  6. Idiopathic pulmonary fibrosis: Current and future treatment.The clinical respiratory journal · 2022
    Review
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 at 3 institutions in 2 countries.

Junghoan ParkDepartment of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
Julip JungDepartment of Software Convergence, Seoul Women's University, Seoul, Republic of Korea.
Soon Ho YoonDepartment of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. yshoka@gmail.com.ORCID http://orcid.org/0000-0002-3700-0165
Helen HongDepartment of Software Convergence, Seoul Women's University, Seoul, Republic of Korea.
Hyungjin KimDepartment of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
Heekyung KimDeparment of Radiology, Eulji Medical Center, Eulji University School of Medicine, Daejeon, Republic of Korea.
Jeong-Hwa YoonInterdisciplinary Program in Medical Informatics, Seoul National University College of Medicine, Seoul, Republic of Korea.
Jin Mo GooDepartment of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
Seoul National University · KRSeoul Women's University · KRNew Generation University College · ET

Funding

National Research Foundation of Korea 2016R1C1B1015761
6 · The paper itself

Abstract

objectivesTo quantify the heterogeneity of fibrosis boundaries in idiopathic pulmonary fibrosis (IPF) using the Gaussian curvature analysis for evaluating disease severity and predicting survival.

methodsWe retrospectively included 104 IPF patients and 52 controls who underwent baseline chest CT scans. Normal lungs below - 500 HU were segmented, and the boundary was three-dimensionally reconstructed using in-house software. Gaussian curvature analysis provided histogram features on the heterogeneity of the fibrosis boundary. We analyzed the correlations between histogram features and the gender-age-physiology (GAP) and CT fibrosis scores. We built a regression model to predict diffusing capacity of carbon monoxide (DLCO) using the histogram features and calculated the modified GAP (mGAP) score by replacing DLCO with the predicted DLCO. The performances of the GAP, CT-GAP, and mGAP scores were compared using 100 repeated random-split sets.

resultsPatients with moderate-to-severe IPF had more numerous Gaussian curvatures at the fibrosis boundary, lower uniformity, and lower 10th to 30th percentiles of Gaussian curvature than controls or patients with mild IPF (all p < 0.0033). The 20th percentile was most significantly correlated with the GAP score (r = - 0.357; p < 0.001) and the CT fibrosis score (r = - 0.343; p = 0.001). More numerous Gaussian curvatures, higher entropy, lower uniformity, and 10th to 30th percentiles (p < 0.001-0.041) were associated with mortality. The mGAP score was comparable to the GAP and CT-GAP scores for survival prediction (mean C-indices, 0.76 vs. 0.79 vs. 0.77, respectively).

conclusionsGaussian curvatures of fibrosis boundaries became more heterogeneous as the disease progressed, and heterogeneity was negatively associated with survival in IPF. KEY POINTS: • Gaussian curvature of the fibrotic lung boundary was more heterogeneous in patients with moderate-to-severe IPF than those with mild IPF or normal controls. • The 20th percentile of the Gaussian curvature of the fibrosis boundary was linearly correlated with the GAP score and the CT fibrosis score. • A modified GAP score that replaced the diffusing capacity of carbon monoxide with a composite measure using histogram features of the Gaussian curvature of the fibrosis boundary showed a comparable ability to predict survival to both the GAP and the CT-GAP score.

Indexed as

Idiopathic Pulmonary FibrosisFibrosisHumansLungRetrospective StudiesSeverity of Illness IndexTomography, X-Ray ComputedIdiopathic pulmonary fibrosisLungQuantitative evaluationTomography, X-ray computed

Identifiers

PMID33439318
PMCPMC7804589
OpenAlexW3119169794

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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.