Evidence map›Paper›PMID 34350554›Full record

ArticleNeurocritical care2022

Combined Radiomics Model for Prediction of Hematoma Progression and Clinical Outcome of Cerebral Contusions in Traumatic Brain Injury.

Liqiong Zhang, Qiyuan Zhuang, Guoqing Wu, Jinhua Yu, Zhifeng Shi, Qiang Yuan, Jian Yu, Jin Hu

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Article in Neurocritical care, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 23% 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

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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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.

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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.

Liqiong ZhangDepartment of Electronic Engineering, Fudan University, Shanghai, China.
Qiyuan ZhuangDepartment of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China.
Guoqing WuDepartment of Electronic Engineering, Fudan University, Shanghai, China.
Jinhua YuDepartment of Electronic Engineering, Fudan University, Shanghai, China.
Zhifeng ShiDepartment of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China.
Qiang YuanDepartment of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China. 297260090@qq.com.
Jian YuDepartment of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China. lance2002@hotmail.com.
Jin HuDepartment of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China.
Fudan University · CNHuashan Hospital · CNRegenerative Medicine Institute · MX

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTraumatic brain injury is a common and devastating injury that is the leading cause of neurological disability and death worldwide. Patients with cerebral lobe contusion received conservative treatment because of their mild manifestations, but delayed intracranial hematoma may increase and even become life-threatening. We explored the noninvasive method to predict the prognosis of progression and Glasgow Outcome Scale (GOS) by using a quantitative radiomics approach and statistical analysis.

methodsEighty-eight patients who were pathologically diagnosed were retrospectively studied. The radiomics method developed in this work included image segmentation, feature extraction, and feature selection. The nomograms were established based on statistical analysis and a radiomics method. We conducted a comparative study of hematoma progression and GOS between the clinical factor alone and fusion radiomics features.

resultsNineteen clinical factors, 513 radiomics features, and 116 locational features were considered. Among clinical factors, international normalized ratio, prothrombin time, and fibrinogen were enrolled for hematoma progression. As for GOS, treatment strategy, age, Glasgow Coma Scale score, and blood platelet were associated factors. Eight features for GOS and five features for hematoma progression were filtered by using sparse representation and locality preserving projection-combined method. Four nomograms were constructed. After fusion radiomics features, area under the curve of hematoma progression prediction increased from 0.832 to 0.899, whereas GOS prediction went from 0.794 to 0.844.

conclusionsA radiomic-based model that merges radiomics and clinical features is a noninvasive approach to predict hematoma progression and clinical outcomes of cerebral contusions in traumatic brain injury.

Indexed as

Brain ContusionBrain Injuries, TraumaticGlasgow Outcome ScaleHematomaHumansNomogramsRetrospective StudiesCerebral contusionsComputational intelligenceNomogramTBI (traumatic brain injury)

Identifiers

PMID34350554
OpenAlexW3191066869

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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.