Evidence map›Paper›PMID 33542900›Full record

ArticleFrontiers in oncology2020

Evaluating Heterogeneity of Primary Lung Tumor Using Clinical Routine Magnetic Resonance Imaging and a Tumor Heterogeneity Index.

Nan Hu, ShaoHan Yin, Qiwen Li, Haoqiang He, Linchang Zhong, Nan-Jie Gong, Jinyu Guo, Peiqiang Cai, Chuanmiao Xie, Hui Liu and 1 more

Abstract read
In one paragraph

Article in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

11 authors.

Nan HuDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangzhou, China.
ShaoHan YinDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangzhou, China.
Qiwen LiDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangzhou, China.
Haoqiang HeDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangzhou, China.
Linchang ZhongDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangzhou, China.
Nan-Jie GongVector Lab for Intelligent Medical Imaging and Neural Engineering, International Innovation Center of Tsinghua University, Shanghai, China.
Jinyu GuoDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangzhou, China.
Peiqiang CaiDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangzhou, China.
Chuanmiao XieDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangzhou, China.
Hui LiuDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangzhou, China.
Bo QiuDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo improve the assessment of primary tumor heterogeneity in magnetic resonance imaging (MRI) of non-small cell lung cancer (NSCLC), we proposed a method using basic measurements from T1- and T2-weighted MRI.

methodsOne hundred and four NSCLC patients with different T stages were studied. Fifty-two patients were analyzed as training group and another 52 as testing group. The ratios of standard deviation (SD)/mean signal value of primary tumor from T1-weighted (T1WI), T1-enhanced (T1C), T2-weighted (T2WI), and T2 fat suppression (T2fs) images were calculated. In the training group, correlation analyses were performed between the ratios and T stages. Then an ordinal regression model was built to generate the tumor heterogeneous index (THI) for evaluating the heterogeneity of tumor. The model was validated in the testing group.

resultsThere were 11, 32, 40, and 21 patients with T1, T2, T3, and T4 disease, respectively. In the training group, the median SD/mean on T1WI, T1C, T2WI, and T2fs sequences was 0.11, 0.19, 0.16, and 0.15 respectively. The SD/mean on T1C (p=0.003), T2WI (p=0.000), and T2fs sequences (p=0.002) correlated significantly with T stages. Patients with more advanced T stage showed higher SD/mean on T2-weighted, T2fs, and T1C sequences. The median THI in the training group was 2.15. THI correlated with T stage significantly (p=0.000). In the testing group, THI was also significantly related to T stages (p=0.001). Higher THI had relevance to more advanced T stage.

conclusionsThe proposed ratio measurements and THI based on MRI can serve as functional radiomic markers that correlated with T stages for evaluating heterogeneity of lung tumors.

Indexed as

heterogeneityMRInon-small cell lung cancerradiation therapyT stage

Identifiers

PMID33542900
PMCPMC7853693

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.