Evidence map›Paper›PMID 25276380›Full record

ReviewJournal of thoracic disease2014

Magnetic resonance imaging for lung cancer screen.

Yi-Xiang J Wang, Gladys G Lo, Jing Yuan, Peder E Z Larson, Xiaoliang Zhang

Open access · greenAbstract readReview
In one paragraph

Review in Journal of thoracic disease, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

18 citing papers in PubMed, 35 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Dual-Tuned Coaxial-Transmission-Line RF Coils for HyperpolarizedIEEE transactions on bio-medical engineering · 2024
    Article
  5. Article
  6. Article
  7. Review
  8. Review
  9. Review
  10. Lung Cancer in Li-Fraumeni Syndrome.JCO precision oncology · 2021
    Article
  11. Gold nanomaterials in the management of lung cancer.Emerging topics in life sciences · 2020
    Review
  12. Article
  13. Article
  14. A Prediction Model with a Combination of Variables for Diagnosis of Lung Cancer.Medical science monitor : international medical journal of experimental and clinical research · 2017
    Article
  15. Article
  16. Article
  17. Review
  18. 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

5 authors at 1 institution in 1 country.

Yi-Xiang J Wang1 Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, China ; 2 Department of Diagnostic Radiology, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong, China ; 3 Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong, China ; 4 Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA ; 5 UCSF/UC Berkeley Joint Bioengineering Program, San Francisco and Berkeley, CA, USA.
Gladys G Lo1 Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, China ; 2 Department of Diagnostic Radiology, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong, China ; 3 Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong, China ; 4 Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA ; 5 UCSF/UC Berkeley Joint Bioengineering Program, San Francisco and Berkeley, CA, USA.
Jing Yuan1 Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, China ; 2 Department of Diagnostic Radiology, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong, China ; 3 Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong, China ; 4 Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA ; 5 UCSF/UC Berkeley Joint Bioengineering Program, San Francisco and Berkeley, CA, USA.
Peder E Z Larson1 Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, China ; 2 Department of Diagnostic Radiology, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong, China ; 3 Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong, China ; 4 Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA ; 5 UCSF/UC Berkeley Joint Bioengineering Program, San Francisco and Berkeley, CA, USA.
Xiaoliang Zhang1 Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, China ; 2 Department of Diagnostic Radiology, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong, China ; 3 Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong, China ; 4 Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA ; 5 UCSF/UC Berkeley Joint Bioengineering Program, San Francisco and Berkeley, CA, USA.
Chinese University of Hong Kong · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer is the leading cause of cancer related death throughout the world. Lung cancer is an example of a disease for which a large percentage of the high-risk population can be easily identified via a smoking history. This has led to the investigation of lung cancer screening with low-dose helical/multi-detector CT. Evidences suggest that early detection of lung cancer allow more timely therapeutic intervention and thus a more favorable prognosis for the patient. The positive relationship of lesion size to likelihood of malignancy has been demonstrated previously, at least 99% of all nodules 4 mm or smaller are benign, while noncalcified nodules larger than 8 mm diameter bear a substantial risk of malignancy. In the recent years, the availability of high-performance gradient systems, in conjunction with phased-array receiver coils and optimized imaging sequences, has made MR imaging of the lung feasible. It can now be assumed a threshold size of 3-4 mm for detection of lung nodules with MRI under the optimal conditions of successful breath-holds with reliable gating or triggering. In these conditions, 90% of all 3-mm nodules can be correctly diagnosed and that nodules 5 mm and larger are detected with 100% sensitivity. Parallel imaging can significantly shorten the imaging acquisition time by utilizing the diversity of sensitivity profile of individual coil elements in multi-channel radiofrequency receive coil arrays or transmit/receive coil arrays to reduce the number of phase encoding steps required in imaging procedure. Compressed sensing technique accelerates imaging acquisition from dramatically undersampled data set by exploiting the sparsity of the images in an appropriate transform domain. With the combined imaging algorithm of parallel imaging and compressed sensing and advanced 32-channel or 64-channel RF hardware, overall imaging acceleration of 20 folds or higher can then be expected, ultimately achieve free-breathing and no ECG gating acquisitions in lung cancer MRI screening. Further development of protocols, more clinical trials and the use of advanced analysis tools will further evaluate the real significance of lung MRI.

Indexed as

cancerCTLungMRscreening

Identifiers

PMID25276380
PMCPMC4178109
OpenAlexW2100189093

What OpenQuestion holds

Textmetadata
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.