Evidence map›Paper›PMID 32252829›Full record

ArticleCancer imaging : the official publication of the International Cancer Imaging Society2020

Diffusion-weighted magnetic resonance imaging of primary cervical cancer in the detection of sub-centimetre metastatic lymph nodes.

Jose Angelo Udal Perucho, Keith Wan Hang Chiu, Esther Man Fung Wong, Ka Yu Tse, Mandy Man Yee Chu, Lawrence Wing Chi Chan, Herbert Pang, Pek-Lan Khong, Elaine Yuen Phin Lee

Open access · goldAbstract readEvaluation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 25% 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, 11 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. 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

9 authors at 4 institutions in 2 countries.

Jose Angelo Udal PeruchoDepartment of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Room 406, Block K, Queen Mary Hospital, Pok Fu Lam Road, Pok Fu Lam, Hong Kong.ORCID https://orcid.org/0000-0001-6088-3173
Keith Wan Hang ChiuDepartment of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Room 406, Block K, Queen Mary Hospital, Pok Fu Lam Road, Pok Fu Lam, Hong Kong.ORCID https://orcid.org/0000-0002-7930-1193
Esther Man Fung WongDepartment of Radiology, Pamela Youde Nethersole Eastern Hospital, 3 Lok Man Road, Chai Wan, Hong Kong.ORCID https://orcid.org/0000-0001-6961-3890
Ka Yu TseDepartment of Obstetrics and Gynaecology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, 6/F, Professorial Block, Queen Mary Hospital, Pok Fu Lam Road, Pok Fu Lam, Hong Kong.ORCID https://orcid.org/0000-0001-8330-0970
Mandy Man Yee ChuDepartment of Obstetrics and Gynaecology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, 6/F, Professorial Block, Queen Mary Hospital, Pok Fu Lam Road, Pok Fu Lam, Hong Kong.ORCID https://orcid.org/0000-0002-1525-0147
Lawrence Wing Chi ChanDepartment of Health Technology and Informatics, Hong Kong Polytechnic University, Room Y934, 9/F, Lee Shau Kee Building, The Hong Kong Polytechnic University, Hung Hom, Hong Kong.ORCID https://orcid.org/0000-0001-6451-2273
Herbert PangSchool of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, G/F, Patrick Manson Building (North Wing), 7 Sassoon Road, Pok Fu Lam, Hong Kong.ORCID https://orcid.org/0000-0002-7896-6716
Pek-Lan KhongDepartment of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Room 406, Block K, Queen Mary Hospital, Pok Fu Lam Road, Pok Fu Lam, Hong Kong.ORCID https://orcid.org/0000-0002-9280-6778
Elaine Yuen Phin LeeDepartment of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Room 406, Block K, Queen Mary Hospital, Pok Fu Lam Road, Pok Fu Lam, Hong Kong. eyplee77@hku.hk.ORCID https://orcid.org/0000-0002-0627-5297
Queen Mary Hospital · CNHong Kong Polytechnic University · HKPamela Youde Nethersole Eastern Hospital · CNUniversity of Hong Kong · HK

Funding

Research Grants Council, University Grants Committee GRF 17119916
6 · The paper itself

Abstract

backgroundMagnetic resonance imaging (MRI) has limited accuracy in detecting pelvic lymph node (PLN) metastasis. This study aimed to examine the use of intravoxel incoherent motion (IVIM) in classifying pelvic lymph node (PLN) involvement in cervical cancer patients.

methodsFifty cervical cancer patients with pre-treatment magnetic resonance imaging (MRI) were examined for PLN involvement by one subspecialist and one non-subspecialist radiologist. PLN status was confirmed by positron emission tomography or histology. The tumours were then segmented by both radiologists. Kruskal-Wallis tests were used to test for differences between diffusion tumour volume (DTV), apparent diffusion coefficient (ADC), pure diffusion coefficient (D), and perfusion fraction (f) in patients with no malignant PLN involvement, those with sub-centimetre and size-significant PLN metastases. These parameters were then considered as classifiers for PLN involvement, and were compared with the accuracies of radiologists.

resultsTwenty-one patients had PLN involvement of which 10 had sub-centimetre metastatic PLNs. DTV increased (p = 0.013) while ADC (p = 0.015), and f (p = 0.006) decreased as the nodal status progressed from no malignant involvement to sub-centimetre and then size-significant PLN metastases. In determining PLN involvement, a classification model (DTV + f) had similar accuracies (80%) as the non-subspecialist (76%; p = 0.73) and subspecialist (90%; p = 0.31). However, in identifying patients with sub-centimetre PLN metastasis, the model had higher accuracy (90%) than the non-subspecialist (30%; p = 0.01) but had similar accuracy with the subspecialist (90%, p = 1.00). Interobserver variability in tumour delineation did not significantly affect the performance of the classification model.

conclusionIVIM is useful in determining PLN involvement but the added value decreases with reader experience.

Indexed as

AdultAgedDiffusion Magnetic Resonance ImagingFemaleHumansLymphatic MetastasisMiddle AgedObserver VariationUterine Cervical NeoplasmsCervical CancerDiffusion-weighted imagingIntravoxel incoherent motionLymph node metastasisMagnetic resonance imagingPerfusion

Identifiers

PMID32252829
PMCPMC7137185
OpenAlexW3015167966

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.