Evidence map›Paper›PMID 34531429›Full record

ArticleScientific reports2021

Temporal subtraction CT with nonrigid image registration improves detection of bone metastases by radiologists: results of a large-scale observer study.

Koji Onoue, Masahiro Yakami, Mizuho Nishio, Ryo Sakamoto, Gakuto Aoyama, Keita Nakagomi, Yoshio Iizuka, Takeshi Kubo, Yutaka Emoto, Thai Akasaka and 4 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 31% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Learning-based three-dimensional registration with weak bounding box supervision.Journal of medical imaging (Bellingham, Wash.) · 2022
    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

14 authors at 5 institutions in 1 country.

Koji OnoueDepartment of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, Kyoto, 606-8507, Japan. onoue.koji.88e@kyoto-u.jp.
Masahiro YakamiDepartment of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, Kyoto, 606-8507, Japan.
Mizuho NishioDepartment of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, Kyoto, 606-8507, Japan.
Ryo SakamotoDepartment of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, Kyoto, 606-8507, Japan.
Gakuto AoyamaMedical Products Technology Development Center, R&D Headquarters, Canon Inc., 30-2, Shimomaruko 3-chome, Ohta-ku, Tokyo, 146-8501, Japan.
Keita NakagomiMedical Products Technology Development Center, R&D Headquarters, Canon Inc., 30-2, Shimomaruko 3-chome, Ohta-ku, Tokyo, 146-8501, Japan.
Yoshio IizukaMedical Products Technology Development Center, R&D Headquarters, Canon Inc., 30-2, Shimomaruko 3-chome, Ohta-ku, Tokyo, 146-8501, Japan.
Takeshi KuboDepartment of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, Kyoto, 606-8507, Japan.
Yutaka EmotoKyoto College of Medical Science, 1-3 Imakita, Koyamahigashi-cho, Sonobe-cho, Nantan, Kyoto, 622-0041, Japan.
Thai AkasakaDepartment of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, Kyoto, 606-8507, Japan.
Kiyohide SatohMedical Products Technology Development Center, R&D Headquarters, Canon Inc., 30-2, Shimomaruko 3-chome, Ohta-ku, Tokyo, 146-8501, Japan.
Hiroyuki YamamotoR&D Headquarters, Canon Inc., 30-2, Shimomaruko 3-chome, Ohta-ku, Tokyo, 146-8501, Japan.
Hiroyoshi IsodaDepartment of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, Kyoto, 606-8507, Japan.
Kaori TogashiDepartment of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, Kyoto, 606-8507, Japan.
Kyoto University · JPCanon (Japan) · JPKobe City Medical Center General Hospital · JPKyoto College of Medical Science · JPKyoto University Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To determine whether temporal subtraction (TS) CT obtained with non-rigid image registration improves detection of various bone metastases during serial clinical follow-up examinations by numerous radiologists. Six board-certified radiologists retrospectively scrutinized CT images for patients with history of malignancy sequentially. These radiologists selected 50 positive and 50 negative subjects with and without bone metastases, respectively. Furthermore, for each subject, they selected a pair of previous and current CT images satisfying predefined criteria by consensus. Previous images were non-rigidly transformed to match current images and subtracted from current images to automatically generate TS images. Subsequently, 18 radiologists independently interpreted the 100 CT image pairs to identify bone metastases, both without and with TS images, with each interpretation separated from the other by an interval of at least 30 days. Jackknife free-response receiver operating characteristics (JAFROC) analysis was conducted to assess observer performance. Compared with interpretation without TS images, interpretation with TS images was associated with a significantly higher mean figure of merit (0.710 vs. 0.658; JAFROC analysis, P = 0.0027). Mean sensitivity at lesion-based was significantly higher for interpretation with TS compared with that without TS (46.1% vs. 33.9%; P = 0.003). Mean false positive count per subject was also significantly higher for interpretation with TS than for that without TS (0.28 vs. 0.15; P < 0.001). At the subject-based, mean sensitivity was significantly higher for interpretation with TS images than that without TS images (73.2% vs. 65.4%; P = 0.003). There was no significant difference in mean specificity (0.93 vs. 0.95; P = 0.083). TS significantly improved overall performance in the detection of various bone metastases.

Indexed as

AgedAged, 80 and overBone NeoplasmsFemaleHumansMaleMiddle AgedObserver VariationRadiologistsSensitivity and SpecificitySoftwareTomography, X-Ray Computed

Identifiers

PMID34531429
PMCPMC8446090
OpenAlexW3199192502

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.