Evidence map›Paper›PMID 28095493›Full record

ArticlePloS one2017

Thoracic Temporal Subtraction Three Dimensional Computed Tomography (3D-CT): Screening for Vertebral Metastases of Primary Lung Cancers.

Shingo Iwano, Rintaro Ito, Hiroyasu Umakoshi, Takatoshi Karino, Tsutomu Inoue, Yuanzhong Li, Shinji Naganawa

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Diagnostic accuracy of imaging modalities for detection of spinal metastases: a systematic review and meta-analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025
    Pooled it
  2. Review
  3. Article
  4. CT temporal subtraction: techniques and clinical applications.Quantitative imaging in medicine and surgery · 2021
    Article
  5. Article
  6. Article
  7. Article
  8. 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

7 authors.

Shingo IwanoDepartment of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan.
Rintaro ItoDepartment of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan.
Hiroyasu UmakoshiDepartment of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan.
Takatoshi KarinoImaging Technology Center, Fujifilm Corporation, Tokyo, Japan.
Tsutomu InoueImaging Technology Center, Fujifilm Corporation, Tokyo, Japan.
Yuanzhong LiImaging Technology Center, Fujifilm Corporation, Tokyo, Japan.
Shinji NaganawaDepartment of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeWe developed an original, computer-aided diagnosis (CAD) software that subtracts the initial thoracic vertebral three-dimensional computed tomography (3D-CT) image from the follow-up 3D-CT image. The aim of this study was to investigate the efficacy of this CAD software during screening for vertebral metastases on follow-up CT images of primary lung cancer patients. MATERIALS AND

methodsThe interpretation experiment included 30 sets of follow-up CT scans in primary lung cancer patients and was performed by two readers (readers A and B), who each had 2.5 years' experience reading CT images. In 395 vertebrae from C6 to L3, 46 vertebral metastases were identified as follows: osteolytic metastases (n = 17), osteoblastic metastases (n = 14), combined osteolytic and osteoblastic metastases (n = 6), and pathological fractures (n = 9). Thirty-six lesions were in the anterior component (vertebral body), and 10 lesions were in the posterior component (vertebral arch, transverse process, and spinous process). The area under the curve (AUC) by receiver operating characteristic (ROC) curve analysis and the sensitivity and specificity for detecting vertebral metastases were compared with and without CAD for each observer.

resultsReader A detected 47 abnormalities on CT images without CAD, and 33 of them were true-positive metastatic lesions. Using CAD, reader A detected 57 abnormalities, and 38 were true positives. The sensitivity increased from 0.717 to 0.826, and on ROC curve analysis, AUC with CAD was significantly higher than that without CAD (0.849 vs. 0.902, p = 0.021). Reader B detected 40 abnormalities on CT images without CAD, and 36 of them were true-positive metastatic lesions. Using CAD, reader B detected 44 abnormalities, and 39 were true positives. The sensitivity increased from 0.783 to 0.848, and AUC with CAD was nonsignificantly higher than that without CAD (0.889 vs. 0.910, p = 0.341). Both readers detected more osteolytic and osteoblastic metastases with CAD than without CAD.

conclusionOur temporal 3D-CT subtraction CAD software easily detected vertebral metastases on the follow-up CT images of lung cancer patients regardless of the osteolytic or osteoblastic nature of the lesions.

Indexed as

AdenocarcinomaAdultAgedAged, 80 and overBone NeoplasmsCarcinoma, Squamous CellFemaleHumansImaging, Three-DimensionalLung NeoplasmsMaleMiddle AgedRadiographic Image Interpretation, Computer-AssistedRadiography, ThoracicRetrospective StudiesROC Curve

Identifiers

PMID28095493
PMCPMC5240957

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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.