Evidence map›Paper›PMID 31044266›Full record

ArticleEuropean journal of nuclear medicine and molecular imaging2019

Ultrafast bone scintigraphy scan for detecting bone metastasis using a CZT whole-body gamma camera.

Tomohiko Yamane, Atsushi Kondo, Masafumi Takahashi, Yuuki Miyazaki, Toshihiko Ehara, Kenji Koga, Ichiei Kuji, Ichiro Matsunari

Abstract read
PubMed Publisher
In one paragraph

Article in European journal of nuclear medicine and molecular imaging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.7field-weighted citation impact, top 10% 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

9 citing papers in PubMed, 30 citations in OpenAlex.

  1. An artificial intelligence-driven image quality assessment system for whole-body [European journal of nuclear medicine and molecular imaging · 2023
    Trial
  2. Article
  3. Article
  4. Article
  5. Review
  6. Dynamic cardiac SPECT with flow measurement using 3D-ring CZT: when SPECT is inspired by PET.European journal of nuclear medicine and molecular imaging · 2023
    Article
  7. Article
  8. Article
  9. 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

8 authors at 2 institutions in 1 country.

Tomohiko YamaneDepartment of Nuclear Medicine, Saitama Medical University International Medical Center, 1397-1 Yamane, Hidaka, 350-1298, Japan. yamane_t@saitama-med.ac.jp.ORCID http://orcid.org/0000-0003-0955-4272
Atsushi KondoDepartment of Central Radiological Technology, Saitama Medical University Hospital, 38 Moro-Hongo, Moroyama, 350-0495, Japan.
Masafumi TakahashiDepartment of Central Radiological Technology, Saitama Medical University Hospital, 38 Moro-Hongo, Moroyama, 350-0495, Japan.
Yuuki MiyazakiDepartment of Central Radiological Technology, Saitama Medical University Hospital, 38 Moro-Hongo, Moroyama, 350-0495, Japan.
Toshihiko EharaDepartment of Central Radiological Technology, Saitama Medical University Hospital, 38 Moro-Hongo, Moroyama, 350-0495, Japan.
Kenji KogaDepartment of Central Radiological Technology, Saitama Medical University Hospital, 38 Moro-Hongo, Moroyama, 350-0495, Japan.
Ichiei KujiDepartment of Nuclear Medicine, Saitama Medical University International Medical Center, 1397-1 Yamane, Hidaka, 350-1298, Japan.
Ichiro MatsunariDivision of Nuclear Medicine, Department of Radiology, Saitama Medical University Hospital, 38 Moro-Hongo, Moroyama, 350-0495, Japan.
Saitama Medical University Hospital · JPSaitama Medical University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo evaluate the feasibility of short whole-body bone scan acquisition times using a novel gamma camera with cadmium-zinc-telluride (CZT) semiconductor detectors.

methodsWe retrospectively enrolled 78 consecutive patients with prostate cancer who underwent bone scintigraphy using a whole-body gamma camera with CZT detectors. After acquisition of list-mode data with 180 s per bed position, anterior and posterior whole-body images were reconstructed using the first 5%, 10%, 25%, 50%, 75% and 100% of the list-mode data. Two experienced nuclear medicine physicians interpreted the images, and interrater agreement and the diagnostic value of the images were determined. Quantitative artificial neural network (ANN) values, bone scan indexes (BSI) and hotspot numbers (HsN) were also calculated by automated diagnostic software.

resultsExcellent interrater reliabilities of the visual assessments were obtained for the 100%, 75%, 50%, and 25% images (κ = 0.88, 0.88, 0.88 and 0.88, respectively). The 5% images also showed high diagnostic value (sensitivity 0.94, specificity 0.84 and accuracy 0.86). Intraclass correlation coefficients (ICC) between the 100% images and the reduced acquisition time images were evaluated in quantitative analyses, and excellent correlations were observed for ANN value in the 75% images (ICC 0.77), for BSI in all the reduced acquisition time images (75%, 50%, 25%, 10% and 5%; ICC 0.99, 0.99, 0.99, 0.96 and 0.75, respectively), and for HsN in the 75%, 50%, 25% and 10% images (ICC 0.99, 0.99, 0.98 and 0.90, respectively).

conclusionWhole-body gamma cameras with CZT detectors have the potential to reduce image acquisition times and the dose of radioisotope injected for bone scans.

Indexed as

AgedAged, 80 and overBone NeoplasmsCadmiumGamma CamerasHumansMaleMiddle AgedProstatic NeoplasmsSensitivity and SpecificitySingle Photon Emission Computed Tomography Computed TomographyTelluriumWhole Body ImagingZincCadmiumCdZnTeTelluriumZincBone metastasis of prostate cancerBone scanCadmium-zinc-telluride (CZT)Gamma cameraUltrafast scan

Identifiers

PMID31044266
OpenAlexW2943712932

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.