Evidence map›Paper›PMID 34773211›Full record

ReviewCurrent osteoporosis reports2021

Statistical Shape and Appearance Models: Development Towards Improved Osteoporosis Care.

Lorenzo Grassi, Sami P Väänänen, Hanna Isaksson

Abstract readReview
In one paragraph

Review in Current osteoporosis reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–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

7 citing papers in PubMed.

  1. A Clinical Primer on Computer Vision.Calcified tissue international · 2026
    Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. 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

3 authors.

Lorenzo GrassiDepartment of Biomedical Engineering, Lund University, Box 118, 221 00, Lund, Sweden. lorenzo.grassi@bme.lth.se.ORCID 0000-0001-7824-9947
Sami P VäänänenDepartment of Applied Physics, University of Eastern Finland, Kuopio, Finland.
Hanna IsakssonDepartment of Biomedical Engineering, Lund University, Box 118, 221 00, Lund, Sweden.

Funding

vetenskapsrådet 2019-04517
6 · The paper itself

Abstract

purpose of reviewStatistical models of shape and appearance have increased their popularity since the 1990s and are today highly prevalent in the field of medical image analysis. In this article, we review the recent literature about how statistical models have been applied in the context of osteoporosis and fracture risk estimation. RECENT

findingsRecent developments have increased their ability to accurately segment bones, as well as to perform 3D reconstruction and classify bone anatomies, all features of high interest in the field of osteoporosis and fragility fractures diagnosis, prevention, and treatment. An increasing number of studies used statistical models to estimate fracture risk in retrospective case-control cohorts, which is a promising step towards future clinical application. All the reviewed application areas made considerable steps forward in the past 5-6 years. Heterogeneities in validation hinder a thorough comparison between the different methods and represent one of the future challenges to be addressed to reach clinical implementation.

Indexed as

Models, StatisticalClinical Decision-MakingFinite Element AnalysisHumansImaging, Three-DimensionalOsteoporosisOsteoporotic FracturesPreoperative PeriodFemurFracture riskHipOsteoporosisStatistical shape and appearance modelsVertebrae

Identifiers

PMID34773211
PMCPMC8716351

What OpenQuestion holds

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LicenceCC BY
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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.