Literature DB >> 30741350

Automated quantitative morphometry of vertebral heights on spinal radiographs: comparison of a clinical workflow tool with standard 6-point morphometry.

Klaus Engelke1,2,3, B Stampa4, P Steiger5, T Fuerst6, H K Genant7.   

Abstract

A workflow tool for measurements of vertebral heights on lateral spine radiographs based on automated placements of 6 points per vertebra was evaluated. The tool helps to standardize point placement among operators. Its success rate is very good in normal vertebrae but lower in vertebrae with more severe fractures. Manual corrections were required in 192 of 1257 analyzed vertebrae.
INTRODUCTION: To evaluate a new workflow tool (SA) for the automated measurements of vertebral heights on lateral spine radiographs.
METHODOLOGY: Lateral radiographs from 200 postmenopausal women were evaluated at two visits. Genant's semi-quantitative fracture assessment (SQ) and manual quantitative morphometry (QM) results were available from prior analyses. Vertebral heights from point placements using SA were compared with manual 6-point placement QM. Differences were quantified as RMS coefficient of variations (rmsCV) and standard deviations (rmsSD). RESULTS AND
CONCLUSIONS: SA required manual corrections in 192 of 1257 vertebrae. SA heights were larger than QM ones by 2.2-3.6%. Correlations (r2 > 0.92) between SA and QM were very high. Differences between QM and SA were higher for fractured (SQ = 2; rmsCV% 14.5%) than for unfractured vertebrae (rmsCV% 4.2-4.7%). rmsCV% for QM varied between 3 and 6% and for SA between 2.5 and 7.5%. For SA, highest rmsCV% was obtained for T4 and L4. Manual correction mostly affected the end vertebrae T4 and L4. SA helps to standardize point placement among operators. The algorithm success rate is very good in normal vertebrae but lower in vertebrae with more severe fractures, which are of greater clinical interest but are more readily recognized without morphometric measurements.

Entities:  

Keywords:  Active shape and appearance models; Automated quantitative morphometry; Vertebral fracture

Mesh:

Year:  2019        PMID: 30741350     DOI: 10.1007/s11657-019-0577-2

Source DB:  PubMed          Journal:  Arch Osteoporos            Impact factor:   2.617


  8 in total

1.  Vertebral Deformity Measurements at MRI, CT, and Radiography Using Deep Learning.

Authors:  Abhinav Suri; Brandon C Jones; Grace Ng; Nancy Anabaraonye; Patrick Beyrer; Albi Domi; Grace Choi; Sisi Tang; Ashley Terry; Thomas Leichner; Iman Fathali; Nikita Bastin; Helene Chesnais; Elena Taratuta; Bruce J Kneeland; Chamith S Rajapakse
Journal:  Radiol Artif Intell       Date:  2021-11-10

2.  Artificial intelligence-based radiomics on computed tomography of lumbar spine in subjects with fragility vertebral fractures.

Authors:  E Biamonte; R Levi; F Carrone; W Vena; A Brunetti; M Battaglia; F Garoli; G Savini; M Riva; A Ortolina; M Tomei; G Angelotti; M E Laino; V Savevski; M Mollura; M Fornari; R Barbieri; A G Lania; M Grimaldi; L S Politi; G Mazziotti
Journal:  J Endocrinol Invest       Date:  2022-06-25       Impact factor: 5.467

3.  Real-World Effectiveness of Denosumab and Bisphosphonates on Risk of Vertebral Fractures in Women with Breast Cancer Undergoing Treatment with Aromatase Inhibitors.

Authors:  Gherardo Mazziotti; Rebecca Pedersini; Walter Vena; Deborah Cosentini; Flaminia Carrone; Stella Pigni; Edda L Simoncini; Rosalba Torrisi; Alberto Zambelli; Davide Farina; Luca Balzarini; Andrea G Lania; Alfredo Berruti
Journal:  Calcif Tissue Int       Date:  2022-07-28       Impact factor: 4.000

4.  A deep learning framework for vertebral morphometry and Cobb angle measurement with external validation.

Authors:  Danis Alukaev; Semen Kiselev; Tamerlan Mustafaev; Ahatov Ainur; Bulat Ibragimov; Tomaž Vrtovec
Journal:  Eur Spine J       Date:  2022-05-21       Impact factor: 2.721

Review 5.  Skeletal health in patients with differentiated thyroid carcinoma.

Authors:  M Cellini; M Rotondi; M L Tanda; E Piantanida; L Chiovato; P Beck-Peccoz; Andrea Lania; G Mazziotti
Journal:  J Endocrinol Invest       Date:  2020-07-21       Impact factor: 4.256

Review 6.  Statistical Shape and Appearance Models: Development Towards Improved Osteoporosis Care.

Authors:  Lorenzo Grassi; Sami P Väänänen; Hanna Isaksson
Journal:  Curr Osteoporos Rep       Date:  2021-11-13       Impact factor: 5.096

7.  Prediction of vertebral fractures in cancer patients undergoing hormone deprivation therapies: Reliability of who fracture risk assessment tool (frax) and bone mineral density in real-life clinical practice.

Authors:  Gherardo Mazziotti; Walter Vena; Rebecca Pedersini; Sara Piccini; Emanuela Morenghi; Deborah Cosentini; Paolo Zucali; Rosalba Torrisi; Silvio Sporeni; Edda L Simoncini; Roberto Maroldi; Luca Balzarini; Andrea G Lania; Alfredo Berruti
Journal:  J Bone Oncol       Date:  2022-03-09       Impact factor: 4.072

8.  Finite Element Analysis-Based Vertebral Bone Strength Prediction Using MDCT Data: How Low Can We Go?

Authors:  Nithin Manohar Rayudu; Karupppasamy Subburaj; Kai Mei; Michael Dieckmeyer; Jan S Kirschke; Peter B Noël; Thomas Baum
Journal:  Front Endocrinol (Lausanne)       Date:  2020-07-28       Impact factor: 5.555

  8 in total

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