Evidence map›Paper›PMID 34518923›Full record

ArticleCalcified tissue international2022

Validation of a Semiautomatic Image Analysis Software for the Quantification of Musculoskeletal Tissues.

Mahdi Imani, Ebrahim Bani Hassan, Sara Vogrin, Aaron Samuel Tze Nor Ch'Ng, Nancy E Lane, Jane A Cauley, Gustavo Duque

Open access · greenAbstract read
In one paragraph

Article in Calcified tissue international, 2022. 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
1.7field-weighted citation impact, top 16% 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, 8 citations in OpenAlex.

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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 at 3 institutions in 2 countries.

Mahdi ImaniAustralian Institute for Musculoskeletal Science (AIMSS), The University of Melbourne and Western Health, St. Albans, VIC, 3021, Australia.
Ebrahim Bani HassanAustralian Institute for Musculoskeletal Science (AIMSS), The University of Melbourne and Western Health, St. Albans, VIC, 3021, Australia.
Sara VogrinAustralian Institute for Musculoskeletal Science (AIMSS), The University of Melbourne and Western Health, St. Albans, VIC, 3021, Australia.
Aaron Samuel Tze Nor Ch'NgAustralian Institute for Musculoskeletal Science (AIMSS), The University of Melbourne and Western Health, St. Albans, VIC, 3021, Australia.
Nancy E LaneCenter for Musculoskeletal Health, University of California at Davis School of Medicine, 4625 2nd Avenue Suite 2000, Sacramento, CA, 95817, USA.
Jane A CauleyDepartment of Epidemiology Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, 15261, USA.
Gustavo DuqueAustralian Institute for Musculoskeletal Science (AIMSS), The University of Melbourne and Western Health, St. Albans, VIC, 3021, Australia. gustavo.duque@unimelb.edu.au.ORCID http://orcid.org/0000-0001-8126-0637
The University of Melbourne · AUUniversity of California, Davis · USUniversity of Pittsburgh · US

Funding

Oregon Clinical and Translational Research Institute - The National COVID Cohort Collaborative (N3C)UL1TR002369 · NCATS · OREGON HEALTH & SCIENCE UNIVERSITY · PI Cynthia D Morris, Christopher G. Slatore · 2017 to 2026
$78.4M
Oregon Clinical and Translational Research InstituteUL1TR000128 · NCATS · OREGON HEALTH & SCIENCE UNIVERSITY · PI ELLISON, DAVID H · 2012 to 2015
$28.7M
Long term fracture risk and change in peripheral bone in the oldest old men: The MrOS studyR01AG066671 · NIA · CALIFORNIA PACIFIC MED CTR RES INSTITUTE · PI BOUXSEIN, MARY L, CAWTHON, PEGGY MANNEN · 2020 to 2024
$13.3M
Osteoporotic Fractures in Men (MrOS) - San Francisco Coordinating CenterU01AR066160 · NIAMS · CALIFORNIA PACIFIC MED CTR RES INSTITUTE · PI CUMMINGS, STEVEN RON · 2013 to 2017
$9.3M
Osteoporotic Fractures in Men (MrOS) - MinneapolisU01AG042145 · NIA · UNIVERSITY OF MINNESOTA · PI ENSRUD, KRISTINE · 2013 to 2019
$5.3M
Osteporotic Fractures in Men (MrOS)- Admin CenterU01AG027810 · NIA · OREGON HEALTH & SCIENCE UNIVERSITY · PI ORWOLL, ERIC S. · 2006 to 2017
$5.1M
Osteoporotic Fractures in Men (MrOS) - PortlandU01AG042124 · NIA · OREGON HEALTH & SCIENCE UNIVERSITY · PI ORWOLL, ERIC S. · 2013 to 2019
$3.0M
Osteoporatic Fractures in Men (MrOS)U01AG042168 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KADO, DEBORAH · 2013 to 2017
$3.0M
Osteoporotic Fractures in Men (Mr. Os) Palo AltoU01AG042143 · NIA · STANFORD UNIVERSITY · PI STEFANICK, MARCIA L. · 2013 to 2017
$3.0M
Osteoporotic Fractures in Men (Mr.OS)U01AG042139 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CAULEY, JANE ANN · 2013 to 2017
$2.9M
Osteoporotic Fractures in Men_MrOS Renewal_BirminghamU01AG042140 · NIA · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI SHIKANY, JAMES M · 2013 to 2019
$2.7M
Long-term fracture risk in older men: the MrOS studyR56AG061085 · NIA · CALIFORNIA PACIFIC MED CTR RES INSTITUTE · PI BOUXSEIN, MARY L, CAWTHON, PEGGY MANNEN · 2019 to 2019
$1.3M
NCATS NIH HHS UL1 TR000128NCATS NIH HHS UL1 TR002369NIAMS NIH HHS U01 AR066160NIA NIH HHS R01 AG066671NIA NIH HHS R56 AG061085NIA NIH HHS U01 AG027810NIA NIH HHS U01 AG042124NIA NIH HHS U01 AG042139NIA NIH HHS U01 AG042140NIA NIH HHS U01 AG042143NIA NIH HHS U01 AG042145NIA NIH HHS U01 AG042168
6 · The paper itself

Abstract

Accurate quantification of bone, muscle, and their components is still an unmet need in the musculoskeletal field. Current methods to quantify tissue volumes in 3D images are expensive, labor-intensive, and time-consuming; thus, a reliable, valid, and quick application is highly needed. Tissue Compass is a standalone software for semiautomatic segmentation and automatic quantification of musculoskeletal organs. To validate the software, cross-sectional micro-CT scans images of rat femur (n = 19), and CT images of hip and abdomen (n = 100) from the Osteoporotic Fractures in Men (MrOS) Study were used to quantify bone, hematopoietic marrow (HBM), and marrow adipose tissue (MAT) using commercial manual software as a comparator. Also, abdominal CT scans (n = 100) were used to quantify psoas muscle volumes and intermuscular adipose tissue (IMAT) using the same software. We calculated Pearson's correlation coefficients, individual intra-class correlation coefficients (ICC), and Bland-Altman limits of agreement together with Bland-Altman plots to show the inter- and intra-observer agreement between Tissue Compass and commercially available software. In the animal study, the agreement between Tissue Compass and commercial software was r > 0.93 and ICC > 0.93 for rat femur measurements. Bland-Altman limits of agreement was - 720.89 (- 1.5e+04, 13,074.00) for MAT, 4421.11 (- 1.8e+04, 27,149.73) for HBM and - 6073.32 (- 2.9e+04, 16,388.37) for bone. The inter-observer agreement for QCT human study between two observers was r > 0.99 and ICC > 0.99. Bland-Altman limits of agreement was 0.01 (- 0.07, 0.10) for MAT in hip, 0.02 (- 0.08, 0.12) for HBM in hip, 0.05 (- 0.15, 0.25) for bone in hip, 0.02 (- 0.18, 0.22) for MAT in L1, 0.00 (- 0.16, 0.16) for HBM in L1, and 0.02 (- 0.23, 0.27) for bone in L1. The intra-observer agreement for QCT human study between the two applications was r > 0.997 and ICC > 0.99. Bland-Altman limits of agreement was 0.03 (- 0.13, 0.20) for MAT in hip, 0.05 (- 0.08, 0.18) for HBM in hip, 0.05 (- 0.24, 0.34) for bone in hip, - 0.02 (- 0.34, 0.31) for MAT in L1, - 0.14 (- 0.44, 0.17) for HBM in L1, - 0.29 (- 0.62, 0.05) for bone in L1, 0.03 (- 0.08, 0.15) for IMAT in psoas, and 0.02 (- 0.35, 0.38) for muscle in psoas. Compared to a conventional application, Tissue Compass demonstrated high accuracy and non-inferiority while also facilitating easier analyses. Tissue Compass could become the tool of choice to diagnose tissue loss/gain syndromes in the future by requiring a small number of CT sections to detect tissue volumes and fat infiltration.

Indexed as

Image Processing, Computer-AssistedSoftwareAnimalsCross-Sectional StudiesHumansObserver VariationReproducibility of ResultsX-Ray MicrotomographyImage processingIntramuscular fatMarrow adipose tissueOsteoporosisOsteosarcopeniaSarcopenia

Identifiers

PMID34518923
PMCPMC8863586
OpenAlexW3174045675

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Registered trials

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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.