Literature DB >> 34406056

Fully Automated Deep Learning Tool for Sarcopenia Assessment on CT: L1 Versus L3 Vertebral Level Muscle Measurements for Opportunistic Prediction of Adverse Clinical Outcomes.

Perry J Pickhardt1, Alberto A Perez1, John W Garrett1, Peter M Graffy1, Ryan Zea1, Ronald M Summers2.   

Abstract

BACKGROUND. Sarcopenia is associated with adverse clinical outcomes. CT-based skeletal muscle measurements for sarcopenia assessment are most commonly performed at the L3 vertebral level. OBJECTIVE. The purpose of this article is to compare the utility of fully automated deep learning CT-based muscle quantitation at the L1 versus L3 level for predicting future hip fractures and death. METHODS. This retrospective study included 9223 asymptomatic adults (mean age, 57 ± 8 [SD] years; 4071 men, 5152 women) who underwent unenhanced low-dose abdominal CT. A previously validated fully automated deep learning tool was used to assess muscle for myosteatosis (by mean attenuation) and myopenia (by cross-sectional area) at the L1 and L3 levels. Performance for predicting hip fractures and death was compared between L1 and L3 measures. Performance for predicting hip fractures and death was also evaluated using the established clinical risk scores from the fracture risk assessment tool (FRAX) and Framingham risk score (FRS), respectively. RESULTS. Median clinical follow-up interval after CT was 8.8 years (interquartile range, 5.1-11.6 years), yielding hip fractures and death in 219 (2.4%) and 549 (6.0%) patients, respectively. L1-level and L3-level muscle attenuation measurements were not different in 2-, 5-, or 10-year AUC for hip fracture (p = .18-.98) or death (p = .19-.95). For hip fracture, 5-year AUCs for L1-level muscle attenuation, L3-level muscle attenuation, and FRAX score were 0.717, 0.709, and 0.708, respectively. For death, 5-year AUCs for L1-level muscle attenuation, L3-level muscle attenuation, and FRS were 0.737, 0.721, and 0.688, respectively. Lowest quartile hazard ratios (HRs) for hip fracture were 2.20 (L1 attenuation), 2.45 (L3 attenuation), and 2.53 (FRAX score), and for death were 3.25 (L1 attenuation), 3.58 (L3 attenuation), and 2.82 (FRS). CT-based muscle cross-sectional area measurements at L1 and L3 were less predictive for hip fracture and death (5-year AUC ≤ 0.571; HR ≤ 1.56). CONCLUSION. Automated CT-based measurements of muscle attenuation for myosteatosis at the L1 level compare favorably with previously established L3-level measurements and clinical risk scores for predicting hip fracture and death. Assessment for myopenia was less predictive of outcomes at both levels. CLINICAL IMPACT. Alternative use of the L1 rather than L3 level for CT-based muscle measurements allows sarcopenia assessment using both chest and abdominal CT scans, greatly increasing the potential yield of opportunistic CT screening.

Entities:  

Keywords:  CT; myosteatosis; opportunistic screening; outcomes; sarcopenia

Mesh:

Year:  2021        PMID: 34406056      PMCID: PMC9028606          DOI: 10.2214/AJR.21.26486

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   6.582


  32 in total

1.  CT of Patients With Hip Fracture: Muscle Size and Attenuation Help Predict Mortality.

Authors:  Robert D Boutin; Sara Bamrungchart; Cyrus P Bateni; Daniel P Beavers; Kristen M Beavers; John P Meehan; Leon Lenchik
Journal:  AJR Am J Roentgenol       Date:  2017-03-07       Impact factor: 3.959

Review 2.  FRAX and its applications to clinical practice.

Authors:  John A Kanis; Anders Oden; Helena Johansson; Fredrik Borgström; Oskar Ström; Eugene McCloskey
Journal:  Bone       Date:  2009-02-03       Impact factor: 4.398

3.  Myosteatosis and prognosis in cancer: Systematic review and meta-analysis.

Authors:  G F P Aleixo; S S Shachar; K A Nyrop; H B Muss; Luis Malpica; G R Williams
Journal:  Crit Rev Oncol Hematol       Date:  2019-12-20       Impact factor: 6.312

4.  Fully automated segmentation and quantification of visceral and subcutaneous fat at abdominal CT: application to a longitudinal adult screening cohort.

Authors:  Scott J Lee; Jiamin Liu; Jianhua Yao; Andrew Kanarek; Ronald M Summers; Perry J Pickhardt
Journal:  Br J Radiol       Date:  2018-03-28       Impact factor: 3.039

Review 5.  Sarcopenia: Current Concepts and Imaging Implications.

Authors:  Robert D Boutin; Lawrence Yao; Robert J Canter; Leon Lenchik
Journal:  AJR Am J Roentgenol       Date:  2015-06-23       Impact factor: 3.959

6.  General cardiovascular risk profile for use in primary care: the Framingham Heart Study.

Authors:  Ralph B D'Agostino; Ramachandran S Vasan; Michael J Pencina; Philip A Wolf; Mark Cobain; Joseph M Massaro; William B Kannel
Journal:  Circulation       Date:  2008-01-22       Impact factor: 29.690

7.  Automated Liver Fat Quantification at Nonenhanced Abdominal CT for Population-based Steatosis Assessment.

Authors:  Peter M Graffy; Veit Sandfort; Ronald M Summers; Perry J Pickhardt
Journal:  Radiology       Date:  2019-09-17       Impact factor: 11.105

8.  Automated Abdominal CT Imaging Biomarkers for Opportunistic Prediction of Future Major Osteoporotic Fractures in Asymptomatic Adults.

Authors:  Perry J Pickhardt; Peter M Graffy; Ryan Zea; Scott J Lee; Jiamin Liu; Veit Sandfort; Ronald M Summers
Journal:  Radiology       Date:  2020-08-11       Impact factor: 11.105

9.  Sarcopenia: revised European consensus on definition and diagnosis.

Authors:  Alfonso J Cruz-Jentoft; Gülistan Bahat; Jürgen Bauer; Yves Boirie; Olivier Bruyère; Tommy Cederholm; Cyrus Cooper; Francesco Landi; Yves Rolland; Avan Aihie Sayer; Stéphane M Schneider; Cornel C Sieber; Eva Topinkova; Maurits Vandewoude; Marjolein Visser; Mauro Zamboni
Journal:  Age Ageing       Date:  2019-01-01       Impact factor: 10.668

10.  Prognostic Impact of Low Skeletal Muscle Mass on Major Adverse Cardiovascular Events in Coronary Artery Disease: A Propensity Score-Matched Analysis of a Single Center All-Comer Cohort.

Authors:  Dong Oh Kang; So Yeon Park; Byoung Geol Choi; Jin Oh Na; Cheol Ung Choi; Eung Ju Kim; Seung-Woon Rha; Chang Gyu Park; Suk-Joo Hong; Hong Seog Seo
Journal:  J Clin Med       Date:  2019-05-19       Impact factor: 4.241

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  1 in total

1.  Deep learning auto-segmentation of cervical skeletal muscle for sarcopenia analysis in patients with head and neck cancer.

Authors:  Mohamed A Naser; Kareem A Wahid; Aaron J Grossberg; Brennan Olson; Rishab Jain; Dina El-Habashy; Cem Dede; Vivian Salama; Moamen Abobakr; Abdallah S R Mohamed; Renjie He; Joel Jaskari; Jaakko Sahlsten; Kimmo Kaski; Clifton D Fuller
Journal:  Front Oncol       Date:  2022-07-28       Impact factor: 5.738

  1 in total

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