CT-derived body composition assessment as a prognostic tool in oncologic patients: from opportunistic research to artificial intelligence–based clinical implementation

DDB Bates, PJ Pickhardt - American Journal of …, 2022 - Am Roentgen Ray Soc
Please see the Editorial Comment by James S. Jelinek discussing this article. CT-based
body composition measures are well established in research settings as prognostic markers …

[HTML][HTML] Sarcopenia–definition, radiological diagnosis, clinical significance

D Vogele, S Otto, N Sollmann… - RöFo-Fortschritte auf …, 2023 - thieme-connect.com
Hintergrund Bei der Sarkopenie handelt es sich um ein altersabhängiges Syndrom, welches
durch einen Verlust an Muskelmasse und-kraft gekennzeichnet ist. In der Folge wird die …

Development and validation of an automated image-based deep learning platform for sarcopenia assessment in head and neck cancer

Z Ye, A Saraf, Y Ravipati, F Hoebers… - Jama network …, 2023 - jamanetwork.com
Importance Sarcopenia is an established prognostic factor in patients with head and neck
squamous cell carcinoma (HNSCC); the quantification of sarcopenia assessed by imaging is …

Abdominal CT body composition thresholds using automated AI tools for predicting 10-year adverse outcomes

MH Lee, R Zea, JW Garrett, PM Graffy, RM Summers… - Radiology, 2022 - pubs.rsna.org
Background CT-based body composition measures derived from fully automated artificial
intelligence tools are promising for opportunistic screening. However, body composition …

AI-based opportunistic CT screening of incidental cardiovascular disease, osteoporosis, and sarcopenia: cost-effectiveness analysis

PJ Pickhardt, L Correale, C Hassan - Abdominal Radiology, 2023 - Springer
Purpose To assess the cost-effectiveness and clinical efficacy of AI-assisted abdominal CT-
based opportunistic screening for atherosclerotic cardiovascular (CV) disease, osteoporosis …

[HTML][HTML] Application of artificial intelligence technology in the field of orthopedics: a narrative review

P Liu, J Zhang, S Liu, T Huo, J He, M Xue… - Artificial Intelligence …, 2024 - Springer
Artificial intelligence (AI) was a new interdiscipline of computer technology, mathematic,
cybernetics and determinism. These years, AI had obtained a significant development by the …

Muscle parameters in fragility fracture risk prediction in older adults: A scoping review

C Vendrami, E Shevroja… - Journal of Cachexia …, 2024 - Wiley Online Library
Half of osteoporotic fractures occur in patients with normal/osteopenic bone density or at
intermediate or low estimated risk. Muscle measures have been shown to contribute to …

[HTML][HTML] CT analysis of thoracolumbar body composition for estimating whole-body composition

JH Hong, H Hong, YR Choi, DH Kim, JY Kim… - Insights into …, 2023 - Springer
Background To evaluate the correlation between single-and multi-slice cross-sectional
thoracolumbar and whole-body compositions. Methods We retrospectively included patients …

[HTML][HTML] Deep learning auto-segmentation of cervical skeletal muscle for sarcopenia analysis in patients with head and neck cancer

MA Naser, KA Wahid, AJ Grossberg, B Olson… - Frontiers in …, 2022 - frontiersin.org
Background/Purpose Sarcopenia is a prognostic factor in patients with head and neck
cancer (HNC). Sarcopenia can be determined using the skeletal muscle index (SMI) …

[HTML][HTML] Deep-learning model for predicting physical fitness in possible sarcopenia: analysis of the Korean physical fitness award from 2010 to 2023

JH Bae, J Seo, DY Kim - Frontiers in Public Health, 2023 - frontiersin.org
Introduction Physical fitness is regarded as a significant indicator of sarcopenia. This study
aimed to develop and evaluate a deep-learning model for predicting the decline in physical …