1
|
Ibad HA, Hathaway QA, Bluemke DA, Kasaeian A, Klein JG, Budoff MJ, Barr RG, Allison M, Post WS, Lima JAC, Demehri S. CT-derived pectoralis composition and incident pneumonia hospitalization using fully automated deep-learning algorithm: multi-ethnic study of atherosclerosis. Eur Radiol 2024; 34:4163-4175. [PMID: 37951855 DOI: 10.1007/s00330-023-10372-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 08/04/2023] [Accepted: 08/14/2023] [Indexed: 11/14/2023]
Abstract
BACKGROUND Pneumonia-related hospitalization may be associated with advanced skeletal muscle loss due to aging (i.e., sarcopenia) or chronic illnesses (i.e., cachexia). Early detection of muscle loss may now be feasible using deep-learning algorithms applied on conventional chest CT. OBJECTIVES To implement a fully automated deep-learning algorithm for pectoralis muscle measures from conventional chest CT and investigate longitudinal associations between these measures and incident pneumonia hospitalization according to Chronic Obstructive Pulmonary Disease (COPD) status. MATERIALS AND METHODS This analysis from the Multi-Ethnic Study of Atherosclerosis included participants with available chest CT examinations between 2010 and 2012. We implemented pectoralis muscle composition measures from a fully automated deep-learning algorithm (Mask R-CNN, built on the Faster Region Proposal Network (R-) Convolutional Neural Network (CNN) with an extension for mask identification) for two-dimensional segmentation. Associations between CT-derived measures and incident pneumonia hospitalizations were evaluated using Cox proportional hazards models adjusted for multiple confounders which include but are not limited to age, sex, race, smoking, BMI, physical activity, and forced-expiratory-volume-at-1 s-to-functional-vital-capacity ratio. Stratification analyses were conducted based on baseline COPD status. RESULTS This study included 2595 participants (51% female; median age: 68 (IQR: 61, 76)) CT examinations for whom we implemented deep learning-derived measures for longitudinal analyses. Eighty-six incident pneumonia hospitalizations occurred during a median 6.67-year follow-up. Overall, pectoralis muscle composition measures did not predict incident pneumonia. However, in fully-adjusted models, only among participants with COPD (N = 507), CT measures like extramyocellular fat index (hazard ratio: 1.98, 95% CI: 1.22, 3.21, p value: 0.02), were independently associated with incident pneumonia. CONCLUSION Reliable deep learning-derived pectoralis muscle measures could predict incident pneumonia hospitalization only among participants with known COPD. CLINICAL RELEVANCE STATEMENT Pectoralis muscle measures obtainable at zero additional cost or radiation exposure from any chest CT may have independent predictive value for clinical outcomes in chronic obstructive pulmonary disease patients. KEY POINTS •Identification of independent and modifiable risk factors of pneumonia can have important clinical impact on patients with chronic obstructive pulmonary disease. •Opportunistic CT measures of adipose tissue within pectoralis muscles using deep-learning algorithms can be quickly obtainable at zero additional cost or radiation exposure. •Deep learning-derived pectoralis muscle measurements of intermuscular fat and its subcomponents are independently associated with subsequent incident pneumonia hospitalization.
Collapse
Affiliation(s)
- Hamza A Ibad
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Russell H. Morgan, Baltimore, MD, USA
| | - Quincy A Hathaway
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Russell H. Morgan, Baltimore, MD, USA
- West Virginia University School of Medicine, Heart and Vascular Institute, Morgantown, WV, USA
| | - David A Bluemke
- University of Wisconsin School of Medicine and Public Health, Department of Radiology, Madison, WI, USA
| | - Arta Kasaeian
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Russell H. Morgan, Baltimore, MD, USA
| | - Joshua G Klein
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Russell H. Morgan, Baltimore, MD, USA
| | - Matthew J Budoff
- Harbor-UCLA Medical Center, Division of Cardiology, Torrance, CA, USA
| | - R Graham Barr
- Columbia University, Division of General Medicine, New York, NY, USA
| | - Matthew Allison
- Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA, USA
| | - Wendy S Post
- Johns Hopkins University School of Medicine, Division of Cardiology, Baltimore, MD, USA
| | - João A C Lima
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Russell H. Morgan, Baltimore, MD, USA
- Johns Hopkins University School of Medicine, Division of Cardiology, Baltimore, MD, USA
| | - Shadpour Demehri
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Russell H. Morgan, Baltimore, MD, USA.
| |
Collapse
|
2
|
Smith LO, Vest MT, Rovner AJ, Caplan RJ, Trabulsi JC, Patel JB, Meng SW, Shapero M, Earthman CP. Malnutrition and pectoralis muscle index in medical intensive care unit patients: A matched cohort study. JPEN J Parenter Enteral Nutr 2024; 48:300-307. [PMID: 38400547 PMCID: PMC10990767 DOI: 10.1002/jpen.2610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 12/01/2023] [Accepted: 01/10/2024] [Indexed: 02/25/2024]
Abstract
BACKGROUND Muscle assessment is an important component of nutrition assessment. The Global Leadership Initiative on Malnutrition (GLIM) consortium recently underscored the need for more objective muscle assessment methods in clinical settings. Various assessment techniques are available; however, many have limitations in clinical populations. Computed tomography (CT) scans, obtained for diagnostic reasons, could serve multiple purposes, including muscle measurement for nutrition assessment. Although CT scans of the chest are commonly performed clinically, there is little research surrounding the utility of pectoralis muscle measurements in nutrition assessment. The primary aim was to determine whether CT-derived measures of pectoralis major cross-sectional area (PMA) and quality (defined as mean pectoralis major Hounsfield units [PMHU]) could be used to identify malnutrition in patients who are mechanically ventilated in an intensive care unit (ICU). A secondary aim was to evaluate the relationship between these measures and clinical outcomes in this population. METHODS A retrospective analysis was conducted on 33 pairs of age- and sex-matched adult patients who are being mechanically ventilated in the ICU. Patients were grouped by nutrition status. Analyses were performed to determine differences in PMA and mean PMHU between groups. Associations between muscle and clinical outcomes were also investigated. RESULTS Compared with nonmalnourished controls, malnourished patients had a significantly lower PMA (P = 0.001) and pectoralis major (PM) index (PMA/height in m2; P = 0.001). No associations were drawn between PM measures and clinical outcomes. CONCLUSION These findings regarding CT PM measures lay the groundwork for actualizing the GLIM call to action to validate quantitative, objective muscle assessment methods in clinical settings.
Collapse
Affiliation(s)
- Luke O. Smith
- Department of Health Behavior and Nutrition Sciences, University of Delaware, Newark, Delaware, USA
| | - Michael T. Vest
- Critical Care Medicine, Department of Medicine, Christiana Care Healthcare System, Sidney Kimmel Medical College, Newark, Delaware, USA
| | - Alisha J. Rovner
- Department of Health Behavior and Nutrition Sciences, University of Delaware, Newark, Delaware, USA
| | - Richard J. Caplan
- Institute for Research in Health Equity and Community Health, Christiana Care Health Service Inc, Newark, Delaware, USA
| | - Jillian C. Trabulsi
- Department of Health Behavior and Nutrition Sciences, University of Delaware, Newark, Delaware, USA
| | - Juhie B. Patel
- Department of Internal Medicine, Christiana Care Healthcare System, Newark, Delaware, USA
| | - Sarah W. Meng
- Division of Community Radiology, Penn Medicine, Philadelphia, Pennsylvania, USA
| | - Mary Shapero
- Department of Food and Nutrition Services, Christiana Care Healthcare System, Newark, Delaware, USA
| | - Carrie P. Earthman
- Department of Health Behavior and Nutrition Sciences, University of Delaware, Newark, Delaware, USA
| |
Collapse
|
3
|
Seo H, Cha SI, Park J, Lim JK, Lee WK, Park JE, Choi SH, Lee YH, Yoo SS, Lee SY, Lee J, Kim CH, Park JY. Pectoralis Muscle Area as a Predictor of Mortality in Patients Hospitalized with Bronchiectasis Exacerbation. Respiration 2024; 103:257-267. [PMID: 38499001 DOI: 10.1159/000538091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 02/27/2024] [Indexed: 03/20/2024] Open
Abstract
INTRODUCTION Data on factors related to mortality in patients with bronchiectasis exacerbation are insufficient. Computed tomography (CT) can measure the pectoralis muscle area (PMA) and is a useful tool to diagnose sarcopenia. This study aimed to evaluate whether PMA can predict mortality in patients with bronchiectasis exacerbation. METHODS Patients hospitalized due to bronchiectasis exacerbation at a single center were retrospectively divided into survivors and non-survivors based on 1-year mortality. Thereafter, a comparison of the clinical and radiologic characteristics was conducted between the two groups. RESULTS A total of 66 (14%) patients died at 1 year. In the multivariate analysis, age, BMI <18.4 kg/m2, sex-specific PMA quartile, ≥3 exacerbations in the previous year, serum albumin <3.5 g/dL, cystic bronchiectasis, tuberculosis-destroyed lung, and diabetes mellitus were independent predictors for the 1-year mortality in patients hospitalized with bronchiectasis exacerbation. A lower PMA was associated with a lower overall survival rate in the survival analysis according to sex-specific quartiles of PMA. PMA had the highest area under the curve during assessment of prognostic performance in predicting the 1-year mortality. The lowest sex-specific PMA quartile group exhibited higher disease severity than the highest quartile group. CONCLUSIONS CT-derived PMA was an independent predictor of 1-year mortality in patients hospitalized with bronchiectasis exacerbation. Patients with lower PMA exhibited higher disease severity. These findings suggest that PMA might be a useful marker for providing additional information regarding prognosis of patients with bronchiectasis exacerbation.
Collapse
Affiliation(s)
- Hyewon Seo
- Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| | - Seung-Ick Cha
- Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| | - Jongmin Park
- Department of Radiology, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| | - Jae-Kwang Lim
- Department of Radiology, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| | - Won Kee Lee
- Biostatistics, Medical Research Collaboration Center, Kyungpook National University, Daegu, Republic of Korea
| | - Ji-Eun Park
- Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| | - Sun Ha Choi
- Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| | - Yong Hoon Lee
- Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| | - Seung-Soo Yoo
- Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| | - Shin-Yup Lee
- Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| | - Jaehee Lee
- Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| | - Chang-Ho Kim
- Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| | - Jae-Yong Park
- Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| |
Collapse
|
4
|
Shang N, Li Q, Ji W, Liu H, Guo S. Acute muscle wasting is associated with poor prognosis in older adults with severe community-acquired pneumonia. Eur Geriatr Med 2024; 15:73-82. [PMID: 38060165 DOI: 10.1007/s41999-023-00895-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 10/30/2023] [Indexed: 12/08/2023]
Abstract
PURPOSE To investigate the impact of acute muscle wasting on 90-day mortality in older patients with severe pneumonia using ultrasound and chest computed tomography (CT). METHODS Quadriceps muscle layer thickness was measured via ultrasound on days 1, 7, and 14, and cross-sectional area of the erector spinae muscle was assessed using chest CT on days 1 and 14 in patients aged ≥ 65 years old. The primary outcome was all-cause 90-day mortality. Receiver operating characteristic curves were conducted for muscle loss to predict 90-day mortality. Cox proportional hazard models and Kaplan-Meier survival curves were employed to evaluate the association between muscle loss and 90-day mortality. RESULTS Sixty-two patients were enrolled with median age of 80.2 years, 29 (46.8%) were men and 28 (45.2%) patients died. Muscle mass measured using ultrasound and CT decreased significantly from baseline to day 14 in the non-survivor group. Muscle loss assessed by ultrasound (with minimum and maximum pressure) and CT independently predicted all-cause 90-day mortality (adjusted hazard ratios = 1.497, 1.400 and 1.082; P < 0.001, P = 0.002, and P = 0.004; respectively), and cutoff values of muscle loss were 0.34 cm, 0.11 cm and 4.92 cm2, correspondingly. A higher muscle loss had an increased risk of 90-day mortality. CONCLUSIONS Acute muscle wasting assessed by ultrasound and chest CT persisted for 14 days and was an independent predictor of adverse outcomes in older patients with severe pneumonia. A greater decline in muscle mass was associated with a higher 90-day mortality risk.
Collapse
Affiliation(s)
- Na Shang
- Department of Emergency Medicine, Beijing Key Laboratory of Cardiopulmonary Cerebral Resuscitation, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, 100020, China
- Department of Emergency Medicine, Capital Medical University School of Rehabilitation Medicine, Beijing Bo'Ai Hospital, China Rehabilitation Research Center, Beijing, 100068, China
| | - Qiujing Li
- Department of Emergency Medicine, Capital Medical University, Beijing Shijitan Hospital, Beijing, 100038, China
| | - Wenqing Ji
- Department of Emergency Medicine, Beijing Key Laboratory of Cardiopulmonary Cerebral Resuscitation, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, 100020, China
| | - Huizhen Liu
- Department of Emergency Medicine, Capital Medical University School of Rehabilitation Medicine, Beijing Bo'Ai Hospital, China Rehabilitation Research Center, Beijing, 100068, China
| | - Shubin Guo
- Department of Emergency Medicine, Beijing Key Laboratory of Cardiopulmonary Cerebral Resuscitation, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, 100020, China.
| |
Collapse
|
5
|
Oh J, Lim H, Jeong CW, Kim MS, Lee J, Kang WS, An UR, Park JU, Ahn Y, Kim YR, Park C. Clinical implication of thoracic skeletal muscle volume as a predictor of ventilation-weaning failure in brain-injured patients: A retrospective observational study. Medicine (Baltimore) 2023; 102:e35847. [PMID: 37904365 PMCID: PMC10615541 DOI: 10.1097/md.0000000000035847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 10/06/2023] [Indexed: 11/01/2023] Open
Abstract
Sarcopenia, a generalized loss of skeletal muscle mass that is primarily evident in the respiratory musculature, is associated with adverse outcomes in critically ill patients. However, the relationship between sarcopenia and ventilation-weaning outcomes has not yet been fully studied in patients with brain injuries. In this study, we examined the effect of reduced respiratory muscle mass on ventilation weaning in patients with brain injury. This observational study retrospectively reviewed the medical records of 73 patients with brain injury between January 2017 and December 2019. Thoracic skeletal muscle volumes were measured from thoracic CT images using the institute's three-dimensional modeling software program of our institute. The thoracic skeletal muscle volumes index (TSMVI) was normalized by dividing muscle volume by the square of patient height. Sarcopenia was defined as a TSMVI of less than the 50th sex-specific percentile. Among 73 patients with brain injury, 12 (16.5%) failed to wean from mechanical ventilation. The patients in the weaning-failure group had significantly higher sequential organ failure assessment scores [7.8 ± 2.7 vs 6.1 ± 2.2, P = .022] and lower thoracic skeletal muscle volume indexes [652.5 ± 252.4 vs 1000.4 ± 347.3, P = .002] compared with those in the weaning-success group. In multivariate analysis, sarcopenia was significantly associated with an increased risk of weaning failure (odds ratio 12.72, 95% confidence interval 2.87-70.48, P = .001). Our study showed a significant association between the TSMVI and ventilation weaning outcomes in patients with brain injury.
Collapse
Affiliation(s)
- Jimi Oh
- Department of Anesthesiology and Pain Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Republic of Korea
| | - Hyun Lim
- Division of Pulmonary Medicine, Department of Internal Medicine, Wonkwang University School of Medicine, Iksan-si, South Korea
| | - Chang Won Jeong
- Smart Health IT Center, Wonkwang University Hospital, Iksan-si, South Korea
| | - Min Su Kim
- Department of Rehabilitation Medicine, Soonchunhyang University, College of Medicine, Cheonan-si, South Korea
| | - Jinseok Lee
- Department of Biomedical Engineering, Kyung Hee University, Yongin-si, South Korea
| | - Wu Seong Kang
- Department of Trauma Surgery, Cheju Halla General Hospital, Jeju-si, South Korea
| | - Ui Ri An
- Division of Pulmonary Medicine, Department of Internal Medicine, Wonkwang University School of Medicine, Iksan-si, South Korea
| | - Joo Un Park
- Division of Pulmonary Medicine, Department of Internal Medicine, Wonkwang University School of Medicine, Iksan-si, South Korea
| | - Youngick Ahn
- Department of Anesthesiology and Pain Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Republic of Korea
| | - Youe Ree Kim
- Department of Radiology, Wonkwang University School of Medicine, Iksan-si, South Korea
| | - Chul Park
- Division of Pulmonary Medicine, Department of Internal Medicine, Wonkwang University School of Medicine, Iksan-si, South Korea
| |
Collapse
|