Pectoralis Muscle Index as Predictor of Outcomes in Patients With Severe Blunt Chest Wall Injury

INTRODUCTION

Sarcopenia has been shown to portend worse outcomes in injured patients; however, little is known about the impact of thoracic muscle wasting on outcomes of patients with chest wall injury. We hypothesized that reduced pectoralis muscle mass is associated with poor outcomes in patients with severe blunt chest wall injury.

METHODS

All patients admitted to the intensive care unit between 2014 and 2019 with blunt chest wall injury requiring mechanical ventilation were retrospectively identified. Blunt chest wall injury was defined as the presence of one or more rib fractures as a result of blunt injury mechanism. Exclusion criteria included lack of admission computed tomography imaging, penetrating trauma, <18 y of age, and primary neurologic injury. Thoracic musculature was assessed by measuring pectoralis muscle cross-sectional area (cm2) that was obtained at the fourth thoracic vertebral level using Slice-O-Matic software. The area was then divided by the patient height in meters2 to calculate pectoralis muscle index (PMI) (cm2/m2). Patients were divided into two groups, 1) the lowest gender-specific quartile of PMI and 2) second-fourth gender-specific PMI quartiles for comparative analysis.

RESULTS

One hundred fifty-three patients met the inclusion criteria with a median (interquartile range) age 48 y (34-60), body mass index of 30.1 kg/m2 (24.9-34.6), and rib score of 3.0 (2.0-4.0). Seventy-five percent of patients (116/153) were male. Fourteen patients (8%) had prior history of chronic lung disease. Median (IQR) intensive care unit length-of-stay and duration of mechanical ventilation (MV) was 18.0 d (13.0-25.0) and 15.0 d (10.0-21.0), respectively. Seventy-three patients (48%) underwent tracheostomy and nine patients (6%) expired during hospitalization. On multivariate linear regression, reduced pectoralis muscle mass was associated with increased MV duration when adjusting for rib score and injury severity score (β 5.98, 95% confidence interval 1.28-10.68, P = 0.013).

CONCLUSIONS

Reduced pectoralis muscle mass is associated with increased duration of MV in patients with severe blunt chest wall injury. Knowledge of this can help guide future research and risk stratification of critically ill chest wall injury patients.

Diagnosis of sarcopenia on thoracic computed tomography and its association with postoperative survival after anatomic lung cancer resection

Computer tomography-derived skeletal muscle index normalized for height in conjunction with muscle density enables single modality-based sarcopenia assessment that accounts for all diagnostic criteria and cutoff recommendations as per the widely accepted European consensus. Yet, the standard approach to quantify skeletal musculature at the third lumbar vertebra is limited for certain patient groups, such as lung cancer patients who receive chest CT for tumor staging that does not encompass this lumbar level. As an alternative, this retrospective study assessed sarcopenia in lung cancer patients treated with curative intent at the tenth thoracic vertebral level using appropriate cutoffs. We showed that skeletal muscle index and radiation attenuation at level T10 correlate well with those at level L3 (Pearson's R = 0.82 and 0.66, p < 0.001). During a median follow-up period of 55.7 months, sarcopenia was independently associated with worse overall (hazard ratio (HR) = 2.11, 95%-confidence interval (95%-CI) = 1.38-3.23, p < 0.001) and cancer-specific survival (HR = 2.00, 95%-CI = 1.19-3.36, p = 0.009) of lung cancer patients following anatomic resection. This study highlights feasibility to diagnose sarcopenia solely by thoracic CT in accordance with the European consensus recommendations. The straightforward methodology offers easy translation into routine clinical care and potential to improve preoperative risk stratification of lung cancer patients scheduled for surgery.

Utility of Noncancerous Chest CT Features for Predicting Overall Survival and Noncancer Death in Patients With Stage I Lung Cancer Treated With Stereotactic Body Radiotherapy

Background: Noncancerous imaging markers can be readily derived from pretreatment diagnostic and radiotherapy planning chest CT examinations. Objective: To explore the ability of noncancerous features on chest CT to predict overall survival (OS) and noncancer-related death in patients with stage I lung cancer treated with stereotactic body radiation therapy (SBRT). Methods: This retrospective study included 282 patients (168 female, 114 male; median age, 75 years) with stage I lung cancer treated with SBRT between January 2009 and June 2017. Pretreatment chest CT was used to quantify coronary artery calcium (CAC) score, pulmonary artery (PA)-to-aorta ratio, emphysema, and body composition in terms of the cross-sectional area and attenuation of skeletal muscle and subcutaneous adipose tissue at the T5, T8, and T10 vertebral levels. Associations of clinical and imaging features with OS were quantified using a multivariable Cox proportional hazards (PH) model. Penalized multivariable Cox PH models to predict OS were constructed using clinical features only and using both clinical and imaging features. Models' discriminatory ability was assessed by constructing time-varying ROC curves and computing AUC at prespecified times. Results: After a median OS of 60.8 months (95% CI 55.8-68.9), 148 (52.5%) patients died, including 83 (56.1%) with noncancer deaths. Higher CAC score (11-399: hazard ratio [HR] 1.83 [95% CI 1.15-2.91], P=.01; ≥400: HR 1.63 [95% CI 1.01-2.63], P=.04), higher PA-to-aorta ratio (HR 1.33 [95% CI 1.16-1.52], P<.001, per 0.1-unit increase), and lower thoracic skeletal muscle index (HR 0.88 [95% CI 0.79-0.98], P=.02, per 10 cm²/m² increase) were independently associated with shorter OS. Discriminatory ability for 5-year OS was greater for the model including clinical and imaging features than for the model including clinical features only (AUC, 0.75 [95% CI 0.68-0.83] versus 0.61 [95% CI 0.53-0.70], p < .01). The model's most important clinical or imaging feature based on mean standardized regression coefficients was the PA-to-aorta ratio. Conclusions: In patients undergoing SBRT for stage I lung cancer, higher CAC score, higher PA-to-aorta ratio, and lower thoracic skeletal muscle index independently predicted worse OS. Clinical Impact: Noncancerous imaging features on chest CT performed before SBRT improve survival prediction compared with clinical features alone.

CT-Derived Body Composition Values and Complications After Pneumonectomy in Lung Cancer Patients: Time for a Sex-Related Analysis?

Purpose

This study aimed to assess if CT-derived body composition values and clinical characteristics are associated with the risk of postsurgical complications in men and women who underwent pneumonectomy for lung cancer.

Materials and Methods

Patients who underwent pneumonectomy between 2004 and 2008 were selected. The ethics committee approved this retrospective study with waiver of informed content. Main clinical data collected were sex, age, weight and height to calculate body mass index (BMI), albumin, C-reactive protein, smoking status, side, sarcopenia, presurgical treatments, reoperation, and complications within 30 days after pneumonectomy, classified as: lung complications, cardiac complications, other complications, and any complication. From an axial CT image at the level of L3, automatic segmentations were performed to calculate skeletal muscle area (SMA), skeletal muscle density, subcutaneous adipose tissue, and visceral adipose tissue. Skeletal muscle index was calculated as SMA/square height. Univariate and multivariate logistic regression analyses were performed to estimate the risk of any complication, both on the total population and in a by sex subgroup analysis. All tests were two tailed and considered significant at 5% level.

Results

A total of 107 patients (84 men and 23 women) were included. Despite no significant differences in BMI, there were significant differences of body composition values in muscle and adipose tissue parameters between men and women, with women being significantly more sarcopenic than men (p = 0.002). Separate analyses for men and women showed that age and SMA were significantly associated with postoperative complications in men (p = 0.03 and 0.02, respectively).

Conclusions

Body composition measurements extracted from routine CT may help in predicting complications after pneumonectomy, with men and women being different in quantity and distribution of muscle and fat, and men significantly more prone to postpneumonectomy complications with the increase of age and the decrease of skeletal muscle area.

Sarcopenia on preoperative chest computed tomography predicts cancer-specific and all-cause mortality following pneumonectomy for lung cancer: A multicenter analysis

Background

Mortality risk prediction in patients undergoing pneumonectomy for non‐small cell lung cancer (NSCLC) remains imperfect. Here, we aimed to assess whether sarcopenia on routine chest computed tomography (CT) independently predicts worse cancer‐specific (CSS) and overall survival (OS) following pneumonectomy for NSCLC.

Methods

We included consecutive adults undergoing standard or carinal pneumonectomy for NSCLC at Massachusetts General Hospital and Heidelberg University from 2010 to 2018. We measured muscle cross‐sectional area (CSA) on CT at thoracic vertebral levels T8, T10, and T12 within 90 days prior to surgery. Sarcopenia was defined as T10 muscle CSA less than two standard deviations below the mean in healthy controls. We adjusted time‐to‐event analyses for age, body mass index, Charlson Comorbidity Index, forced expiratory volume in 1 second in % predicted, induction therapy, sex, smoking status, tumor stage, side of pneumonectomy, and institution.

Results

Three hundred and sixty‐seven patients (67.4% male, median age 62 years, 16.9% early‐stage) underwent predominantly standard pneumonectomy (89.6%) for stage IIIA NSCLC (45.5%) and squamous cell histology (58%). Sarcopenia was present in 104 of 367 patients (28.3%). Ninety‐day all‐cause mortality was 7.1% (26/367). After a median follow‐up of 20.5 months (IQR, 9.2–46.9), 183 of 367 patients (49.9%) had died. One hundred and thirty‐three (72.7%) of these deaths were due to lung cancer. Sarcopenia was associated with shorter CSS (HR 1.7, p = 0.008) and OS (HR 1.7, p = 0.003).

Conclusions

This transatlantic multicenter study confirms that sarcopenia on preoperative chest CT is an independent risk factor for CSS and OS following pneumonectomy for NSCLC.

Low thoracic muscle mass index on computed tomography predicts adverse outcomes following lobectomy via thoracotomy for lung cancer

OBJECTIVES

The aim of this study was to determine whether the preoperative thoracic muscle mass is associated with postoperative outcomes in patients undergoing lobectomy via thoracotomy for lung cancer.

METHODS

Consecutive patients undergoing lobectomy were retrospectively reviewed. The thoracic muscle mass index (TMMI) was obtained at the level of the fifth thoracic vertebra on preoperative thoracic computed tomography (CT). Patients were analysed comparatively by being dividing into low and high muscle index groups by the median of sex-specific TMMI. The primary outcomes were the incidence of any or postoperative pulmonary complications. The secondary outcomes were postoperative intensive care unit (ICU) admission, length of stay (LOS) in the ICU, total hospital LOS, readmission and mortality.

RESULTS

The study population consisted of 120 patients (63.6 ± 9.8 years; 74% male). Each groups included 60 patients. Major complications occurred in 28.3% (34/120) and readmission in 18.3% (22/120) of patients. The adjusted multivariable analysis showed that each unit increase in TMMI (cm2/m2) was independently associated with the rates of less any complications [odds ratio (OR) 0.92, P = 0.014], pulmonary complications (OR 0.27, P = 0.019), ICU admission (OR 0.76, P = 0.031), hospitalization for >6 days (OR 0.90, P = 0.008) and readmission (OR 0.93, P = 0.029).

CONCLUSIONS

Low TMMI obtained from the preoperative thoracic CT is an independent predictor of postoperative adverse outcomes in patients following lobectomy via thoracotomy for lung cancer. TMMI measurements may contribute to the development of preoperative risk stratification studies in the future.

The use of alternate vertebral levels to L3 in computed tomography scans for skeletal muscle mass evaluation and sarcopenia assessment in patients with cancer: a systematic review

Body composition measurement using diagnostic computed tomography (CT) scans has emerged as a method to assess sarcopenia (low muscle mass) in oncology patients. Assessment of skeletal muscle mass (SMM) using the cross-sectional area of a single vertebral slice (at lumbar L3) in a CT scan is correlated with whole-body skeletal muscle volume. This method is used to assess CT-defined sarcopenia in patients with cancer, with low SMM effecting outcomes. However, as diagnostic scans are based on tumour location, not all include L3. We evaluated the evidence for the use of alternate vertebral CT slices for SMM evaluation when L3 is not available. Five electronic databases were searched from January 1996 to April 2020 for studies using CT scan vertebral slices above L3 for SM measurement in adults with cancer (solid tumours). Validation with whole-body SMM, rationale for the chosen slice and sarcopenia cut-off values were investigated. Thirty-two studies were included, all retrospective and cross-sectional in design. Cervical, thoracic and lumbar slices were used (from C3 to L1), with no validation of whole-body SMM using CT scans. Alternate slices were used in lung, and head and neck cancer patients. Sarcopenia cut-off values were reported in 75 % of studies, with differing methods, with or without sex-specific values, and a lack of consensus. Current evidence is inadequate to provide definitive recommendations for alternate vertebral slice use for SMM evaluation in cancer patients. Variation in sarcopenia cut-offs warrants more robust investigation, in order for risk stratification to be applied to all patients with cancer.

Novel application of respiratory muscle index obtained from chest computed tomography to predict postoperative respiratory failure after major non-cardiothoracic surgery

BACKGROUND

Postoperative respiratory failure (PRF) is a serious complication associated with significant morbidity and mortality. We propose a new method to predict PRF by utilizing computed tomography (CT) of the chest to assess degree of respiratory muscle wasting prior to surgery.

METHODS

Patients who received a chest CT and required invasive mechanical ventilation (MV) after major non-cardiothoracic surgery were included. Exclusion criteria included cardiothoracic surgery. Respiratory muscle index (RMI) was calculated at the T6 vertebra measured on Slice-O-Matic® software.

RESULTS

Thirty three patients met inclusion with a mean (±SD) age, BMI, and APACHE II score of 62.2 years (±12.1), 28.1 kg/m² (±7.8), and 14.1 (±4.7). Most patients were female (n = 22 [67%]). Eleven patients (33%) developed PRF with a mean of 6.0 (±10.7) initial ventilation days. There was no difference in baseline demographics between groups. RMI values for the PRF group were significantly lower when compared to the non-PRF group: 22.7 cm²/m² (±5.3) vs. 28.5 cm²/m² (±5.9) (p = 0.008).

CONCLUSION

Presence of respiratory muscle wasting prior to surgery was found to be associated with postoperative respiratory failure.

Significance of Acquisition Parameters for Adipose Tissue Segmentation on CT Images

OBJECTIVE. CT-based body composition analysis quantifies skeletal muscle and adipose tissue. However, acquisition parameters and quality can vary between CT images obtained for clinical care, which may lead to unreliable measurements and systematic error. The purpose of this study was to estimate the influence of IV contrast medium, tube current-exposure time product, tube potential, and slice thickness on cross-sectional area (CSA) and mean attenuation of subcutaneous (SAT), visceral (VAT), and inter-muscular adipose tissue (IMAT). MATERIALS AND METHODS. We retrospectively analyzed 244 images from 105 patients. We applied semiautomated threshold-based segmentation to CTA, dual-energy CT, and CT images acquired as part of PET examinations. An axial image at the level of the third lumbar vertebral body was extracted from each examination to generate 139 image pairs. Images from each pair were obtained with the same scanner, from the same patient, and during the same examination. Each image pair varied in only one acquisition parameter, which allowed us to estimate the effect of the parameter using one-sample t or median tests and Bland-Altman plots. RESULTS. IV contrast medium application reduced CSA in each adipose tissue compartment, with percentage change ranging from -0.4% (p = .03) to -9.3% (p < .001). Higher tube potential reduced SAT CSA (median percentage change, -4.2%; p < .001) and VAT CSA (median percentage change, -2.8%; p = .001) and increased IMAT CSA (median percentage change, -5.4%; p = .001). Thinner slices increased CSA in the VAT (mean percentage change, 3.0%; p = .005) and IMAT (median percentage change, 17.3%; p < .001) compartments. Lower tube current-exposure time product had a variable effect on CSA (median percentage change, -3.2% for SAT [p < .001], -12.6% for VAT [p = .001], and 58.8% for IMAT [p < .001]). IV contrast medium and higher tube potential increased mean attenuation, with percentage change ranging from 0.8% to 1.7% (p < .05) and from 6.2% to 20.8% (p < .001), respectively. Conversely, thinner slice and lower tube current-exposure time product reduced mean attenuation, with percentage change ranging from -5.4% to -1.0% (p < .001) and from -8.7% to -1.8% (p < .001), respectively. CONCLUSION. Acquisition parameters significantly affect CSA and mean attenuation of adipose tissue. Details of acquisition parameters used for CT-based body composition analysis need to be scrutinized and reported to facilitate interpretation of research studies.

The Year in Thoracic Anesthesia: Selected Highlights from 2019

THIS special article is the 4th in an annual series for the Journal of Cardiothoracic and Vascular Anesthesia. The authors thank the editor-in-chief, Dr. Kaplan; the associate editor-in-chief, Dr. Augoustides; and the editorial board for the opportunity to expand this series, the research highlights of the year that specifically pertain to the specialty of thoracic anesthesia. The major themes selected for 2019 are outlined in this introduction, and each highlight is reviewed in detail in the main body of the article. The literature highlights in this specialty for 2019 include updates in the preoperative assessment and optimization of patients undergoing lung resection and esophagectomy, updates in one lung ventilation (OLV) and protective ventilation during OLV, a review of recent meta-analyses comparing truncal blocks with paravertebral catheters and the introduction of a new truncal block, meta-analyses comparing nonintubated video-assisted thoracoscopic surgery (VATS) with those performed using endotracheal intubation, a review of the Society of Thoracic Surgeons (STS) recent composite score rating for pulmonary resection of lung cancer, and an update of the Enhanced Recovery After Surgery (ERAS) guidelines for both lung and esophageal surgery.

Feasibility, Safety and Effects of a One-Week, Ski-Based Exercise Intervention in Brain Tumor Patients and Their Relatives: A Pilot Study

A brain tumor diagnosis poses a significant psychological burden and it severely impacts quality of life (QOL), both in patients and relatives. However, comprehensive strategies addressing QOL in this setting remain rare. Here, we aim to share our findings of a one-week ski exercise intervention, with emphasis on feasibility, safety, QOL, and physical exercise. The intervention consisted of week-long daily ski sessions with professional ski guides as well as dedicated physicians present. The participants were handed questionnaires, including distress and QOL items before, during, and after the intervention. Using fitness watches, exercise intensity was also tracked at these timepoints. During the intervention, patients were checked for adverse events daily. Fifteen participants, nine patients after multidisciplinary treatment, and six relatives were included in the study. Additionally, 13 children participated in the exercise, but not in the study. All of the participants completed the entire program. No severe adverse events were documented during daily checks. There was a strong increase in quantified activity and QOL with a corresponding decrease in distress during the intervention, and, partly, afterwards. This prospective brain tumor rehabilitation study demonstrates the feasibility and safety of challenging ski exercise in brain tumor patients. The findings also underline the exercise-mediated QOL benefits, emphasizing the need for more comprehensive brain tumor rehabilitation programs.

Machine Learning for Automatic Paraspinous Muscle Area and Attenuation Measures on Low-Dose Chest CT Scans

RATIONALE AND OBJECTIVES

To develop and evaluate an automated machine learning (ML) algorithm for segmenting the paraspinous muscles on chest computed tomography (CT) scans to evaluate for presence of sarcopenia.

MATERIALS AND METHODS

A convolutional neural network based on the U-Net architecture was trained to perform muscle segmentation on a dataset of 1875 single slice CT images and was tested on 209 CT images of participants in the National Lung Screening Trial. Low-dose, noncontrast CT examinations were obtained at 33 clinical sites, using scanners from four manufacturers. The study participants had a mean age of 71.6 years (range, 70-74 years). Ground truth was obtained by manually segmenting the left paraspinous muscle at the level of the T12 vertebra. Muscle cross-sectional area (CSA) and muscle attenuation (MA) were recorded. Comparison between the ML algorithm and ground truth measures of muscle CSA and MA were obtained using Dice similarity coefficients and Pearson correlations.

RESULTS

Compared to ground truth segmentation, the ML algorithm achieved median (standard deviation) Dice scores of 0.94 (0.04) in the test set. Mean (SD) muscle CSA was 14.3 (3.6) cm² for ground truth and 13.7 (3.5) cm² for ML segmentation. Mean (SD) MA was 41.6 (7.6) Hounsfield units (HU) for ground truth and 43.5 (7.9) HU for ML segmentation. There was high correlation between ML algorithm and ground truth for muscle CSA (r² = 0.86; p < 0.0001) and MA (r² = 0.95; p < 0.0001).

CONCLUSION

The ML algorithm for measurement of paraspinous muscles compared favorably to manual ground truth measurements in the NLST. The algorithm generalized well to a heterogeneous set of low-dose CT images and may be capable of automated quantification of muscle metrics to screen for sarcopenia on routine chest CT examinations.