Reliability of Skeletal Muscle Area Measurement on CT with Different Parameters: A Phantom Study

Skeletal muscle alterations indicate poor prognosis in cirrhotic patients: a multicenter cohort study in China

INTRODUCTION

We aimed to determine the diagnostic criteria of myosteatosis in a Chinese population and investigate the effect of skeletal muscle abnormalities on the outcomes of cirrhotic patients.

METHODS

Totally 911 volunteers were recruited to determine the diagnostic criteria and impact factors of myosteatosis, and 480 cirrhotic patients were enrolled to verify the value of muscle alterations for prognosis prediction and establish new noninvasive prognostic strategies.

RESULTS

Multivariate analysis showed age, sex, weight, waist circumference, and biceps circumference had a remarkable influence on the L3 skeletal muscle density (L3-SMD). Based on the cut-off of a mean - 1.28 × SD among adults aged < 60 years, the diagnostic criteria for myosteatosis was L3-SMD < 38.93 Hu in males and L3-SMD < 32.82 Hu in females. Myosteatosis rather than sarcopenia has a close correlation with portal hypertension. The concurrence of sarcopenia and myosteatosis not only is associated with poor liver function but also evidently reduced the overall and liver transplantation-free survival of cirrhotic patients (p < 0.001). According to the stepwise Cox regression hazard model analysis, we established nomograms including TBil, albumin, history of HE, ascites grade, sarcopenia, and myosteatosis for easily determining survival probabilities in cirrhotic patients. The AUC is 0.874 (95% CI 0.800-0.949) for 6-month survival, 0.831 (95% CI 0.764-0.898) for 1-year survival, and 0.813 (95% CI 0.756-0.871) for 2-year survival prediction, respectively.

CONCLUSIONS

This study provides evidence of the significant correlation between skeletal muscle alterations and poor outcomes of cirrhosis, and establishes valid and convenient nomograms incorporating musculoskeletal disorders for the prognostic prediction of liver cirrhosis. Further large-scale prospective studies are necessary to verify the value of the nomograms.

Comparing fully automated AI body composition measures derived from thin and thick slice CT image data

PURPOSE

To compare fully automated artificial intelligence body composition measures derived from thin (1.25 mm) and thick (5 mm) slice abdominal CT data.

METHODS

In this retrospective study, fully automated CT-based body composition algorithms for quantifying bone attenuation, muscle attenuation, muscle area, liver attenuation, liver volume, spleen volume, visceral-to-subcutaneous fat ratio (VSR) and aortic calcium were applied to both thin (1.25 × 0.625 mm) and thick (5 × 3 mm) abdominal CT series from two patient cohorts: unenhanced scans in asymptomatic adults undergoing colorectal cancer screening, and post-contrast scans in patients with colorectal cancer. Body composition measures derived from thin and thick slice data were compared, including correlation coefficients and Bland-Altman analysis.

RESULTS

A total of 9882 CT scans (mean age, 57.0 years; 4527 women, 5355 men) were evaluated, including 8947 non-contrast and 935 contrast-enhanced CT exams. Very strong positive correlation was observed for all soft tissue measures: muscle attenuation (r2 = 0.97), muscle area (r2 = 0.98), liver attenuation (r2 = 0.99), liver volume (r2 = 0.98) and spleen volume (r2 = 0.99), VSR (r2 = 0.98), and aortic calcium (r2 = 0.92); (p < 0.001 for all). Moderate positive correlation was observed for bone attenuation (r2 = 0.35). Bland-Altman analysis showed strong agreement for muscle attenuation, muscle area, liver attenuation, liver volume and spleen volume. Mean percentage differences amongst body composition measures were less than 5% for VSR (4.6%), muscle area (- 0.5%), liver attenuation (0.4%) and liver volume (2.7%) and less than 10% for muscle attenuation (- 5.5%) and spleen volume (5.1%). For aortic calcium, thick slice overestimated for Agatston scores between 0 and 100 and > 400 burden in 3.1% and 0.3% relative to thin slice, respectively, but underestimated scores between 100 and 400.

CONCLUSION

Automated body composition measures derived from thin and thick abdominal CT data are strongly correlated and show agreement, particularly for soft tissue applications, making it feasible to use either series for these CT-based body composition algorithms.

Value of Cystatin C-Based Sarcopenia Index in Patients Undergoing Surgery for Renal Tumors

INTRODUCTION

Sarcopenia is a condition of low muscle strength and quantity, severe if low physical performances. The sarcopenia index (SI), calculated by blood levels of creatinine and cystatin C, had been reported to be correlated with skeletal muscle mass and is a potential simple screening tool for sarcopenia. We hypothesized that patients with a low SI, meaning low muscle mass, would have an inflated estimated glomerular filtration rate (eGFR) value based on serum creatinine levels. We also tested the prognostic value of the SI in a cohort of patients who had surgery for renal malignancies.

PATIENTS AND METHODS

We conducted a retrospective, observational study of 322 patients that had surgery for renal tumors in National Cancer Center Hospital East (Kashiwa, Chiba) between April 2017 and June 2023. We assessed sarcopenia measuring psoas muscle index (PMI), psoas muscle density (PMD), and skeletal muscle area (SMA) by computed tomography. We assessed the association between SI and eGFR before and after surgery. We also assessed the association between SI and postoperative outcome, including overall survival.

RESULTS

Of the 322 patients, 211 (66%) were males, with a median age of 69 years. SI had a weak correlation with both PMI and PMD in males (PMI: ρ = 0.25; PMD: ρ = 0.21). In females, SI and PMD exhibited a low correlation (ρ = 0.26), while SI and PMI displayed an insignificant correlation (ρ = 0.19). The correlation between SMA and SI was moderate for both males and females (males: ρ = 0.51; females: ρ = 0.46). After radical nephrectomy, eGFR decreased in 98% of patients with high SI, compared to 69% of patients with low SI. We also demonstrated that low SI predicted poor prognosis.

CONCLUSIONS

Clinicians can recognize the possibility of overestimated eGFR in the low SI group by measuring SI around the surgery. Low SI may also help predict poor prognosis.

Low-dose versus conventional CT urography using dual-source CT with different time-current product values and the same tube voltage: image quality and diagnostic performance in various diagnoses

OBJECTIVES

To compare the image quality and diagnostic performance of low-dose CT urography to that of concurrently acquired conventional CT using dual-source CT.

METHODS

This retrospective study included 357 consecutive CT urograms performed by third-generation dual-source CT in a single institution between April 2020 and August 2021. Two-phase CT images (unenhanced phase, excretory phase with split bolus) were obtained with two different tube current-time products (280 mAs for the conventional-dose protocol and 70 mAs for the low-dose protocol) and the same tube voltage (90 kVp) for the two X-ray tubes. Iterative reconstruction was applied for both protocols. Two radiologists independently performed quantitative and qualitative image quality analysis and made diagnoses. The correlation between the noise level or the effective radiation dose and the patients' body weight was evaluated.

RESULTS

Significantly higher noise levels resulting in a significantly lower liver signal-to-noise ratio and contrast-to-noise ratio were noted in low-dose images compared to conventional images (P < .001). Qualitative analysis by both radiologists showed significantly lower image quality in low-dose CT than in conventional CT images (P < .001). Patient's body weight was positively correlated with noise and effective radiation dose (P < .001). Diagnostic performance for various diseases, including urolithiasis, inflammation, and mass, was not different between the two protocols.

CONCLUSIONS

Despite inferior image quality, low-dose CT urography with 70 mAs and 90 kVp and iterative reconstruction demonstrated diagnostic performance equivalent to that of conventional CT for identifying various diseases of the urinary tract.

ADVANCES IN KNOWLEDGE

Low-dose CT (25% radiation dose) with low tube current demonstrated diagnostic performance comparable to that of conventional CT for a variety of urinary tract diseases.

Cigarette smoking and disproportionate changes of thoracic skeletal muscles in low-dose chest computed tomography

Association between smoking intensity and the quantity and quality of thoracic skeletal muscles (TSMs) remains unexplored. Skeletal muscle index (SMI; skeletal muscle area/height2) and percentage of normal attenuation muscle area (NAMA%) were measured to represent the quantity and quality of the skeletal muscles, respectively, and quantification was performed in pectoralis muscle at aortic arch (AA-PM), TSM at carina (C-TSM), erector spinae muscle at T12 (T12-ESM), and skeletal muscle at L1 (L1-SM). Among the 258 men (median age, 62 years [IQR: 58-69]), 183 were current smokers (median smoking intensity, 40 pack-years [IQR: 30-46]). SMI and NAMA% of AA-PM significantly decreased with pack-year (β =  - 0.028 and - 0.076; P < 0.001 and P = 0.021, respectively). Smoking intensity was inversely associated with NAMA% of C-TSM (β =  - 0.063; P = 0.001), whereas smoking intensity showed a borderline association with SMI of C-TSM (β =  - 0.023; P = 0.057). Smoking intensity was associated with the change in NAMA% of L1-SM (β =  - 0.040; P = 0.027), but was not associated with SMI of L1-SM (P > 0.05). Neither NAMA% nor SMI of T12-ESM was affected by smoking intensity (P > 0.05). In conclusion, smoking intensity was associated with the change of TSMs. Its association varied according to the location of TSMs, with the most associated parts being the upper (AA-PM) and middle TSMs (C-TSM).

Association between computed tomography-assessed sarcopenia and mortality in patients with anti-neutrophil cytoplasmic antibody-associated vasculitis

AIM

Sarcopenia is frequently observed in patients with autoimmune rheumatic diseases; however, its relationship with patient outcomes has not been well understood. This study evaluated the influence of sarcopenia, especially muscle quality, on outcomes of antineutrophil cytoplasmic antibody-associated vasculitis (AAV).

METHODS

Records of patients with AAV at the Severance Hospital with computed tomography (CT) images taken at initial disease diagnosis were retrospectively reviewed. For measures of sarcopenia, normal attenuation muscle area (NAMA), low attenuation muscle area (LAMA), intramuscular adipose tissue (IMAT), and total abdominal muscle area (TAMA) in the axial muscles of the middle third lumbar vertebra level were calculated. Correlations between NAMA, LAMA, IMAT, and baseline patient characteristics, as well as the association between the NAMA/TAMA ratio and clinical outcomes were assessed.

RESULTS

A total of 136 patients with CT images at AAV diagnosis were identified. Correlation analyses revealed that age, female sex, total cholesterol, and alanine aminotransferase were significantly associated with NAMA. LAMA was associated with age, body mass index (BMI), five-factor score (FFS), and C-reactive protein, and a relationship between IMAT and age and BMI was observed. During the follow up of 31.2 months, 23 (16.9%) patients died, and Cox-proportional hazard analysis demonstrated that a NAMA/TAMA ≤0.46 (odds ratio [OR] 10.247, p < .001), female sex (OR 0.206, p = .006), dyslipidemia (OR 3.143, p = .027), creatinine (OR 1.342, p = .012), and FFS (OR 1.775, p = .046), were independently associated with patient mortality.

CONCLUSION

A higher rate of mortality was observed in patients with AAV with NAMA/TAMA ≤0.46, indicating that careful monitoring is required in these patients.

A comparative study of two automated solutions for cross-sectional skeletal muscle measurement from abdominal computed tomography images

BACKGROUND

Measurement of cross-sectional muscle area (CSMA) at the mid third lumbar vertebra (L3) level from computed tomography (CT) images is becoming one of the reference methods for sarcopenia diagnosis. However, manual skeletal muscle segmentation is tedious and is thus restricted to research. Automated solutions are required for use in clinical practice.

PURPOSE

The aim of this study was to compare the reliability of two automated solutions for the measurement of CSMA.

METHODS

We conducted a retrospective analysis of CT images in our hospital database. We included consecutive individuals hospitalized at the Grenoble University Hospital in France between January and May 2018 with abdominal CT images and sagittal reconstruction. We used two types of software to automatically segment skeletal muscle: ABACS, a module of the SliceOmatic software solution "ABACS-SliceOmatic," and a deep learning-based solution called "AutoMATiCA." Manual segmentation was performed by a medical expert to generate reference data using "SliceOmatic." The Dice similarity coefficient (DSC) was used to measure overlap between the results of the manual and the automated segmentations. The DSC value for each method was compared with the Mann-Whitney U test.

RESULTS

A total of 676 hospitalized individuals was retrospectively included (365 males [53.8%] and 312 females [46.2%]). The median DSC for SliceOmatic vs AutoMATiCA (0.969 [5th percentile: 0.909]) was greater than the median DSC for SliceOmatic vs. ABACS-SliceOmatic (0.949 [5th percentile: 0.836]) (p < 0.001).

CONCLUSIONS

AutoMATiCA, which used artificial intelligence, was more reliable than ABACS-SliceOmatic for skeletal muscle segmentation at the L3 level in a cohort of hospitalized individuals. The next step is to develop and validate a neural network that can identify L3 slices, which is currently a fastidious process.

Association of pectoralis muscle area on computed tomography with airflow limitation severity and respiratory outcomes in COPD: A population-based prospective cohort study

BACKGROUND

Previous studies have shown that patients with chronic obstructive pulmonary disease (COPD) of severe or very severe airflow limitation have a reduced pectoralis muscle area (PMA), which is associated with mortality. However, whether patients with COPD of mild or moderate airflow limitation also have a reduced PMA remains unclear. Additionally, limited evidence is available regarding the associations between PMA and respiratory symptoms, lung function, computed tomography (CT) imaging, lung function decline, and exacerbations. Therefore, we conducted this study to evaluate the presence of PMA reduction in COPD and to clarify its associations with the referred variables.

METHODS

This study was based on the subjects enrolled from July 2019 to December 2020 in the Early Chronic Obstructive Pulmonary Disease (ECOPD) study. Data including questionnaire, lung function, and CT imaging were collected. The PMA was quantified on full-inspiratory CT at the aortic arch level using predefined -50 and 90 Hounsfield unit attenuation ranges. Multivariate linear regression analyses were performed to assess the association between the PMA and airflow limitation severity, respiratory symptoms, lung function, emphysema, air trapping, and the annual decline in lung function. Cox proportional hazards analysis and Poisson regression analysis were used to evaluate the PMA and exacerbations after adjustment.

RESULTS

We included 1352 subjects at baseline (667 with normal spirometry, 685 with spirometry-defined COPD). The PMA was monotonically lower with progressive airflow limitation severity of COPD after adjusting for confounders (vs. normal spirometry; Global Initiative for Chronic Obstructive Lung Disease [GOLD] 1: β=-1.27, P=0.028; GOLD 2: β=-2.29, P<0.001; GOLD 3: β=-4.88, P<0.001; GOLD 4: β=-6.47, P=0.014). The PMA was negatively associated with the modified British Medical Research Council dyspnea scale (β=-0.005, P=0.026), COPD Assessment Test score (β=-0.06, P=0.001), emphysema (β=-0.07, P<0.001), and air trapping (β=-0.24, P<0.001) after adjustment. The PMA was positively associated with lung function (all P<0.05). Similar associations were discovered for the pectoralis major muscle area and pectoralis minor muscle area. After the 1-year follow-up, the PMA was associated with the annual decline in the post-bronchodilator forced expiratory volume in 1 s percent of predicted value (β=0.022, P=0.002) but not with the annual rate of exacerbations or the time to first exacerbation.

CONCLUSION

Patients with mild or moderate airflow limitation exhibit a reduced PMA. The PMA is associated with airflow limitation severity, respiratory symptoms, lung function, emphysema, and air trapping, suggesting that PMA measurement can assist with COPD assessment.

The validation of low-dose CT scans from the [18F]-FDG PET-CT scan to assess skeletal muscle mass in comparison with diagnostic neck CT scans

PURPOSE

Radiologically defined sarcopenia, or a low skeletal muscle index (SMI), is an emerging biomarker for adverse clinical outcomes in head and neck cancer (HNC) patients. Recently, SMI measurements have been validated at the level of the third cervical vertebra (C3) on diagnostic neck CT scans but are not yet validated on low-dose (LD) neck CT scans from the [¹⁸F]-FDG PET-CT. This hampers SMI analysis in HNC patients without a diagnostic neck CT but with a [¹⁸F]-FDG PET-CT scan. Therefore, the aim was to study whether (low) SMI based on LD CT scan from [¹⁸F]-FDG PET-CT is comparable to those derived from diagnostic neck CT scans.

METHODS

HNC patients with both diagnostic CT and [¹⁸F]-FDG PET-CT of the neck were prospectively included into the OncoLifeS data-biobank. Skeletal muscle was retrospectively delineated at the level of the third cervical vertebra (C3), and (low) SMI (cm²/m²) was calculated for diagnostic and LD neck CTs. (Low) SMI from the diagnostic neck CT was considered the reference standard. Intra-class correlation coefficient (ICC), Bland-Altman plots, and Cohen's Kappa analysis were performed.

RESULTS

The cohort (n = 233) mean age was 66.2 ± 12.8 years, and 74.2% of patients were male. Inter-rater reliability was excellent (ICC > 0.990, 95% confidence interval 0.975-0.996, p < 0.001). The agreement of SMI between both modalities was high according to the Bland-Altman plot (mean ΔSMI =  - 0.19 cm²/m²), and there was no substantial bias. Cohen's Kappa analysis showed an almost perfect agreement of low SMI between the two modalities (κ = 0.911, p < 0.001). The position of arms didn't affect the high agreement of (low) SMI.

CONCLUSION

Skeletal muscle mass, as measured with (low) SMI, remains constant irrespective of CT acquisition parameters (diagnostic neck CT scans versus LD neck scans of the [18F]-FDG PET-CT scan), positioning of arms, and observers. These findings contribute to the construction of a clinically useful radiological biomarker for SMI and therefore identify patients at risk for adverse clinical outcomes.

A Cross-Sectional Study on Gluteal Muscles in Patients with Ankylosing Spondylitis at Different Stages of Hip Involvement

Hip involvement in ankylosing spondylitis (AS) is associated with severe functional impairment, and early diagnosis can improve the disease prognosis. We investigated gluteal muscle cross-sectional area (CSA) and radiodensity at different stages of hip involvement and their associations with AS-related clinical and laboratory parameters. This cross-sectional study included 83 patients with AS and 83 age- and sex-matched controls. Patients with AS were divided into three groups according to the Bath Ankylosing Spondylitis Radiology Hip Index system. The CSA and radiodensity of the gluteus maximus, medius, and minimus muscles were measured using computed tomography images. Muscle parameters were compared, and their relationships with clinical and laboratory parameters were evaluated. For the gluteus maximus, patients with AS had a lower CSA than controls, regardless of the degree of hip involvement. For the gluteus medius and minimus, patients with moderate/advanced hip involvement had significantly lower CSA and radiodensity than those with mild to no hip involvement. The severity of hip involvement was negatively associated with muscle parameters. CSA of the gluteus maximus decreased in early-stage hip involvement without any changes in radiographs, while radiodensity decreased in the later stages. Muscle parameters on computed tomography may be a more sensitive indicator than radiographic findings.

The effect of computed tomography parameters on sarcopenia and myosteatosis assessment: a scoping review

Computed tomography (CT) is a valuable assessment method for muscle pathologies such as sarcopenia, cachexia, and myosteatosis. However, several key underappreciated scan imaging parameters need consideration for both research and clinical use, specifically CT kilovoltage and the use of contrast material. We conducted a scoping review to assess these effects on CT muscle measures. We reviewed articles from PubMed, Scopus, and Web of Science from 1970 to 2020 on the effect of intravenous contrast material and variation in CT kilovoltage on muscle mass and density. We identified 971 articles on contrast and 277 articles on kilovoltage. The number of articles that met inclusion criteria for contrast and kilovoltage was 11 and 7, respectively. Ten studies evaluated the effect of contrast on muscle density of which nine found that contrast significantly increases CT muscle density (arterial phase 6-23% increase, venous phase 19-57% increase, and delayed phase 23-43% increase). Seven out of 10 studies evaluating the effect of contrast on muscle area found significant increases in area due to contrast (≤2.58%). Six studies evaluating kilovoltage on muscle density found that lower kilovoltage resulted in a higher muscle density (14-40% increase). One study reported a significant decrease in muscle area when reducing kilovoltage (2.9%). The use of contrast and kilovoltage variations can have dramatic effects on skeletal muscle analysis and should be considered and reported in CT muscle analysis research. These significant factors in CT skeletal muscle analysis can alter clinical and research outcomes and are therefore a barrier to clinical application unless better appreciated.

Associations Between Trunk Muscle/Fat Composition, Narrowing Lumbar Disc Space, and Low Back Pain in Middle-Aged Farmers: A Cross-Sectional Study

Objective

To investigate the association of trunk fat and muscle composition, lumbar disc space narrowing, and low back pain in middle-aged farmers.

Methods

Fat and muscle areas were identified using standard Hounsfield unit ranges for adipose tissue and skeletal muscle with computed tomography images at the mid-L4 vertebral level. Trunk fat mass, muscle mass, and fat/muscle mass ratio were calculated. Low back pain was assessed using the Oswestry Disability Index (ODI). The L4/5-disc space and low back pain were also assessed.

Results

Male had a higher total trunk, back, psoas, and abdominal muscle mass, and visceral fat; female had a higher subcutaneous fat mass and fat/muscle ratio. Pearson correlation coefficients with ODI for waist circumference, total fat mass, visceral fat mass, and fat/muscle ratio were all significant in female; only the fat/muscle ratio was significant in male. Pearson correlation coefficients with L4/5-disc space narrowing grades for visceral fat mass, total, back, and psoas muscle mass, and fat/muscle ratio, were all significant in female; total and back muscle mass, and fat/muscle ratio in male.

Conclusion

There were significant relationships between: fat indicators with low back pain; trunk muscle mass with lumbar disc degeneration; and fat/muscle ratio with both lumbar disc degeneration and low back pain. The fat/muscle ratio may be a useful index for low back pain.

A reliable and robust method for the upper thigh muscle quantification on computed tomography: toward a quantitative biomarker for sarcopenia

Background

We aimed to evaluate the feasibility of the upper thigh level as a landmark to measure muscle area for sarcopenia assessment on computed tomography (CT).

Methods

In the 116 healthy subjects who performed CT scans covering from mid-abdomen to feet, the skeletal muscle area in the upper thigh level at the inferior tip of ischial tuberosity (SMA_UT), the mid-thigh level (SMA_MT), and L3 inferior endplate level (SMA_L3) were measured by two independent readers. Pearson correlation coefficients between SMA_UT, SMA_MT, and SMA_L3 were calculated. Inter-reader agreement between the two readers were evaluated using intraclass correlation coefficient (ICC) and Bland-Altman plots with 95% limit of agreement (LOA).

Results

In readers 1 and 2, very high positive correlations were observed between SMA_UT and SMA_MT (r = 0.91 and 0.92, respectively) and between SMA_UT and SMA_L3 (r = 0.90 and 0.91, respectively), while high positive correlation were observed between SMA_MT and SMA_L3 (r = 0.87 and 0.87, respectively). Based on ICC values, the inter-reader agreement was the best in the SMA_UT (0.999), followed by the SMA_L3 (0.990) and SMA_MT (0.956). The 95% LOAs in the Bland-Altman plots indicated that the inter-reader agreement of the SMA_UT (− 0.462 to 1.513) was the best, followed by the SMA_L3 (− 9.949 to 7.636) and SMA_MT (− 12.105 to 14.605).

Conclusion

Muscle area measurement at the upper thigh level correlates well with those with the mid-thigh and L3 inferior endpoint level and shows the highest inter-reader agreement. Thus, the upper thigh level might be an excellent landmark enabling SMA_UT as a reliable and robust biomarker for muscle area measurement for sarcopenia assessment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-022-05032-2.

Validation for measurements of skeletal muscle areas using low-dose chest computed tomography

Various methods were suggested to measure skeletal muscle areas (SMAs) using chest low-dose computed tomography (chest LDCT) as a substitute for SMA at 3rd lumbar vertebra level (L3-SMA). In this study, four SMAs (L1-SMA, T12-erector spinae muscle areas, chest wall muscle area at carina level, pectoralis muscle area at aortic arch level) were segmented semi-automatically in 780 individuals taking concurrent chest and abdomen LDCT for healthcare screening. Four SMAs were compared to L3-SMA and annual changes were calculated from individuals with multiple examinations (n = 101). Skeletal muscle index (SMI; SMA/height²) cut-off for sarcopenia was determined by lower 5th percentile of young individuals (age ≤ 40 years). L1-SMA showed the greatest correlation to L3-SMA (men, R² = 0.7920; women, R² = 0.7396), and the smallest annual changes (0.3300 ± 4.7365%) among four SMAs. L1-SMI cut-offs for determining sarcopenia were 39.2cm²/m² in men, and 27.5cm²/m² in women. Forty-six men (9.5%) and ten women (3.4%) were found to have sarcopenia using L1-SMI cut-offs. In conclusion, L1-SMA could be a reasonable substitute for L3-SMA in chest LDCT. Suggested L1-SMI cut-offs for sarcopenia were 39.2cm²/m² for men and 27.5cm²/m² for women in Asian.

Development of a fully automatic deep learning system for L3 selection and body composition assessment on computed tomography

As sarcopenia research has been gaining emphasis, the need for quantification of abdominal muscle on computed tomography (CT) is increasing. Thus, a fully automated system to select L3 slice and segment muscle in an end-to-end manner is demanded. We aimed to develop a deep learning model (DLM) to select the L3 slice with consideration of anatomic variations and to segment cross-sectional areas (CSAs) of abdominal muscle and fat. Our DLM, named L3SEG-net, was composed of a YOLOv3-based algorithm for selecting the L3 slice and a fully convolutional network (FCN)-based algorithm for segmentation. The YOLOv3-based algorithm was developed via supervised learning using a training dataset (n = 922), and the FCN-based algorithm was transferred from prior work. Our L3SEG-net was validated with internal (n = 496) and external validation (n = 586) datasets. Ground truth L3 level CT slice and anatomic variation were identified by a board-certified radiologist. L3 slice selection accuracy was evaluated by the distance difference between ground truths and DLM-derived results. Technical success for L3 slice selection was defined when the distance difference was < 10 mm. Overall segmentation accuracy was evaluated by CSA error and DSC value. The influence of anatomic variations on DLM performance was evaluated. In the internal and external validation datasets, the accuracy of automatic L3 slice selection was high, with mean distance differences of 3.7 ± 8.4 mm and 4.1 ± 8.3 mm, respectively, and with technical success rates of 93.1% and 92.3%, respectively. However, in the subgroup analysis of anatomic variations, the L3 slice selection accuracy decreased, with distance differences of 12.4 ± 15.4 mm and 12.1 ± 14.6 mm, respectively, and with technical success rates of 67.2% and 67.9%, respectively. The overall segmentation accuracy of abdominal muscle areas was excellent regardless of anatomic variation, with CSA errors of 1.38-3.10 cm². A fully automatic system was developed for the selection of an exact axial CT slice at the L3 vertebral level and the segmentation of abdominal muscle areas.

Effects of Contrast Phases on Automated Measurements of Muscle Quantity and Quality Using CT

OBJECTIVE

Muscle quantity and quality can be measured with an automated system on CT. However, the effects of contrast phases on the muscle measurements have not been established, which we aimed to investigate in this study.

MATERIALS AND METHODS

Muscle quantity was measured according to the skeletal muscle area (SMA) measured by a convolutional neural network-based automated system at the L3 level in 89 subjects undergoing multiphasic abdominal CT comprising unenhanced phase, arterial phase, portal venous phase (PVP), or delayed phase imaging. Muscle quality was analyzed using the mean muscle density and the muscle quality map, which comprises normal and low-attenuation muscle areas (NAMA and LAMA, respectively) based on the muscle attenuation threshold. The SMA, mean muscle density, NAMA, and LAMA were compared between PVP and other phases using paired t tests. Bland-Altman analysis was used to evaluate the inter-phase variability between PVP and other phases. Based on the cutoffs for low muscle quantity and quality, the counts of individuals who scored lower than the cutoff values were compared between PVP and other phases.

RESULTS

All indices showed significant differences between PVP and other phases (p < 0.001 for all). The SMA, mean muscle density, and NAMA increased during the later phases, whereas LAMA decreased during the later phases. Bland-Altman analysis showed that the mean differences between PVP and other phases ranged -2.1 to 0.3 cm² for SMA, -12.0 to 2.6 cm² for NAMA, and -2.2 to 9.9 cm² for LAMA.The number of patients who were categorized as low muscle quantity did not significant differ between PVP and other phases (p ≥ 0.5), whereas the number of patients with low muscle quality significantly differed (p ≤ 0.002).

CONCLUSION

SMA was less affected by the contrast phases. However, the muscle quality measurements changed with the contrast phases to greater extents and would require a standardization of the contrast phase for reliable measurement.