Dataset Information

Thoracic skeletal muscle index is effective for CT-defined sarcopenia evaluation in patients with head and neck cancer.

ABSTRACT:

Purpose

Computed tomography (CT)-defined sarcopenia, as a measurement of low skeletal muscle (SM), is a poor prognostic indicator in patients with head and neck cancer (HNC), independent of weight or nutritional status. We used SM measures at the second thoracic vertebra (T2) to determine T2-SM index (SMI) thresholds for sarcopenia, and investigate the impact of low T2-SMI on overall survival (OS), and weight loss during radiotherapy (RT).

Methods

Adult patients with newly diagnosed HNC with a diagnostic PET-CT or RT planning CT scan were included. SM was analysed at T2 and a model applied to predict SM at L3. T2-SMI thresholds for sarcopenia were established with predicted measures, stratified by BMI and sex. Impact of sarcopenia and low T2-SMI on OS and weight loss during RT was investigated.

Results

A total of 361 scans were analysed (84% males, 54% oropharynx tumours). Sarcopenia was found in 49%, demonstrating worse OS (p = 0.037). T2-SMI cutoff values were: females-74 cm²/m² [area under the curve (AUC): 0.89 (95%CI 0.80-0.98)], males (BMI < 25)-63 cm²/m² [AUC 0.93 (95%CI 0.89-0.96)], males (BMI ≥ 25)-88cm²/m² [AUC 0.86 (95%CI 0.78-0.93)]. No difference in OS with T2-SMI categories. Lowest T2-SMI quartile of < 63 cm²/m² demonstrated worse OS (p = 0.017). Weight loss during RT was higher in patients; who were not sarcopenic (6.2% vs 4.9%, p = 0.023); with higher T2-SMI (6.3% vs 4.9%, p = 0.014) and; in the highest quartiles (3.6% vs 5.7% vs 7.2%, p < 0.001).

Conclusions

These T2-SMI thresholds are effective in assessing CT-defined sarcopenia in HNC. Further assessment of clinical application is warranted.

SUBMITTER: Vangelov B

PROVIDER: S-EPMC10620319 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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Publications

Thoracic skeletal muscle index is effective for CT-defined sarcopenia evaluation in patients with head and neck cancer.

Vangelov Belinda B Smee Robert R Moses Daniel D Bauer Judith J

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery 20230812 12

<h4>Purpose</h4>Computed tomography (CT)-defined sarcopenia, as a measurement of low skeletal muscle (SM), is a poor prognostic indicator in patients with head and neck cancer (HNC), independent of weight or nutritional status. We used SM measures at the second thoracic vertebra (T2) to determine T2-SM index (SMI) thresholds for sarcopenia, and investigate the impact of low T2-SMI on overall survival (OS), and weight loss during radiotherapy (RT).<h4>Methods</h4>Adult patients with newly diagnos ...[more]

PMID: 37573279

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Project description:Measurements of skeletal muscle cross-sectional area (SMA) at the level of the third lumbar (L3) vertebra derived from clinical computed tomography (CT) scans are commonly used in assessments of sarcopenia, the loss of skeletal muscle mass and function associated with aging. As SMA is correlated with height and Body Mass Index (BMI), body size adjustment is necessary to fairly assess sarcopenic low muscle mass in individuals of different height and BMI. The skeletal muscle index, a widely used measure, adjusts for height as [Formula: see text] but uses no BMI adjustment. There is no agreed upon standard for body size adjustment. We extracted L3 SMA using non-contrast-enhanced CT scans from healthy adults, split into 'Under-40' and 'Over-40' cohorts. Sex-specific allometric analysis showed that height to the power of one was the optimal integer coefficient for height adjusted SMA in both males and females. We computed two height-adjusted measures [Formula: see text] and [Formula: see text], comparing their Pearson correlations versus age, height, weight, and BMI separately by sex and cohort. Finally, in the 'Under-40' cohort, we used linear regression to convert each height-adjusted measure into a z-score ([Formula: see text], [Formula: see text]) adjusted for BMI. [Formula: see text] was less correlated with height in both males and females ([Formula: see text], [Formula: see text] and [Formula: see text], [Formula: see text]) than [Formula: see text] ([Formula: see text] and [Formula: see text], [Formula: see text]). [Formula: see text] was uncorrelated with BMI and weight, and minimally correlated with height in males and females ([Formula: see text], [Formula: see text] and [Formula: see text], [Formula: see text]). The final [Formula: see text] equation was: [Formula: see text], where [Formula: see text], [Formula: see text], [Formula: see text], and sex = 1 if male, 0 if female. We propose [Formula: see text] for optimal height adjustment and the [Formula: see text] score for optimal height and BMI adjustment. By minimizing correlations with height and BMI, the [Formula: see text] score produces unbiased assessments of relative L3 skeletal muscle area across the full range of body sizes.

Project description:ObjectivesCross-sectional area (CSA) measurements of the neck musculature at the level of third cervical vertebra (C3) on CT scans are used to diagnose radiological sarcopenia, which is related to multiple adverse outcomes in head and neck cancer (HNC) patients. Alternatively, these assessments are performed with neck MRI, which has not been validated so far. For that, the objective was to evaluate whether skeletal muscle mass and sarcopenia can be assessed on neck MRI scans.MethodsHNC patients were included between November 2014 and November 2018 from a prospective data-biobank. CSAs of the neck musculature at the C3 level were measured on CT (n = 125) and MRI neck scans (n = 92 on 1.5-T, n = 33 on 3-T). Measurements were converted into skeletal muscle index (SMI), and sarcopenia was defined (SMI < 43.2 cm2/m2). Pearson correlation coefficients, Bland-Altman plots, McNemar test, Cohen's kappa coefficients, and interclass correlation coefficients (ICCs) were estimated.ResultsCT and MRI correlated highly on CSA and SMI (r = 0.958-0.998, p < 0.001). The Bland-Altman plots showed a nihil mean ΔSMI (- 0.13-0.44 cm2/m2). There was no significant difference between CT and MRI in diagnosing sarcopenia (McNemar, p = 0.5-1.0). Agreement on sarcopenia diagnosis was good with κ = 0.956-0.978 and κ = 0.870-0.933, for 1.5-T and 3-T respectively. Observer ICCs in MRI were excellent. In general, T2-weighted images had the best correlation and agreement with CT.ConclusionsSkeletal muscle mass and sarcopenia can interchangeably be assessed on CT and 1.5-T and 3-T MRI neck scans. This allows future clinical outcome assessment during treatment irrespective of used modality.Key points• Screening for low amount of skeletal muscle mass is usually measured on neck CT scans and is highly clinical relevant as it is related to multiple adverse outcomes in head and neck cancer patients. • We found that skeletal muscle mass and sarcopenia determined on CT and 1.5-T and 3-T MRI neck scans at the C3 level can be used interchangeably. • When CT imaging of the neck is missing for skeletal muscle mass analysis, patients can be assessed with 1.5-T or 3-T neck MRIs.

Project description:BackgroundSarcopenia is generally diagnosed by the total area of skeletal muscle in the CT axial slice located in the third lumbar (L3) vertebra. However, patients with severe liver cirrhosis cannot accurately obtain the corresponding total skeletal muscle because their abdominal muscles are squeezed, which affects the diagnosis of sarcopenia.PurposeThis study proposes a novel lumbar skeletal muscle network to automatically segment multi-regional skeletal muscle from CT images, and explores the relationship between cirrhotic sarcopenia and each skeletal muscle region.MethodsThis study utilizes the skeletal muscle characteristics of different spatial regions to improve the 2.5D U-Net enhanced by residual structure. Specifically, a 3D texture attention enhancement block is proposed to tackle the issue of blurred edges with similar intensities and poor segmentation between different skeletal muscle regions, which contains skeletal muscle shape and muscle fibre texture to spatially constrain the integrity of skeletal muscle region and alleviate the difficulty of identifying muscle boundaries in axial slices. Subsequentially, a 3D encoding branch is constructed in conjunction with a 2.5D U-Net, which segments the lumbar skeletal muscle in multiple L3-related axial CT slices into four regions. Furthermore, the diagnostic cut-off values of the L3 skeletal muscle index (L3SMI) are investigated for identifying cirrhotic sarcopenia in four muscle regions segmented from CT images of 98 patients with liver cirrhosis.ResultsOur method is evaluated on 317 CT images using the five-fold cross-validation method. For the four skeletal muscle regions segmented in the images from the independent test set, the avg. DSC is 0.937 and the avg. surface distance is 0.558 mm. For sarcopenia diagnosis in 98 patients with liver cirrhosis, the cut-off values of Rectus Abdominis, Right Psoas, Left Psoas, and Paravertebral are 16.67, 4.14, 3.76, and 13.20 cm2/m2 in females, and 22.51, 5.84, 6.10, and 17.28 cm2/m2 in males, respectively.ConclusionThe proposed method can segment four skeletal muscle regions related to the L3 vertebra with high accuracy. Furthermore, the analysis shows that the Rectus Abdominis region can be used to assist in the diagnosis of sarcopenia when the total muscle is not available.

Dataset Information

Thoracic skeletal muscle index is effective for CT-defined sarcopenia evaluation in patients with head and neck cancer.

Purpose

Methods

Results

Conclusions

Publications

Thoracic skeletal muscle index is effective for CT-defined sarcopenia evaluation in patients with head and neck cancer.

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