Muscle Reference Values From Thoracic and Abdominal CT for Sarcopenia Assessment: The Framingham Heart Study.
Loss of muscle mass is a known feature of sarcopenia and predicts poor clinical outcomes. Although muscle metrics can be derived from routine computed tomography (CT) images, sex-specific reference values at multiple vertebral levels over a wide age range are lacking.
The aim of this study was to provide reference values for skeletal muscle mass and attenuation on thoracic and abdominal CT scans in the community-based Framingham Heart Study cohort to aid in the identification of sarcopenia.
This secondary analysis of a prospective trial describes muscle metrics by age and sex for participants from the Framingham Heart Study without prior history of cancer who underwent at least 1 CT scan between 2002 and 2011. Using 2 previously validated machine learning algorithms followed by human quality assurance, skeletal muscle was analyzed on a single axial CT image per level at the 5th, 8th, 10th thoracic, and 3rd lumbar vertebral body (T5, T8, T10, L3). Cross-sectional muscle area (cm 2 ), mean skeletal muscle radioattenuation (SMRA, in Hounsfield units), skeletal muscle index (SMI, in cm 2 /m 2 ), and skeletal muscle gauge (SMRA·SMI) were calculated. Measurements were summarized by age group (<45, 45-54, 55-64, 65-74, ≥75 years), sex, and vertebral level. Models enabling the calculation of age-, sex-, and vertebral-level-specific reference values were created and embedded into an open access online Web application.
The cohort consisted of 3804 participants (1917 [50.4%] males; mean age, 55.6 ± 11.8 years; range, 33-92 years) and 7162 CT scans. Muscle metrics qualitatively decreased with increasing age and female sex.
This study established age- and sex-specific reference values for CT-based muscle metrics at thoracic and lumbar vertebral levels. These values may be used in future research investigating the role of muscle mass and attenuation in health and disease, and to identify sarcopenia.
Tonnesen PE
,Mercaldo ND
,Tahir I
,Dietrich AW
,Amayri W
,Graur A
,Allaire B
,Bouxsein ML
,Samelson EJ
,Kiel DP
,Fintelmann FJ
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Subcutaneous and Visceral Adipose Tissue Reference Values From the Framingham Heart Study Thoracic and Abdominal CT.
Computed tomography (CT) captures the quantity, density, and distribution of subcutaneous and visceral (SAT and VAT) adipose tissue compartments. These metrics may change with age and sex.
The study aims to provide age-, sex-, and vertebral level-specific reference values for SAT on chest CT and for SAT and VAT on abdomen CT.
This secondary analysis of an observational study describes SAT and VAT measurements in participants of the Framingham Heart Study without known cancer diagnosis who underwent at least 1 of 2 CT examinations between 2002 and 2011. We used a previously validated machine learning-assisted pipeline and rigorous quality assurance to segment SAT at the fifth, eighth, and tenth thoracic vertebra (T5, T8, T10) and SAT and VAT at the third lumbar vertebra (L3). For each metric, we measured cross-sectional area (cm 2 ) and mean attenuation (Hounsfield units [HU]) and calculated index (area/height 2 ) (cm 2 /m 2 ) and gauge (attenuation × index) (HU × cm 2 /m 2 ). We summarized body composition metrics by age and sex and modeled sex-, age-, and vertebral level-specific reference curves.
We included 14,898 single-level measurements from up to 4 vertebral levels of 3797 scans of 3730 Framingham Heart Study participants (1889 [51%] male with a mean [standard deviation] age of 55.6 ± 10.6 years; range, 38-81 years). The mean VAT index increased with age from 65 (cm 2 /m 2 ) in males and 29 (cm 2 /m 2 ) in females in the <45-year-old age group to 99 (cm 2 /m 2 ) in males and 60 (cm 2 /m 2 ) in females in >75-year-old age group. The increase of SAT with age was less pronounced, resulting in the VAT/SAT ratio increasing with age. A free R package and online interactive visual web interface allow access to reference values.
This study establishes age-, sex-, and vertebral level-specific reference values for CT-assessed SAT at vertebral levels T5, T8, T10, and L3 and VAT at vertebral level L3.
Marquardt JP
,Tonnesen PE
,Mercaldo ND
,Graur A
,Allaire B
,Bouxsein ML
,Samelson EJ
,Kiel DP
,Fintelmann FJ
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Age- and sex-adjusted CT-based reference values for temporal muscle thickness, cross-sectional area and radiodensity.
Muscle mass has been traditionally assessed by measuring paraspinal muscle areas at the level of the third lumbar vertebra on computed tomography (CT). Neurological or neurosurgical patients seldom undergo CT scans of the lumbar region. Instead, temporal muscle thickness (TMT), cross-sectional area (TMA) and radiodensity measured from head CT scans are readily available measures of muscle mass and quality in these patient cohorts. The purpose of this retrospective study was to establish CT-based reference values for TMT, TMA and radiodensity for each decade of age from 0 to 100 years normalized by age and sex, and to define cut-off values for subjects at risk for sarcopenia as defined by the European Working Group on Sarcopenia in Older People (EWGSOP). Subjects diagnosed with a concussion at the Oulu University Hospital between January 2014 and December 2022 (n = 9254) were identified to obtain a reference population. Subjects with significant pre-existing co-morbidities were excluded. TMT, TMA and radiodensity were measured, measurement reliability was quantified, and sex-adjusted reference values were calculated for each age decade. Quantile regression was used to model age-related changes in muscle morphomics. A total of 500 subjects [250 (50.0%) males] with a mean age of 49.2 ± 27.9 years were evaluated. Inter- and intra-observer reliability was almost perfect for TMT and TMA, and substantial-to-almost perfect for radiodensity. The mean TMT, TMA and radiodensity were 5.2 ± 1.9 mm, 284 ± 159 mm2 and 44.6 ± 17.7HU, respectively. The cut-off values for reduced TMT, TMA and radiodensity for males/females using the European Working Group on Sarcopenia in Older People compliant criteria were ≤ 4.09 mm/≤3.44 mm, ≤ 166 mm2/≤156 mm2, and ≤ 35.5HU/≤35.2HU, respectively. We described a standardized CT-based TMT and TMA measurement protocol practical for clinical use with almost perfect reliability. Using the protocol, we produced quantile regression models for the detection of reduced TMT, TMA and radiodensity at the lowest 5th, 10th, 20th, 30th, 40th and 50th percentiles as well as the EWGSOP compliant criteria cut-off values for reduced muscle mass to facilitate generalizable radiological sarcopenia research.
Pesonen EK
,Arponen O
,Niinimäki J
,Hernández N
,Pikkarainen L
,Tetri S
,Korhonen TK
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Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.
Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided.
(1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS?
Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses.
Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS.
Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments.
Level III, diagnostic study.
Lee CC
,Chen CW
,Yen HK
,Lin YP
,Lai CY
,Wang JL
,Groot OQ
,Janssen SJ
,Schwab JH
,Hsu FM
,Lin WH
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