Simple Age Specific Cutoff Value for Sarcopenia Evaluated by Computed Tomography

2017 ◽  
Vol 71 (3-4) ◽  
pp. 157-163 ◽  
Author(s):  
Ji Sun Kim ◽  
Won Young Kim ◽  
Hyun Kyung Park ◽  
Myung Chun Kim ◽  
Woong Jung ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Skeletal Muscle ◽  
Muscle Mass ◽  
Skeletal Muscle Mass ◽  
Psoas Muscle ◽  
Health Screening ◽  
Healthy Adults ◽  
Cutoff Value ◽  
Cutoff Values ◽  
The Mean

Objective: Until now, cutoff values of low skeletal muscle mass using computed tomography (CT) were driven by optimal stratification to predict mortality in cancer patients. The aim of the present study was to investigate the simple, age-specific, cutoff value of low skeletal muscle mass by CT in healthy adults. Design: This is a retrospective, observational, single-center study. Setting: This study was performed in the health screening department of a university-affiliated hospital during a 10-year period. Patients: Medical records of 1,422 patients presenting to the health screening department were reviewed. Cross-sectional area of psoas muscle at the level of the third lumbar vertebra on abdominal CT was measured and adjusted by height (mm2/m2). This value (psoas muscle index [PMI]) was assumed to represent whole skeletal muscle mass. We divided the patients according to age, sex, and defined cutoff value of low skeletal muscle mass as 2 SDs below the mean. Intervention: None. Measurements and Main Results: Among 1,422 patients, 550 patients (38.6%) were male. The mean PMI was 896.60 (mm2/m2) for men and 570.54 (mm2/m2) for women. Cutoff values of PMI for men were 592.3 mm2/m2 for 20-39 years, 474.0 mm2/m2 for 40-49 years, 422.2 mm2/m2 for 50-59 years, 374.4 mm2/m2 for 60-69 years, and 331.5 mm2/m2 for 70-89 years. The values for women were 399.9 mm2/m2 for 20-39 years, 287.7 mm2/m2 for 40-49 years, 242.5 mm2/m2 for 50-59 years, 220.4 mm2/m2 for 60-69 years, and 147.6 mm2/m2 for 70-89 years. Conclusions: Cutoff values of low skeletal muscle mass using CT differed in healthy adults as age increased. Further studies on the effect of sarcopenia intervention using this cutoff value are needed.

scholarly journals Predictors of Discordance in the Assessment of Skeletal Muscle Mass between Computed Tomography and Bioimpedance Analysis

2019 ◽  
Vol 8 (3) ◽  
pp. 322 ◽  
Author(s):  
Min Jo ◽  
Tae Lim ◽  
Mi Jeon ◽  
Hye Lee ◽  
Beom Kim ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Skeletal Muscle ◽  
Muscle Mass ◽  
Skeletal Muscle Mass ◽  
Female Gender ◽  
Albumin Level ◽  
Advanced Age ◽  
Bioimpedance Analysis ◽  
Skeletal Muscle Index ◽  
Cutoff Values

Computed tomography (CT) and bioimpedance analysis (BIA) can assess skeletal muscle mass (SMM). Our objective was to identify the predictors of discordance between CT and BIA in assessing SMM. Participants who received a comprehensive medical health check-up between 2010 and 2018 were recruited. The CT and BIA-based diagnostic criteria for low SMM are as follows: Defined CT cutoff values (lumbar skeletal muscle index (LSMI) <1 standard deviation (SD) and means of 46.12 cm2/m2 for men and 34.18 cm2/m2 for women) and defined BIA cutoff values (appendicular skeletal muscle/height2 <7.0 kg/m2 for men and <5.7 kg/m2 for women). A total of 1163 subjects were selected. The crude and body mass index (BMI)-adjusted SMM assessed by CT were significantly associated with those assessed by BIA (correlation coefficient = 0.78 and 0.68, respectively; p < 0.001). The prevalence of low SMM was 15.1% by CT and 16.4% by BIA. Low SMM diagnosed by CT was significantly associated with advanced age, female gender, and lower serum albumin level, whereas low SMM diagnosed by BIA was significantly associated with advanced age, female gender, and lower BMI (all p < 0.05). Upon multivariate analysis, age >65 years, female and BMI <25 kg/m2 had significantly higher risks of discordance than their counterparts (all p < 0.05). We found a significant association between SMM assessed by CT and BIA. SMM assessment using CT and BIA should be interpreted cautiously in older adults (>65 years of age), female and BMI <25 kg/m2.

Analysis of the optimal psoas muscle mass index cut‐off values, as measured by computed tomography, for the diagnosis of loss of skeletal muscle mass in Japanese people

2020 ◽  
Vol 50 (6) ◽  
pp. 715-725 ◽  
Author(s):  
Masatsugu Ohara ◽  
Goki Suda ◽  
Megumi Kimura ◽  
Osamu Maehara ◽  
Tomoe Shimazaki ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Skeletal Muscle ◽  
Muscle Mass ◽  
Skeletal Muscle Mass ◽  
Psoas Muscle ◽  
Japanese People

Validity of measuring psoas muscle mass index for assessing sarcopenia in patients with gynecological cancer

2020 ◽  
Author(s):  
Ryutaro Yamada ◽  
Yukiharu Todo ◽  
Hiroyuki Kurosu ◽  
Kaoru Minowa ◽  
Tomohiko Tsuruta ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Skeletal Muscle ◽  
Confidence Interval ◽  
Muscle Mass ◽  
Skeletal Muscle Mass ◽  
Psoas Muscle ◽  
Dual Energy ◽  
X Ray ◽  
Index Measurement ◽  
Skeletal Muscle Mass Index

Abstract Objective The current study evaluated the performance of psoas muscle mass measurement for detecting low skeletal muscle mass quantity. Methods A sample of 82 consecutive patients with gynecological cancers was examined using computed tomography and dual energy X-ray absorptiometric scan before treatment. Skeletal muscle mass index was measured by dual energy X-ray absorptiometric scan and its cut-off value was set at 5.40 kg/m2 for detecting low skeletal muscle mass. Psoas muscle mass index was manually measured with cross-sectional computed tomography imaging at the level of L3 by six evaluators. Results Low skeletal muscle mass index was identified in 23 (28.0%) patients. Two-way analysis of variance confirmed a significant main effect of skeletal muscle mass index on mean psoas muscle mass index values (P &lt; 0.0001). A receiver operating characteristic curve obtained from a total of 492 psoas muscle mass index data points gathered from six evaluators produced an area under the curve value of 0.697 (95% confidence interval 0.649–0.744) and a cut-off value of 3.52 cm2/m2, with sensitivity of 79.0% and specificity of 59.6%. Using the cut-off value, the kappa coefficient for evaluating diagnostic agreement between skeletal muscle mass index (low vs. normal) and psoas muscle mass index (low vs. normal) was 0.308 (95% confidence interval 0.225–0.392), suggesting poor agreement. Fleiss’ kappa produced a coefficient of 0.418 (95% confidence interval 0.362–0.473), suggesting moderate agreement. Conclusions Although relevance between skeletal muscle mass index and psoas muscle mass index was confirmed, intensity of relevance between them was weak. Psoas muscle mass index measurement should be subordinated to skeletal muscle mass index measurement for detection of low skeletal muscle mass.

scholarly journals Association between hand muscle thickness and whole-body skeletal muscle mass in healthy adults: a pilot study

2017 ◽  
Vol 29 (9) ◽  
pp. 1644-1648 ◽  
Author(s):  
Akio Morimoto ◽  
Tadashi Suga ◽  
Nobuaki Tottori ◽  
Michio Wachi ◽  
Jun Misaki ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Pilot Study ◽  
Muscle Mass ◽  
Skeletal Muscle Mass ◽  
Muscle Thickness ◽  
Healthy Adults ◽  
Whole Body ◽  
Hand Muscle

Clinical implication of psoas muscle mass measurement for predicting death within 3 months in patients with incurable uterine cervical or corpus malignancy

2021 ◽  
Author(s):  
Hiroyuki Kurosu ◽  
Yukiharu Todo ◽  
Ryutaro Yamada ◽  
Kaoru Minowa ◽  
Tomohiko Tsuruta ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Muscle Mass ◽  
Cancer Cachexia ◽  
Mass Measurement ◽  
Characteristic Curve ◽  
Lumbar Vertebra ◽  
Psoas Muscle ◽  
Data Set ◽  
Cutoff Value ◽  
Computed Tomography Images

Abstract Objective The aim of this study was to find a clinical marker for identifying refractory cancer cachexia. Methods We analyzed computed tomography imaging data, which included the third lumbar vertebra, from 94 patients who died of uterine cervix or corpus malignancy. The time between the date of examination and date of death was the most important attribute for this study, and the computed tomography images were classified into &gt;3 months before death and ≤ 3 months before death. Psoas muscle mass index was defined as the left–right sum of the psoas muscle areas (cm2) at the level of third lumbar vertebra, divided by height squared (m2). Results A data set of 94 computed tomography images was obtained at baseline hospital visit, and a data set of 603 images was obtained at other times. One hundred (16.6%) of the 603 non-baseline images were scanned ≤3 months before death. Mean psoas muscle mass index change rates at &gt;3 months before death and ≤3 months before death were −1.3 and −20.1%, respectively (P &lt; 0.001). Receiver operating characteristic curve analysis yielded a cutoff value of −13.0%. The area under the curve reached a moderate accuracy level (0.777, 95% confidence interval 0.715–0.838). When we used the cutoff value to predict death within 3 months, sensitivity and specificity were 74.0 and 82.1%, respectively. Conclusions Measuring change in psoas muscle mass index might be useful for predicting cancer mortality within 3 months. It could become a potential tool for identifying refractory cancer cachexia.

scholarly journals Predictors of changes in skeletal muscle mass after esophagectomy in elderly patients with esophageal cancer

2021 ◽  
Author(s):  
Tsuyoshi Harada ◽  
Noriatsu Tatematsu ◽  
Junya Ueno ◽  
Yu Koishihara ◽  
Nobuko Konishi ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Esophageal Cancer ◽  
Elderly Patients ◽  
Muscle Mass ◽  
Skeletal Muscle Mass ◽  
Quadriceps Muscle ◽  
Computed Tomography Images ◽  
Ratio Change ◽  
Comprehensive Rehabilitation ◽  
The Mean

Abstract Purpose : Although a change in skeletal muscle mass index (SMI) 4 months after esophagectomy impacts prognosis, predictors of a change in SMI have not been revealed. The purpose of this exploratory retrospective study was to clarify the predictors of a change in SMI after curative esophagectomy in elderly patients with esophageal cancer.Methods : Fifty-four patients who underwent esophagectomy and perioperative rehabilitation from 2015 to 2018 were enrolled. Preoperative and postoperative SMI (cm 2 /m 2 ) were calculated using computed tomography images. The ratio change in SMI was calculated as follows: (postoperative SMI − preoperative SMI) ÷ preoperative SMI × 100%. Potential predictors of a change in SMI ratio were analyzed by multiple regression. Results : The mean ratio change in SMI 4 months after esophagectomy was −7.1% ± 9.4%. The ratio change in quadriceps muscle strength in the first month after surgery ([postoperative strength − preoperative strength] ÷ preoperative strength × 100%) (standardized β = .273, p = .038) and neoadjuvant chemotherapy (NAC) (standardized β = .398, p = .006) were predictors of the ratio change in SMI independent of age, sex, pathological stage, and preoperative SMI. Conclusion : Quadriceps muscle weakness in the first month after esophagectomy and NAC were predictors of the ratio change in SMI after esophagectomy. Continuous postoperative comprehensive rehabilitation and supportive care may inhibit loss of skeletal muscle mass.

scholarly journals Skeletal muscle mass at C3 may not be a strong predictor for skeletal muscle mass at L3 in sarcopenic patients with head and neck cancer

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254844
Author(s):  
Joon-Kee Yoon ◽  
Jeon Yeob Jang ◽  
Young-Sil An ◽  
Su Jin Lee
Keyword(s):  
Skeletal Muscle ◽  
Head And Neck Cancer ◽  
Diagnostic Accuracy ◽  
Prediction Model ◽  
Muscle Mass ◽  
Skeletal Muscle Mass ◽  
Strong Predictor ◽  
Healthy Adults ◽  
Muscle Area ◽  
The Relationship

Purpose To evaluate the feasibility of using skeletal muscle mass (SMM) at C3 (C3 SMM) as a diagnostic marker for sarcopenia in head and neck cancer (HNC) patients. Methods We evaluated 165 HNC patients and 42 healthy adults who underwent 18F-fluorodeoxyglucose positron emission tomography/computed tomography scans. The paravertebral muscle area at C3 and skeletal muscle area at L3 were measured by CT. Pearson’s correlation was used to assess the relationship between L3 and C3 SMMs. The prediction model for L3 SMM was developed by multiple linear regression. Then the correlation and the agreement between actual and predicted L3 SMMs were assessed. To evaluate the diagnostic value of C3 SMM for sarcopenia, the receiver operating characteristics (ROC) curves were analyzed. Results Of the 165 HNC patients, 61 (37.0%) were sarcopenic and 104 (63.0%) were non-sarcopenic. A very strong correlation was found between L3 SMM and C3 SMM in both healthy adults (r = 0.864) and non-sarcopenic patients (r = 0.876), while a fair association was found in sarcopenic patients (r = 0.381). Prediction model showed a very strong correlation between actual SMM and predicted L3 SMM in both non-sarcopenic patients and healthy adults (r > 0.9), whereas the relationship was moderate in sarcopenic patients (r = 0.7633). The agreement between two measurements was good for healthy subjects and non-sarcopenic patients, while it was poor for sarcopenic patients. On ROC analysis, predicted L3 SMM showed poor diagnostic accuracy for sarcopenia. Conclusions A correlation between L3 and C3 SMMs was weak in sarcopenic patients. A prediction model also showed a poor diagnostic accuracy. Therefore, C3 SMM may not be a strong predictor for L3 SMM in sarcopenic patients with HNC.

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