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Objective@#The prognostic value of the volume and density of skeletal muscles in the abdominal waist of patients with colon cancer remains unclear. This study aimed to investigate the association between the automated computed tomography (CT)-based volume and density of the muscle in the abdominal waist and survival outcomes in patients with colon cancer. @*Materials and Methods@#We retrospectively evaluated 474 patients with colon cancer who underwent surgery with curative intent between January 2010 and October 2017. Volumetric skeletal muscle index and muscular density were measured at the abdominal waist using artificial intelligence (AI)-based volumetric segmentation of body composition on preoperative pre-contrast CT images. Patients were grouped based on their skeletal muscle index (sarcopenia vs. not) and muscular density (myosteatosis vs. not) values and combinations (normal, sarcopenia alone, myosteatosis alone, and combined sarcopenia and myosteatosis). Postsurgical disease-free survival (DFS) and overall survival (OS) were analyzed using univariable and multivariable analyses, including multivariable Cox proportional hazard regression. @*Results@#Univariable analysis showed that DFS and OS were significantly worse for the sarcopenia group than for the nonsarcopenia group (P = 0.044 and P = 0.003, respectively, by log-rank test) and for the myosteatosis group than for the nonmyosteatosis group (P < 0.001 by log-rank test for all). In the multivariable analysis, the myosteatotic muscle type was associated with worse DFS (adjusted hazard ratio [aHR], 1.89 [95% confidence interval, 1.25–2.86]; P = 0.003) and OS (aHR, 1.90 [95% confidence interval, 1.84–3.04]; P = 0.008) than the normal muscle type. The combined muscle type showed worse OS than the normal muscle type (aHR, 1.95 [95% confidence interval, 1.08–3.54]; P = 0.027). @*Conclusion@#Preoperative volumetric sarcopenia and myosteatosis, automatically assessed from pre-contrast CT scans using AI-based software, adversely affect survival outcomes in patients with colon cancer.
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Objectives@#Intraoperative navigation reduces the risk of major complications and increases the likelihood of optimal surgical outcomes. This paper presents an augmented reality (AR)-based simulation technique for ventriculostomy that visualizes brain deformations caused by the movements of a surgical instrument in a three-dimensional brain model. This is achieved by utilizing a position-based dynamics (PBD) physical deformation method on a preoperative brain image. @*Methods@#An infrared camera-based AR surgical environment aligns the real-world space with a virtual space and tracks the surgical instruments. For a realistic representation and reduced simulation computation load, a hybrid geometric model is employed, which combines a high-resolution mesh model and a multiresolution tetrahedron model. Collision handling is executed when a collision between the brain and surgical instrument is detected. Constraints are used to preserve the properties of the soft body and ensure stable deformation. @*Results@#The experiment was conducted once in a phantom environment and once in an actual surgical environment. The tasks of inserting the surgical instrument into the ventricle using only the navigation information presented through the smart glasses and verifying the drainage of cerebrospinal fluid were evaluated. These tasks were successfully completed, as indicated by the drainage, and the deformation simulation speed averaged 18.78 fps. @*Conclusions@#This experiment confirmed that the AR-based method for external ventricular drain surgery was beneficial to clinicians.
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Objective@#To evaluate the reliability of CT measurements of muscle quantity and quality using variable CT parameters. @*Materials and Methods@#A phantom, simulating the L2–4 vertebral levels, was used for this study. CT images were repeatedly acquired with modulation of tube voltage, tube current, slice thickness, and the image reconstruction algorithm. Reference standard muscle compartments were obtained from the reference maps of the phantom. Cross-sectional area based on the Hounsfield unit (HU) thresholds of muscle and its components, and the mean density of the reference standard muscle compartment, were used to measure the muscle quantity and quality using different CT protocols. Signal-to-noise ratios (SNRs) were calculated in the images acquired with different settings. @*Results@#The skeletal muscle area (threshold, -29 to 150 HU) was constant, regardless of the protocol, occupying at least 91.7% of the reference standard muscle compartment. Conversely, normal attenuation muscle area (30–150 HU) was not constant in the different protocols, varying between 59.7% and 81.7% of the reference standard muscle compartment. The mean density was lower than the target density stated by the manufacturer (45 HU) in all cases (range, 39.0–44.9 HU). The SNR decreased with low tube voltage, low tube current, and in sections with thin slices, whereas it increased when the iterative reconstruction algorithm was used. @*Conclusion@#Measurement of muscle quantity using HU threshold was reliable, regardless of the CT protocol used. Conversely, the measurement of muscle quality using the mean density and narrow HU thresholds were inconsistent and inaccurate across different CT protocols. Therefore, further studies are warranted in future to determine the optimal CT protocols for reliable measurements of muscle quality.
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Background@#Sarcopenia is defined as the loss of skeletal muscle mass and is associated with negative clinical outcomes. This study aimed to establish sex-specific cutoff values for the skeletal muscle area (SMA) and skeletal muscle index (SMI) at the third lumbar vertebral (L3) level using computed tomography (CT) imaging to identify sarcopenia in healthy Korean liver donors. @*Methods@#This retrospective study included 659 healthy liver donors (408 men and 251 women) aged 20 to 60 years who had undergone abdominal CT examinations between January 2017 and December 2018. Assessment of body composition was performed with an automated segmentation technique using a deep-learning system. Sex-specific SMA and SMI distributions were assessed, and cutoff values for determining sarcopenia were defined as values at either two standard deviations (SDs) below the mean reference value or below the fifth percentile. @*Results@#Using the SD definition, cutoff values for SMA and SMI were 117.04 cm2 and 39.33 cm2/m2, respectively, in men and 71.39 cm2 and 27.77 cm2/m2, respectively, in women. Using the fifth percentile definition, cutoff values for SMA and SMI were 126.88 cm2 and 40.96 cm2/m2, respectively, in men and 78.85 cm2 and 30.60 cm2/m2, respectively, in women. @*Conclusion@#Our data provide sex-specific cutoff values for the SMA and SMI at the L3 level measured by CT imaging in a healthy Korean population, which may be applicable for identifying sarcopenia in this population.
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Objective@#To evaluate the reliability of CT measurements of muscle quantity and quality using variable CT parameters. @*Materials and Methods@#A phantom, simulating the L2–4 vertebral levels, was used for this study. CT images were repeatedly acquired with modulation of tube voltage, tube current, slice thickness, and the image reconstruction algorithm. Reference standard muscle compartments were obtained from the reference maps of the phantom. Cross-sectional area based on the Hounsfield unit (HU) thresholds of muscle and its components, and the mean density of the reference standard muscle compartment, were used to measure the muscle quantity and quality using different CT protocols. Signal-to-noise ratios (SNRs) were calculated in the images acquired with different settings. @*Results@#The skeletal muscle area (threshold, -29 to 150 HU) was constant, regardless of the protocol, occupying at least 91.7% of the reference standard muscle compartment. Conversely, normal attenuation muscle area (30–150 HU) was not constant in the different protocols, varying between 59.7% and 81.7% of the reference standard muscle compartment. The mean density was lower than the target density stated by the manufacturer (45 HU) in all cases (range, 39.0–44.9 HU). The SNR decreased with low tube voltage, low tube current, and in sections with thin slices, whereas it increased when the iterative reconstruction algorithm was used. @*Conclusion@#Measurement of muscle quantity using HU threshold was reliable, regardless of the CT protocol used. Conversely, the measurement of muscle quality using the mean density and narrow HU thresholds were inconsistent and inaccurate across different CT protocols. Therefore, further studies are warranted in future to determine the optimal CT protocols for reliable measurements of muscle quality.
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Background@#Sarcopenia is defined as the loss of skeletal muscle mass and is associated with negative clinical outcomes. This study aimed to establish sex-specific cutoff values for the skeletal muscle area (SMA) and skeletal muscle index (SMI) at the third lumbar vertebral (L3) level using computed tomography (CT) imaging to identify sarcopenia in healthy Korean liver donors. @*Methods@#This retrospective study included 659 healthy liver donors (408 men and 251 women) aged 20 to 60 years who had undergone abdominal CT examinations between January 2017 and December 2018. Assessment of body composition was performed with an automated segmentation technique using a deep-learning system. Sex-specific SMA and SMI distributions were assessed, and cutoff values for determining sarcopenia were defined as values at either two standard deviations (SDs) below the mean reference value or below the fifth percentile. @*Results@#Using the SD definition, cutoff values for SMA and SMI were 117.04 cm2 and 39.33 cm2/m2, respectively, in men and 71.39 cm2 and 27.77 cm2/m2, respectively, in women. Using the fifth percentile definition, cutoff values for SMA and SMI were 126.88 cm2 and 40.96 cm2/m2, respectively, in men and 78.85 cm2 and 30.60 cm2/m2, respectively, in women. @*Conclusion@#Our data provide sex-specific cutoff values for the SMA and SMI at the L3 level measured by CT imaging in a healthy Korean population, which may be applicable for identifying sarcopenia in this population.
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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.