Validation of a Semiautomatic Image Analysis Software for the Quantification of Musculoskeletal Tissues

Accuracy of pelvic bone segmentation for 3d printing: a study of segmentation accuracy based on anatomic landmarks to evaluate the influence of the observer

BACKGROUND

3D printing has a wide range of applications and has brought significant change to many medical fields. However, ensuring quality assurance (QA) is essential for patient safety and requires a QA program that encompasses the entire production process. This process begins with imaging and continues on with segmentation, which is the conversion of Digital Imaging and Communications in Medicine (DICOM) data into virtual 3D-models. Since segmentation is highly influenced by manual intervention the influence of the users background on segmentation accuracy should be thoroughly investigated.

METHODS

Seventeen computed tomography (CT) scans of the pelvis with physiological bony structures were identified, anonymized, exported as DICOM data sets, and pelvic bones were segmented by four observers with different backgrounds. Landmarks were measured on DICOM images and in the segmentations. Intraclass correlation coefficients (ICCs) were calculated to assess inter-observer agreement, and the trueness of the segmentation results was analyzed by comparing the DICOM landmark measurements with the measurements of the segmentation results. The correlation between segmentation trueness and segmentation time was analyzed.

RESULTS

The lower limits of the 95% confidence intervals of the ICCs for the seven landmarks analyzed ranged from 0.511 to 0.986. The distance between the iliac crests showed the highest agreement between observers, while the distance between the ischial tuberosities showed the lowest. The distance between the upper edge of the symphysis and the promontory showed the lowest deviation between DICOM measurements and segmentation measurements (mean deviations < 1 mm), while the intertuberous distance showed the highest deviation (mean deviations 14.5-18.2 mm).

CONCLUSIONS

Investigators with diverse backgrounds in segmentation and varying experience with slice images achieved pelvic bone segmentations with landmark measurements of mostly high agreement in a setup with high realism. In contrast, high variability was observed in the segmentation of the coccyx. In general, interobserver agreement was high, but due to measurement inaccuracies, landmark-based approaches cannot conclusively show that segmentation accuracy is within a clinically tolerable range of 2 mm for the pelvis. If the segmentation is performed by a very inexperienced user, the result should be reviewed critically by the clinician in charge.

Objective comparison of commonly used computed tomography body composition analysis software

OBJECTIVES

Sarcopenia is defined as an age-related, involuntary loss of skeletal muscle mass and strength. This condition is increasingly gaining clinical attention, as it has proved a predictor of complications and unfavorable outcomes in several diseases. For analysis of body composition on computed tomography images, several different software packages are used. Extensive research is being conducted globally to establish general cutoff values for different patient groups by combining the results of different studies with meta-analysis. Therefore, it is important that the measurements are independent of the software used. However, clinical software comparisons suggest there are differences between analysis packages, which would complicate establishment of cutoff values. For this study, we compared the eight most used analysis software programs in an objective manner, using a phantom image, to assess if their results can be readily compared.

METHODS

Eight software packages (sliceOmatic, OsiriX, ImageJ/Fiji, Mimics, CoreSlicer, SarcoMeas, 3D Slicer, and Aquarius iNtuition) were objectively evaluated, by performing measurements in a standardized synthetic image, containing fixed muscle and fat compartments with homogeneous radiodensities. For all programs, the measured areas and radiodensities of the regions of interest were assessed.

RESULTS

For sliceOmatic, OsiriX, ImageJ/Fiji, Mimics, CoreSlicer, SarcoMeas, and 3D Slicer, identical results were found, all reporting correct values for muscle and fat areas as well as correct radiodensity values, whereas values reported by Aquarius iNtuition deviated ≤ 5% for area measurements and had slight variation in radiodensity measurements.

CONCLUSIONS

Seven of eight software packages (sliceOmatic, OsiriX, ImageJ/Fiji, Mimics, CoreSlicer, SarcoMeas, and 3D Slicer) perform identically, so their results can be readily compared and combined when assessing body composition in computed tomography images. Area measurements acquired with Aquarius iNtuition may differ slightly (≤ 5%) from the other packages.

A perspective on muscle phenotyping in musculoskeletal research

Musculoskeletal research should synergistically investigate bone and muscle to inform approaches for maintaining mobility and to avoid bone fractures. The relationship between sarcopenia and osteoporosis, integrated in the term 'osteosarcopenia', is underscored by the close association shown between these two conditions in many studies, whereby one entity emerges as a predictor of the other. In a recent workshop of Working Group (WG) 2 of the EU Cooperation in Science and Technology (COST) Action 'Genomics of MusculoSkeletal traits Translational Network' (GEMSTONE) consortium (CA18139), muscle characterization was highlighted as being important, but currently under-recognized in the musculoskeletal field. Here, we summarize the opinions of the Consortium and research questions around translational and clinical musculoskeletal research, discussing muscle phenotyping in human experimental research and in two animal models: zebrafish and mouse.

Sarcopenia assessments as predictors of overall survival in patients with metastatic renal cell carcinoma

BACKGROUND

Sarcopenia represents an important prognostic marker in tumor patients. However, measurement methods and threshold values are not uniformly defined. The aim of this study is therefore to determine the prognostic value of current definitions of sarcopenia in patients with metastatic renal cell carcinoma treated with tyrosine-kinase-inhibitors (TKIs).

METHODS

In 93 patients with metastatic renal cell carcinoma, sarcopenia was assessed based on manually assisted software measurements of sarcopenia indices based on different muscle areas. Whole muscle area and psoas muscle area at L3 were estimated and adjusted to patient's height in routine CT imaging before the start of first-line TKI therapy. The correlation of different sarcopenia definitions to overall survival was investigated in a univariate analysis as well as in a multivariate analysis.

RESULTS

The mean patients' age at inclusion was 65.8 years (21-86 years). Median survival was 12.3 months (IQR: 5.7-29.8 months), and mean survival was 18.8 months (SD: 17.2 months). As the definitions of sarcopenia differ considerably, 7.6% to 96.7% of the patients were classified as sarcopenic. In univariate analysis, sarcopenia was significantly associated with overall survival. Multivariate analysis, taking into account the Memorial Sloan Kettering Cancer Center risk score, revealed that some sarcopenia-indices are additional and independent prognostic markers. The risk of death was approximately doubled in sarcopenic patients.

CONCLUSIONS

Sarcopenia is an important prognostic factor in patients with metastatic renal cell carcinoma treated with TKIs. Multivariate analysis demonstrates a doubling of the risk of death in sarcopenic patients. The assessment of sarcopenia can be performed by the analysis of routine staging imaging using indices of the total muscle area or the psoas muscle area.

Intermuscular adipose tissue in Type 2 diabetes mellitus: Non-invasive quantitative imaging and clinical implications

Intermuscular adipose tissue (IMAT) is an ectopic fat depot found beneath the fascia and within the muscles. IMAT modulates muscle insulin sensitivity and triggers local and systemic chronic low-grade inflammation by producing cytokines and chemokines, which underlie the pathogenesis of Type 2 diabetes mellitus (T2DM). Imaging techniques have been increasingly used to non-invasively quantify IMAT in patients with diabetes in research and healthcare settings. In this study, we systematically reviewed the cell of origin and definition of IMAT, and the use of quantitative and functional imaging technology pertinent to the etiology, risk factors, lifestyle modification, and therapeutic treatment of diabetes. The purpose of this article is to provide important insight into the current understanding of IMAT and future prospects of targeting IMAT for T2DM control.