Quantification of body composition in renal cell carcinoma patients: Comparing computed tomography and magnetic resonance imaging measurements. Issue 132 (November 2020)

• Record Type: Journal Article
• Authors: Higgins, Michelle I.; Martini, Dylan J.; Patil, Dattatraya H.; Steele, Sean; Evans, Sean; Petrinec, Benjamin P.; Psutka, Sarah P.; Sekhar, Aarti; Bilen, Mehmet Asim; Master, Viraj A.
• Is Part Of: European journal of radiology. Issue 132(2020)
• Publication Date: 2020-11
• Subjects: Computed tomography -- Magnetic resonance imaging -- Skeletal muscle area -- Adipose tissue -- Body composition -- Performance status; Medical radiology -- Periodicals; Radiology -- Periodicals; Radiologie médicale -- Périodiques; Medical radiology; Periodicals; 616.075705
• DOI: 10.1016/j.ejrad.2020.109307
• Languages: English
• ISSNs: 0720-048X

Abstract

Abstract: Purpose: Body composition measures provide valuable information for prognostication and treatment election in cancer patients. We investigated the novel use of magnetic resonance imaging (MRI) for skeletal muscle and adipose tissue cross-sectional area measurements in preoperative renal cell carcinoma (RCC) patients. Materials and methods: RCC patients with pre-operative CT and MRI abdominal imaging were identified. Semi-automatic segmentation measurement of skeletal muscle area (SMA), intramuscular fat area (IMFA), visceral fat area (VFA), subcutaneous fat area (SFA), linear measurements of psoas, paraspinal muscles were performed. Pearson correlation coefficients, Bland-Altman plot analyses were done. Multivariable regression analysis examined the relationship between patient characteristics and skeletal muscle. Results: Image analysis was performed on 58 RCC patients with preoperative CT and MRI imaging. For segmentation measures, r = 0.99, 0.99, 0.99, and 0.98 for SMA, IMFA, VFA, SFA, respectively, and 0.96 for linear measures of skeletal muscle. Bland-Altman analysis revealed a bias toward larger CT value for SMA (1.35 %), linear muscle measures (2.79 %), and SFA (10.34 %), and toward larger MRI values for IMFA (0.75 %) and VFA (5.81 %). ECOG ≥ 1 was associated with lower skeletal muscle than ECOG 0 for all measurements. Conclusions: Strong correlation of CT and MRI cross sectional measurements of skeletal muscle and adipose tissues supports the use of axial MRI images for comprehensive measurement of body composition. This has widespread implications for body composition research and cancer patient care.