Validation of automated body composition analysis using diagnostic computed tomography imaging in patients with pancreatic cancer

Validation of an automated segmentation method for body composition analysis in colorectal cancer patients using diagnostic abdominal computed tomography images

BACKGROUND & AIMS

Several automated programs have been developed to facilitate body composition analysis of images from abdominal computed tomography (CT) scans. External validation in patients with colorectal cancer is necessary for use in research and clinical practice. Our aim was to validate an automatic method (AutoMATiCA) of segmenting CT images at the third lumbar level (L3) from patients with colorectal cancer, by comparing with manual segmentation.

METHODS

Diagnostic abdominal CT scans of consecutive patients with stage I-III colorectal cancer were analysed to measure cross-sectional areas and tissue densities of skeletal muscle and intra-muscular, visceral, and subcutaneous adipose tissue. Trained analysts performed manual segmentation of L3 CT images using SliceOmatic. Automatic segmentation was performed using AutoMATiCA, an open-source software. The Dice similarity coefficient (DSC) was calculated to assess segmentation accuracy. Agreement of automatic with manual segmentation was evaluated using intra-class correlation coefficients (ICCs) and Bland-Altman plots with limits of agreement.

RESULTS

A total of 292 scans were included, of which 62% were from male patients. The agreement of AutoMATiCA with the manual segmentation was excellent, with median DSC values ranging from 0.900 to 0.991 and ICCs above 0.95 for all segmented areas. No systematic deviations were observed in Bland-Altman plots for all segmented areas, with overall narrow limits of agreement.

CONCLUSIONS

AutoMATiCA provides an accurate segmentation of abdominal CT images from patients with colorectal cancer. Our findings support its use as a highly efficient automated tool for body composition analysis in research and potentially also in clinical practice.

Quantitative Assessment of Body Composition in Cirrhosis

Changes in body composition often accompany the progression of liver disease and seem to be an aggravating pathophysiological factor. Specifically, accelerated loss of skeletal muscle mass, lower muscle quality, and changes in body fat distribution have been shown to be associated with poor clinical outcomes. The aim of the present narrative review was to discuss the current status and relevance of commonly applied, advanced, non-invasive methods to quantify skeletal muscle mass, muscle fat infiltration-i.e., myosteatosis-and fat distribution. This review focuses in particular on Computed Tomography (CT), Dual-energy X-ray Absorptiometry (DXA), Bioelectrical Impedance Analysis (BIA), Magnetic Resonance Imaging (MRI), and Ultrasonography (US). We propose future directions to enhance the diagnostic and prognostic relevance of using these methods for quantitative body composition assessment in patients with cirrhosis.

Pancreatic cancer and sarcopenia: a narrative review of the current status

Pancreatic cancer is still a difficult disease to treat, despite recent advances in surgical techniques and chemotherapeutic drugs. Its incidence continues to rise, as does the number of older patients. Sarcopenia is defined as a progressive and generalized loss of skeletal muscle mass and strength. Sarcopenia is present in approximately 40% in patients with pancreatic cancer. Sarcopenia is primarily diagnosed through imaging, and progress is being made in the development of automated methods and artificial intelligence, as well as biomarker research. Sarcopenia has been linked to a poor prognosis in pancreatic cancer patients. However, some studies suggest that sarcopenia is not always associated with a poor prognosis, depending on the resectability of pancreatic cancer and the nature of treatment, such as surgery or chemotherapy. Recent meta-analyses have found that sarcopenia is not linked to postoperative complications. It is still debated whether there is a link between sarcopenia and drug toxicity during chemotherapy. The relationship between sarcopenia and immunity has been investigated, but the mechanism is still unknown.

Skeletal muscle estimation: A review of techniques and their applications

Quantifying skeletal muscle size is necessary to identify those at risk for conditions that increase frailty, morbidity, and mortality, as well as decrease quality of life. Although muscle strength, muscle quality, and physical performance have been suggested as important assessments in the screening, prevention, and management of sarcopenic and cachexic individuals, skeletal muscle size is still a critical objective marker. Several techniques exist for estimating skeletal muscle size; however, each technique presents with unique characteristics regarding simplicity/complexity, cost, radiation dose, accessibility, and portability that are important factors for assessors to consider before applying these modalities in practice. This narrative review presents a discussion centred on the theory and applications of current non-invasive techniques for estimating skeletal muscle size in diverse populations. Common instruments for skeletal muscle assessment include imaging techniques such as computed tomography, magnetic resonance imaging, peripheral quantitative computed tomography, dual-energy X-ray absorptiometry, and Brightness-mode ultrasound, and non-imaging techniques like bioelectrical impedance analysis and anthropometry. Skeletal muscle size can be acquired from these methods using whole-body and/or regional assessments, as well as prediction equations. Notable concerns when conducting assessments include the absence of standardised image acquisition/processing protocols and the variation in cut-off thresholds used to define low skeletal muscle size by clinicians and researchers, which could affect the accuracy and prevalence of diagnoses. Given the importance of evaluating skeletal muscle size, it is imperative practitioners are informed of each technique and their respective strengths and weaknesses.

Prognostic value of preoperative CT scan derived body composition measures in resected pancreatic cancer

BACKGROUND

It remains unclear whether preoperative body composition may affect the prognosis of pancreatic cancer patients undergoing surgery. The aim of the present study was to assess the extent to which preoperative body composition impacts on postoperative complication severity and survival in patients undergoing pancreatoduodenectomy for pancreatic ductal adenocarcinoma (PDAC).

METHODS

A retrospective cohort study was performed on consecutive patients who underwent pancreatoduodenectomy with preoperative CT scan imaging available. Body composition parameters including total abdominal muscle area (TAMA), visceral fat area (VFA), subcutaneous fat area and liver steatosis (LS) were assessed. Sarcopenic obesity was defined as a high VFA/TAMA ratio. Postoperative complication burden was evaluated with the comprehensive complication index (CCI).

RESULTS

Overall, 371 patients were included in the study. At 90 days after surgery, 80 patients (22%) experienced severe complications. The median CCI was 20.9 (IQR 0-30). At multivariate linear regression analysis, preoperative biliary drainage, ASA score ≥3, fistula risk score and sarcopenic obesity (37% increase; 95%CI 0.06-0.74; p = 0.046) were associated to an increase in CCI. Patient characteristics associated to sarcopenic obesity were older age, male gender and preoperative LS. At a median follow-up of 25 months (IQR 18-49), median disease-free survival (DFS) was 19 months (IQR 15-22). At cox-regression analysis, only pathological features were associated with DFS, while LS and other body composition measures did not show any prognostic role.

CONCLUSION

The combination of sarcopenia and visceral obesity was significantly associated with increased complication severity after pancreatoduodenectomy for cancer. Patients' body composition did not affect disease free survival after pancreatic cancer surgery.