Impact of Body Composition During Neoadjuvant Chemoradiotherapy on Complications, Survival and Tumor Response in Patients With Locally Advanced Rectal Cancer

Preoperative visceral fat area predicts intraoperative adverse events during lymphadenectomy in laparoscopic gastrectomy for gastric cancer: a post hoc analysis

BACKGROUND

Visceral obesity has been increasingly recognized as a potential risk factor for surgical complications in gastric cancer surgery, yet its impact on lymphadenectomy during laparoscopic gastrectomy remains undefined. This study aimed to investigate the influence of visceral fat area (VFA) on intraoperative adverse events (iAEs) during lymphadenectomy in laparoscopic gastrectomy.

METHODS

A post hoc analysis was performed using data from two previous prospective studies ([NCT02327481] and [NCT01609309]). The patients were divided into high and low VFA groups based on preoperative computed tomography images at the umbilical level. All iAEs were reviewed from the surgical videos and graded using ClassIntra. The factors influencing iAEs were identified, and predictive models for iAEs were constructed.

RESULTS

This study included 490 patients, with 244 and 246 patients in the high and low VFA groups, respectively. Restricted cubic splines demonstrated a positive linear association between VFA and iAEs. Compared with the low VFA group, the high VFA group exhibited a significantly higher incidence of iAEs (29% vs. 12%, p < 0.001), primarily in the infrapyloric (9.0% vs. 2.0%) and suprapancreatic (23.4% vs. 9.3%) regions and higher rates of ClassIntra I-III. Multivariate logistic regression identified high VFA as an independent risk factor for iAEs (hazard ratio [HR] 2.16, 95% confidence interval [CI]: 1.22 - 3.83). Based on the VFA, nomograms were developed to predict iAEs (training area under the curve [AUC] 0.722, validation AUC 0.730). Meanwhile, a web-based calculator was developed to facilitate clinical application.

CONCLUSIONS

High preoperative VFA is independently correlated with iAEs after laparoscopic gastrectomy for gastric cancer. Nomograms based on VFA showed potential in predicting iAEs, helping identify high-risk patients early and facilitating tailored perioperative management.

Sarcopenia as a Prognostic Factor for the Outcomes of Surgical Treatment of Colorectal Carcinoma

Background/Objectives: Sarcopenia, defined as the progressive loss of muscle mass and function, is increasingly associated with worse outcomes in the surgical treatment of colorectal cancer (CRC). This paper focuses on analyzing the impact of sarcopenia as a prognostic factor on postoperative outcomes in CRC patients. The aim of the study is to identify the main factors influencing postoperative results. This will be accomplished via bibliometric analysis and highlighting the significance of muscle condition in the preoperative assessment of patients. Methods: The methodological approach involves analyzing bibliographic data from relevant scientific databases focused on sarcopenia and oncological surgery. The study employs a quantitative analysis of citations and collaborations among authors and institutions. The focus will be on research publications from 2013, when we first identified references to sarcopenia in the examined context. Results: The results show that sarcopenia significantly increases the risk of postoperative morbidity and mortality in CRC patients. Network analysis and keyword mapping reveal dominant research topics such as muscle condition, mortality, and postoperative complications. Meanwhile, we identify the need for standardized diagnostic methods for sarcopenia and their integration into clinical practice to improve predictive models and clinical approaches. Conclusions: These findings underscore the importance of interdisciplinary collaboration, preoperative assessment of muscle condition, and the implementation of standardized approaches to improve clinical outcomes for patients.

A Scoping Review of the Implications and Applications of Body Composition Assessment in Locally Advanced and Locally Recurrent Rectal Cancer

Background: A strong body of evidence exists demonstrating deleterious relationships between abnormal body composition (BC) and outcomes in non-complex colorectal cancer. Complex rectal cancer (RC) includes locally advanced and locally recurrent tumours. This scoping review aims to summarise the current evidence examining BC in complex RC. Methods: A literature search was performed on Ovid MEDLINE, EMBASE, and Cochrane databases. Original studies examining BC in adult patients with complex RC were included. Two authors undertook screening and full-text reviews. Results: Thirty-five studies were included. Muscle quantity was the most commonly studied BC metric, with sarcopenia appearing to predict mortality, recurrence, neoadjuvant therapy outcomes, and postoperative complications. In particular, 10 studies examined relationships between BC and neoadjuvant therapy response, with six showing a significant association with sarcopenia. Only one study examined interventions for improving BC in patients with complex RC, and only one study specifically examined patients undergoing pelvic exenteration. Marked variation was also observed in terms of how BC was quantified, both in terms of anatomical location and how cut-off values were defined. Conclusions: Sarcopenia appears to predict mortality and recurrence in complex RC. An opportunity exists for a meta-analysis examining poorer BC and neoadjuvant therapy outcomes. There is a paucity of studies examining interventions for poor BC. Further research examining BC specifically in patients undergoing pelvic exenteration surgery is also lacking. Pitfalls identified include variances in how BC is measured on computed tomography and whether external cut-off values for muscle and adipose tissue are appropriate for a particular study population.

Prognostic significance of preoperative CT-based sarcopenia in locally advanced rectal cancer: a multicenter retrospective study

OBJECTIVES

The association between preoperative CT-based sarcopenia and prognosis in locally advanced rectal cancer (LARC) remains unclear. The aim of this study was to investigate the relationship between CT-based sarcopenia and clinical outcomes in patients with LARC.

MATERIALS AND METHODS

This multicenter retrospective study analyzed 503 LARC patients who underwent radical resection in three tertiary hospitals in China from January 2018 to June 2021 and were pathologically confirmed. All patients were followed for a period of at least three years. Clinical, pathological, and imaging data were carefully collected. According to the sex-specific skeletal muscle index (SMI), patients were evaluated for the presence of CT-based sarcopenia. The SMI was obtained by measuring the cross-sectional muscle area and standardizing it by the height of different patients. The primary endpoint was post-operative overall survival (OS), and the secondary endpoint included disease-free survival (DFS), postoperative complications, prolonged length of stay (LOS), readmission, and cancer-specific survival (CSS).

RESULTS

This study included 503 patients [mean age: 61.5 ± 10.8 years; 353 male (70.2%)], who were divided into the non-sarcopenic group (375 patients, 74.5%) and the sarcopenic group (128 patients, 25.5%). Over a mean follow-up period of 47 months (range 4-73), a total of 108 (21.4%) deaths and 162 (32.2%) combined endpoints, including recurrence or metastasis, were observed. Multivariate Cox regression analysis revealed that CT-based sarcopenia (hazard ratio [HR], 2.41; 95% confidence interval [CI], 1.49 ~ 3.87; P < 0.001) was independently associated with worse OS in LARC patients over a three-year period, but was not associated with shorter DFS (HR, 1.34; 95% CI, 0.89 ~ 2.03; P = 0.163). CT-based sarcopenia was not significantly associated with postoperative complications of grade II or greater (odds ratio [OR]: 1.29, 95% CI: 0.62 ~ 2.68, P = 0.496) or prolonged LOS (OR: 1.05, 95% CI: 0.6 ~ 1.86, P = 0.853). However, sarcopenic patients showed a higher risk of readmission (OR: 5.53, 95% CI: 1.57 ~ 19.5, P = 0.008) and a significant correlation with poorer CSS (HR: 2.78, 95% CI: 1.64 ~ 4.72, P < 0.001). Kaplan-Meier analysis showed that sarcopenic LARC patients had a significantly higher cumulative hazard of OS compared to non-sarcopenic patients (P < 0.001, log-rank test). Similar patterns of association were observed in subgroup analyses (all P values for interaction > 0.05).

CONCLUSIONS

Preoperative CT-based sarcopenia is independently associated with decreased OS, CSS, and an elevated risk of readmission in patients with LARC. These findings emphasize the importance of identifying sarcopenic patients at higher risk for adverse outcomes and suggest that interventions aimed at improving physical strength and endurance may play a critical role in informing treatment strategies and guiding clinical decisions.

Sarcopenic obesity predicts short- and long-term outcomes after neoadjuvant chemotherapy and surgery for gastric cancer

BACKGROUND

Sarcopenic obesity (SO) affects outcomes in various malignancies. However, its clinical significance in patients undergoing neoadjuvant chemotherapy (NAC) for locally advanced gastric cancer (LAGC) remains unclear. This study investigated the impact of pre- and post-NAC SO on postoperative morbidity and survival.

METHODS

Data from 207 patients with LAGC, who underwent NAC followed by radical gastrectomy between January 2010 and October 2019, were reviewed. Skeletal muscle mass and visceral fat area were measured pre- and post-NAC using computed tomography to define sarcopenia and obesity, the coexistence of which was defined as SO.

RESULTS

Among the patients, 52 (25.1%) and 38 (18.4%) developed SO before and after NAC, respectively. Both pre- (34.6%) and post- (47.4%) NAC SO were associated with the highest postoperative morbidity rates; however, only post-NAC SO was an independent risk factor for postoperative morbidity [hazard ratio (HR) = 9.550, 95% confidence interval (CI) = 2.818-32.369; P < .001]. Pre-NAC SO was independently associated with poorer 3-year overall [46.2% vs. 61.3%; HR = 1.258 (95% CI = 1.023-1.547); P = .049] and recurrence-free [39.3% vs. 55.4%; HR 1.285 (95% CI 1.045-1.579); P = .017] survival.

CONCLUSIONS

Pre-NAC SO was an independent prognostic factor in patients with LAGC undergoing NAC; post-NAC SO independently predicted postoperative morbidity.

A Cross-Sectional Validation of Horos and CoreSlicer Software Programs for Body Composition Analysis in Abdominal Computed Tomography Scans in Colorectal Cancer Patients

BACKGROUND

Body composition assessment using computed tomography (CT) scans may be hampered by software costs. To facilitate its implementation in resource-limited settings, two open-source segmentation programs (Horos and CoreSlicer) were transversally validated in colorectal cancer patients.

METHODS

Contrast-enhanced abdominal CT scans were analyzed following the Alberta protocol. The Cross-Sectional Area (CSA) and intensities of skeletal muscle tissue (MT), subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and intramuscular adipose tissue (IMAT) were measured. The Skeletal Muscle Index (SMI) was calculated. Cutoff points were applied to the SMI, MT intensity, and VAT CSA to define muscle atrophy, myosteatosis, and abdominal obesity. The inter-software agreement was evaluated using different statistical tools.

RESULTS

A total of 68 participants were measured. The MT CSA and SMI displayed no differences. The MT CSA agreement was excellent, and both programs provided equal muscle atrophy prevalences. CoreSlicer underestimated the MT intensity, with a non-significant myosteatosis prevalence increase (+5.88% and +8.82%) using two different operative definitions. CoreSlicer overestimated the CSA and intensity in both VAT and SAT, with a non-significant increase (+2.94%) in the abdominal obesity prevalence.

CONCLUSIONS

Both software programs were feasible tools in the study group. The MT CSA showed great inter-software agreement and no muscle atrophy misdiagnosis. Segmentation differences in the MT intensity and VAT CSA caused limited diagnostic misclassification in the study sample.

Post-diagnosis adiposity and colorectal cancer prognosis: A Global Cancer Update Programme (CUP Global) systematic literature review and meta-analysis

The adiposity influence on colorectal cancer prognosis remains poorly characterised. We performed a systematic review and meta-analysis on post-diagnosis adiposity measures (body mass index [BMI], waist circumference, waist-to-hip ratio, weight) or their changes and colorectal cancer outcomes. PubMed and Embase were searched through 28 February 2022. Random-effects meta-analyses were conducted when at least three studies had sufficient information. The quality of evidence was interpreted and graded by the Global Cancer Update Programme (CUP Global) independent Expert Committee on Cancer Survivorship and Expert Panel. We reviewed 124 observational studies (85 publications). Meta-analyses were possible for BMI and all-cause mortality, colorectal cancer-specific mortality, and cancer recurrence/disease-free survival. Non-linear meta-analysis indicated a reverse J-shaped association between BMI and colorectal cancer outcomes (nadir at BMI 28 kg/m2). The highest risk, relative to the nadir, was observed at both ends of the BMI distribution (18 and 38 kg/m2), namely 60% and 23% higher risk for all-cause mortality; 95% and 26% for colorectal cancer-specific mortality; and 37% and 24% for cancer recurrence/disease-free survival, respectively. The higher risk with low BMI was attenuated in secondary analyses of RCTs (compared to cohort studies), among studies with longer follow-up, and in women suggesting potential methodological limitations and/or altered physiological state. Descriptively synthesised studies on other adiposity-outcome associations of interest were limited in number and methodological quality. All the associations were graded as limited (likelihood of causality: no conclusion) due to potential methodological limitations (reverse causation, confounding, selection bias). Additional well-designed observational studies and interventional trials are needed to provide further clarification.

Different impacts of adipose tissue dynamics on prognosis in patients with resectable locally advanced rectal cancer treated with and without neoadjuvant treatment

Background

Body composition is recognized to be associated with clinical outcomes in patients with locally advanced rectal cancer (LARC). This study aimed to determine the prognostic role of regional adipose tissue distribution in patients with resectable LARC treated with or without neoadjuvant chemoradiotherapy (nCRT).

Methods

This retrospective study included 281 consecutive patients who underwent radical surgery for LARC with or without preoperative nCRT between 2013 and 2019. Patients underwent contrast-enhanced CT scans before nCRT and before surgery. Visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue (aSAT), and gluteal subcutaneous adipose tissue (gSAT) were quantified on the CT images. The association of adipose tissue distribution with progression-free survival (PFS) was analyzed using Cox proportional hazards analysis.

Results

A total of 102 nCRT-treated and 179 primarily resected patients were included. During a median follow-up period of 24 months, 74 (26.3%) patients experienced local recurrence or metastasis. Multivariable analysis showed that VAT was associated with PFS in all patients (hazard ratio [HR] 1.28, 95% confidence interval [CI] 1.04-1.57; P = 0.021). This association was only maintained in primarily resected patients (HR 1.31, 95% CI 1.02-1.69; P = 0.037). For patients receiving preoperative nCRT, VAT was not significantly associated with PFS, while the dynamic change in gSAT (ΔgSAT) between nCRT and surgery was associated with PFS (HR 0.43, 95%CI 0.27-0.69, P = 0.001).

Conclusion

Visceral obesity is an adverse prognostic factor in patients with resectable LARC treated by primary resection, while increased gluteal subcutaneous adiposity during preoperative nCRT may indicate favorable clinical outcomes.

Artificial intelligence measured 3D body composition to predict pathological response in rectal cancer patients

BACKGROUND

The treatment of locally advanced rectal cancer (LARC) is moving towards total neoadjuvant therapy and potential organ preservation. Of particular interest are predictors of pathological complete response (pCR) that can guide personalized treatment. There are currently no clinical biomarkers which can accurately predict neoadjuvant therapy (NAT) response but body composition (BC) measures present as an emerging contender. The primary aim of the study was to determine if artificial intelligence (AI) derived body composition variables can predict pCR in patients with LARC.

METHODS

LARC patients who underwent NAT followed by surgery from 2012 to 2023 were identified from the Australian Comprehensive Cancer Outcomes and Research Database registry (ACCORD). A validated in-house pre-trained 3D AI model was used to measure body composition via computed tomography images of the entire Lumbar-3 vertebral level to produce a volumetric measurement of visceral fat (VF), subcutaneous fat (SCF) and skeletal muscle (SM). Multivariate analysis between patient body composition and histological outcomes was performed.

RESULTS

Of 214 LARC patients treated with NAT, 22.4% of patients achieved pCR. SM volume (P = 0.015) and age (P = 0.03) were positively associated with pCR in both male and female patients. SCF volume was associated with decreased likelihood of pCR (P = 0.059).

CONCLUSION

This is the first study in the literature utilizing AI-measured 3D Body composition in LARC patients to assess their impact on pathological response. SM volume and age were positive predictors of pCR disease in both male and female patients following NAT for LARC. Future studies investigating the impact of body composition on clinical outcomes and patients on other neoadjuvant regimens such as TNT are potential avenues for further research.

Impact of body composition parameters on radiation therapy compliance in locally advanced rectal cancer: A retrospective observational analysis

Background

The impact of body composition and sarcopenia in locally advanced rectal cancer (LARC) is still unclear, even several studies have been published on this issue. Our study aims to analyze the impact of sarcopenia on neoadjuvant chemoradiotherapy (nCRT) tolerance and survival outcomes.

Methods

This is a retrospective, monocentric study where LARC patients treated between 2010 and 2020 were enrolled. A single slice, from the pre-therapy simulation computed tomography (CT) scan, was used to perform the body composition analysis with dedicated software. The primary endpoint was the impact of body composition on radiotherapy (RT) interruption secondarily on overall survival (OS), disease-free survival (DFS), and local control (LC).

Results

The study included 628 LARC patients (40.9 % female, mean age 63.4 years): 24 % had low skeletal muscle index (SMI), 30 % had low muscle density (MD) and 17 (10.3 % of obese) were sarcopenic obese. Higher BMI (OR 2.38, 95 % CI 1.36-4.01) and lower SMI (0.73, 95 % CI 0.55-0.94) resulted as independent predictors of RT interruption. Sarcopenic obesity (HR 2.83, 95 % CI 1.24-6.45) was related to worse OS, while MD (0.96, 95 % CI 0.93-0.98), and higher SMI (0.97, 95 % CI 0.95-0.99) were related to better OS; a lower MD remained also associated even in adjusted multivariable analysis (0.96, 95 % CI0.93-0.98). Moreover, higher visceral adipose tissue (VAT) resulted associated with worse DFS (1.02, 95 % CI 1.01-1.03), while higher SMI was related to better Local Control (0.96, 95 % CI 0.93-0.99).

Conclusions

Body composition analysis, particularly of muscle and fat masses, may be a useful tool for better management of LARC patients undergoing RT. Increased collaboration between radiation oncologists and clinical nutritionists is advisable, to enable early nutritional support of LARC.

Identification of Differences in Body Composition Measures Using 3D-Derived Artificial Intelligence from Multiple CT Scans across the L3 Vertebra Compared to a Single Mid-Point L3 CT Scan

Purpose

Body composition analysis in colorectal cancer (CRC) typically utilises a single 2D-abdominal axial CT slice taken at the mid-L3 level. The use of artificial intelligence (AI) allows for analysis of the entire L3 vertebra (non-mid-L3 and mid-L3). The goal of this study was to determine if the use of an AI approach offered any additional information on capturing body composition measures.

Methods

A total of 2203 axial CT slices of the entire L3 level (4-46 slices were available per patient) were retrospectively collected from 203 CRC patients treated at Western Health, Melbourne (97 males; 47.8%). A pretrained artificial intelligence (AI) model was used to segment muscle, visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) on these slices. The difference in body composition measures between mid-L3 and non-mid-L3 scans was compared for each patient, and for males and females separately.

Results

Body composition measures derived from non-mid-L3 scans exhibited a median range of 0.85% to 6.28% (average percent difference) when compared to the use of a single mid-L3 scan. Significant variation in the VAT surface area (p = 0.02) was observed in females compared to males, whereas male patients exhibited a greater variation in SAT surface area (p < 0.001) and radiodensity (p = 0.007).

Conclusion

Significant differences in various body composition measures were observed when comparing non-mid-L3 slices to only the mid-L3 slice. Researchers should be aware that considering only the use of a single midpoint L3 CT scan slice will impact the estimate of body composition measurements.

The preoperative geriatric nutritional risk index predicts long-term prognosis in elderly locally advanced rectal cancer patients: a two-center retrospective cohort study

BACKGROUND

The objective is to explore the value of preoperative geriatric nutritional risk index (GNRI) in evaluating long-term prognosis in elderly locally advanced rectal cancer (LARC) patients who accepted neoadjuvant chemoradiotherapy (NCRT) and to compare GNRI with established nutritional markers, including prognostic nutritional index (PNI) and controlling nutritional status (CONUT) score.

METHODS

Preoperative GNRI was retrospectively assessed in 172 LARC patients aged ≥ 60 years who underwent radical resection after NCRT at two centers. Optimal cutoff value of GNRI was determined by X-tile program. The association of GNRI with clinicopathological parameters and nutritional markers was analyzed. The survival ability of markers was evaluated using time-dependent receiver-operating characteristic (ROC) curve analysis. Finally, survival analysis was performed using Kaplan-Meier and Cox regression analysis.

RESULTS

GNRI was highly correlated with nutritional markers. An optimal cutoff value for the GNRI was 96. In the time-dependent ROC curve, GNRI demonstrated a stable predictive ability for both disease-free survival (DFS) and overall survival (OS). Multivariate analysis showed that GNRI was the only nutritional marker that independently predicted DFS (HR 2.457, 95% CI 1.066-5.665, P = 0.035) and OS (HR 9.002, 95% CI 3.100-26.146, P < 0.001). As an additional benefit, GNRI was able to stratify survival in subgroups of ypTNM and tumor response.

CONCLUSION

Preoperative GNRI is a promising predictor of long-term survival for elderly LARC patients undergoing NCRT, superior to the established nutritional markers.

Development and validation of a nomogram to predict anastomotic leakage in colorectal cancer based on CT body composition

Background

Anastomotic leakage (AL) is one of the most serious postoperative complications. This study aimed to investigate the predictive value of preoperative body composition for AL in patients with colorectal cancer (CRC).

Methods

We first reviewed data from 3,681 patients who underwent radical CRC resection 2013–2021 in our hospital, and 60 patients were diagnosed with AL after surgery. We designed a nested case-control study and two controls were randomly selected for each case according to the time and position of surgery. Body composition was measured at the level of the third lumbar vertebra based on computed tomography (CT) images. The risk factors of AL were analyzed by univariate and multivariate analysis. Nomogram was built using binary regression analysis and assessed for clinical usefulness, calibration, and discrimination.

Results

In the multivariate analysis, gender, blood glucose, nutrition risk screening (NRS), skeletal muscle area (SMA) and visceral fat area (VFA) were independent risk factors for developing anastomotic leakage after surgery. The prognostic model had an area under the receiver operating characteristic curve of 0.848 (95% CI, 0.781–0.914). The calibration curve showed good consistency between the predicted and observed outcomes. Decision curve analysis indicated that patients with colorectal cancer can benefit from the prediction model.

Conclusions

The nomogram that combined with gender, blood glucose, NRS, SMA, and VFA had good predictive accuracy and reliability to AL. It may be conveniently for clinicians to predict AL preoperatively and be useful for guiding treatment decisions.