Abdominal adipose tissue radiodensity is associated with survival after colorectal cancer

The role of Adiponectin and Leptin in Colorectal Cancer and Adenoma: a systematic review and meta-analysis

BACKGROUND

Colorectal cancer ranks as the third most frequently diagnosed cancer globally. Adipokines, including adiponectin and leptin, are believed to play a vital role in the development and progression of tumors. This study aimed to clarify the association between circulating adiponectin and leptin concentrations and the risk of colorectal cancer and adenoma.

METHODS

A detailed literature review was conducted in different databases, including Google Scholar, Web of Science, Scopus, and PubMed. Articles measuring serum concentrations of adiponectin and leptin in colorectal adenoma or cancer patients were analyzed. Pooled odds ratios (ORs) and their related 95% confidence intervals (CIs) were estimated through a random-effects meta-analysis.

RESULTS

In total, 30 articles were analyzed. According to the meta-analysis, higher adiponectin concentrations were inversely linked to a reduced CRC risk (OR: 0.85, 95% CI: 0.74-0.96), particularly in men. However, no notable connection was detected between higher leptin concentrations and risk of CRC (OR: 1.12, 95% CI: 0.96-1.31). In subgroup analyses, BMI adjustment reinforced the negative association between higher adiponectin levels and risk of CRC, while insulin adjustment yielded non-significant results. Additionally, higher leptin levels revealed a meaningful relationship with colorectal adenoma risk (OR: 1.39, 95% CI: 1.06-1.84), whereas higher levels of adiponectin were not significantly linked to adenoma (OR: 0.79, 95% CI: 0.46-1.36).

CONCLUSION

According to this meta-analysis, elevated adiponectin concentrations may play a protective role against CRC, while leptin could potentially contribute to an elevated colorectal adenoma risk. Further studies are required to explore the potential mechanisms underlying adipokine-mediated colorectal carcinogenesis.

Body composition metrics as a determinant of trastuzumab deruxtecan related toxicity and response

Body composition is an important predictor in cancer patients, with skeletal muscle loss and high adiposity associated with poorer prognosis. This study evaluated how body composition affects treatment efficacy in 48 women with metastatic breast cancer receiving trastuzumab deruxtecan. Using computed tomography, skeletal muscle, visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) were assessed within 60 days before initiating treatment. High SAT and VAT areas were significantly associated with a higher likelihood of dose reductions (Odds Ratio [OR] = 5.34, p = .032 and OR = 5.52, p = 0.032, respectively). Higher SAT areas correlated with a lower objective response rate (OR = 0.22, p = 0.047). Medium SAT and low/medium VAT densities increased the risk of dose reductions. A body mass index over 25 kg/m2 was linked to higher dose reductions (OR = 4.97, p = 0.016). These findings emphasize the need for personalized treatment strategies based on body composition.

Predicting 3-year all-cause mortality in rectal cancer patients based on body composition and machine learning

Objectives

The composition of abdominal adipose tissue and muscle mass has been strongly correlated with the prognosis of rectal cancer. This study aimed to develop and validate a machine learning (ML) predictive model for 3-year all-cause mortality after laparoscopic total mesorectal excision (LaTME).

Methods

Patients who underwent LaTME surgery between January 2018 and December 2020 were included and randomly divided into training and validation cohorts. Preoperative computed tomography (CT) image parameters and clinical characteristics were collected to establish seven ML models for predicting 3-year survival post-LaTME. The optimal model was determined based on the area under the receiver operating characteristic curve (AUROC). The SHAPley Additive exPlanations (SHAP) values were utilized to interpret the optimal model.

Results

A total of 186 patients were recruited and divided into a training cohort (70%, n = 131) and a validation cohort (30%, n = 55). In the training cohort, the AUROCs of the seven ML models ranged from 0.894 to 0.949. In the validation cohort, the AUROCs ranged from 0.727 to 0.911, with the XGBoost model demonstrating the best predictive performance: AUROC = 0.911. SHAP values revealed that subcutaneous adipose tissue index (SAI), visceral adipose tissue index (VAI), skeletal muscle density (SMD), visceral-to-subcutaneous adipose tissue ratio (VSR), and subcutaneous adipose tissue density (SAD) were the five most important variables influencing all-cause mortality post-LaTME.

Conclusion

By integrating body composition, multiple ML predictive models were developed and validated for predicting all-cause mortality after rectal cancer surgery, with the XGBoost model exhibiting the best performance.

Subcutaneous adipose tissue radiodensity as a predictor of poor prognosis in advanced biliary tract cancer

BACKGROUND

High subcutaneous adipose tissue radiodensity (SATr), an indirect surrogate marker of adipose tissue quality, was associated with poor prognosis in various cancers. The present study aimed to assess the association of SATr with survival outcomes in patients with advanced biliary tract cancer (BTC).

METHODS

This retrospective, single-center study included patients with unresectable or recurrent BTC who underwent chemotherapy/chemoradiotherapy. Overall survival (OS) and progression-free survival (PFS) were assessed using the log-rank test and the Cox proportional hazards model according to the SATr status.

RESULTS

The study cohort included 234 patients, including 38 and 196 patients with high and non-high SATr, respectively. The median OS durations were 10.5 and 17.4 months (HR = 1.72, 95% CI: 1.19-2.49, p < .01) and the median PFS durations were 4.9 and 8.0 months (HR = 1.52, 95% CI: 1.05-2.20, p = .03) in patients with high and non-high SATr, respectively. By multivariate analysis, high SATr, neutrophil/lymphocyte ratio >5, modified Glasgow prognostic score 1-2, and serum carcinoembryonic antigen >5.0 ng/mL were predictors for OS (HR, 1.66, 2.42, 2.00, and 1.56, respectively; p < .05). By multivariate analysis, metastatic disease status, high SATr, neutrophil/lymphocyte ratio >5, and modified Glasgow prognostic score 1-2 were independent risk factors for worse PFS (HR, 1.56, 1.56, 1.81, and 1.57, respectively; p < .05).

CONCLUSIONS

High SATr was associated with risk of tumor progression and poor prognosis in patients with advanced BTC treated by palliative chemotherapy/chemoradiotherapy.

The Association Between Body Composition, Overall Survival, Treatment Decisions, and Patient-Reported Outcomes in Metastatic Non-Small-Cell Lung Cancer

INTRODUCTION

The purpose of this study was to evaluate the association between body composition, overall survival, odds of receiving treatment, and patient-reported outcomes (PROs) in individuals living with metastatic non-small-cell lung cancer (mNSCLC).

METHODS

This retrospective analysis was conducted in newly diagnosed patients with mNSCLC who had computed-tomography (CT) scans and completed PRO questionnaires close to metastatic diagnosis date. Cox proportional hazard models and logistic regression evaluated overall survival and odds of receiving treatment, respectively. Hazard ratios (HR) and odds ratios (OR) were evaluated as the interquartile range for body composition compartments. Multiple linear regression evaluated the association between PROs and body composition. Models were adjusted for gender, age at diagnosis, smoking history, and mutation status. The survival model also included adjustment for tumor histology.

RESULTS

Our sample (n = 69) included men (52%) and women (48%), with a median age of 67.4-years, history of smoking (67%), wild-type genotype (75.4%), and a tumor histology of adenocarcinoma (68%). Greater skeletal muscle area was associated with higher physical function scores. Larger intermuscular adipose tissue area was associated with higher mortality risk (HR 2.03, 95% CI 1.32, 3.11), lower odds of receiving treatment (OR 0.76, 95% CI 0.61, 0.93), and higher fatigue. Larger subcutaneous adipose tissue area was associated with lower mortality risk (HR 0.42, 95% CI 0.22, 0.82) and higher odds of receiving treatment (OR 1.03, 95% CI 1.01, 1.06). Larger total adipose tissue area was linked with improved survival (HR 0.59, 95% CI 0.36, 0.96).

CONCLUSION

Findings support an association between different body composition compartments at mNSCLC diagnosis and survival, decisions to treat, and PROs. This work supports the use of data collected in routine CT scans and PROs to inform treatment decisions and supportive care options.

High Subcutaneous Adipose Tissue Radiodensity Predicts Poor Prognosis in Patients With Gastric Cancer

Background/Aim

Although the impact of body composition on cancer treatment outcomes of patients with cancer has been increasingly reported, it is still unclear whether the radiodensity of subcutaneous adipose tissue (SAT) on computed tomography (CT) images has a prognostic impact on patients with gastric cancer. We measured muscle and SAT profiles on CT and performed an integrated analysis with clinicopathologic factors.

Patients and Methods

We retrospectively analyzed 230 patients with gastric cancer who underwent gastrectomy between June 2016 and December 2020. SAT radiodensity (SAT-R), and skeletal muscle index (SMI) were measured in preoperative CT images. These were compared with clinicopathologic factors, overall survival (OS), and recurrence-free survival (RFS).

Results

High SAT-R was significantly associated with older age (p=0.003) and lower BMI, lymphocyte, hemoglobin, γ-GTP, cholinesterase, albumin, and triglyceride values (p<0.001, <0.001, 0.027, 0.032, <0.001, 0.001, and <0.001, respectively). In the univariate analysis, high SAT-R, and low SMI were significantly associated with poor OS (p=0.003 and <0.001) and poor RFS (p=0.014 and 0.011). In the multivariate analysis by Cox proportional hazard model, high SAT-R and low SMI were identified as independent prognostic factors for poor OS (p=0.037 and 0.007).

Conclusion

High SAT-R on preoperative CT was associated with poor OS in patients with gastric cancer after gastrectomy. SAT-R has a potential to be a novel prognostic marker for surgically treated patients with gastric cancer.

Radiodensities of Skeletal Muscle and Visceral Adipose Tissues Are Prognostic Factors in Clear-Cell Renal Cell Carcinoma

BACKGROUND

Body composition may be related to survival in patients with clear-cell renal cell carcinoma (ccRCC), but studies have not simultaneously considered adipose and muscle tissue quantity and radiodensity.

METHODS

We analyzed data from 1,022 patients with ccRCC who underwent nephrectomy between 2000 and 2020 at Memorial Sloan Kettering Cancer Center. Skeletal muscle, visceral adipose tissue, and subcutaneous adipose tissue indexes (cm2/m2) and radiodensities [Hounsfield units (HU)] were assessed from noncontrast presurgical CT scans; clinical and demographic characteristics were available from the time of surgery. HRs and confidence intervals were estimated for overall (OS) and disease-free survival (DFS) through March 2023 in multivariable models that simultaneously accounted for all body composition measures.

RESULTS

The median age of the patients was 58 years, 69% were male, and 90% were White. There were 169 OS events over 8,392 person-years and 253 DFS events over 7,753 person-years of follow-up. In adjusted analyses, poor OS was associated with lower skeletal muscle radiodensity [-10 HU, HR (95% confidence interval), 1.37 (1.05-1.77)] and greater visceral adipose tissue radiodensity [+10 HU, 1.66 (1.06-2.59)], with similar findings for DFS. Poor survival was also associated with greater visceral adipose tissue index [+40 cm2/m2, OS: 1.32 (0.97, 1.79); DFS: 1.33 (1.04, 1.71)]. Associations with skeletal muscle radiodensity were limited to patients with stage 1/2 disease.

CONCLUSIONS

Radiodensities of skeletal muscle and visceral adipose tissues may be novel presurgical prognostic factors for patients with ccRCC.

IMPACT

The findings underscore the importance of evaluating the full range of body composition features simultaneously in multivariable models.

The association of body composition phenotypes before chemotherapy with epithelial ovarian cancer mortality

BACKGROUND

The association of body composition with epithelial ovarian carcinoma (EOC) mortality is poorly understood. To date, evidence suggests that high adiposity is associated with decreased mortality (an obesity paradox), but the impact of muscle on this association has not been investigated. Herein, we define associations of muscle and adiposity joint-exposure body composition phenotypes with EOC mortality.

METHODS

Body composition from 500 women in the Body Composition and Epithelial Ovarian Cancer Survival Study was dichotomized as normal or low skeletal muscle index (SMI), a proxy for sarcopenia, and high or low adiposity. Four phenotypes were classified as fit (normal SMI and low adiposity; reference; 16.2%), overweight or obese (normal SMI and high adiposity; 51.2%), sarcopenia and overweight or obese (low SMI and high adiposity; 15.6%), and sarcopenia or cachexia (low SMI and low adiposity; 17%). We used multivariable Cox models to estimate associations of each phenotype with mortality for EOC overall and high-grade serous ovarian carcinoma (HGSOC).

RESULTS

Overweight or obesity was associated with up to 51% and 104% increased mortality in EOC and HGSOC [Hazard Ratio (HR)] = 1.51, 95% CI = 1.05 to 2.19 and HR = 2.04, 95% CI = 1.29 to 3.21). Sarcopenia and overweight or obesity was associated with up to 66% and 67% increased mortality in EOC and HGSOC (HR = 1.66, 95% CI = 1.13 to 2.45 and HR = 1.67, 95% CI = 1.05 to 2.68). Sarcopenia or cachexia was associated with up to 73% and 109% increased mortality in EOC and HGSOC (HR = 1.73, 95% CI = 1.14 to 2.63 and HR = 2.09, 95% CI = 1.25 to 3.50).

CONCLUSIONS

Overweight or obesity, sarcopenia and overweight or obesity, and sarcopenia or cachexia phenotypes were each associated with increased mortality in EOC and HGSOC. Exercise and dietary interventions could be leveraged as ancillary treatment strategies for improving outcomes in the most fatal gynecological malignancy with no previously established modifiable prognostic factors.

Age-adjusted Charlson comorbidity index and its association with body composition and overall survival in patients with colorectal cancer

OBJECTIVE

To examine the relationship between the age-adjusted Charlson comorbidity index (A-CCI) with body composition and overall survival in patients newly diagnosed with colorectal cancer (CRC).

RESEARCH METHODS AND PROCEDURES

In this cohort study, patients (≥ 18 years old) with CRC were followed for 36 months. Computed tomography images of the third lumbar were analyzed to determine body composition, including skeletal muscle area (SMA), skeletal muscle index (SMI), skeletal muscle radiodensity (SMD), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT). Phenotypes based on comorbidity burden assessed by A-CCI and body composition parameters were established.

RESULTS

A total of 436 participants were included, 50% male, with a mean age of 61 ± 13.2 years. Approximately half of the patients (50.4%) had no comorbidity, and the A-CCI median score was 4 (interquartile range: 3-6). A higher A-CCI score was a risk factor for 36-month mortality (HR = 3.59, 95% CI = 2.17-5.95). Low SMA and low SMD were associated with a higher A-CCI. All abnormal phenotypes (high A-CCI and low SMA; high A-CCI and low SMD; high A-CCI and high VAT) were independently associated with higher 36-month mortality hazard (adjusted HR 5.12, 95% CI 2.73-9.57; adjusted HR 4.58, 95% CI 2.37-8.85; and adjusted HR 2.36, 95% CI 1.07-5.22, respectively).

CONCLUSION

The coexistence of comorbidity burden and abnormal body composition phenotypes, such as alterations in muscle or fat compartments, may pose an additional risk of mortality in patients newly diagnosed with CRC. Early assessment and management of these phenotypes could be crucial in optimizing outcomes in such patients.

Phantomless calibration of CT scans for hip fracture risk prediction in silico: Comparison with phantom-based calibration

Finite element models built from quantitative computed tomography images rely on element-wise mapping of material properties starting from Hounsfield Units (HU), which can be converted into mineral densities upon calibration. While calibration is preferably carried out by scanning a phantom with known-density components, conducting phantom-based calibration may not always be possible. In such cases, a phantomless procedure, where the scanned subject's tissues are used as a phantom, is an interesting alternative. The aim of this study was to compare a phantom-based and a phantomless calibration method on 41 postmenopausal women. The proposed phantomless calibration utilized air, adipose, and muscle tissues, with reference equivalent mineral density values of -797, -95, and 38 mg/cm3, extracted from a previously performed phantom-based calibration. A 9-slice volume of interest (VOI) centred between the femoral head and knee rotation centres was chosen. Reference HU values for air, adipose, and muscle tissues were extracted by identifying HU distribution peaks within the VOI, and patient-specific calibration was performed using linear regression. Comparison of FE models calibrated with the two methods showed average relative differences of 1.99% for Young's modulus1.30% for tensile and 1.34% for compressive principal strains. Excellent correlations (R2 > 0.99) were identified for superficial maximum tensile and minimum compressive strains. Maximum normalised root mean square relative error (RMSRE) values settled at 4.02% for Young's modulus, 2.99% for tensile, and 3.22% for compressive principal strains, respectively. The good agreement found between the two methods supports the adoption of the proposed methodology when phantomless calibration is needed.

Obesity and early-onset colorectal cancer risk: emerging clinical evidence and biological mechanisms

Early-onset colorectal cancer (EOCRC) is defined as diagnosed at younger than 50 years of age and indicates a health burden globally. Patients with EOCRC have distinct risk factors, clinical characteristics, and molecular pathogenesis compared with older patients with CRC. Further investigations have identified different roles of obesity between EOCRC and late-onset colorectal cancer (LOCRC). Most studies have focused on the clinical characteristics of obesity in EOCRC, therefore, the mechanism involved in the association between obesity and EOCRC remains inconclusive. This review further states that obesity affects the carcinogenesis of EOCRC as well as its development and progression, which may lead to obesity-related metabolic syndrome, intestinal dysbacteriosis, and intestinal inflammation.

Development and validation of machine learning models and nomograms for predicting the surgical difficulty of laparoscopic resection in rectal cancer

BACKGROUND

The objective of this study is to develop and validate a machine learning (ML) prediction model for the assessment of laparoscopic total mesorectal excision (LaTME) surgery difficulty, as well as to identify independent risk factors that influence surgical difficulty. Establishing a nomogram aims to assist clinical practitioners in formulating more effective surgical plans before the procedure.

METHODS

This study included 186 patients with rectal cancer who underwent LaTME from January 2018 to December 2020. They were divided into a training cohort (n = 131) versus a validation cohort (n = 55). The difficulty of LaTME was defined based on Escal's et al. scoring criteria with modifications. We utilized Lasso regression to screen the preoperative clinical characteristic variables and intraoperative information most relevant to surgical difficulty for the development and validation of four ML models: logistic regression (LR), support vector machine (SVM), random forest (RF), and decision tree (DT). The performance of the model was assessed based on the area under the receiver operating characteristic curve(AUC), sensitivity, specificity, and accuracy. Logistic regression-based column-line plots were created to visualize the predictive model. Consistency statistics (C-statistic) and calibration curves were used to discriminate and calibrate the nomogram, respectively.

RESULTS

In the validation cohort, all four ML models demonstrate good performance: SVM AUC = 0.987, RF AUC = 0.953, LR AUC = 0.950, and DT AUC = 0.904. To enhance visual evaluation, a logistic regression-based nomogram has been established. Predictive factors included in the nomogram are body mass index (BMI), distance between the tumor to the dentate line ≤ 10 cm, radiodensity of visceral adipose tissue (VAT), area of subcutaneous adipose tissue (SAT), tumor diameter >3 cm, and comorbid hypertension.

CONCLUSION

In this study, four ML models based on intraoperative and preoperative risk factors and a nomogram based on logistic regression may be of help to surgeons in evaluating the surgical difficulty before operation and adopting appropriate responses and surgical protocols.

Could nutrition status predict fatigue one week before in patients with nasopharynx cancer undergoing radiotherapy?

BACKGROUND

Patients with nasopharyngeal carcinoma (NPC) undergoing radiotherapy experience significant fatigue, which is frequently underestimated due to the lack of objective indicators for its evaluation. This study aimed to explore the longitudinal association between fatigue and nutrition status 1 week in advance.

METHODS

From January 2021 to June 2022, a total of 105 NPC patients who received intensity-modulated radiation therapy were enrolled in the observational longitudinal study. The significant outcomes, including the Piper Fatigue Scale-12 (PFS-12), the Scored Patient-Generated Subjective Global Assessment (PG-SGA), four body composition indices, and the Hospital Anxiety and Depression Scale (HADS), were assessed weekly from pre-treatment until the completion of radiotherapy (T0-T7) to explore their relationship.

RESULTS

The trajectories of PFS-12 and all dimensions for 105 participants reached a peak during the fifth week. Sensory fatigue consistently received the highest scores (T0 = 1.60 ± 2.20, T5 = 6.15 ± 1.57), whereas behavior fatigue exhibited the fastest increase over time (T0 = 1.11 ± 1.86, T5 = 5.47 ± 1.70). Higher PG-SGA scores were found to be weakly explainable for aggravating fatigue (β = 0.02 ~ 0.04). Unlike generalized additive mixed models, marginal structural models (MSM) produced larger effect values (β = 0.12 ~ 0.21). Additionally, body composition indices showed weakly negative relationships with fatigue in MSMs one week in advance.

CONCLUSIONS

The PG-SGA may be a more accurate predictor of future-week fatigue than individual body composition indicators, particularly when HADS is controlled for as a time-dependent confounder.

Adipose tissue composition determines its computed tomography radiodensity

OBJECTIVES

Adipose tissue radiodensity in computed tomography (CT) performed before surgeries can predict surgical difficulty. Despite its clinical importance, little is known about what influences radiodensity. This study combines desorption electrospray ionization mass spectrometry imaging (DESI-MSI) and electrospray ionization (ESI) with machine learning to unveil how chemical composition of adipose tissue determines its radiodensity.

METHODS

Patients in the study underwent abdominal surgeries. Before surgery, CT radiodensity of fat near operated sites was measured. Fifty-three fat samples were collected and analyzed by DESI-MSI, ESI, and histology, and then sorted by radiodensity, demographic parameters, and adipocyte size. A non-negative matrix factorization (NMF) algorithm was developed to differentiate between high and low radiodensities.

RESULTS

No associations between radiodensity and patient age, gender, weight, height, or fat origin were found. Body mass index showed negative correlation with radiodensity. A substantial difference in chemical composition between adipose tissues of high and low radiodensities was observed. More radiodense tissues exhibited greater abundance of high molecular weight species, such as phospholipids of various types, ceramides, cholesterol esters and diglycerides, and about 70% smaller adipocyte size. Less radiodense tissue showed high abundance of short acyl-tail fatty acids.

CONCLUSIONS

This study unveils the connection between abdominal adipose tissue radiodensity and its chemical composition. Because the radiodensity of the fat around the surgical site is associated with surgical difficulty, it is important to understand how adipose tissue composition affects this parameter. We conclude that fat tissue with a higher content of various phospholipids and waxy lipids is more CT radiodense.

CLINICAL RELEVANCE STATEMENT

This study establishes the connection between the CT radiodensity of adipose tissue and its chemical composition. Clinicians may use this information for preoperative planning of surgical procedures, potentially modifying their surgical approach (for example, performing partial nephrectomy openly rather than laparoscopically).

KEY POINTS

• Adipose tissue radiodensity values in computed tomography images taken prior to the surgery can potentially predict surgery difficulty. • Fifty-three human specimens were analyzed by advanced mass spectrometry, molecular imaging, and machine learning to establish the key features that determine Hounsfield units' values of adipose tissue. • The findings of this research will enable clinicians to better prepare for surgical procedures and select operative strategies.

Association between increased Subcutaneous Adipose Tissue Radiodensity and cancer mortality: Automated computation, comparison of cancer types, gender, and scanner bias

PURPOSE

Body composition analysis using computed tomography (CT) is proposed as a predictor of cancer mortality. An association between subcutaneous adipose tissue radiodensity (SATr) and cancer-specific mortality was established, while gender effects and equipment bias were estimated.

METHODS

7,475 CT studies were selected from 17 cohorts containing CT images of untreated cancer patients who underwent follow-up for a period of 2.1-118.8 months. SATr measures were collected from published data (n = 6,718) or calculated according to CT images using a deep-learning network (n = 757). The association between SATr and mortality was ascertained for each cohort and gender using the p-value from either logistic regression or ROC analysis. The Kruskal-Wallis test was used to analyze differences between gender distributions, and automatic segmentation was evaluated using the Dice score and five-point Likert quality scale. Gender effect, scanner bias and changes in the Hounsfield unit (HU) to detect hazards were also estimated.

RESULTS

Higher SATr was associated with mortality in eight cancer types (p < 0.05). Automatic segmentation produced a score of 0.949 while the quality scale measurement was good to excellent. The extent of gender effect was 5.2 HU while the scanner bias was 10.3 HU. The minimum proposed HU change to detect a patient at risk of death was between 5.6 and 8.3 HU.

CONCLUSIONS

CT imaging provides valuable assessments of body composition as part of the staging process for several cancer types, saving both time and cost. Gender specific scales and scanner bias adjustments should be carried out to successfully implement SATr measures in clinical practice.

Body composition and cancer survival: a narrative review

Interest in understanding the relationship between body composition and cancer survival has remained strong for decades, with a number of recent systematic reviews on the topic. However, the current state of evidence is based on heterogeneous exposure definitions based on anthropometry, yielding inconsistent findings with regard to this association. Recently the field has taken an exciting direction with the application of radiological assessments to measure specific aspects of body composition, yet reconciliation of findings from these modern assessment tools with those from the historic use of anthropometric data proves challenging. In this paper, I briefly review the biological basis for a link between body composition and cancer survival and summarize the epidemiological evidence with consideration to specific exposure measures. As enthusiasm is building around novel assessments, I conclude with a discussion of issues that researchers should be aware of when interpreting results from these new modalities.

Longitudinal Dynamic in Weight Loss Impacts Clinical Outcomes for Veterans Undergoing Curative Surgery for Colorectal Cancer

Background

Definitions of malnutrition imperfectly reflect nutritional status or predict perioperative consequences. We sought to identify predictive nutritional trends by examining the effect of preoperative weight on postoperative outcomes in patients with colorectal cancer (CRC).

Methods

This retrospective review examined 148 patients with CRC treated with curative-intent surgery at the Veterans Affairs Ann Arbor Healthcare System in Michigan from January 1, 2015 to December 31, 2019. We evaluated weight dynamics of patients, starting 1 year before cancer diagnosis until 1 year after surgery. We evaluated the association of these weight dynamics with surgical outcomes. Primary outcomes observed were hospital readmission and length of stay (LOS), chemotherapy completion, and delayed recovery defined as abnormal clinical developments.

Results

There were 115 patients in the colon cancer (CC) cohort and 33 in the rectal cancer (RC) cohort. Low preoperative albumin (< 3.5 g/dL) was present in 25 patients with CC (22%) and 11 patients with RC (33%). Six-month preoperative weight loss of at least 3% occurred in 32 patients with CC (36%). Delayed recovery was observed in 35 patients with CC (30%) and 21 patients with RC (64%). Nutrition consultation rates for the CC and RC groups were 15% and 36%, respectively, before the operation; 95% and 100%, respectively, for postoperative inpatients; and 12% and 73%, respectively, for postoperative outpatients. Six-month preoperative weight loss of ≥ 3% was significantly associated with delayed recovery (P < .001) and 60-day readmissions (P = .015) but not increased LOS or chemotherapy noncompletion.

Conclusions

A ≥ 3% weight loss 6 months preceding curative surgery for CRC was associated with adverse outcomes. An intensive nutrition prehabilitation program initiated at the time of cancer diagnosis is needed and may reduce associated complications.

Fat quantification: Imaging methods and clinical applications in cancer

Recently, the study of the relationship between lipid metabolism and cancer has evolved. The characteristics of intratumoral and peritumoral fat are distinct and changeable during cancer development. Subcutaneous and visceral adipose tissue are also associated with cancer prognosis. In non-invasive imaging, fat quantification parameters such as controlled attenuation parameter, fat volume fraction, and proton density fat fraction from different imaging methods complement conventional images by providing concrete fat information. Therefore, measuring the changes of fat content for further understanding of cancer characteristics has been applied in both research and clinical settings. In this review, the authors summarize imaging advances in fat quantification and highlight their clinical applications in cancer precaution, auxiliary diagnosis and classification, therapy response monitoring, and prognosis.

Abdominal adiposity as a prognosis biomarker of clinical outcome in metastatic colorectal cancer

OBJECTIVES

Adipose tissue distribution and radiodensity are associated with prognosis in many types of cancer. However, the roles of adipose tissue distribution and radiodensity in patients with metastatic colorectal cancer (mCRC) remain unclear. The aim of this study was to assess the prognostic effect of adiposity and adipose tissue radiodensities in patients with mCRC.

METHODS

Patients with mCRC who received first-line palliative chemotherapy and had a computed tomography (CT) scan at the third lumbar vertebra (L3) level, admitted between January 2010 and December 2018, were sequentially enrolled. Body composition was assessed using CT-derived measurements. Univariate and multivariate logistic regression analyses and Kaplan-Meier curves were used to determine prognostic values.

RESULTS

The study included 237 patients. Cox analyses demonstrated that high subcutaneous adipose tissue (SAT) index was associated with a lower risk for death (hazard ratio [HR], 0.51; 95% confidence interval [CI], 0.29-0.88; Ptrend < 0.025). There was no significant association between visceral adipose tissue (VAT) index tertiles and overall survival. However, high VAT and SAT radiodensities were significantly associated with increased mortality (HR, 1.80; 95% CI, 1.12-2.89; Ptrend < 0.030 and HR, 1.85; 95% CI, 1.19-2.86; Ptrend < 0.021, respectively).

CONCLUSIONS

A higher SAT index in patients with mCRC was associated with a favorable overall survival outcome, whereas higher SAT and VAT radiodensities were associated with an increased risk for death, supporting that early nutritional intervention may improve mCRC prognosis.

Abdominal Fat Characteristics and Mortality in Rectal Cancer: A Retrospective Study

The aim of this study was to evaluate the association of adipose tissue characteristics with survival in rectal cancer patients. All consecutive patients, diagnosed with stage II-IV rectal cancer between 2010-2016 using baseline unenhanced Computed Tomography (CT), were included. Baseline total, subcutaneous and visceral adipose tissue areas (TAT, SAT, VAT) and densities (TATd, SATd, VATd) at third lumbar vertebra (L3) were retrospectively measured. The association of these tissues with cancer-specific and progression-free survival (CCS, PFS) was assessed by using competitive risk models adjusted by age, sex and stage. Among the 274 included patients (median age 70 years, 41.2% females), the protective effect of increasing adipose tissue area on survival could be due to random fluctuations (e.g., sub-distribution hazard ratio-SHR for one cm2 increase in SAT = 0.997; 95%confidence interval-CI = 0.994-1.000; p = 0.057, for CSS), while increasing density was associated with poorer survival (e.g., SHR for one Hounsfield Unit-HU increase in SATd = 1.03, 95% CI = 1.01-1.05, p = 0.002, for CSS). In models considering each adipose tissue area and respective density, the association with CSS tended to disappear for areas, while it did not change for TATd and SATd. No association was found with PFS. In conclusion, adipose tissue density influenced survival in rectal cancer patients, raising awareness on a routinely measurable variable that requires more research efforts.

Adipose tissue radiodensity and mortality among patients with nonmetastatic breast cancer

BACKGROUND & AIMS

Computed tomography (CT) scans can measure quantity and distribution of adipose tissue, which are associated with breast cancer prognosis. As a novel prognostic marker, radiodensity of adipose tissue has been examined in multiple cancer types, but never in breast cancer. Lower density indicates larger adipocytes with greater lipid content, whereas higher density can reflect inflammation, fibrosis, vascularity, or even metabolic changes; and both may impact breast cancer prognosis.

METHODS

We included 2868 nonmetastatic patients with breast cancer diagnosed between January 2005 and December 2013 at Kaiser Permanente Northern California, an integrated healthcare system. From CT scans at diagnosis, we assessed the radiodensity of subcutaneous (SAT) and visceral adipose tissue (VAT) at the third lumbar vertebra and categorized their radiodensity into three levels: low (<1 standard deviation [SD] below the mean), middle (mean ± 1 SD), and high (>1 SD above the mean). Using multivariable Cox proportional hazards regression with adjustment for clinicopathological characteristics including body mass index, we calculated hazard ratios (HRs [95% confidence intervals]) for the associations of adipose tissue radiodensity with overall mortality and breast-cancer-specific mortality.

RESULTS

Median age at diagnosis of breast cancer was 56.0 years, most (63.3%) were non-Hispanic White and nearly half (45.6%) were stage II. Compared to middle SAT radiodensity, high SAT radiodensity was significantly associated with increased risk of overall mortality (HR: 1.45 [1.15-1.81]), non-significantly with breast-cancer-specific mortality (HR: 1.32 [0.95-1.84]). Neither low SAT radiodensity nor high or low VAT radiodensity was significantly associated with overall or breast-cancer-specific mortality.

CONCLUSIONS

High radiodensity of SAT at diagnosis of nonmetastatic breast cancer was associated with increased risk of overall mortality, independent of adiposity and other prognostic factors. Considering both radiodensity and quantity of adipose tissue at different locations could deepen understanding of the role of adiposity in breast cancer survival.

Predicting the Recurrence of Gastric Cancer Using the Textural Features of Perigastric Adipose Tissue on [18F]FDG PET/CT

This study aimed to assess the relationship between the histopathological and textural features of perigastric adipose tissue (AT) on 2-deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]FDG) positron emission tomography/computed tomography (PET/CT) and to evaluate the prognostic significance of perigastric AT textural features in predicting recurrence-free survival (RFS) in patients with gastric cancer. Sixty-nine patients with gastric cancer who underwent staging [¹⁸F]FDG PET/CT and subsequent curative surgery were retrospectively reviewed. Textural features of perigastric AT were extracted from PET images. On histopathological analysis, CD4, CD8, and CD163 cell infiltration and matrix metalloproteinase-11 and interleukin-6 (IL-6) expression in perigastric AT were graded. The degree of CD163 cell infiltration in perigastric AT was significantly correlated with the mean standardized uptake value (SUV), SUV histogram entropy, grey-level co-occurrence matrix (GLCM) energy, and GLCM entropy of perigastric AT. The degree of IL-6 expression in the perigastric AT was significantly correlated with the mean and median SUVs of perigastric AT. In multivariate survival analysis, GLCM entropy, GLCM dissimilarity, and GLCM homogeneity of perigastric AT were significant predictors of RFS. The textural features of perigastric AT on [¹⁸F]FDG PET/CT significantly correlated with inflammatory response in perigastric AT and were significant prognostic factors for predicting RFS in patients with gastric cancer.