Effect of adipose tissue volume on prognosis in patients with non-small cell lung cancer

Detection of cancer-associated cachexia in lung cancer patients using whole-body [18F]FDG-PET/CT imaging: A multi-centre study

BACKGROUND

Cancer-associated cachexia (CAC) is a metabolic syndrome contributing to therapy resistance and mortality in lung cancer patients (LCP). CAC is typically defined using clinical non-imaging criteria. Given the metabolic underpinnings of CAC and the ability of [18F]fluoro-2-deoxy-D-glucose (FDG)-positron emission tomography (PET)/computer tomography (CT) to provide quantitative information on glucose turnover, we evaluate the usefulness of whole-body (WB) PET/CT imaging, as part of the standard diagnostic workup of LCP, to provide additional information on the onset or presence of CAC.

METHODS

This multi-centre study included 345 LCP who underwent WB [18F]FDG-PET/CT imaging for initial clinical staging. A weight loss grading system (WLGS) adjusted to body mass index was used to classify LCP into 'No CAC' (WLGS-0/1 at baseline prior treatment and at first follow-up: N = 158, 51F/107M), 'Dev CAC' (WLGS-0/1 at baseline and WLGS-3/4 at follow-up: N = 90, 34F/56M), and 'CAC' (WLGS-3/4 at baseline: N = 97, 31F/66M). For each CAC category, mean standardized uptake values (SUV) normalized to aorta uptake () and CT-defined volumes were extracted for abdominal and visceral organs, muscles, and adipose-tissue using automated image segmentation of baseline [18F]FDG-PET/CT images. Imaging and non-imaging parameters from laboratory tests were compared statistically. A machine-learning (ML) model was then trained to classify LCP as 'No CAC', 'Dev CAC', and 'CAC' based on their imaging parameters. SHapley Additive exPlanations (SHAP) analysis was employed to identify the key factors contributing to CAC development for each patient.

RESULTS

The three CAC categories displayed multi-organ differences in . In all target organs, was higher in the 'CAC' cohort compared with 'No CAC' (P < 0.01), except for liver and kidneys, where in 'CAC' was reduced by 5%. The 'Dev CAC' cohort displayed a small but significant increase in of pancreas (+4%), skeletal-muscle (+7%), subcutaneous adipose-tissue (+11%), and visceral adipose-tissue (+15%). In 'CAC' patients, a strong negative Spearman correlation (ρ = -0.8) was identified between and volumes of adipose-tissue. The machine-learning model identified 'CAC' at baseline with 81% of accuracy, highlighting of spleen, pancreas, liver, and adipose-tissue as most relevant features. The model performance was suboptimal (54%) when classifying 'Dev CAC' versus 'No CAC'.

CONCLUSIONS

WB [18F]FDG-PET/CT imaging reveals groupwise differences in the multi-organ metabolism of LCP with and without CAC, thus highlighting systemic metabolic aberrations symptomatic of cachectic patients. Based on a retrospective cohort, our ML model identified patients with CAC with good accuracy. However, its performance in patients developing CAC was suboptimal. A prospective, multi-centre study has been initiated to address the limitations of the present retrospective analysis.

Prognostic value of CT body composition analysis for 1-year mortality after transcatheter aortic valve replacement

OBJECTIVES

To investigate the value of body composition indices derived from pre-procedural computed tomography (CT) in predicting 1-year mortality among patients who underwent transcatheter aortic valve replacement (TAVR).

MATERIALS AND METHODS

We assessed consecutive patients who underwent TAVR between June 2016 and December 2021 at a single academic medical center. Skeletal muscle and subcutaneous fat area at the T4, T12, and L3 levels on pre-procedural CT were measured. The association between body composition and 1-year mortality was evaluated using Cox proportional hazard regression analysis.

RESULTS

Finally, 408 patients were included (185 men and 223 women; mean age, 81.7 ± 5.1 years; range, 62-98 years). Post-procedural death occurred in 13.2% of patients. The muscle-height index and fat-height index at the L3 level were more strongly correlated with those at the T12 level (r = 0.765, p < 0.001 and r = 0.932, p < 0.001, respectively) than with those at the T4 level (r = 0.535, p < 0.001 and r = 0.895, p < 0.001, respectively). The cumulative 1-year mortality rate was highest for patients with both sarcopenia and adipopenia (26%), followed by those with adipopenia only (17%), those with sarcopenia only (12%), and those with neither sarcopenia nor adipopenia (8%, p = 0.002). Multivariable analysis revealed that body composition at the T12 level was an independent risk factor for 1-year mortality (hazard ratio: 4.09, 95% confidence interval: 2.01-8.35) in patients with both sarcopenia and adipopenia (p < 0.001).

CONCLUSION

Sarcopenia or adipopenia assessed with CT at the thoracic level may be valuable for stratifying 1-year all-cause mortality in patients who undergo TAVR.

CLINICAL RELEVANCE STATEMENT

Skeletal muscle and subcutaneous fat mass indices at the level of T12, measured on pre-procedural CT, have value for risk stratification of 1-year all-cause mortality in patients who undergo transcatheter aortic valve replacement.

KEY POINTS

Sarcopenia and adipopenia are associated with the prognosis of patients undergoing transcatheter aortic valve replacement. Body composition at the T12 level was an independent risk factor for 1-year all-cause mortality. Sarcopenia or adipopenia assessed at T12 with pre-procedural CT is valuable for risk stratification.

Increased adipose tissue is associated with improved overall survival, independent of skeletal muscle mass in non-small cell lung cancer

BACKGROUND

The prognostic significance of non-cancer-related prognostic factors, such as body composition, has gained extensive attention in oncological research. Compared with sarcopenia, the prognostic significance of adipose tissue for overall survival in non-small cell lung cancer remains unclear. We investigated the prognostic value of skeletal muscle and adipose tissue in patients with non-small cell lung cancer.

METHODS

This retrospective study included 4434 patients diagnosed with non-small cell lung cancer between January 2014 and December 2016. Cross-sectional areas of skeletal muscle and subcutaneous fat were measured, and the pericardial fat volume was automatically calculated. The skeletal muscle index and subcutaneous fat index were calculated as skeletal muscle area and subcutaneous fat area divided by height squared, respectively, and the pericardial fat index was calculated as pericardial fat volume divided by body surface area. The association between body composition and outcomes was evaluated using Cox proportional hazards model.

RESULTS

A total of 750 patients (501 males [66.8%] and 249 females [33.2%]; mean age, 60.9 ± 9.8 years) were included. Sarcopenia (60.8% vs. 52.7%; P < 0.001), decreased subcutaneous fat index (51.4% vs. 25.2%; P < 0.001) and decreased pericardial fat index (55.4% vs. 16.5%; P < 0.001) were more commonly found in the deceased group than survived group. In multivariable Cox regression analysis, after adjusting for clinical variables, increased subcutaneous fat index (hazard ratio [HR] = 0.56, 95% confidence interval [CI]: 0.47-0.66, P < 0.001) and increased pericardial fat index (HR = 0.47, 95% CI: 0.40-0.56, P < 0.001) were associated with longer overall survival. For stage I-III patients, increased subcutaneous fat index (HR = 0.62, 95% CI: 0.48-0.76, P < 0.001) and increased pericardial fat index (HR = 0.43, 95% CI: 0.34-0.54, P < 0.001) were associated with better 5-year overall survival rate. Similar results were recorded in stage IV patients. For patients with surgery, the prognostic value of increased subcutaneous fat index (HR = 0.60, 95% CI: 0.44-0.80, P = 0.001) and increased pericardial fat index (HR = 0.51, 95% CI: 0.38-0.68, P < 0.001) remained and predicted favourable overall survival. Non-surgical patients showed similar results as surgical patients. No association was noted between sarcopenia and overall survival (P > 0.05).

CONCLUSIONS

Increased subcutaneous fat index and pericardial fat index were associated with a higher 5-year overall survival rate, independent of sarcopenia, in non-small cell lung cancer and may indicate a reduced risk of non-cancer-related death.

Prognostic Significance of Adipose Tissue Distribution and Metabolic Activity in PET/CT in Patients with Metastatic Colorectal Cancer

PURPOSE

In this study, we aimed to evaluate the prognostic significance of adipose tissue distribution and metabolic activity in PET/CT to predict survival in patients with metastatic colorectal cancer (mCRC).

METHODS

The volume, density (HU), and FDG uptake (standardized uptake value (SUV)) of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) and maximum FDG uptake of the tumor tissue were measured. Subcutaneous adipose tissue of volume-to-density ratio (SAT ratio) was calculated.

RESULTS

The median OS for the patients with SAT ratio value <  -1.1 and ≥  -1.1 were 38.5 (95% CI 31.54-45.58) and 24.5 (95% CI 14.13-34.93) months, respectively (p = 0.05). During follow-up, 69 patients experienced disease progression. The median progression-free survival (PFS) was 11.03 months (95% CI: 9.11-12.95). Median PFS for patients with tumor SUV max value < 11.5 and ≥ 11.5 were 9.2 (95% CI 7.25-11.27) and 12.6 (95% CI 10.02-15.27) months, respectively (p = 0.14). Forty-eight patients received bevacizumab therapy. VAT SUV mean (HR: 0.09; 95% CI 0.01-0.52, p = 0.008) was significantly associated with PFS in patients receiving bevacizumab. SAT ratio was the significant parameter for the OS (HR: 0.58; 95% CI 0.33-1.01, p = 0.05) and PFS (HR: 1.99; 95% CI 1.02-3.91, p = 0.043).

CONCLUSIONS

SAT ratio was an independent prognostic factor for survival in patients with mCRC. Higher SAT volume is correlated with longer survival in mCRC patients.

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.

A novel analytical approach for outcome prediction in newly diagnosed NSCLC based on [18F]FDG PET/CT metabolic parameters, inflammatory markers, and clinical variables

OBJECTIVES

To develop a novel analytical approach based on ¹⁸F-fluorodeoxyglucose ([¹⁸F]FDG) positron emission tomography (PET) metabolic parameters, serum inflammatory markers, and clinical variables to improve the outcome prediction in NSCLC.

METHODS

A total of 190 newly diagnosed NSCLC patients who underwent pretreatment [¹⁸F]FDG PET/CT were retrospectively enrolled and divided into a training cohort (n = 127) and a test cohort (n = 63). Cox regression analysis was used to investigate the predictive values of PET metabolic parameters, inflammation markers, and clinical variables for progression-free survival (PFS) and overall survival (OS). Based on the results of multivariate analysis, PET-based, clinical, and combined models were constructed. The predictive performance of different models was evaluated using time-dependent ROC curve analysis, Harrell concordance index (C-index), calibration curve, and decision curve analysis.

RESULTS

The combined models incorporating SULmax, MTV, NLR, and ECOG PS demonstrated significant prognostic superiority over PET-based models, clinical models, and TNM stage in terms of both PFS (C-index: 0.813 vs. 0.786 vs. 0.776 vs. 0.678, respectively) and OS (C-index: 0.856 vs. 0.792 vs. 0.781 vs. 0.674, respectively) in the training cohort. Similar results were observed in the test cohort for PFS (C-index: 0.808 vs. 0.764 vs. 0.748 vs. 0.679, respectively) and OS (C-index: 0.836 vs. 0.785 vs. 0.726 vs. 0.660, respectively) prediction. The combined model calibrated well in two cohorts. Decision curve analysis supported the clinical utility of the combined model.

CONCLUSIONS

We reported a novel analytical approach combining PET metabolic information with inflammatory biomarker and clinical characteristics, which could significantly improve outcome prediction in newly diagnosed NSCLC.

KEY POINTS

• The nomogram incorporating SULmax, MTV, NLR, and ECOG PS outperformed the TNM stage for outcome prediction in patients with newly diagnosed NSCLC. • The established nomogram could provide refined prognostic stratification.

Adiposity and cancer survival: a systematic review and meta-analysis

PURPOSE

The increasing availability of clinical imaging tests (especially CT and MRI) that directly quantify adipose tissue has led to a rapid increase in studies examining the relationship of visceral, subcutaneous, and overall adiposity to cancer survival. To summarize this emerging body of literature, we conducted a systematic review and meta-analysis of imaging-measured as well as anthropometric proxies for adipose tissue distribution and cancer survival across a wide range of cancer types.

METHODS

Using keywords related to adiposity, cancer, and survival, we conducted a systematic search of the literature in PubMed and MEDLINE, Embase, and Web of Science Core Collection databases from database inception to 30 June 2021. We used a random-effect method to calculate pooled hazard ratios (HR) and corresponding 95% confidence intervals (CI) within each cancer type and tested for heterogeneity using Cochran's Q test and the I2 test.

RESULTS

We included 203 records for this review, of which 128 records were utilized for quantitative analysis among 10 cancer types: breast, colorectal, gastroesophageal, head and neck, hepatocellular carcinoma, lung, ovarian, pancreatic, prostate, and renal cancer. We found that imaging-measured visceral, subcutaneous, and total adiposity were not significantly associated with increased risk of overall mortality, death from primary cancer, or cancer progression among patients diagnosed with these 10 cancer types; however, we found significant or high heterogeneity for many cancer types. For example, heterogeneity was similarly high when the pooled HRs (95% CI) for overall mortality associated with visceral adiposity were essentially null as in 1.03 (0.55, 1.92; I2 = 58%) for breast, 0.99 (0.81, 1.21; I2 = 71%) for colorectal, versus when they demonstrated a potential increased risk 1.17 (0.85, 1.60; I2 = 78%) for hepatocellular carcinoma and 1.62 (0.90, 2.95; I2 = 84%) for renal cancer.

CONCLUSION

Greater adiposity at diagnosis (directly measured by imaging) is not associated with worse survival among cancer survivors. However, heterogeneity and other potential limitations were noted across studies, suggesting differences in study design and adiposity measurement approaches, making interpretation of meta-analyses challenging. Future work to standardize imaging measurements and data analyses will strengthen research on the role of adiposity in cancer survival.

Imaging modalities for diagnosis and monitoring of cancer cachexia

Cachexia, a multifactorial wasting syndrome, is highly prevalent among advanced-stage cancer patients. Unlike weight loss in healthy humans, the progressive loss of body weight in cancer cachexia primarily implicates lean body mass, caused by an aberrant metabolism and systemic inflammation. This may lead to disease aggravation, poorer quality of life, and increased mortality. Timely detection is, therefore, crucial, as is the careful monitoring of cancer progression, in an effort to improve management, facilitate individual treatment and minimize disease complications. A detailed analysis of body composition and tissue changes using imaging modalities—that is, computed tomography, magnetic resonance imaging, (¹⁸F) fluoro-2-deoxy-d-glucose (¹⁸FDG) PET and dual-energy X-ray absorptiometry—shows great premise for charting the course of cachexia. Quantitative and qualitative changes to adipose tissue, organs, and muscle compartments, particularly of the trunk and extremities, could present important biomarkers for phenotyping cachexia and determining its onset in patients. In this review, we present and compare the imaging techniques that have been used in the setting of cancer cachexia. Their individual limitations, drawbacks in the face of clinical routine care, and relevance in oncology are also discussed.

Impact of body composition, nutritional and inflammatory status on outcome of non-small cell lung cancer patients treated with immunotherapy

BACKGROUND AND AIMS

Body composition and balance of nutritional and inflammatory status are important for the immune system. Alterations of these aspects may impact on response, outcome and toxicities of immunotherapy. In this review we try to clarify some definitions and tools used for the assessment of the different aspects of nutritional disorders, body composition and inflammatory status with a focus on lung cancer.

METHODS

We primary investigate the definitions of malnutrition, cachexia, sarcopenia and overweight. Secondary, tools used to measure body composition, nutritional and inflammatory status, mainly in lung cancer are reviewed.

RESULTS

All these features, in the time of precision medicine may improve assessment and selection of patients, incorporating also early palliative care in standard therapy.

CONCLUSIONS

A multimodal approach based on nutrition assessment and physical exercise should be evaluated to improve aspects of the immune response against cancer and to propose the best treatment to every patient.

Computed tomography-derived body composition analysis in patients with advanced cancer: clinical utility and future research

PURPOSE OF REVIEW

With weight loss increasingly occurring against a background of obesity across a variety of advanced cancers, there has been increasing interest in computed tomography (CT)-derived body composition analysis. Various imaging software packages and thresholds are commonly in use in CT-derived body composition analysis. This review discusses the current research in field of body composition with emphasis on the information required for such measurements to be taken into routine clinical practice.

RECENT FINDINGS

CT is widely used for tumour staging in patients with cancer. Over the last decade, this imaging modality has been exploited to make measurements of body composition. Using a common landmark (L3) several different thresholds have been developed to stratify adipose and muscle tissue areas according to age, sex and BMI and their relationship with survival. A significant relationship between CT-derived body composition and clinical outcomes has been shown in different tumour types and geographical locations. However, there is considerable variation with methods, thresholds and muscle groups used for analysis. Therefore, there would appear to be a need to develop reliable methodology and population-specific reference ranges to guide clinical interpretation and enable routine clinical use.

SUMMARY

There has been an explosion of clinical research interest in CT-derived body composition analysis. Such body composition analysis provides important host phenotype information which has prognostic value. For CT-derived body composition to be fit for use in routine clinical practice, there is need for universally accepted terminology, software, muscle group selection, prognostic thresholds to standardize such body composition analysis.

Prognostic Value of CT-Attenuation and 18F-Fluorodeoxyglucose Uptake of Periprostatic Adipose Tissue in Patients with Prostate Cancer

This study aimed to assess the prognostic value of computed tomography (CT)-attenuation and ¹⁸F-fluorodeoxyglucose (FDG) uptake of periprostatic adipose tissue (PPAT) for predicting disease progression-free survival (DPFS) in patients with prostate cancer. Seventy-seven patients with prostate cancer who underwent staging FDG positron emission tomography (PET)/CT were retrospectively reviewed. CT-attenuation (HU) and FDG uptake (SUV) of PPAT were measured from the PET/CT images. The relationships between these PPAT parameters and clinical factors were assessed, and a Cox proportional hazard regression test was performed to evaluate the prognostic significance of PPAT HU and SUV. PPAT HU and SUV showed significant positive correlations with tumor stage and serum prostate-specific antigen level (PSA) (p < 0.05). Patients with high PPAT HU and SUV had significantly worse DPFS than those with low PPAT HU and SUV (p < 0.05). In multivariate analysis, PPAT SUV was a significant predictor of DPFS after adjusting for tumor stage, serum PSA, and tumor SUV (p = 0.003; hazard ratio, 1.50; 95% confidence interval, 1.15–1.96). CT-attenuation and FDG uptake of PPAT showed significant association with disease progression in patients with prostate cancer. These imaging findings may be evidence of the role of PPAT in prostate cancer progression.

Nutritional Support in Lung Cancer Patients: The State of the Art

Lung cancer (LC) represents the most commonly diagnosed neoplasm worldwide for both sexes and is the leading cause of cancer mortality. Malnutrition is a comorbidity frequently found in neoplastic patients, but it remains often underestimated and thus undertreated. In this review, we aimed to investigate the incidence of malnutrition among LC patients according to different screening and assessment tools, to evaluate the impact of weight loss and body composition on survival, and to analyze the efficacy of different nutritional interventions in this setting. Although malnutrition, weight loss, and body composition changes can affect survival and other clinical outcomes in LC patients, the role of nutritional interventions is not yet strongly proven, and further studies are recommended. Nevertheless, screening, assessing, and eventually treating malnutrition in LC patients are strongly recommended, according to the most recent nutritional intervention guidelines for oncology patients.

Prognostic value of anthropometric measures extracted from whole-body CT using deep learning in patients with non-small-cell lung cancer

INTRODUCTION

The aim of the study was to extract anthropometric measures from CT by deep learning and to evaluate their prognostic value in patients with non-small-cell lung cancer (NSCLC).

METHODS

A convolutional neural network was trained to perform automatic segmentation of subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and muscular body mass (MBM) from low-dose CT images in 189 patients with NSCLC who underwent pretherapy PET/CT. After a fivefold cross-validation in a subset of 35 patients, anthropometric measures extracted by deep learning were normalized to the body surface area (BSA) to control the various patient morphologies. VAT/SAT ratio and clinical parameters were included in a Cox proportional-hazards model for progression-free survival (PFS) and overall survival (OS).

RESULTS

Inference time for a whole volume was about 3 s. Mean Dice similarity coefficients in the validation set were 0.95, 0.93, and 0.91 for SAT, VAT, and MBM, respectively. For PFS prediction, T-stage, N-stage, chemotherapy, radiation therapy, and VAT/SAT ratio were associated with disease progression on univariate analysis. On multivariate analysis, only N-stage (HR = 1.7 [1.2-2.4]; p = 0.006), radiation therapy (HR = 2.4 [1.0-5.4]; p = 0.04), and VAT/SAT ratio (HR = 10.0 [2.7-37.9]; p < 0.001) remained significant prognosticators. For OS, male gender, smoking status, N-stage, a lower SAT/BSA ratio, and a higher VAT/SAT ratio were associated with mortality on univariate analysis. On multivariate analysis, male gender (HR = 2.8 [1.2-6.7]; p = 0.02), N-stage (HR = 2.1 [1.5-2.9]; p < 0.001), and the VAT/SAT ratio (HR = 7.9 [1.7-37.1]; p < 0.001) remained significant prognosticators.

CONCLUSION

The BSA-normalized VAT/SAT ratio is an independent predictor of both PFS and OS in NSCLC patients.

KEY POINTS

• Deep learning will make CT-derived anthropometric measures clinically usable as they are currently too time-consuming to calculate in routine practice. • Whole-body CT-derived anthropometrics in non-small-cell lung cancer are associated with progression-free survival and overall survival. • A priori medical knowledge can be implemented in the neural network loss function calculation.

Significance of CT attenuation and F-18 fluorodeoxyglucose uptake of visceral adipose tissue for predicting survival in gastric cancer patients after curative surgical resection

BACKGROUND

The purpose of this study was to investigate the prognostic significance of computed tomography (CT) attenuation and F-18 fluorodeoxyglucose (FDG) uptake of visceral adipose tissue (VAT) to predict peritoneal recurrence-free survival (RFS) as well as RFS and overall survival (OS) in patients with advanced gastric cancer (AGC).

METHODS

We retrospectively enrolled 117 patients with AGC who underwent staging FDG positron emission tomography (PET)/CT and subsequent curative surgical resection. CT attenuation and FDG uptake (SUV) of VAT and maximum FDG uptake of primary tumor (SUVmaxT) were measured from PET/CT images. The relationship of VAT attenuation and SUV with clinico-histopathologic factors and survival was assessed.

RESULTS

There was a significant positive correlation between VAT attenuation and SUV (p < 0.001, r = 0.799). In correlation analyses, both VAT attenuation and SUV showed significant positive correlations with T stage, TNM stage, tumor size, and platelet-to-lymphocyte ratio (p < 0.05), and patients who experienced recurrence during the first 3-year after surgery had significantly higher VAT attenuation and SUV than those who had no recurrence (p < 0.05). Patients with high VAT attenuation and SUV showed significantly worse RFS, peritoneal RFS, and OS than those with low values (p < 0.05). On multivariate survival analysis, VAT attenuation was significantly associated with peritoneal RFS and OS and VAT SUV was significantly associated with OS (p < 0.05).

CONCLUSIONS

CT attenuation and FDG uptake of VAT on staging FDG PET/CT were correlated with tumor characteristics and were significant predictive factors for peritoneal RFS and OS in patients with AGC.

Prognostic Significance of Abdominal-to-Gluteofemoral Adipose Tissue Distribution in Patients with Breast Cancer

This study aimed to evaluate the association between abdominal-to-gluteofemoral adipose tissue (AT) distribution and recurrence-free survival (RFS) in breast cancer patients. Staging F-18 fluorodexoyglucose (FDG) positron emission tomography/computed tomography (PET/CT) images of 336 women with breast cancer were retrospectively analyzed. From CT images, the volume and CT-attenuation of visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue (SAT), and gluteofemoral AT were measured and the ratio of abdomen-to-gluteofemoral AT volume (AG volume ratio) was calculated. The relationships between adipose tissue parameters and RFS were assessed. Through univariate analysis, abdominal SAT volume, gluteofemoral AT volume, and AG volume ratio were significantly associated with RFS. An increase in abdominal SAT volume and AG volume ratio were associated with an increased risk of recurrence, whereas increased gluteofemoral AT volume was associated with a decreased risk of recurrence. On multivariate analysis, abdominal SAT volume, gluteofemoral AT volume, and AG volume ratio were found to be significant predictors of RFS after adjusting for clinic-histological factors. Irrespective of obesity, patients with a high AG volume ratio showed a higher recurrence rate than those with a low AG volume ratio. Increased abdominal SAT volume and decreased gluteofemoral AT volume were related to poor RFS in breast cancer patients.

Prognostic Significance of CT-Attenuation of Tumor-Adjacent Breast Adipose Tissue in Breast Cancer Patients with Surgical Resection

The purpose of this study was to evaluate the prognostic significance of computed tomography (CT)-attenuation of tumor-adjacent breast adipose tissue for predicting recurrence-free survival (RFS) in patients with breast cancer. We retrospectively enrolled 287 breast cancer patients who underwent pretreatment 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/CT. From non-contrast-enhanced CT images of PET/CT, CT-attenuation values of tumor-adjacent breast adipose tissue (TAT HU) and contralateral breast adipose tissue (CAT HU) were measured. Difference (HU difference) and percent difference (HU difference %) in CT-attenuation values between TAT HU and CAT HU were calculated. The relationships of these breast adipose tissue parameters with tumor factors and RFS were assessed. TAT HU was significantly higher than CAT HU (p < 0.001). TAT HU, HU difference, and HU difference % showed significant correlations with T stage and estrogen receptor and progesterone receptor status (p < 0.05), whereas CAT HU had no significant relationships with tumor factors (p > 0.05). Patients with high TAT HU, HU difference, and HU difference % had significantly worse RFS than those with low values (p < 0.001). In multivariate analysis, TAT HU and HU difference % were significantly associated with RFS after adjusting for clinico-pathologic factors (p < 0.05). CT-attenuation of tumor-adjacent breast adipose tissue was significantly associated with RFS in patients with breast cancer. The findings seem to support the close contact between breast cancer cells and tumor-adjacent adipocytes observed with imaging studies.