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

Ovarian cancer-derived TGF-β1 induces cancer-associated adipocytes formation by activating SMAD3/TRIB3 pathway to establish pre-metastatic niche

Ovarian cancer (OC) is prone to adipose tissue metastasis. However, the underlying molecular mechanisms remain elusive. Here, we observed that omental adipocytes were induced into cancer-associated adipocytes (CAAs) by OC-derived TGF-β1 to establish a pre-metastatic niche (PMN) through collagen and fibronectin secretion. Mechanistically, OC-derived TGF-β1 binds to adipocyte membrane receptors and thus activates intracellular signaling by SMAD3 phosphorylation. The activation of TGF-β1/SMAD3 signaling pathway dedifferentiates adipocytes into CAAs by upregulating Tribbles homolog 3 (TRIB3), which suppresses the phosphorylation of CEBPβ. Additionally, CAAs secrete collagen I, collagen VI, and fibronectin to remodel the extracellular matrix and promote the adhesion of OC cells. Pharmacological inhibition of the TGF-β1/SMAD3 pathway significantly inhibits CAAs and PMN formation, thereby reducing the OC metastatic burden. Our findings indicate that the formation of CAAs and PMN in adipose tissues facilitates OC cell implantation and blocking the TGF-β1/SMAD3 signaling pathway could prevent OC omental metastasis.

The Relationship of Pathological Response and Visceral Muscle and Fat Volume in Women With Breast Cancer Who Received Neoadjuvant Chemotherapy

Objective

Differences in individual muscle/fat volumes may change the effectiveness of chemotherapy. In this study, the relationship between trunkal muscle and fat volume and body mass index (BMI) obtained before receiving neoadjuvant chemotherapy (NCT) in patients with breast cancer and complete pathological response (pCR) was investigated.

Materials and Methods

The volumes of psoas, abdominal and paraspinal muscles, and trunkal subcutaneous and visceral fat were calculated using CoreSlicer AI 2.0 opensource program from the F-18 fluorodeoxyglucose positron emission tomography/computed tomography (CT) and CT images before NCT and postoperative pCR rates to NCT were recorded. Muscle/fat volumes and BMI prior to NCT were compared in terms of pathological pCR rates. Patients were followed up regularly for recurrence and survival.

Results

Ninety-three patients were included with median (range) values for age, BMI, and body weights of 48 (28-72) years, 27 (16.8-51.6) kg/m2, and 71.94 (43-137) kg, respectively. The median follow-up time was 18.6 (6.7-59.6) months. No significant correlation was found between total muscle or fat volumes of patients with and without pCR. BMI [26.2 (16.8-51.6) kg/m2 vs. 24.6 (20.3-34.3) kg/m2, p = 0.03] and pCR rates in patients with low right-psoas muscle volume [11.74 (7.03-18.51) vs. 10.2 (6.71-13.36), p = 0.025] were significantly greater. A significant relationship was found between right psoas muscle volume and disease-free survival (DFS) (11.74 cm3 (7.03-18.51) vs. 10.2 cm3 (6.71-13.36), p = 0.025). However, no significant relationship was detected between total muscle-fat volume, BMI and overall survival and DFS (p>0.05).

Conclusion

This is the first published study investigating the relationship between the pCR ratio and body muscle and fat volume measured by CoreSlicer AI 2.0 in patients with breast cancer who received NCT. No correlation was found between the pCR ratio and total muscle plus fat volume. However, these results need to be validated with larger patient series.

Peritumoral Adipose Tissue Density Predicts the Malignancy in cT1 Renal Masses

OBJECTIVE

Not only the frequency of surgery for small renal masses has increased secondary to the improvements and frequent use of imaging techniques but also the frequency of detection of benign lesions in nephrectomy specimens has increased as well. We aimed to assess the predictive value of computed tomography density of perirenal adipose tissue and peritumoral adipose tissue in distinguishing between benign and malignant renal masses.

MATERIALS AND METHODS

The current study included 116 patients who underwent nephrectomy for renal masses between January 2015 and December 2020. Clinicodemographic and preoperative computed tomography features and final pathological findings of the patients were recorded. According to the final pathological results, the patients were divided into 2 groups benign (n = 32) and malignant (n = 84). Groups were compared statistically in terms of perirenal adipose tissue and peritumoral adipose tissue density.

RESULTS

The median tumor size was 5.00 cm. The rate of benign tumors was higher in female patients (P = .005). The median peritumoral adipose tissue density among cT1 and cT1a tumors was higher in the malignant group (P < .001, for each). At a cutoff value of 97.50 Hounsfield Units, the peritumoral adipose tissue density had a sensitivity of 83.0% and a specificity of 79.2% for predicting the presence of malignant tumors in ≤7 cm renal masses. Using a cutoff value of -97.50 Hounsfield Units, the peritumoral adipose tissue density had a sensitivity of 88.9% and a specificity of 83.3% for predicting the presence of malignant tumors in ≤4 cm renal masses.

CONCLUSION

The peritumoral adipose tissue density in the preoperative computed tomography images predicts the malignancy in cT1 renal masses.

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.

Prognostic Value of Dual-Time-Point [18F]FDG PET/CT for Predicting Distant Metastasis after Treatment in Patients with Non-Small Cell Lung Cancer

This study aimed to evaluate the prognostic significance of 2-Deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) uptake in the bone marrow (BM) and primary tumors on dual-time-point (DTP) PET/CT for predicting progression-free survival (PFS) and distant metastasis-free survival (DMFS) in patients with non-small cell lung cancer (NSCLC). We retrospectively analyzed DTP [18F]FDG PET/CT images from 211 patients with NSCLC. The maximum standardized uptake value (SUV) of primary lung cancer and mean [18F]FDG uptake of the BM (BM SUV) were measured from early and delayed PET/CT images, and the percent changes in these parameters (∆maximum SUV and ∆BM SUV) were calculated. On multivariate survival analysis, the maximum SUV and BM SUV on both early and delayed PET/CT scans were significantly associated with PFS, while the ∆maximum SUV and ∆BM SUV failed to show statistical significance. For DMFS, the ∆maximum SUV and ∆BM SUV were independent predictors along with the TNM stage. Distant progression was observed only in 1.3% of patients with low ∆maximum SUV and ∆BM SUV, whereas 28.2% of patients with high ∆maximum SUV and ∆BM SUV experienced distant progression. The ∆maximum SUV and ∆BM SUV on DTP [18F]FDG PET/CT were significant independent predictors for DMFS in patients with NSCLC.

Predicting cancer outcomes with radiomics and artificial intelligence in radiology

The successful use of artificial intelligence (AI) for diagnostic purposes has prompted the application of AI-based cancer imaging analysis to address other, more complex, clinical needs. In this Perspective, we discuss the next generation of challenges in clinical decision-making that AI tools can solve using radiology images, such as prognostication of outcome across multiple cancers, prediction of response to various treatment modalities, discrimination of benign treatment confounders from true progression, identification of unusual response patterns and prediction of the mutational and molecular profile of tumours. We describe the evolution of and opportunities for AI in oncology imaging, focusing on hand-crafted radiomic approaches and deep learning-derived representations, with examples of their application for decision support. We also address the challenges faced on the path to clinical adoption, including data curation and annotation, interpretability, and regulatory and reimbursement issues. We hope to demystify AI in radiology for clinicians by helping them to understand its limitations and challenges, as well as the opportunities it provides as a decision-support tool in cancer management.

Prognostic significance of imaging features of peritumoral adipose tissue in FDG PET/CT of patients with colorectal cancer

PURPOSE

This study investigated the relationship of imaging features of primary tumor and peritumoral VAT on PET/CT with histopathological findings of peritumoral VAT and recurrence-free survival (RFS) in patients with colorectal cancer.

METHODS

We retrospectively reviewed 133 patients diagnosed with colorectal cancer who underwent staging FDG PET/CT and received curative surgery. Histogram-based imaging features of primary tumor and peritumoral VAT were extracted from PET/CT images. Based on histopathological analysis of peritumoral VAT, the degree of CD4, CD8, and CD163 cell infiltration and the expression of matrix metalloproteinase-11 and interleukin 6 (IL-6) were graded. Differences in imaging parameters based on the histopathological results and the relationships between imaging features and RFS were assessed.

RESULTS

Mean CT-attenuation and SUV of peritumoral VAT showed significant positive correlation with CD163 cell infiltration and IL-6 expression of peritumoral VAT. Univariable survival analysis revealed significant correlation between RFS and the mean CT-attenuation, mean SUV, and first-order SUV entropy of peritumoral VAT (p < 0.05). Multivariable analysis indicated that mean SUV and SUV entropy of peritumoral VAT remained significant predictors of RFS after adjustment for age, sex, and T stage (p < 0.05).

CONCLUSION

FDG uptake of peritumoral VAT was significantly associated with inflammatory response in peritumoral VAT and was an independent predictor of RFS in colorectal cancer patients.

Clinical Significance of Peritumoral Adipose Tissue PET/CT Imaging Features for Predicting Axillary Lymph Node Metastasis in Patients with Breast Cancer

We investigated whether textural parameters of peritumoral breast adipose tissue (AT) based on F-18 fluorodeoxyglucose (FDG) PET/CT could predict axillary lymph node metastasis in patients with breast cancer. A total of 326 breast cancer patients with preoperative FDG PET/CT were retrospectively enrolled. PET/CT images were visually assessed and the maximum FDG uptake of axillary lymph nodes (LN SUVmax) was measured. From peritumoral breast AT, 38 textural features of PET imaging were extracted. The diagnostic ability of PET based on visual analysis, LN SUVmax, and textural features of peritumoral breast AT for predicting axillary lymph node metastasis were assessed using the area under the receiver operating characteristic curve (AUC) values. Among the 38 peritumoral breast AT textural features, grey-level co-occurrence matrix (GLCM) entropy showed the highest AUC value (0.830) for predicting axillary lymph node metastasis. The value of GLCM entropy was higher than that of visual analysis (0.739; p < 0.05) and the AUC value was comparable to that of LN SUVmax (0.793; p > 0.05). In the subgroup analysis of patients with negative findings on visual analysis, GLCM entropy still showed a high diagnostic ability (AUC: 0.759) in predicting lymph node metastasis. The findings suggest a potential diagnostic role of PET/CT imaging features of peritumoral breast AT in predicting axillary lymph node metastasis in patients with breast cancer.

Intermuscular fat density as a novel prognostic factor in breast cancer patients treated with adjuvant chemotherapy

BACKGROUND

Body composition, including sarcopenia and fat parameters, has received much attention as a prognostic factor in breast cancer.

METHODS

A total of 479 breast cancer patients who underwent surgery and received adjuvant chemotherapy were enrolled in this study. Body composition, including the index and density of skeletal muscle, visceral fat, subcutaneous fat, and intermuscular fat calculated by CT scan, was used as a prognostic factor. The endpoints were breast cancer-specific survival (BCSS) and overall survival (OS).

RESULTS

The number of patients with stages I, II, and III was 146 (30.5%), 237 (49.5%), and 96 (20%), respectively. Sarcopenia and muscle density were not significant prognostic factors for BCSS and OS. A high visceral fat index (VFI) was an independent prognostic factor for BCSS (HR, 2.55; 95% CI 1.10-5.95, p = 0.03) and OS (HR 2.55, 95% CI 1.26-5.16, p = 0.01). In addition, high intermuscular fat density (IMFD) was also a significant prognostic factor for BCSS (HR, 2.95; 95% CI 1.34-6.46, p = 0.007) and OS (HR 2.28, 95% CI 1.22-4.26, p = 0.01) in multivariate analysis.

CONCLUSION

VFI and IMFD were significant prognostic factors for BCSS and OS in breast cancer patients treated with adjuvant chemotherapy.

Prognosis predicting value of semiquantitative parameters of visceral adipose tissue and subcutaneous adipose tissue of 18F-FDG PET/CT in newly diagnosed secondary hemophagocytic lymphohistiocytosis

PURPOSE

The purpose of this study was to investigate the prognosis predicting value of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) of 18F-FDG PET/CT, and clinical inflammatory cytokines in newly diagnosed secondary hemophagocytic lymphohistiocytosis (SHLH).

METHODS

We retrospectively collected 58 patients with newly diagnosed SHLH from August 2016 to July 2019 in our hospital. All patients were followed up between 6 and 24 months. First, a comprehensive comparison of the general data between the death and the survival group was performed. Clinical lab indexes included were recorded and analyzed retrospectively. Second, the correlation between 18F-FDG PET/CT semiquantitative metabolic parameters of VAT, SAT and inflammatory cytokines was performed. 3D slicer software was used to get SUV and volume of VAT and SAT from 18F-FDG PET/CT. Third, overall survival (OS) analysis was performed. Finally, the prognosis predicting model was built based on risk factors to stratify SHLH patients.

RESULTS

There was significant difference in WBC, PLT, FBG, IL-10, PCR tests of EBV-DNA loads, SCD25 between the death group and the survival group. There was significant correlation between SAT coefficient variance (CV) and CRP, the mean standardized uptake value (SUVmean) of SAT (SAT SUVmean) and TG, SAT SUVmean and ESR. In univariate analysis with Cox regression analysis, SUVmean of VAT (VAT SUVmean), SAT Volume, SUVmean of SAT, CV of SAT (SAT HU CV), plasma EBV-DNA, WBC, PLT, FBG showed significance with OS. In multivariate Cox regression analysis, SAT Volume, SUVmean of SAT, plasma EBV-DNA, were independent prognostic factors for OS.

CONCLUSIONS

For newly diagnosed SHLH, SAT Volume, SUVmean of SAT, plasma EBV-DNA had significant relationship with poor prognosis. They were important independent predictors for overall survival for newly diagnosed SHLH.

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.

The Key Genes for Perineural Invasion in Pancreatic Ductal Adenocarcinoma Identified With Monte-Carlo Feature Selection Method

Background

Pancreatic ductal adenocarcinoma (PDAC) is the most aggressive form of pancreatic cancer. Its 5-year survival rate is only 3–5%. Perineural invasion (PNI) is a process of cancer cells invading the surrounding nerves and perineural spaces. It is considered to be associated with the poor prognosis of PDAC. About 90% of pancreatic cancer patients have PNI. The high incidence of PNI in pancreatic cancer limits radical resection and promotes local recurrence, which negatively affects life quality and survival time of the patients with pancreatic cancer.

Objectives

To investigate the mechanism of PNI in pancreatic cancer, we analyzed the gene expression profiles of tumors and adjacent tissues from 50 PDAC patients which included 28 patients with perineural invasion and 22 patients without perineural invasion.

Method

Using Monte-Carlo feature selection and Incremental Feature Selection (IFS) method, we identified 26 key features within which 15 features were from tumor tissues and 11 features were from adjacent tissues.

Results

Our results suggested that not only the tumor tissue, but also the adjacent tissue, was informative for perineural invasion prediction. The SVM classifier based on these 26 key features can predict perineural invasion accurately, with a high accuracy of 0.94 evaluated with leave-one-out cross validation (LOOCV).

Conclusion

The in-depth biological analysis of key feature genes, such as TNFRSF14, XPO1, and ATF3, shed light on the understanding of perineural invasion in pancreatic ductal adenocarcinoma.

Plasma cfDNA as a Potential Biomarker to Evaluate the Efficacy of Chemotherapy in Gastric Cancer

Objective

To investigate the clinical value of plasma cell-free DNA (cfDNA) as a potential biomarker for advanced gastric cancer (GC).

Patients and Methods

One hundred and six cases of advanced gastric cancer patients receiving chemotherapy were selected as study objects. Another 40 healthy volunteers were included as control groups. Plasma cfDNA concentration was detected by (SuperbDNA^TM) hybridization. Changes in cfDNA concentration during chemotherapy in patients with gastric cancer whose efficacy was assessed as partial response (PR), stable disease (SD) and disease progression (PD) were analyzed respectively. The relationship between the level of cfDNA and the efficacy of chemotherapy and clinical characteristics was also explored. In addition, cfDNA and other tumor markers were subjected to specificity and sensitivity analyses using ROC.

Results

cfDNA concentration in advanced GC patients was significantly higher than that in healthy controls (P<0.05). The concentration of plasma cfDNA in patients with PD showed an increasing trend over time. The concentration of plasma cfDNA in patients with therapeutic effect of PR decreased over time. In patients with therapeutic effect of SD, the plasma DNA concentration showed a stable trend over time. There was no significant correlation between cfDNA concentration and factors including gender, age, pathological type, CA724, CA125,CA199, AFP and CEA. ROC results showed that the area under the curve of cfDNA was larger than other tumor markers.

Conclusion

Plasma cfDNA concentration was significantly increased in patients with gastric cancer, and its diagnostic efficacy was superior to that of traditional tumor markers. It can be used as a tumor biomarker to monitor the efficacy of chemotherapy for gastric cancer.

Relationship Between Changes in Myocardial F-18 Fluorodeoxyglucose Uptake and Radiation Dose After Adjuvant Three-Dimensional Conformal Radiotherapy in Patients with Breast Cancer

This study aimed to assess the relationship between radiation dose and changes in the irradiated myocardial F-18 fluorodeoxyglucose (FDG) uptake after radiotherapy (RT) in breast cancer patients. The data of 55 patients with left and 48 patients with right breast cancer who underwent curative surgical resection and adjuvant three-dimensional conformal RT and staging (PET1), post-adjuvant chemotherapy (PET2), post-RT (PET3), and surveillance (PET4) FDG positron emission tomography/computed tomography (PET/CT) were retrospectively reviewed. The median interval between PET1 and curative surgical resection, between the end of adjuvant chemotherapy and PET2, between the end of RT and PET3, and between the end of RT and PET4 were five days, 13 days, 132 days, and 353 days, respectively. The myocardial-to-blood pool uptake ratio was measured in all patients. For patients with left breast cancer, the 30 Gy- (30 Gy) and 47.5 Gy-irradiated myocardium-to-low-irradiated myocardium (47.5 Gy) FDG uptake ratios were additionally measured. There were no differences in the myocardial-to-blood pool uptake ratios between left and right breast cancer on all PET scans. For left breast cancer, higher 30 Gy and 47.5 Gy uptake ratios were observed on PET3 than on PET1 and PET2. Both uptake ratios decreased on PET4 compared to PET3, but, were still higher compared to PET1. On PET3 and PET4, the 47.5 Gy were higher than the 30 Gy uptake ratios, while there were no differences between them on PET1 and PET2. Although the whole myocardium FDG uptake showed no significant change, the irradiated myocardium FDG uptake significantly increased after RT and was related to radiation dose to the myocardium in breast cancer patients. These results might be an imaging evidence that supports the increased risk of heart disease after RT in patients with left breast cancer.