Evaluation of patients with advanced epithelial ovarian cancer before primary treatment: correlation between tumour burden assessed by [18F]FDG PET/CT volumetric parameters and tumour markers HE4 and CA125

Relationship between HE4 levels and metabolic parameters in PET of non-small cell lung cancer patients

AIM

To investigate the relationship between serum human epididymis protein 4 (HE4) levels and metabolic parameters of positron emission tomography (PET) imaging in patients with lung cancer.

METHODS

Sixty non-small cell lung cancer (NSCLC) patients were included in this prospective study. Demographic information, smoking status, comorbid pathologies, preoperative HE4 levels, PET imaging metabolic parameters, disease stage and histopathology were recorded.

RESULTS

Significant positive correlations between serum HE4 levels and all the metabolic parameters were observed (p < 0.05). In univariate regression analyses, it was observed that high serum HE4 levels could indicate tumor be squamous cell carcinoma (SCC) (p = 0.029), advanced T stage (p = 0.041), and have high maximum standart uptake value (SUVmax) (p = 0.017).

CONCLUSION

Serum HE4 levels can be used as a biomarker to predict tumor burden and metabolic activity for NSCLC patients. Although sufficient per power analysis, this study may have benefited from further expansion, and by patient heterogeneity in TNM stage and tumor histology, potentially affecting the assessment of parameter relationships.

Artificial intelligence algorithm for preoperative prediction of FIGO stage in ovarian cancer based on clinical features integrated 18F-FDG PET/CT metabolic and radiomics features

PURPOSE

The International Federation of Gynecology and Obstetric (FIGO) stage is critical to guiding the treatments of ovarian cancer (OC). We tried to develop a model to predict the FIGO stage of OC through machine learning algorithms with patients' pretreatment clinical, positron emission tomography scan (PET/CT) metabolic, and radiomics features.

METHODS

We enrolled OC patients who underwent PET/CT scans and divided them into two cohorts according to their FIGO stage. Then we manually delineated the volume of interest (VOI) and calculated PET metabolic features. Other PET/CT radiomics features were extracted by Python. We developed 11 prediction models to predict stages based on four groups of features and conducted three experiments to verify the meaning of PET/CT features. We also redesigned experiments to demonstrate the stage prediction performance in ovarian clear cell carcinoma (OCCC) and mucinous ovarian cancer (MCOC).

RESULTS

183 OC patients were enrolled in this study, and we obtained 137 features from four groups of data. The best model was an adaptive ensemble with an area under the curve (AUC) value of 0.819. Our proposed models presented the best result of 0.808 in terms of AUC in OCCC and MCOC patients' groups.

CONCLUSION

Through artificial intelligence (AI) algorithms, the PET/CT metabolic and radiomics features combined with clinical features could improve the accuracy of staging prediction.

CT-Based Radiomics for the Preoperative Prediction of Occult Peritoneal Metastasis in Epithelial Ovarian Cancers

RATIONALE AND OBJECTIVES

The objective of this study was to develop a comprehensive combined model for predicting occult peritoneal metastasis (OPM) in epithelial ovarian cancers (EOCs) using radiomics features derived from computed tomography (CT) and clinical-radiological predictors.

MATERIALS AND METHODS

A total of 224 patients with EOCs were randomly divided into training dataset (N = 156) and test dataset (N = 86). Five clinical factors and seven radiological features were collected. The radiomics features were extracted from CT images of each patient. Multivariate logistic regression was employed to construct clinical and radiological models. The correlation analysis and least absolute shrinkage and selection operator algorithm were used to select radiomics features and build radiomics model. The important clinical, radiological factors, and radiomics features were integrated into a combined model by multivariate logistic regression. Receiver operating characteristics curve with area under the curve (AUC) were used to evaluate and compare predictive performance.

RESULTS

Carbohydrate antigen 125 (CA-125) and human epididymal protein 4 (HE-4) were independent clinical predictors. Laterality, thickened septa and margin were independent radiological predictors. In the training dataset, the AUCs for the clinical, radiological and radiomics models in evaluating OPM were 0.759, 0.819, and 0.830, respectively. In the test dataset, the AUCs for these models were 0.846, 0.835, and 0.779, respectively. The combined model outperformed other models in both the training and the test datasets with AUCs of 0.901 and 0.912, respectively. Decision curve analysis indicated that the combined model yielded a higher net benefit compared to the other models.

CONCLUSION

The combined model, integrating radiomics features with clinical and radiological predictors exhibited improved accuracy in predicting OPM in EOCs.

Prognostic value of HE4 in advanced-stage, high-grade serous ovarian cancer: Analysis of HE4 kinetics during NACT, predicting surgical outcome and recurrence in comparison to CA125

OBJECTIVES

To assess the prognostic value of human epididymis protein 4 (HE4) kinetics during and after neoadjuvant chemotherapy (NACT) cycles compared with cancer antigen 125 (CA-125), in predicting the surgical outcomes of interval debulking surgery (IDS) in patients with advanced-stage, high-grade serous ovarian cancer.

METHODS

This retrospective cohort study was conducted at Severance Hospital in Seoul, South Korea and involved 123 women with high-grade serous epithelial ovarian, fallopian tube, or primary peritoneal cancer who were diagnosed between April 2015 and July 2020. Three outcomes were considered: the chemotherapy response score (CRS) by omentum, residual disease after IDS, and recurrence. Other clinical, imaging, and biological parameters at baseline, during NACT cycles, and pre- and postoperative time were collected and analyzed.

RESULTS

We observed a substantial and gradual decrease in both CA-125 level (median from 1612 to 85.55 U/mL; p < 0.001) and HE4 level (514.7 to 87.7 pmol/L; p < 0.001) during NACT cycles, while pre-to-postoperative reduction was only significant for HE4 (median from 77.3 to 62.0 pmol/L (p < 0.001)). Of the total patients, 4.1% showed no response to NACT (chemoresistance) and 65.9% had a partial response. Residual disease was observed in 55 (44.7%) patients. Recurrence occurred in 90 patients (73.2%), with a median progression-free survival of 15.28 months. The percent reduction in CA-125 level- but not HE4 - during NACT was significantly associated with CRS (by omentum); the reduction in CA-125 during NACT cycles was higher when the CRS was found to be 3 and 2 (median = 96.4 [IQR = 8.3] and 93.7 [12.2] respectively) compared to score 1 (68.3 [34.1]), and the difference was statistically significant (p = 0.004). However, no significant association was observed between the percent reduction in CA-125 or HE4 levels during NACT and residual disease or recurrence. The normalization of HE4 - but not CA-125 - before surgery was predictive for surgery outcome; that is, an abnormal preop HE4 level was associated with a residual disease risk ratio of 2.72 (95% CI = 1.27-5.79).

CONCLUSION

Monitoring HE4 or CA-125 levels has low prognostic value in patients with advanced-stage, high-grade serous ovarian cancer who are treated with NACT followed by IDS. However, the preoperative level of the HE4 biomarker may be useful in identifying patients at higher risk for suboptimal cytoreductive surgery or who may require more extensive surgery. Further prospective studies are warranted to explore the prognostic utility of eventual combinations of clinical, radiological, and biological parameters, notably by using artificial intelligence-based models.

Response to treatment and prognostic significance of supradiaphragmatic disease in patients with high-grade serous ovarian cancer

OBJECTIVES

This study was designed to investigate the response to chemotherapy of supradiaphragmatic disease diagnosed by preoperative imaging. As secondary objectives, oncologic outcomes of patients affected by supradiaphragmatic disease and their pattern of recurrence were also evaluated.

METHODS

Data of consecutive patients with newly diagnosed FIGO stage IV (for supradiaphragmatic disease) epithelial ovarian cancer undergoing either primary debulking surgery or neoadjuvant chemotherapy plus interval debulking surgery between 2004 and 2021, were retrospectively collected. All patients were preoperatively evaluated by chest/abdominal CT scan or ¹⁸F-FDG PET/CT preoperatively and at follow-up to evaluate response to chemotherapy. At follow-up visits, site of recurrence diagnosed by imaging techniques was systematically recorded as it occurred. Progression-free and overall survival were measured by using Kaplan-Meier and Cox models.

RESULTS

A total of 130 patients was included in this study with a median (range) follow-up of 32.9 (12.8-176.7) months. Complete or partial response was achieved in most of the patients after 3 cycles (77.7%) and 6 cycles (85.4%) of chemotherapy. At follow-up, recurrence occurred in 96 (73.8%) patients and the main site of recurrence was abdomen only in 64 (66.7%) patients. At multivariate analysis, residual disease after surgery was the only variable influencing survival outcomes.

CONCLUSIONS

Supradiaphragmatic disease respond to chemotherapy in most patients affected by advanced EOC and recurrence mainly occurs in the abdomen. Results from this study confirms that abdominal optimal cytoreduction is the main surgical goal in the treatment of women affected by FIGO stage IV EOC.

Clinical usefulness of circulating tumor markers

Tumor markers are a heterogeneous group of substances released by cancer cells into bloodstream, but also expressed by healthy tissues. Thus, very small concentrations can be present in plasma and serum from healthy subjects. Cancer patients tend to show increased levels correlating with tumor bulk, but false positive results could be present in patients with benign conditions. The correct interpretation of TM results could be challenging and many factors should be considered, from pre-analytical conditions to patient concomitant diseases. In this line, the Clinical Chemistry and Laboratory Medicine journal has made important contributions though several publications promoting the adequate use of TM and therefore improving patient safety. TM measurement offers valuable information for cancer patient management in different clinical contexts, such as helping diagnosis, estimating prognosis, facilitating early detection of relapse and monitoring therapy response. Our review analyzes the clinical usefulness of tumor markers applied in most frequent epithelial tumors, based on recent evidence and guidelines.

Preoperative PET/CT score can predict incomplete resection after debulking surgery for advanced serous ovarian cancer better than CT score, MTV, tumor markers and hematological markers

INTRODUCTION

Complete resection after debulking surgery is strongly associated with prolonged survival for advanced serous ovarian cancer (ASOC). Though positron emission tomography/computed tomography (PET/CT) is more advantageous than computed tomorgraphy (CT) for detecting metastases, studies on the PET/CT prediction model for incomplete resection for ovarian cancer are insufficient. We analyzed and compared the predictive value of preoperative PET/CT score, CT score, metabolic parameters, tumor markers and hematological markers for incomplete resection after debulking surgery for ASOC.

MATERIAL AND METHODS

A total of 62 ASOC patients who underwent preoperative [¹⁸ F]FDG PET/CT and debulking surgery were retrospectively analyzed. PET/CT and CT scores were based on the Suidan model. The predictive value of PET/CT score, CT score, the maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), human epididymis protein 4 (HE4), cancer antigen 125 (CA125), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR) for incomplete resection were analyzed and compared.

RESULTS

Preoperative PET/CT score had the highest predictive value for incomplete resection in primary debulking surgery group (sensitivity: 65.0%, specificity: 88.9%, area under the ROC curve (AUC): 0.847, p < 0.001), however, in secondary debulking surgery group, preoperative PET/CT score and CT score had the same and highest predictive value for incomplete resection (sensitivity: 80.0%, specificity: 94.7%, AUC: 0.853, p = 0.017), compared with preoperative metabolic parameters SUVmax and MTV, tumor markers HE4 and CA125, and hematological markers LMR, PLR and NLR. Preoperative PET/CT score ≥ 3 (Suidan model) and preoperative PET/CT score ≥ 2 predicted a high risk of incomplete resection after primary and secondary debulking surgeries, respectively. There was no statistical difference between primary and secondary debulking surgery groups in predictive value of PET/CT score for incomplete resection (p = 0.971). There were significant differences between PET/CT scores and CT scores in primary debulking surgery group and no significant differences in secondary debulking surgery group.

CONCLUSIONS

A high PET/CT score predicted a high risk of incomplete resection. The preoperative PET/CT score had an identical predictive value in primary and secondary debulking surgery groups. PET/CT score was more accurate in the detection of metastases than CT score was.