Preoperative 18F-FDG PET/CT tumor markers outperform MRI-based markers for the prediction of lymph node metastases in primary endometrial cancer

PET/MRI in Endometrial Cancer: Imaging Biomarkers are Associated with Disease Progression and Overall Survival

RATIONALE AND OBJECTIVES

To evaluate the association between positron emission tomography (PET)/magnetic resonance imaging (MRI) biomarkers and survival outcomes in patients with endometrial cancer.

MATERIALS AND METHODS

Between April 2014 and April 2016, 88 patients with newly diagnosed endometrial cancer participated this prospective study and underwent [18F] fluorodeoxyglucose PET/MRI. Sixty-nine patients with measurable tumors on PET/MRI were included in the image analysis. Imaging biomarkers included the minimum and mean apparent diffusion coefficients (ADCmin and ADCmean), maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the primary tumors. The log-rank test and Cox proportional hazards model were used to assess the relationship between imaging biomarkers and survival.

RESULTS

After a median follow-up of 80 months, 15 (22%) patients had tumor progression and six (9%) patients died. The results of ADCmin, ADCmean, and SUVmax did not show a significant association with progression-free survival (PFS) and overall survival (OS). Significantly shorter PFS was noted in patients with primary tumors with higher MTV (P < 0.001) and TLG (P < 0.001). Significantly shorter OS was also noted in patients with primary tumors with higher MTV (P = 0.048) and TLG (P = 0.034). In the multivariate analysis, MTV was an independent predictor of PFS (hazard ratio = 10.84, P = 0.033).

CONCLUSION

PET/MRI biomarkers, particularly MTV and TLG, are associated with PFS and OS in patients with endometrial cancer. MTV was an independent predictor of PFS.

Retrospective analysis of the 18F-FDG PET/CT cutoff value for metabolic parameters was performed as a prediction model to evaluate risk factors for endometrial cancer

PURPOSE

The study retrospectively analyzed the accuracy and predictive ability of preoperative integrated whole-body 18F-FDG PET/CT for the assessment of high-risk factors in patients with endometrial carcinoma (EC).

MATERIALS AND METHODS

A total of 205 patients with endometrial cancer who underwent preoperative PET/CT at Shanghai General Hospital from January 2018 to December 2021 were retrospectively evaluated and last follow-up was June 2023. Our study evaluated the ability and optimal cutoff values of three metabolic and volumetric parameters-standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG)-to predict deep myometrial invasion (DMI), endocervical stroma invasion (ESI) and lymph node metastases (LNM) in endometrial cancer. The accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of PET/CT were used to assess the diagnostic performance for the prediction.

RESULTS

Our study demonstrated a significant relationship between SUVmax (11.29, 17.38, 9.47), SUVmean (5.20, 6.12, 4.49), MTV (38.15, 36.28, 33.79 ml), and TLG (199.30, 225.10, 156.40 g) on PET/CT and histologically confirmed DMI, ESI and LNM in endometrial carcinoma (EC), with sensitivity, specificity, accuracy, PPV, and NPV of 100%/100%/100%, 96.53%/98.89%/87.14%, 97.56%/99.02%/91.22%, 92.42%/92.85%/78.31%, and 100%/100%/100%, respectively. Our study showed a risk model based on optimal cutoff values for MTV and TLG of 19.6 ml/126.3 g, 20.54 ml/84.80 g and 24 ml/49.83 g to preoperatively predict DMI, ESI, and LNM, respectively, in endometrial carcinoma. The 4-year OS (HR) for Stage IA, IB, II, III and IV according to 2009 FIGO was 98.00% (0.22), 95.20% (0.04), 83.90% (0.18), 90.50% (0.09) and 60% (0.51). Accordingly, estimated 4-year DFS (HR) for the stage IA-III was 98% (0.02), 95.20% (0.05), 76.90% (0.27) and 76.30% (0.35), all the patients in stage IV occurred recurrence and progression.

CONCLUSION

The present study showed patients with MTV > = 19.6 ml of MI and PET- positive LN with MTV cutoff > = 24 ml tended to predict poor OS and PFS in endometrial carcinoma. The cutoff of MTV and TLG in PET/CT assessment could be an independent prognostic factors to predict aggressive forms of EC.

Prognostic value of 18F-FDG PET/CT in malignant pleural mesothelioma: a meta-analysis

BACKGROUND

Several FDG PET/CT parameters have been utilized to evaluate the prognosis in malignant pleural mesothelioma (MPM). However, there are still controversial results due to the low incidence of MPM.

PURPOSE

To assess the prognostic value of 18F-FDG PET/CT in MPM.

MATERIAL AND METHODS

A systematic literature search was performed in PubMed, Embase, Medline, and The Cochrane Library to identify eligible studies from inception to 12 February 2020. The pooled hazard ratios (HRs) and 95% confidence intervals (CIs) of several variables, such as maximum standardized uptake value (SUV_max), the reduction of SUV_max after treatment (ΔSUV_max), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and the reduction of TLG after treatment (ΔTLG), were calculated. Meta-regression with subsequent subgroup analyses were conducted to determine the heterogeneity of cutoff values, treatment regimen, study design, uptake time, and scanners across various studies.

RESULTS

In total, 19 eligible studies including 1819 patients were enrolled in the meta-analysis. The univariate analysis showed that the pooled HRs (95% CI) of SUV_max, ΔSUV_max, MTV, TLG, and ΔTLG were 1.29 (1.16-1.42), 1.12 (1.05-1.19), 1.15 (1.00-1.33), 1.47 (1.23-1.76), and 1.27 (1.12-1.45), respectively. The multivariate analysis showed that the pooled HRs (95% CI) of SUV_max, ΔSUV_max, MTV, and TLG for overall survival (OS) were 1.20 (1.08-1.33), 1.10 (1.02-1.19), 0.95 (0.81-1.11), and 1.13 (1.08-1.18), respectively.

CONCLUSION

SUV_max, ΔSUV_max, TLG, and ΔTLG are significant prognostic indicators for OS, while more clinical studies are needed to confirm the prognostic value of MTV in MPM.

Risk stratification of endometrial cancer and lymph node metastases prediction using 18F-FDG PET/CT: role of metabolic tumor volume and total lesion glycolysis

Background

Endometrial cancer is the commonest gynecologic malignancy. Pelvic lymph node metastasis is considered one of its most important prognostic factors. Surgery is considered the most important and effective treatment, still there is controversy about indication and necessity of pelvic lymph node dissection. 18F-fluorodeoxyglucose positron emission tomography/computed tomography is investigated in his study to evaluate its value in preoperative detection of lymph node metastases and risk stratification of endometrial cancer.

Results

Reviewing the records of 33 women with endometrial cancer, all 18F-FDG PET/CT studied indices, SUVmax, SUVmean, MTV and TLG, mean difference was statistically significant in all the studied risk categories (tumor grade, Myometrial invasion, lymphovascular space invasion, tumor stage, and risk stratification). SUVmax and TLG showed highest area under the curve for detection of Myometrial invasion > 50% (AUC = 0.911) with cut-off value of SUVmax > 14.55 showing 88.89% sensitivity and 86.67% specificity, and TLG > 192.653 having 88.89% sensitivity and 80% specificity. TLG showed highest AUC (0.889 and 0.921) for detection of LVSI and LNMs with 100% sensitivity and 66.67% specificity for cut-off value > 179.374 and 88.89% sensitivity and 83.33% specificity for cut-off value > 249.366, respectively. Concerning risk stratification of EC, SUVmax and TLG showed highest AUC (0.839) with cut-off value > 14.55 showing 77.27% sensitivity and 90.91% specificity, and > 192.653 having 77.27% sensitivity and 81.82% specificity, respectively.

Conclusion

The results of this study suggest that 18F-FDG PET/CT is a very valuable tool for prediction of lymph node metastases and risk stratification in endometrial cancer patients. Applying TLG cutoff values increases the accuracy and preoperative diagnosis of lymph node metastases which aids in sparing women with low-risk early stage EC unnecessary surgical risk and morbidity of lymphadenectomy.

Development of machine learning models integrating PET/CT radiomic and immunohistochemical pathomic features for treatment strategy choice of cervical cancer with negative pelvic lymph node by mediating COX-2 expression

Objectives: We aimed to establish machine learning models based on texture analysis predicting pelvic lymph node metastasis (PLNM) and expression of cyclooxygenase-2 (COX-2) in cervical cancer with PET/CT negative pelvic lymph node (PLN).

Methods: Eight hundred and thirty-seven texture features were extracted from PET/CT images of 148 early-stage cervical cancer patients with negative PLN. The machine learning models were established by logistic regression from selected features and evaluated by the area under the curve (AUC). The correlation of selected PET/CT texture features predicting PLNM or COX-2 expression and the corresponding immunohistochemical (IHC) texture features was analyzed by the Spearman test.

Results: Fourteen texture features were reserved to calculate the Rad-score for PLNM and COX-2. The PLNM model predicting PLNM showed good prediction accuracy in the training and testing dataset (AUC = 0.817, p < 0.001; AUC = 0.786, p < 0.001, respectively). The COX-2 model also behaved well for predicting COX-2 expression levels in the training and testing dataset (AUC = 0.814, p < 0.001; AUC = 0.748, p = 0.001). The wavelet-LHH-GLCM ClusterShade of the PET image selected to predict PLNM was slightly correlated with the corresponding feature of the IHC image (r = −0.165, p < 0.05). There was a weak correlation of wavelet-LLL-GLRLM LongRunEmphasis of the PET image selected to predict COX-2 correlated with the corresponding feature of the IHC image (r = 0.238, p < 0.05). The correlation between PET image selected to predict COX-2 and the corresponding feature of the IHC image based on wavelet-LLL-GLRLM LongRunEmphasis is considered weak positive (r = 0.238, p=<0.05).

Conclusion: This study underlined the significant application of the machine learning models based on PET/CT texture analysis for predicting PLNM and COX-2 expression, which could be a novel tool to assist the clinical management of cervical cancer with negative PLN on PET/CT images.

PET-CTBased Quantitative Parameters for Assessment of Treatment Response and Disease Activity in Cancer and Noncancerous Disorders

The various semiquantitative and quantitative PET-CT parameters provide measurement of disease activity and assessment of treatment response in the PET-CT studies. These include standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG), and total metabolic tumor volume (TMTV). Thresholding and adaptive thresholding methods are commonly used algorithms for the evaluation of global disease activity. Readily available commercial software frequently in-built with the current generation PET-CT scanners for providing easy, less time consuming, highly reproducible, and more accurate measurement of global disease activity on PET-CT imaging in evaluation of malignant as well as benign disorders.

Preoperative pelvic MRI and 2-[18F]FDG PET/CT for lymph node staging and prognostication in endometrial cancer-time to revisit current imaging guidelines?

OBJECTIVE

This study presents the diagnostic performance of four different preoperative imaging workups (IWs) for prediction of lymph node metastases (LNMs) in endometrial cancer (EC): pelvic MRI alone (IW1), MRI and [¹⁸F]FDG-PET/CT in all patients (IW2), MRI with selective [¹⁸F]FDG-PET/CT if high-risk preoperative histology (IW3), and MRI with selective [¹⁸F]FDG-PET/CT if MRI indicates FIGO stage ≥ 1B (IW4).

METHODS

In 361 EC patients, preoperative staging parameters from both pelvic MRI and [¹⁸F]FDG-PET/CT were recorded. Area under receiver operating characteristic curves (ROC AUC) compared the diagnostic performance for the different imaging parameters and workups for predicting surgicopathological FIGO stage. Survival data were assessed using Kaplan-Meier estimator with log-rank test.

RESULTS

MRI and [¹⁸F]FDG-PET/CT staging parameters yielded similar AUCs for predicting corresponding FIGO staging parameters in low-risk versus high-risk histology groups (p ≥ 0.16). The sensitivities, specificities, and AUCs for LNM prediction were as follows: IW1-33% [9/27], 95% [185/193], and 0.64; IW2-56% [15/27], 90% [174/193], and 0.73 (p = 0.04 vs. IW1); IW3-44% [12/27], 94% [181/193], and 0.69 (p = 0.13 vs. IW1); and IW4-52% [14/27], 91% [176/193], and 0.72 (p = 0.06 vs. IW1). IW3 and IW4 selected 34% [121/361] and 54% [194/361] to [¹⁸F]FDG-PET/CT, respectively. Employing IW4 identified three distinct patient risk groups that exhibited increasing FIGO stage (p < 0.001) and stepwise reductions in survival (p ≤ 0.002).

CONCLUSION

Selective [¹⁸F]FDG-PET/CT in patients with high-risk MRI findings yields better detection of LNM than MRI alone, and similar diagnostic performance to that of MRI and [¹⁸F]FDG-PET/CT in all.

KEY POINTS

• Imaging by MRI and [¹⁸F]FDG PET/CT yields similar diagnostic performance in low- and high-risk histology groups for predicting central FIGO staging parameters. • Utilizing a stepwise imaging workup with MRI in all patients and [¹⁸F]FDG-PET/CT in selected patients based on MRI findings identifies preoperative risk groups exhibiting significantly different survival. • The proposed imaging workup selecting ~54% of the patients to [¹⁸F]FDG-PET/CT yield better detection of LNMs than MRI alone, and similar LNM detection to that of MRI and [¹⁸F]FDG-PET/CT in all.

Radiation therapy in the definitive management of medically inoperable endometrial cancer

The incidence of endometrial cancer continues to increase worldwide with growing life expectancy and rates of obesity. While endometrial cancer is primarily a surgical disease managed with hysterectomy, a small proportion of patients are deemed to be poor surgical candidates due to their co-morbidities. These medically inoperable patients should be considered for curative treatment with definitive radiation therapy, and brachytherapy is an integral component of their care. Referral to a high-volume center early on in the care of potentially inoperable patients is crucial to optimize their management. These patients should be evaluated by a high-risk surgical and anesthesia team to confirm their medical inoperability. For inoperable patients, use of image-guided brachytherapy is encouraged. Brachytherapy applicator selection is determined based on a patient’s anatomy, uterine size, and extent of tumor. Advances in anatomic and functional imaging including multiparametric magnetic resonance imaging (MRI) have improved clinical staging of these patients and have also allowed for the delivery of three-dimensional image-guided brachytherapy with improved accuracy. With recent consensus guidelines to guide local computed tomography and/or MRI volume-based delineation of targets and organs-at-risk, local outcomes have improved and treatments are delivered with less acute and late morbidity. Ongoing trials are looking at novel systemic agents, such as immunotherapy, to induce a systemic anti-tumor immune response and improve outcomes in these patients.

Risk Stratification of Endometrial Cancer Patients: FIGO Stage, Biomarkers and Molecular Classification

Endometrial cancer (EC) is the most common gynaecologic malignancy in developed countries. The main challenge in EC management is to correctly estimate the risk of metastases at diagnosis and the risk to develop recurrences in the future. Risk stratification determines the need for surgical staging and adjuvant treatment. Detection of occult, microscopic metastases upstages patients, provides important prognostic information and guides adjuvant treatment. The molecular classification subdivides EC into four prognostic subgroups: POLE ultramutated; mismatch repair deficient (MMRd); nonspecific molecular profile (NSMP); and TP53 mutated (p53abn). How surgical staging should be adjusted based on preoperative molecular profiling is currently unknown. Moreover, little is known whether and how other known prognostic biomarkers affect prognosis prediction independent of or in addition to these molecular subgroups. This review summarizes the factors incorporated in surgical staging (i.e., peritoneal washing, lymph node dissection, omentectomy and peritoneal biopsies), and its impact on prognosis and adjuvant treatment decisions in an era of molecular classification of EC. Moreover, the relation between FIGO stage and molecular classification is evaluated including the current gaps in knowledge and future perspectives.

Feasibility and utility of MRI and dynamic 18F-FDG-PET in an orthotopic organoid-based patient-derived mouse model of endometrial cancer

BACKGROUND

Pelvic magnetic resonance imaging (MRI) and whole-body positron emission tomography-computed tomography (PET-CT) play an important role at primary diagnostic work-up and in detecting recurrent disease in endometrial cancer (EC) patients, however the preclinical use of these imaging methods is currently limited. We demonstrate the feasibility and utility of MRI and dynamic 18F-fluorodeoxyglucose (FDG)-PET imaging for monitoring tumor progression and assessing chemotherapy response in an orthotopic organoid-based patient-derived xenograft (O-PDX) mouse model of EC.

METHODS

18 O-PDX mice (grade 3 endometrioid EC, stage IIIC1), selectively underwent weekly T2-weighted MRI (total scans = 32), diffusion-weighted MRI (DWI) (total scans = 9) and dynamic 18F-FDG-PET (total scans = 26) during tumor progression. MRI tumor volumes (vMRI), tumor apparent diffusion coefficient values (ADCmean) and metabolic tumor parameters from 18F-FDG-PET including maximum and mean standard uptake values (SUVmax/SUVmean), metabolic tumor volume (MTV), total lesion glycolysis (TLG) and metabolic rate of 18F-FDG (MRFDG) were calculated. Further, nine mice were included in a chemotherapy treatment study (treatment; n = 5, controls; n = 4) and tumor ADCmean-values were compared to changes in vMRI and cellular density from histology at endpoint. A Mann-Whitney test was used to evaluate differences between groups.

RESULTS

Tumors with large tumor volumes (vMRI) had higher metabolic activity (MTV and TLG) in a clear linear relationship (r2 = 0.92 and 0.89, respectively). Non-invasive calculation of MRFDG from dynamic 18F-FDG-PET (mean MRFDG = 0.39 μmol/min) was feasible using an image-derived input function. Treated mice had higher tumor ADCmean (p = 0.03), lower vMRI (p = 0.03) and tumor cellular density (p = 0.02) than non-treated mice, all indicating treatment response.

CONCLUSION

Preclinical imaging mirroring clinical imaging methods in EC is highly feasible for monitoring tumor progression and treatment response in the present orthotopic organoid mouse model.

Nomograms of Combining Apparent Diffusion Coefficient Value and Radiomics for Preoperative Risk Evaluation in Endometrial Carcinoma

Objectives

To evaluate the value of nomogram models combining apparent diffusion coefficient (ADC) value and radiomic features on magnetic resonance imaging (MRI) in predicting the type, grade, deep myometrial invasion (DMI), lymphovascular space invasion (LVSI), and lymph node metastasis (LNM) of endometrial carcinoma (EC) preoperatively.

Methods

This study included 210 EC patients. ADC value was calculated, and radiomic features were measured on T2-weighted images. The univariate and multivariate logistic regressions and cross-validations were performed to reduce valueless features, then radiomics signatures were developed. Nomogram models using ADC combined with radiomic features were developed in the training cohort. The receiver operating characteristic (ROC) curve was performed to estimate the diagnostic efficiency of nomogram models by the area under the curve (AUC) in the training and validation cohorts.

Results

The ADC value was significantly different between each subgroup. Radiomic features were ultimately limited to four features for type, six features for grade, six features for DMI, four features for LVSI, and eight features for LNM for the nomogram models. The AUC of the nomogram model combining ADC value and radiomic features in the training and validation cohorts was 0.851 and 0.867 for type, 0.959 and 0.880 for grade, 0.839 and 0.766 for DMI, 0.816 and 0.746 for LVSI, and 0.910 and 0.897 for LNM.

Conclusions

The nomogram models of ADC value combined with radiomic features were associated with the type, grade, DMI, LVSI, and LNM of EC, and provide an effective, non-invasive method to evaluate preoperative risk stratification for EC.

FDG-PET/CT and Para-Aortic Staging in Endometrial Cancer. A French Multicentric Study

BACKGROUND

FDG-PET/CT is a noninvasive examination that could be helpful for the management of endometrial cancer. The aim of this study was to evaluate the performance of FDG-PET/CT in assessing para-aortic lymph-node involvement in high-risk endometrial cancer.

METHODS

We performed a retrospective multicenter study including all patients who had a high-risk endometrial cancer with a preoperative FDG-PET/CT and a para-aortic lymphadenectomy (PAL) between 2009 and 2019. The main objective was to evaluate the overall performance of FDG-PET/CT. The secondary objectives were to evaluate its performances according to the histological type and according to FDG-PET/CT date (before or after hysterectomy), and to compare its overall performance with that of the MRI scan.

RESULTS

We included 200 patients from six different centers. After the false positive FDG-PET/CT was reread by nuclear physicians, FDG-PET/CT had a sensitivity of 61.8%, a specificity of 89.7%, a positive predictive value of 69.4%, a negative predictive value of 86.1%, and an AUC of 0.76. There were no statistically significant differences in the performances according to either histological type and or FDG-PET/CT date. The sensitivity of FDG-PET/CT was better than that of MRI (p < 0.01), but the specificity was not (p = 0.82).

CONCLUSION

Currently, FDG-PET/CT alone cannot replace PAL for the lymph node evaluation of high-risk endometrial cancers. It seems essential to reread it in multidisciplinary meetings before validating the therapeutic management of patients, particularly in the case of isolated para-aortic involvement.

Whole-Volume Tumor MRI Radiomics for Prognostic Modeling in Endometrial Cancer

Background

In endometrial cancer (EC), preoperative pelvic MRI is recommended for local staging, while final tumor stage and grade are established by surgery and pathology. MRI‐based radiomic tumor profiling may aid in preoperative risk‐stratification and support clinical treatment decisions in EC.

Purpose

To develop MRI‐based whole‐volume tumor radiomic signatures for prediction of aggressive EC disease.

Study Type

Retrospective.

Population

A total of 138 women with histologically confirmed EC, divided into training (n_T = 108) and validation cohorts (n_V = 30).

Field Strength/Sequence

Axial oblique T₁‐weighted gradient echo volumetric interpolated breath‐hold examination (VIBE) at 1.5T (71/138 patients) and DIXON VIBE at 3T (67/138 patients) at 2 minutes postcontrast injection.

Assessment

Primary tumors were manually segmented by two radiologists with 4 and 8 years' of experience. Radiomic tumor features were computed and used for prediction of surgicopathologically‐verified deep (≥50%) myometrial invasion (DMI), lymph node metastases (LNM), advanced stage (FIGO III + IV), nonendometrioid (NE) histology, and high‐grade endometrioid tumors (E3). Corresponding analyses were also conducted using radiomics extracted from the axial oblique image slice depicting the largest tumor area.

Statistical Tests

Logistic least absolute shrinkage and selection operator (LASSO) was applied for radiomic modeling in the training cohort. The diagnostic performances of the radiomic signatures were evaluated by area under the receiver operating characteristic curve in the training (AUC_T) and validation (AUC_V) cohorts. Progression‐free survival was assessed using the Kaplan–Meier and Cox proportional hazard model.

Results

The whole‐tumor radiomic signatures yielded AUC_T/AUC_V of 0.84/0.76 for predicting DMI, 0.73/0.72 for LNM, 0.71/0.68 for FIGO III + IV, 0.68/0.74 for NE histology, and 0.79/0.63 for high‐grade (E3) tumor. Single‐slice radiomics yielded comparable AUC_T but significantly lower AUC_V for LNM and FIGO III + IV (both P < 0.05). Tumor volume yielded comparable AUC_T to the whole‐tumor radiomic signatures for prediction of DMI, LNM, FIGO III + IV, and NE, but significantly lower AUC_T for E3 tumors (P < 0.05). All of the whole‐tumor radiomic signatures significantly predicted poor progression‐free survival with hazard ratios of 4.6–9.8 (P < 0.05 for all).

Data Conclusion

MRI‐based whole‐tumor radiomic signatures yield medium‐to‐high diagnostic performance for predicting aggressive EC disease. The signatures may aid in preoperative risk assessment and hence guide personalized treatment strategies in EC.

Level of Evidence

4

Technical Efficacy Stage

2