Diagnostic accuracy of preoperative 18F-FDG PET or PET/CT in detecting pelvic and para-aortic lymph node metastasis in patients with endometrial cancer: a systematic review and meta-analysis

Prediction of Lymph Node Metastasis in Endometrial Cancer Based on Color Doppler Ultrasound Radiomics

RATIONALE AND OBJECTIVES

To construct a model using radiomics features based on ultrasound images and evaluate the feasibility of noninvasive assessment of lymph node status in endometrial cancer (EC) patients.

METHODS

In this multicenter retrospective study, a total of 186 EC patients who underwent hysterectomy and lymph node dissection were included, Pathology confirmed the presence or absence of lymph node metastasis (LNM). The study encompassed patients from seven centers, spanning from September 2018 to November 2023, with 93 patients in each group (with or without LNM). Extracted ultrasound radiomics features from transvaginal ultrasound images, used five machine learning (ML) algorithms to establish US radiomics models, screened clinical features through univariate and multivariate logistic regression to establish a clinical model, and combined clinical and radiomics features to establish a nomogram model. The diagnostic ability of the three models for LNM with EC was compared, and the diagnostic performance and accuracy of the three models were evaluated using receiver operating characteristic curve analysis.

RESULTS

Among the five ML models, the XGBoost model performed the best, with AUC values of 0.900 (95% CI, 0.847-0.950) and 0.865 (95% CI, 0.763-0.950) for the training and testing sets, respectively. In the final model, the nomogram based on clinical features and the ultrasound radiomics showed good resolution, with AUC values of 0.919 (95% CI, 0.874-0.964) and 0.884 (0.801-0.967) in the training and testing sets, respectively. The decision curve analysis verified the clinical practicality of the nomogram.

CONCLUSION

The ML model based on ultrasound radiomics has potential value in the noninvasive differential diagnosis of LNM in patients with EC. The nomogram constructed by combining ultrasound radiomics and clinical features can provide clinical doctors with more comprehensive and personalized image information, which is highly important for selecting treatment strategies.

A meta-analysis of the effect of pelvic and para-aortic lymph node dissection on the prognosis of patients with endometrial cancer

Endometrial cancer (EC) is the second most common malignant tumor of the female reproductive system, and it occurs in the peri- and post-menopausal periods. The metastasis routes of EC include direct spread, hematogenous metastasis and lymph node metastasis. Symptoms such as vaginal discharge or irregular vaginal bleeding may occur in the early stage. The pathological stage of the patients treated at this time is mostly in the early stage, and comprehensive treatment such as surgery, radiotherapy and chemotherapy can improve the prognosis. This article investigates whether endometrial cancer requires pelvic and para-aortic lymph node dissection. The clinical data of 228 patients with endometrial cancer who underwent pelvic lymphadenectomy in our hospital from July 2020 to September 2021 were retrospectively analyzed. All patients underwent preoperative clinical staging and postoperative pathological staging. This paper compared lymph node spread rates of endometrial carcinoma in different stages, depth of muscle invasion, and pathological characteristics to analyze lymph node metastasis risk factors. Results showed metastasis rates of 7.5% in 228 cases of endometrial cancer, increasing with deeper myometrial invasion. Different clinicopathological factors had varying lymph node spread rates. Different clinicopathological factors have different pelvic lymph node spread rates in surgical patients. The lymph node spread rate of differentially differentiated carcinoma is higher than that of well-differentiated carcinoma. The lymph node spread rate of serous carcinoma is 100%, but there is no difference between the lymph node metastasis rate of special type carcinoma and adenocarcinoma. Statistical significance (P > 0.05).

Role of ultrasound in detection of lymph-node metastasis in gynecological cancer: systematic review and meta-analysis

OBJECTIVE

To assess the diagnostic performance of transvaginal sonography (TVS) for the preoperative evaluation of lymph-node metastasis in gynecological cancer.

METHODS

This was a systematic review and meta-analysis of studies published between January 1990 and May 2023 evaluating the role of ultrasound in detecting pelvic lymph-node metastasis (index test) in gynecological cancer, using histopathological analysis as the reference standard. The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Pooled sensitivity, specificity and diagnostic odds ratio were estimated.

RESULTS

The literature search identified 2638 citations. Eight studies reporting on a total of 967 women were included. The mean prevalence of pelvic lymph-node metastasis was 24.2% (range, 14.0-65.6%). The risk of bias was low for most domains assessed. Pooled sensitivity, specificity and diagnostic odds ratio of TVS were 41% (95% CI, 26-58%), 98% (95% CI, 93-99%) and 32 (95% CI, 14-72), respectively. High heterogeneity was found between studies for both sensitivity and specificity.

CONCLUSION

TVS showed a high pooled specificity for the detection of pelvic lymph-node metastasis in gynecological cancer, but pooled sensitivity was low. © 2024 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Diagnostic role of F-18 FDG PET/CT in determining preoperative Lymph node status of patients with rectal cancer: a meta-analysis

PURPOSE

To obtain performance values of PET/CT for determining the nodal status of rectal cancer.

MATERIALS

A comprehensive literature search was performed on PubMed and Embase for original diagnostic accuracy studies on the diagnostic performance of PET-CT for detection of LN metastasis in rectal cancer. The QUADAS-2 was used to evaluate the methodological quality of each study. Pooled sensitivity, specificity, and AUC were calculated to estimate the diagnostic role of PET/CT using a random-effects model. A subgroup analysis was performed to investigate the influence of different parameters on diagnostic performance.

RESULTS

A total of 15 studies and 1209 patients were included. A publication bias was observed. The pooled sensitivity, specificity, and AUC for PET/CT was 0.62 (95% CI 0.49, 0.74), 0.94 (95% CI 0.87, 0.97), and 0.87 (95% CI 0.83-0.89), respectively. Per-node basis yields higher accuracy than per-patient basis, with pooled sensitivities of 0.65 (95% CI 0.50-0.79) vs. 0.56 (95% CI 0.36-0.77) and specificities of 0.96 (95% CI 0.92-1.00) vs. 0.88 (95% CI 0.76-1.00), but there were no significant differences in diagnostic accuracy.

CONCLUSION

PET/CT has high specificity but moderate sensitivity for the detection of LN metastasis in rectal cancer. The current data suggests that the diagnostic capabilities of this method is limited due to its moderate sensitivity.

Staging by imaging in gynecologic cancer and the role of ultrasound: an update of European joint consensus statements

In recent years the role of diagnostic imaging by pelvic ultrasound in the diagnosis and staging of gynecological cancers has been growing exponentially. Evidence from recent prospective multicenter studies has demonstrated high accuracy for pre-operative locoregional ultrasound staging in gynecological cancers. Therefore, in many leading gynecologic oncology units, ultrasound is implemented next to pelvic MRI as the first-line imaging modality for gynecological cancer. The work herein is a consensus statement on the role of pre-operative imaging by ultrasound and other imaging modalities in gynecological cancer, following European Society guidelines.

The value of machine learning in preoperative identification of lymph node metastasis status in endometrial cancer: a systematic review and meta-analysis

Background

The early identification of lymph node metastasis status in endometrial cancer (EC) is a serious challenge in clinical practice. Some investigators have introduced machine learning into the early identification of lymph node metastasis in EC patients. However, the predictive value of machine learning is controversial due to the diversity of models and modeling variables. To this end, we carried out this systematic review and meta-analysis to systematically discuss the value of machine learning for the early identification of lymph node metastasis in EC patients.

Methods

A systematic search was conducted in Pubmed, Cochrane, Embase, and Web of Science until March 12, 2023. PROBAST was used to assess the risk of bias in the included studies. In the process of meta-analysis, subgroup analysis was performed according to modeling variables (clinical features, radiomic features, and radiomic features combined with clinical features) and different types of models in various variables.

Results

This systematic review included 50 primary studies with a total of 103,752 EC patients, 12,579 of whom had positive lymph node metastasis. Meta-analysis showed that among the machine learning models constructed by the three categories of modeling variables, the best model was constructed by combining radiomic features with clinical features, with a pooled c-index of 0.907 (95%CI: 0.886-0.928) in the training set and 0.823 (95%CI: 0.757-0.890) in the validation set, and good sensitivity and specificity. The c-index of the machine learning model constructed based on clinical features alone was not inferior to that based on radiomic features only. In addition, logistic regression was found to be the main modeling method and has ideal predictive performance with different categories of modeling variables.

Conclusion

Although the model based on radiomic features combined with clinical features has the best predictive efficiency, there is no recognized specification for the application of radiomics at present. In addition, the logistic regression constructed by clinical features shows good sensitivity and specificity. In this context, large-sample studies covering different races are warranted to develop predictive nomograms based on clinical features, which can be widely applied in clinical practice.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO, identifier CRD42023420774.

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.

Clinical issues of surgery for uterine endometrial cancer in Japan

OBJECTIVE

The mainstay of treatment for uterine endometrial cancer is surgery, and recurrent-risk cases require multidisciplinary treatment, including surgery, chemotherapy and radiation therapy.

METHODS

The standard surgery for uterine endometrial cancer is hysterectomy and bilateral salpingooophorectomy, with additional retroperitoneal lymph node dissection and omentectomy, depending on the case. The appropriate treatment is determined based on the risk classification, such as the depth of invasion into the myometrium, diagnosis of histological type and grade, and risk assessment of lymph node metastasis.

RESULTS

Recently, minimally invasive surgery has been widely used not only in low-risk patients but also in intermediate- and high-risk patients. In low-risk patients, the possibility of ovarian preservation is discussed from a healthcare perspective for young women. Determining the need for retroperitoneal lymph node dissection based on sentinel lymph node evaluation may contribute in minimizing the incidence of post-operative lymphedema while ensuring accurate diagnosis of lymph node metastasis. Recently, many studies using sentinel lymph nodes have been reported for patients with uterine endometrial cancer, and the feasibility of sentinel lymph node mapping surgery has been proven. Unfortunately, sentinel lymph node biopsy and sentinel lymph node mapping surgery have not been widely adopted in surgery for uterine cancer in Japan. In addition, the search for biomarkers, such as RNA sequencing using The Cancer Genome Atlas, metabolic profile and lipidomic profile for early detection and prognostic evaluation, has been actively pursued.

CONCLUSIONS

Gynecologic oncologists expect to be able to provide uterine endometrial cancer patients with appropriate treatment that preserves their quality of life without compromising oncologic outcomes in the near future.

Diagnostic Accuracy of FEC-PET/CT, FDG-PET/CT, and Diffusion-Weighted MRI in Detection of Nodal Metastases in Surgically Treated Endometrial and Cervical Carcinoma

PURPOSE

Preoperative nodal staging is important for planning treatment in cervical cancer and endometrial cancer, but remains challenging. We compare nodal staging accuracy of 18F-ethyl-choline-(FEC)-PET/CT, 18F-fluoro-deoxy-glucose-(FDG)-PET/CT, and diffusion-weighted-MRI (DW-MRI) with conventional morphologic MRI.

EXPERIMENTAL DESIGN

A prospective, multicenter observational study of diagnostic accuracy for nodal metastases was undertaken in 5 gyne-oncology centers. FEC-PET/CT, FDG-PET/CT, and DW-MRI were compared with nodal size and morphology on MRI. Reference standard was strictly correlated nodal histology. Eligibility included operable cervical cancer stage ≥ 1B1 or endometrial cancer (grade 3 any stage with myometrial invasion or grade 1-2 stage ≥ II).

RESULTS

Among 162 consenting participants, 136 underwent study DW-MRI and FDG-PET/CT and 60 underwent FEC-PET/CT. In 118 patients, 267 nodal regions were strictly correlated at histology (nodal positivity rate, 25%). Sensitivity per patient (n = 118) for nodal size, morphology, DW-MRI, FDG- and FEC-PET/CT was 40%*, 53%, 53%, 63%*, and 67% for all cases (*, P = 0.016); 10%, 10%, 20%, 30%, and 25% in cervical cancer (n = 40); 65%, 75%, 70%, 80% and 88% in endometrial cancer (n = 78). FDG-PET/CT outperformed nodal size (P = 0.006) and size ratio (P = 0.04) for per-region sensitivity. False positive rates were all <10%.

CONCLUSIONS

All imaging techniques had low sensitivity for detection of nodal metastases and cannot replace surgical nodal staging. The performance of FEC-PET/CT was not statistically different from other techniques that are more widely available. FDG-PET/CT had higher sensitivity than size in detecting nodal metastases. False positive rates were low across all methods. The low false positive rate demonstrated by FDG-PET/CT may be helpful in arbitration of challenging surgical planning decisions.

Establishment of a Diagnostic Method for Pelvic Sentinel Lymph Node Metastasis by Contrast-Enhanced Ultrasound in Uterine Cancer

This study investigated the usefulness of conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS) in distinguishing metastasis of pelvic sentinel lymph nodes (SLNs) in patients with gynecological cancer. We examined 74 SLNs of patients with endometrial cancer (n = 26) and cervical cancer (n = 11). Patients underwent US and CEUS followed by SLN biopsy; US and CEUS results were evaluated visually and quantitatively and compared between pathological metastasis-negative and -positive groups. To support CEUS results, the microvessel density of SLNs was evaluated immunohistochemically. Seventeen positive and 40 negative SLNs were evaluable. Margin and enhancement patterns by visual assessment revealed significant differences (p = 0.046 and 0.022, respectively). In quantitative time-intensity curve analyses, the weakest peak intensities (PI_min), PI ratio and PI difference indicated significant differences (p = 0.045, p < 0.001 and p < 0.001, respectively). The areas under the receiver operating characteristic curves (AUCs) were 0.64, 0.82 and 0.83, respectively. The most effective PI ratio from the AUC was 1.3 (sensitivity = 82%, specificity = 70%), and the PI difference from the AUC was 20 (sensitivity = 88%, specificity = 70%). Microvessel density was significantly lower in metastatic lesions than in other areas. The quantitative analysis of CEUS seemed to be a reasonable method for distinguishing lymph node metastasis in patients with gynecological cancer.

Radiologists with MRI-based radiomics aids to predict the pelvic lymph node metastasis in endometrial cancer: a multicenter study

OBJECTIVE

To construct a MRI radiomics model and help radiologists to improve the assessments of pelvic lymph node metastasis (PLNM) in endometrial cancer (EC) preoperatively.

METHODS

During January 2014 and May 2019, 622 EC patients (age 56.6 ± 8.8 years; range 27-85 years) from five different centers (A to E) were divided into training set, validation set 1 (351 cases from center A), and validation set 2 (271 cases from centers B-E). The radiomics features were extracted basing on T2WI, DWI, ADC, and CE-T1WI images, and most related radiomics features were selected using the random forest classifier to build a radiomics model. The ROC curve was used to evaluate the performance of training set and validation sets, radiologists based on MRI findings alone, and with the aid of the radiomics model. The clinical decisive curve (CDC), net reclassification index (NRI), and total integrated discrimination index (IDI) were used to assess the clinical benefit of using the radiomics model.

RESULTS

The AUC values were 0.935 for the training set, 0.909 and 0.885 for validation sets 1 and 2, 0.623 and 0.643 for the radiologists 1 and 2 alone, and 0.814 and 0.842 for the radiomics-aided radiologists 1 and 2, respectively. The AUC, CDC, NRI, and IDI showed higher diagnostic performance and clinical net benefits for the radiomics-aided radiologists than for the radiologists alone.

CONCLUSIONS

The MRI-based radiomics model could be used to assess the status of pelvic lymph node and help radiologists improve their performance in predicting PLNM in EC.

KEY POINTS

• A total of 358 radiomics features were extracted. The 37 most important features were selected using the random forest classifier. • The reclassification measures of discrimination confirmed that the radiomics-aided radiologists performed better than the radiologists alone, with an NRI of 1.26 and an IDI of 0.21 for radiologist 1 and an NRI of 1.37 and an IDI of 0.24 for radiologist 2.

Combining positron emission tomography/computed tomography, radiomics, and sentinel lymph node mapping for nodal staging of endometrial cancer patients

OBJECTIVE

To evaluate the combination of positron emission tomography/computed tomography (PET/CT) and sentinel lymph node (SLN) biopsy in women with apparent early-stage endometrial carcinoma. The correlation between radiomics features extracted from PET images of the primary tumor and the presence of nodal metastases was also analyzed.

METHODS

From November 2006 to March 2019, 167 patients with endometrial cancer were included. All women underwent PET/CT and surgical staging: 60/167 underwent systematic lymphadenectomy (Group 1) while, more recently, 107/167 underwent SLN biopsy (Group 2) with technetium-99m +blue dye or indocyanine green. Histology was used as standard reference. PET endometrial lesions were segmented (n=98); 167 radiomics features were computed inside tumor contours using standard Image Biomarker Standardization Initiative (IBSI) methods. Radiomics features associated with lymph node metastases were identified (Mann-Whitney test) in the training group (A); receiver operating characteristic (ROC) curves, area under the curve (AUC) values were computed and optimal cut-off (Youden index) were assessed in the test group (B).

RESULTS

In Group 1, eight patients had nodal metastases (13%): seven correctly ridentified by PET/CT true-positive with one false-negative case. In Group 2, 27 patients (25%) had nodal metastases: 13 true-positive and 14 false-negative. Sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of PET/CT for pelvic nodal metastases were 87%, 94%, 93%, 70%, and 98% in Group 1 and 48%, 97%, 85%, 87%, and 85% in Group 2, respectively. On radiomics analysis a significant association was found between the presence of lymph node metastases and 64 features. Volume-density, a measurement of shape irregularity, was the most predictive feature (p=0001, AUC=0,77, cut-off 0.35). When testing cut-off in Group B to discriminate metastatic tumors, PET false-negative findings were reduced from 14 to 8 (-43%).

CONCLUSIONS

PET/CT demonstrated high specificity in detecting nodal metastases. SLN and histologic ultrastaging increased false-negative PET/CT findings, reducing the sensitivity of the technique. PET radiomics features of the primary tumor seem promising for predicting the presence of nodal metastases not detected by visual analysis.

Transperitoneal Laparoscopic Para-Aortic Lymphadenectomy and Body Mass Index: Is It Really a Limiting Factor for the Procedure?

Objective: To explore if obesity measured by body mass index (BMI) ≥30 kg/m² represents a limiting factor for para-aortic lymphadenectomy done with a transperitoneal laparoscopic approach. Materials and Methods: Retrospective observational study with 146 consecutive patients, diagnosed with a gynecological cancer submitted to para-aortic surgical staging between January 2010 and December 2018. The mean age was 52 years and the mean BMI was 27 kg/m². 72.6% (106 patients) had BMI <30 kg/m² and 27.4% (40 patients) had BMI ≥30 kg/m². Half of the patients did not have prior abdominal surgeries. Results: The statistical analysis showed that there were no significant differences between two groups depending on their BMI in the lymph node count: BMI <30 kg/m² 14 nodes versus BMI ≥30 kg/m² 10 nodes (P = .122); rate of intraoperative complications: BMI <30: 6.3% versus BMI ≥30: 0% (P = .180), postoperative complications: BMI <30: 6.6% versus BMI ≥30: 5% (P = .723); feasibility rate: BMI <30: 97.1% versus BMI ≥30: 95.6% (P = .063) or the mean hospital stay BMI <30: 2.47 ± 2.05 days (standard deviation [SD]), BMI ≥30: 2.64 ± 0.93 days (SD) (P = .171). The only significant difference observed was due to the operating time: BMI <30: 103.1 ± 60.8 (SD) versus BMI ≥30: 146.9 ± 82.5 (SD) (P = .019), being longer in obese patients. Conclusions: Obesity, estimated by BMI, does not seem to represent a limiting factor for this surgical procedure in our series. We feel it is a feasible and justified approach in obese patients when other surgical procedures have to be carried out in the same surgical act. Probably, other factors and anthropometric measurements are more accurate to select patients in which this approach is feasible.