An update on the role of PET/CT and PET/MRI in ovarian cancer

Ultrasonography Findings in Ovarian Hemangiomas: Report of Three Cases and Review of the Literature

Ovarian hemangioma is a rare ovarian tumor. The imaging manifestations were rarely mentioned in previous literatures. One of the patients came to hospital with the complaints of an elevation of CA125. Another two patients found a mass in adnexa area accidentally. The oophorectomy procedures were performed and the pathological results of ovarian hemangioma were concluded. We summarized the ultrasound features of three cases retrospectively, of which could provide more information before operation to guide a management direction. A well-defined, regular-shape solid mass in ovary could be considered the possibility of hemangioma, especially when a richly vascularized tumor with prominent blood flow is detected on color Doppler sonography.

Development and validation of radiomics nomogram for metastatic status of epithelial ovarian cancer

To develop and validate an enhanced CT-based radiomics nomogram for evaluating preoperative metastasis risk of epithelial ovarian cancer (EOC). One hundred and nine patients with histologically confirmed EOC were retrospectively enrolled. The volume of interest (VOI) was delineated in preoperative enhanced CT images, and 851 radiomics features were extracted. The radiomics features were selected by the least absolute shrinkage and selection operator (LASSO), and the rad-score was calculated using the formula of the radiomics label. A clinical model, radiomics model, and combined model were constructed using the logistic regression classification algorithm. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were used to evaluate the diagnostic performance of the models. Seventy-five patients (68.8%) were histologically confirmed to have metastasis. Eleven optimal radiomics features were retained by the LASSO algorithm to develop the radiomic model. The combined model for evaluating metastasis of EOC achieved area under the curve (AUC) values of 0.929 (95% CI 0.8593-0.9996) in the training cohort and 0.909 (95% CI 0.7921-1.0000) in the test cohort. To facilitate clinical use, a radiomic nomogram was built by combining the clinical characteristics with rad-score. The DCA indicated that the nomogram had the most significant net benefit when the threshold probability exceeded 15%, surpassing the benefits of both the treat-all and treat-none strategies. Compared with clinical model and radiomics model, the radiomics nomogram has the best diagnostic performance in evaluating EOC metastasis. The nomogram is a useful and convenient tool for clinical doctors to develop personalized treatment plans for EOC patients.

ESGO-ESMO-ESP consensus conference recommendations on ovarian cancer: pathology and molecular biology and early, advanced and recurrent disease

The European Society of Gynaecological Oncology, the European Society for Medical Oncology (ESMO) and the European Society of Pathology held a consensus conference (CC) on ovarian cancer on 15-16 June 2022 in Valencia, Spain. The CC panel included 44 experts in the management of ovarian cancer and pathology, an ESMO scientific advisor and a methodologist. The aim was to discuss new or contentious topics and develop recommendations to improve and harmonise the management of patients with ovarian cancer. Eighteen questions were identified for discussion under four main topics: (i) pathology and molecular biology, (ii) early-stage disease and pelvic mass in pregnancy, (iii) advanced stage (including older/frail patients) and (iv) recurrent disease. The panel was divided into four working groups (WGs) to each address questions relating to one of the four topics outlined above, based on their expertise. Relevant scientific literature was reviewed in advance. Recommendations were developed by the WGs and then presented to the entire panel for further discussion and amendment before voting. This manuscript focuses on the recommendation statements that reached a consensus, their voting results and a summary of evidence supporting each recommendation.

An Unusual Presentation: High-Grade Serous Carcinoma of the Fallopian Tube Manifesting With Altered Mental Status Secondary to a Single Brain Metastasis-A Case Report and Review of the Literature

Epithelial ovarian and fallopian cancers are aggressive lesions that rarely metastasize to the central nervous system. Brain metastases usually occur in the setting of known primary disease or widespread metastatic disease. However, in extremely rare cases, an isolated intracranial neoplasm may be the first presentation of fallopian cancer. To the best of our knowledge, only one such case has been reported previously. We present an illustrative case with multimodality imaging and histopathologic correlation of a fallopian tube carcinoma first presenting with altered mental status secondary to an isolated brain metastasis. A 64-year-old female with no pertinent medical history presented with altered mentation. Initial workup identified a 1.6 cm avidly enhancing, solitary brain lesion at the gray-white junction with associated vasogenic edema concerning for either central nervous system lymphoma or metastatic disease. Additional imaging identified a 7.5 × 3 cm left adnexal lesion, initially thought to be a hydrosalpinx with hemorrhage, but magnetic resonance imaging suggested gynecologic malignancy. No lesions elsewhere in the body were identified. Given the lack of locoregional or systemic disease, the intracranial and pelvic lesions were assumed to represent synchronous but distinct processes. The intracranial lesion was biopsied. Preliminary results were suggestive of lymphoma, but further analysis was consistent with high-grade serous carcinoma of müllerian origin. Positron emission tomography/computed tomography was performed to evaluate for other neoplastic lesions, only highlighting the intracranial and pelvic lesions. At this point, a diagnosis of metastatic fallopian cancer was made. The patient was taken for robot-assisted laparoscopy with surgical debulking of the pelvic neoplasm, pathology demonstrating high-grade serous carcinoma of the fallopian tube, matching that of the intracranial lesion. Even though rare, metastatic fallopian cancer should be considered in patients with isolated brain lesions and adnexal lesions, even in the absence of locoregional or systemic disease.

Initial Experience with the Radiotracer 18F-Fluciclovine PET/CT in Ovarian Cancer

OBJECTIVE

Early and accurate staging of ovarian cancer is paramount to disease survival. Conventional imaging including FDG PET/CT are limited in the evaluation of small metastatic lesions. 18F-Fluciclovine has minimal urine and bowel excretion allowing optimal visualization of the abdomen and pelvis. This study examines 18F-fluciclovine uptake in known primary and recurrent ovarian cancer.

METHODS

Seven patients with a confirmed diagnosis of epithelial ovarian cancer underwent 18F-fluciclovine PET/CT imaging. Forty-one (41) lesions were identified with 18F-fluciclovine and confirmed to be true positive (n = 41). We aim to explore if 18F-fluciclovine uptake in ovarian lesions were greater than background uptake of bone marrow, blood pool, and bladder. Quantification analysis was performed to determine max and mean standard uptake values (SUVmax and SUVmean) of known and suspected lesions compared to SUVmean uptake of background structures.

RESULTS

18F-Fluciclovine demonstrated 100% sensitivity (41/41) for uptake in known ovarian lesions. The average SUVmax (±SD) uptake of known ovarian lesions was 5.9 (±2.6) and 5.1 (±2.0) on early and delayed images, respectively. The average tumor SUVmax to SUVmean of background (±SD) (T:B) ratios on early and delay were 1.9 (±0.8), 2.1 (±0.9) for marrow; 3.8 (±1.8), 3.4 (±1.5) for aorta; and 8.4 (±4.3), 1.5 (±1.7) for bladder, respectively.

CONCLUSION

18F-Fluciclovine uptake in malignant ovarian lesions was above background levels suggesting its feasibility in the imaging of ovarian cancer. Due to increasing tracer washout via the urinary bladder over time, early imaging at 4 min post injection is favorable.

Copine 1 predicts poor clinical outcomes by promoting M2 macrophage activation in ovarian cancer

OBJECTIVE

Copine 1 (CPNE1), a membrane-binding protein, influences the prognosis of various cancers. According to cBioPortal, CPNE1 amplification is a prevalent genetic mutation in ovarian cancer but with unknown oncogenic mechanism.

METHODS

This study analysed the CPNE1 expression in ovarian cancer using online datasets, as validated by immunohistochemistry (IHC), quantitative polymerase chain reaction (qPCR) and western blotting. Concurrently, the prognostic value of CPNE1 was accessed. Cell Counting Kit-8, colony formation, transwells and xenograft experiments were performed to evaluate the functions of CPNE1 during ovarian cancer carcinogenesis. CPNE1 and its related genes were analysed by g:Profiler and Tumour Immune Estimation Resource. Furthermore, human monocytic THP-1 cells were co-cultured with ES2 cells to investigate the effect of CPNE1 on macrophage polarization.

RESULTS

The results of bioinformatic analysis, IHC, qPCR and western blotting indicated a higher CPNE1 in ovarian cancer. CPNE1 overexpression demonstrated an association with a poor prognosis of ovarian cancer. Functionally, CPNE1 overexpression increased ES2 and SKOV3 cell proliferation, invasion and migration in vitro and promoted ovarian tumour xenograft growth in vivo, while CPNE1 knockdown led to opposite effects. Additionally, CPNE1 expression demonstrated an association with immune cell infiltration in ovarian cancer, especially macrophage. CPNE1 promoted protumour M2 macrophage polarization by upregulating cluster of differentiation 163 (CD163), CD206 and interleukin-10.

CONCLUSIONS

Our study revealed that CPNE1 mediated M2 macrophage polarization and provided a therapeutic target for ovarian cancer.

"Things Have Changed"-Laparoscopic Cytoreduction for Advanced and Recurrent Ovarian Cancer: The Experience of a Referral Center on 108 Patients

OBJECTIVE

To report the feasibility of laparoscopic cytoreduction surgery for primary and recurrent ovarian cancer in a select group of patients.

METHODS

A retrospective analysis was conducted on a cohort of patients with FIGO stage IIIA-IV advanced ovarian cancer who underwent laparoscopic primary debulking surgery (PDS), interval debulking surgery (IDS), or secondary debulking surgery (SDS) between June 2008 and January 2020. The primary endpoint was achieving optimal cytoreduction, defined as residual tumor less than 1 cm. Secondary endpoints included evaluating surgical complications and long-term survival, assessed at three-month intervals during the initial two years and then every six months.

RESULTS

This study included a total of 108 patients, among whom, 40 underwent PDS, 44 underwent IDS, and 24 underwent SDS. Optimal cytoreduction rates were found to be 95.0%, 97.7%, and 95.8% for the PDS, ISD, and SDS groups, respectively. Early postoperative complications (<30 days from surgery) occurred in 19.2% of cases, with 7.4% of these cases requiring reintervention. One patient died following postoperative respiratory failure. Late postoperative complications (<30 days from surgery) occurred in 9.3% of cases, and they required surgical reintervention only in one case. After laparoscopic optimal cytoreduction with a median follow-up time of 25 months, the overall recurrence rates were 45.7%, 38.5%, and 39.3% for PDS, ISD, and SDS, respectively. The three-year overall survival rates were 84%, 66%, and 63%, respectively, while the three-year disease-free survival rates were 48%, 51%, and 71%, respectively.

CONCLUSIONS

Laparoscopic cytoreduction surgery is feasible for advanced ovarian cancer in carefully selected patients, resulting in high rates of optimal cytoreduction, satisfactory peri-operative morbidity, and encouraging survival outcomes. Future studies should focus on establishing standardized selection criteria and conducting well-designed investigations to further refine patient selection and evaluate long-term outcomes.

Application of medical imaging in ovarian cancer: a bibliometric analysis from 2000 to 2022

Background

Ovarian cancer (OC) is the most lethal tumor within the female reproductive system. Medical imaging plays a significant role in diagnosis and monitoring OC. This study aims to use bibliometric analysis to explore the current research hotspots and collaborative networks in the application of medical imaging in OC from 2000 to 2022.

Methods

A systematica search for medical imaging in OC was conducted on the Web of Science Core Collection on August 9, 2023. All reviews and articles published from January 2000 to December 2022 were downloaded, and an analysis of countries, institutions, journals, keywords, and collaborative networks was perfomed using CiteSpace and VOSviewer.

Results

A total of 5,958 publications were obtained, demonstrating a clear upward trend in annual publications over the study peroid. The USA led in productivity with 1,373 publications, and Harvard University emerged as the most prominent institution with 202 publications. Timmerman D was the most prolific contributor with 100 publications, and Gynecological Oncology led in the number of publications with 296. The top three keywords were "ovarian cancer" (1,256), "ultrasound" (725), and "diagnosis" (712). In addition, "pelvic masses" had the highest burst strength (25.5), followed by "magnetic resonance imaging (MRI)" (21.47). Recent emergent keywords such as "apoptosis", "nanoparticles", "features", "accuracy", and "human epididymal protein 4 (HE 4)" reflect research trends in this field and may become research hotspots in the future.

Conclusion

This study provides a comprehensive summary of the key contributions of OC imaging to field's development over the past 23 years. Presently, primary areas of OC imaging research include MRI, targeted therapy of OC, novel biomarker (HE 4), and artificial intelligence. These areas are expected to influence future research endeavors in this field.

Diagnostic performance of noninvasive imaging using computed tomography, magnetic resonance imaging, and positron emission tomography for the detection of ovarian cancer: a meta-analysis

OBJECTIVE

The aim of this meta-analysis was to compare the diagnostic value of noninvasive imaging methods computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) in the detection of ovarian cancer (OC).

METHODS

PubMed, Embase, and Ovid were comprehensively searched from the date of inception to 31st, March, 2022. Pooled sensitivity, specificity, positive likelihood ratio (+ LR), negative likelihood ratio (- LR), diagnostic odds ratio (DOR), and area under the curve (AUC) of summary receiver operating characteristic (SROC) with their respective 95% confidence intervals (CIs) were calculated.

RESULTS

Sixty-one articles including 4284 patients met the inclusion criteria of this study. Pooled estimates of sensitivity, specificity, and AUC of SROC with respective 95% CIs of CT on patient level were 0.83 (0.73, 0.90), 0.69 (0.54, 0.81), and 0.84 (0.80, 0.87). The overall sensitivity, specificity, SROC value with respective 95% CIs of MRI were 0.95 (0.91, 0.97),0.81 (0.76, 0.85), and 0.90 (0.87, 0.92) on patient level. Pooled estimates of sensitivity, specificity, SROC value of PET/CT on patient level were 0.92 (0.88, 0.94), 0.88 (0.83, 0.92), and 0.96 (0.94, 0.97).

CONCLUSION

Noninvasive imaging modalities including CT, MRI, PET (PET/CT, PET/MRI) yielded favorable diagnostic performance in the detection of OC. Hybrid implement of different tools (PET/MRI) is more accurate for identifying metastatic OC.

Speculation on optimal numbers of examined lymph node for early-stage epithelial ovarian cancer from the perspective of stage migration

Introduction

In early-stage epithelial ovarian cancer (EOC), how to perform lymphadenectomy to avoid stage migration and achieve reliable targeted excision has not been explored in depth. This study comprehensively considered the stage migration and survival to determine appropriate numbers of examined lymph node (ELN) for early-stage EOC and high-grade serous ovarian cancer (HGSOC).

Methods

From the Surveillance, Epidemiology, and End Results database, we obtained 10372 EOC cases with stage T1M0 and ELN ≥ 2, including 2849 HGSOC cases. Generalized linear models with multivariable adjustment were used to analyze associations between ELN numbers and lymph node stage migration, survival and positive lymph node (PLN). LOESS regression characterized dynamic trends of above associations followed by Chow test to determine structural breakpoints of ELN numbers. Survival curves were plotted using Kaplan-Meier method.

Results

More ELNs were associated with more node-positive diseases, more PLNs and better prognosis. ELN structural breakpoints were different in subgroups of early-stage EOC, which for node stage migration or PLN were more than those for improving outcomes. The meaning of ELN structural breakpoint varied with its location and the morphology of LOESS curve. To avoid stage migration, the optimal ELN for early-stage EOC was 29 and the minimal ELN for HGSOC was 24. For better survival, appropriate ELN number were 13 and 8 respectively. More ELNs explained better prognosis only at a certain range.

Discussion

Neither too many nor too few numbers of ELN were ideal for early-stage EOC and HGSOC. Excision with appropriate numbers of lymph node draining the affected ovary may be more reasonable than traditional sentinel lymph node resection and systematic lymphadenectomy.

A comparative study of [68Ga]Ga-FAPI-04 PET/MR and [18F]FDG PET/CT in the diagnostic accuracy and resectability prediction of ovarian cancer

PURPOSE

To provide a theory for guiding clinical treatment by comparing the clinical application value of [18F]fluorodeoxyglucose ([18F]FDG) PET/CT and [68Ga]Ga-FAPI (fibroblast activating protein inhibitor) PET/MR in the diagnosis and evaluation of resectability of ovarian cancer.

METHODS

Thirty patients with high clinical suspicion of ovarian malignancies were enrolled from July 2021 to October 2022 and underwent [18F]FDG PET/CT and [68Ga]Ga-FAPI-04 PET/MR within 5 days. Twenty patients underwent [18F]FDG PET/MR at once completing [18F]FDG PET/CT for consistency checking. Images were analysed for comparing SUVs and for judging incomplete resectability according to the peritoneal cancer index (PCI) and SUIDAN scoring system. The expression of FAP, HK2 and Ki67 was analysed by immunohistochemistry staining.

RESULTS

There was no significant difference between PET/MR and PET/CT in SUVs-FDG at different locations (p > 0.05), and their diagnostic accuracies were similar. The diagnostic accuracy of [68Ga]Ga-FAPI-04 PET/MR had advantages for peritoneal metastasis since SUVsFAPI were higher (p < 0.01). The sensitivity of [68Ga]Ga-FAPI-04 PET/MR in the diagnosis of peridiaghragmatic metastases was higher because SUVmax in the liver was decreased (p < 0.001). [68Ga]Ga-FAPI-04 PET/MR might have advantages in diagnosing gastrointestinal invasion. In PCI score analysis, [68Ga]Ga-FAPI-04 PET/MR could partially correct missing or underestimated scores by [18F]FDG PET/CT, but the matching probability between left peri-intestinal metastasis scores was low and easy to overestimate. Interestingly, diaphragmatic metastasis detected by [68Ga]Ga-FAPI-04 PET/MR had the greatest correlation with the prediction of incomplete resectability (logistic regression p = 0.02). Through immunohistochemistry, the expression of FAP had a strong correlation with SUVmax-FAPI (p < 0.001), while the expression of HK2 was correlated with SUVmax-FDG (p < 0.01). In addition, SUVmax-FDG with Ki67 ≥ 20% was significantly higher than that with Ki67 < 20% (p < 0.05).

CONCLUSIONS

[68Ga]Ga-FAPI-04 PET/MR had obvious advantages for metastases diagnosis and could more accurately assess tumour load and predict incomplete resectability. SUVmax-FDG was conducive to evaluating the degree of tumour malignancy.

Predictive value of PET metabolic parameters for occult lymph node metastases in PET/CT defined node-negative patients with advanced epithelial ovarian cancer

Accurate lymph node metastasis (LNM) prediction is crucial for patients with advanced epithelial ovarian cancer (AEOC) since it guides the decisions about lymphadenectomy. Previous studies have shown that occult lymph node metastasis (OLNM) is common in AEOC. The objective of our study is to quantitatively assess the probability of occult lymph node metastasis defined by 18F-Fluorodeoxyglucose PET/CT in AEOC and explore relationship between OLNM and PET metabolic parameters. The patients with pathologically confirmed AEOC who underwent PET/CT for preoperative staging at our institute were reviewed. Univariate and multivariate analysis were performed to evaluate the predictive value of PET/CT-related metabolic parameters for OLNM. The result of our study showed metastatic TLG index had a better diagnostic performance than other PET/CT-related metabolic parameters. Two variables were independently and significantly associated with OLNM in multivariate analysis: metastatic TLG index and primary tumor location. The logistic model combining metastatic TLG index, primary tumor location, and CA125 might be a promising tool to effectively predict the individualized possibility of OLNM for AEOC patients.

Comparison of Ultrasound Scores in Differentiating between Benign and Malignant Adnexal Masses

Subjective ultrasound assessment by an expert examiner is meant to be the best option for the differentiation between benign and malignant adnexal masses. Different ultrasound scores can help in the classification, but whether one of them is significantly better than others is still a matter of debate. The main aim of this work is to compare the diagnostic performance of some of these scores in the evaluation of adnexal masses in the same set of patients. This is a retrospective study of a consecutive series of women diagnosed as having a persistent adnexal mass and managed surgically. Ultrasound characteristics were analyzed according to IOTA criteria. Masses were classified according to the subjective impression of the sonographer and other ultrasound scores (IOTA simple rules -SR-, IOTA simple rules risk assessment -SRRA-, O-RADS classification, and ADNEX model -with and without CA125 value-). A total of 122 women were included. Sixty-two women were postmenopausal (50.8%). Eighty-one women had a benign mass (66.4%), and 41 (33.6%) had a malignant tumor. The sensitivity of subjective assessment, IOTA SR, IOTA SRRA, and ADNEX model with or without CA125 and O-RADS was 87.8%, 66.7%, 78.1%, 95.1%, 87.8%, and 90.2%, respectively. The specificity for these approaches was 69.1%, 89.2%, 72.8%, 74.1%, 67.9%, and 60.5%, respectively. All methods with similar AUC (0.81, 0.78, 0.80, 0.88, 0.84, and 0.75, respectively). We concluded that IOTA SR, IOTA SRRA, and ADNEX models with or without CA125 and O-RADS can help in the differentiation of benign and malignant masses, and their performance is similar to the subjective assessment of an experienced sonographer.

Prediction of Surgical Outcome in Advanced Ovarian Cancer by Imaging and Laparoscopy: A Narrative Review

Maximal-effort upfront or interval debulking surgery is the recommended approach for advanced-stage ovarian cancer. The role of diagnostic imaging is to provide a systematic and structured report on tumour dissemination with emphasis on key sites for resectability. Imaging methods, such as pelvic and abdominal ultrasound, contrast-enhanced computed tomography, whole-body diffusion-weighted magnetic resonance imaging and positron emission tomography, yield high diagnostic performance for diagnosing bulky disease, but they are less accurate for depicting small-volume carcinomatosis, which may lead to unnecessary explorative laparotomies. Diagnostic laparoscopy, on the other hand, may directly visualize intraperitoneal involvement but has limitations in detecting tumours beyond the gastrosplenic ligament, in the lesser sac, mesenteric root or in the retroperitoneum. Laparoscopy has its place in combination with imaging in cases where ima-ging results regarding resectability are unclear. Different imaging models predicting tumour resectability have been developed as an adjunctional objective tool. Incorporating results from tumour quantitative analyses (e.g., radiomics), preoperative biopsies and biomarkers into predictive models may allow for more precise selection of patients eligible for extensive surgery. This review will discuss the ability of imaging and laparoscopy to predict non-resectable disease in patients with advanced ovarian cancer.

A Nomogram for Preoperative Prediction of the Risk of Lymph Node Metastasis in Patients with Epithelial Ovarian Cancer

Objective: To develop a nomogram for predicting lymph node metastasis (LNM) in patients with epithelial ovarian cancer (EOC). Methods: Between December 2012 and August 2022, patients with EOC who received computed tomography (CT) and serological examinations and were treated with upfront staging or debulking surgery were included. Systematic pelvic and para-aortic lymphadenectomy was performed in all patients. Univariate and multivariate analysis was used to identify significant risk factors associated with LNM. A nomogram was then constructed to assess the risk of LNM, which was evaluated with respect to its area under the receiver operating characteristic curve (AUC), calibration, and clinical usefulness. Results: Of 212 patients enrolled in this study, 78 (36.8%) had positive LNs. The nomogram integrating CT-reported LN status, child-bearing status, tumour laterality, and stage showed good calibration and discrimination with an AUC of 0.775, significantly improving performance over the CT results (0.699, p = 0.0002) with a net reclassification improvement of 0.593 (p < 0.001) and integrated discrimination improvement of 0.054 (p < 0.001). The decision curve analysis showed the nomogram was of clinical use. Conclusions: A nomogram was constructed and internally validated, which may act as a decision aid in patients with EOC being considered for systemic lymphadenectomy.

Current Update on PET/MRI in Gynecological Malignancies-A Review of the Literature

Early detection of gynecological malignancies is vital for patient management and prolonging the patient's survival. Molecular imaging, such as positron emission tomography (PET)/computed tomography, has been increasingly utilized in gynecological malignancies. PET/magnetic resonance imaging (MRI) enables the assessment of gynecological malignancies by combining the metabolic information of PET with the anatomical and functional information from MRI. This article will review the updated applications of PET/MRI in gynecological malignancies.

Artificial intelligence performance in image-based ovarian cancer identification: A systematic review and meta-analysis

BACKGROUND

Accurate identification of ovarian cancer (OC) is of paramount importance in clinical treatment success. Artificial intelligence (AI) is a potentially reliable assistant for the medical imaging recognition. We systematically review articles on the diagnostic performance of AI in OC from medical imaging for the first time.

METHODS

The Medline, Embase, IEEE, PubMed, Web of Science, and the Cochrane library databases were searched for related studies published until August 1, 2022. Inclusion criteria were studies that developed or used AI algorithms in the diagnosis of OC from medical images. The binary diagnostic accuracy data were extracted to derive the outcomes of interest: sensitivity (SE), specificity (SP), and Area Under the Curve (AUC). The study was registered with the PROSPERO, CRD42022324611.

FINDINGS

Thirty-four eligible studies were identified, of which twenty-eight studies were included in the meta-analysis with a pooled SE of 88% (95%CI: 85-90%), SP of 85% (82-88%), and AUC of 0.93 (0.91-0.95). Analysis for different algorithms revealed a pooled SE of 89% (85-92%) and SP of 88% (82-92%) for machine learning; and a pooled SE of 88% (84-91%) and SP of 84% (80-87%) for deep learning. Acceptable diagnostic performance was demonstrated in subgroup analyses stratified by imaging modalities (Ultrasound, Magnetic Resonance Imaging, or Computed Tomography), sample size (≤300 or >300), AI algorithms versus clinicians, year of publication (before or after 2020), geographical distribution (Asia or non Asia), and the different risk of bias levels (≥3 domain low risk or < 3 domain low risk).

INTERPRETATION

AI algorithms exhibited favorable performance for the diagnosis of OC through medical imaging. More rigorous reporting standards that address specific challenges of AI research could improve future studies.

FUNDING

This work was supported by the Natural Science Foundation of China (No. 82073647 to Q-JW and No. 82103914 to T-TG), LiaoNing Revitalization Talents Program (No. XLYC1907102 to Q-JW), and 345 Talent Project of Shengjing Hospital of China Medical University (No. M0268 to Q-JW and No. M0952 to T-TG).

Automatic Detection and Segmentation of Ovarian Cancer Using a Multitask Model in Pelvic CT Images

Ovarian cancer is one of the most common malignant tumours of female reproductive organs in the world. The pelvic CT scan is a common examination method used for the screening of ovarian cancer, which shows the advantages in safety, efficiency, and providing high-resolution images. Recently, deep learning applications in medical imaging attract more and more attention in the research field of tumour diagnostics. However, due to the limited number of relevant datasets and reliable deep learning models, it remains a challenging problem to detect ovarian tumours on CT images. In this work, we first collected CT images of 223 ovarian cancer patients in the Affiliated Hospital of Qingdao University. A new end-to-end network based on YOLOv5 is proposed, namely, YOLO-OCv2 (ovarian cancer). We improved the previous work YOLO-OC firstly, including balanced mosaic data enhancement and decoupled detection head. Then, based on the detection model, a multitask model is proposed, which can simultaneously complete the detection and segmentation tasks.

Strongyloides stercoralis infestation mimicking recurrence of ovarian cancer in the liver

Ovarian cancer is the most lethal gynecological cancer and can recur in most cases. Surgery is an option for recurrent ovarian cancer. Parasitic infestation disseminated in an immunocompromised host can be fatal. The case is here presented of a female patient diagnosed with early-stage ovarian cancer. Chemotherapy was initiated for treatment. At the follow-up examination, masses in the liver suggestive of recurrence were detected on positron emission tomography computed tomography. Surgery was performed. A Strongyloides stercoralis infestation mimicking relapsing ovarian cancer in the liver was diagnosed.

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.

Nomogram Predicting Lymph Node Metastasis in the Early-Stage Cervical Cancer

Background

Accurately predicting the risk level of lymph node metastasis is essential for the treatment of patients with early cervical cancer. The purpose of this study is to construct a new nomogram based on 2-deoxy-2-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) and clinical characteristics to assess early-stage cervical cancer patients’ risk of lymph node metastasis.

Materials and Methods

From January 2019 to November 2020, the records of 234 patients with stage IA-IIA [International Federation of Gynecology and Obstetrics (FIGO) 2018] cervical cancer who had undergone PET/CT examination within 30 days before surgery were retrospectively reviewed. A nomogram to predict the risk of lymph node metastasis was constructed based on it. The nomogram was developed and validated by internal and external validation. The validation cohorts included 191 cervical cancer patients from December 2020 to October 2021.

Results

Four factors [squamous cell carcinoma associated antigen (SCCA), maximum standardized uptake value of lymph node (nSUVmax), uterine corpus invasion in PET/CT and tumor size in PET/CT] were finally determined as the predictors of the nomogram. At the area under the receiver operating characteristic curve cohort was 0.926 in the primary and was 0.897 in the validation cohort. The calibration curve shows good agreement between the predicted probability and the actual probability. The decision curve analysis showed the clinical utility of the nomogram.

Conclusion

We had established and verified a simple and effective nomogram, which can be used to predict the lymph node metastasis of cervical cancer patients before surgery.

Evaluation of a CD13 and Integrin αvβ3 Dual-Receptor Targeted Tracer 68Ga-NGR-RGD for Ovarian Tumor Imaging: Comparison With 18F-FDG

Ovarian cancer has the highest mortality rate of gynecologic malignancy. ¹⁸F-FDG positron emission tomography (PET) adds an important superiority over traditional anatomic imaging modalities in oncological imaging but has drawbacks including false negative results at the early stage of ovarian cancer, and false positives when inflammatory comorbidities are present. Aminopeptidase N (APN, also known as CD13) and integrin α_vβ₃ are two important targets overexpressed on tumor neo-vessels and frequently on ovarian cancerous cells. In this study, we used subcutaneous and metastatic models of ovarian cancer and muscular inflammation models to identify ⁶⁸Ga-NGR-RGD, a heterodimeric tracer consisting of NGR and RGD peptides targeting CD13 and integrin α_vβ₃, respectively, and compared it with ¹⁸F-FDG. We found that ⁶⁸Ga-NGR-RGD showed greater contrast in SKOV3 and ES-2 tumors than ¹⁸F-FDG. Low accumulation of ⁶⁸Ga-NGR-RGD but avid uptake of ¹⁸F-FDG were observed in inflammatory muscle. In abdominal metastasis models, PET imaging with ⁶⁸Ga-NGR-RGD allowed for rapid and clear delineation of both peritoneal and liver metastases (3-6 mm), whereas, ¹⁸F-FDG could not distinguish the metastasis lesions due to the relatively low metabolic activity in tumors and the interference of intestinal physiological ¹⁸F-FDG uptake. Due to the high tumor-targeting efficacy, low inflammatory uptake, and higher tumor-to-background ratios compared to that of ¹⁸F-FDG, ⁶⁸Ga-NGR-RGD presents a promising imaging agent for diagnosis, staging, and follow-up of ovarian tumors.

Applications of artificial intelligence (AI) in ovarian cancer, pancreatic cancer, and image biomarker discovery

BACKGROUND

Artificial intelligence (AI), including machine learning (ML) and deep learning, has the potential to revolutionize biomedical research. Defined as the ability to "mimic" human intelligence by machines executing trained algorithms, AI methods are deployed for biomarker discovery.

OBJECTIVE

We detail the advancements and challenges in the use of AI for biomarker discovery in ovarian and pancreatic cancer. We also provide an overview of associated regulatory and ethical considerations.

METHODS

We conducted a literature review using PubMed and Google Scholar to survey the published findings on the use of AI in ovarian cancer, pancreatic cancer, and cancer biomarkers.

RESULTS

Most AI models associated with ovarian and pancreatic cancer have yet to be applied in clinical settings, and imaging data in many studies are not publicly available. Low disease prevalence and asymptomatic disease limits data availability required for AI models. The FDA has yet to qualify imaging biomarkers as effective diagnostic tools for these cancers.

CONCLUSIONS

Challenges associated with data availability, quality, bias, as well as AI transparency and explainability, will likely persist. Explainable and trustworthy AI efforts will need to continue so that the research community can better understand and construct effective models for biomarker discovery in rare cancers.

de Hingh I, Houwink AP, Stoevelaar HJ, Sonke GS, van Driel WJ. Standardizing HIPEC and perioperative care for patients with ovarian cancer in the Netherlands using a Delphi-based consensus

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Implementation of HIPEC for ovarian cancer is ongoing, aiming to offer this treatment to all eligible patients in the Netherlands.

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Standardization reduces unwanted variation in clinical treatment.

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We intend to standardize patient selection, technical aspects, and perioperative care of CRS and HIPEC.

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This consensus study comprised a two-phase modified Delphi approach.

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Consensus was reached on 82% of items.

Objective

Hyperthermic Intraperitoneal Chemotherapy (HIPEC) is standard of care in the Netherlands in patients with stage III epithelial ovarian cancer following interval cytoreductive surgery (CRS). Differences in patient selection, technical aspects, and perioperative management exist between centers performing HIPEC. Standardization aims to reduce unwanted variation in clinical practice. As part of an implementation process, we aimed to standardize perioperative care for patients treated with CRS and HIPEC using a Delphi-based consensus approach.

Methods

We performed a two-phase modified Delphi method involving a multidisciplinary panel of 40 experts who completed a survey on CRS and HIPEC. During a consensus meeting, survey outcomes and available scientific evidence was discussed. Items without consensus (<75% agreement) were adjusted and evaluated in a second survey.

Results

Consensus was reached in the first round on 51% of items. After two rounds, consensus was reached on the majority of items (82%) including patient selection, preoperative workup, technical aspects of CRS and HIPEC, and postoperative care. No consensus was reached on the role of HIPEC in rare ovarian cancer types, preoperative bowel preparation, timing to create bowel anastomoses, and manipulation of the perfusate.

Conclusions

Dutch experts reached consensus on most items regarding interval CRS and HIPEC for ovarian cancer. This consensus study may help to align treatment protocols and to minimize practice variation. Topics without consensus may be put on the research agenda of HIPEC for ovarian cancer.

Nanomaterial-based biosensor developing as a route toward in vitro diagnosis of early ovarian cancer

The grand challenges of ovarian cancer early diagnosis have led to an alarmingly high mortality rate from ovarian cancer (OC) in the past half century. In vitro diagnosis (IVD) has great potential in the early diagnosis of OC through non-invasive and dynamic analysis of biomarkers. However, common IVDs often fail to provide reliable test results due to lack of sensitivity, specificity, and convenience. In recent years, the discovery of new biomarkers and the progress of nanomaterials can solve the shortcomings of traditional IVD for early OC. These emerging biosensors based on nanomaterials offer great improvements in convenience, speed, selectivity, and sensitivity of IVD. In this review, we firstly systematically summarized the limits of commercial IVD biosensors of OC and the latest discovery of new biomarkers for OC. The representative optimization strategies for six potential ovarian cancer biomarkers are systematically discussed with emphasis on nanomaterial selection and the design of detection principles. Then, various strategies adopted by emerging biosensors based on nanomaterials are also introduced in detail, including optical, electrochemical, microfluidic, and surface plasmon sensors. Finally, current challenges of early OC IVD are proposed, and future research directions on this promising field are also discussed.

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Failure to diagnose OC early will lead to high mortality.

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The detection of OC-related biomarkers by IVD method will achieve early diagnosis of OC.

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The development of nanomaterials-based biosensors is expected to enhance efficiency of detection.

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Strategies and progress for nanomaterials-based biosensors are systematically reviewed.

Magnetic Fields and Cancer: Epidemiology, Cellular Biology, and Theranostics

Humans are exposed to a complex mix of man-made electric and magnetic fields (MFs) at many different frequencies, at home and at work. Epidemiological studies indicate that there is a positive relationship between residential/domestic and occupational exposure to extremely low frequency electromagnetic fields and some types of cancer, although some other studies indicate no relationship. In this review, after an introduction on the MF definition and a description of natural/anthropogenic sources, the epidemiology of residential/domestic and occupational exposure to MFs and cancer is reviewed, with reference to leukemia, brain, and breast cancer. The in vivo and in vitro effects of MFs on cancer are reviewed considering both human and animal cells, with particular reference to the involvement of reactive oxygen species (ROS). MF application on cancer diagnostic and therapy (theranostic) are also reviewed by describing the use of different magnetic resonance imaging (MRI) applications for the detection of several cancers. Finally, the use of magnetic nanoparticles is described in terms of treatment of cancer by nanomedical applications for the precise delivery of anticancer drugs, nanosurgery by magnetomechanic methods, and selective killing of cancer cells by magnetic hyperthermia. The supplementary tables provide quantitative data and methodologies in epidemiological and cell biology studies. Although scientists do not generally agree that there is a cause-effect relationship between exposure to MF and cancer, MFs might not be the direct cause of cancer but may contribute to produce ROS and generate oxidative stress, which could trigger or enhance the expression of oncogenes.

A Comprehensive Updated Review on Magnetic Nanoparticles in Diagnostics

Magnetic nanoparticles (MNPs) have been studied for diagnostic purposes for decades. Their high surface-to-volume ratio, dispersibility, ability to interact with various molecules and superparamagnetic properties are at the core of what makes MNPs so promising. They have been applied in a multitude of areas in medicine, particularly Magnetic Resonance Imaging (MRI). Iron oxide nanoparticles (IONPs) are the most well-accepted based on their excellent superparamagnetic properties and low toxicity. Nevertheless, IONPs are facing many challenges that make their entry into the market difficult. To overcome these challenges, research has focused on developing MNPs with better safety profiles and enhanced magnetic properties. One particularly important strategy includes doping MNPs (particularly IONPs) with other metallic elements, such as cobalt (Co) and manganese (Mn), to reduce the iron (Fe) content released into the body resulting in the creation of multimodal nanoparticles with unique properties. Another approach includes the development of MNPs using other metals besides Fe, that possess great magnetic or other imaging properties. The future of this field seems to be the production of MNPs which can be used as multipurpose platforms that can combine different uses of MRI or different imaging techniques to design more effective and complete diagnostic tests.

Hepatic Hilar Lymph Node Resection in Cytoreductive Surgery for Advanced Ovarian Cancer: A Necessity or Not?

Objective

This review aims to clarify the necessity of hepatic hilar lymph node resection on advanced ovarian cancer patients.

Background

PARP inhibitors and surgery have significantly improved the survival of patients with ovarian cancer. However, for patients with advanced ovarian cancer, there are often extensive epigastric disseminated metastatic lesions, especially the lymph nodes in the hepatic hilar area. Because of the complicated anatomical relationship and lack of experience in this area, this is easily ignored by gynecological oncologists.

Methods

Through the retrieval and analysis of the current database, namely PubMed, Medline, Web of Science, EMBASE, Cochrane Library, and Wangfang, etc., the literature regarding this topic published before March 2021 were thoroughly investigated.

Conclusion

For the hepatic hilar regional lymph node surgery, through careful preoperative evaluation, surgical-indication clarification, appropriate case selection, standardized surgical operations and multidisciplinary cooperation with general surgeons, the prognosis of patients is significantly improved. Postoperative complications are also safe and controllable and convincing. To conclude, the application of hilar region lymph node cytoreductive surgery for patients with advanced ovarian cancer is a feasible and preferred choice.

The Development of Nanoparticles for the Detection and Imaging of Ovarian Cancers

Ovarian cancer remains as one of the most lethal gynecological cancers to date, with major challenges associated with screening, diagnosis and treatment of the disease and an urgent need for new technologies that can meet these challenges. Nanomaterials provide new opportunities in diagnosis and therapeutic management of many different types of cancers. In this review, we highlight recent promising developments of nanoparticles designed specifically for the detection or imaging of ovarian cancer that have reached the preclinical stage of development. This includes contrast agents, molecular imaging agents and intraoperative aids that have been designed for integration into standard imaging procedures. While numerous nanoparticle systems have been developed for ovarian cancer detection and imaging, specific design criteria governing nanomaterial targeting, biodistribution and clearance from the peritoneal cavity remain key challenges that need to be overcome before these promising tools can accomplish significant breakthroughs into the clinical setting.

Population-based cancer staging for oesophageal, gastric, and pancreatic cancer 2012-2014: International Cancer Benchmarking Partnership SurvMark-2

Cancer stage at diagnosis is important information for management and treatment of individual patients as well as in epidemiological studies to evaluate effectiveness of health care system in managing cancer patients. Population-based studies to examine international disparities on cancer survival by stage, however, has been challenging due to the lack of international standardization on recording stage information and variation in stage completeness across regions and countries. The International Cancer Benchmarking Partnership (ICBP) previously assessed the availability and comparability of staging information for colorectal, lung, female breast and ovarian cancers. Stage conversion algorithms were developed to aggregate and map all stage information into a single staging system to allow international comparison by stage at diagnosis. In this article, we developed stage conversion algorithms for three additional cancers, namely oesophageal, gastric and pancreatic cancers. We examined all stage information available, evaluated stage completeness, applied each stage conversion algorithm, and assessed the magnitude of misclassification using data from six Canadian cancer registries (Alberta, Manitoba, Newfoundland, Nova Scotia, Prince Edward Island and Saskatchewan). In addition, we discussed five recommendations for registries to improve international cancer survival comparison by stage: (a) improve collection and completeness of staging data; (b) promote a comparable definition for stage at diagnosis; (c) promote the use of a common stage classification system; (d) record versions of staging classifications and (e) use multiple data sources for valid staging data.

Lateral Hepatic Fissure Peritoneal Carcinomatosis as a Pitfall for Hepatic Metastasis of Advanced Ovarian Cancer

ABSTRACT

A 52-year-old woman previously treated for a stage IIIc high-grade ovarian serous carcinoma presented right upper quadrant abdominal pain, 3 years after extended surgery and chemotherapy. Abdominal CT, MRI, and 18F-FDG PET/CT showed a right hepatic mass, consistent for lone recurrence nearby the hepatic lateral fissure. Preoperative and histologic examination identified a peritoneal lateral fissure lesion. The patient underwent atypic segment 5 segmentectomy. She has been disease-free for 3 years now. Advanced ovarian cancer can be responsible for perihepatic sulcus lesions, such as this right fissure lesion. They should not be mistaken for inoperable parenchyma metastases.

A multidisciplinary approach remains the best strategy to improve and strengthen the management of ovarian cancer (Review)

Ovarian cancer represents one of the most aggressive female tumors worldwide. Over the decades, the therapeutic options for the treatment of ovarian cancer have been improved significantly through the advancement of surgical techniques as well as the availability of novel effective drugs able to extend the life expectancy of patients. However, due to its clinical, biological and molecular complexity, ovarian cancer is still considered one of the most difficult tumors to manage. In this context, several studies have highlighted how a multidisciplinary approach to this pathology improves the prognosis and survival of patients with ovarian cancer. On these bases, the aim of the present review is to present recent advantages in the diagnosis, staging and treatment of ovarian cancer highlighting the benefits of a patient‑centered care approach and on the importance of a multidisciplinary team for the management of ovarian cancer.

A Comparative Study between 18F-FDG PET/CT and Conventional Imaging in the Evaluation of Progressive Disease and Recurrence in Ovarian Carcinoma

The aim of this study is to compare the efficiency of conventional imaging and 18F-FDG PET-CT in detecting progressive disease and recurrences over a period of one year (2018), in the case of ovarian cancer, and also to assess the importance of 18F-FDG PET/CT in changing the course of the treatment for these patients. This study included 29 patients diagnosed in various stages with ovarian carcinoma, most of them of epithelial origin. All patients were evaluated throughout their treatment using 18F-FDG PET/CT and various conventional techniques (computed tomography (CT), magnetic resonance imaging (MRI), abdominal and intravaginal ultrasound, chest X-ray). PET/CT was more useful and effective in our group of patients in detecting progressive disease compared with conventional imaging (37.93% vs. 17.24%) and also in establishing the recurrences (24.14% vs. 6.90%). Moreover, F18-FDG PET-CT led to a therapeutic change in 55.17% of the patients of our group, compared with only 17.24% after conventional imaging. This underlines the crucial aspect of the metabolic changes of tumors that should be assessed alongside the morphological ones, with PET-CT imaging remaining the only viable tool for achieving that at present. PET/CT with 18F-FDG represents one of the most important imaging techniques used in the diagnosis and management of ovarian carcinoma. Our results seem to fall in line with what other authors reported, indicating that 18F-FDG PET-CT is potentially gaining more ground in the management of ovarian carcinoma, by influencing therapeutic strategies and by being able to detect relapse and progression accurately.

A radiomic nomogram based on arterial phase of CT for differential diagnosis of ovarian cancer

Purpose

To develop and validate a radiomic nomogram based on arterial phase of CT to discriminate the primary ovarian cancers (POCs) and secondary ovarian cancers (SOCs).

Methods

A total of 110 ovarian cancer patients in our hospital were reviewed from January 2010 to December 2018. Radiomic features based on the arterial phase of CT were extracted by Artificial Intelligence Kit software (A.K. software). The least absolute shrinkage and selection operation regression (LASSO) was employed to select features and construct the radiomics score (Rad-score) for further radiomics signature calculation. Multivariable logistic regression analysis was used to develop the predicting model. The predictive nomogram model was composed of rad-score and clinical data. Nomogram discrimination and calibration were evaluated.

Results

Two radiomic features were selected to build the radiomics signature. The radiomics nomogram that incorporated 2 radiomics signature and 2 clinical factors (CA125 and CEA) showed good discrimination in training cohort (AUC 0.854), yielding the sensitivity of 78.8% and specificity of 90.7%, which outperformed the prediction model based on radiomics signature or clinical data alone. A visualized differential nomogram based on the radiomic score, CEA, and CA125 level was established. The calibration curve demonstrated the clinical usefulness of the proposed nomogram.

Conclusion

The presented nomogram, which incorporated radiomic features of arterial phase of CT with clinical features, could be useful for differentiating the primary and secondary ovarian cancers.

Diagnostic performance of PET/CT and PET/MR in the management of ovarian carcinoma-a literature review

Ovarian cancer is a challenging disease. It often presents at an advanced stage with frequent recurrence despite optimal management. Accurate staging and restaging are critical for improving treatment outcomes and determining the prognosis. Imaging is an indispensable component of ovarian cancer management. Hybrid imaging modalities, including positron emission tomography/computed tomography (PET/CT) and PET/magnetic resonance imaging (MRI), are emerging as potential non-invasive imaging tools for improved management of ovarian cancer. This review article discusses the role of PET/CT and PET/MRI in ovarian cancer.

Glycolytic phenotypes in an evaluation of ovarian carcinoma based on carcinogenesis and BRCA mutation

BACKGROUNDS

Recently, a dualistic carcinogenesis model of ovarian cancer has emerged. We aimed to investigate differences in the glycolytic phenotypes of type I and type II ovarian carcinoma on the basis of FDG uptake and in the pathological features according to tumour grade and histology.

MATERIALS AND METHODS

In total, 386 epithelial ovarian carcinoma patients underwent debulking surgery, and the histopathological results of the patients were retrospectively reviewed from 2003 to 2017. Among these patients, 170 patients had histopathological data that were available due to primary cytoreductive surgery and could be analysed regarding FDG avidity in type I and type II ovarian cancer. The FDG uptake of the tumour (SUVmax), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were analysed according to the tumour grade, histology and type of ovarian carcinogenesis (type I and II) and prognosis.

RESULTS

Among the 386 patients, there was a significant difference in SUVmax among ovarian cancer subtypes. There was a significant increase in SUVmax as the tumour grade increased (8.08 ± 0.63, 10.5 ± 0.40, and 12.7 ± 0.38 for grades I, II and III, respectively, Kruskal-Wallis test, p < 0.0001). Among the 90 type I and 80 type II ovarian carcinoma patients, there was a significant difference in SUVmax (type I and II, 9.47 ± 0.54 and 12.97 ± 0.70, respectively, Mann-Whitney test, p = 0.0003). However, no significant change in SUVmax was observed between BRCA-positive and BRCA-negative patients (N = 80, 13.8 ± 5.78 and 12.4 ± 6.30, Student's t-test, p = 0.3075). Among clinicopathologic and metabolic parameters, type of ovarian cancer, MTV and CA125 were significant factors in the prediction of recurrence.

CONCLUSIONS

The glycolytic phenotype was related to tumour grade and histological subtype, with significant differences between type I and II ovarian cancer. SUVmax of the ovarian cancer would be considered in the differentiation of type I and II ovarian cancer.

Comprehensive Serum Glycopeptide Spectra Analysis Combined with Artificial Intelligence (CSGSA-AI) to Diagnose Early-Stage Ovarian Cancer

Ovarian cancer is a leading cause of deaths among gynecological cancers, and a method to detect early-stage epithelial ovarian cancer (EOC) is urgently needed. We aimed to develop an artificial intelligence (AI)-based comprehensive serum glycopeptide spectra analysis (CSGSA-AI) method in combination with convolutional neural network (CNN) to detect aberrant glycans in serum samples of patients with EOC. We converted serum glycopeptide expression patterns into two-dimensional (2D) barcodes to let CNN learn and distinguish between EOC and non-EOC. CNN was trained using 60% samples and validated using 40% samples. We observed that principal component analysis-based alignment of glycopeptides to generate 2D barcodes significantly increased the diagnostic accuracy (88%) of the method. When CNN was trained with 2D barcodes colored on the basis of serum levels of CA125 and HE4, a diagnostic accuracy of 95% was achieved. We believe that this simple and low-cost method will increase the detection of EOC.

Accuracy of peritoneal carcinomatosis extent diagnosis by initial FDG PET CT in epithelial ovarian cancer: A multicentre study of the FRANCOGYN research group

INTRODUCTION

Peritoneal carcinomatosis extent in ovarian cancer is difficult to evaluate by imaging techniques even though it determines the surgical complexity and survival. The aim of this study was to estimate the accuracy of 2-[18F]-fluoro-2-deoxy-d-glucose (FDG)-PET CT (Positron-emission tomography coupled with Computerised Tomography) performed before any treatment, in the diagnosis of the extent of peritoneal carcinomatosis. We compared these results to per-operative observations/ histology samples obtained during surgery (laparotomy/ laparoscopy).

MATERIAL AND METHODS

All women managed for an epithelial ovarian cancer between 1st January 2000 and 30th June 2016 were included if they had a FDG PET CT, before initiation of any treatment (neoadjuvant chemotherapy or frontline cytoreductive surgery). The extent of disease on histology samples from cytoreductive surgery/observations during exploratory laparoscopy were compared with the PET CT results.

RESULTS

Over the study period, 980 women were managed for epithelial ovarian cancer, among them 90 (9.2 %) had a PET CT before any treatment. The diagnostic reliability of an ovarian lesion was 67.8 %, a colon lesion was 61.25 %, a small intestine lesion was 50.6 %, an epiploic lesion was 41.7 %, a pelvic ganglionic invasion was 62.9 % and a paraortic lymph node invasion was 61.5 %. PET CT was less effective than a standard CT examination.

CONCLUSION

PET CT is not the most effective imaging examination to estimate the extent of peritoneal carcinomatosis during the initial management of an epithelial ovarian cancer.

CT Scan in the Prediction of Lymph Node Involvement in Ovarian Cancer - a Retrospective Analysis of a Tertiary Gyneco-Oncological Unit

Background The prognostic value of lymph node removal in ovarian cancer varies depending on the tumor stage. While in the advanced stage the removal of clinically normal lymph nodes does not improve the prognosis, this is still unclear in the early stages. Evaluation of the lymph nodes based on preoperative imaging influences the surgical procedure.

Methods This retrospective analysis was performed by analyzing data from 114 patients with ovarian cancer, treated in our university hospital in the years 2000 – 2012. Diagnostic performance of imaging by computer tomography with respect to the correct prediction of lymph node status was analyzed in terms of sensitivity, specificity, positive predictive value and negative predictive value.

Results Imaging by computer tomography showed a rather limited diagnostic performance with regard to the detection of lymph node metastases in ovarian cancer, with a sensitivity of 40.7%, a specificity of 89.1%, a positive predictive value of 80.0%, and a negative predictive value of 58.3%. A separate analysis for pelvic and paraaortic lymph node involvement showed a better diagnostic performance of computer tomography for the detection of positive paraaortic lymph nodes (41.2, 93.1, 84.0, and 64.3% for sensitivity, specificity, positive predictive value and negative predictive value, respectively) as compared to the detection of positive pelvic lymph nodes (25.6, 91.8, 62.5, and 69.8%).

Conclusion The preoperative prediction of lymph node status by computer tomography is limited. A decision for or against lymphadenectomy should not be made solely on the basis of this approach.

Pretreatment tumor-related leukocytosis misleads positron emission tomography-computed tomography during lymph node staging in gynecological malignancies

The accuracy of fluorine-18-fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG-PET/CT) can be influenced by the increased glycolytic activity of inflammatory lesions. Here, using clinical data obtained from gynecological cancer patients, tumor samples and animal models, we investigate the impact of pretreatment tumor-related leukocytosis (TRL) on the diagnostic performance of 18F-FDG-PET/CT in detecting pelvic and paraaortic lymph node metastasis. We demonstrate that pretreatment TRL misleads 18F-FDG-PET/CT during lymph node staging in gynecological malignancies. In the mechanistic investigations, we show that the false-positive 18F-FDG-PET/CT result for detecting nodal metastasis can be reproduced in animal models of TRL-positive cancer bearing G-CSF expressing cervical cancer cells. We also show that increased 18F-FDG uptake in non-metastatic nodes can be explained by the MDSC-mediated premetastatic niche formation in which proinflammatory factors, such as S100A8 or S100A9, are abundantly expressed. Together, our results suggest that the MDSC-mediated premetastatic niche created in the lymph node of TRL-positive patients misleads 18F-FDG-PET/CT for detecting nodal metastasis.

MRI-Based Machine Learning for Differentiating Borderline From Malignant Epithelial Ovarian Tumors: A Multicenter Study

BACKGROUND

Preoperative differentiation of borderline from malignant epithelial ovarian tumors (BEOT from MEOT) can impact surgical management. MRI has improved this assessment but subjective interpretation by radiologists may lead to inconsistent results.

PURPOSE

To develop and validate an objective MRI-based machine-learning (ML) assessment model for differentiating BEOT from MEOT, and compare the performance against radiologists' interpretation.

STUDY TYPE

Retrospective study of eight clinical centers.

POPULATION

In all, 501 women with histopathologically-confirmed BEOT (n = 165) or MEOT (n = 336) from 2010 to 2018 were enrolled. Three cohorts were constructed: a training cohort (n = 250), an internal validation cohort (n = 92), and an external validation cohort (n = 159).

FIELD STRENGTH/SEQUENCE

Preoperative MRI within 2 weeks of surgery. Single- and multiparameter (MP) machine-learning assessment models were built utilizing the following four MRI sequences: T₂ -weighted imaging (T₂ WI), fat saturation (FS), diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC), and contrast-enhanced (CE)-T₁ WI.

ASSESSMENT

Diagnostic performance of the models was assessed for both whole tumor (WT) and solid tumor (ST) components. Assessment of the performance of the model in discriminating BEOT vs. early-stage MEOT was made. Six radiologists of varying experience also interpreted the MR images.

STATISTICAL TESTS

Mann-Whitney U-test: significance of the clinical characteristics; chi-square test: difference of label; DeLong test: difference of receiver operating characteristic (ROC).

RESULTS

The MP-ST model performed better than the MP-WT model for both the internal validation cohort (area under the curve [AUC] = 0.932 vs. 0.917) and external validation cohort (AUC = 0.902 vs. 0.767). The model showed capability in discriminating BEOT vs. early-stage MEOT, with AUCs of 0.909 and 0.920, respectively. Radiologist performance was considerably poorer than both the internal (mean AUC = 0.792; range, 0.679-0.924) and external (mean AUC = 0.797; range, 0.744-0.867) validation cohorts.

DATA CONCLUSION

Performance of the MRI-based ML model was robust and superior to subjective assessment of radiologists. If our approach can be implemented in clinical practice, improved preoperative prediction could potentially lead to preserved ovarian function and fertility for some women.

LEVEL OF EVIDENCE

Level 4.

TECHNICAL EFFICACY

Stage 2. J. Magn. Reson. Imaging 2020;52:897-904.

The Role of Positron Emission Tomography/Magnetic Resonance Imaging in Gynecological Malignancies

Accurate oncological staging for early detection is of utmost importance in patient care and increasing the overall patient survival outcome. Hybrid imaging in the form of positron emission tomography (PET)/computed tomography has been successfully implemented in oncological imaging and, where available, has been used consistently in patients with gynecologic malignancies. The implementation of PET/magnetic resonance imaging (MRI) enables high-quality assessment of gynecological malignancies by combining the diagnostic advantages of metabolic information of PET along with the high-resolution anatomical and functional information from the MRI to provide precise information about staging, recurrence, and metastases. This article will review the various applications of PET/MRI in gynecological cancer.

Imaging before cytoreductive surgery in advanced ovarian cancer patients

Appropriate and accurate pre-operative imaging in epithelial ovarian cancer patients may allow selection of patients that may mostly benefit either from primary cytoreductive surgery or from neoadjuvant chemotherapy. If the patient is considered suitable for upfront surgery, pre-operative imaging may help in planning the surgical approach, to forecast the operating time, and to estimate the need for other consulting specialists. Currently, computed tomography (CT) imaging is the standard of care for pre-operative evaluation of ovarian cancer patients; however, advanced magnetic resonance imaging (MRI) is emerging as a technique that may overcome the limitations of CT imaging, especially for small peritoneal deposits in difficult-to-resect sites. Positron emission tomography (PET)-CT imaging in the pre-operative setting is currently limited, whereas the use of the new hybrid technique PET-MRI is still under evaluation. Since criteria that may preclude optimal cytoreductive surgery may vary, depending on the aggressiveness of the surgical procedure and surgeon skill, multidisciplinary consensus conferences are the ideal platform to evaluate extent of the disease and surgical strategy.